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The Cost of Environmental Degradation (COED)
Methodology
July 1‐5, 2008 Crowne Plaza Hotel Beirut, Lebanon
Training Manual on
For further details contact:
Mutasem El Fadel Professor of Environmental Engineering Faculty of Engineering and Architecture
American University of Beirut Bliss Street, PO Box 11‐0236
Riad El Solh 1107 2020 Beirut, Lebanon
Phone: +961 (0)1 350 000 Ext. 3470 Fax: +961 (0)1 744 462
Mobile: +961 (0)3 228 338 Email: [email protected]
i
ACKNOWLEDGEMENTS
Special thanks are extended to Dr. Dahlia Lotayef, Senior Environmental Specialist at the
World Bank and METAP Coordinator for the Middle East and North Africa Region, and
Ms. Saliha Dobardzic METAP Operations Officer at The World Bank, as well as Mr. Fadi
Doumani, Consultant at the World Bank for their support and assistance during the
preparation for this workshop.
The following references have been quoted directly, adapted or used as a primary
source for major parts of this document. Secondary and indirect references are cited
within the document. While the document provides a good introductory summary for
most related topics, it is by no means a complete resource on the subject. The reader is
highly advised to consult relevant references similar to those cited below for in depth
examinations.
1. Asafu-Adjaye, J. 2005. Environmental Economics for Non-economists. Techniques and Policies for Sustainable Development. 2nd Edition. World Scientific Publishing Co., London.
2. Barton, D.N. The transferability of benefit transfer: contingent valuation of water quality improvements in Costa Rica. Ecological Economics, 42, 147–164, 2002.
3. Chapman, D. 1999. Environmental Economics: Theory, Application, and Policy. Addison Wesley, USA.
4. Garrod G. and Willis K.G. 2001. Economic Valuation of the Environment: Methods and Case Studies. Edward Elgar Publishing, UK.
5. Hodge, I. 1995. Environmental Economics: Individual Incentives and Public Choices. MACMILLAN PRESS LTD.
6. Hussen, A. M. 1999. Principles of Environmental Economics, Ecology, and Public Policy. Routledge, UK.
7. King, D.M. and Mazotta, M. Ecosystem valuation. www.ecosystemvaluation.org
8. McComb, G., Lantz, V., Nash, K., and Rittmaster, R., 2006. International valuation databases: Overview, methods and operational issues. Ecological Economics, 60, 461-472.
9. Ministère de l’Aménagement du Territoire et de l’Environnement, 2002. Plan National d’Actions pour l’Environnement et le Développement Durable (PNAE-DD). République Algérienne Démocratique et Populaire
10. Prüss-Üstün, A., Campbell-Lendrum, D., Corvalán, C., Woodward, A. 2003. Introduction and methods: Assessing the environmental burden of disease at national and local levels. Environmental Burden of Disease Series, No. 1. World Health Organization, Geneva.
ii
11. Sarraf, M., Larsen, B., and Owaygen, M. 2004. Cost of environmental degradation: The case of Lebanon and Tunisia. Environment Department Paper No. 97, The World Bank, Washington D.C.
12. Kuchler, F and Kohler, E. 1998. Assigning Values to Life: Comparing Methods for Valuing Health Risks. Agricultural Economic Report No. 784. Food and Rural Economics Division, Economic Research Service, U.S. Department of Agriculture, Washington, D.C.
13. World Bank, 1998. The Effects of Pollution on Health: The Economic Toll. In Pollution Prevention and Abatement Handbook. The World Bank.
14. World Bank, 2002. Cost Assessment of Environmental Degradation in the Arab Republic of Egypt. Sector Note. Report No. 25175 –EGT. Rural Development, Water and Environment Department, Middle East and North Africa Region, The World Bank.
15. World Bank, 2003. Cost Assessment of Environmental Degradation in the Kingdom of Morocco. Report No. 25992-MOR. Water, Environment, Social and Rural Development Department, Middle East and North Africa Region, The World Bank.
16. World Bank, 2004. Cost Assessment of Environmental Degradation in the Syrian Arab Republic. World Bank. METAP.
17. World Bank, 2007. Economic Assessment of Environmental Degradation due to the July 2006 Hostilities in the Republic of Lebanon. Sector Note. Report No. 39787-LB. Sustainable Development Department, Middle East and North Africa Region, The World Bank.
18. Whittington, D. Improving the performance of contingent valuation studies in developing countries. Environmental and Resources Economics, 22, 323-367, 2002.
19. Whittington, D. 1996. Administering Contingent Valuation Surveys in Developing Countries. Economy and Environment Program for Southeast Asia (EEPSEA).
iii
WORKSHOP OVERVIEW
Day Session Time Topic
1 1 08:30‐10:00 Participants’ registration Official opening 1. Introductions and purpose of the workshop
10:00‐10:30 Coffee break
2 10:30‐12:00 2. Brief overview of basic economic principles 3. Introduction to environmental valuation
12:00‐12:30 Coffee break
3 12:30‐14:00 The revealed preference approach 4. The productivity method (Theory, application, advantages, limitations, case‐studies)
5. The market price method (Theory, application, advantages, limitations, case‐studies)
6. The damage cost, replacement cost, and substitution cost methods(Theory, application, advantages, limitations, case‐studies)
14:00‐15:30 Lunch
4 15:30‐17:30 Case‐studies on the productivity method and the market values approach
2 5 08:30‐10:00 The revealed preference approach (cont’d) 7. The travel cost method (Theory, application, advantages, limitations, case‐studies)
10:00‐10:30 Coffee break
6 10:30‐12:00 The revealed preference approach (cont’d) 8. The hedonic pricing method (Theory, application, advantages, limitations, case‐studies)
9. The averting behavior method (Theory, application, advantages, limitations, case‐studies)
12:00‐12:30 Coffee break
7 12:30‐14:00 Group Exercises: Ayubia National Park In Pakistan (Travel Cost) Non‐Priced Forest Recreation Areas In Malaysia (Travel Cost) Valuing Landscape and Amenity Attributes In Central England (Hedonic Pricing)
14:00‐15:00 Lunch
8 15:30‐17:30 Presentation and discussion of group exercises
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Day Session Time Topic
3 9 08:30‐10:00 The stated preference approach 10. The contingent valuation method (Theory, application, advantages, limitations, case‐studies)
10:00‐10:30 Coffee break
10 10:30‐12:00 The stated preference approach (cont’d) 11. The discrete choice method (Theory, application, advantages, limitations, case‐studies)
12. The benefit transfer method (Theory, application, advantages, limitations, case‐studies)
12:00‐12:30 Coffee break
11 12:30‐14:00 Group exercise: Stated preference approach Air quality in Beijing Ecosystem services in Ejina China Environmental services in the Yaqui River Delta, Mexico Sustainable development in Sweden coastal zone Coastal ecosystems in Phang Nga Bay, Thailand
14:00‐15:00 Lunch
12 15:30‐17:30 Presentation and discussion of selected group exercises Case‐studies: Coastal zone in North Lebanon, Climate Change MENA Region
14:00‐15:00 Lunch
4 13 08:30‐10:00 13. Cost‐benefit analysis Case‐studies: wastewater and solid waste management
10:00‐10:30 Coffee break
14 10:30‐12:00 14. The value of life and health Including the burden of disease (DALY), the human capital approach, the cost of illness approach, and the contingent valuation approach
Case studies: Drinking water quality; Emissions from the cement industry; Particulate matter in urban areas; Lead phase‐out
12:30‐13:00 Coffee break
5 15 8:30‐10:00 Case studies: Drinking water quality; Emissions from the cement industry; Particulate matter in urban areas; Lead phase‐out
10:00‐10:30 Coffee break
16 10:30‐12:00 Group exercises on the value of life and health: Urban air pollution from particulates in selected MENA countries Water, sanitation and hygiene in selected MENA countries
12:00‐12:30 Coffee break
17 12:30‐14:00 Presentation and discussion of group exercises
14:15:30 Lunch
18 12:30‐14:00 Wrap‐up case with various concepts: the July 2006 War in Lebanon 15. Policy implications and workshop conclusion Workshop evaluation
14:00‐15:00 Lunch
The highlighted titles are detailed in the following section.
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ABBREVIATIONS
BCR = Benefit Cost Ratio BoD = Burden of Disease CAC = Command and Control CBA = Cost Benefit Analysis COED = Cost of Environmental Degradation COI = Cost of Illness CS = Consumer Surplus CVM = Contingent Valuation Method DALYs = Disability Adjusted Life Years Dh = Dirham DRRs = Dose‐Response Relations EA = Environment Agency EIA = Environmental Impact Assessment GBD = Global Burden of Disease GDP = Gross Domestic Product GIS = Geographic Information System HCA = Human Capital Approach HPM = Hedonic Price Method IRR = Internal Rate of Return MC = Marginal Cost MBI = Market‐based instruments MENA = Middle East and North Africa METAP = Middle East Technical Assistance Program MR = Marginal Revenue NPV = Net Present Value NSB = Net Social Benefit O&M = Operation and Maintenance OC = Opportunity Cost RAD = Restricted Activity Days SCBA = Social cost benefit analysis TCE = Trichloroethylene TCM = Travel Cost Model UK = United Kingdom US = United States USD = United States Dollar VOSL = Value of Statistical Life W Korean Won WHO = World Health Organization WLD = Work Loss Days WTA = Willingness to Accept WTP = Willingness to Pay WWTP = Wastewater Treatment Plant
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INTRODUCTIONS AND PURPOSE OF THE WORKSHOP
Session 1
Region
al Training Worksho
p on
: Th
e Co
st of E
nviron
men
tal D
egrada
tion
Metho
dology
1
SESSION 1
1 INTRODUCTION AND PURPOSE OF THE WORKSHOP
Environmental degradation has become one of the most prominent adverse phenomena
in today’s world. The scope of environmental problems has grown substantially in the
past decade and will continue to expand and diversify more in the future; no generation
has ever faced a more daunting agenda. The world today confronts a multitude of
environmental problems, more than ever before, over a wider range of spatial and
temporal scales, and requiring various skills for proper control. Within this context, the
Middle East and North Africa (MENA) region is no exception in suffering from serious
environmental problems and natural resource degradation. Environmental pollution is
evident throughout the region which is exhibiting various types of degradation whether
water (coastal and inland surface, and ground), soil, and air (indoor and outdoor).
According to the Middle East Technical Assistance Program (METAP)/World Bank
Country studies1, the cost of environmental degradation in seven countries (Lebanon,
Syria, Jordan, Egypt, Tunisia, Algeria, and Morocco) ranges between US$228 million per
year in Jordan and US$4.2 billion per year in Egypt. Figure 1 illustrates the distribution of
the average estimated annual damage costs of environmental degradation in countries
in the MENA region by country and category in percent of Gross Domestic Product
(GDP).
Figure 1. Average annual damage costs of environmental degradation from studies in MNA countries
(percentage of GDP)
1 METAP website: www.metap.org
2
According to Figure 1, the cost of environmental degradation in MENA countries
constitutes between 2 and 5 percent of the country’s GDP, as compared to 1‐2% of GDP
in OECD countries, 4.5% of GDP in 1991 in India, 3.3% of GDP in Mexico, and 8% of GDP
in China. Yet, it is important to note that these results are underestimates because of
data limitations. As such, they do not include damage stemming from several potential
contributors such as untreated industrial, hazardous, and hospital wastes or losses of
forest cover and biodiversity. Also owing to data constraints, the impact of inadequate
treatment of industrial and municipal wastewater is limited to coastal recreational and
tourism losses.
The Cost of Environmental Degradation (COED) methodology in the MENA region is an
environmental economics tool developed by the METAP/World Bank. This tool enables
key professionals to carry out assessments of the economic cost of environmental
degradation. It has been successfully used in the valuation of environmental degradation
on a macroeconomic and sector levels, in terms of giving an estimate of GDP lost to
environmental degradation. The importance of economic valuation of environmental
degradation is that it allows the quantification of benefits of environmental projects/
policies, thus fostering the incorporation and prioritization of environmental issues in
decision‐making. It can be a powerful means for raising awareness about environmental
issues and fostering progress towards sustainable development. However, a main
obstacle to conducting policy‐relevant and timely studies in environmental economics is
the shortage of human capacity at governmental ministries/organizations as well as
academic institutions.
The current project, which is funded by the World Bank/ METAP and implemented by
the American University of Beirut, aims at enhancing regional capacity in environmental
economics. This document was prepared as part of the training course in COED
methodology. It aims to provide participants a comprehensive and easy to use reference
on this subject and follows the same sequence of the course syllabus.
BRIEF OVERVIEW OF BASIC ECONOMIC PRINCIPLES
& INTRODUCTION TO ENVIRONMENTAL
VALUATION
Session 2
Region
al Training Worksho
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: Th
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Metho
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SESSION 2
2 BRIEF OVERVIEW OF BASIC OF ECONOMIC PRINCIPLES
Activities of economic agents contribute to the generation of pollution. The operation of
the market system is intimately related to the nature and amount of pollution
generated. The purpose of this session is to introduce the participants to the basic
concepts of economic analysis, in terms of how markets work and why markets fail.
2.1 The competitive market
A market can be defined as the coming together of consumers (or buyers) and producers
(or sellers) to exchange goods and services for money. The buyers and sellers do not
have to be physically present to carry out transactions. Usually a market exists for a
single good or service. Markets may be classified according to the numbers of sellers and
buyers. In a perfectly competitive market, there are many buyers and sellers. A
monopoly is a market in which there is a single seller, such as the utilities sector in many
countries, where the government is the sole provider of electricity and water. An
oligopoly is an intermediate case in which there are few sellers. The Australian car
manufacturing market is an example of an oligopoly because there are four main sellers.
A monopsony is a market in which there is a single buyer. For example, a small town
with a single major industry that is the sole buyer of labor.
The competitive market has the following characteristics:
− There are many buyers and sellers and none of them are influential enough to affect
the market price or output
− The buyers and sellers are free to enter and leave the market in response to price
changes
− The goods and services being offered for sale are identical or homogeneous. This
implies that buyers do not care from whom they buy, provided prices are identical
− All the participants in the market have perfect knowledge. That is, consumers know
product prices and producers know input prices.
2.1.1 Consumer behavior and demand
The demand function is a curve that indicates how much of a good a consumer will buy
at various prices (Figure 2). Note the inverse relationship between price and quantity
demanded. This is referred to as the Law of Demand. That is, given income, preferences
and prices of alternative goods, an individual will be willing to purchase decreasing
amounts of a given good (or service) as its price increases.
4
− The points on the curve represent the maximum amount an individual is willing to pay for different quantities of q1
− The individual's demand for good q1 is defined given that all other goods and income remain constant
− The demand curve is defined for a given period of time. Thus, the demand curve in a different period of time will have a different shape and position
Figure 2. Individual demand function for a good q1
2.1.2 The concept of elasticity
The term 'elasticity' refers to the responsiveness of the quantity demanded (or supplied)
to changes in other variables (e.g., price and income). The concept of elasticity is
important because a key factor in the functioning of the economic system is the reaction
of economic agents to price incentives. Own price elasticity of demand is the ratio of the
change in quantity demanded of a given good to the change in its own price. That is:
εD = (percent change in quantity of q1 demanded)/ (percent change in price of q1)
Depending on the magnitude of the elasticity parameter, own‐price elasticity of demand
can be perfectly elastic, relatively elastic, relatively inelastic, or perfectly inelastic, as
illustrated in Table 1.
5
Table 1. Forms of elasticities
Type Graph DescriptionPerfectly elastic | εD | = ∞
A small increase in the price of the good causes the quantity demanded to fall to zero. In practice, no good has perfect price elasticity.
Relatively elastic | εD |>1
A small change in the price of the good causes a relatively large change in quantity demanded. In general, most luxury goods tend to be relatively price elastic.
Relatively inelastic| εD |<1
In this case, a change in the price of the good causes little change in quantity demanded. Necessities such as food and utilities (e.g., water and energy) tend to be relatively price inelastic.
Perfectly inelastic| εD |=0
A change in the price of the good does not lead to a change in quantity demanded
Cross‐price elasticity of demand refers to the responsiveness of the quantity of a
demanded good (q1) as a result of changes in another good (q2).
εD 12 = (percent change in quantity of q1 demanded)/ (percent change in price of p2)
1. εD12>0, implies q1 and q2 are substitutes. That is, an increase in the price of one good
causes consumers to switch to the other, resulting in an increase in the quantity
demanded of the second good. Examples of substitute goods are sugar and
NutraSweet, bus and rail transportation, etc.
2. εD12<0, implies q1 and q2 are complements. Complementary goods are consumed
together and therefore an increase in the price of one good leads to a reduction in
its consumption, and hence a reduction in demand.
Income elasticity of demand refers to the responsiveness of the quantity of a demanded
good (q1) as a result of changes in another good (q2)
6
ηγ = (percent change in quantity of q1 demanded)/ (percent change in income)
1. ηγ > 0, implies the good is a normal good. Most goods are normal goods because an
increase in income leads to an increase in quantity demanded.
2. ηγ < 0, implies the good is an inferior good. That is, an increase in γ leads to a
decrease in q1. There are not many practical examples of inferior goods. However, a
low‐ income family that currently consumes dried vegetables might reduce their
consumption and switch to fresh vegetables in response to an increase in household
income.
2.1.3 Producer behavior and supply
The production function of a good q is a function of various inputs, including labor, land
and capital that are used in producing good q. The producer's aim is to maximize profit
subject to the constraint of the above production function. Given the profit motive, the
producer will increase the output of q if its price rises so as to increase profits. The
production function (Figure 3) is positively sloped because producers are willing to
supply more as price increases. In addition, the curve refers to a given point in time.
− The supply curve is also the marginal cost (MC) curve. That is, it indicates the cost of producing each additional unit of the good. In order to maximize profits, the producer will increase production up to the point where marginal revenue (MR), the price per unit of output in a competition market, just equal marginal cost.
Figure 3. Market supply function
2.1.4 Market Equilibrium in the Competitive Market
The interaction of supply and demand forces in the market determines the equilibrium
or market clearing price, and the equilibrium quantity demanded. The equilibrium price,
in turn, determines the price for each unit of output, that is, marginal revenue. In Figure
4, market equilibrium is achieved at point E. Thus, at price PE, the market demand is
exactly equal to the quantity the market is willing to supply (SE).
7
Figure 4. Equilibrium in the market for a product Q1
Now suppose the market price per unit of Q1 increased to P’, the producer will supply S’,
while the consumer will demand only D’, which will result in demand deficit (Figure 5).
To clear the deficit, the producer will decrease the price and the consumer will increase
the purchase. The producer will decrease the quantities supplied until equilibrium is
reached and demand equals supply. On the other hand, if market price decreases to PA,
the consumer demand increases to DA. However, the producer is not willing to supply at
this price, causing a shortage in the market. This will put upward pressure on prices and
the producer will respond by increasing supply. As the price goes up, consumers will
reduce their purchases until the price decreases, at which point, quantity demanded will
be equal to quantity supplied (Figure 5).
Figure 5. Shift in market equilibrium for product Q1
Factors that can shift the demand curve include income, prices of substitutes or
complements, and consumer tastes and preferences. An income increase causes an
upward or rightward shift in market equilibrium, while an income decrease causes a
downward or leftward shift. For example, an increase in per capita income in a given
population (with all other factors constant) will shift the demand curve for mobile
telephones upwards. However, due to the excess demand, the price of mobile
telephones will rise to re‐establish equilibrium.
8
Decrease in income Increase in income
Figure 6. Shift in market equilibrium with change in income
A decrease in the price of substitutes for a good will cause the demand curve for the
good to shift downward, while a decrease in the price of complements for the good will
cause the demand curve to shift upward. For example, a decrease in the price of oil will
cause a downward shift in the demand for natural gas. The quantity of natural gas falls
and the price also falls to re‐establish equilibrium.
Factors that can cause the supply curve to shift include, price of inputs, taxes, subsidies,
improvements in technology and weather for agricultural products. A decrease in the
price of inputs for making good q will make the supply curve for q to shift outwards,
whereas an increase in the price of inputs will cause an inward shift. Improvement in
technology will cause an outward shift because more output can be produced with the
same level of inputs. For agriculture and other forms of production that are weather
dependent, deterioration in weather conditions will cause a leftward shift in the supply
curve.
Decrease in input price Increase in input price
Figure 7. Shift in market equilibrium with change in inputs
The examples of equilibrium illustrated above are highly simplified in order to convey
the basic concepts. In real life, equilibrium does not tend to be static. The demand curve
9
is constantly shifting due to changes in tastes and incomes, while the supply curve also
shift in response to resource constraints and technological advances. One important
assumption underlying the market equilibrium analysis above is that property rights are
well defined. That is, the seller owns the rights to the good or service and can therefore
appropriate any benefits from the sale.
2.1.5 Consumer and producer surplus
Consumer and producer surplus are illustrated in Figure 8. Consumer surplus is the
maximum amount of money consumers are willing to pay for the good or service minus
the market price. It is a measure of net benefits or welfare (Δ abc). The sole reliance on only the market price could result in an under estimation of benefits. Producer surplus is
the net benefits received by the producer and is given by the difference between the
market price and marginal cost (Δ bcd).
Figure 8. Consumer and producer surplus
2.1.6 Application of the Competitive Model‐ The socially optimal level of forestry
Clear felling of timber has several undesirable effects on society, including loss of forest
cover and associated problems such as increased soil erosion, loss of soil nutrients, loss
of biodiversity, etc. Assume that the stumpage price is currently p. At this price, q logs
will be harvested (Figure 9). Now suppose that the government charges an extra $5 per
log to cover the environment damage. This policy will result in an upward shift in the
supply curve from S to S’ by a vertical distance of $5 (Figure 9). assuming the demand for
logs remains constant during the period of the analysis, the quantity of logs harvested
will decline and equilibrium will be re‐established at q’, the socially optimal level.
10
Figure 9. Socially optimal level of forestry
2.2 Market Failure
Market failure occurs when some costs and/or benefits are not fully reflected in market
prices. The market system fails to function properly for many kinds of environmental
goods because such resources, including the services they provide, are often not traded
in markets. There are many reasons for market failure including:
− Property rights related to ecosystems and their services are often not clearly defined
− Many ecosystems provide services that are public goods
− Many ecosystem services are affected by externalities
− Type of market structure
2.2.1 Property rights
When property rights are not well defined or absent in the economic system, there is no
incentive for an individual to invest in an asset because they cannot appropriate the full
benefits. When one purchases an asset, it comes with a set of well‐defined ownership
rights and responsibilities. These have the following general characteristics:
− Well defined: in the form of registration certificate of purchase receipt. In some
cases the entitlement may be informal and may have been institutionalized by social
or cultural norms.
− Exclusive: the buyer is the only one who has the right to use the asset, although he
may choose who else may use it and under what conditions. It is important to note
that restrictions accompany ownership rights.
− Transferable: the buyer may transfer property rights of his asset to another
individual either permanently by selling it or temporarily by renting it.
− Secure and enforceable: the property rights to an asset are secure and enforceable.
Effective enforcement involves the effective detection and apprehension of violators
and application of an appropriate penalty. To be effective, the penalty must exceed
the actual or anticipated benefits of violation.
11
Property rights regimes
In practice, there are different types of property rights regimes. The complete set of
property rights described above is at one end of the spectrum and is typical of private
goods. At the other end of the spectrum, there are public goods, with congestion goods
in between these two. Public goods can be classified into pure public goods, semi public
goods, and open access or common property goods (Figure 10).
Figure 10. Taxonomy of environmental goods
Most environmental goods fall under the category of pure public goods or open
access/common property goods. In such cases lack of well‐defined property rights
results in market failure. A consequence of market failure is inefficient allocation of
resources (e.g., excessive pollution). For example, a farmer has the right to prevent
someone from polluting his or her land, but cannot prevent anyone from polluting a
nearby river. Furthermore, he or she may have no legal right to receive compensation
from the upstream polluters. The upstream polluters, who do not bear costs of their
activities, have no economic incentives to limit the amount of pollution especially when
they know that the farmer has no property rights. This type of market failure has led to
calls for governments to intervene in the market.
Private vs. public goods
As mentioned earlier, a private good has characteristics such as exclusivity,
transferability, security, and enforceability. In addition, a private good has a positive
marginal cost. That is, the cost of supplying one additional unit is above zero. A private
good is rival in consumption. That is, once someone consumes the good, another person
cannot consume it. On the other hand, a pure public good is non‐exclusive and non‐rival
in consumption, and has zero marginal cost. 'None exclusive' and 'non‐rival' mean the
Goods and
Services
Private goods Congestion goods Public goods
Open access & common property
goods
Pure public goodsSemi-public goods
12
good is available to everyone and that one person's consumption of the good does not
reduce the amount available to others. 'Zero‐marginal costs' means the cost of supplying
an additional unit of the good to any particular individual is zero. Examples of pure
public goods are national defense, biodiversity, clean air, flood protection, noise and
visual amenities. A distinctive characteristic of a pure public good is that consumers do
not have the option of not consuming. As suggested earlier, a pure public good will be
under‐provided because the owner cannot appropriate the full benefits.
Open access goods are rival in consumption, non‐exclusive, non‐transferable, and often
non‐enforceable even when ownership rights exist. Examples of open goods are ocean
fisheries and migratory wildlife. Common property goods (e.g., common grazing land)
are rival in consumption and are exclusive for a group of people (e.g., a local
community). Rights of use may be transferable by individuals or the group. There may
not be legal or formal title to ownership but the group may be able to enforce their
ownership rights by means of social sanctions. Under open access or common property
rights regimes, the resource will be overexploited. However, under some form of
common property systems, resource management is likely to be more efficient because
it is based on communal rules and customs.
Semi‐public (or quasi public) goods are non‐rival in consumption, have a zero marginal
cost of provision and are non‐exclusive although ownership rights exist. An important
distinction of semi‐public goods is that even though the owner or the providers of the
service cannot exclude others form consumption, consumers can choose not to
consume. Examples of this category of goods include radio and TV broadcasts and
lighthouse.
Congestion goods are exclusive and can be either non‐rival or rival in consumption. Such
goods do not fall neatly into any of these categories and may exhibit characteristics of
private goods or public goods at different levels of consumption. An example of this type
of good is a campsite, roads, bridges, an art gallery, fishing and boating sites, and a
historic site.
2.2.2 Externalities
As the word suggests, an externality is an effect that is 'external' to the causing agent.
That is, the person causes an effect that impact on other people. An externality is said to
exist when some agent A (individual or firm) takes an action which has an impact on
another agent B, that B has not chosen to accept. In an externality, agent B cannot
13
choose the level of the impact like in a normal economic transaction and the impact on
B is not a deliberate attempt from A. An externality is often negative. This occurs when
the affected person suffers a loss in utility that is uncompensated. Examples of negative
externalities are air, water and noise pollution. A positive externality (external economy
or external benefit) occurs when the effect is beneficial to the affected person. An
example of a positive externality is immunization. Another example of a positive
externality is where one firm's technological breakthrough benefits other firms in the
industry who have not contributed to the research costs.
The following factors give rise to externalities:
1. Interdependence between economic agents: the market system fails to 'price' this
interdependence, as a result of which the affected party is uncompensated.
2. Lack of or weak property rights: due to lack of or weak property rights, the affected
party is unable to demand that the externality be reduced or ask for compensation.
3. High transactions costs: the cost of negotiating, implementing and enforcing and
agreement between the parties may be high.
Once the affected agent is compensated for his or her loss of welfare, the externality is
said to be 'internalized', and society is better off by the gainer compensating the loser.
Types of externalities
Externalities can be classified into relevant externalities, pareto‐relevant externalities,
static or dynamic externalities, and pecuniary externalities. A relevant externality is
when the affected person is made worse off by the activity and wants the offending
person to reduce the level of the activity. A pareto‐relevant externality exists whenever
its removal results in a pareto improvement. A pareto improvement is a situation where
it is possible to take action such that the affected person is made better off without
making the offending person worse off. A dynamic externality exists when the
externality has adverse impacts for the future. To illustrate static and dynamic
externalities, take the example of two fishers who are operating under an open access
or property rights regime. A static externality is when one creates an externality for the
other by overfishing. However, the externality can become dynamic if the offending
party is harvesting fish that may have some future value. This could happen, for
example, if the offender is harvesting juvenile fish species. In this case, the opportunity
cost of the fish reflects a forgone value in the sense that there will be adverse impacts
for the future. A pecuniary externality is a form of externality that is transmitted through
the price system. An externality is usually an 'unpriced' effect. However, a pecuniary
14
externality occurs when the externality is transmitted through higher prices or reduced
costs. An example is increased rental prices in an area due to a new business opening
there. Pollution is not a pecuniary externality because the effect is not transmitted
through higher prices. Even if penalties exist, they do not reflect the amount of damage
inflicted on the environment.
2.2.3 Type of Market Structure
The type of market structure or organization can also cause market failure. We consider
the following two cases: a perfectly competitive market with external costs and a
monopoly.
Resource allocation in a perfectly competitive market
Consider a gold mining company that dumps mine tailings into a nearby river without
paying for clean up or treating the waste. In this case, production at the mine includes
the production of gold as well as pollution. Or to put it differently, the river water is an
unpriced input in the gold production process. Let us define the following variables:
D = demand curve for gold; MCp = marginal private cost of producing gold (i.e., the
firm's supply curve); MSC= marginal social cost (Figure 11).
Figure 11. Resource allocation in a competitive market with externalities
We assume that MSC is greater than MCp at any level of output because society
considers both the costs of pollution as well as gold production, but the company
considers only its marginal private cost. The marginal social cost of gold production is
therefore given by the marginal external cost, the cost of disutility caused by the
externality, plus the marginal private cost. That is:
C=MCp+ MSC
15
Under a perfectly competitive market structure, the company maximizes its producer
surplus by producing q0 units of gold. However, from society’s point of view, q0 is not
the efficient allocation. Society's net benefits could be maximized by producing less gold,
that is, q’ units. The triangular area Δabc represents a deadweight loss to society. Note the following observations about Figure 11:
1. The socially optimal level of pollution (which is assumed to be proportional to gold
production) is not zero. This implies that it may not be socially optimal to have zero
pollution.
2. In a perfectly competitive market where pollution is unpriced (i.e., there is no
pollution abatement), production results in more output that is socially desirable,
resulting in excessive pollution.
3. If pollution abatement is enforced, the company will reduce pollution but raise the
price per unit of output, resulting in reduced output of gold. However, in this case,
the reduced output is the socially efficient level and the higher price is also the
efficient price.
Resource allocation in a monopoly
Assuming a perfectly competitive market and a system of private property rights, the
price mechanism will combine to result in an efficient allocation of resources. However,
the presence of monopoly rights causes market failure or inefficient allocation of
resources from society's point of view. Take the case of a single monopolistic firm with a
marginal cost curve, MC, facing a market demand curve, D (Figure 12). Under perfect
competition, q units of the good will be supplied by setting the price = marginal revenue
(MR) = marginal cost (MC). Note, however, that in the case of a monopoly, the demand
curve is above the marginal revenue curve and therefore price is not equal to marginal
revenue.
Figure 12. Resource allocation in a monopoly
16
Monopoly profit is maximized by setting MR equal to MC. This results in less output, qm,
and a higher price, pm. Consumer surplus under a monopoly is apmb, which is less than
consumer surplus under perfect competition, Δ ap’c. Recall that the demand curve (D)
represents the marginal benefit of goods to consumers. Figure 12 indicates that for a
monopolist, marginal benefit exceeds marginal cost and therefore the level of output
(qm) is inefficient. Consequently, there is dead weight loss to society represented by
triangle Δbdc.
The monopolist's production decision may be somewhat unexpected because it seems
to suggest that less pollution will be created in a monopoly than in perfect competition.
Furthermore, the monopolist's higher initial price (pm) suggests that, given a fixed stock
of natural capital, the price path will be less steep over time than in perfect competition.
However, caution must be exercised in making such comparisons because other factors
such as elasticity of demand affect the outcome.
2.3 Policy failure
Policy or government failure occurs when the government creates incentives for the
prices of certain goods and services to be lower than the actual cost of production per
unit. An example of policy failure is a government subsidy on pesticides which provides
incentives for farmers to use more pesticide than is socially efficient, resulting in adverse
environmental impacts. Other types of subsidies include guaranteed prices for
agricultural products and subsidies which tend to encourage large scale production and
loss of forest cover. In general, subsidies in the developing countries are on the decline
as most of them have adopted structural adjustment programs over the past two
decades.
2.3.1 Solutions to environmental pollution problems
Two main approaches have been proposed for dealing with externality problems. The
first approach, known as the property rights or market solution, was proposed by Ronald
Coase and involves allowing the free market system to solve the problem through
bargaining between the affected parties. However, it is based on assumptions that may
not apply in the real world, including, zero transaction costs, well‐defined property
rights, perfect competition, and no free‐rider effect. The second approach is by means of
government intervention. There is always a need for government interventions to
correct externality problems. Government pollution control policies can take two main
forms: market based instruments (MBI) and command‐and control (CAC) instruments
(Figure 13).
17
Figure 13. Government pollution control policies
Command and control instruments are the oldest form of pollution control policies. They
require setting the standard and monitoring and enforcing it. They have the advantage
of being a widely understood form of policy and being more pragmatic and socially
acceptable than MBIs. On the other hand, such policies provide no incentive for
pollution reduction beyond standards. In addition, penalties tend to be too low and
enforcement too weak. Governments must know the marginal social cost and marginal
social benefits curves to set an optimal penalty and penalties need to be revised
frequently, which is costly. Furthermore, financial costs for setting and enforcing
standards are high; political costs may arise if standards are stringent; and standards are
uniformly set to all firms and regions.
As for market‐based instruments, they use price or some other economic variables to
provide incentive for economic agents to abate pollution. They have the advantage of
achieving the same objective as CACs at a lower cost, and of generating significant
revenue for the government. However, they cannot be applied where the institutional
framework is weak.
When choosing the right instrument for pollution abatement and control, various
criteria need to be considered including, economic efficiency, effectiveness in achieving
the desired environmental objective, adaptability to changing circumstances, equity in
the distribution of costs and benefits among different groups in the society, and political
acceptability.
18
3 INTRODUCTION TO ENVIRONMENTAL VALUATION
The proper valuation of non‐market environmental commodities has significant policy
implications. In the past, such commodities have been assigned zero to low values due
to difficulties involved in assigning economic values. Failure to properly account for the
values of some environmental resources has resulted in decisions that have had
negative implications for the environment and society.
An environment resource has a range of values that need to be accounted for. These
values can be categorized into use‐values and non‐use values (Figure 14).
Figure 14. The elements of total economic value
Some of the environmental functions are used directly, either contributing towards the
production of marketed outputs or else contributing to consumption directly. For
example, agricultural land provides the medium for the production of crops and timber.
The environment may also be used directly for consumption purposes, for recreation or
as landscape value. The third category of use values is the ecological functions of the
environment, such as flood control, waste assimilation, or carbon storage. Alternatively,
non‐use or intrinsic values are inherent in the good. The satisfaction we derive from the
good is not related to its consumption per se. Non‐use values comprise existence value,
bequest value, and option value. Existence value arises from the benefit that an
individual derives from knowing that a resource exists or will continue to exist regardless
of the fact that he has never seen or used this resource, or intends to see or use it in the
future. An example is the international outcry over the whaling issue. Bequest values
arise from the benefit that individuals derive from knowing that a resource will be
19
available for their children and children’s children. Option value is a little more complex.
It represents the value of potential uses. An individual is prepared to pay now, to retain
options for future uses.
Use values can be readily measured by market prices or other means and are well‐
accounted for in decision‐making processes. However, non‐use values are problematic
because they can constitute a significant component of total economic value, and yet
they are not traded and therefore cannot be valued by market prices. For this purpose,
non‐market valuation techniques have been developed.
3.1 Non‐market valuation techniques
Non‐market valuation methods can be broadly classified into two categories, revealed
preference models and stated preference models (Figure 15).
Figure 15. Non‐market valuation methods
Revealed preference models make use of individual behavior in real and simulated
markets to infer the value of an environmental good or service. For example, wilderness
is valuated from the cost incurred to travel to the area for recreation. Revealed
preference models measure use values only. The choices made are real rather than
hypothetical. The revealed preference models are based on a clear principle but
complicated applications. Examples of revealed preference methods include the travel
cost method, the hedonic pricing methods, the averting behavior method, and the
market values method.
Stated preference models attempt to elicit environmental values directly from
respondents using survey techniques such as questionnaires. They are flexible and
Preferences
Revealed preferences
Stated Preferences
Market Values
Travel Cost Methods
HedonicMarkets
Averting Behavior
Contingent Valuation
Choice Experiments
20
applied to a wide range of goods and they measure both use and non‐use values.
However, these models are subject to many biases. The following chapters discuss in
detail the various non‐market valuation methods.
THE PRODUCTIVITY METHOD &
THE MARKET PRICE METHOD &
THE DAMAGE COST, SUBSTITUTION COST, AND REPLACEMENT COST
Sessions 3 & 4
Region
al Training Worksho
p on
: Th
e Co
st of E
nviron
men
tal D
egrada
tion
Metho
dology
21
SESSIONS 3 & 4
4 THE PRODUCTIVITY METHOD
4.1 Theory
The production function method is one of the most widely used valuation techniques. It
focuses on environmental resources as an input to the production of goods and services.
It is used to estimate the economic value of ecosystem products or services that
contribute to the production of commercially marketed goods. Thus, if a natural
resource is a factor of production, then changes in the quantity or quality of the
resource will result in changes in production costs, and/or productivity of other inputs.
This may affect the price and/or quantity supplied of the final good. It may also affect
the economic returns to other inputs. For example, agricultural production is a function
of soil (S) and other inputs (x). As soil quality declines from S1 to S2 due to soil erosion,
the production function shifts to Q2 (Figure 16). Accordingly, the farmer has the option
of producing at Q2 or to keep production at Q1 by increasing other inputs from X1 to X2.
Figure 16. The production function curve
Two types of benefits (or costs) may be important (Figure 17):
− Changes in the quality or price to consumers of the final good will result in changes
in consumer surplus
− Changes in productivity or production cost changes will result in changes in producer
surplus
22
Figure 17. Market supply and demand functions
Thus, the economic benefits from improvements in the resource can be estimated using
changes in observable data.
The production‐function method is most easily applied in two specific cases:
− Cases where the resource in question is a perfect substitute for other inputs: For
example, improved water quality in a reservoir means that less chlorine is needed
for treating the water. An increase in quantity or quality of the resource will result in
decreased costs for the other inputs. The benefits of improved water quality can be
directly measured by the decreased chlorination costs.
− Cases where only producers of the final good benefit from changes in quantity or
quality of the resource and consumers are not affected: For example, improved
quality of irrigation water may lead to greater agricultural productivity. If the market
price of the crops to consumers does not change, benefits can be estimated from
changes in producer surplus resulting from increased income from the other inputs.
The profits per acre will increase, and this increase can be used to estimate the
benefits of improved irrigation water quality
Selected applications of the production function method are outlined in Figure 18.
Pressure Environmental
Impact Productivity Impact Change in Income
Overgrazing Soil erosion Reduced capacity of soil to sustain crops
Reduced farmers income
Wastewater discharge
Polluted river Reduced capacity to sustain fish stocks
Reduced income of fishermen
Increased vehicle use
Air pollution Increased respiratory problems among workers
Lost workdays
Uncontrolled irrigation
Salinity of cropland
Declining yields Reduced farmers income
Figure 18. Selected applications of the productivity method
23
4.2 Applying the Productivity Method
Steps to be followed when applying this method include:
1. Determine the physical impact solely arising from the driving force or behaviour
under study. Note that it is sometimes difficult to differentiate impacts due to a
series of complex biological interrelationships.
2. Collect data on how changes in the quantity/ quality of the natural resource affect
costs of production for the final good, supply and demand for the final good, and
supply and demand for other factors of production. Sources of data include
experimental data using field trials and statistical data using cross‐section or time‐
series data. Experimental data are usually difficult to extrapolate, while statistical
data are available for short time horizons and are difficult to control for other
factors.
3. Link the impact of changes in the quantity/ quality of the resource to changes in
consumer surplus and/or producer surplus. Problems encountered with this step
include:
− Distorted prices due to government interventions
− Change under study is not large enough to impact market price
− Change in market price is too large
− Change in production alters costs 4. Estimate the economic benefits
The productivity method has the advantage of being a straightforward methodology
that is inexpensive to apply due to limited data requirements and ready availability of
relevant data. However, this methods does not account for non‐use values, hence it
provides only the lower bound estimate. Furthermore, it is limited to valuing resources
that can be used as inputs in production of marketed goods. It also requires information
on the scientific relationships between actions to improve quality or quantity of the
resource and the actual outcomes of those actions. Finally, if the changes in the natural
resource affect the market price of the final good, or the prices of any other production
inputs, the method becomes much more complicated and difficult to apply.
4.3 Illustration 1‐ Polluted municipal drinking water reservoir
A municipal drinking water reservoir is polluted by agricultural runoff. The economic
benefits of implementing measures that eliminate the runoff need to be determined.
Accordingly, the productivity method was selected because environmental quality
directly affects the cost of producing municipal drinking water. In addition, cleaner
water is a direct substitute for other production inputs, such as water treatment
24
chemicals and filtration. Thus, the benefits of improved water quality can be easily
related to reduced purification costs.
To apply the production‐function method, first, specify the production function for
treated drinking water. Inputs include water of a particular quality from the reservoir,
chemicals, and filtration, while outputs include pure drinking water. Second, estimate
how the cost of treatment changes when reservoir water quality changes, using the
production function estimated in the first step. Calculate the quantities of treatment
chemicals and filters needed for different levels of reservoir water quality and multiply
these quantities by their costs. Third, estimate the economic benefits of protecting the
reservoir from runoff, in terms of reduced purification costs. If all runoff is eliminated,
the reservoir water will need very little treatment and the purification costs for drinking
water will be minimal. Compare the outcome to the cost of treating water where runoff
is not controlled. The difference in treatment costs is an estimate of the benefits of
eliminating runoff. The benefits for different levels of runoff reduction can also be
estimated. This requires information about the projected success of actions to reduce
runoff, in terms of the decrease in runoff and the resulting changes in reservoir water
quality.
4.4 Illustration 2‐ Values of Wetlands in the Peconic Estuary, Long Island
The Peconic estuary encompasses productive wetlands of different types, including
eelgrass, salt marsh, and intertidal mudflats. Development and resulting water quality
degradation have reduced the quantity of these wetlands. Various management actions
for the estuary and surrounding land areas need to be considered and assessed using a
productivity study for wetlands.
The study focused on valuing marginal changes in acres of wetlands, in terms of their
contribution to the production of crabs, scallops, clams, birds, and waterfowl, assuming
that wetlands provide both food chain and habitat support for these species. The
productivity of different wetlands types in terms of food chain production was
estimated and linked to production of the different species of fish. The expected yields
of fish and birds per acre of habitat were valued using commercial values for fish,
viewing values for birds, and hunting values for waterfowl.
The study results estimated that:
− An acre of eelgrass is worth $1,065 per year
− An acre of salt marsh is worth $338 per year
− An acre of intertidal mudflat is worth $68 per year, in terms of increased productivity
25
of crabs, scallops, clams, birds, and waterfowl
Based on the results the economic value for productivity services of preserving or
restoring wetlands in the estuary can be calculated. Note that these values are an
understatement of the total economic value for the wetlands, as they only address
values in production of commercially and recreationally valuable species. They overlook
other services, such as erosion and storm protection or aesthetics.
4.5 Case‐study: Degraded agricultural land & rangeland in Morocco
About 93% of Morocco is arid. Fragile soils suffer from water and wind erosion.
Furthermore, overexploitation and unsustainable management is resulting in arable land
loss, decrease in crop yield, silting of dams, loss in biodiversity, and loss in terms of
attenuating emissions of gases causing greenhouse effect. In Morocco, around 65 million
ha of pastureland provide 30% of overall animal food requirements. Erosion, drought,
overgrazing, land clearing and removal of woods are resulting in degraded pastureland.
4.5.1 Methodology
Degradation of agricultural land is estimated by calculating the value of lost agriculture
production due to a decrease in land productivity. Since the majority of agricultural land
is planted with cereals, the cost of degraded agricultural land corresponds to the value
of lost cereal production. As for the degradation of rangeland, it is estimated by
calculating the cost of lost forage production
Step 1: Estimation of degraded agricultural land
FAO classified the degradation of 8.7 million ha in Morocco as “severe”. According to the
FAO, three scenarios are possible:
− 10 to 25% of land is severely degraded
− 25 to 50% of land is moderately degraded
− 50 to 100% of land is slightly degraded
Surveys did not show any case of severe land degradation, thus only moderate and slight
degradation are used.
Step 2: Estimation of the decrease in agricultural yield
Young estimated the decrease in cereal yield as follows:
− Slight degradation corresponds to a 5% decrease in cereal yield
− Moderate degradation corresponds to a 20% decrease in cereal yield
26
Given that the mean yield for cereals in Morocco is 1 Ton/ha, then a slight degradation
will result in a decrease of 50 Kg/ha in cereal production, while a moderate degradation
will result in a 200 Kg/ha decrease.
Step 3: Assessing the cost of degraded agricultural land
The average of the lower bound and the upper bound of moderate and slight
degradation were used. The adopted selling price of cereal was 2,580 Dh/Ton.
Accordingly, the average cost of agricultural land degradation is estimated at Dh 1,263
million, constituting 0.36% of the GDP (Table 2).
Table 2. Assessing the cost of degraded agricultural land
Parameter Lower limit Upper limit
Moderate erosion 25% 50%
Degraded agricultural land (000 ha) 2,175 4,350
Level of decrease 20% 20%
Decrease in yield (Kg/ha) 200 200
Lost production (Tons) 435 870
Lost value (millions of Dh) 1,122 2,244
Slight erosion 50% 100%
Degraded agricultural land (000 ha) 4,350 8,700
Level of decrease 5% 5%
Decrease in yield (Kg/ha) 50 50
Lost production (Tons) 217.5 435
Lost value (millions of Dh) 561 1,122
Average (millions of Dh) 842 1,683
Step 4: Estimation of degraded pastureland
When estimating the cost of degraded pastureland, calculations considered only the
areas with dominant steppe and forest covers, excluding the Saharan region. The total
dominant steppe area considered was 12 million ha and the total dominant forest area
considered was 5.1 million ha. According to REEM, 46% of dominant steppe is degraded,
amounting to 5.52 million ha, and 19% of dominant forest area is degraded, amounting
to 0.969 million ha.
Step 5: Estimation of the loss of productivity
The Ministry of Agriculture and Agricultural Development estimated land productivity as
79 FU/ha/year (FU: Forage Unit equivalent to 1Kg Barley) for steppe and 558 FU/ha/year
27
for forest. The Ministry of Agriculture and Agricultural Development adopted 2 levels of
loss, 6% and 10%. Accordingly, the estimated productivity loss was as follows:
Steppe: 6% 26.1 million FU / year
10% 43.6 million FU / year
Forest: 6% 26.1 million FU / year
10% 43.6 million FU / year
Step 6: Assessing the cost of rangeland degradation
Given that the price of barley is 2,270 Dh/Ton, the FU price is 2.27 Dh. Accordingly, the
average cost of rangeland degradation is estimated at 177.4 Dh million, which
constitutes 0.05% of the GDP (Table 3).
Table 3. Assessing the cost of rangeland degradation
Parameter Steppe Forest Total
Pasture area (000ha) 12,000 5,100 17,100
Degraded area (%) 46% 19%
Degraded area (000ha) 5,520 969 6,489
Land productivity (FU/ha/year) 79 558
Loss in yield in degraded area 10%
Lost yield (000FU/year) 43,608 54,070 97,678
Lost value (million Dh) 99.0 122,7 221.7
Loss in yield in degraded area 6%
Lost yield (000FU/year) 26,165 32,442 58,607
Lost value (million Dh) 59.4 73,6 133.0
Average (million Dh) 79.2 98.2 177.4
Based on the above estimations, the total cost of land degradation, including both
agricultural and rangeland, is estimated to range between Dh 975 and 1,895 million,
with an average of 1,440 million Dh, which constitutes 0.41% of the GDP.
5 THE MARKET PRICE METHOD
The market price method makes use of observed market prices for environmental goods
and services. It values changes in quantity and/or quality of a good or service by using
standard economic techniques for measuring the economic benefits from marketed
goods. This method is applied for goods and services with established markets, and
28
which have direct uses, such as plantation timber, commercial fisheries, and tourism;
some indirect uses, such as value of water from protected watersheds; and some option
values, such as gene research and forest conservation.
5.1 Applying the Market Price Method
Market price represents the value of an additional unit of that good or service, assuming
the good is sold through a perfectly competitive market. Applying the method requires
data to estimate consumer surplus and producer surplus. To estimate consumer surplus,
the demand function must be estimated, which requires time series data on the quantity
demanded at different prices, and data on other factors that might affect demand, such
as income or other demographic data. To estimate producer surplus, data is needed on
variable costs of production and revenues received.
5.2 Advantages and limitations
The advantages of the market price method include the following:
− It is relatively simple and straightforward
− It relies on actual market values
− The price, quantity and cost data are easy to obtain for established markets
− The method uses observed data of actual consumer preferences
− The method uses standard, accepted economic techniques
The application of the market price method is associated with several issues and
limitations including:
− Market data may only be available for a limited number of goods and services
provided by a resource
− Available market data may not reflect the value of all productive uses of a resource
− The true economic value of goods or services may not be fully reflected in market
transactions, due to market imperfections and/or policy failures
− Seasonal variations and other effects on price must be considered
− Cannot be easily used to measure the value of larger scale changes that are likely to
affect the supply of or demand for a good or service
− Does not deduct the market value of other resources used to bring ecosystem
products to market, and thus may overstate benefits
5.3 Illustration 1‐ Closure of a commercial fishing area due to water pollution
Water pollution is causing the closure of a commercial fishing area. The benefits of
cleanup need to be evaluated before deciding on their implementation. The market
29
price method was used because the primary resource affected is fish, for which market
data are available.
The objective is to measure the total economic surplus for the increased fish harvest
that would occur if the pollution is cleaned up. The difference between economic
surplus before and after the closure must be estimated. The results of the analysis can
be used to compare the benefits of actions that would allow the area to be reopened, to
the costs of such actions.
Step 1
Use market data to estimate the market demand function and consumer surplus for the
fish before the closure. Assume a linear demand function, where the initial market price
is $5/g and the maximum willingness to pay is $10/g. At $5/g, consumers purchased
10,000 g fish/yr, thus spending $50,000 on fish per year. The shaded area on the graph
represents the total consumer surplus received from the fish before the closure = ($10‐
$5)*10,000/2 = $25,000 (Figure 19).
02468
1012
0 5,000 10,000 15,000 20,000 25,000
Quantity demanded (g)
Pric
e ($
/g)
Figure 19. Demand for fish before closure
Step 2
Estimate the market demand function and consumer surplus for the fish after the
closure. The market price of fish increased from $5/g to $7/g. The total quantity
demanded decreased to 6,000 g/yr. The new consumer surplus is ($10‐$7)*6,000/2 =
$9,000 (Figure 20).
Consumer surplus
30
02468
1012
0 5,000 10,000 15,000 20,000 25,000
Quantity demanded (g)
Pric
e ($
/g)
Figure 20. Demand for fish after closure
Step 3
Estimate the loss in economic benefits to consumers by subtracting benefits after the
closure from benefits before the closure. The loss in benefits to consumers is 25,000 ‐
9,000 = $16,000.
Step 4
Estimate the losses to producers by first measuring the producer surplus before the
closure. Producer surplus is measured by the difference between the total revenues
earned from a good, and the total variable costs of producing it. Before the closure,
10,000 g of fish were caught per year. Fishermen were paid $1/g, with their total
revenues amounting to $10,000 per year. The variable cost to harvest the fish was
$0.50/g (total variable cost = $5,000 per year). The producer surplus before the closure
was $10,000 ‐ $5,000 = $5,000.
Step 5:
Measure the producer surplus after the closure (Table 4).
Step 6:
Calculate the loss in producer surplus due to the closure (Table 4).
Consumer surplus
31
Table 4. Summary of calculations
Before closure After closure
Fish caught per year = 10,000 g Fish caught per year = 6,000 g
Fishermen were paid $1/g Fishermen were paid $1/g
Total revenues = 1 × 10,000 = $10,000 per year Total revenues = 1 × 6,000 = $6,000 per year
Variable cost to harvest fish = $0.50/g Variable cost to harvest fish = $0.60/g
Total variable cost = 0.5 × 10,000 = $5,000 per year Total variable cost = 0.5 × 6,000 = $3,600 per year
The producer surplus = $10,000 ‐ $5,000 = $5,000 The producer surplus = $6,000 ‐ $3,600 = $2,400
Loss in producer surplus due to the closure = $5,000 ‐ $2,400 = $2,600
Step 7:
Calculate the total economic losses due to the closure. Total economic loss = lost
consumer surplus ($16,000) + lost producer surplus ($2,600). Thus, the benefits of
cleaning up pollution in order to reopen the area are equal to $18,600.
Finally, it is important to note that this example is based on assumptions that greatly
simplify the analysis. Some factors might make the analysis complicated. For instance,
some fishermen might switch to another fishery after the closure, and thus losses would
be lower.
6 DAMAGE COST AVOIDED, REPLACEMENT COST, AND
SUBSTITUTE COST METHODS
These methods estimate values of ecosystem services based on the costs of avoiding
damages due to lost services, the cost of replacing ecosystem services, or the cost of
providing substitute services. These methods assume that the costs of avoiding damages
or replacing ecosystems or their services provide useful estimates of the value of these
ecosystems or services. They also assume that if people incur costs to avoid damages
caused by lost ecosystem services, or to replace the services of ecosystems, then those
services must be worth at least what people paid to replace them. The damage cost
avoided, replacement cost, and substitute cost methods are most appropriately applied
in cases where damage avoidance or replacement expenditures have actually been, or
will actually be, made.
The damage cost avoided method uses either the value of property protected or the
cost of actions taken to avoid damages as a measure of the benefits provided. For
example, if a wetland protects adjacent property from flooding, the flood protection
32
benefits may be estimated by the damages avoided if the flooding does not occur or by
the expenditures property owners make to protect their property from flooding. The
replacement cost method uses the cost of replacing an ecosystem or its services as an
estimate of the value of the ecosystem or its services. As for the substitute cost method,
it uses the cost of providing substitutes for an ecosystem or its services as an estimate of
the value of the ecosystem or its services. For example, the flood protection services of a
wetland might be replaced by a retaining wall or levee.
6.1 Applying the methods
Step 1: Assess the environmental service provided
This is done by specifying the relevant services, how they are provided, to whom they
are provided, and the levels provided. For example, in the case of flood protection, this
would involve predictions of flooding occurrences and their levels, as well as the
potential impacts on property.
Steps 2 and 3
For the damage cost avoided method, estimate the potential physical damage to
property, either annually or over some discrete time period. Then calculate either the
dollar value of potential property damage, or the amount that people spend to avoid
such damage.
For the replacement or substitute cost method, identify the least costly alternative
means of providing the service and calculate the cost of the substitute or replacement
service. Then establish public demand for this alternative, which requires gathering
evidence that the public would be willing to accept the substitute or replacement
service in place of the ecosystem service.
Examples of applications of these methods
− Valuing improved water quality by measuring the cost of controlling effluent
emissions
− Valuing erosion protection services of a forest or wetland by measuring the cost of
removing eroded sediment from downstream areas
− Valuing the water purification services of a wetland by measuring the cost of filtering
and chemically treating water
− Valuing storm protection services of coastal wetlands by measuring the cost of
building retaining walls
− Valuing fish habitat and nursery services by measuring the cost of fish breeding and
stocking programs
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6.2 Advantages and limitations
The advantages of these methods include:
− They may provide a rough indicator of economic value, subject to data constraints
and the degree of similarity or substitutability between related goods.
− They are less data and resource‐intensive, whereby it is easier to measure the costs
of producing benefits than the benefits themselves, when goods, services, and
benefits are non‐marketed.
− Data or resource limitations may rule out valuation methods that estimate
willingness to pay
− They provide surrogate measures of value that are as consistent as possible with the
economic concept of use value, for services which may be difficult to value by other
means
Issues and limitations associate with these methods include:
− They do not provide a technically correct measure of economic value, which is
properly measured by the maximum amount of money or other goods that a person
is willing to give up to have a particular good, less the actual cost of the good.
− They assume that expenditures to repair damages or to replace ecosystem services
are valid measures of the benefits provided.
− They do not consider social preferences for ecosystem services, or individuals’
behaviour in the absence of those services.
− They may be inconsistent because few environmental actions and regulations are
based solely on benefit‐cost comparisons, particularly at the national level. For
instance, the cost of a protective action may exceed the benefits to society.
Alternatively, the cost of actions already taken to protect an ecological resource will
underestimate the benefits of a new action to improve or protect the resource.
− The replacement cost method requires information on the degree of substitution
between the market good and the natural resource. Substitute goods are unlikely to
provide the same types of benefits as the natural resource.
− The goods/services being replaced probably represent only a portion of the full
range of services provided by the natural resource. Thus, the benefits of an action to
protect or restore the ecological resource would be understated.
− Without evidence that the public would demand the least cost alternative for the
affected ecosystem, this methodology is not an economically appropriate estimator
of ecosystem service value.
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6.3 Illustration 1‐ Restoration of degraded wetlands
An agency is considering restoring some degraded wetlands in order to improve their
ability to protect the surrounding area from flooding. Cost‐based methods are used
because the agency is only interested in valuing the flood protection services of the
wetlands and because a limited budget is available for the valuation study.
Step 1
Conduct an ecological assessment of the flood protection services provided by the
wetlands to determine the current level of flood protection and the expected level of
protection after full restoration of the wetlands
Step 2
The Damage Cost Avoided method is applied using two different approaches
− Use the information on flood protection obtained in the first step to estimate
potential damages to property if flooding were to occur. Estimate, in dollars, the
probable damages to property if the wetlands are not restored.
− Determine whether nearby property owners have spent money to protect their
property from the possibility of flood damage by purchasing additional insurance or
by reinforcing their basements. These avoidance expenditures would be summed
over all affected properties to provide an estimate of the benefits from increased
flood protection.
Note that the two approaches are not expected to produce the same estimate.
The replacement cost method cannot be applied since flood protection services cannot
be directly replaced.
The substitute cost method can be applied since a substitute for the affected services
such as a retaining wall or a levee might be built to protect nearby properties from
flooding. In this case, estimate the cost of building and maintaining such a wall or levee.
Also determine whether people would be willing to accept the wall or levee in place of a
restored wetland.
Step 3
Compare the cost of the property damages avoided, or of providing substitute flood
protection services to the restoration costs to determine whether it is worthwhile to
restore the flood protection services of the wetlands.
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6.4 Illustration 2: Soil Erosion in Korea using the replacement cost method
Urban growth and industrial development in Korea caused farming activities to move
into hilly upland area. Inadequate soil management techniques and errors in field layout
and construction resulted in soil erosion of these upland areas. It is required to evaluate
the benefits of proposed new soil management techniques, including retaining the soil
and nutrients on the upland areas and protecting downslope areas from damage by the
eroded soil.
The researchers measured the cost of physically replacing lost soil, nutrients, and water
in upland areas and the cost of compensating for downstream losses by:
− calculating the annual soil loss per hectare, nutrient loss/hectare, and water
runoff/hectare (Table 5)
− calculating the expected losses, in terms of replacement costs, if the new
management practices were not implemented. The net present value of the losses
amounted to W 2,039,662, using a 15 year time horizon.
Table 5. Cost of replacement activities
Measured parameter Cost (W/ha/yr)
Recovering and replacing eroded soil 80,000
Fertilizer and spreading to replace lost nutrients 31,200
Annual field maintenance and repair 35,000
Damage to downstream fields in lost production 30,000
Supplemental irrigation to replace lost water 92,000
Total cost of soil erosion under existing management 268,200
Net present value using a 15 year time horizon 2,039,662
Then calculate the costs with the new management techniques, including compensation
payments, soil replacement, nutrient replacement, and mulching. The net present value
of the costs of new management techniques was estimated at W 1,076,742.
The cost of new management techniques (W 1,076,742) is about half the replacement
cost (W 2,039,662). Thus, the proposed preventive steps are worth implementing.
6.5 Illustration 3: Oil spill damage in Puerto Rico (replacement cost method)
The Zoe Colocotroni was a ship that spilled oil off the coast of Puerto Rico. The case was
taken to court to determine the monetary damages resulting from the spill’s effects on
the local ecosystem. The replacement cost method was used to estimate monetary
36
damages. This was done by calculating the number of lower trophic organisms killed by
the spill and adding up the cost of purchasing these organisms from a scientific
catalogue. However, the US Court of Appeals rejected the use of the replacement cost
method in this case, as it was not planned to actually purchase the organisms and
restore them to the ocean. By the time such a plan could have been carried out, the
organisms would have restored themselves. Thus the costs of purchasing the organisms
did not accurately measure the actual ecosystem damages.
THE TRAVEL COST METHOD
Session 5
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SESSION 5
7 THE TRAVEL COST METHOD
The travel cost method (TCM) is used to estimate use values associated with ecosystems
or sites that are used for recreation. The concept of using travel costs to value recreation
was first proposed by Hotelling in 1949 and formalised by Clawson (1959). This concept
assumes that the value of the site or its recreational services is reflected in how much
people are willing to pay to get there. This method is useful in planning for the provision
and management of outdoor recreation, such as changes in access costs for a
recreational site, elimination of an existing recreational site, addition of a new
recreational site, and changes in environmental quality at a recreational site.
7.1 Theory
The travel cost method is based on the premises that the cost an individual incurs in
visiting a site reflects his valuation to the site, and that individuals will react to an
increase in entry fees the same way as they would react to an increase in travel cost.
That is, at some high level of entry fee or travel cost, no one would visit the site. By
asking visitors questions relating to where they had travelled from and the costs they
had incurred, and relating this information to the number of visits they make per year, a
trip generation function can be generated for the recreational site under question. An
aggregate demand curve is then derived for visits to the sites per year. The demand
curve shows how many visits people would make at various travel cost prices and is thus
used to estimate the willingness to pay for people to visit the site. The curve is
downward sloping, where the travel cost is inversely related to the number of visits.
That is, people who live farther from the site will visit it less often, because it costs more
in terms of actual travel costs and time to reach the site. Other factors that might affect
the number of visitors to the site include a visitor’s income, the availability of alternative
sites or substitutes, ad factors like personal interest in the type of site, or level of
recreational experience.
Travel cost models can assume a linear functional form or a log‐linear functional form.
Figure 21 illustrates the linear functional form.
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Figure 21. Linear demand curve
V = α + βC +γS Where: V = number of visits to a site
α = constant β = coefficient of C, usually negative C = cost of travel to gain access to site
γ = coefficient of S, probably negative S = cost of travel to gain access to the respondent’s preferred substitute site
The travel cost model is used to estimate α, β, and γ. The estimated consumer surplus
(CS) for an individual making q visits to the site is as follows:
CS = ‐q2 / 2β
Note that this functional form implies finite visits at zero costs and it has a critical cost
above which negative visits will be demanded.
The Log‐Linear functional form is illustrated in Figure 22.
Figure 22. Log‐linear demand curve
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lnV = α + βC +γS
Where: V = number of visits to a site
α = constant β = coefficient of C, usually negative C = cost of travel to gain access to site
γ = coefficient of S, probably negative S = cost of travel to gain access to the respondent’s preferred substitute site
The travel cost model is used to estimate α, β, and γ. The estimated consumer surplus
(CS) for an individual making q visits to the site is as follows:
CS = ‐q / β
This functional form has been widely used in TCM models. It implies a finite number of
visits at zero cost, and it never predicts negative visits even at very high costs.
7.2 Forms of TCMs
There are three forms of TCMs: the zonal TCM, the individual TCM, and the random
utility approach.
7.2.1 Zonal TCM approach
In the Zonal TCM approach, concentric zones are defined around each site such that the
cost of travel from all points in a given zone is approximately constant (Figure 23).
Visitors to the site are grouped according to their zone of origin. This approach is the
simplest and least expensive. It can rely on secondary data and it is suitable when
visitors’ origins are relatively evenly distributed and it is unsuitable for linear
recreational sites.
Figure 23. Concentric zones around site S
Steps to apply the Zonal TCM:
1. Identify the site and collect data from visitors on their points of origin, number of
visits from each origin zone, round‐trip mileage from each zone, travel costs per
mile, and demographic information about people from each zone.
2. Define zones of origin and allocate visitors to the appropriate zone. Zones are
commonly defined based on the straight line distance from the site. Geographic
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Information system (GIS) techniques allow redefining zones based on road distances
or travel times.
3. Calculate zonal visits per household to the site by estimating the number of
households per zone and dividing the number of household visits originating in the
zone by the total number of households in the zone.
4. Calculate the average travel cost from each zone to the site.
5. Use census data to derive variables relating to zonal socio‐economic characteristics.
6. Use data collected above to estimate the trip generation function:
Vh/Nh = f(Ch,Xh,Sh)
where: Vh = # of visits from zone h
Nh = population of zone h
Ch = travel cost from zone h
Xh = a vector of socio‐economic variables that explain changes in V
Sh = a vector of substitute recreational site characteristics for residents of zone h
7. Derive the demand curve
8. Obtain zonal household consumer surplus estimates through integrating under the
demand curve
9. Calculate aggregate zonal consumer surplus by multiplying consumer surplus per
household by the number of households in each zone
10. Aggregate zonal consumer surplus estimates to obtain an estimate of total consumer
surplus or the benefits of the site
7.2.2 Individual TCM methodology
The Individual TCM uses the number of visits made per year by an individual, rather than
the zonal visits, as the basis for generating the demand curve. This method requires
more data collection, as compared to the zonal TCM, and slightly more complicated
analysis. Yet, it is more flexible. It is applicable at a wider range of sites, and it gives
more precise and statistically efficient results.
Steps in applying the Individual TCM:
1. Identify the site.
2. Use an on‐site questionnaire survey to collect data from visitors relating to the cost
of travel to the site, the number of visits to the sites, recreational preferences, and
socio‐economic characteristics.
3. Specify the trip‐generation function:
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Vij = f(Cij,Tij,Qi,Sj, Yi)
where: Vi = # of visits made by individual i to site j
Cij = travel cost incurred by individual i when visiting site j
Qj = a vector of perceived qualities of the recreation site j
Sj = a vector of available substitute recreational site characteristics
Yi = household income of individual i
4. Estimate the travel cost model taking truncation into account for non‐visitors
behavior
5. Derive demand curve and obtain household consumer surplus estimates through
integrating under the demand curve
6. Calculate aggregate consumer surplus for the site
Note that more complicated and thorough applications of the individual TCM may also
collect information about:
− exact distance that each individual travelled to the site
− exact travel expenses
− the length of the trip
− the amount of time spent at the site
− other locations visited during the same trip, and amount of time spent at each
− substitute sites that the person might visit instead of this site, and the travel distance
to each
− other reasons for the trip (is the trip only to visit the site, or for several purposes)
− quality of the recreational experience at the site, and at other similar sites (e.g.,
fishing success)
− perceptions of environmental quality at the site
− characteristics of the site and other, substitute, sites
7.2.3 The random utility approach
This approach allows for much more flexibility in calculating benefits, yet it is the most
complicated and expensive. It is best suited to estimate benefits for specific
characteristics of sites, rather than for the site as a whole, and it is most appropriate
when there are many substitute sites. The random utility approach focuses attention on
the choice among alternative sites for any given recreational trip and assumes the visitor
is comparing utilities for available destinations. It first models the individual’s decision
on whether or not to participate in recreational activity, and then models the decision
on the number of visits. Models used include probit, tobit, and logit.
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7.3 Advantages and limitations of TCMs
Advantages of the TCM include the following:
− It is based on real data rather than stated willingness to pay and as such provides
true values
− It is relatively inexpensive to apply
− On‐site surveys provide opportunities for large sample sizes, as visitors tend to be
interested in participating
− The results are relatively easy to interpret and explain
However, the TCM is associated with various issues and limitations that should be taken
into consideration, including the following:
− The method assumes that people perceive and respond to changes in travel costs
the same way that they would respond to changes in admission price.
− The simplest models assume that individuals take a trip for the single purpose of
visiting a specific recreational site. Thus, if a trip has more than one purpose, the
value of the site may be overestimated.
− Defining and measuring the opportunity cost of time, or the value of time spent
travelling, can be problematic. There is no consensus on how to account for time,
whereby travel time may be a benefit if people enjoy the travel itself, leading to an
overestimation of the value of the site.
− The availability of substitute sites will affect values. For example, if two people travel
the same distance, they are assumed to have the same value. However, if one
person has several substitutes available but travels to this site because it is
preferred, this person’s value is actually higher. Some of the more complicated
models account for the availability of substitutes.
− The assumption that travel costs reflect recreational value may not always be true.
Those who value certain sites may choose to live nearby, resulting in low travel
costs, but high values for the site.
− Visits to certain sites could be seasonal and thus survey results could be biased
unless survey is conducted for a long period.
− Interviewing visitors on site can introduce sampling biases to the analysis.
− Measuring recreational quality and relating it to environmental quality can be
difficult.
− Standard travel cost approaches provides information about current conditions, but
not about gains or losses from anticipated changes in resource conditions.
− The demand function requires enough difference between distances travelled to
affect travel costs and for differences in travel costs to affect the number of trips
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made. Thus, the TCM is not well suited for sites near major population centres
where many visitations may be from "origin zones" that are close to one another.
− The travel cost method is limited in its scope of application because it requires user
participation. Thus, it cannot be used to assign values to on‐site environmental
features and functions that users of the site do not find valuable. It cannot be used
to value off‐site values supported by the site, or to measure non‐use values. It
excludes non‐users who may have significant values for the site
− Certain statistical problems can affect the results, including, choice of the functional
form used to estimate the demand curve, choice of the estimating method, and
choice of variables included in the model
7.4 Illustration‐ Recreational fishing site
A site used mainly for recreational fishing is threatened by development in the
surrounding area. Pollution and other impacts from this development could destroy the
fish habitat at the site, resulting in a serious decline in, or total loss of, the site’s ability
to provide recreational fishing services. Resource agency staff wants to determine the
value of programs or actions to protect fish habitat at the site.
The TCM was selected because the site is primarily valuable to people as a recreational
site. In addition, this site has no endangered species or other highly unique qualities that
would make non‐use values for the site significant. Furthermore, the expenditures for
projects to protect the site are relatively low. Alternative approaches, including the
contingent valuation or contingent choice methods, might produce more precise
estimates of values for specific characteristics of the site and could capture non‐use
values. However, they are considerably more complicated and expensive to apply.
7.4.1 Application of the Zonal Travel Cost Approach
Step 1
Define a set of zones surrounding the site by concentric circles around the site, or by
geographic divisions such as metropolitan areas or counties surrounding the site at
different distances.
Step 2
Collect information on the number of visitors from each zone and the number of visits
made in the last year. For this example, assume that the staff at the site keeps records of
the number of visitors and their zip code, which can be used to calculate total visits per
zone over the last year.
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Step 3
Calculate the visitation rates per 1,000 population in each zone, which is the total visits
per year from the zone, divided by the zone’s population in thousands (Table 6).
Table 6. Visitation rates for the site
Zone Total Visits/Year Zone Population Visits/1000
0 400 1,000 400
1 400 2,000 200
2 400 4,000 100
3 400 8,000 50
Beyond 3 0
Total visits 1,600
Step 4
Calculate the average round‐trip travel distance and travel time to the site for each
zone. Using average cost per mile and per hour of travel time, calculate the travel cost
per trip, by assuming that this cost per mile is USD 0.30. The cost of time is calculated
using the simplest approach involving the average hourly wage. It is assumed that the
average hourly wage is 9 USD/hour or $0.15 USD/minute for all zones; although in
practice it is likely to differ by zone (Table 7).
Table 7. Travel cost calculation
Zone Round Trip Travel Distance
Round Trip Travel Time
Distance × Cost/mile ($.30)
Travel Time × Cost/minute ($.15)
Total Travel (Cost/Trip)
0 0 0 0 0 0
1 20 30 $6 $4.50 $10.50
2 40 60 $12 $9.00 $21.00
3 80 120 $24 $18.00 $42.00
Step 5
Estimate the trip generation function using regression analysis. This allows the
estimation of the demand function for the average visitor. The analysis might include
demographic variables, such as age, income, gender, and education levels, using the
average values for each zone. To maintain the simplest possible model, calculating the
equation with only the travel cost and visits/1000:
Visits/1000 = 330 – 7.755 * Travel Cost
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Step 6
Construct the demand function for visits to the site. The first point on the demand curve
is the total visitors to the site at current access costs, or 1,600 visits per year. The other
points are found by estimating the number of visitors with different hypothetical
entrance fees. For example, start by assuming a $10 entrance fee, plugging this into the
estimated regression equation, V = 330 – 7.755C, gives the data in Table 8.
Table 8. Deriving the demand curve
Zone Travel Cost plus $10
Visits/1000 Population Total Visits
0 $10 252 1,000 252
1 $20.50 171 2,000 342
2 $31.00 90 4,000 360
3 $52.00 0 8,000 0
Total Visits 954
This gives the second point on the demand curve: 954 visits at an entry fee of $10. In the
same way, the number of visits for increasing entry fees can be calculated (Table 9).
These points give the demand curve for trips to the site (Figure 24).
Table 9. Number of visits for increasing entry fees
Entry Fee Total Visits
$20 409
$30 129
$40 20
$50 0
0
10
20
30
40
50
60
0 400 800 1200 1600 2000
Total visits
Adde
d co
st p
er tr
ip
Figure 24. Demand curve for the trips to the site
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Step 7
Estimate the total economic benefit of the site to visitors by calculating the consumer
surplus, or the area under the demand curve. The total estimate of economic benefits
from recreational uses of the site is around $23,000 per year, or around $14.38 per visit.
Thus, if the actions to protect the site cost less than $23,000 per year, the cost will be
less than the benefits provided by the site. If the costs are greater than this, the staff will
have to decide whether other factors make them worthwhile.
7.4.2 Application of the Individual Travel Cost Approach
Step 1
Conduct a survey of visitors on:
− location of the visitor’s home –distance travelled to the site
− how many times they visited the site in the past year or season
− the length of the trip
− the amount of time spent at the site
− travel expenses
− the person’s income or other information on the value of their time
− other socioeconomic characteristics of the visitor
− other locations visited during the same trip, and amount of time spent at each
− other reasons for the trip (is the trip only to visit the site, or for several purposes)
− fishing success at the site (how many fish caught on each trip)
− perceptions of environmental quality or quality of fishing at the site
− substitute sites that the person might visit instead of this site
Step 2
Estimate the relationship between number of visits and travel costs and other relevant
variables using regression analysis. Use individual data rather than data for each zone.
The regression equation gives the demand function for the “average” visitor to the site
and the area below this demand curve gives the average consumer surplus.
Step 3
Multiply the average consumer surplus by the total relevant population in the region
where visitors come from to estimate the total consumer surplus for the site.
Step 4
Value estimates can be improved by adding other factors to the statistical model,
including additional data about visitors, substitute sites, and quality of the site. Including
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information about the quality of the site allows the researcher to estimate the change in
value of the site if its quality changes. In this case, two different demand curves would
be estimated; one for each level of quality. The area between these two curves is the
estimate of the change in consumer surplus when quality changes
7.4.3 Application of the Random Utility Approach
The agency might want to value the economic losses from a decrease in fish
populations, rather than from loss of the entire fish stock. The random utility approach
focuses on choices among alternative sites which have different quality characteristics. It
assumes that individuals will pick the site that they prefer, out of all possible fishing
sites. This model requires information on all possible sites that a visitor might select,
their quality characteristics, and the travel costs to each site.
Step 1
Conduct a telephone survey of randomly selected residents of the state, asking residents
if they go fishing or not. If they do, then ask a series of questions: how many fishing trips
they took over the last year (or season), where they went, the distance to each site, and
other information similar to the information collected in the individual travel cost
survey. One might also ask questions about fish species targeted on each trip, and how
many fish were caught.
Step 2
Estimate a statistical model that can predict the choice to go fishing or not and the
factors that determine which site is selected. If quality characteristics of sites are
included, the model can estimate values for changes in site quality, for example the
economic losses caused by a decrease in catch rates at the site.
7.5 Case application‐ Hell Canyon preservation
The following is a case application of the Travel Cost Method as part of the efforts to
preserve the.
The Hell Canyon is situated on the Snake River separating Oregon and Idaho. It offers
spectacular vistas and outdoor amenities to visitors and supports important fish and
wildlife habitat. It also has economic potential as a site to develop hydropower. Yet,
generating hydropower there would require building a dam. The dam and resulting lake
would significantly and permanently alter the ecological and aesthetic characteristics of
Hell Canyon. During the 1970’s, there were controversies regarding the future of Hell
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Canyon. Thus, environmental economists were asked to develop an economic analysis
justifying the preservation of Hell Canyon in its natural state.
Accordingly, the net economic value (cost savings) of producing hydropower at Hell
Canyon was $80,000 higher than at the "next best" site which was not environmentally
sensitive. The recreational value of Hell Canyon was estimated via a low‐cost/low
precision travel‐cost survey at about $900,000. Even if the "true value" of recreation at
Hell Canyon was ten times less than their estimate, it would still be greater than the
$80,000 economic payoff from generating power there as opposed to the other site.
Congress voted to prohibit further development of Hell Canyon, based largely on the
results of this non‐market valuation study.
7.6 Case‐study: The value of forestry in Britain
The travel cost method was used to estimate the total recreational value of Forestry
Commission Woodland in Great Britain, by Willis. In order to do this it was first
necessary to define some representative forest types. Using a statistical technique called
cluster analysis, 14 similar groups of forests were identified and travel cost studies were
undertaken of sample forests from each of these groups. Interviews were undertaken
with visitors in 15 forests. Visitors to sites were allocated into 20 concentric distance
zones, at five‐mile intervals. Those from further away were allocated together into a
single further zone. Willis then estimated relationships between the visit rate from each
zone and the transport costs, taking account of the socio‐economic characteristics of the
zones.
These relationships, referred to as trip generating functions, were then used in order to
estimate the consumer surplus, or the total value of each visit, represented by the
maximum willingness to pay, less the cost of each trip. Summing across all visitors to
each site produced estimates of the total value for each site. Some of the results are
shown in Table 10. This shows the estimated consumer surplus per visit, the consumer
surplus per hectare of forest at the survey site, the total annual number of visitors at all
of the forests within this group of forests and the total consumer surplus generated by
this group of forests.
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Table 10. Consumer surplus estimates for non‐priced recreation for forest districts
Forest Consumer surplus per recreational
visitor (£)
Consumer surplus per hectare of
forest (£/ha)
Annual number of visitors to the cluster of forests (1000s)
Total consumer surplus (£million)
New Forest 1.43 425 8,000 11,440
Loch Awe 3.31 <1 34 0.114
Brecon 2.26 27 2,117 4.784
South Lakes 1.34 31 1,968 2.637
Thetford 2.66 14 4,742 10.718
By summing all of the estimates of consumer surplus, it is possible to obtain an estimate
of the value of non‐priced recreation for Forestry Commission forests as a whole. This
gives a figure of £53 million. This compares with a figure of £71 million income to
Forestry Enterprise, the timber production arm of the Forestry Commission, from the
sale of timber 1988. In this year, there was an annual net subsidy of £8.5 million paid on
forestry recreation and amenity. This amount represents a net cost to the Forestry
Commission of providing facilities, such as visitor centers, forest walks, wildlife
conservation and amenity tree planting. The figures indicated the importance of
recreation in the role of the Forestry Commission and suggested that its provision for
non‐priced recreation represents good value.
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THE HEDONIC PRICING METHOD
&
THE AVERTING BEHAVIOR METHOD
Session 6
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SESSION 6
8 THE HEDONIC PRICING METHOD
The Hedonic Pricing Method (HPM) is used to estimate the value or price of an
environmental feature by looking at actual markets where the attributes are traded. It is
most commonly applied in relation to the public’s willingness to pay for housing/
property and in labour markets for health economic valuation.
8.1 Theory
The HPM is based on the assumption that people value the characteristics of a good, or
the services it provides, rather than the good itself. Thus, prices will reflect the value of a
set of characteristics, including environmental characteristics that people consider
important when purchasing the good. For example, the price of a car reflects the
characteristics of that car, in terms of transportation, comfort, style, luxury, fuel
economy, etc. One can value the individual characteristics of a car or other good by
looking at how the price people are willing to pay for it changes when the characteristics
change.
The HPM assumes that the price of a product is a function of its characteristics; the
range of product choices is continuous; the choice is based on perfect information and
with no mobility restrictions; and the amount of a particular characteristic can be varied
independently.
The HPM is relatively straightforward and uncontroversial to apply, because it is based
on actual market prices and fairly easily measured data. If data are readily available, it
can be relatively inexpensive to apply. However, if data must be gathered and compiled,
cost can increase substantially.
The HPM is usually applied ex post, to examine the effects of developments and policies
after implementation. It can be used to estimate economic benefits or costs associated
with:
− Environmental risk. For example, the effect of information of different levels of
earthquake damage on property values
− Environmental quality, including water pollution, such as the impact on waterfront
property; air pollution; noise, such as the impact of highway noise and aircraft noise;
soil quality and erosion
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− Environmental amenities, such as aesthetic views, proximity to recreational sites,
hazardous sites, waste management sites, etc.
The hedonic technique may also be applied to wage rates. It is based on the assumption
that an individual choice of job may be influenced by the job location if it improves
access to desirable services. The main issue with this technique is high unemployment,
where individuals cannot satisfy their demand for environmental improvement due to
unavailability of suitable jobs in areas of higher environmental quality.
8.2 Applying the Hedonic Pricing Method using housing prices
The price of a house is related to the structural characteristics of the house (plot size,
number of rooms, garage space, structural integrity, etc.), local socio‐economic and
public sector characteristics (unemployment rate, social conditions, quality of schools,
etc.) and local amenity (environmental quality, access to services, communications, etc.).
Upon controlling for non‐environmental factors, any remaining differences in price can
be attributed to differences in environmental quality. For example, if all characteristics
of houses and neighbourhoods in a given area were the same, except for the level of air
pollution, then houses with better air quality would cost more. This higher price reflects
the value of cleaner air to people who purchase houses in the area.
Step 1
Collect the needed information. Data requirements fall into two broad categories:
− Specific data: cross‐section and/or time‐series data on property values and property
and household characteristics for a well‐defined market area including, structural
and locational information, and details of purchase or tenancy (price, date, personal
and financial particulars of the purchasers).
− Local data: pertaining to the area where transaction occurred including,
neighbourhood, amenity, environmental, and socio‐economic factors, and a
measure or index of the environmental amenity of interest.
Sources of data depend on country/ state involved. These may include government
agencies, estate agents and realtors, mortgage granting institutions, GIS, postcode
classification of neighbourhood types, etc.
Step 2
Analyze the data using regression analysis, relating the price of the property to its
characteristics and the environmental characteristics of interest. The analysis will
indicate how much property values will change for a small change in each characteristic,
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holding all other characteristics constant. This analysis may be complicated by a number
of factors. For example, the relationship between price and characteristics of the
property may not be linear, whereby prices may increase at an increasing or decreasing
rate when characteristics change. Another factor is multicollinearity, where many of the
variables are likely to be correlated, so that their values change in similar ways. This can
lead to understating the significance of some variables in the analysis.
Different functional forms and model specifications for the analysis must be considered.
Restrictive functional forms include: linear, semi‐log, log‐linear, and linear Box‐Cox.
These involve simple and transparent relationships between variables. Other more
flexible functional forms may also be used.
8.3 Advantages and limitations
The advantages of the HPM include:
− It can be used to estimate values based on actual behaviour and choices.
− Property markets are relatively efficient in responding to information, so can be
good indications of value.
− Property records are typically very reliable.
− Data on property sales and characteristics are readily available through many
sources, and can be related to other secondary data sources to obtain descriptive
variables for the analysis.
− It is a versatile method that can be adapted to consider several possible interactions
between market goods and environmental quality.
The issues and limitations that are associated with the HPM include:
− The scope of environmental benefits that can be measured is limited to things that
are related to property values.
− It will only capture people’s willingness to pay for perceived differences in
environmental attributes, and their direct consequences. Thus, if people aren’t
aware of the linkages between the environmental attribute and benefits to them or
their property, the value will not be reflected in home prices.
− It assumes that people are free to select the combination of characteristics satisfying
their preferences, given their income. However, the housing market may be affected
by outside influences, like taxes, interest rates, or other factors.
− It is relatively complex to implement and interpret, requiring a high degree of
statistical expertise.
− The results depend heavily on model specifications.
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− It is susceptible to multicollinearity i.e. a high degree of correlation among the
variables under study which makes it difficult to estimate their individual effect. For
example, air pollution measures where the levels of one form of pollution (PM) is
closely related to levels of another (NO2)
− Large amounts of data must be gathered and manipulated.
− The time and expense to carry out an application depends on the availability and
accessibility of data.
8.4 Illustration‐ Open space preservation program
Agency staff wants to measure the benefits of an open space preservation program in a
region where open land is rapidly being developed. The Hedonic Pricing Method is used
because housing prices in the area appear to be related to proximity to open space, and
because data on real estate transactions and open space parcels are readily available.
Alternative approaches include the travel cost method, if the open space of concern is
used mainly for recreation. Survey‐based methods, like contingent valuation or
contingent choice may be used, but these are more difficult and expensive to apply.
Step 1
Collect and compile data on residential property sales in the region for a specific time
period including
− Selling prices and locations of residential properties
− Structural characteristics (lot size, number and size of rooms, number of bathrooms)
− Local socio‐economic characteristics
− Local amenity including the environmental characteristic of concern‐ the proximity
to open space
Collect data on the amount and type of open space within a given radius of each
property, noting the direct proximity of a property to open space. Data may be obtained
from computer‐based GIS maps.
Step 2
Statistically estimate a function that relates property values to the property
characteristics, including the distance to open space. The resulting function measures
the portion of the property price that is attributable to each characteristic. Estimate the
value of preserving open space by looking at how the value of the average home
changes when the amount of open space nearby changes
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Step 3
Evaluate agency investments in open space preservation and determine the benefits of
preserving each parcel, which can then be compared to the cost
8.5 Case Study 1: Values of Environmental Amenities in Marickville and Rockdale,
Sydney
An early study of hedonic prices was undertaken in two municipalities in Sydney,
Marrickville and Rockdale by Peter Abelson. Data were collected from house sales in
these areas in 1972 and 1973, giving a total sample of 1,414 observations. Information
was included on about twenty characteristics of each property and its local
environment. These included the size, age and construction of the house, the size of the
plot of land, the type and amount of traffic on the road outside the house, access to
public transport and shops, aircraft noise, zoning and whether there were any plans for
road widening. Some of these variables could be measured directly, such as the number
of rooms. Some were measured on a subjective scale. For example, road traffic levels
were described on a three point scale (noisy, normal and quiet). For a third group of
variables it was only possible to define whether or not an item was present, such as
whether or not the house had a double garage.
Various different types of statistical relationships between house prices and
characteristics were tested. These were able to explain about two thirds of the variation
in house prices. The major determinants of house prices were found to be house quality
and size and plot size. Aircraft noise was found to be a significant determinant of house
prices in Marrickville. The results indicated that the price of a very noisy house would be
about $1,250 less than that of a quiet house. For higher priced houses in Rockdale the
difference was about $3250. The price difference between a house on a noisy road in
Marrickville and one on a quiet road was about $1,400 or 5.6 per cent of the house
price. The value of a good view (assessed subjectively) in Rockdale was valued at about
$440 compared with an average view, which in turn was worth $440 more than a poor
view.
Abelson recognizes the limitations of his analysis. There were difficulties in measuring
several of the housing attributes. The hedonic prices which were estimated may not
represent the willingness to pay for amenities because buyers may not have been well
informed when making decisions about house purchase or the housing market may not
have been in equilibrium, i.e. residents may not have been able to select the houses and
characteristics which would best meet their preferences. Abelson did not undertake the
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second stage to the analysis, so that the estimates may only relate to small changes in
environmental characteristics.
8.6 Case‐study 2: Quarries in Mount Lebanon
Quarries can cause various environmental impacts, including destruction of natural
vegetation and habitats, air pollution from dust, and a reduction in aesthetic value in
and around such localities. There are more than 700 quarries in Lebanon, of which more
than half are in Mount Lebanon province. Many of the quarries are abandoned with
minimal or no rehabilitation and many have been established with little consideration
for the environment and surrounding human settlements. While it would be a significant
undertaking to assess the damage cost of all the quarries, the impact of four quarries on
surrounding settlements in Mount Lebanon was assessed in this study.
8.6.1 The methodology
The cost of degradation due to quarrying was estimated by measuring the loss in land
and apartment values associated with a reduction in aesthetic value. A survey of impacts
on surrounding areas around four quarries in Mount Lebanon (Shnanaayer, Abou‐Mizan,
Antelias, and Nahr Ibrahim) was conducted. Additional impacts recorded to occur during
quarries operation include, structural damage to buildings and infrastructures from
explosives used, dust pollution, and traffic congestion due to quarry transport activities.
These impacts represent a fraction of the losses in land and apartment values and were
not included in this assessment.
The degradation cost associated with the surveyed quarries cannot be extrapolated to
the other quarries in Lebanon (>700), due to differentials in property prices and
locations
Step 1: Estimate the loss in land value around surveyed quarries
First, determine the area of land affected. Then, multiply the area of land by the decline
in land price, based on information from municipality officials and real estate agents
(Table 11). Note that the area around Nahr Ibrahim quarry experienced a reduction in
land prices during quarry operation due to traffic congestion and dust. However, after
quarry closure land prices were no longer affected anymore (contrary to other quarries).
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Table 11. Calculation of loss in land prices due to quarrying
Quarry Areas affected Land area affected (m2)
Decline in land price
(US $/m2)
Loss in land value
(US $ million)
Shnanaayer Shnanaayer municipality 600,000 125 75.0
Abou‐Mizan Shirine, Bteghrine, and other villages
175,000 7.5 1.3
Antelias Raboueh and Qornet Chehouane municipality
100,000 50 5.0
Total 875,000 93 81.3
Annualized loss (“low”)* 8.1
Annualized loss (“High”)* 9.6
Step 2: Estimate the loss in apartment values around surveyed quarries
First, determine the number of apartments affected and their surface areas. Then,
multiply the estimated are by the decline in apartment price, based on information from
municipality officials and real estate agents. Only the quarries in Shnanaayer and
Antelias are overlooked by residential buildings (Table 12).
Table 12. Calculation of loss in apartment prices due to quarrying
Quarry Areas affected Apartments affected (m2)
Decline in apartment
price (US $/m2)
Loss in apartment value(US $ million)
Shnanaayer Shnanaayer municipality 36,000 225 8.1
Antelias Raboueh and Qornet Chehouane municipality
8,000 100 0.8
Total 44,000 202 8.9
Annualized loss (“low”)* 0.9
Annualized loss (“High”)* 1.0
Step 3: Estimate land value occupied by other quarries (not surveyed)
Caution is warranted before extrapolating costs to other quarries in Lebanon due to
differentials in property prices and location. As a conservative estimate, the cost of
degradation associated with the more than 700 other quarries is calculated as the value
of the land that the quarries occupy. Estimated land value ranges between 3 and 5
US$/m2. Average size of quarry ranges between 15,000 and 20,000 m2 (Table 13).
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Table 13. Calculation of land value occupied by quarries
Lower bound Higher bound
Number of quarries 710
Average area of quarry (m2) 15,000 20,000
Average land value (US $/m2) 3 5
Total land value (US $ million) 207.6 415.3
Annualized loss (US $ million/year)* 5.0 5.9
Percent of GDP (%) 0.03 0.04
Total losses in land value were annualized at a discount rate f 10% over 20 to 100 years (high and low estimates)
Step 4: Assess the total cost of degradation due to quarries
The total cost of degradation due to quarries is assessed by summing up the loss in land
value around surveyed quarries, the loss in apartment value around surveyed quarries,
and the annual land value occupied by all quarries (Table 14). Accordingly, the average
total annual degradation cost due to quarries in Lebanon is 15.25 USD million or 0.10
percent of the GDP.
Table 14. Calculation of the total cost of degradation due to quarries
Parameter Lower bound
Higher bound
Loss in land value around surveyed quarries (US $ million) 8.1 9.6
Loss in apartment value around surveyed quarries (US $ million) 0.9 1.0
Annual land value occupied by all quarries (US $ million) 5.0 5.9
Total loss (US $ million) 14.0 16.5
Percent of GDP (%) 0.08 0.10
This is estimated at USD 48 million. As an annual damage cost, this corresponds to USD
5‐6 million per year. In total, the annual damage cost of quarries is conservatively
estimated at USD 14‐16 million, or about 0.1 percent of GDP.
9 THE AVERTING BEHAVIOR METHOD
Actions are taken to reduce or avoid the consequences and costs of environmental
damage. The costs incurred due to these actions are considered equivalent to the costs
of environmental degradation. Averting behaviors may include, drinking bottled water
or purchasing water filters due to polluted water, frequent painting of dwellings due to
59
smoke emissions from a nearby factory, moving away from a polluted location, installing
air purifiers, staying indoors, installing soundproof walling to reduce noise, etc. In many
cases, several types of aversive expenditures are undertaken simultaneously. For
example, possible action in response to a noisy road may include installing double
glazing and moving to another area. Thus the total benefits are estimated by summing
up all expenditures.
The application of this technique differs with the type of pollution and the aversive
behavior adopted. A general methodology includes:
Step 1‐ Identification of the environmental hazard and the affected population
Monitoring equipment may be used to measure variables indicative of the
environmental hazard. Common sense should be adopted in defining the population at
risk.
Step 2‐ Observation of the responses of individuals
Survey design should avoid biased sample, strategic bias, and self‐selection. Public
expenditures should be indentified and included with the Willingness to Pay (WTP)
estimation.
Step 3‐ Measurement of the cost of taking action
One should understand why the individual is taking a certain action and if the chosen
course is enough to avoid the hazard.
Issues to consider when applying this methodology include:
− Some actions are difficult to monetize, such as moving house and leaving a familiar
neighborhood, thus the cost of the action is a minimum estimate.
− Some impacts have consequences with no possible averting actions, such as the
impact of air pollution on reduced visibility or the impact of air pollution on lake
acidification. Hence the cost of the action is not accurate or complete.
− Some goods provide additional non‐environmental benefits, for example, bottled
water tastes better, or air conditioning ameliorates room temperature. This needs to
be accounted for to avoid overestimation of benefits.
− Some are only partial substitutes for the environment. For example, double glazing
partially reduces noise, this discomfort may still occur. This should be included in the
analysis.
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9.1 Case Study 1: The Cost of Pesticide Contamination of Drinking Water
Consider the cost of pesticide contamination of drinking water. Households may take a
variety of possible actions in order to reduce the risks faced by pollutants. Abdalla and
his colleagues have studied the responses of residents in Perkasie, a small town in
Pennsylvania, USA, to the chemical contamination of water supplies. In late 1987,
Trichloroethylene (TCE) was detected in well supplying water to the area. Levels of TCE
were as high as 35 parts per billion, well in excess of the Environmental Protection
Agency's limit 5 parts per billion. As there were no means of reducing the
contamination, water consumers were notified of the contamination in June 1988. No
solution had been implemented as of December 1989. A postal survey was undertaken
in September 1989 of a sample of 1,733 households in the town. Replies were received
from 761 respondents, a response rate of about 45 per cent. The questionnaire asked
for information on actions taken to avoid exposure to the chemical. These included
increased purchases of bottled water by those who had previously purchased it,
purchases by those who had not purchased it before, installation of home water
treatment systems, bringing in water from other sources and boiling water. On the basis
of the responses received, the costs of the actions were estimated. Because the water
treatment systems would last for longer than the expected period of chemical
contamination, only a proportion of this cost was included. The results are shown in
Table 15. As there is no clear logic for choosing the value to attach to the time spent on
averting behavior, the table shows two possible approaches.
Table 15. Costs of averting actions undertaken
Actions undertaken Low estimatea (USD) High estimateb (USD)
Increased purchase of bottled water 11,135 11,135
New purchases of bottled water 17,342 17,342
Home water treatment systemsc 4,691 4,691
Hauling water 12,513 34,013
Boiling water 15,633 64,135
Total cost 61,313 133,334 a Time valued at minimum wage rate (3.35 USD/hr) b Time valued at estimated hourly wage c Because such a system would last for longer than the contamination period, a proportion of the cost was included
The results should be regarded as a minimum estimate of the costs of the chemical
contamination. It is notable that, despite the requirement that households should be
notified, only 43 per cent of respondents were aware of the presence of TCE in their
water. It must be assumed therefore that expenditure would have been higher had
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more people known about the contamination. It must also be assumed that the averting
behavior by households did not remove all consequences of the chemical
contamination. No allowance has been made for any possible ecological impacts which
may not have any impact on local consumers or which would not be affected by actions
taken within the home. The analysis does suggest that if the contamination could be
avoided for an expenditure of USD 60,000, this should be undertaken. However, this is
not to say that preventative measures should not be undertaken if they cost more than
this figure. The full costs of contamination may well by substantially higher than the
costs identified in this survey.
9.2 Case‐study 2: Consumption of Bottled Water in Lebanon
Lebanon’s population consumes a large quantity of bottled water mostly due to the
perception that municipal water is of a low quality. Water pollution and possible
contamination of municipal water in the distribution system has a cost to society.
According to the State of the Environment Report (SOER), bottled water expenditure
represent 0.60% of total per capita expenditure. The average price of one liter of bottled
water is 0.23 US$. Thus, bottled water consumption is about 115 liters per capita per
year (Table 16).
Table 16. Bottled water consumption in Lebanon
Parameter Unit Value
Per capita expenditures in Lebanon US$/capita/yr 4,465
Per capita bottled water expenditures in Lebanon % 0.60
Bottled water expenditure in Lebanon US$/capita/yr 26.8
Average price of bottled water in Lebanon US$/liter 0.23
Actual bottled water consumption in Lebanon Liter/capita/yr 115
Some consumption is due to taste and lifestyle preferences. This estimate is based on
bottled water consumption in Europe and the United States in the 1970s (prior to the
large increase in bottled water consumption in the 1980s and 1990s, widely believed to
be due to perceptions of inferior municipal water quality). The expected bottled water
consumption associated with preference is estimated in the Table 17. The expected
consumption is adjusted for GDP per capita differentials and price differentials between
several European countries (in the 1970) and Lebanon.
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Table 17. Estimate of expected bottled water consumption in Lebanon if consumers perceived no health risk of potable municipal water
Unit Value
GDP per capita 2000 (Western Europe and USA) US$/capita 17,253 ‐ 27,750
GDP per capita 2000 in Lebanon US$/capita 3,875
Bottled water consumption in several European countries in 1970’s
Liter/capita/yr 30
Income elasticity of bottled water demand 0.25 to 0.4
Price elasticity of bottled water demand (“low”) ‐1.5 to ‐1.5
Price elasticity of bottled water demand (“High”) ‐2 to ‐2
Average price of bottled water in European countries US$/liter 0.3 to ‐0.3
Average price of bottled water in Lebanon US$/liter 0.23
Expected bottled water consumption in Lebanon “Low” Liter/capita/yr 30 ‐ 24
Expected bottled water consumption in Lebanon “High” Liter/capita/yr 34 ‐ 27
The cost of municipal water of inferior quality (in terms of bottled water consumption) is
the difference between actual bottled water consumption and the estimated
consumption associated with taste and lifestyle preferences. The cost is estimated at
US$82 ‐89 million per year, or around 0.5 percent of GDP (Table 18).
Table 18. Estimation of bottled water consumption to protect against risk
Parameter Value
Low High
Actual bottled water consumption in Lebanon (Liter/capita/yr) 115 115
Expected bottled water consumption in Lebanon “Low” (Liter/capita/yr) 30 24
Expected bottled water consumption in Lebanon “High” (Liter/capita/yr) 34 27
Average expected bottled water consumption in Lebanon (Liter/capita/yr) 32 26
Bottled water consumption to protect against risk (Liter/capita/yr) 83 89
Lebanese population in 2000 (million capita) 4.2
Total bottled water consumption to protect against risk (million liter/yr) 356 383
Total cost of bottled water consumption to protect against risk (million US$/yr) 82 88
% GDP 0.49 0.53
THE REVEALED PREFERENCE APPROACH:
GROUP EXERCISES
Sessions 7 & 8
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SESSIONS 7 & 8
GROUP EXERCISES
The group exercise comprised of the following case‐studies: Ayubia National Park in Pakistan‐ The Travel Cost Method Himayatullah, 2003. Economic Valuation of the Environment and the Travel Cost Approach: The Case of
Ayubia National Park. The Pakistan Development Review 42: 4 Part II (Winter 2003) pp. 537–551 Non‐priced Forest Recreation Areas in Malaysia‐ The Travel Cost Method Garrod G. and Willis K.G. 2001. Economic Valuation of the Environment: Methods and Case Studies.
Edward Elgar Publishing, UK. Valuing Landscape and Amenity Attributes in Central England‐ Hedonic Pricing Garrod G. and Willis K.G. 2001. Economic Valuation of the Environment: Methods and Case Studies.
Edward Elgar Publishing, UK.
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THE CONTINGENT VALUATION METHOD
Session 9
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SESSION 9
10 THE CONTINGENT VALUATION METHOD
The Contingent Valuation Method (CVM) is the most widely used method for estimating
non‐use values. It is called “contingent” valuation, because it is contingent on simulating
a hypothetical market for the good in question. It involves directly asking individuals
how much they would be willing to pay (WTP) to preserve or use a given good or service
or the amount of compensation they would be willing to accept (WTA) to forgo specific
environmental services. The CVM can be used to estimate economic values for all kinds
of ecosystem and environmental services, for both use and non use values. The CVM has
been applied to estimate the values of landscape, recreation, beaches, water quality,
nature conservation, endangered species, visibility and air quality, etc. Yet, the CVM is
the most controversial of the non‐market valuation methods, whereby many
economists, psychologists and sociologists, for many different reasons, do not believe
that the dollar estimates that result from CV are valid. In addition, many jurists and
policy‐makers will not accept the results of CV. However, studies have shown that a
carefully composed and tested study, where the circumstances are not too distant from
the experience of the respondent and the issue is not too emotive, can produce answers
of value.
10.1 Steps in a CVM Procedure
10.1.1 Setting up the hypothetical market
This step involves devising a convincing contingent valuation scenario to demonstrate
that respondents are actually stating their values for these services when they answer
the valuation questions. A reason for the good or service needs to be established and
pictorial aids could be of use.
10.1.2 Obtaining bids Bids, or the people’s WTP values, are obtained through a questionnaire survey. Possible
bid vehicles include income taxes, property taxes, value added or sales tax, utility bills,
entry fees, and payments into a trust fund. Yet, not all bid vehicles are viable options in a
given situation. The chosen bid vehicle should have a plausible connection with the
valued amenity and should be perceived as fair and equitable. People have different
views on the acceptability of different types of taxes.
Focus groups should precede surveys. They provide insight on the respondents’ likely
understanding of and attitude towards the issue being investigated. They also provide
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valuable information in framing and designing a CV study and questionnaire survey.
Focus groups are usually drawn from a cross‐section of the population, stratified by
social class. Around 8 to 10 participants in a focus group meet for one to two hours to
discuss their understanding of the context of the good, the good itself, its value, who
should provide it, how it should be paid for, whether they should contribute, and how
much they are willing to pay. However, care should be taken when handling focus
groups due to many reasons. For instance, responses may be influenced by the person
conducting the focus group. In addition, focus group participants have a longer time to
think about the issue than in a typical CV survey and they have more information to base
their judgment on. Furthermore, individuals behave differently in group situations
compared to situations when they are alone.
As mentioned previously, bids are obtained through a questionnaire survey and an
elicitation format where respondents are asked to state their maximum WTP to increase
quantity/ prevent quantity decrease of an environmental good or their minimum WTA
compensation to forgo an increase in the quantity/ accept less of the good. Various bid
elicitation methods may be used including, bidding games, payment cards, open‐ended
questions, and close‐ended questions. Bidding games are when respondents are given
progressively higher bids until they reach their maximum WTP. The payment card
method involves providing a range of values to the respondent on a card, and asking him
to choose from them. In open‐ended questions, no value is specified, and respondents
are asked to report their maximum WTP. However, this method is not recommended as
respondents that have no prior experience in purchasing the good in question may find
it difficult to respond. Close‐ended questions can be asked under various formats. One is
the dichotomous choice referendum, where a single amount is offered and respondents
are asked to agree or disagree. In the double‐bounded referendum, respondents who
disagree are offered a lower amount and those who agree are offered a higher amount.
This method is highly recommended. In the trichotomous choice, respondents are
offered three choice: ‘yes’, ‘no’, and ‘indifferent’.
In the questionnaire survey, three sets of information are obtained from respondents
(Figure 25).
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Figure 25. Information obtained in questionnaire surveys
Note that data on use, preferences and substitutes should be collected at the beginning
of the questionnaire. Respondents must be reminded of their budget constraints when
eliciting their bids.
Questionnaires are administered in a number of ways, including face‐to‐face interviews,
self‐filled questionnaires, telephone interviews, and mail shots. Face‐to‐face
interviewing is the usual method adopted. It allows the definition and explanation of the
good more thoroughly and it minimizes non‐response. However, it is expensive to
conduct. Self‐fill questionnaires involve questionnaires left at recreation sites for visitors
or in public places. While this is a cheap data collection method, it can only be used with
questions that can be easily comprehended and it often yields a low response rate. Mail
shots are used where the hypothetical market is easily explained to respondents. This
method is most appropriate when respondents are widely scattered over space, and
when they have expert knowledge and interest in the good. Only questions that are
easily comprehended may be used in mail shots. Finally, telephone interviewing is often
faced with problems due to the absence of visual cues and due to the difficulty in
maintaining respondents’ attention. A combined telephone interview and mail shot is
usually recommended as it can be cost‐effective and it can increase the response rate.
The telephone secures the respondent’s interest and the mail follow‐up provides visual
and questionnaire material.
Deciding on a sample size for the questionnaire is a crucial step, as it determines the
precision of the sample statistics used as mean WTP/ WTA. The larger the sample, the
smaller the variation in mean WTP measured by standard error and confidence intervals.
Mitchell and Carson (1989) devised a system to determine sample size based on choice
of acceptable deviation between the ‘true’ and estimated WTPs. For a deviation of 5%,
95% of the time, a sample of 6,000 is needed; while for a deviation of 20%, 90% of the
time, a sample of 286 is needed Mitchell and Carson argue that a sample greater than
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600 is needed for applications seeking to evaluate policy. This ensures a deviation of
15%, 95% of the time.
10.1.3 Estimating mean and median WTP/WTA
WTP means, medians, modes, trimmed and modified estimators, and standards of
deviation can be found from individual bids. Mean WTP, or trimmed or modified
estimators based on mean WTP are the most appropriate, as they represent cardinal
measures of the utility that individuals derive from the good. Median WTP is
recommended because it is unaffected by large bids and because it is lower than the
mean WTP and may underestimate the value. As for the trimmed estimator, it involves
trimming the top and bottom 5% or 10% of the distribution of WTP observations.
However, this may result in the omission of some true estimates of WTP. The modified
estimator is considered to provide the truest value, as it identifies and excludes biased
and illegitimate responses by a series of questions included in the questionnaire.
Probit, logit and random utility models can be used for close‐ended referendum bids.
Bid curves can also be estimated by regressing WTP against socio‐economic variables.
Differentiating bid curves (dWTP/dV) provides the demand curve for the good and the
consumer surplus can thus be calculated as the area under the curve.
WTPi = f(Yi, Vi, Pi, Si, Ei)
Where, Y = income level; V = visits; P = preferences = S = substitutes; E = socio‐economic
variables (age, education, etc.)
10.1.4 Aggregating WTP or WTA amounts
Mean WTP/ WTA from the sample survey are aggregated across the total population.
TOTAL VALUE of the good/ service = (mean WTP) × (# of population units)
While mean WTP/ WTA may be modest for non‐use benefits, the populations over
which they are aggregated can be large.
10.1.5 Assessing the validity of CV studies The validity of the CV study is assessed by examining three aspects: content validity,
criterion validity, and construct validity. Content validity examines the appropriate
framing of the study and questions asked in relation to the good being valued. Criterion
validity involves the comparison of CV estimates with actual market or simulated market
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experience. As for construct validity, it examines the convergence between a CV
measure and other methods such as travel cost and hedonic price measures of the value
of the same good. It measures the extent to which the findings of the CV study are
consistent with theoretical expectations.
10.2 Considerations and biases When applying a CV study, the following need to be considered:
− Before designing the survey, learn as much as possible about how people think
about the good or service in question.
− Determine the extent of the affected populations or markets for the good or service
in question, and choose the survey sample based on the appropriate population.
− The choice scenario must provide an accurate and clear description of the change in
environmental services associated with the event, program, investment, or policy
choice under consideration. Convey this information using photographs, videos, or
other multi‐media techniques, as well as written and verbal descriptions.
− Specify whether comparable services are available from other sources, when the
good is going to be provided, and whether the losses or gains are temporary or
permanent.
− The respondent must believe that if the money was paid, whoever was collecting it
could effect the specified environmental change.
− Respondents should understand the frequency of payments required, for example
monthly or annually, whether or not the payments will be required over a long
period of time in order to maintain the quantity or quality change, and who would
have access to the good and who else will pay for it, if it is provided.
− Thoroughly pre‐test the valuation questionnaire for potential biases.
− Include validation questions in the survey to verify comprehension and acceptance
of the scenario and to elicit socioeconomic and attitudinal characteristics of
respondents.
− Make sure that survey results are analyzed and interpreted by professionals before
making any claims about the resulting dollar values.
The CVM is associated with many biases that need to avoided or minimized. These
include:
− Hypothetical bias: occurs since individuals do not have to pay their stated amounts.
This will cause them to overstate their true WTP. This bias is not very significant.
− Embedding effect: occurs when WTP is lower when it is valued as part of a more
inclusive good. This is attributed by some to the existence of substitutes.
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− Strategic bias: occurs when an individual deliberately overstates/understates the bid
to influence a particular outcome. This bias is difficult to detect and test but, it is not
significant.
− Bid vehicle bias: occurs when respondents give different WTP amounts, depending
on the specific payment vehicle chosen. For example, an individual disliking taxation
might understate his WTP. In such cases, a neutral vehicle such as a trust fund is
recommended.
− Starting point bias: occurs when a start‐off amount is misinterpreted by the
respondent as a cue for an appropriate WTP range. Extensive pre‐tests may minimize
this bias.
− Information bias: occurs when insufficient information makes it difficult on the
respondent to give a proper valuation, especially if the issue is new to him. Too much
information will be a definite source of bias
− Part‐whole bias: occurs when respondents asked to valuate a given asset and then to
valuate a part of it tend to give a similar answer. This is minimized by reminding
respondents of their budget constraints and by restricting valuation to whole goods
rather than parts of goods.
− Non‐response bias: occurs because people with interest in the subject are more
likely to respond. Non‐respondents are likely to have, on average, different values
than individuals who do respond. This is minimized by using questions that are easy
to answer.
Biases may be minimized by including certain questions as part of the survey. The
following are show cards prepared to elicit legitimate and illegitimate reason for WTP
answers.
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Show card to elicit legitimate and illegitimate reason for NOT being WTP towards low flow alleviation in rivers
Question Bias
a. I cannot afford to pay more water charges at present
b. I have no interest in having different flow levels in rivers
c. I would not pay anymore in water charges but I would be prepared to pay by some other means of payment
Payment vehicle
d. Someone else should pay rather than me Strategic
e. The water company should pay not customers Bid vehicle
f. Low levels in rivers are not a problem
g. I require more information to answer this question
h. Other reasons. Please specify
i. Don’t know
j. Refused to answer
Show card to elicit legitimate and illegitimate reason for being WTP towards low water quality
Question Bias
a. It was the most I could afford to pay
b. Rivers and beaches are important for recreation and I am happy to pay to ensure that they are well looked after
c. I would pay this much each year to ensure that rivers and beaches are protected for future generations
d. Rivers and beaches are important for wildlife and ecology and I am happy to pay to ensure that they are well looked after.
e. I wanted to show my support for environmental improvement in general Strategic
f. It’s an important issue and by saying I’d pay such a large sum each year I hope to get something done about it
Strategic
g. I’m very concerned about this issue and although I’m not sure I could afford to pay this much each year I wish I could
Hypothetical
h. Rivers and beaches are important for a number of reasons and I am happy to pay to ensure that they are well looked after
i. Other reason. Please specify;
j. Don’t know
k. Refuse to answer
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10.3 Advantages and limitations
Advantages associated with the CVM include:
− It is the most widely accepted method for estimating total economic value including
use values and all types of non‐use values
− It is straightforward and highly flexible, whereby it can used to estimate the
economic value of virtually anything
− It requires few theoretical assumptions
− The nature and results of CV studies are easy to analyze and describe. Dollar values
can be presented in terms of a mean or median value per capita or per household, or
as an aggregate value for the affected population.
− A great deal of research is being conducted to improve the methodology, make
results more valid and reliable, and better understand its strengths and limitations.
Issues and limitations associated with the CVM include:
− There is considerable controversy over whether CVM adequately measures people's
willingness to pay for environmental quality. CV assumes that people understand the
good in question and will reveal their preferences in the contingent market just as
they would in a real market. However, most people are unfamiliar with placing dollar
values on environmental goods and services and may not have an adequate basis for
stating their true value.
− Expressed answers to a willingness to pay question may be biased.
− Respondents may make associations among environmental goods that the
researcher had not intended. For example, if asked for willingness to pay for
improved visibility (through reduced pollution), the respondent may actually answer
based on the health risks that he or she associates with dirty air.
− WTA very significantly exceeds WTP. This result may invalidate the CVM approach,
showing responses to be expressions of what individuals would like to have happen
rather than true valuations.
− The “ordering problem”: in some cases, people’s expressed willingness to pay for
something has been found to depend on where it is placed on a list of things being
valued.
− Difficulty to validate externally the estimates of non‐use values.
− When conducted appropriately, contingent valuation methods can be very expensive
and time‐consuming, because of the extensive pre‐testing and survey work.
− Many people, including jurists policy‐makers, economists, and others, do not believe
the results of CV.
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10.4 Illustration‐Mining on public land
A remote site on public land provides important habitat for several species of wildlife.
The management agency in charge of the area must decide whether to issue a lease for
mining at the site. For this purpose, they must weigh the value of the mining lease
against the wildlife habitat benefits that may be lost if the site is developed. Non‐use
values are the largest component of the value for preserving the site because few
people actually visit it, or view the animals that rely on it for habitat. This necessitates
the use of the CVM.
Step 1
Define the valuation problem by determining what services are being valued and who
the relevant population is. In this case, the resource to be valued is a specific site and
the services it provides are primarily wildlife habitat. Because the land is federally
owned public land, the relevant population would be all citizens of the U.S.
Step 2
Make preliminary decisions about the survey itself: whether it will be conducted by mail,
phone or in person; how large the sample size will be; who will be surveyed, etc. The
answers will depend, among other things, on the importance of the valuation issue, the
complexity of the question being asked, and the size of the budget. The researchers
decided to conduct a mail survey, as they want to survey a large sample, over a large
geographical area. They are asking questions about a specific site and its benefits, which
should be relatively easy to describe in writing in a relatively short survey
Step 3
The actual survey design may take six months or more to complete. It is accomplished in
several steps. It starts with initial interviews and/or focus groups with the types of
people who will be receiving the final survey, in this case the general public. The
researchers would ask general questions about peoples’ understanding of the issues
related to the site, whether they are familiar with the site and its wildlife, and whether
and how they value this site and the habitat services it provides. In later focus groups,
the questions would get more detailed and specific in order to help develop specific
questions for the survey and to decide what kind of background information is needed
and how to present it. People might need information on the location and
characteristics of the site, the uniqueness of species that have important habitat there,
and whether there are any substitute sites that provide similar habitat. The researchers
would also want to learn about peoples’ knowledge of mining and its impacts, and
whether mining is a controversial use of the site. If people are opposed to mining, they
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may answer the valuation questions with this in mind, rather than expressing their value
for the services of the site. At this stage, different approaches to the valuation question
and different payment mechanisms would be tested. Questions that can identify any
“protest” bids or other answers that do not reveal peoples’ values for the services of
interest would also be developed and tested at this stage.
After a number of focus groups, pretesting of the survey is started. The survey should be
pretested with as little interaction with the researchers as possible. Pre‐testing will
continue until a survey is developed that people seem to understand and answer in a
way that makes sense and reveals their values for the services of the site.
Step 4
At this stage, actual survey implementation takes place. The survey sample is selected.
The sample should be a randomly selected sample of the relevant population, using
standard statistical sampling methods. For instance, a mailing list of randomly sampled
U.S. Citizens may be obtained and a standard repeat‐mailing and reminder method may
be used to get the greatest possible response rate for the survey.
Step 5
The results are compiled, analyzed and reported. Data must be entered and analyzed
using statistical techniques appropriate for the type of question. The researchers also
attempt to identify any responses that may not express the respondent’s value for the
services of the site. They can deal with possible non‐response bias in a number of ways.
The most conservative way is to assume that those who did not respond have zero
value.
Step 6
The final step involves estimating the average value for an individual or household in the
sample, and extrapolating this to the relevant population in order to calculate the total
benefits from the site. If the mean willingness to pay is $.10 per capita, the total benefits
to all citizens would be $26 million.
10.5 Sample application 1‐ Mono Lake
Reduced water flows to Mono Lake affect food supplies for nesting and migratory birds.
The State of California Water Resources Control board has to decide about the water
quantity to be allocated to Los Angeles from sources flowing into Mono Lake. A
contingent valuation study was conducted to measure the use and non‐use values of
citizens in California households for increased water flows in Mono Lake. An initial mail
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survey was conducted where residents of California were told that, according to
biologists, the higher flows to the lake were needed to maintain food supplies for
nesting and migratory birds. Residents were then asked whether they would pay more
on their water bill for higher cost replacement water supplies, so that natural flows
could once again go into Mono Lake. According to the respondents, average WTP per
household was $13 per month or $156 per year. The total benefits exceeded the $26
million cost of replacing the water supply by a factor of 50. As follow‐up to this survey,
the State of California hired a consulting firm to perform a more detailed CV survey. The
new survey involved the use of photo‐simulations showing what the lake would look like
at alternative water levels. It gave detailed information about effects of changing lake
levels on different bird species. The survey was conducted over the telephone with
people who had been mailed information booklets with maps and photo‐simulations.
Survey respondents were asked how they would vote in a hypothetical referendum
regarding Mono Lake. This study showed that the benefits of a moderately high (but not
the highest) lake level were greater than the costs. Accordingly, the California Water
Resources Control Board reduced Los Angeles’ water rights by half, from 100,000 acre
feet to about 50,000 acre feet, to allow more flows into Mono Lake.
10.6 Case‐study‐ Exxon Valdez Oil Spill At 12.04 a.m. on 24 March 1989, the oil tanker Exxon Valdez ran aground on Bligh Reef
in Prince William Sound, Alaska. It was carrying crude oil from wells on Alaska's North
Slope, brought to Valdez through the Tans‐Alaska pipeline. From Valdez, the crude is
carried by tankers to refineries in the southern United States. The Exxon Valdez was
carrying more than 50 million gallons of crude oil, of which approximately 11 million
gallons poured into the Sound. This was the largest spill in United States history. By
August, the oil had moved across nearly 10,000 square miles of water and about 1,600
miles of the Sound's convoluted shoreline was heavily oiled.
The oil had a massive impact on wildlife in the area, killing many birds and marine mammals. Over 20,000 dead birds were recovered, mostly murres but also many other
species including 100 bald eagles. The total numbers killed were probably three to six
times the numbers recovered. About 2,650 sea otters died, probably about 40 per cent
of the population in the affected area. Seals and many other species were also killed or
damaged by the spill, including plants and microorganisms. However, none of these
losses threatened the extinction of the species involved. It was expected that bird and
mammal populations would recover to their pre‐spill levels in about three to five years.
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The spill had a variety of impacts on human values. The Sound is important for
commercial and recreational fishing and tourism, and these uses were severely damages
by the oil spill. These types of impact could be valued relatively easily. However, we may
anticipate that the area also has significant non‐use values: existence, option and
bequest values. As part of an assessment of the total damages arising from the oil spill, it
would be important to find some means of estimating the extent of these non‐use
values. In connection with legal action taken by the State of Alaska against Exxon
Corporation and related companies, a contingent valuation study was commissioned
from a number of well‐known economists working in the field of valuation.
The study involved a survey of residents across the United States. Alaska was excluded
from this as the aim was to focus on non‐use values. In principle, the survey should seek
to estimate the population's willingness to accept compensation for the damage arising
from the Exxon Valdez oil spill. However, because of the difficulty involved in designing
surveys of this sort, it was decided to adopt a willingness to pay approach. The valuation
question was based on a hypothetical proposal for a scheme to prevent future oil spills
of the sort which had just been experienced. Respondents in the survey were asked to
indicate whether or not they would vote for a proposal to provide escort ships to
accompany oil tankers through the Sound. The ships would carry special booms which
could be put into place immediately any oil spill occurred so as to hold the oil within a
confined area. The spilt oil could then be skimmed off the surface and taken away for
safe disposal. This system has been used successfully by the Norwegians in the North
Sea. Without this scheme, respondents were told that over the next ten years, another
large oil spill can be expected to occur in Prince William Sound. The scheme would be
paid for from a special tax on oil company profits and from a single tax on all
households.
In carrying out the survey, after investigating respondents' prior knowledge of the issue,
interviewers provided respondents with information on the Exxon Valdez oil spill and its
impacts. The basic valuation question put to each respondent was whether or not he or
she would vote for a proposal to implement the scheme, given a specified level of a
single one‐time tax on each household. The initial tax values were set at $10, $30, $60
and $120 for different households. If respondents answered that they would be
prepared to vote for the scheme at this level of tax, the amount was raised and the
question asked just once more. If they refused to vote for the scheme, the amount was
lowered and the question was asked just once more. The survey also collected
information on interests in environmental issues, the composition of the respondent's
household, education and incomes.
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Excerpts of the administered questionnaire: The only mammals killed by the spill were sea otters and harbour seals. This card shows information about what happened to Prince William Sound. According to scientific studies, about 580 otters and 100 seals in the Sound were killed by the spill. Scientists expect the population size of these two species to return to normal within a couple of years after the spill. Many species of fish live in these waters. Because most of the oil floated on the surface of the water, the spill harmed few fish. Scientific studies indicate there will be no long‐term harm to any of the fish populations. #2. Of course, whether people would vote for or against the escort ship program depends on how much it will cost their household At present, government officials estimate the program will cost your household a total of $______. You would pay this in a special one‐time charge in addition to your regular federal taxes. This money would only be used for the program to prevent damage from another oil spill in Prince William Sound. If the program cost your household a total of $______, would you vote for or against it?” #3. What if the final cost estimate showed that the program would cost your household a total of $_______. Would you vote for or against the program? #4. What is it about the program that made you willing to pay something for it? #5. Before the survey, did you think the damage caused by the Valdez oil spill was more serious than was described to you, less serious, or about the same as described? #6. Is anyone in your household an angler, birdwatcher, backpacker, or environmentalist? #7. This card shows amounts of yearly incomes. Which category best describes the total income from all members of your family before?
A total of 1,043 interviews were successfully completed, achieving a response rate of 75
per cent. The proportions of respondents indicating that they would vote for the
proposed scheme at the alternative tax levels are shown in Table 19. As would be
expected, the proportion falls as the specified cost of the scheme increases, although
there is little difference between the $30 and $60 questions.
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Table 19. Positive response to alternative tax levels
Questionnaire version
Initial tax level per household (USD)
Percent of respondents willing to
pay taxes
A 10 67
B 30 52
C 60 51
D 120 34
From these results, it is possible to estimate statistically a figure for the median
willingness to pay. This is midpoint in the distribution, so that there is an equal number
of a figure above and below the median. The preferred estimate was for $31 per
household. A figure of $94 was estimated as the mean willingness to pay, but the nature
of the questions asked meant that this figure is unreliable. Just over one‐third of
respondents were not willing to vote for the scheme at either of the prices offered to
them and of these one third indicated that a reason for this negative response was that
they felt that the oil companies should pay. Varying the assumptions used in the analysis
either tended to increase the estimated median willingness to pay or else had little
effect on it.
It is possible to extrapolate the results of the survey in order to estimate the total value
for the non‐use values lost in the United States as a whole. This figure is obtained by
multiplying the total number of households by $31 and produces a figure of $2.8 billion,
with a confidence interval of $2.4 billion to $3.2 billion.
This analysis was at the centre of a fierce debate. If Exxon and the other companies were
found to be liable for the damage caused, they would face an enormous bill for the non‐
use values alone. The debate focused on the role of contingent valuation in estimating
these sorts of values. In this context a panel of distinguished economists was established
by the National Oceanic and Atmospheric Administration, including two Nobel Prize
winners, to examine the role of contingent valuation in the valuation of non‐use values
for the purposes of assessing the damages from oil spills. The panel concluded that
contingent valuation studies can convey useful information that is sufficiently reliable
from a starting point for the process of assessing damages in the courts. However, they
had reservations about the ways in which contingent valuations have often been
undertaken and set out a series of guidelines for the way in which they believed that
they should be undertaken.
THE DISCRETE CHOICE METHOD &
THE BENEFIT TRANSFER METHOD
Session 10
Region
al Training Worksho
p on
: Th
e Co
st of E
nviron
men
tal D
egrada
tion
Metho
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SESSION 10
11 DISCRETE CHOICE METHOD
Contingent choice, also referred to as conjoint analysis, was developed in the fields of
marketing and psychology to measure preferences for different characteristics or
attributes of a multi‐attribute choice. It asks the respondent to state a preference
between one group of environmental services or characteristics, at a given price or cost
to the individual, and another group of environmental characteristics at a different price
or cost. It is especially suited to policy decisions where a set of possible actions might
result in different impacts. For example, improved water quality in a lake will improve
the quality of several services provided by the lake, such as drinking water supply,
fishing, swimming, and biodiversity. While contingent choice can be used to estimate
dollar values, the results may also be used to simply rank options, without focusing on
dollar values.
The contingent choice method is similar to contingent valuation, whereby it involves
asking people to make choices based on a hypothetical scenario. Furthermore, it can be
used to estimate economic values for any ecosystem or environmental service and it can
be used to estimate non‐use as well as use values. Yet, the contingent choice method
differs from contingent valuation in that it requires people to evaluate several
alternatives separately, it does not directly ask people to state their values in dollars,
and the values are inferred from the hypothetical choices or tradeoffs that people make.
There are a variety of formats for applying contingent choice methods. Contingent
rating, contingent ranking and paired rating are summarized in Table 20, and choice
modeling is detailed in the section below.
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Table 20. Types of contingent choice formats Contingent Rating − Respondents presented with a set of attributes associated with each alternative
− Respondents requested to rate their preference for several alternatives on a scale
− Ratings regressed against attributes − Marginal rate of substitution between an attribute and its price provides an estimate of the value of the attribute
− Summing up all values provides the aggregate WTP for the environmental value Contingent Ranking
− Respondents asked to rank all alternatives from least preferred to most preferred− Analysis similar to contingent rating − Rankings converted to rating scale and analyzed with multiple regression techniques
− Other measures such as probit, or logit analysis may be used Paired Rating − Respondents presented with successive sets of two choices and asked to rate the
difference between them in terms of preference on a scale − Data analyzed using multiple regression, probit, or logit models
Choice modeling − Respondents presented with a series of alternatives, each defined by a set of attributes and containing three or more resource use options
− Attributes varied across alternatives − Respondents to choose preferred alternative − More flexible and versatile but requires complex survey designs
11.1 Choice experiments
Choice experiments are used to examine the response of the individual to changes in the
attributes of the scenario as well as the scenario as a whole. They allow breaking down
the relevant attributes of the situation and determining preferences over attributes and
they allow for more flexibility than CVM. Choice experiments attempt to identify the
utility the individuals have for the attributes of the goods and services by examining the
tradeoffs that they make between them when making choice decisions. Steps in the
choice modeling experiment are summarized in and detailed below:
1. Identify the good or service to be investigated
2. Identify key attributes and determine the attribute levels to be used
The initial screening of the attributes is a crucial stage in study design. The attributes
should be familiar and relevant to respondents and the attribute levels should be
measureable using quantitative or qualitative scales. Attributes may be portrayed
verbally or pictorially, etc. Defining an appropriate number of attributes is important
whereby too many attributes burden the respondents and too few cause problems
with estimation and reliability. Pre‐testing and focus groups are helpful in defining
attributes and determining their numbers.
3. Develop an appropriate experimental design for profiles
This involves the specification of a factorial or fractional factorial experimental
design to estimate the utility for the good in question. An orthogonal main‐effects
plan sampled from the complete factorial design is used to select the profiles to be
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used in the choice experiment. Procedures in computer packages such as SAS and
SPSS may be used to create an orthogonal matrix based on the attribute levels
specified by the researcher
4. Design questionnaire survey and incorporate choice experiments. The types of
questionnaires that may be adopted along with a description of each are presented
in (Figure 26).
Face‐to‐face interviews − The usual method adopted − Allow the definition and explanation of the good
more thoroughly − Minimize non‐response − Expensive to conduct
Self‐fill questionnaires − Questionnaires left at recreation sites for
visitors or in public places − Low response rate − Cheap data collection − Only questions that can be easily comprehended
may be used Telephone interviews − Problems due to absence of visual cues − Problems due to difficulty in maintaining
respondents attention − A combined telephone interview and mail shot
can be cost‐effective and increase response rate − Telephone secures respondent’s interest − Mail follow‐up provides visual and questionnaire
material
Mail shots − Used where hypothetical market easily
explained to respondents − Most appropriate when respondents − Are widely scattered over space − Have expert knowledge, interest in the good,
etc. − Only questions that are easily comprehended
may be used
Figure 26. Types of survey questionnaires
5. Perform pre‐tests and undertake survey
6. Analyze choices made and determine trade‐offs made by respondents. Random
utility theory is used to model the choices as a function of attribute levels, based on
the hypothesis that individuals make choices based on the attributes of the
alternatives along with some degree of randomness. Following repeated
observations of choice, one can examine how the levels of various attributes affect
the probability of choice. An assumption of normality leads to the binary probit
model, while an assumption of a Gumbel distribution means that the multinomial or
Mother Logit can be employed.
7. Calculate welfare measures
8. Aggregate over population of relevance
Whatever format is selected, choices that respondents make are statistically analyzed
using discrete choice statistical techniques, to determine the relative values for the
different characteristics or attributes. If one of the characteristics is a monetary price,
then it is possible to compute the respondent’s willingness to pay for the other
characteristics.
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A good contingent choice study will consider the following:
− Before designing the survey, learn as much as possible about how people think
about the good or service in question. Consider people’s familiarity with the good or
service, as well as the importance of such factors as quality, quantity, accessibility,
the availability of substitutes, and the reversibility of the change.
− Determine the extent of the affected populations or markets for the good or service
in question, and choose the survey sample based on the appropriate population.
− The choice scenario must provide an accurate and clear description of the change in
environmental services associated with the event, program, investment, or policy
choice under consideration. If possible, convey this information using photographs,
videos, or other multi‐media techniques, as well as written and verbal descriptions.
− The nature of the good and the changes to be valued must be specified in detail, and
it is important to make sure that respondents do not inadvertently assume that one
or more related improvements are included.
− The respondent must believe that if the money was paid, whoever was collecting it
could effect the specified environmental change.
− Respondents should be reminded to consider their budget constraints.
− Specify whether comparable services are available from other sources, when the
good is going to be provided, and whether the losses or gains are temporary or
permanent.
− Respondents should understand the frequency of payments required, for example
monthly or annually, whether or not the payments will be required over a long
period of time in order to maintain the quantity or quality change, and who would
have access to the good and who else will pay for it, if it is provided.
− In the case of collectively held goods, respondents should understand that they are
currently paying for a given level of supply. The scenario should clearly indicate
whether the levels being valued are improvements over the status quo, or potential
declines in the absence of sufficient payments.
− If the household is the unit of analysis, the reference income should be the
household’s, rather than the respondent’s, income.
− Thoroughly pre‐test the questionnaire for potential biases. Test different ways of
asking the same question and test whether the question is sensitive to changes in
the description of the good or resource being valued.
− Conduct post‐survey interviews to determine whether respondents are stating their
values as expected.
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− Include validation questions in the survey to verify comprehension and acceptance
of the scenario and to elicit socioeconomic and attitudinal characteristics of
respondents.
11.2 Advantages and limitations
The main advantages of the contingent choice method include:
− It can be used to value the outcomes of an action as a whole, as well as the various
attributes or effects of the action.
− It does not ask the respondent to make a tradeoff directly between environmental
quality and money. The tradeoff process may encourage respondent introspection
and make it easier to check for consistency of responses. Respondents may be able
to give more meaningful answers to questions about their behavior (i.e. they prefer
one alternative over another), than to questions that ask them directly about the
dollar value of a good or service or the value of changes in environmental quality.
− Respondents are generally more comfortable providing qualitative rankings or
ratings of attribute bundles that include prices, rather than dollar valuation of the
same bundles without prices.
− Even if the absolute dollar values estimated are not precise, the relative values or
priorities elicited by a contingent choice survey are likely to be valid and useful for
policy decisions.
− It minimizes many of the biases that can arise in open‐ended contingent valuation
studies where respondents are presented with the unfamiliar and often unrealistic
task of putting prices on non‐market amenities.
− It has the potential to reduce problems such as expressions of symbolic values,
protest bids, and some of the other sources of potential bias associated with
contingent valuation.
The main issues and limitations that are associated with a contingent valuation process
include:
− Respondents may find some tradeoffs difficult to evaluate, because they are
unfamiliar.
− The respondents’ behavior underlying the results of a contingent choice study is not
well understood. Respondents may resort to simplified decision rules if the choices
are too complicated, which can bias the results of the statistical analysis.
− If the number of attributes or levels of attributes is increased, the sample size and/or
number of comparisons each respondent makes must be increased.
− When presented with a large number of tradeoff questions, respondents may lose
interest or become frustrated.
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− Contingent choice may extract preferences in the form of attitudes instead of
behavior intentions.
− By only providing a limited number of options, it may force respondents to make
choices that they would not voluntarily make.
− Contingent ranking requires more sophisticated statistical techniques to estimate
willingness to pay.
− Translating the answers into dollar values, may lead to greater uncertainty in the
actual value that is placed on the good or service of interest.
− Validity and reliability for valuing non‐market commodities is largely untested.
11.3 Illustration‐ Mining in public land
There is a remote site on public land that provides important habitat for several species
of wildlife. The management agency in charge must decide whether to issue a lease for
mining at the site. Suppose that there are several possible options for preserving and/or
using the site, including allowing no mining and preserving the site as a wilderness
habitat area, or specifying various levels and locations for the mining operation, each of
which would have different impacts on the site. The contingent choice method was
selected because the outcomes of several policy options need to be valued and because
non‐use values are the largest component of the value for preserving the site. Thus,
TCM will underestimate the benefits of preserving the site. The CVM might also be used,
but the survey questions might become very complicated.
Contingent choice and contingent valuation have very similar application. The main
differences are in the design of the valuation question(s), and the data analysis.
Step 1
Define the valuation problem by determining exactly what services are being valued,
and who the relevant population is. In this case, the resource to be valued is a specific
site and the services it provides is wildlife habitat. Because it is federally owned public
land, the relevant population would be all citizens of the U.S.
Step 2
Make preliminary decisions about the survey, including whether it will be conducted by
mail, phone or in person, how large the sample size will be, who will be surveyed, and
other related questions. In this case, the researchers decided to conduct a mail survey
since it will be administered to a large sample over a large geographical area. Questions
about a specific site and its benefits should be relatively easy to describe in writing.
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Step 3
The actual survey design is accomplished in several steps. It starts with initial interviews
and/or focus groups with the types of people who will be receiving the final survey, in
this case the general public. In the initial focus group, the researchers would ask general
questions about peoples’ understanding of the issues related to the site, whether they
are familiar with the site and its wildlife, and whether and how they value this site and
the habitat services it provides. In later focus groups, the questions would get more
detailed and specific. Different approaches to the choice questions are tested. Each
choice might be described in terms of the site’s ability to support each of the important
wildlife species. People will be making tradeoffs among the different species that might
be affected in different ways by each possible choice of scenario. After a number of
focus groups, pretesting of the survey is started. The survey should be pretested with as
little interaction with the researchers as possible. People would be asked to assume that
they’ve received the survey in the mail and to fill it out. Then the researchers would ask
respondents about how they filled it out, and let them ask questions about anything
they found confusing. A mail pretest might be conducted. This process is continued until
a survey is developed that people seem to understand and answer in a way that makes
sense and reveals their values for the services of the site.
Step 4
At this stage, actual survey implementation takes place. The survey sample is selected.
The sample should be a randomly selected sample of the relevant population, using
standard statistical sampling methods. For instance, a mailing list of randomly sampled
U.S. Citizens may be obtained and a standard repeat‐mailing and reminder method may
be used to get the greatest possible response rate for the survey.
Step 5
The results are compiled, analyzed and reported. The statistical analysis for contingent
choice is often more complicated than that for contingent valuation requiring the use of
discrete choice analysis methods to infer willingness to pay from the tradeoffs made by
respondents. The researchers need to estimate the average value for each of the
services of the site, for an individual or household, and then extrapolate to the relevant
population in order to calculate the total benefits from the site under different policy
scenarios. The average value for a specific action and its outcomes can also be
estimated, or the different policy options can be ranked in terms of peoples’ preferences
The results of the survey might show that the economic benefits of preserving the site
by not allowing mining are greater than the benefits received from allowing mining. The
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mining lease might not be issued, unless other factors override these results. The results
might indicate that some mining scenarios are acceptable, in terms of economic costs
and benefits. The different options should be ranked and the most preferred option
selected.
11.4 Case‐application: Landfill Siting in Rhode Island With its primary landfill nearing capacity, the State of Rhode Island was faced with the
need to choose locations for new landfills. Besides technical considerations, the State
wanted to address the social and economic tradeoffs and values related to the location
of a landfill to avoid some of the controversy associated with landfill siting. A contingent
choice, paired comparison, survey was conducted. The survey asked Rhode Island
residents to choose between pairs of hypothetical sites and locations for a new landfill,
described in terms of their characteristics. The site comparisons described the natural
resources that would be lost on a hypothetical 500 acre landfill site area surrounding the
landfill. Each comparison gave the cost per household for locating a landfill at each
hypothetical site or location. The results were used by the State to predict how residents
would vote in a referendum on different possible landfill locations. First, 59 possible
sites were selected, based on geological and public health criteria. Sites were ranked
using the contingent choice survey results, in order to come up with a short list of
potential sites. The final decision, based on geological, public health, public preferences,
and political considerations, was to expand the existing landfill site.
11.5 Case‐study: The Environmental Costs of Low River Flows
11.5.1 Background River flows may be reduced to sub‐optimal levels by natural phenomenon such as low
rainfall, or may be caused by the abstraction of water either from the river itself or from
the underlying aquifer. In the United Kingdom (UK) when river flows are seriously low,
the Environment Agency (EA) is responsible for the design and implementation of
schemes to alleviate this problem. A number of options are available to the EA to
alleviate low flows in these rivers. All of the available options involve a cost, and before
any decisions are made regarding which particular solutions to the low flow problem are
adopted, careful consideration has to be given to the question of whether or not the
additional benefits from increasing the flow to some environmentally acceptable flow
regime outweigh the costs involved.
The case study focuses on the south west of England, an area encompassing 176
beaches designated as Euro‐beaches by the European Community, with other smaller
beaches and coves, and approximately 4,000 miles of rivers. The particular focus was on
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seven rivers that were identified as being seriously affected by low flows at certain times
of the year. Given that the benefits of increasing river flows were likely to comprise both
use values and non‐use values, it was decided that some form of expressed preference
method would be most appropriate to elicit willingness to pay. The issue of non‐use
values was an important consideration, and any survey of the general public was likely
to result in a high proportion of non‐users being samples. This would include who do not
visit rivers at all and, more commonly, individuals who not visit any of the designated
low‐flow rivers in the south west of England. This lack of familiarity would have made it
difficult for respondents to give meaningful answers to an open‐ended WTP question or
to a bidding game relating to EA activities. This consideration led to the concentration on
the choice experiment approach with the aim of estimating the marginal WTP of the
general public for unit improvements in low flow alleviation in rivers in the south west of
England. The choice experiment would also be used to estimate the public's marginal
WTP for unit improvements in the numbers of clean beaches and miles of unpolluted
rivers in the area.
This concentration on marginal WTP confronts the issue of scale and should provide
more robust welfare estimates for decision making. Furthermore, the more holistic
choice experiment approach is less vulnerable to other sequencing effects such as
embedding.
11.5.2 The benefits of low flow alleviation The total economic value of low flow alleviation in a given river is the sum of all use
values derived from it, plus any non‐use values which this activity may generate. Use
values are benefits arising either directly or indirectly from the improvement in flows,
while non‐use values are generated by the consumption of the flow of information
about the good which is consumed as a preservation benefit, i.e. a value arising from the
knowledge that the river remains healthy and viable and will persist. A survey of the
general public survey in the south west of England was carried out in the summer of
1996, including both users and non‐users. Non‐users were identified as those
respondents who did not visit any of the low flow rivers in the south west specified in
this project.
11.5.3 Questionnaire design A series of focus groups was undertaken prior to the design of the questionnaire with
the intention of informing the design process and suggesting the levels of information
that respondents would require. The focus groups suggested that the public considered
problems of coastal and river pollution to be the most pressing water quality issues in
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the south west; however, when shown a portfolio of photographs illustrating the varying
effects of low flows most participants agreed that this issue was also important (though
not as pressing as pollution, to which it was seen as a contributory factor). The design of
the questionnaire was intended to provoke respondents into thinking more deeply
about the consequences of their response to the choice experiments and to make those
responses as realistic as possible given the artificial context. The effect of the
questionnaire design on welfare estimates in this case should have been to limit them
rather than inflate them, thus leading to conservation welfare estimates that can be
interpreted as lower‐bound figures. The magnitude of welfare estimates was limited by
using a sequence of questions and statements designed to remind respondents of other
environmental quality issues that they might wish to support, rather than allowing them
to focus on the water quality issues with which this study was concerned. The notion of
a multi‐good environment was introduced early in the questionnaire, when respondents
were asked questions regarding their donations to good causes and their willingness and
ability to contribute more to such causes in the future. This helped to establish a context
within which respondents could begin to determine how much they would be willing to
pay towards water quality improvements. This approach was tested and refined over
two separate pilot surveys. The notion of a multi‐good environment was introduced
early in the questionnaire, when respondents were asked questions regarding their
donations to good causes and their willingness and ability to contribute more to such
causes in the future. This helped to establish a context within which respondents could
begin to determine how much they would be willing to pay towards water quality
improvements. This approach was tested and refined over two separate pilot surveys.
Respondents were then presented with a brochure describing the EA's activities under
three headings: reducing river pollution; monitoring marine pollution in coastal waters;
and improving flows in low flow rivers. Text was kept to a minimum and illustrations
were used wherever possible. Information was limited to bullet points describing the
problem being tackled, its causes and consequences and what the EA was doing to
tackle the problem across the south‐west. Rather than just emphasize the scale of the
problem, the brochure also attempted to show how much had in fact been achieved in
tackling these problems. This had the twin effects of demonstrating that additional
spending could bring about further positive environmental benefits, but that current
levels of spending (£90 million per year in 1996) were already achieving significant
improvements in each of the categories shown in the brochure.
The focus on activities in the south west was thought most appropriate in a survey that
would cover a wide variety of households in that region. Specifically, it was felt that
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respondents would relate better to more familiar local issues than to national ones and
this would promote more considered response to the choice experiment questions. In
the choice experiments, respondents were given a sheet similar to that shown in Figure
27 and asked to choose one of the three choices. Having made their choice respondents
were shown three more cards and asked to choose their preferred choice from each.
Cards were chosen at random form an orthogonal set of 64 choice cards. In the choice
experiments the issue of low flows is embedded in a broader set of water quality goods
discouraging a single focus on the issue of low flows. This confronts the issue of
embedding by ensuring that respondents act consistently and make choices based on
the same set of related goods.
CARD 06
Please choose one column
CHOICE 1(current situation)
CHOICE 2 CHOICE 3
Increase in water charges needed to achieve targets
No increase £5 increase £10 increase
Beaches in the South West NOT MEETING European standards on cleanliness
9 beaches 5 beaches 3 beaches
Rivers in the South West WITHOUT good quality water
990 miles 350 miles 350 miles
Rivers in the South West WITHOUT acceptable flow levels
130 miles 80 miles 60 miles
Figure 27. Example of a choice experiment card
11.5.4 River usage by the general public Nearly half of the households interviewed claimed to live one mile or less from a river;
and more than two‐thirds lived within two miles of a river. Most households regularly
undertook recreational activities along rivers, with only 23% claiming not to undertake
some form of regular recreation along rivers. Around 88% of households had visited
more than one river the 12 months preceding the survey, but only 45% had visited one
of the low flow rivers in the south west. The frequency of visits to beaches over the
summer months had much the same distribution as visits to rivers, though greater
differences began to emerge during the winter.
11.5.5 Empirical Results
Preliminary questions demonstrated public perceptions of the abstraction problem.
Nearly three‐quarters of respondents thought that rivers were an important source of
water; but just over half thought too much water was being abstracted from rivers by
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water companies and other users. Investigations into the public's WTP for good causes
showed that 80% of respondents would prefer to see additional public expenditure on
the natural environment (a lower rate than for health or education). However, only 40%
of respondents indicated that they would be willing to contribute more than they
currently contribute towards that they considered 'good causes'.
Following Adamowicz et al. (1996) the responses from choice experiments were used to
estimate a discrete choice model of the probability Pr(i) of choosing a given alternative i:
Pr (i) =exp (sVi)/∑exp (sVj)
Models were estimated using linear and quadratic functional forms. Under the quadratic
specification some attribute coefficients were not statistically significant; therefore the
linear functional form was used for benefit estimation. Table 21 reports WTP for the
marginal improvements in water quality defined by unit reductions in the number of
polluted beaches and the lengths of river affected by low flows and poor water quality.
Respondents were willing to pay between £1.31 and £1.43 to ensure that one additional
beach meets EC standards on cleanliness and £0.02 to clean up a mile of polluted river.
Similarly, respondents were willing to pay up to £0.06 per mile to improve conditions on
low flow rivers. These estimates were used for the purposes of aggregation, but this
relies on the presumption that it is reasonable to assume constant marginal WTP for
water quality improvement measures across the south west. This may be the case for
beaches but it is possible that following substantial reductions in the length of rivers
affected by low flows and pollution that WTP for additional lengths to be improved.
Table 21. WTP for marginal improvement in water quality Reduction Extended specification
1 polluted beach £1.307 £1.431
1 mile of polluted river £0.017 £0.019
1 mile of low flow river £0.052 £0.058
11.5.6 Estimating the number of users and non‐users The population of users for this study was defined to encompass all households who had
visited a given low flow river in the two‐year period immediately preceding the survey.
Respondents were shown a list of the seven low flow rivers that were the main focus of
this study and asked whether or not they had visited these rivers at any time during the
last two years. This data can be used to estimate the number of households that visit
each low flow river. Nearly 45% of households in the south‐west had visited at least one
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of the low flow rivers during the last two years. Table 22 reports results for each river to
give an estimate of the bi‐annual number of visitors to each river. The population of the
south west is divided into user and non‐user households for each of the seven low flow
rivers. It also reports the length of each river affected by low flows. This latter figure is
important in the estimation of the aggregate benefits of low flow alleviation. Although
quite high, these estimates seemed reasonable. Rivers are linear features and instead of
offering a single point of access provide many and varied opportunities for individuals to
encounter them. Added to this is the fact that all of the rivers are located in areas with
considerable scenic attractions where local people as well as those from further afield
would be expected to enjoy the considerable recreational opportunities on offer.
Table 22. User and non‐user populations for low‐flow rivers from the south west River User Households Non‐user households Miles affected by low flows
Allen 85,897 1,562,533 20
Upper Avon 230,717 1,417,713 35
Meavy 166,760 1,481,670 7
Otter 157,982 1,490,448 5
Piddle 157,854 1,490,576 16
Tavvy 240,155 1,408,275 16
Wylye 162,481 1,485,949 30
11.5.7 Aggregate benefit estimates The choice experiments reported in the previous section can be used to derive random
utility models based on the subsets of users and non‐users defined previously. These
models yield estimates of the marginal WTP for a unit decrease in the length of rivers
affected by low flows. The estimate for users will comprise a combination of use values
and nonuse values, while for non‐users the estimate is made up entirely of non‐use
values. The validity of this latter estimate is highly suspect because the coefficient on the
LOWFLOW variable in the non‐users' model was not statistically significant at any
reasonable level. This implies that when selecting their preferred card in the choice
experiments, the non‐user population did not give much weight to improvements in low
flow rivers. Rather, their choices were based upon cost and the improvements that
could be made to polluted rivers and beaches.
The population of low flow river users was estimated at 734,161. For each low flow river,
the maximum aggregate annual benefit for user households is calculated by multiplying
this figure, first by the length of river affected by low flows, and then by £ 0.076 per mile
(see Table 23). The proportion of this amount contributed by visitors can also be
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calculated using the same procedure and substituting the estimated number of visitors
for the user population. The aggregate benefits for non‐user households are calculated
in a similar fashion, using the marginal value of £0.0435.
Table 23. Approximate aggregate annual benefits for improving low flows
River Aggregate benefits for user Households
Aggregate benefits for visitor households
Aggregate benefits for non‐user households
Allen £1,115,925 £130,563 £795,414
Upper Avon £1,952,868 £613,707 £1,391,975
Meavy £390,574 £88,716 £278,395
Otter £278,981 £60,033 £198,854
Piddle £892,740 £191,950 £636,331
Tavvy £892,740 £292,028 £636,331
Wylye £1,673,887 £370,457 £1,193,121
11.5.8 The costs of low flow alleviation The costs of various options to alleviate low flows on rivers in the south west were
calculated by Environmental Resources Management. Table 24 summarizes the present
values of the costs of the cheapest available option for low flow alleviation on six of the
seven rivers: no solution has yet been put forward for low flow alleviation on the Tavy.
Table 24 also reports the present value of the benefits of low flow alleviation for the
user sub‐sample. Present values were calculated by assuming a constant flow of benefits
across the period 1997 to 2017 and discounting at 6%. Net benefits and benefit cost
ratios were calculated using these figures. These figures can be used to carry out partial
benefit‐cost analysis in order to identify which options require further investigation
before they can be implemented (Table 24).
Table 24. Net present value of aggregate benefits for improving low flows across the length of the rivers
River Present value of costs
Present value of aggregate user
benefits
Net present value
Benefit‐cost ratio
Allen 11,867,000 13,915,000 2,048,000 1.17
Upper Avon 763,000 24,252,000 23,589,000 31.92
Meavy 80,000 4,870,000 4,790,000 60.88
Otter 34,430,000 3,480,000 ‐30,950,000 0.10
Piddle 5,471,000 11,132,000 5,661,000 2.03
Tavvy Unknown 11,132,000 ‐ ‐
Wylye 224,000 20,873,000 20,649,000 93.18
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Benefits exceed costs by a wide margin for the rivers Avon, Meavy and Wylye, and to a
lesser extent for the Piddle. Costs are prohibitive only on the Otter, while the benefit‐
cost ratio for the Allen suggests that while benefits probably exceed costs there is
relatively little difference between them. As benefits are based only on the user sample,
these benefit‐cost ratios ignore any benefits that might accrue to non‐users but include
non‐use benefits for low flow river visitors who do not visit the river in question. If only
the present value of the aggregate benefits accruing to visitors is considered then the
least cost solutions for the Piddle and Allen fall to levels substantially below that of the
associated costs, while the benefits for the A von, Meavy and Wylye still outstrip costs
by a ratio of at least 10 to 1 .
The results of the study strongly suggest that there are considerable welfare gains to be
made from implementing the least cost low flow alleviation options on the Rivers Wylye,
Meavy and Upper Avon. Similarly, there is strong evidence to suggest that only a low
flow alleviation option costing considerably less than the one costed in this study would
be justified on the Otter. The benefits of the least‐cost low flow alleviation options for
the Piddle and Allen can only be justified on the basis of non‐use values, and then only
tentatively. In these cases we would recommend that investigation of the non‐
recreational benefits of low flow alleviation be carried out to provide a clearer picture in
a fuller benefit‐cost analysis.
12 THE BENEFIT TRANSFER METHOD
The benefit transfer method involves transferring values that have been estimated for a
similar good or service from another location/context to the current location/context. It
represents a useful method under budget and time constraints. This method has been
applied to value the impact of improved water quality on recreation values and public
health. It has also been the normal procedure adopted in regulatory command and
control mechanisms in which common standards are applied. For instance, the EU
assumes that benefits of environmental improvement are of equal value in different
areas of the EU. Yet, it should be noted that benefit transfers can only be as accurate as
the initial study.
The simplest type of benefit transfer is the unit day approach, where existing values for
activity days are used to value the same activity at other sites. The estimates are based
on expert judgment in combining and averaging benefit estimates from a number of
existing studies and “unit day values” may be adjusted for characteristics of the study
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site when they are applied. A more rigorous approach involves transferring a benefit
function from another study. The benefit function statistically relates peoples’
willingness to pay to characteristics of the ecosystem and the people whose values were
elicited. Adjustments can then be made for differences in these characteristics, thus
allowing for more precision in transferring benefit estimates between contexts.
12.1 Approaches for applying benefit transfer and assessing the validity of the attempts
12.1.1 Unit day values The ‘unit day value’ was applied by the US Forest Service in the 70s and 80s. Federal
guidelines in 1982 recommended a value of $6.10‐$17.90 per day for specialized
recreation (wilderness use, trout fishing, big‐game hunting, white water boating) and
$1.50‐$4.50 per day for general recreation (picnicking, swimming, small game hunting,
camping, boating). When applied to a new site, unit day values are adjusted on the basis
of the demand functions of site‐visitors. Demand depends on site attributes such as
congestion, accessibility and parking conditions, environmental quality; scenery, pests,
water, air, climate, socio‐economic characteristics of recreationalists, preferences, price,
and availability of substitute sites. None of these factors will be identical across different
sites. Expert judgment is required to assess what the benefits of a new site might be
from a range of possible values. The unit day values can be updated to account for
inflation and observed changes in price and income elasticities for recreation over time.
12.1.2 Transfer from HPM models
Benefit transfer from studies using hedonic price models may be applied by relying on
judgments of real‐estate agents’ to adjust the results. Yet, while some research
suggested close correlation between estate agents’ estimates of total house price and
estimates derived from a hedonic price model, other research revealed discrepancies.
12.1.3 Transfer from TCM models
Benefit transfer via the Travel Cost Model may be applied by transferring demand
functions from existing facilities, resembling closely the prospective facility in the type of
recreation provided. If the catchment areas of the two sites are mutually exclusive, then
multiplying the existing site coefficients by the values for independent variables of the
new site will give estimates of the number of visits and benefits attributable to the new
site. This approach is expected to yield more accurate results than simply applying an
average value of benefit per visitor day to the site. However, if the proposed facility is
situated within the catchment area of an existing facility, the existing demand function
should be applied to the new site as if unique. If the new consumer surplus exceeds the
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existing one, the net gain from having the new facility is the difference between the two.
The lack of homogeneity in product mix may be remedied by valuing the different
recreational activities separately and then aggregating, rather than developing a
demand curve for the site as a whole. Errors in Benefit Transfer via TCM may occur due
to several reasons, including, choosing the wrong functional form, selecting an
incomplete or inappropriate set of arguments, measuring arguments incorrectly such as
value of time, income, cost of access, measuring the dependent variable with error, and
the presence of substitute sites. The latter could be cancelled out if sites are randomly
distributed via a simulation model.
12.1.4 Transfer from CVM models
Benefit transfer from studies using contingent valuation models can be affected by ex
ante‐ ex post valuation perspective, whereby some estimates elicited after the
uncertainty about the good is removed are employed in an ex ante project appraisal.
Application may also be affected by scale or quantity value. For instance, if the new
good or policy is identical to the old and lies within the same market area, then it
represents an additional quantity of the good and should be valued less than the existing
good at the site. The sequential position of the supply of the good may also affect
application, particularly where goods are complements or substitutes. In this case, the
sequence in which a particular good is provided in relation to others determines its
value. Other factors influencing application of benefit transfer via CVM include
differences in attributes, as well as compositional effects, or when respondents have
difficulty in disentangling the structure of the substitution and complementary
interrelationships among attributes within the same holistic set.
12.1.5 Transfer from meta‐analysis
Benefit transfer may also be applied via meta‐analysis, where data‐based aids are used
to explain variations in estimated benefits across different studies with the aim of
applying past results to future resource policy decisions. This approach attempts to
assess environmental values by investigating the relationship between benefit estimates
(WTP), the features of the goods, and the assumptions of the models. It entails the
systematic application of statistical methods to assess common features and variations
across a wide range of prior studies. It is undertaken using a variety of techniques
encompassing qualitative and quantitative econometric methods. Yet, meta‐analysis is
relatively underdeveloped in the field of benefit transfer. However, it is important as a
means of investigating the factors and issues involved in the derivation and construction
of value. For example, Walsh et al. (1989) conducted a study to explain variations in net
economic benefits per activity day in terms of site, location, and methodological
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variables. For this purpose, 287 benefit estimates were compared: 156 based on TCM,
129 based on CVMs, and 2 based on HPMs. Some main findings included that omitting
travel time in TCM studies reduced benefit estimates by 34% and that Individual TCM
estimates were about 46% greater than Zonal TCM estimates using the same functional
form. Another finding was that if TCM was accepted as the standard for benefit
estimation, then CV estimates needed to be adjusted upwards by 20‐30%.
12.2 Standards of benefit transfer studies Different standards for benefit transfer may be applied in different contexts A higher
standard of accuracy may be required when the costs of making a poor decision are
higher. On the other hand, a lower standard of accuracy may be acceptable when costs
are lower, or when the information from the benefit transfer is only one of a number of
sources of information, or when it is used as a screening tool for the early stages of a
policy analysis.
The benefit transfer method is most reliable when the original site and the study site are
very similar in terms of quality, location, and population characteristics, when the
goods/services in both sites have similar characteristics, when the original valuation
study has been carefully conducted and used sound valuation techniques, and when
values in original study have not been valuated a long time ago since preferences change
over time.
Three tests have been suggested to determine the accuracy of benefit transfer:
− Comparing benefit transfer values with primary data values obtained from the policy
site
− Determining whether different populations have the same preferences for the same
non‐market good, after controlling for differences in socio‐economic characteristics
− Determining whether transfers are stable over time
When applying the benefit transfer methodology, the following steps should be
followed:
1. Identify existing studies or values that can be used for the transfer. There are a
number of valuation databases that can be useful.
2. Evaluate the existing values to determine whether they are appropriately
transferable. Consider whether the service being valued is comparable to the service
valued in the existing studies (site features, site qualities, availability of substitutes)
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and whether the characteristics of the relevant population are comparable in terms
of demographics and people’s preferences.
3. Evaluate the quality of studies to be transferred. The better the quality of the initial
study, the more accurate and useful the transferred value will be. This requires the
professional judgment of the researcher.
4. Adjust the existing values to better reflect the values for the site under
consideration, using available and relevant information. Supplemental data may
need to be collected through survey key informants, by talking to the investigators of
the original studies, getting the original data sets, or collecting some primary data at
the study site to use to make adjustments.
5. Estimate the total value by multiplying the transferred values by the number of
affected people.
12.3 Advantages and limitations
Advantages of benefit transfer include:
− The BT method is less costly than conducting an original valuation study
− The economic benefits are estimated faster than when undertaking an original
valuation study
− The BT method can be used as a screening technique to determine if a more
detailed, original valuation study should be conducted
− The method can easily and quickly be applied for making gross estimates of
recreational values
− The more similar the sites and the recreational experiences, the fewer biases will
result
Issues and Limitations associated with benefit transfer:
− Lack of accuracy, except for making gross estimates of recreational values, unless the
sites share all of the site, location, and user specific characteristics
− Unavailability of good studies for the policy or issue in question
− Difficulty in finding appropriate studies, since many are not published
− Reporting of existing studies may be inadequate to make the needed adjustments
− Difficulty in assessing the adequacy of existing studies
− Extrapolation beyond the range of characteristics of the initial study is not
recommended
− Benefit transfers can only be as accurate as the initial value estimate
− Unit value estimates can quickly become dated
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12.4 Illustration A park is being upgraded to provide additional recreational opportunities. A proposal is
to add a swimming beach to the lake in the park. The benefits of the new beach needs to
be explored, however, there is limited budget for the valuation study. For this purpose,
the Benefit Transfer Method is preferred because of the lack of a large budget for site‐
specific benefits studies and because values for recreational uses are relatively easy to
transfer.
The applied methodology is as follows:
Step 1
Identify existing studies or values that can be used for the transfer. Look for studies that
value beach use, specifically for lake beaches if possible. Assume that the researcher has
found two travel cost studies that estimated values for swimming at lake beaches.
Step 2
Decide whether the existing values are transferable by examining various criteria. The
existing values or studies would be evaluated based on several criteria, including:
− Is the service being valued comparable to the service valued in the existing
studies in terms of similar types of sites (lake beaches in a park), similar quality of
sites (water quality and facilities), similar availability of substitutes (the number
of other lake beaches nearby)
− Are characteristics of the relevant population comparable? Are demographics
similar? If not, are data available to make adjustments?
In the example, the first study is for a similar lake beach. The beach is also in a park, has
comparable water quality and facilities, and a similar number of substitute sites in the
area. It is located in an urban area, while the beach being valued is in a rural area. The
characteristics of visitors can be expected to be different for the two sites. The second
study is in a rural area with similar types of visitors, but the lake has many more
available substitutes.
Step 3
Evaluate the quality of studies to be transferred. In this example, the researcher has
decided that both studies are acceptable in terms of quality.
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Step 4
Adjust the existing values to better reflect the values for the site under consideration. In
this case, the sites valued in each of the existing studies differ from the site of interest.
The researcher might adjust the values from the first study by applying demographic
data to adjust for the differences in users. If the second study has a benefit function that
includes the number of substitute sites, the function could be adjusted to reflect the
different number of substitutes available at the site of interest. Because the beach will
be new, the researcher will need to estimate how many people will use the beach. They
may conduct a survey of park visitors, asking whether they would use a beach on the
lake, and how many times they would use it. Then, these visitation estimates can be
multiplied by the value per day for beach use (adjusted for differences in population and
site characteristics), to get an estimate of the economic benefits for the new beach.
12.5 Case‐application: Wetlands Restoration in Saginaw Bay, Michigan
The State of Michigan is considering plans to protect and restore coastal wetlands along
the southern shore of Saginaw Bay. The State must estimate the potential benefits from
protecting and restoring the wetlands. A survey asked people about their support for
restoring wetlands, but did not include a valuation question. The researchers used
benefit transfer methods to estimate the value of protecting and restoring wetlands
around the Bay.
A valuation study for proposed wetlands protection and restoration of Ohio’s Lake Erie
coastal wetlands was used for the benefit transfer. Researchers assumed that the values
estimated for Ohio were similar enough to be transferable to Michigan. The study
valued similar programs and quantities of wetlands to those proposed in Michigan.
However, coastal residents were not surveyed. The transfer of values from the Ohio
study to coastal residents in Michigan requires the assumption that coastal residents
have values similar to those of residents of other areas of the drainage basin.
Estimates of wetland values for Michigan, based on the Ohio study were $500 ‐ $9,000
per acre for residents of the drainage basin and $7,200 ‐ $61,000 per acre for residents
of the State of Michigan.
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THE STATED PREFERENCE APPROACH:
GROUP EXERCISES &
CASE‐STUDIES
Sessions 11 & 12
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SESSIONS 11 & 12
GROUP EXERCISES & CASE‐STUDIES
Air quality in Beijing
Wang, X.J.,Zhang, W., Li, Y., Yang, K. Z., and Bai, M. Air quality improvement estimation and
assessment using contingent valuation method: A case study in Beijing. Environmental
Monitoring and Assessment, 120, 153‐168, 2006.
Ecosystem services in Ejina China
Zhongmin, X. Guodong, C. Zhiqiang, Z., Zhiyong, S. and Loomis, J. Applying contingent valuation
in China to measure the total economic value of restoring ecosystem services in Ejina region.
Ecological Economics, 44, 345‐358, 2003
Environmental services in the Yaqui River Delta, Mexico
Ojedaa, M.I., Mayerb, A.S., and Solomon, B.D. Economic valuation of environmental services
sustained by water flows in the Yaqui River Delta. Ecological Economics, 2007. (In Press).
Sustainable development in Swedish coastal zone
Söderqvista, T., Eggertb, H., Olssonb, B., Soutukorvac, A., 2004. Economic valuation for
sustainable development in the Swedish coastal zone. SUCOZOMA research program.
Case‐studies
Doumani, F. 2007. Economic valuation of the coastal zone of the Mohafaza of North Lebanon:
Coastal zone municipal assessment, Coastal zone direct and indirect use value, Coastal zone
economic activity. Short and Medium Term Priority Action Program III. Integrated
Management of East Mediterranean Coastlines: Northern Lebanon, funded by The European
Commission. University of Balamand, Lebanon.
World Bank/ METAP, 2008. Climate Change Adaptation in the Water Sector in the Middle East &
North Africa Region: A Review of Main Issues. Presented at the Mediterranean Workshop on
Integrated Coastal Zone Management (ICZM) Policy, Alghero, Sardinia (Italy), May 19‐21,
2008.
World Bank/METAP, 2008. Carbon Finance Instrument to Improve Coastal Zone Solid Waste
Management. Presented at the Mediterranean Workshop on Integrated Coastal Zone
Management (ICZM) Policy, Alghero, Sardinia (Italy), May 19‐21, 2008.
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COST‐BENEFIT ANALYSIS
Session 13
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SESSION 13
13 COST BENEFIT ANALYSIS
Cost benefit analysis (CBA) is one of the most widely used techniques for project
appraisal in the public sector. It represents a framework for policy decision‐making. Its
first formal application was in 1768, to evaluate the net benefits of the Forth‐Clyde
Canal in Scotland.
13.1 Measures of benefit
The demand curve, also referred to as the marginal benefit curve, indicates the cost of
consuming one extra unit of good and provides an idea of changes in ‘utility’ or level of
satisfaction. The price one is willing to pay for a good depends on the satisfaction one
derives from consuming it, which is taken as a measure of benefits. For environmental
goods, the benefit or WTP exceeds the market price, if it exists (Figure 28). Valuation
methods discussed earlier are used to obtain estimates of WTP.
Total benefits = Total Revenue + Consumer Surplus
= Area of 0ECD + Area of ΔACE
Figure 28. Demand curve or marginal benefit curve
13.2 The concept of costs The cost in a cost benefit analysis refers to the opportunity cost (OC) to carrying out the
investment. Under perfect competition, the OC of a good is the same as the market
price of that good. For environmental goods, there is no market‐price; alternative
methods are to be used to measure the OC.
13.3 The concept of Net Social Benefits It is important to distinguish between a social CBA and a private CBA. A social cost
benefit analysis (SCBA) is conducted from a society’s perspective and is referred to as
economic analysis, while a private CBA is carried out from an individual investor’s view
point and is referred to as financial analysis. A project may be financially viable but
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socially undesirable. The objectives of a SCBA is to determine whether a project is
socially beneficial, whereby:
Net Social Benefit (NSB) = Benefits – Costs = WTP – OC > 0
If NSB > 0, then the state can use the surplus to compensate the losers.
13.4 Steps in Conducting an SCBA The steps in conducting a SCBA are outlined in Figure 29. The following sections will
detail the steps of a cost benefit analysis process along with a case‐study illustrating its
step by step application.
1. Define objectives and scope of project
2. Identify and screen alternatives
3. Identify and value the costs and benefits for the remaining alternatives
4. Calculate discounted cash flows and project performance criteria for each alternative
5. Rank the alternatives in order of preference
6. Conduct a sensitivity analysis and/or risk analysis for the preferred alternative(s)
7. Make a final recommendation Figure 29. Steps in a social cost‐benefit analysis
The case‐study involves the Bintuli Wastewater Treatment Project. The city of Bintuli in
the Republic of Kabastan is a center of commerce and industry. Main industries include,
metal manufacturing, coal extraction, chemical manufacturing, construction, paper
making and food processing. The value of industrial output was estimated at 200 million
USD in 1990 as compared to 16 million USD for agriculture. Quantities of domestic and
industrial effluents in water bodies increased significantly, whereby the total industrial
effluent amounted to 163,700 m3/day, with the total effluent including 271,700 m3/day
of domestic wastewater. Only 30% of industrial effluent was treated by the existing
Bintuli Wastewater Treatment Plant (WWTP), while no domestic effluent was being
treated. River courses in the city turned black and emitted unpleasant odors. Thus, it
was proposed to build a wastewater treatment facility with pumping stations and
drainage networks to treat 28% of industrial waste and the remaining domestic waste.
The treated effluent discharged in river to be used by industries and agriculture.
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13.4.1 Defining objectives and project scope The objectives are often specified by decision‐makers in the bureaucracy. Objectives
should be clear and unambiguous. In the case of the Bintuli WWT Project, the objectives
are to improve the health of the community and to increase economic activity by
improving wastewater treatment facilities in the city.
13.4.2 Identifying and screening alternatives All possible options for reaching objectives need to be listed, including the ‘do nothing’
option. A preliminary screening of alternatives should be conducted. In the case of the
Bintuli Wastewater Treatment Project, possible alternatives include:
− Maintaining the status quo
− Expanding the existing WWT facilities. This alternative was ruled out because it
uses outdated technology and would be difficult to maintain
− Building a new WWT facility
− Various locations and site options. Only one potential site considered in this
application
13.4.3 Identifying and valuing benefits and costs As mentioned earlier, costs and benefits differ for an SCBA as compared to private
investors. A benefit in an SCBA refers to an outcome resulting in an increase in an
individual’s utility and a cost in an SCBA refers to an outcome resulting in a decrease in
an individual’s utility. In identifying costs and benefits, it is important to note the
following:
− An incremental approach is adopted in assessing costs and benefits, which involves
first identifying and valuing costs and benefits of the project, and then compare
them with the situation to prevail without the project. The difference is the net
incremental benefit arising from the project. Only additional changes in costs and
benefits are considered, and not total costs and benefits.
− Sunk costs and benefits incurred before project commencement must be excluded.
Previous costs are not an opportunity cost as they do not represent a loss of future
income from an alternative use of resources.
− Transfer payments must be excluded. These include taxes, subsidies, loans, and debt
services, which do not result in an increase in net benefits. Taxes by foreign investors
should be included.
− Depreciation and interest are excluded from the cost in a SCBA. SCBA involves
discounting values of capital items at their opportunity costs. Thus, including
depreciation as a cost will result in double counting. The discount rate in an SCBA
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already takes into account the interest. Including interest as a cost will result in
double counting.
Costs and benefits are normally classified into primary costs and benefits related directly
to the project, and secondary costs and benefits. The latter arise from events and
activities triggered by the project and should be handled with care as they could
exaggerate estimates. The opportunity cost must be used as a guideline. Resources are
sometimes merely transferred from one part of the economy to another. Costs and
benefits may also be classified into market costs and benefits non‐market costs and
benefits. In the case of the Bintuli WWT Project, the identified costs and benefits are
presented in Table 25.
Table 25. Costs and benefits associated with the Bintuli WWT project
Costs Benefits Primary Investment
− Construction of a pumping station, office building, WWT facilities
− Purchase of equipment Operation and maintenance (O&M)
− Wages and salaries − Fuel and chemical costs − Other costs (project management,
preparation, training and commissioning
Primary Economic User charges Reduction in health costs and mortality
rates Reduction in costs of treating increasingly
polluted water supplies Increase in labor productivity due to
reduction in absence from work due to illness
Secondary Benefits to industry and agriculture from
using recycled water Additional revenues from re‐afforestation Increase in reed harvesting for the paper
mill industry
Valuing benefits and costs allows comparison between alternatives. The valuation
should be done according to the opportunity cost principle, whereby prices of inputs
that do not reflect their true value to the society are adjusted (shadow pricing).
Comparison of costs and benefits should focus on the “with vs. without” the project,
rather than “before vs. after” the project.
Valuing the costs involves first finding the market prices for the inputs and outputs. All
costs must be in present day or constant prices, whereby costs incurred over the project
lifetime must be valued at prices prevailing at the time of the project appraisal and the
annual costs must be assumed to increase at the inflation rate. The residual value should
be considered for assets with an economic life that exceeds the planning horizon or
project life. The economic life is the estimate of the duration of the operation of an asset
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before it requires refurbishment. The residual or salvage value of the asset must be
included as a cash inflow at the end of the planning horizon. This is calculated using
either a linear method or a diminishing value method. The linear method assumes that
the asset value declines linearly over time:
Residual value at time t is (1‐t/n)P
Where t = time; n = economic life; P = initial price
For example, consider an asset purchased at $100,000 and has an economic life of 20
years. At the end of the planning period of 15 years, its residual value is (1‐
15/20)*100,000 = $25,000
As for the diminishing value method, it assumes that the asset value declines by a fixed
proportion of the beginning of year value per annum:
Residual value at time t is (1‐1/n)t P
Where t = time; n = economic life; P = initial price
Other costs that need to be considered include:
− Land and pre‐existing building and plant, property that is already owned by
operating authority must be valued at its opportunity costs. Opportunity costs
should be current variations based on the most profitable alternative uses.
− When a project is to be constructed in stages, only the portion of investment and
operating costs to satisfy demand in the current planning horizon must be attributed
to the project.
− Working capital, which often constitutes 2% of the total capital outlays, must be
considered as cash outflow at the time when capital expenditures are made and cash
inflow at the end of the project.
− Operating costs, which include labor, utilities, supplies, repairs and maintenance,
equipment hiring and leasing, insurance and administrative overheads, are to be
estimated on an annual basis.
− Implicit costs should also be considered. These include opportunity costs and social
costs, such as the use of land, buildings, plants, already purchased by the local
authority, and time spent on the project by agency staff.
The costs incurred in the case of the Bintuli WWT Project, are summarized in Table 26.
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Table 26. Costs of the Bintuli WWT Project
Item Cost (million USD)
Investment costs Buildings and structures Equipment and supplies Total investment cost
3.42 13.15 16.57
O&M costs Electricity Salaries Chemicals Maintenance Other Total O&M costs
0.68 0.09 0.06 0.58 0.21 1.62
They are based on the following:
− All equipment and construction materials are imported and valued in US$
− Fuel and chemical supplies are adjusted by subtracting the government subsidies on
these items
− Because of high unemployment in the area, unskilled labor is shadow priced at 50%
of the wage rate
− Skilled labor valued based on annual salaries
− Construction is to take 3 years
Benefits of the Bintuli WWT project encompass revenues from user charges, and
economic benefits derived from the WWT plant, including, reduced mortality,
productivity gained from reduced morbidity, water treatment cost savings, sale of
recycled water, afforestation benefits, and reed harvesting.
User charges
User charges include both new charges and existing charges. New charges are based on
the principle of full cost recovery and estimated at 6.9 cents/m3. For a total of 54.75
million m3/year of effluent treated, the annual revenue is estimated at 3.78 million USD
per year. As for the existing charges, they are estimated at 0.61 million USD per year (for
a user charged of 6.9 cents/m3 and a total effluent of 11.4 million m3/year already being
treated). Thus, the net incremental sales revenue is estimated at 3.17 million USD by
year 6, when the new plant is at full capacity.
Recycled water
Regarding recycled water benefits, about 60% of the treated wastewater will be reused
for irrigation and industrial purposes. The opportunity cost of this recycled water is
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estimated at 10 cents/m3. The economic benefits from recycled water were therefore
estimated at 66,000 USD at year 4, rising to 3.29 million USD per year by year 8.
Afforestation
As for afforestation benefits, pine and hard wood species will be planted on 142.8 ha.
The net return per hectare was taken from estimates provided by Kabastani authorities
for experimental plots. These were reported at 689 USD/ha. Thus, the net benefits are
estimated at 10,000 USD in year 8 and a maximum of 100,000 USD by year 17.
Reed harvesting
Economic benefits are also expected from reed harvesting for the paper mill industry.
The Kabastani authorities have estimated the net returns to be 258.4 USD per ha.
Applying this figure to the projected area of 95.25 ha results in net annual benefits of
about 20,000 USD starting Year 6.
Reduced mortality benefits
Using World Bank estimates for Kabastan, mortality reduction from the project was
taken to be 0.005, 0.008, and 0.024 percent respectively, for the age categories of 15‐24
years, 25‐29 years, and over 60 years. On the basis of estimates for the number of
people in each category, the total number of deaths per year was calculated. Using the
estimated proportion of people employed in each age category and the mortality
reduction rates, an estimate of both employed and unemployed deaths was made.
Given the local annual wage of 620 USD (which includes housing subsidies and other
government payments) and assuming average working lives of between 5 and 45 years
for the three age categories, annual income losses avoided were estimated. For the
unemployed, a leisure value of half the annual wage was assumed. On the basis of this
estimate, the annual gains in leisure from saving deaths were estimated. Given that the
project will treat about half of Bintuli’s wastewater, only 50 percent of the potential
mortality and morbidity benefits were attributed to the project. The income benefits
from reduced mortality were therefore estimated at 10,000 USD in year 4, rising to
110,000 USD by the end of the project.
Productivity gains from reduced morbidity
A major social impact of the project is the reduction of the incidence of pollution‐related
illnesses and hence a reduction in worker absenteeism. These benefits were estimated
as follows. First, it was assumed that the current average number of days lost per
worker per year as a result of illness is 3 days. Next, using the employment statistics,
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potential productivity losses avoided per worker per annum were estimated to be about
180,000 USD in year 4, rising to about 1.8 million USD by the end of the project.
Water treatment cost savings
As indicated above, the benefits of the project include the avoided cost of treating
polluted water. An estimate of 0.002/m3 of water treatment cost savings estimated by
the World Bank was assumed. The estimated benefits of water treatment cost savings
was estimated to be 110,000 USD per year,
The incremental economic benefits derived from the project were estimated at 96,000
USD in year 4, rising to 5.38 million USD by the end of the project (Table 27).
Table 27. Incremental economic benefits of Bintuli WWT project (million USD)
Year Recycled water
Afforestation Reed harvesting
Reduced mortality
Reduced morbidity
Water treatment cost savings
Incremental economic benefits
1 2 3 4 0.66 0.01 0.18 0.11 0.965 0.99 0.02 0.38 0.11 1.506 1.64 0.02 0.03 0.57 0.11 2.377 2.63 0.02 0.05 0.76 0.11 3.578 3.29 0.01 0.02 0.06 0.95 0.11 4.449 3.29 0.02 0.02 0.06 1.00 0.11 4.5010 3.29 0.03 0.02 0.06 1.06 0.11 4.5711 3.29 0.04 0.02 0.07 1.11 0.11 4.6412 3.29 0.05 0.02 0.07 1.17 0.11 4.7113 3.29 0.06 0.02 0.07 1.23 0.11 4.7814 3.29 0.07 0.02 0.08 1.30 0.11 4.8715 3.29 0.08 0.02 0.08 1.37 0.11 4.9516 3.29 0.09 0.02 0.09 1.44 0.11 5.0417 3.29 0.10 0.02 0.09 1.51 0.11 5.1218 3.29 0.10 0.02 0.10 1.59 0.11 5.2119 3.29 0.10 0.02 0.10 1.68 0.11 5.3020 3.29 0.10 0.02 0.11 1.76 0.11 5.39
13.4.4 Calculating discounted cash flows and project performance criteria
Once the costs and benefits with and without the project have been identified and
valued in monetary terms, the analyst is now ready to make a decision as to which
alternative to accept or reject. This requires reducing future streams of benefits and
costs to their present values to enable comparisons to be made between alternatives.
Given a stream of benefits (B0, B1…Bn) and a stream of costs (C0, C1…Cn), the Net Present
Value (NPV) is calculated using the following equation:
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∑= +
−=
+
−+
+
−+
+
−+−=
n
t nrnCnB
nrnCnB
r
CB
r
CBCBNPV
0 )1()1(...2)1(
221
1100
where r = discount rate
The discount rate in a SCBA reflects society’s preferences between present and future
consumption. A high discount rate implies that society has a stronger preference for
present consumption over future consumption, while a low discount rate implies that
society has a stronger preference for future consumption over present consumption.
The choice of a discount rate is often controversial. Environmentalists argue against high
discount rates, which they believe are associated with environmental degradation.
Economists tended to use long‐term interest rates on government bonds as a measure
of opportunity cost of capital. For example, in the US, a rate of 10 percent is used and in
Australia, a rate of 8 percent is used. The discount rate must be a real rate. That is, the
nominal interest rate minus the inflation rate.
Another critical factor in computing the discounted cash flows is the planning period or
horizon. The planning period varies with nature of project. It should be determined by a
period within which estimates are made with a certain degree of confidence and it
should correspond to the economic life of the project.
Project performance criteria include the following, NPV, benefit‐cost ratio (BCR), internal
rate of return (IRR), and payback period. The BCR is the ratio of the present value of
project benefits to the present value of the project costs. It is calculated as follows:
∑=
+
∑=
+=
++
++
++
++
++
++
= n
tnrnC
n
tnrnB
nrC
r
Cr
CC
nrB
r
Br
BBBCR
n
n
0)1(
0)1(
)1(...2)1(10
)1(...2)1(10
21
21
The payback period is defined as the number of years required for a project to recover
its costs. In general, it discriminates against projects with high capital expenditures and
long‐term benefits. It is not recommended as a measure of project worth.
The IRR is the discount rate at which the present value of project benefits equals the
present value of project costs. It represents the maximum interest rate at which a
project could recover the investment and operating cost and still break even. It is
difficult to calculate and may not exist or may not be unique. A trial and error method
112
must be used. The IRR can be found by finding the discount rate at which the following
equation holds:
0)1(
...2)1(22
111
00 =+
−+
+
−+
+
−+−
ninCnB
i
CB
i
CBCB
The rule is to accept a project when NPV ≥ 0, BCR ≥ 1, and IRR > the social opportunity
cost of capital. The NPV is the most preferred criterion because it provides an estimate
of the size of the Pareto improvement. If two or more projects have NPVs > 0, then IRR
can be used to rank them.
A real rate of 12% was chosen as a discount rate to produce the discounted cash flows.
This rate is the average of the published World Bank discount rates for the past 10 years.
A planning period of 20 years was used based on advice received from engineers. Based
on the calculations shown in Table 28, the NPV at the 12% discount rate is estimated at
12.08 million USD and the IRR is 21 percent, which is above the opportunity cost of
capital of 12 percent. Therefore, it can be concluded that the Bintuli Wastewater
Treatment Project is economically viable.
Table 28. Incremental net benefits of Bintuli WWT project (million USD)
Year Incremental
economic costs Incremental sales
revenue Incremental
economic benefitsIncremental net
benefits 1 2.01 ‐2.01 2 8.45 ‐8.45 3 6.11 ‐6.11 4 2.42 1.91 0.96 0.45 5 1.62 1.91 1.5 1.79 6 1.62 3.17 2.37 3.92 7 1.62 3.17 3.57 5.12 8 1.62 3.17 4.44 5.99 9 1.62 3.17 4.50 6.05 10 1.62 3.17 4.57 6.12 11 1.62 3.17 4.64 6.19 12 1.62 3.17 4.71 6.26 13 1.62 3.17 4.78 6.33 14 1.62 3.17 4.87 6.42 15 1.62 3.17 4.95 6.50 16 1.62 4.43 5.04 7.85 17 1.62 4.43 5.12 7.93 18 1.62 4.43 5.21 8.02 19 1.62 4.43 5.30 8.11 20 ‐0.02 4.43 5.39 9.84
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13.4.5 Conduct a sensitivity analysis and/or risk analysis In economics and business, a distinction is made between risk and uncertainty. Risk is
the potential outcome whose magnitude and probability of occurrence are known or
can be determined. Uncertainty refers to a situation where the magnitude of the
outcome may or may not be known and the probability of occurrence is unknown. In
practical situations, however, it is difficult to define precisely the probability of an
occurrence. Therefore, the distinction between the risk and uncertainty may not be
clear‐cut. Common methods for accounting for risk and uncertainty include, sensitivity
analysis, break‐even analysis, cross‐over values, and risk analysis.
Sensitivity analysis is used to assess the possible impact of uncertainty by posing ‘what
if’ questions. It highlights the critical factors affecting the project’s viability. Parameters
usually subjected to sensitivity analysis include discount rate, length of project planning
horizon, different timing of the project’s operation, changes in the capital outlays,
changes in the price of non‐market goods, and changes in social and environmental
benefits and costs. Sensitivity analysis is carried out by recalculating project
performance criteria using a range of values for the uncertain parameter. The project
performance criteria commonly used are NPV and IRR. Sensitivity analysis is conducted
by first determining a realistic range of values for the variables that are subject to
uncertainty. For example, capital cost ± 30 percent, O&M costs ± 30 percent, and
product prices ± 30 percent. Then, the effect of possible changes on the project
selection criteria are calculated while varying one variable and holding the others
constant. Finally, the economic viability of the project is reconsidered in light of the
performed calculations.
The break even value of a given project is the value of the discount rate at which the
NPV is zero or the value at which the entire costs will be recovered. On the benefit side,
if a variable appears to be higher than the break‐even level, this increases confidence in
the project’s viability. On the cost side, an estimate that is lower than the break‐even
level means that the project is likely to be economically viable.
The switching or cross‐over value of a project performance criterion (e.g. NPV) is the
discount rate at which the ranking of two projects changes. This method is
recommended when considering only one uncertain variable.
In the case of the Bintuli WWT project, a sensitivity analysis was conducted. For this
purpose, critical, uncertain variables were chosen for analysis, including changes in
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capital and O&M costs, and changes in the net incremental economic benefits (Table
29).
Table 29. Sensitivity analysis for the Bintuli WWT project
Change in net economic benefit
Changes in capital costs
‐30% ‐15% 0% +15% +30%
‐30% 23 25 27 29 31
‐15% 20 22 24 25 27
0% 17 19 21 23 24
+15% 15 17 19 21 22
+30% 14 16 17 19 20
Changes in O&M costs
‐30% 19 21 23 25 26
‐15% 18 20 22 24 25
0% 17 19 21 23 24
+15% 16 18 20 22 23
+30% 15 17 19 21 22
The sensitivity analysis indicated that IRR is robust whereby a 30% decline in economic
benefits reduced IRR to 17% assuming no change in capital and O&M costs. Similarly, a
30% increase in capital costs assuming no change in economic benefits reduced the IRR
to 17%. Furthermore, a 30% increase in operating costs reduced IRR to 19%. Thus, it can
be concluded that the estimate is insensitive to large changes in the projected economic
costs and benefits.
Risk analysis is suitable in the cases where the values of several parameters are
uncertain. Risk analysis involves the use of the probabilities of occurrence of the key
variables as weights to recompute the project performance criteria. This is carried out
using special purpose computer packages such as ‘@RISK’, which generates probability
distributions for NPV and IRR. A major difficulty in risk analysis is obtaining probability
estimates. Common probability distributions include uniform distributions, which
require minimum and maximum estimates, and triangular distributions, which require
most pessimistic (minimum), most likely (mode), and most optimistic (maximum)
estimates. Beta distributions may also be used.
Finally, based on the cost‐benefit analysis conducted for the proposed Bintuli WWT
project, it can be concluded that water pollution in Bintuli is a serious problem and that
project implementation is urgently required to protect the health of the community and
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reduce environmental degradation. The proposed project is expected to yield
substantial economic benefits. The IRR was estimated at 21% and sensitivity and risk
analysis indicated that the estimate is insensitive to costs and benefits. Therefore it is
recommended to implement the project with the institution of a good monitoring
program.
13.5 Cost Cost Effectiveness Analysis
Although CBA is a useful tool to assist decision‐making, it may not be a suitable
approach in all situations. When it is not possible to value a project's major benefits in
dollar terms, or when two projects have similar economic benefits, then a cost
effectiveness analysis (CEA) may be used. For example, if the decision problem is to
choose between building two hospitals, a CEA would be appropriate since the social
benefits in either case would be similar. Both CBA and CEA are based on the principle of
economic efficiency and therefore do not consider equity or distributional issues. That
is, a project is deemed to be socially desirable if the gainers can potentially compensate
the losers. They both do not deal with the issue of who the losers are or how they
should be compensated. Cost effectiveness analysis looks only at financial costs. A CEA takes the objective as
given, and then works out the costs of the alternative ways of achieving that objective.
The decision on whether to use CEA instead of CBA will depend on a number of factors
including the following: − The size and complexity of the project;
− The extent to which there are quantifiable benefits; and
− The extent to which the benefits can be valued in monetary terms.
For large‐scale projects CBA is the preferred approach because it enables the major
items of costs and benefits to be identified and valued and discounted cash flow
performance criteria to be computed. However, in cases where the major benefits
cannot be quantified in dollar terms, CEA is the preferred approach. CEA is also
appropriate in a case where the choice is between, say, two wastewater treatment
options with the same outputs or service levels but the difference is in, say, location.
Most of the foregoing discussion on CBA applies generally to CEA. Unlike CBA, CEA does
not have absolute criteria by which to judge the economic viability of projects. CEA is
therefore not recommended when a decision about the level of output or service to be
provided is at issue.
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13.5.1 Conducting a Cost‐Effectiveness Analysis The steps involved in carrying out a CEA are similar to those for a CBA. They include:
1. Project definition
2. Choice of method of analysis
3. Identification and valuation of costs and benefits
4. Discounted cash flow analysis
5. Calculation of measures of effectiveness, and
6. Sensitivity analysis
THE VALUE OF LIFE AND HEALTH
Session 14
Region
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SESSION 14
14 THE VALUE OF LIFE AND HEALTH
Environmental changes, particularly increased pollution, often result in adverse impacts
on human health, which can be translated into monetary values. In estimating monetary
values of changes in human health associated with environmental changes, two links
need to be established (Figure 30).
Figure 30. The process of health impact valuation
The first link is between environmental change and change in health status. This involves
measuring health impacts and establishing dose‐response relations and calculating the
burden of disease (BoD) through disability adjusted life years (DALYs). The second link is
between the change in health status and its monetary equivalent, which involves
establishing willingness to pay values.
14.1 Measuring health impacts
Health impacts of pollution may be well recognized. Air pollution affects human health
in a variety of ways, from itchy eyes and chest discomfort, to chronic bronchitis and
asthma attacks. Inadequate water supply and sanitation affects human health through
diarrhea, intestinal nematodes, and other diseases. Health impacts are measured
through various types of studies including, epidemiology and field studies, human
clinical studies, and laboratory and toxicology studies.
14.1.1 Epidemiology and field studies
Epidemiological and field studies involve estimating a statistical relationship between
the frequencies of specific health effects observed in a study population and measured
levels of pollutants. There are two main types of epidemiological studies: the cohort
studies and the population studies. Cohort studies analyze the incidence of health
effects in a sample of identified individuals usually selected specifically for the study.
They allow better control of risk factors since characteristics of individuals are well
known. Population studies rely on the data available for the population as a whole
rather than tracking the effects on specific individuals. These studies are readily
available and cost‐effective.
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Advantages of epidemiology and field studies include:
− Providing sufficient information to infer a concentration‐response function used to
predict a change in the number of cases of a given health effect and pollutant
concentration
− Defining, health effects in terms of factors that can be directly related to perceived
welfare, including risks of premature death and days with noticeable symptoms.
The main limitation associated with such a type of studies is the uncertainty about
whether the causal factors for the observed association with health effects has been
fully and accurately specified.
14.1.2 Human clinical studies
Human clinical studies examine the response of human subjects to pollutant exposure in
a controlled laboratory setting. Such studies can provide evidence of causation because
confounding variables are well controlled. They have the advantage of providing more
accurate dose‐response information. However, the application of human clinical studies
is limited to considerations of short‐term reversible health effects that can be induced
on purpose in human subjects and it requires assumptions to link human exposure in
real life to health effect observed in a laboratory setting.
14.1.3 Laboratory and toxicology studies Laboratory and toxicology studies use animal subjects and human tissue or cells to study
biological responses to pollutants in a controlled laboratory setting. They provide
important information about specific biological pathways and mechanisms by which
pollutants cause harm to living organisms. Laboratory and toxicological studies has the
advantage of well‐controlled pollutant exposures and reduced variations in confounding
factors. In addition, they can consider both long term and short term exposures.
However, analysis and assumptions are required to link human exposure in real‐life to
laboratory exposure. Furthermore, these times of studies are associated with
uncertainty in extrapolating data from animal subjects to human populations. They
sometimes focus on health effects that are difficult to interpret in terms of specific
symptoms
The aim of these types of studies is to establish dose‐response relations (DRR) linking
environmental variables with observable health effects, particularly in the case of air
pollution. DRRs correlate mortality and morbidity outcomes for susceptible population
groups with ambient concentration of a given air pollutant. Most of the conducted
studies have focused on mortality effects. For instance, chronic exposure to PM results
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in exacerbated respiratory illness, pulmonary disease and cardiovascular disease,
culminating in premature mortality. Similarly, acute exposure to PM affects individuals
in a weakened state or especially susceptible, resulting in premature mortality. An
example of estimated DRRs for air pollutants are presented in Table 30.
Table 30. Estimated increments in annual health effects associated with increments in air pollutants
(IDIEN, 1998)
Outcome PM10
(10μg/m3
)
SO2
(10μg/m3) Ozone(pphm)
Lead (1 mg/m3)
NO2
(pphm)
Premature mortality (% change) 0.96 0.48
Premature mortality/ 100,000 6.72
Respiratory hospital admissions/100,000 12 7.7
Emergency room visits/100,000 235.4
Restricted activity days/person 0.575
Lower respiratory illness/child 0.016
Asthma symptoms/asthmatic 0.326 0.68
Respiratory symptoms/person 1.83 0.55
Chronic bronchitis/100,000 61.2
Minor restricted activity days/person 0.34
Respiratory symptoms/1,000 children 0.18
Respiratory symptoms per adults 0.1 0.1
Eye irritations/person 0.266
14.2 Burden of Disease
A BoD study aims to quantify the burden of premature mortality and disability for major
diseases or disease groups. It uses a summary measure of population health (DALY) to
combine estimates of the years of life lost and years lived with disability. Data are
broken down by age, sex, and region. The Global Burden of Disease (GBD) constituted
the most comprehensive set of estimates of mortality and morbidity yet produced
(Murray and Lopez, 1996). The World Health Organization (WHO) now regularly
develops BoD estimates at regional and global level for a set of more than 135 causes of
disease and injury. National BoD studies involve obtaining country‐specific estimates for
input to national policy. The following section discusses the calculation of DALYs, the
unit measures of BoD.
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14.2.1 Disability Adjusted Life Years The DALY measures health gaps as opposed to health expectancies, using time
measures. It estimates the difference between a current situation and an ideal situation
where everyone lives up to the age of standard life expectancy. DALY is based on two
key value choices:
− How long should people in good health expect to live?
− How should we compare years of life lost through deaths with years lived with poor
health or disability of various levels of severity?
DALY combines in one measure the time lived with disability and the time lost due to
premature mortality:
DALY = YLL + YLD
Where:
YLL = years of life lost due to premature mortality
YLD = years of life lost due to disability
YLL corresponds to the number of deaths multiplied by the standard life expectancy at
the age at which death occurs:
YLL = N × L Where:
N = number of deaths
L = standard life expectancy at age of death in years
YLD is estimated by measuring the incidence of disability and the average duration of
each disability. The number of disabilities is multiplied by the average weight factor that
reflects the severity of the disease on a scale from 0 (perfect health) to 1(dead). Thus
the Years of Life with Disability (without applying social preferences):
YLD = I × DW × L
Where:
I = number of incident cases
DW = disability weight
L = average duration of disability (years)
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Disability weights quantify societal preferences for different health states. It is important
to note that disability weights DO NOT represent the lived experience of any disability or
health state and they DO NOT imply any societal value for the person in the disability.
For example, a weight for paraplegia of 0.57 does NOT mean that the person in this
health state is half dead, or that the person experiences life as half way between life and
death, nor that society values them less as a person compared to healthy people. It
rather means that society judges a year with blindness (0.43) to be preferable than a
year with paraplegia. It also means that society would prefer living for 3 years followed
by death (1.7 lost healthy years) than have one year of good health followed by death (2
lost healthy years). Disability weights for various diseases calculated by Murray and
Lopez (1996) are presented in Table 31.
Table 31. Disability weights (Murray and Lopez, 1996)
Disease Mean disability weight
Disease Mean disability weight
AIDS 0.50 Asthma, cases 0.10
Infertility 0.18 Deafness 0.22
Diarrhea disease, episode 0.11 Brain injury, long term 0.41
Measles episode 0.15 Spinal cord injury 0.73
Tuberculosis 0.27 Sprains 0.06
Malaria episode 0.20 Burns (> 60%) long term 0.25
Cancer, terminal stages 0.81 Congestive heart failure 0.32
Parkinson disease cases 0.39 Benign prostatic hypertrophy 0.04
Alzheimer disease cases 0.64
Other social values that could be taken into account when calculating DALYs are age and
time. Age weights are sometimes used whereby a year of healthy life lived at younger
and older ages was weighted lower than for other ages. This was based on the fact that
various studies have shown a broad social preference to value a year lived by a young
adult more than a year lived by a young child or lived at older ages. However, age
weights in DALYs are controversial. Time discounting may also be used whereby the net
present value of lives lost is estimated using a 3% discount rate. This is based on studies
showing that people prefer a healthy year of life immediately, rather than in the future.
However, it is important to note that BoD studies may or may not include time
discounting and age weights depending on local preference
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Calculating DALYs with a 3% discount rate:
)1( e rL
rNYLL −−=
Where:
N = number of deaths
L = standard life expectancy at age of death
r = discount rate (0.03)
)1( e rL
rLDWIYLD −−
××=
Where:
I = number of incident cases
DW = disability weight
L = duration of disability in years
r = discount rate (0.03)
Calculating DALYs with age weight and a 3% discount rate:
)1(1]]1)([]1))(([[)(
)())((2 e rLaraLr
ra
rKareaLre
rKCeYLL −+−++− −
−+−+−−−++−
+= ββ
βββ
Where:
a = age of death (years)
r = discount rate (0.03)
β = age weighting constant (Ex: β = 0.04) K = age weighting modulation constant (Ex: K =1)
C= adjustment constant for age‐weights (Ex: C = 0.1658)
L = standard life expectancy at age of death (years)
)}1(1]]1)([]1))(([[)(
{ )())((2 e rLaraLr
ra
rKareaLre
rKCeDWYLD −+−++− −
−+−+−−−++−
+= ββ
βββ
Usually DALYs adjusted for age and time are calculated using MS Excel spreadsheets,
Examples of DALY spreadsheets are presented below.
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Figure 31. Calculating YLL for diarrhea
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Figure 32. Calculating YLD for Alzheimer
14.3 Valuating Health Impacts
After measuring the health impacts of pollution, the established DRRs and/or DALYs
need to be monetized. Several methods may be used to value health impacts using the
WTP approach (Figure 33). Many of these methods have been discussed in detail in
previous chapters and thus will only be mentioned briefly.
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Figure 33. Methods for valuing health impacts
14.3.1 The Human Capital Approach (HCA)
The HCA considers individuals as units of human capital that produce goods and services
for society. It values human life and time spent ill or recovering using forgone earnings.
As such, it measures loss of productivity resulting from an individual’s death (Work Loss
Days‐WLD) and injury (Restricted Activity Days‐RAD)
HCA = (# of Life Years Lost due to premature death or due to illness) × (Average Wage Rate)
WLD and/or RAD are either estimated for specific individuals in a detailed study or for
average individuals. The latter is most commonly applied. HCA usually provides a lower‐
bound estimate, as it does not account for pain and discomfort accompanying a certain
illness.
HCA values calculated are dependent on income, skill level, and country of residence.
Accordingly, this method is considered as the most difficult and controversial aspect of
valuing health effects associated with environmental changes. Table 32 presents the
human capital and mortality costs by age in the US for the year 1992. Cost estimates are
based on life‐expectancy at the time of death and include labor‐force participation rates,
average earnings, the value of home‐making services, and a 6% discount rate.
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Table 32. Human capital and mortality cost by age in the US
Age group (yrs) Life years lost Mortality cost (1992 US$)
< 5 75 502,421
5‐14 68 671,889
15‐24 57 873,096
25‐44 42 785,580
45‐64 25 278,350
65+ 10 22,977
The following steps need to be followed when applying the HCA
1. Specify the type of economy for the population of interest
2. Specify the characteristics of the economy for the population of interest
3. Specify the family and community structure
4. Specify the unit of analysis
5. Specify the desired measure of productivity changes
6. Estimate the maximum loss in productive time as a result of the health outcome.
This requires information as to the groups of patients that are working and requires
decisions about value of time of children and retired people
There are various problems associated with the HCA. This approach faces difficulty in
accurately estimating forgone earnings, since employee’s compensation includes
pension plans, health insurance, flexible hours, and not just wages. Furthermore, the
HCA does not provide information about the individual’s WTP to reduce probability of
loss of life. It also does not measure net contribution to society. It assumes full
employment and no substitutability of labor. It also assumes a dominant cash economy
where market prices exist, which is not the case in developing countries. HCA also
ignores non‐market activities important to individuals. It undervalues retired people,
children, and home‐makers, and it does not value pain and suffering, the individual’s
own well‐being and preferences, and the sentiments of the society. Finally, the
estimated value using the HCA highly depends on the discount rate used. The higher the
discount rate, the lower the economic value of children.
Several issues need to be considered when applying the HCA:
− Uncertainty about the number of days or years an individual actually takes off work
which requires an assumption about life‐expectancy
− Productivity estimations do not consider the declining economic value as people get
older
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− WLD and RAD depend on the individual and how he/she responds to symptoms and
illness
− Lack of labor market data in many developing countries
− Data cannot be generalized between populations and countries as values are highly
dependent on local factors
14.3.2 Cost of Illness (COI) Approach The cost of illness approach involves measuring two types of costs, (1) the direct costs or
the costs of medication, hospitalization, and doctors’ visits, and (2) the indirect costs or
the forgone labor earnings due to days spent in bed, days missed from work, and days
when activity was restricted due to illness. The latter are calculated following the HCA
approach mentioned earlier.
The COI approach is considered a useful economic tool as it indicates the direction and
magnitude of the economic flows resulting from health shocks to the economy. It is
easily understood and often readily available being based on available market and
expenditure data. However, COI provides an estimate of an individual welfare loss.
Direct expenditures do not correspond to a drop in income or consumption for the
economy as a whole, but constitute a redirection of economic activity, with some
sectors benefiting from increased activity. Furthermore, COI does not provide a direct
measure of disease severity. Direct medical expenditures are influenced by income
distribution, whereby increased income is accompanied with increased consumption of
health care. Thus direct medical expenditures reflect the ability of current medical
techniques to treat the disease under consideration. For example, treatment of malaria
is expected to generate less expenditure than treatment of cold because the former has
few remedies as compared to the latter. The COI not only measures disease severity but
also the population’s education, skill level, income, insurance coverage, types of medical
interventions currently available, etc.
There are various issues pertaining to its application, including:
− Difficulty to disaggregate hospital payments, including drugs administered on the
premise and salaries paid to health professionals and staff
− Inaccuracies in hospital diagnostic data and the fact that expenses might not be
attributed to the correct illness
− A number of illnesses may be grouped under one diagnostic code making it hard to
decipher individual expenses
− Large data sets assume the same charge for all types of physician services. For
example, a visit for a routine checkup does not cost the same as a visit for cancer
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− Treatment of multiple conditions where all expenses are allocated to the patient’s
primary condition
The following steps are recommended when estimating the direct cost of medical care
(WASH, 1991):
− Estimate the proportion of those affected at each level of severity of the disease
− Estimate the proportion of those desiring treatment and who have access to
treatment
− Specify the process of treatment for each level of severity of the disease
o Resource use
o Number of inpatient days
o Outpatient visits
− Estimate the unit costs of resources used for treatment and the side effects for each
level of severity of the disease taking into account that many fixed costs are not
affected by reductions in the use of the health service
− Estimate total treatment costs for each level of severity of the disease without
intervention
− Determine the proportion of the costs that can be avoided in the short‐ and long‐run
− Determine the direct costs that would have been avoided
14.3.3 Hedonic Pricing Hedonic pricing involves the valuation of incremental morbidity or mortality by
identifying wage differentials due to risk differences. It is based on the theory that
workers have to be paid a premium to undertake jobs that are inherently risky, which
can be used to estimate the implicit value individuals place on sickness or premature
death. It assumes that there is a fixed supply of jobs and a freely functioning job market
where individuals choose jobs based on perfect information and with no mobility
restrictions. The value of a statistical life in the US, estimated using the hedonic pricing
method ranges between 1.9‐10.7 million USD (1990 dollars).
In the HPM, calculation are based on the assumptions that
− The only difference between two jobs is the level of risk
− The attitudes to risk are identical between individuals
− Labor markets are competitive
− Individuals only take risky jobs because they pay more
− Individuals correctly perceive risk
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The general hedonic wage equation is:
P = P(J,R,S)
Where:
P = payment rate for a given job
S = vector of skills required to do the job
J = vector of other job‐related attributes (working hours, holiday, sickness benefits)
R = risk of death
The partial differential of this function with respect to R gives an estimate of the
additional payment required by individuals to accept a marginal increase in the chance
of death.
Issues and limitations associated with HPM:
− Faces difficulty in assessing an objective measure of the risk of death
− Contains a high degree of uncertainty
− Requires considerable data sets for regression analysis, containing data on all
relevant and confounding variables
− Results are not transferable between countries due to differences in attitudes to risk
and incomes
14.3.4 The Contingent Valuation Method
The CVM has a great potential for eliciting WTP for environmental health interventions,
including developing countries. One main advantage of the CVM is that questions can be
structured so that respondents can value only the benefits of interest. As such, health,
amenity, and non‐use benefits can be separated for the same environmental health
intervention. Accordingly,
Total Benefit/Cost
= ∑WTP of all concerned members of the society
= Value of Statistical Life (VOSL)
Main steps in a CVM process include:
1. Define the sample of respondents
2. Give respondents a detailed description of the hypothetical market and the good
being evaluated
3. Ask respondents the price they are willing to pay to receive the amenity
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4. Collect information on demographics and socio‐economic characteristics of
respondents
5. Estimate aggregate WTP
Advantages of a CVM
− Can take into account non‐use values
− Can be designed to include only the variables or characteristics of the market
relevant to the objective of the study
− Allows individuals to consider the true costs to themselves of a particular injury or
illness
− CVM results are repeatable in terms of similarity in results across different settings
and using a test‐retest methodology
Problems associated with CVM
− Does not require cash transactions
− Biases: Strategic, design, hypothetical, etc.
− Survey responses cannot be verified except through comparison with actual
behavior following survey
− WTP vs. WTA
− Short time given to respondents to think about the answer
− In developing countries, questionnaires need to be adapted carefully and trained
researchers are required to administer the surveys
Issues to consider when conducting a CVM study:
− WTP questions should be clear and unambiguous
− Respondents must be familiar with the valued commodity
− Health risk studies involving common, mild illnesses have a greater chance of being
understandable, meaningful, plausible, than severe, rare diseases
− Respondents should have prior valuation/ choice experience with respect to
consumption levels of the commodity in order to give it well‐formed values
14.3.5 Benefit transfer Values may be adopted from the other countries by adjusting for per capita income as
follows:
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Pe r capita incom e of country i = X i
⇒ Income ra tio Xj/X i
Pe r capita incom e of country j = Xj
⇓
V alue of mortality or morbi dity outcome in country i = Y i
⇒ Multip ly Y i by Xj /X i ⇒ Value of morta lity or morbid ity outcome in country j = Yj
14.3.6 Disability Adjusted Life Years The VOSL obtained from wage differential and contingent valuation studies may be
linked with the corresponding number of DALYs lost in a specific study and so estimate
the implicit value per DALY.
The cost of a DALY lost may be valued by two approaches:
1. DALY (yrs) × GDP/capita (USD/year)
This is based on the rationale that the economic value of a year lost to illness or early
death is the productive value of that year, which is approximated by GDP per capita. It
usually represents the lower bound estimate and has nothing to do with the non‐
economic value of life in general
2. DALY (yrs) × WTP for mortality reduction
This is based on the WTP by an individual to reduce the risk of death. Valuations arrived
at, in studies in the United States and Europe that apply WTP, are substantially higher
than the GDP per capita approach (at least for adults).
Finally recommended methods of valuation for health related benefits are summarized
in Table 33.
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Table 33. Recommended methods for valuation of health related benefits
Types of benefits Market value(COI, HCA)
Avertive expenditure
Hedonic pricing
Contingent valuation
Improved health‐related quality of life
Improved life expectancy
Medical cost avoided ( )
Reduced time spent in care ( )
Reduced travel expenses to care ( )
Reduced avertive expenditure ( ) ( )
Increased productivity ( )
Reduced sick leave ( )
THE VALUE OF LIFE AND HEALTH: CASE‐STUDIES
Session 15
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SESSION 15
CASE STUDIES
These case‐studies will be distributed as handouts to the workshop participants.
Drinking water quality in Lebanon
El‐Fadel, M., Maroun, R., Semerjian, L., and Harajli, H. A health‐based socio‐economic
assessment of drinking water quality, Management of Environmental Quality, 14, 3, 353‐
368, 2003. (Literati Awards of Excellence 2004)
Emissions from the cement industry, Lebanon
El‐Fadel, M., Kobrossi, R., and Metni, M. Economic benefits of reducing SO2 emissions from the
cement industry, Journal of Environmental Assessment Policy and Management, 5, 1, 99‐
120, 2003.
Particulate matter in urban areas, Lebanon
El‐Fadel, M., Massoud, M. Particulate matter in urban areas: Health based economic
assessment, The Science of Total Environment, 257, (2‐3) pp. 133‐146, 2000.
Lead phase‐out in Lebanon
Hashisho, Z. and El‐Fadel, M. A case study in socio‐economic benefits of the phase‐out of leaded
gasoline, Environmental Management and Health, 12, 4, 389‐406, 2001.
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THE VALUE OF LIFE AND HEALTH GROUP EXERCISES
Sessions 16 & 17
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SESSIONS 16 & 17
GROUP EXERCISES
Urban air pollution from particulates in selected MENA countries
Sarraf, M., Larsen, B., and Owaygen, M. 2004. Cost of environmental degradation: The case of
Lebanon and Tunisia. Environment Department Paper No. 97, The World Bank, Washington
D.C.
World Bank, 2002. Cost Assessment of Environmental Degradation in the Arab Republic of Egypt.
Sector Note. Report No. 25175 –EGT. Rural Development, Water and Environment
Department, Middle East and North Africa Region, The World Bank.
World Bank, 2003. Cost Assessment of Environmental Degradation in the Kingdom of Morocco.
Report No. 25992‐MOR. Water, Environment, Social and Rural Development Department,
Middle East and North Africa Region, The World Bank.
World Bank, 2004. Cost Assessment of Environmental Degradation in the Syrian Arab Republic.
World Bank. METAP.
Water, sanitation and hygiene in selected MENA countries
Sarraf, M., Larsen, B., and Owaygen, M. 2004. Cost of environmental degradation: The case of
Lebanon and Tunisia. Environment Department Paper No. 97, The World Bank, Washington
D.C.
World Bank, 2002. Cost Assessment of Environmental Degradation in the Arab Republic of Egypt.
Sector Note. Report No. 25175 –EGT. Rural Development, Water and Environment
Department, Middle East and North Africa Region, The World Bank.
World Bank, 2003. Cost Assessment of Environmental Degradation in the Kingdom of Morocco.
Report No. 25992‐MOR. Water, Environment, Social and Rural Development Department,
Middle East and North Africa Region, The World Bank.
World Bank, 2004. Cost Assessment of Environmental Degradation in the Syrian Arab Republic.
World Bank. METAP.
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WRAP‐UP CASE: THE JULY 2006 WAR IN LEBANON
& POLICY IMPLICATIONS AND
CONCLUSIONS
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SESSION 18
15 POLICY IMPLICATIONS AND CONCLUSIONS
Environmental values are used in policy and project appraisal in a number of ways. They
are less routinely incorporated into policy and project appraisal in a systematic way.
Environmental changes tend to be assessed through Environmental Impact Assessment
(EIA) rather than through the estimation of changes in environmental values and cost‐
benefit analysis. There are many instances where the environmental impacts of projects
are only described or enumerated in physical terms with no monetary values attached to
them. This leaves the decision‐makers to make intuitive judgments on whether the
welfare gains from the project will outweigh the ensuing environmental degradation.
The environmental impact assessment study quantifies and describes the physical
impact of projects and policies and documents complexity of an environmental issue.
However, it fails to help the decision‐maker who has little knowledge of how
environmental changes affect the utility of the individual. As such, environmental
valuation gives the ‘true’ value of environmental resources to the society and tends to
remove ambiguity and vagueness in the decision‐making process. However, care should
be taken in order not to apply environmental valuation in order to maximize benefits in
order to justify a policy or in order to minimize the estimated externality values of a
project to ensure its approval.
Environmental impacts should be valued in monetary terms in order that they are given
due and proper weight in the decision‐making process. The non‐monetization of
environmental impacts may mean that either they are under‐valued or over‐valued in
the intuitive decision‐making process. Monetization will permit the comparison of
various environmental management proposals. Many studies revealed the inconsistency
of intuitive decision‐making compared with a more structured approach of
environmental valuation. The numerous cognitive psychological biases in intuitive
decisions render rational choice problematic.
Environmental values have been used limitedly in decision‐making due to many factors,
including:
− Skepticism towards environmental valuation methods
− Lack of environmental economists within government agencies
− Absence of a legal requirement to undertake a CBA of projects or policies
− Uncritical acceptance of other methods such as
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− Effect on production
− Dose response
− Opportunity cost approaches
− Suspicion of non‐use values
− Distorted perceptions of the valuation methods by non‐economist
− Large variance associated with mean WTP and WTA values
Currently, environmental values are less routinely incorporated into policy and project
appraisal in a systematic way. Environmental changes tend to be assessed through EIAs
in the US and EU rather than through economic valuation and CBA. The World Bank and
the Asian Development Bank advocate the use of valuation methods to estimate the
welfare effects of environmental changes. Environmental valuation studies in different
European countries were undertaken spasmodically with varying degrees of influence on
decisions and with marked variations between countries. For instance, Switzerland has
produced a number of academic/ scientific employing TCMs, HPMs, CVMs, all being
applied, and researchers receiving funds from a variety of institutions. Studies in
Germany have been proportionately fewer and more policy oriented. In the UK, a shift
away from TCMs to HPMs and CVMs occurred in the 1990s, which was mostly attributed
to the nature of the goods being valued. In the Netherlands, while academic interest in
environmental economics is strong, demand for valuation studies by governments and
organizations is low. In Norway, benefit estimation studies provided support for
environmental decision‐making but had not played a crucial role in the process.
In some cases, the environmental valuation process is formalized and fairly explicit and
institutionally incorporated in the decision‐making process. For example, at the US
Forest Service, there is an explicit inclusion of environmental values in the application of
‘unit day values’ of recreational opportunities and resources. Environmental values are
also explicitly included in Type A assessment of natural resource damage from pollution
spills under CERCLA legislation. Economic damages are calculated from an economic
database in which injuries and losses to particular species of fish, water fowls, etc. are
measured as reductions in harvesting or in recreational use values. For major pollution
incidents, a Type B assessment under CERCLA requires a site specific investigation.
Furthermore, the US Department of Interior regulations authorized methods for
environmental valuation. Where a reasonably competitive market exists for a resource,
market price is used to estimate economic damage. If market prices are not appropriate,
appraisal can be based on Uniform Appraisal Standards for Federal Law Acquisition.
Where neither of these approaches is appropriate, environmental valuation methods
are adopted. Use values may be measured via TCM, HPM, unit values, CVM, and stated
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preference techniques. Non‐use values may only be measured via CVM and stated
preference techniques.
The desire to establish formal benefit transfer methods by governments and agencies
and the advocacy for the use of benefit transfer by organizations will result in
environmental valuation methods that are more institutionalized and more routinely
included in CBAs. In the near future, environmental valuation will witness a search for
more accurate and robust semi‐ and non‐parametric estimators, improved
understanding of the psychology of making choices and decisions, the analysis of the
non‐stationarity of environmental values, and the application of other theories and
techniques from other branches of economics, such as the Bayesian Perspectives and
the Game Theory.
In the MENA region, effort should be direct to increase awareness on environmental
valuation, to build capacity on COED methodology, to institutionalize COED
methodology in decision‐making process, and to establish a database for environmental
valuation studies in the region. Various databases on environmental valuation could be
of help, as listed in Table 34. Other useful websites are listed in Table 35.
140
Table 34. Main features of selected valuation databases (McComb et al, 2006)
Name of database Web host Purpose of the database Number of studies
Regions covered
Available languages
Environmental Valuation Reference Inventory
Environment Canada on behalf of the EVRI Club1 http://www.evri.ca
To help policy analysts using the benefits transfer approach to estimate economic values for changes in environmental goods and services or human health
1,500 International English, French
Envalue New South Wales Environment Protection Authority http://www.epa.nsw.gov.au/envalue
To help stakeholders value changes in environmental quality
400 International English
Ecosystem Services Database
Gund Institute for Ecological Economics, University of Vermont http://esd.uvm.edu
To provide a data and analysis portal to assist in the informed estimation of the economic values of ecosystem services
300 International English
Review of Externality Data
European Commissionhttp://www.red‐externalities.net
To assist policy makers in capturing the effects of externalities from new policies that have sustainable development as their core concern
200 International English
New Zealand Non‐market Valuation Database
Lincoln University, Canterbury, New Zealandhttp://oldlearn.lincoln.ac.nz.markval
To help researchers identify nonmarket valuation studies undertaken in New Zealand
Searchable database with 100 primary studies from New Zealand
ValuebaseSwe Beijer International Institute of Ecological Economics, and the Swedish Environmental. Protection Agency http://www.beijer.kva.se/valuebase.htm
To provide a survey of empirical economic valuation studies on environmental change in Sweden
Database with 200 primary studies from Sweden
Beneficial Use Values database
Department of Agricultural and Resource Economics, University of California, Davis http://buvd.ucdavis.edu/
A guide for decision makers, policy analysts, and others interested in valuation of water resources
Database of economic values for beneficial uses of water. Variety of sources
Sportfishing Values database
Industrial Economics, Incorporated under contract to the U.S. Fish and Wildlife Service http://www.indecon.com/fish/default.asp
To provide a detailed account of the contents of numerous recent non‐market valuation studies
One hundred non‐market valuation studies of sports fishing activity
141
Table 35. Useful web resources for environmental economists
Name Description Website
Association of Environmental and Resource Economists (AERE)
AERE was established as a means of exchanging ideas, stimulating research, and promoting graduate training in resource and environmental economics. AERE provides many forums for exchanging ideas relevant to the allocation and management of natural and environmental resources and has two journals, the Journal of Environmental Economics and Management (JEEM), and the Review of Environmental Economics and Policy (REEP), and a newsletter issued to members twice a year.
www.aere.org
European Association of Environmental and Resource Economics (EAERE)
EAERE is an international scientific association which aims to contribute to the development and application of environmental and resource economics as a science in Europe, to improve communication and contacts between teachers, researchers and students in environmental and resource economics in different European countries, and to develop and encourage cooperation between university level teaching institutions and research institutions in Europe.
http://www.eaere.org
South Asian Network for Development and Environmental Economics (SANDEE)
SANDEE is a regional network that seeks to bring together analysts from different countries in South Asia to address its development‐environment problems. SANDEE's mission is to strengthen the capacity of individuals and institutions in South Asia to undertake research on the inter‐linkages among economic development, poverty, and environmental change and to disseminate practical information that can be applied to development policies.
http://www.sandeeonline.org
The Economy and Environment Program for Southeast Asia (EEPSEA)
EEPSEA is similar to SANDEE and supports training and research in environmental & resource economics in South East Asia. This web site offers downloadable Research reports on issues relevant to developing countries.
http://www.idrc.org/eepsea
Latin American and Caribbean Environmental Economics Program (LACEEP)
LACEEP was launched with a grant from IDRC. The program will operate in ways similar to EEPSEA and its South Asian counterpart SANDEE, offering research awards, short courses, workshops and mentoring.
http://www.laceep.org
Middle East and North Africa Network for Environmental Economists (MENANEE)
MENANEE is a joint venture between the Beijer Institute of Resource Economics and the Library of Alexandria. It is considered as a regional network that aims at strengthening the capacity of individuals and institutions in the region in the field of environmental and resources economics. It also intends to highlight to policy and decisions‐makers the linkages between economic development and environmental changes.
http://www.bibalex.com/MENANEE/Home/Home.aspx
142
Name Description Website
Center for Environmental Economics and Policy in Africa (CEEPA)
The mission of CEEPA is to enhance the capacity of African researchers to conduct environmental economics and policy inquiry of relevance to African problems and increase the awareness of environmental and economic managers and policy makers of the role of environmental economics in sustainable development.
http://www.ceepa.co.za/mo.html
Society for Environmental Economics and Policy Studies (SEEPS)
SEEPS is a scientific association which aims to contribute to the theoretical and empirical research of environmental economics and policy studies; to improve communication and contacts between teachers, researchers and students in environmental economics and policy studies; to promote international scientific cooperation in environmental economics and policy studies.
http://wwwsoc.nii.ac.jp/seeps/eng/index.html
Environmental Economics Unit at Göteborg University, Sweden (EEU)
EEU is a research and teaching unit within the Göteborg University with graduate students working on various projects related to natural resources and environmental economics. EEU specializes in environmental economics research and training. The research is focused on natural resource management in developing countries, the choice of policy instruments for transport, industrial environmental problems and welfare related issues.
http://www.hgu.gu.se/item.aspx?id=2496
The UK Network of Environmental Economists (UKNEE)
UKNEE aims to bring together environmental economists from academia, consultancy and public and private sectors to foster closer relationships, follow recent developments and share experience. UKNEE organizes regular seminars on topical subjects in environmental economics followed by social evenings.
http://www.eftec.co.uk/UKNEE/index.htm
Asociacion Hispano Portuguesa de Economia de los Recursos Naturales y Ambientales (AERNA)
AERNA was founded in 2002 as a response to the motivation of a group of academics and researchers in the Iberian Peninsula, for exchanging ideas and knowledge, stimulating research and supporting the government and other interested groups decisions on the field of the multiple relations between economics and environment.
http://www.aerna.org/paginas.asp?id_pagina=1
International Society for Ecological Economics (ISEE)
ISEE facilitates understanding between economists and ecologist and the integration of their thinking into a trans‐discipline aimed at developing a sustainable world
http://www.ecoeco.org/
REGIONAL WORKSHOP REGIONAL WORKSHOP ONON
THE COST OF THE COST OF ENVIRONMENTAL ENVIRONMENTAL
DEGRADATION (COED) DEGRADATION (COED) METHODOLOGYMETHODOLOGY
July 1-5, 2008Crowne Plaza Hotel
Beirut, Lebanon
REGIONAL WORKSHOP ONREGIONAL WORKSHOP ON
THE COST OF ENVIRONMENTAL THE COST OF ENVIRONMENTAL DEGRADATION (COED) DEGRADATION (COED)
METHODOLOGYMETHODOLOGYJuly 1-5, 2008
Crowne Plaza HotelBeirut, Lebanon
INTRODUCTIONINTRODUCTION
• Environmental degradation one of the most prominent adverse phenomena in today’s world
• The MENA region is suffering from serious environmental problems– air pollution– water pollution– land degradation– forest and biodiversity loss– waste pollution– coastal zone degradation
Air pollutionAir pollution Land and coast degradationLand and coast degradation
Liquid Liquid waste waste
pollutionpollution
Solid waste pollutionSolid waste pollution
Economic valuation of environmental degradation
Quantification of benefits of environmental projects/
policies
Incorporating and prioritizing environmental issues in
decision-making
Environmental ValuationEnvironmental Valuation
Raising Raising awareness onawareness onenvironmental environmental
issuesissues
Progress Progress towards towards
sustainable sustainable developmentdevelopment
Cost of Environmental DegradationCost of Environmental Degradation• According to the METAP/World Bank Country studies
– US$228 million per year in Jordan and US$4.2 billion per year in Egypt
• In comparison with other countries:– OECD countries: 1-2% of GDP– India: average annual 4.5% of GDP in 1991– Mexico: average annual 3.3% of GDP– China: 8% of GDP
0123456
Tunisia(1999)
Jordan(2000)
Lebanon(2000)
Syria(2001)
Algeria(1999)
Morocco(2000)
Egypt(1999)
Perc
ent G
DP
Water Soil Air Coastal Zone Waste
Cost of Environmental DegradationCost of Environmental Degradation
• The COED in the MENA region is an environmental economics tool – developed by the METAP/World Bank– enables professionals to carry out assessments of the
economic cost of environmental degradation– successfully used in the valuation of environmental
degradation on a macroeconomic and sector levels
A main obstacle to conducting research in environmental economics is the shortage of human capacity at governmental ministries/organizations and local
universities
Capacity Building for COEDCapacity Building for COED
• Aims to enhance regional capacity in environmental economics
• Funded by the World Bank/ METAP• Implemented by AUB• Main tasks:
Environmental Economic Unit at
AUB
Training course in COED
methodology
Policy Papers on COED
•Maghreb •Mashreq
COURSE COURSE OUTLINEOUTLINE
Day Session Time Topic
1 1 08:30‐10:00 Participants registration Official opening Introductions and purpose of the workshop
10:00‐10:30 Coffee break
2 10:30‐12:00 Brief overview of basic economic principles
Introduction to environmental valuation and policy implications
12:00‐12:30 Coffee break
3 12:30‐14:00 The revealed preference approach a) The productivity method (Theory, application, advantages, limitations, case‐studies)
b) The market values approach including damage cost, replacement cost, and substitution cost methods (Theory, application, advantages, limitations, case‐studies)
14:00‐15:30 Lunch
4 15:30‐17:30 Case‐studies on the productivity method and the market values approach
2 5 08:30‐10:00 The revealed preference approach (cont’d) c) The travel cost method (Theory, application, advantages, limitations, case‐studies)
10:00‐10:30 Coffee break
6 10:30‐12:00 The revealed preference approach (cont’d) d) The hedonic pricing method (Theory, application, advantages, limitations, case‐studies)
e) The aversive behavior method (Theory, application, advantages, limitations, case‐studies)
12:00‐12:30 Coffee break
7 12:30‐14:00 Group Exercises: Ayubia National Park In Pakistan (Travel Cost) Non‐Priced Forest Recreation Areas In Malaysia (Travel Cost) Valuing Landscape and Amenity Attributes In Central England (Hedonic Pricing)
14:00‐15:30 Lunch
8 15:30‐17:30 Presentation and discussion of group exercises
COURSE COURSE OUTLINEOUTLINE
Day Session Time Topic
3 9 08:30‐10:00 The stated preference approach a) The contingent valuation method (Theory, application, advantages, limitations, case‐studies)
10:00‐10:30 Coffee break
10 10:30‐12:00 The stated preference approach (cont’d) b) The discrete choice method (Theory, application, advantages, limitations, case‐studies)
The benefit transfer method (Theory, application, advantages, limitations, case‐studies)
12:00‐12:30 Coffee break
11 12:30‐14:00 Group exercise: Stated preference approach Air quality in Beijing Ecosystem services in Ejina China Environmental services in the Yaqui River Delta, Mexico Sustainable development in Sweden coastal zone Coastal ecosystems in Phang Nga Bay, Thailand
14:00‐15:30 Lunch
12 15:30‐17:30 Presentation and discussion of group exercises
Case‐studies: Coastal zone in North Lebanon, Climate Change MENA region
4 13 08:30‐10:00 Cost‐benefit analysis Case‐studies: wastewater and solid waste management
10:00‐10:30 Coffee break
14 10:30‐12:00 The value of life and health Including the burden of disease (DALY), the human capital approach, the cost of illness approach, and the contingent valuation approach
Case studies: Drinking water quality, Emissions from the cement industry Particulate matter in urban areas, Lead phase‐out
12:30‐13:00 Coffee break
5 15 08:30‐10:00 Case studies: Drinking water quality, Emissions from the cement industry Particulate matter in urban areas, Lead phase‐out
10:00‐10:30 Coffee break
16 10:30‐12:00 Group exercise on the value of life and health: Urban air pollution from particulates in selected MENA countries Water, sanitation and hygiene in selected MENA countries
12:00‐12:30 Coffee break
17 12:30‐14:00 Presentation and discussion of group exercises
14:00‐15:30 Lunch
18 15:30‐17:30 Wrap‐up case with various concepts: The July 2006 War in Lebanon
Policy implications and workshop conclusion
Workshop evaluation
OUTLINEOUTLINEBasic Economic
Principles Market Pricing
Production Function Travel Cost
Averting Behavior
Hedonic Pricing
Contingent Valuation
Contingent Choice
Value of Life and Health
Benefit Transfer
Cost-Benefit Analysis
Decision-making and Policy
Group exercise
Group exercise
Case-studies
Group exercise
July 2006 War
Lebanon
Revealed Preference
Stated Preference
Valuation Methods EEnd of nd of SSession ession 11
Thank YouThank You
REGIONAL WORKSHOP ONREGIONAL WORKSHOP ON
THE COST OF THE COST OF ENVIRONMENTAL ENVIRONMENTAL
DEGRADATION DEGRADATION METHODOLOGYMETHODOLOGY
Session 2OVERVIEW OF BASIC ECONOMIC
PRINCIPLES&
INTRODUCTION TO ENVIRONMENTAL VALUATION AND POLICY IMPLICATIONS
REGIONAL WORKSHOP ONREGIONAL WORKSHOP ON
THE COST OF ENVIRONMENTAL THE COST OF ENVIRONMENTAL DEGRADATION METHODOLOGYDEGRADATION METHODOLOGY
Session 2aOVERVIEW OF BASIC ECONOMIC PRINCIPLES
&INTRODUCTION TO ENVIRONMENTAL
VALUATION
OUTLINEOUTLINE• The competitive market
– Consumer behavior and demand– Producer behavior and supply– Market equilibrium
• Market failure– Property rights– Types of goods– Externalities– Types of market structure
• Policy failure• Pollution control approaches• Introduction to environmental valuation
The Competitive MarketThe Competitive Market
• A market is defined as the coming together of consumers and producers to exchange goods and services for money– It exists for a single good or service– It has many buyers and sellers (perfectly
competitive)– Buyers and sellers do not have to be
physically present to carry out operations
The Competitive MarketThe Competitive Market
• Classification of markets according to buyers and sellers– Monopoly: a single seller
• Ex: the utilities sector in many countries where the government is the only provider of water or electricity
– Oligopoly: few sellers• Ex: the domestic car manufacturing industry in Australia
– Monopsony: a single buyer• Ex: a mine as a single major industry in a town and a sole
buyer of labor and other goods and services
The Competitive MarketThe Competitive Market
• Characteristics– Many sellers and buyers with none of them highly
influential to affect the price– Buyers and sellers are free to enter or leave the
market in response to price changes– Goods and services offered for sale are
homogeneous • i.e. choice of buyer is only affected by price
– All market participants have perfect knowledge • i.e. consumers know product prices and producers know
input prices
Consumer Behavior and DemandConsumer Behavior and Demand
• Demand function– A curve indicating how
much of a good a consumer is willing to buy at various prices
• Inverse relation between price and quantity demanded
• The demand for a good is defined given that all other goods and income remain constant
• The demand curve is defined for a given period of time
B0
A
Consumer’s Demand
Quantity
Pric
e pe
r un
it C
D
The points on the curve represent the maximum amount of money a consumer is willing to pay
(WTP) for different quantities of the good
Consumer Behavior and DemandConsumer Behavior and Demand
• Elasticity– The responsiveness of quantity demanded/ supplied
to changes in variables such as price and income
– Own-price elasticity of demand can be:
Perfectly elastic (εD=∞) Relatively elastic (εD >1)
Perfectly inelastic (εD =0) Relatively inelastic (εD <1)
Own-price elasticity of demand:εD = % change in quantity of q1 demanded
% change in price of q1
Price
Quantity
DPrice
Quantity
D
Price
Quantity
D
Quantity
D
Price
Consumer Behavior and DemandConsumer Behavior and Demand
• Cross-price elasticity of demand– The responsiveness of the quantity of a
demanded good (q1) as a result of changes in another good (q2)
– If εD12 > 0, then q1 and q2 are substitutes
– If εD12 < 0, then q1 and q2 are complements
Cross-price elasticity of demand:εD
12 = % change in quantity of q1 demanded% change in price of p2
Consumer Behavior and DemandConsumer Behavior and Demand
• Income elasticity of demand– The responsiveness of the quantity of a
demanded good (q1) given a changes in income
– If ηϒ > 0, then the good is a normal good– If ηϒ < 0, then the good is an inferior good
Income elasticity of demand:ηϒ = % change in quantity of q1 demanded
% change in income
Producer Behavior and SupplyProducer Behavior and Supply
• The production function is a function of various inputs– Labor, land, capital, etc.
• The producer’s aim is to maximize profit– The producer will increase
the production output if its price rises
• Main observations– The curve is positively
sloped• Producers supply more as
price increases– The supply curve refers to
a given point in time
0
A
Market supply curve(Marginal cost curve)
Quantity
Pric
e pe
r un
it
C
D
The marginal cost curve indicates the cost of producing each additional unit of the good. To
maximize profit, the producer increases production up to a point where marginal revenue, the price per unit of output in a
competitive market, just equals marginal cost.
Market Equilibrium in the Market Equilibrium in the Competitive MarketCompetitive Market
• The interaction of supply and demand forces in the market determine– Equilibrium price/ Market revenue (PE)– Equilibrium quantity demanded (SE)
Quantity produced0
PE
Market demand
Market supply
E
SE P
Price per unit
At price PE, market demand is exactly equal to the quantity the market is willing to supply (SE)
Market Equilibrium in the Market Equilibrium in the Competitive MarketCompetitive Market
• If price ↑ to P’– Producer will supply S’– Consumers will demand only
D’– Demand Deficit
• To clear deficit– Producer will ↓ price– Consumers ↑ purchase– Producers ↓ supply– Demand = Supply
• If market price ↓ to PA– Consumers demand ↑ to DA– Producers not willing to supply– Surplus demand
• Shortage of supply– Upward pressure on price– Producer increases supply– Demand = Supply
Market demand
Quantity produced0
PE
Market supply
SE
Price per unit
E
PA
DAS’D’
P’
Market Equilibrium in the Market Equilibrium in the Competitive MarketCompetitive Market
• Factors that can shift the demand curve– Income
• Income increase causes an upward (rightward shift)
• Income decrease causes a downward (leftward shift)
– Prices of substitutes/ complements
• Decrease in price of substitute causes a downward shift
• Decrease in price of complement causes an upward shift
– Consumer tastes and preferences
Quantity produced0
P1
Market demand
Market supply
S1 P
Price per unit
S2
P2
Quantity produced0
P2
Market demand
Market supply
S2 P
Price per unit
S1
P1
Incr
ease
in in
com
eD
ecre
ase
in in
com
e
Market Equilibrium in the Market Equilibrium in the Competitive MarketCompetitive Market
• Factors that can shift the supply curve– Price of inputs, taxes,
subsidies• Input price increase
causes an inward shift• Input price decrease
causes an outward shift– Technology improvement
• Technology improvement causes an outward shift
– More output produced at same input level
– Weather improvement• For weather dependent
productions, weather deterioration causes a leftward shift Quantity produced
0
P2
D1
S1
S2 P
Price per unit
S1
P1
Incr
ease
in in
put p
rice
S2
Dec
reas
e in
inpu
t pric
e
Quantity produced0
P1
S1 P
Price per unit
S2
P2
S1
S2
D1
Market Equilibrium in the Market Equilibrium in the Competitive MarketCompetitive Market
• Notes– Equilibrium examples simplified– Equilibrium does not tend to be static
• Demand function shifts due to changes in taste and income
• Supply function shifts due to resource constraints and technological advances
– It is assumed that property rights are well defined
• The seller has the rights to the goods and to any benefits from sale
Consumer and Producer SurplusConsumer and Producer Surplus
• Consumer surplus (Δabc)– is the maximum amount of
money consumers are willing to pay for the good or service MINUS the market price
– is a measure of net benefits or welfareThe sole reliance on the market price could result in an underestimation of benefits
• Producer surplus (Δbcd)• the net benefit received by
the producer• the difference between the
market price and marginal cost
Quantity produced0
a
Market demand
Market supply
c
SE P
Price per unit
b
d
Producer surplus
Consumer surplus
Application of the Competitive Model:Application of the Competitive Model:The socially optimal level of forestryThe socially optimal level of forestry• Clear felling of timber causes
– Loss of forest cover– Increased soil erosion– Loss of soil nutrients– Loss of biodiversity, etc.
• Effect of policy to include environmental cost to stumpage price
Application of the Competitive Model:Application of the Competitive Model:The socially optimal level of forestryThe socially optimal level of forestry• At current stumpage price
p q logs are harvested• An extra 5 USD
government charge per log– Upward shift of supply
curve from S to S’– Assuming constant
demand, • Equilibrium established at
q’• the quantity of harvested
logs decline (q’ < q)Number of harvested logs
0
p
S
q
Stumpage price ($)
5 $
5 $
S’
p’
q’
MARKET FAILUREMARKET FAILURE
• It occurs when some costs and/or benefits are not fully reflected in market prices– Common for many kinds of environmental goods
which are not usually traded in markets• Reasons for market failure
– property rights related to ecosystems and their services are often not clearly defined.
– many ecosystems provide services that are public goods
– many ecosystem services are affected by externalities
– type of market structure
Lack of or Weak Property Lack of or Weak Property RightsRights
When property rights are weak or lacking in an environmental system, there is no incentive for an individual to invest in an asset because he cannot appropriate the full benefits
• Characteristics of ownership/ property rights– Well-defined
• Formal (certificate, receipt,…)• Informal (institutionalized by social and cultural norms)
– Exclusive– Transferable– Secure and enforceable
Lack or Weak Property RightsLack or Weak Property Rights
Most environmental goods
Pure public goods or open access/common property goods
Lack of well defined property rights results in market failure
Inefficient allocation of resources
Taxonomy of Environmental GoodsTaxonomy of Environmental Goods
Goodsand
Services
Private goods Congestion goods Public goods
Open accessand common
property goodsPure public goodsSemi-public goods
Private vs Pure Public GoodsPrivate vs Pure Public Goods
• Private goods– Are exclusive– Have a positive
marginal cost• Positive cost for
supplying additional goods
– Are rival in consumption
• If one person consumes it, another cannot
• Public goods– Are non-exclusive
• Goods available to everyone
– Have zero marginal cost• zero cost for supplying
additional goods– Are non-rival in
consumption• Goods consumption does
not affect goods availability– Consumers do not have
the option of not consuming
Open Access and Common Open Access and Common Property GoodsProperty Goods
• Open access goods– Rival in consumption– Non-exclusive– Non-transferable– Non-enforceable even
when ownership rights exist
Ex: ocean fisheries and migratory wildlife
• Common property goods– Rival in consumption– Exclusive for a group of
people– Rights of use may be
transferable by individual or group
– May be enforceable through social sanctions
Ex: common grazing land
Under these regimes resources may be exploited (Hardin’s tragedy of the commons).However, under some form of common property systems, resource management islikely to be more efficient because it is based on communal rules and customs
SemiSemi--public and Congestion Goodspublic and Congestion Goods
• Semi-public goods– Non-rival in consumption– Non-exclusive– Zero marginal cost– Ownership rights exist– Consumers can choose not
to consume
Ex: TV broadcast and lighthouse
• Congestion goods– Rival or non-rival
consumption– Exclusive – May exhibit characteristics
of private or public goods at different levels of consumption
– May be enforceable through social sanctions
Ex: roads, boating sites, historic sites
ExternalitiesExternalities
• An externality exists when some agent A(individual or firm) takes an action which has an impact on another agent B, that B has not chosen to accept– It is negative when the affected person suffers a loss
in utility that is uncompensated• Ex: air, water, and noise pollution
– It is positive when the effect is beneficial• This is very rare• Ex: immunization
• Some features of externalities:– Agent B cannot choose the level of the impact like in
a normal economic transaction– The impact on B is not a result of a deliberate attempt
from A
ExternalitiesExternalities
• Causes of externalities– Interdependence between economic agents
• The market system fails to account for the interdependence, resulting in an uncompensated affected party
– Lack of or weak property rights• The affected party is unable to demand a reduction of the
externality or ask for compensation
– High transaction costs• Cost of negotiating, implementing and enforcing an
agreement
Once the affected party is compensated, the externality is Once the affected party is compensated, the externality is ‘‘internalizedinternalized’’and the society is better of by the gainer compensating the loseand the society is better of by the gainer compensating the loserr
ExternalitiesExternalities
• Types of externalities– Relevant externalities
• When the affected person is made worse off by the activity and wants the offender to reduce it
– Pareto-relevant externalities• When it is possible to take action such that the affected person is
made better off without making the offender worse off– Static vs dynamic externalities
• When the externality has adverse impacts for the future, it becomes dynamic
– Pecuniary externalities• Transmitted through the price system and is not a result of market
failure• Ex: increased rental prices in an area due to a new business
opening there• Pollution is not pecuniary because even if penalties exist
Types of Market StructureTypes of Market Structure
• The type of market structure can cause market failure– Perfectly competitive market with external
costs– Monopoly
Resource allocation in a perfectly Resource allocation in a perfectly competitive marketcompetitive market
• Illustration:– A gold mining company
dumping mine tailings in a nearby river without paying for cleanup or waste treatment
• D: Demand curve for gold
• MCp: Marginal private cost of producing gold
• MSC: Marginal social cost
– Assume: MSC > MCp since MSC = MCp + external cost of pollution
Quantity (q)0
p0
MCp
q0
Price/Cost ($)MSC
p’
q’
D
b
c
a
Resource allocation in a perfectly Resource allocation in a perfectly competitive marketcompetitive market
• Illustration (cont’d):– The company
maximizes producer surplus by producing q0
– For society, • q0 is not an efficient
allocation• q’ (less gold) will
maximize society’s benefits
– Δabc is a deadweight loss to society
Quantity (q)0
p0
MCp
q0
Price/Cost ($)MSC
p’
q’
D
b
c
a
Resource allocation in a perfectly Resource allocation in a perfectly competitive marketcompetitive market
• Illustration (cont’d):– The socially optimal
pollution level is NOT zero– When pollution is unpriced,
• Production results in more output than is socially desired
• Excessive pollution results– If pollution abatement is
enforced• Company will raise price
per unit of good• Company will reduce
output• The reduced quantity is
socially sufficient and the price is efficient
Quantity (q)0
p0
MCp
q0
Price/Cost ($)MSC
p’
q’
D
b
c
a
Resource allocation in a monopolyResource allocation in a monopoly
• Monopoly rights cause market failure from society’s point of view– A single monopolistic
curve • marginal cost curve MC• Demand curve D
– Under perfect competition
• Price = MR = MC• q’ units will be supplied
Quantity (q)0
P’
MC
q’
Price/Cost ($)
MR
pm
qm
D
c
d
b
a
Resource allocation in a monopolyResource allocation in a monopoly
• In the case of a monopoly– Demand curve above
marginal revenue curve– Price ≠ MR– Monopoly profit maximized
by setting MR = MC• Less output (qm)• Higher price (pm)• Consumer surplus = Δ apmb instead of Δ ap’c
– Marginal benefit exceeds marginal cost
– The level of output is inefficient
– Deadweight loss to society = Δbdc
Quantity (q)0
P’
MC
q’
Price/Cost ($)
MR
pm
qm
D
c
d
b
a
POLICY FAILUREPOLICY FAILURE
• Policy failure occurs when the government creates incentives for the prices of certain goods to be lower than the actual cost of production per unit– Ex: Government subsidy on pesticides
• In general, subsidies in developing countries are declining due to the adoption of structural adjustment programs
POLLUTION CONTROL POLLUTION CONTROL APPROACHESAPPROACHES
• Two main approaches– Property rights or market (Coasian) solution
• Allowing the market system to solve the problem through bargaining between affected parties
• Based on assumptions that may not apply in the real world
– Zero transaction costs– Well defined property rights– Perfect competition– No free-rider effect
– Government intervention
Government PoliciesGovernment Policies• There is always a need for government
interventions to correct the externality problem
Other InstrumentsMarket Based(MBIs) Instruments
Subsidies MarketablePermitsCharges
— Emission charges— User charges— Product charges— Administrative charges
— Deposit refundSchemes
— Ecolabelling— Performance bonds— Traditional
property rights
Other MBIs
Command and Control (CAC)
Instrument
AmbientStandards
EmissionStandards
— Performance-basedstandards
— Technology-basedstandards
— Voluntary incentives
— Liabilitylegislation
— Education— Zoning— Fines— Bans
Command and Control Command and Control InstrumentsInstruments
• Oldest form of pollution control policies• Require setting the standard and monitoring and
enforcing it• Advantages
– A widely understood form of policy– More pragmatic and socially acceptable than MBIs
• Disadvantages– Provides no incentive for pollution reduction beyond standards– Penalties tend to be too low and enforcement too weak– Governments must know the marginal social cost and marginal
social benefits curves to set an optimal penalty– Penalties need to be revised frequently which is costly– Financial costs for setting and enforcing standards are high– Political costs may arise if standards are stringent– Standards are uniformly set to all firms and regions
MarketMarket--based Instrumentsbased Instruments
• Use price or some other economic variables to provide incentive for economic agents to abate pollution
• Advantages– Achieve the same objective as CACs at a lower cost– Generate significant revenue for the government
• Disadvantage– Cannot be applied where the institutional framework
is weak
Choosing the Right InstrumentChoosing the Right Instrument
• Criteria to consider– Economic efficiency– Effectiveness in achieving the desired
environmental objective– Adaptability to changing circumstances– Equity in the distribution of costs and benefits
among different groups in the society– Political acceptability
INTRODUCTION TO INTRODUCTION TO ENVIRONMENTAL VALUATIONENVIRONMENTAL VALUATION
Assigning zero/ low values to non-market environmental commodities
Failure to account for the values of environmental resources
Decisions/ Policies with negative environmental and social implications
The Elements of Total Economic The Elements of Total Economic ValueValue
Benefits
Direct Use Values
Ecological Function Values
USE VALUESUSE VALUES(consumptive and non-
consumptive)
Unpriced Benefits
Marketed Outputs
• Recreation• Landscape• Local culture
• Crops• Meat• Timber• Renewable
energy
• Flood control• Carbon storage• Water catchment• Waste
assimilation
NONNON--USE VALUESUSE VALUES(inherent in the good)
Benefits
Option Values
• Future drugs• Potential gene
pool• Recreation
options
Benefits
Existence Values
• Satisfaction from knowledge of existence
Benefits
Bequest Values
• Passing benefits to future generations
NonNon--use valuesuse values
• Can constitute a significant component of total economic value
• Not traded cannot be valued by market prices
• Non-market valuation methods were developed for this purpose
NonNon--market Valuation Methodsmarket Valuation Methods
• Revealed preference models– Make use of individual
behavior in real and simulated markets to infer the value of an environmental good or service
– Measures use values only– Choices made are real
rather than hypothetical– Clear principle but
complicated applications– Example
• Wilderness valuated from the cost incurred to travel to the area for recreation
• Stated preference models– Elicits environmental values
directly from respondents using survey techniques such as questionnaires
– Flexible and applied to a wide range of goods
– Measure use and non-use values
– Are subject to many biases discussed later
Preferences
Revealedpreferences
StatedPreferences
MarketValues
Travel Cost Methods
HedonicMarkets
Averting Behavior
ContingentValuation
ChoiceExperiments
USE VALUES USE + NON-USE VALUES
Dose Response Functions
NonNon--Market Valuation MethodsMarket Valuation Methods
EEnd of nd of SSession ession 22
Thank YouThank You
REGIONAL WORKSHOP ONREGIONAL WORKSHOP ON
THE COST OF ENVIRONMENTAL THE COST OF ENVIRONMENTAL DEGRADATION METHODOLOGYDEGRADATION METHODOLOGY
Session 2bMacroeconomics and Policy Implications
Macroeconomics and the Macroeconomics and the EnvironmentEnvironment
• Macroeconomic instability is not good for the environment.
• Macroeconomic reforms may exacerbate existing policy and market failures; this is an argument for reforming the environmental sector, not abandoning macroeconomic adjustment
• Many macroeconomic reforms are positive for the environment – royalty collection, user fees, pricing reforms, subsidy
reductions, pollution taxes, trade liberalization and consequent access to new technology
The Policy Matrix: What The Policy Matrix: What Instruments?Instruments?
Lessons learned fromLessons learned fromsuccessful financing initiatives:successful financing initiatives:
Successful sustainable development and environmental management initiatives usually have the following characteristics:
• Financial sustainability• Administrative sustainability
Lessons learned from Lessons learned from successful financing initiativessuccessful financing initiatives
• Public/private consensus• Policy integration
Financing sustainable development is not only about having the financial resources but also about these other dimensions. Investing time in ‘consensus’ building can reduce the financial needs of a project.
Financial sustainabilityFinancial sustainability
• Governments often face strict fiscal regimes –effective policies help generate resources
• The environment is usually a second (or third) priority
• Society is willing to pay for a better environment– Defining property rights– who is responsible??– Economic instruments can help in internalizing
external costs and raising revenues• When the externality is global, resources can be
captured internationally– GEF; Carbon Funding
Administrative sustainabilityAdministrative sustainability
• The creation of markets and the imposition of new taxes require environmental management bureaucracies/ institutions
• Countries can often use existing fiscal systems
• Need to invest in training and capacity building: building institutions is however slow
Building a public/privateBuilding a public/privateconsensusconsensus
• Important to identify ‘winners’ and ‘losers’and clearly communicate this information
• Subsidy removal will be opposed by established interests (that benefit from the subsidies)
• Need to promote a public demand for change; governments very rarely lead in environmental policy reform
Achieving policy integrationAchieving policy integration
• Governments need to generate financial resources, often via taxes
• Revenue raising environmental instruments need to be compatible with existing fiscal regime and take into account equity considerations
Achieving policy integrationAchieving policy integration
• A mix of financing mechanisms is needed to• At the macroeconomic level, consider the
links between environmental management and– Liberalization and privatization– Fiscal and monetary instability / Exchange rate
instability– Growth– Poverty alleviation
ConclusionConclusion
• Very little/ no new Official Development Aid for the environment
• Large present flows of private and public capital offer much promise
• Financing tools exist that can be used to increase financing for the environment
• Both “polluter pays” and “beneficiary pays” approaches can be used
• Subsidy reduction – politically hard to do/ often unpopular
• Polluter pays – especially for new developments
ConclusionsConclusions
• User fees – show large promise for recreational/ amenity values
• Both Command and Control and Economic-based Instruments
• Institutions and monitoring needed for both types of policies –Command and Control and Economic-based Instruments
• Vested interests powerful (and clever!)
• Political will needed for effective financing reform
• Public awareness and involvement essential to create political will
EEnd of nd of SSession ession 2b2b
Thank YouThank You
REGIONAL WORKSHOP REGIONAL WORKSHOP ONON
THE COST OF THE COST OF ENVIRONMENTAL ENVIRONMENTAL
DEGRADATION DEGRADATION METHODOLOGYMETHODOLOGY
Sessions 3 & 4ENVIRONMENTAL VALUATION
USINGMARKET VALUE METHODS
WORKSHOP ONWORKSHOP ON
COST OF ENVIRONMENTAL COST OF ENVIRONMENTAL DEGRADATION METHODOLOGYDEGRADATION METHODOLOGY
Sessions 3 & 4ENVIRONMENTAL VALUATION USING
MARKET VALUE METHODS
Preferences
Revealedpreferences
StatedPreferences
MarketValues
Travel Cost Methods
HedonicMethod
Averting Behavior
ContingentValuation
ChoiceExperiments
USE VALUES USE + NON-USE VALUES
Dose Response Functions
Environmental Valuation MethodsEnvironmental Valuation Methods
MARKET VALUESMARKET VALUES
• Production function method
• Market price method
• Damage cost, Replacement cost, and substitution cost methods
Revealed Preference ApproachRevealed Preference Approach
The Production Function The Production Function MethodMethod
Production Function MethodProduction Function Method
• One of the most widely used valuation techniques
• Focuses on environmental resources as an input to the production of goods and services
• Used to estimate the economic value of ecosystem products or services that contribute to the production of commercially marketed goods
Production Function MethodProduction Function Method• If a natural resource is a factor of production, then
– changes in the quantity or quality of the resource will result in changes in production costs, and/or productivity of other inputs
– this may affect the price and/or quantity supplied of the final good– it may also affect the economic returns to other inputs.
Production
Other inputs
Q1
Q2
X1 X2
Due to soil erosion
Q1 = f(S1, X)
Q2 = f(S2, X)
Production Function
• Production is a function of soil (S) and other inputs (x)
• As soil quality declines from S1to S2 the production function shifts to Q2
• Options for farmer• Produce at Q2• Keep production at Q1 by increasing other inputs from X1 to X2
Production Function MethodProduction Function Method
Two types of benefits (or costs) may be important
– Changes in the quality or price to consumers of the final good changes will result in changes in consumer surplus
– Changes in productivityor production cost changes will result in changes in producer surplus
Quantity produced0
a
Market demand
Market supply
c
SE P
Price per unit
b
d
Producer surplus
Consumer surplus
Thus, the economic benefits from improvements in the resource can be estimated using changes in observable market data
Production Function MethodProduction Function Method
• Selected applicationsPressure Environmental
ImpactProductivity Impact Change in Income
Overgrazing Soil erosion Reduced capacity of soil to sustain crops
Reduced farmers income
Wastewater discharge
Polluted river Reduced capacity to sustain fish stocks
Reduced income of fishermen
Increased vehicle use
Air pollution Increased respiratory problems among
workers
Lost workdays
Uncontrolled irrigation
Salinity of cropland
Declining yields Reduced farmers income
Production Function MethodProduction Function Method
• The method is most easily applied in two specific cases: 1. Cases where the resource in question is a perfect substitute for
other inputs• Ex: increased water quality in a reservoir means that less chlorine
is needed for treating the water.– An increase in quantity or quality of the resource will result in
decreased costs for the other inputs. – The benefits of increased water quality can be directly measured by
the decreased chlorination costs2. Cases where only producers of the final good benefit from
changes in quantity or quality of the resource and consumers are not affected• Ex: improved quality of irrigation water may lead to greater
agricultural productivity– If the market price of the crops to consumers does not change,
benefits can be estimated from changes in producer surplus resulting from increased income from the other inputs.
– The profits per acre will increase, and this increase can be used to estimate the benefits of improved irrigation water quality
Production Function MethodProduction Function Method
Applying the Productivity Method 1. Determine the physical impact solely arising from
the driving force or behaviour under study• Sometimes difficult to differentiate impacts due to a series
of complex biological interrelationships2. Collect data on how changes in the quantity/ quality
of the natural resource affect• costs of production for the final good • supply and demand for the final good • supply and demand for other factors of production
– Sources of data• Experimental using field trials
– Difficult to extrapolate• Statistical using cross-section or time-series data
– Available for short time horizons– Difficult to control for other factors
Production Function MethodProduction Function Method
Applying the Productivity Method 3. Link the impact of changes in the quantity/
quality of the resource to changes in consumer surplus and/or producer surplus• Problems include
– Distorted prices due to government interventions– Change under study is not large enough to impact
market price– Change in market price is too large– Change in production alters costs
4. Estimate the economic benefits
Production Function MethodProduction Function Method
Illustration 1*– A municipal drinking water reservoir is
polluted by agricultural runoff – The economic benefits of measures to
eliminate the runoff need to be determined• Productivity Method selected because
– Environmental quality directly affects the cost of producing municipal drinking water
– Cleaner water is a direct substitute for other production inputs, such as water purification chemicals and filtration
*Adapted from www.ecosystemvaluation.org
Production Function MethodProduction Function Method
• Step 1– Specify the production function for purified drinking water
• Inputs:– water of a particular quality from the reservoir– Chemicals– Filtration
• Output: – pure drinking water
• Step 2– Estimate how the cost of purification changes when reservoir
water quality changes, using the production function estimated in the first step
– Calculate the quantities of purification chemicals and filters needed for different levels of reservoir water quality
– Multiply these quantities by their costs
Production Function MethodProduction Function Method
• Step 3:– Estimate the economic benefits of protecting the
reservoir from runoff, in terms of reduced purification costs
• If all runoff is eliminated, the reservoir water will need very little treatment and the purification costs for drinking water will be minimal
• Compare this to the cost of purifying water where runoff is not controlled
• The difference in purification costs is an estimate of the benefits of eliminating runoff.
– The benefits for different levels of runoff reduction can also be estimated
• requires information about the projected success of actions to reduce runoff, in terms of the decrease in runoff and the resulting changes in reservoir water quality.
Production Function MethodProduction Function Method
• Illustration 2*Values of Wetlands in the PeconicEstuary, Long Island
Cornell university library
*Adapted from www.ecosystemvaluation.org
Production Function MethodProduction Function Method
• Illustration 2*Values of Wetlands in the PeconicEstuary, Long Island– The estuary includes productive wetlands of
different types• eelgrass, salt marsh, and intertidal mudflats
*Adapted from www.ecosystemvaluation.org
Production Function MethodProduction Function Method
• Illustration 2*Values of Wetlands in the Peconic Estuary, Long Island– The estuary includes productive wetlands of different
types• eelgrass, salt marsh, and intertidal mudflats
– Development and resulting water quality degradation have reduced the quantity of these wetlands
• Challenge– Considering various management actions for the
Estuary and surrounding land areas– Assessing these management actions using a
productivity study for wetlands*Adapted from www.ecosystemvaluation.org
Production Function MethodProduction Function Method
• Analysis – Valuing marginal changes in acres of wetlands, in terms of their
contribution to the production of crabs, scallops, clams, birds,and waterfowl
– It was assumed that wetlands provide both food chain and habitat support for these species
– The productivity of different wetlands types in terms of food chain production was estimated and linked to production of the different species of fish
– The expected yields of fish and birds per acre of habitat were valued using
• commercial values for fish• viewing values for birds• hunting values for waterfowl
Production Function MethodProduction Function Method
• Results– The study results estimated that
• An acre of eelgrass is worth $1,065 per year• An acre of salt marsh is worth $338 per year• An acre of intertidal mudflat is worth $68 per year, in terms of
increased productivity of crabs, scallops, clams, birds, and waterfowl
– Based on the results the economic value for productivity services of preserving or restoring wetlands in the Estuary can be calculated
– These values are an understatement of the total economic value for the wetlands
• They only address values in production of commercially and recreationally valuable species
• They overlook other services, such as erosion and storm protection or aesthetics
ProductionProduction Function MethodFunction Method
• Advantages– Straightforward methodology – Inexpensive to apply due to
• Limited data requirements• Ready availability of relevant data
ProductionProduction FunctionFunction MethodMethod
• Issues and Limitations– Does not account for non-use values hence it
provides only the lower bound estimate– Limited to valuing resources that can be used as
inputs in production of marketed goods– Information is needed on the scientific relationships
between actions to improve quality or quantity of the resource and the actual outcomes of those actions
– If the changes in the natural resource affect the market price of the final good, or the prices of any other production inputs, the method becomes much more complicated and difficult to apply
The situation• 93% of Morocco is arid• Fragile soils suffer from water and wind erosion• Overexploitation and unsustainable management
–– arable land loss arable land loss –– decrease in crop yielddecrease in crop yield– silting of dams– loss in biodiversity– loss in terms of attenuating emissions of
gases causing greenhouse effect
The Production Function MethodThe Production Function MethodCaseCase--study 1: Degraded agricultural landstudy 1: Degraded agricultural land
& rangeland in Morocco& rangeland in Morocco
The situation• 65 million ha of pastureland providing 30% of
overall animal food requirements• Erosion, drought, overgrazing, land clearing and
removal of woods
Degraded pasturelandDegraded pastureland
The Production Function MethodThe Production Function MethodCaseCase--study 1: Degraded agricultural landstudy 1: Degraded agricultural land
& rangeland in Morocco& rangeland in Morocco
The Production Function MethodThe Production Function MethodCaseCase--study 1: Degraded agricultural landstudy 1: Degraded agricultural land
& rangeland in Morocco& rangeland in Morocco
The methodology• Degradation of agricultural land
–– value of lost agriculture production due to a value of lost agriculture production due to a decrease in land productivitydecrease in land productivity
– The majority of agricultural land is planted with cereals
Cost of degraded agricultural land Cost of degraded agricultural land corresponds to the value of lost cereal corresponds to the value of lost cereal
productionproduction• Degradation of rangeland
Cost corresponds to the value of lost Cost corresponds to the value of lost forage productionforage production
The methodology (Agricultural Land)• Step 1: Estimation of degraded agricultural land
– FAO* classified the degradation of 8.7 million ha in Morocco as “severe”
– According to the FAO method 3 scenarios are possible:
• 10 – 25% of land is severely degraded• 25 – 50% of land is moderately degraded• 50 – 100% of land is slightly degraded
– Surveys did not show any case of severe land degradation, only moderate and slight degradationare used
* FAO, Land Resources Potential and Constraints at Regional and Country Level, World Soil Resources Report 90, Rome, 2000
The Production Function MethodThe Production Function MethodCaseCase--study 1: Degraded agricultural landstudy 1: Degraded agricultural land
& rangeland in Morocco& rangeland in Morocco
The methodology (Agricultural Land)• Step 2: Estimation of the decrease in agricultural yield
– Young* estimated the decrease in cereal yield
• Slight degradation 5% decrease in cereal yield
• Moderate degradation 20% decrease in cereal yield
– The mean yield for cereals in Morocco is 1 Ton/ha• 50 Kg/ha for slight degradation• 200 Kg/ha for moderate degradation
* Young, A. Land degradation in South Asia: its severity, causes and effects upon the people, 1994* Young, A., Land resources: now and for the future, Cambridge University Press, Cambridge, U.K.1998
The Production Function MethodThe Production Function MethodCaseCase--study 1: Degraded agricultural landstudy 1: Degraded agricultural land
& rangeland in Morocco& rangeland in Morocco
The methodology (Agricultural Land)• Step 3: Assessing the cost of
degraded agricultural land– The average of the lower bound
and the upper bound of moderate and slight degradation were used
– Selling price: 2,580 dirham/Ton
Lower limit Upper limitModerate erosion 25% 50%
Degraded agricultural land (000ha)
2,175=25% ×8,700 4,350=50% ×8,70
Level of decrease 20% 20%
Decrease in yield (Kg/ha)
200=20% ×1Ton/ha 200
Lost production (Kg) 435,000=2,175×200
870,000=4,350 ×200
Lost value (millions of Dh)
1,122=435,000 ×2,580
2,244=870,000 ×2,58
Slight erosion 50% 100%
Degraded agricultural land (000ha)
4,350=50% ×8,700 8,700=100% ×8,700
Level of decrease 5% 5%
Decrease in yield (Kg/ha)
50=5% ×1Ton/ha 50
L t d ti (K ) 217 500 435 000
The average cost of The average cost of agricultural land agricultural land
degradation: degradation: Dh 1,263 millionDh 1,263 million=(842+1,683)/2=(842+1,683)/2
0 36% f th GDP0 36% f th GDP
The Production Function MethodThe Production Function MethodCaseCase--study 1: Degraded agricultural landstudy 1: Degraded agricultural land
& rangeland in Morocco& rangeland in Morocco
The methodology (Rangeland)• Step 1: Estimation of degraded pastureland
– Calculations considered only the areas with dominant steppe and forest covers (excluding the Saharianregion)
• Dominant steppe area: 12 million ha• Dominant forest area: 5.1 million ha
– REEM calculated the average percentage of degraded rangeland as:
• Dominant steppe 46% 5.52 million ha degraded• Dominant forest 19% 0.969 million ha degraded
* REEM: Rapport sur l’Etat de l’Environnement du Maroc, Ministry of Land Use Planning, Environment, Urbanism and Habitat, 2001.
The Production Function MethodThe Production Function MethodCaseCase--study 1: Degraded agricultural landstudy 1: Degraded agricultural land
& rangeland in Morocco& rangeland in Morocco
The methodology (Rangeland)• Step 2: Estimation of the loss of productivity
– MAMVA* estimated land productivity as:• Steppe: 79 FU / ha / year (FU: Forage Unit 1Kg Barely)• Forest: 558 FU / ha / year
– MAMVA adopted 2 levels of loss 6% and 10%:• Steppe loss: 6% 26.1 million FU / year
10% 43.6 million FU / year• Forest loss: 6% 26.1 million FU / year
10% 43.6 million FU / year* MAMVA: Ministry of Agriculture and Agricultural Development, Plan National d’Aménagement des Bassins Versants,
Phase II, Volume 1, 1994.* MAMVA: Ministry of Agriculture and Agricultural Development, Plan National d’Aménagement des Bassins Versants
Priorités régionales, Phase II Rapport de synthèse, 1995.
The Production Function MethodThe Production Function MethodCaseCase--study 1: Degraded agricultural landstudy 1: Degraded agricultural land
& rangeland in Morocco& rangeland in Morocco
The methodology (Rangeland)
• Step 3: Assessing the cost of rangeland degradation– Barley price: 2,270 Dh/Ton– FU price: 2.27 Dh
The average cost of The average cost of rangeland degradation: rangeland degradation:
177.4 Dh million177.4 Dh million0.05% of the GDP0.05% of the GDP
Steppe Forest TotalPasture area (000ha) 12,000 5,100 17,100
Degraded area (%) 46% 19%
Degraded area (000ha) 5,520=46%
×12,000
969=19%
×5,100
6,489=5,520+
969
Land productivity (FU/ha/year) 79 558
10% lossLoss in yield in degraded area 10%
Lost yield (000 FU/year) 43,608=5,520
×79 ×10%
54,070=969 ×558
×10%
97,678
Lost value (million Dh) 99.0=43,608
×2.27
122,7=54,070
×2.27
221.7
6% loss
The Production Function MethodThe Production Function MethodCaseCase--study 1: Degraded agricultural landstudy 1: Degraded agricultural land
& rangeland in Morocco& rangeland in Morocco
The Results
Average estimate: Average estimate: 1,440 million1,440 million
0.41% of the GDP0.41% of the GDP
Cost of degradation of agricultural land
Cost of degradation of rangeland
Cost of land degradation = +
The Production Function MethodThe Production Function MethodCaseCase--study 1: Degraded agricultural landstudy 1: Degraded agricultural land
& rangeland in Morocco& rangeland in Morocco
The Production Function MethodThe Production Function MethodCaseCase--study 2: Beach degradation in Lebanonstudy 2: Beach degradation in Lebanon
The situation• The coastal zones of Lebanon represent unique
economic and recreational assets• Coast line
– > 240 km long– Inhabited by > 50% of population
• Untreated municipal wastewater disposal, seafront solid waste dumps, uncontrolled development of resorts and vacation homes, etc.
Coastal zone/Beach degradationCoastal zone/Beach degradation(Reduced recreational and tourism value)(Reduced recreational and tourism value)
The Production Function MethodThe Production Function MethodCaseCase--study 2: Beach degradation in Lebanonstudy 2: Beach degradation in Lebanon
The methodology• Annual cost of coastal degradation
– Domestic recreational losses– Losses of ecological and non-use value– Fishery losses due to pollution–– International tourism lossesInternational tourism losses
• Lebanon would likely have attracted a number of beach tourists if the coast was not degraded
Value of international beach touristValue of international beach tourist--nights nights unrealized due to beach degradationunrealized due to beach degradation
The Production Function MethodThe Production Function MethodCaseCase--study 2: Beach degradation in Lebanonstudy 2: Beach degradation in Lebanon
The methodology• Step 1: Estimation of international beach-tourist nights
lost– Calculated based on a comparison with Tunisia and adjusting for
• Differences in Kms of beaches/tourist zones, and• Domestic prices in Lebanon
Extrapolation of Western European (WE) and Northern American (NA) beach tourism in Tunisia for 1999
TunisiaTunisiaCoastline (km) 1,300
Beaches (km) 575
Tourist zones (km) 80
International tourist nights from WE and NA (in 1999) 28,500,000
Beach tourism 90%
International beach-tourist nights 25,650,000
International beach-tourist nights per km beaches 44,609
International beach-tourist nights per km tourist zones 320,625
International beach-tourist nights per km tourist zones in Tunisia:Tunisia:320,625 nights320,625 nights
The Production Function MethodThe Production Function MethodCaseCase--study 2: Beach degradation in Lebanonstudy 2: Beach degradation in Lebanon
The methodology• Step 1: Estimation of international beach-tourist nights
lost (cont’d)– Adjustment for differences in kms of tourist zones between Lebanon and
TunisiaLebanonLebanon
Low HighCoastline (km) 243 243Beaches (km) 36 36High potential beaches (if not degraded) (km) 5 10International beach-tourist nights per km tourist zones in Tunisia 320,625
Potential international beach-tourist nights lost in Lebanon*
1,603,125=320,625
×53,206,250
* Unadjusted for domestic prices
The Production Function MethodThe Production Function MethodCaseCase--study 2: Beach degradation in Lebanonstudy 2: Beach degradation in Lebanon
The methodology• Step 1: Estimation of international beach-tourist nights lost
(cont’d)– Adjustment for domestic price differentials between Lebanon and Tunisia
• Prices are generally higher in Lebanon• The adjustment was conducted by applying a price elasticity of international
tourism demand*– Price elasticity of demand: -2 and -2.25
*Papatheodorou, A. 1999. The Demand for International Tourism in the Mediterranean Region. Applied Economics, 31, (5), 619-630.*Syriopoulos, T. and Sinclair, M.T. 1993. An Economic Study of Tourism Demand: The AIDS Model of US and European Tourism in
Mediterranean Countries. Applied Economics, 25, (12), 1541-1552.
Potential international beach-tourist nights lost in Lebanon: Lebanon: 726,942 726,942 –– 849,769 nights849,769 nights
The Production Function MethodThe Production Function MethodCaseCase--study 2: Beach degradation in Lebanonstudy 2: Beach degradation in Lebanon
The methodology• Step 2: Assessing the value of international
beach-tourism loss– Average tourist expenditure in Tunisia was about 50 US$ in 1999– A range of 75-100 US$ (average 87.5 US$) was used for Lebanon
Low HighPotential international beach-tourist nights lost in Lebanon 726,942 849,769Expenditure per tourist per night (US$) 75 100Average expenditure per tourist per night (US$) 87.5
Total international beach tourism revenue losses (US$/year)63,607,388=726,942
×87.574,354,794
Percent of GDP (%) 0.38 0.45
The average international beachThe average international beach--tourism revenue tourism revenue losses:losses:
69 US$ million, 0.42 % of the GDP69 US$ million, 0.42 % of the GDP
Revealed Preference ApproachRevealed Preference Approach
The Market Price MethodThe Market Price Method
Market Price MethodMarket Price Method
• Makes use of observed market prices for environmental goods and services
• Values changes in quantity and/or quality of a good or service
• Uses standard economic techniques for measuring the economic benefits from marketed goods
• Applied for goods and services with established markets, and which have– Direct uses
• Ex: Plantation timber; commercial fisheries; tourism– Some indirect uses
• Ex: value of water from protected watersheds– Some option values
• Ex: gene research; forest conservation
Market Price MethodMarket Price Method
• Applying the Market Price Method– Market price represents the value of an additional unit
of that good or service, assuming the good is sold through a perfectly competitive market
– Applying the method requires data to estimate consumer surplus and producer surplus.
• To estimate consumer surplus, the demand function must be estimated
– time series data on the quantity demanded at different prices– data on other factors that might affect demand, such as income
or other demographic data• To estimate producer surplus
– data on variable costs of production and revenues received
Market Price MethodMarket Price Method
Illustration 1– Water pollution causing the closure of a commercial fishing area– The benefits of cleanup need to be evaluated
• This method was used because– The primary resource affected is fish, for which market data are
available• Application of the Market Price Method
– The objective is to measure total economic surplus for the increased fish harvest that would occur if the pollution is cleaned up
– the difference between economic surplus before and after the closure must be estimated
– The results of the analysis can be used to compare the benefits of actions that would allow the area to be reopened, to the costs of such actions
*Adapted from www.ecosystemvaluation.org
Market Price MethodMarket Price MethodStep 1• Use market data to estimate the market demand function
and consumer surplus for the fish before the closure.– Assume a linear
demand function• the initial market price
= $5/g• the maximum willingness
to pay = $10/g– At $5/g
• consumers purchased10,000 g fish/yr
• consumers spent $50,000on fish per year
– The shaded area on the graph represents the total consumer surplus received from the fish before the closure = $25,000
Consumer Surplus = ($10-$5)*10,000/2 = $25,000
Consumer Surplus
Demand for fish before closure
Market Price MethodMarket Price MethodStep 2• Estimate the market demand function and consumer
surplus for the fish after the closure– the market price of fish increased
from $5/Kg to $7/Kg– the total quantity demanded
decreased to 6,000 Kg/yr – The new consumer surplus
is $9,000Step 3
– Estimate the loss in economic benefits to consumers
• Subtract benefits after theclosure from benefits beforethe closure
– The loss in benefits to consumers is• 25,000 - 9,000 = $16,000.
Consumer Surplus = ($10-$7)*6,000/2 = $9,000
02468
1012
0 5,000 10,000 15,000 20,000 25,000
Quantity demanded (Kg)
Pric
e ($
/Kg) Consumer Surplus after closure
Demand for fish after closure
Step 4• Estimate the losses to producers by first measuring the
producer surplus before the closure – Producer surplus is measured by the difference between the total
revenues earned from a good, and the total variable costs of producing it
– Before the closure• 10,000 Kg of fish were caught per year• Fishermen were paid $1/Kg
their total revenues = $10,000 per year• The variable cost to harvest the fish was $0.50/Kg
total variable cost = $5,000 per year• The producer surplus before the closure was
$10,000 - $5,000 = $5,000
Market Price MethodMarket Price Method
Market Price MethodMarket Price MethodStep 5:• Measure the producer surplus after the closure
Step 6:• Calculate the loss in producer surplus due to the
closure
Market Price MethodMarket Price MethodSteps 4, 5, and 6
Before closure After closureFish caught per year = 10,000 Kg Fish caught per year = 6,000 KgFishermen were paid $1/Kg Fishermen were paid $1/Kg Total revenues = 1 × 10,000 =
$10,000 per yearTotal revenues = 1 × 6,000 =
$6,000 per yearVariable cost to harvest fish = $0.50/Kg
Variable cost to harvest fish = $0.60/Kg
Total variable cost = 0.5 × 10,000 $5,000 per year
Total variable cost = 0.6 × 6,000$3,600 per year
The producer surplus = $10,000 - $5,000= $5,000
The producer surplus = $6,000 - $3,600= $2,400
Loss in producer surplus due to the closure$5 000 - $2 400 = $2 600
Market Price MethodMarket Price MethodStep 7:• Calculate the total economic losses due to the closure
The benefits of cleaning up pollution in order to reopen the area are equal to $18,600
• Notes– This example is based on assumptions that greatly simplify the
analysis– Some factors might make the analysis complicated
• Some fishermen might switch to another fishery after the closure, and thus losses would be lower
Lost consumersurplus$16,000
Lost producersurplus$2,600
Total economicloss
$18,600+ =
Market Price MethodMarket Price Method
• Advantages– Relatively simple and straightforward– Relies on actual market values– Price, quantity and cost data are easy to
obtain for established markets – The method uses observed data of actual
consumer preferences– The method uses standard, accepted
economic techniques
Market Price MethodMarket Price Method
• Issues and limitations– Market data may only be available for a limited number of goods
and services provided by a resource– Available market data may not reflect the value of all productive
uses of a resource– The true economic value of goods or services may not be fully
reflected in market transactions, due to market imperfections and/or policy failures
– Seasonal variations and other effects on price must be considered
– Cannot be easily used to measure the value of larger scale changes that are likely to affect the supply of or demand for a good or service
– Does not deduct the market value of other resources used to bring ecosystem products to market, and thus may overstate benefits
Revealed Preference ApproachRevealed Preference Approach
Damage Cost AvoidedDamage Cost AvoidedReplacement CostReplacement Cost
Substitute Cost MethodsSubstitute Cost Methods
Damage Cost Avoided, Replacement Damage Cost Avoided, Replacement Cost, and Substitute Cost Methods Cost, and Substitute Cost Methods
• Estimate values of ecosystem services based on – the costs of avoiding damages due to lost services – the cost of replacing ecosystem services, or– the cost of providing substitute services
• Assume that– the costs of avoiding damages or replacing ecosystems or their
services provide useful estimates of the value of these ecosystems or services
– if people incur costs to avoid damages caused by lost ecosystem services, or to replace the services of ecosystems, then those services must be worth at least what people paid to replace them.
• Are most appropriately applied in cases where damage avoidance or replacement expenditures have actually been, or will actually be, made
Damage Cost Avoided, Replacement Damage Cost Avoided, Replacement Cost, and Substitute Cost Methods Cost, and Substitute Cost Methods
• The damage cost avoided method – uses either the value of property protected or
the cost of actions taken to avoid damages as a measure of the benefits provided
• Ex: if a wetland protects adjacent property from flooding, the flood protection benefits may be estimated by
– the damages avoided if the flooding does not occur – or the expenditures property owners make to protect their
property from flooding
Damage Cost Avoided, Replacement Damage Cost Avoided, Replacement Cost, and Substitute Cost Methods Cost, and Substitute Cost Methods
• The replacement cost method– uses the cost of replacing an ecosystem or its
services as an estimate of the value of the ecosystem or its services
• The substitute cost method – uses the cost of providing substitutes for an
ecosystem or its services as an estimate of the value of the ecosystem or its services.
• Example, the flood protection services of a wetland might be replaced by a retaining wall or levee
Damage Cost Avoided, Replacement Damage Cost Avoided, Replacement Cost, and Substitute Cost Methods Cost, and Substitute Cost Methods
Applying the methods• Step 1
– Assessing the environmental service provided• specifying the relevant services
– how they are provided, to whom they are provided, and the levels provided.
• Example: in the case of flood protection, this would involve predictions of flooding occurrences and their levels, as well as the potential impacts on property
Damage Cost Avoided, Replacement Damage Cost Avoided, Replacement Cost, and Substitute Cost Methods Cost, and Substitute Cost Methods
Applying the methods• Steps 2 and 3
– for the damage cost avoided method• estimate the potential physical damage to property, either
annually or over some discrete time period• calculate either the dollar value of potential property damage,
or the amount that people spend to avoid such damage– for the replacement or substitute cost method
• identify the least costly alternative means of providing the service
• calculate the cost of the substitute or replacement service• Establish public demand for this alternative
– This requires gathering evidence that the public would be willing to accept the substitute or replacement service in placeof the ecosystem service
Damage Cost Avoided, Replacement Cost, Damage Cost Avoided, Replacement Cost, and Substitute Cost Methods and Substitute Cost Methods
• Examples of applications – Valuing improved water quality
• by measuring the cost of controlling effluent emissions. – Valuing erosion protection services of a forest or wetland
• by measuring the cost of removing eroded sediment from downstream areas.
– Valuing the water purification services of a wetland• by measuring the cost of filtering and chemically treating water
– Valuing storm protection services of coastal wetlands• by measuring the cost of building retaining walls.
– Valuing fish habitat and nursery services• by measuring the cost of fish breeding and stocking programs
Damage Cost Avoided, Replacement Damage Cost Avoided, Replacement Cost, and Substitute Cost Methods Cost, and Substitute Cost Methods
Illustration 1* (damage and substitute cost methods)
– An agency is considering restoring some degraded wetlands in order to improve their ability to protect the surrounding area from flooding
– Cost-Based Methods are used because• Agency only interested in valuing the flood protection
services of the wetlands• Limited budget available for valuation study• the easiest and least costly method to apply in this case
*Adapted from www.ecosystemvaluation.org
Damage Cost Avoided, Replacement Damage Cost Avoided, Replacement Cost, and Substitute Cost Methods Cost, and Substitute Cost Methods
Step 1• Conduct an ecological assessment of the flood protection services provided
by the wetlands to determine– the current level of flood protection– the expected level of protection after full restoration of the wetlands
Step 2• The Damage Cost Avoided applied using two different approaches
– use the information on flood protection obtained in the first step to estimate potential damages to property if flooding were to occur
• estimate, in dollars, the probable damages to property if the wetlands are not restored.– determine whether nearby property owners have spent money to protect their
property from the possibility of flood damage• by purchasing additional insurance or by reinforcing their basements.• These avoidance expenditures would be summed over all affected properties to provide
an estimate of the benefits from increased flood protection– the two approaches are not expected to produce the same estimate
Damage Cost Avoided, Replacement Damage Cost Avoided, Replacement Cost, and Substitute Cost Methods Cost, and Substitute Cost Methods
Step 2 (cont’d)• The replacement cost method
– flood protection services cannot be directly replaced, so this cannot be applied
• The substitute cost method – a substitute for the affected services such as a retaining wall or a levee
might be built to protect nearby properties from flooding• estimate the cost of building and maintaining such a wall or levee• also determine whether people would be willing to accept the wall or levee in
place of a restored wetland.
Step 3– Compare the cost of the property damages avoided, or of providing
substitute flood protection services to the restoration costs to determine whether it is worthwhile to restore the flood protection services of the wetlands
Damage Cost Avoided, Replacement Damage Cost Avoided, Replacement Cost, and Substitute Cost Methods Cost, and Substitute Cost Methods
Illustration 2*: Soil Erosion in Korea (replacement cost method)
• Background
• The challenge– Evaluate the benefits of proposed new soil management techniques
• retaining the soil and nutrients on the upland areas• protecting downslope areas from damage by the eroded soil
*Adapted from www.ecosystemvaluation.org
urban growth and industrial development
farming moved into hilly upland areas
Inadequate soil management techniques and errors in field layout and construction
Heavy soil erosion on upland areas
Damage Cost Avoided, Replacement Damage Cost Avoided, Replacement Cost, and Substitute Cost Methods Cost, and Substitute Cost Methods
• Analysis – Researchers measured the cost of physically replacing lost soil,
nutrients, and water in upland areas the cost of compensating for downstream losses
• calculate the annual soil loss per hectare, nutrient loss/hectare, and water runoff/hectare
• calculate the expected losses, in terms of replacement costs, if the new management practices were not implemented
Measured parameter Cost (W/ha/yr)Recovering and replacing eroded soil 80,000Fertilizer and spreading to replace lost nutrients 31,200 Annual field maintenance and repair 35,000Damage to downstream fields in lost production 30,000Supplemental irrigation to replace lost water 92,000Total cost of soil erosion under existing management 268,200Net present value using a 15 year time horizon 2,039,662
Damage Cost Avoided, Replacement Damage Cost Avoided, Replacement Cost, and Substitute Cost Methods Cost, and Substitute Cost Methods
• Analysis (cont’d)– calculate costs with the new management techniques
• compensation payments• soil replacement, nutrient replacement, and mulching
– The net present value of the costs of new management techniques was estimated at W1,076,742
• Results– the cost of new management techniques (W1,076,742) is
about half the replacement cost (2,039,662)
– The proposed preventive steps are worth implementing
Damage Cost Avoided, Replacement Damage Cost Avoided, Replacement Cost, and Substitute Cost Methods Cost, and Substitute Cost Methods
Illustration 3*: Oil spill damages in Puerto Rico (replacement cost method)• Background
– The Zoe Colocotroni was a ship that spilled oil off the coast of Puerto Rico– The case was taken to court to determine the monetary damages resulting from the
spill’s effects on the local ecosystem
• Analysis– The replacement cost method was used to estimate monetary damages
• Calculating the number of lower trophic organisms killed by the spill• Adding up the cost of purchasing these organisms from a scientific catalogue
• Results– The US Court of Appeals rejected the use of the replacement cost method in this
case• It was not plannned to actually purchase the organisms and restore them to the ocean• By the time such a plan could have been carried out, the organisms would have restored
themselves
• The costs of purchasing the organisms did not accurately measure the actual ecosystem damages.
Damage Cost Avoided, Replacement Damage Cost Avoided, Replacement Cost, and Substitute Cost Methods Cost, and Substitute Cost Methods
• Advantages
– May provide a rough indicator of economic value• subject to data constraints and the degree of similarity or
substitutability between related goods. – They are less data and resource-intensive
• It is easier to measure the costs of producing benefits than the benefits themselves, when goods, services, and benefits are non-marketed
– Data or resource limitations may rule out valuation methods that estimate willingness to pay
– Provide surrogate measures of value that are as consistent as possible with the economic concept of use value, for services which may be difficult to value by other means
Damage Cost Avoided, Replacement Damage Cost Avoided, Replacement Cost, and Substitute Cost Methods Cost, and Substitute Cost Methods
• Issues and Limitations
– Do not provide a technically correct measure of economic value, which is properly measured by the maximum amount of money or other goods that a person is willing to give up to have a particular good, less the actual cost of the good
– Assume that expenditures to repair damages or to replace ecosystem services are valid measures of the benefits provided
– Do not consider social preferences for ecosystem services, or individuals’ behaviour in the absence of those services
Damage Cost Avoided, Replacement Damage Cost Avoided, Replacement Cost, and Substitute Cost Methods Cost, and Substitute Cost Methods
• Issues and Limitations (cont’d)
– May be inconsistent because few environmental actions and regulations are based solely on benefit-cost comparisons, particularly at the national level
• the cost of a protective action may exceed the benefits to society
• the cost of actions already taken to protect an ecological resource will underestimate the benefits of a new action to improve or protect the resource
Damage Cost Avoided, Replacement Damage Cost Avoided, Replacement Cost, and Substitute Cost Methods Cost, and Substitute Cost Methods
• Issues and Limitations (cont’d)– The replacement cost method requires information on
the degree of substitution between the market good and the natural resource
• Substitute goods are unlikely to provide the same types of benefits as the natural resource
Damage Cost Avoided, Replacement Damage Cost Avoided, Replacement Cost, and Substitute Cost Methods Cost, and Substitute Cost Methods
• Issues and Limitations (cont’d)
– The goods/services being replaced probably represent only a portion of the full range of services provided by the natural resource
• the benefits of an action to protect or restore the ecological resource would be understated.
– Without evidence that the public would demand the least cost alternative for the affected ecosystem, this methodology is not an economically appropriate estimator of ecosystem service value
EEnd of nd of SSessions essions 33 & & 44
Thank YouThank You
REGIONAL WORKSHOP REGIONAL WORKSHOP ONON
THE COST OF THE COST OF ENVIRONMENTAL ENVIRONMENTAL
DEGRADATION DEGRADATION METHODOLOGYMETHODOLOGY
Session 5THE TRAVEL COST METHOD
REGIONAL WORKSHOP ONREGIONAL WORKSHOP ON
THE COST OF ENVIRONMENTAL THE COST OF ENVIRONMENTAL DEGRADATION METHODOLOGYDEGRADATION METHODOLOGY
Session 5THE TRAVEL COST METHOD
Preferences
Revealedpreferences
StatedPreferences
MarketValues
Travel Cost Methods
HedonicMethod
Averting Behavior
ContingentValuation
ChoiceExperiments
USE VALUES USE + NON-USE VALUES
Dose Response Functions
Environmental Valuation MethodsEnvironmental Valuation Methods
TRAVEL COST METHODTRAVEL COST METHODOUTLINEOUTLINE
• Introduction• Theory• Forms of TCM• Illustration• Advantages• Issues and Limitations• Case-applications
– Environmental conservation– Improvements in water quality
• Case studies– Beach degradation in Morocco– The value of forestry in Britain
TRAVEL COST METHODTRAVEL COST METHODIntroductionIntroduction
• Used to estimate use values associated with ecosystems or sites that are used for recreation
• Assumes that the value of the site or its recreational services is reflected in how much people are willing to pay to get there
• Useful in planning for the provision and management of outdoor recreation, such as: – changes in access costs for a recreational site – elimination of an existing recreational site – addition of a new recreational site – changes in environmental quality at a recreational site
TRAVEL COST METHODTRAVEL COST METHODTheoryTheory
• Based on the premise that– The cost an individual incurs in visiting a site reflects his
valuation to the site – Individuals will react to an increase in entry fees the same
way as they would react to an increase in travel cost
• The most controversial aspects of the travel cost method include – accounting for the opportunity cost of travel time– handling multi-purpose and multi-destination trips– the fact that travel time might not be a cost to some
people, but might be part of the recreational experience
TRAVEL COST METHODTRAVEL COST METHODTheoryTheory
• A demand curve can be generated for the site in question– By collecting information
from people on• Where they had travelled
from• The costs they have
incurred– By deriving a trip generation
function– By deriving an aggregate
demand curve for visits to the site per year, and thus for the recreational or scenic services of the site
Number of visits per year
Trav
el c
ost p
er v
isit
(US
D)
Trip Generation Function
Consumer surplus
B
A
C
D
TRAVEL COST METHODTRAVEL COST METHODInterpreting TravelInterpreting Travel--Cost ModelsCost Models
Linear functional form: V = α + βC +γSWhere:
V = number of visits to a siteα = constantβ = coefficient of C, usually negativeC = cost of travel to gain access to siteγ = coefficient of S, probably negativeS = cost of travel to gain access to the respondent’s preferred substitute site
– The TCM is used to estimate α, β, and γ• Estimated consumer surplus (CS) for an individual
making q visits to the siteCS = -q2 / 2β
– This functional form implies finite visits at zero costs
– This functional form has a critical cost above which negative visits will be demanded
TRAVEL COST METHODTRAVEL COST METHODInterpreting TravelInterpreting Travel--Cost ModelsCost Models
Log-Linear functional form: lnV = α + βC +γSWhere:
V = number of visits to a siteα = constantβ = coefficient of C, usually negativeC = cost of travel to gain access to siteγ = coefficient of S, probably negativeS = cost of travel to gain access to the respondent’s preferred substitute site
– The TCM is used to estimate α, β, and γ• Estimated consumer surplus (CS) for an individual
making q visits to the siteCS = -q / β
– This functional form has been widely used in TCM models
• It implies a finite number of visits at zero cost• It never predicts negative visits even at very high costs
TRAVEL COST METHODTRAVEL COST METHODTheoryTheory
• This demand curve– shows how many visits people would
make at various travel cost prices– is used to estimate the willingness to
pay for people who visit the site– is downward sloping where travel cost
is inversely related to number of visits• people who live farther from a site will
visit it less often, because it costs more in terms of actual travel costs and time to reach the site.
• Other factors that may affect the number of visits to a site– Visitors’ income – The availability of alternative sites or
substitutes– Factors like personal interest in the
type of site, or level of recreational experience
Number of visits per year
Trav
el c
ost p
er v
isit
(US
D)
Demand curve for the travel cost method
Consumer
surplus
TRAVEL COST METHODTRAVEL COST METHODForms of the TCMForms of the TCM
Individual TCM
• Uses the number of visits per year made by an individual
• Requires more data collection and slightly more complicated analysis
• Gives more precise and statistically efficient results
• More flexible than ZTCM and applicable at a wider range of sites
Random utility approach
• The most complicated and expensive
• Allows for much more flexibility in calculating benefits
• Best suited to estimate benefits for specific characteristics of sites, rather than for the site as a whole
• Most appropriate when there are many substitute sites
Zonal TCM
• Concentric zones defined around each site
• Cost of travel in each zone is constant
• Site visitors grouped by zone of origin
• May rely on secondary data• The simplest and least
expensive approach• Suited when visitors origins
are relatively evenly distributed
• Unsuitable for linear recreational sites
TRAVEL COST METHODTRAVEL COST METHODZonalZonal TCMTCM
• Zonal TCM methodology1. Identify site and collect data from visitors on
• their points of origin• number of visits from each origin zone• round-trip mileage from each zone • travel costs per mile • demographic information about people from each zone
2. Define zones of origin and allocate visitors to the appropriate zone• Zones commonly defined based on
straight line distance from site• GIS techniques allow redefining zones
based on road distances or travel times3. Calculate zonal visits per household to the site
• Estimate number of households per zone• Divide number of household visits originating in zone h by the total number of
households in the zone4. Calculate average travel cost from each zone to the site5. Use census data to derive variables relating to zonal socio-economic
characteristics
32
1S
TRAVEL COST METHODTRAVEL COST METHODZonalZonal TCMTCM
• Zonal TCM methodology (cont’d)6. Use data collected above to estimate the trip generation
function
VVhh/N/Nhh = f(C= f(Chh,X,Xhh,S,Shh))
6. Derive demand curve7. Obtain zonal household consumer surplus estimates through
integrating under the demand curve8. Calculate aggregate zonal consumer surplus
• By multiplying consumer surplus per household by the number of households in each zone
10. Aggregate zonal consumer surplus estimates to obtain an estimate of total consumer surplus or the benefits of the site
where: Vh = # of visits from zone hNh = population of zone hCh = travel cost from zone hXh = a vector of socio-economic variables that
explain changes in VSh = a vector of substitute recreational site
characteristics for residents of zone h
TRAVEL COST METHODTRAVEL COST METHODIndividual TCMIndividual TCM
• Individual TCM methodology1. Identify site2. Use an on-site questionnaire survey to collect data from
visitors relating to• Cost of travel to the site• Number of visits to the sites• Recreational preferences• Socio-economic characteristics
3. Specify trip-generation function
Vij = f(Cij,Tij,Qi,Sj, Yi) where: Vi = # of visits made by individual i to site jCij = travel cost incurred by individual i when visiting site jQj = a vector of perceived qualities of the recreation site jSj = a vector of available substitute recreational site
characteristics Yi = household income of individual i
TRAVEL COST METHODTRAVEL COST METHODIndividual TCMIndividual TCM
• More complicated, and thorough, applications may also collect information about: – exact distance that each individual travelled to the site – exact travel expenses – the length of the trip – the amount of time spent at the site – other locations visited during the same trip, and amount of time spent at
each – substitute sites that the person might visit instead of this site, and the
travel distance to each – other reasons for the trip (is the trip only to visit the site, or for several
purposes) – quality of the recreational experience at the site, and at other similar
sites (e.g., fishing success) – perceptions of environmental quality at the site – characteristics of the site and other, substitute, sites
TRAVEL COST METHODTRAVEL COST METHODIndividual TCMIndividual TCM
• Individual TCM methodology (cont’d)4. Estimate travel cost model taking truncation
into account• Truncation accounts for non-visitors behavior
5. Derive demand curve and obtain household consumer surplus estimates through integrating under the demand curve
6. Calculate aggregate consumer surplus for the site
TRAVEL COST METHODTRAVEL COST METHODRandom utility approachRandom utility approach
• Focuses attention on the choice among alternative sites for any given recreational trip and assumes the visitor is comparing utilities for available destinations
• First models the individual’s decision on whether or not to participate in recreational activity
• Then models the decision on the number of visits
• Models used include– Probit, tobit, and logit
TRAVEL COST METHODTRAVEL COST METHODIllustrationIllustration
• Background– A site used mainly for recreational fishing is threatened by development
in the surrounding area• Pollution and other impacts from this development could destroy the fish
habitat at the site, resulting in a serious decline in, or total loss of, the site’s ability to provide recreational fishing services
• Resource agency staff want to determine the value of programs or actions to protect fish habitat at the site
• The Travel Cost Method was selected because– The site is primarily valuable to people as a recreational site– There are no endangered species or other highly unique qualities that
would make non-use values for the site significant– The expenditures for projects to protect the site are relatively low
• Alternative Approaches– Contingent valuation or contingent choice methods
• might produce more precise estimates of values for specific characteristics of the site
• could capture non-use values• are considerably more complicated and expensive to apply
TRAVEL COST METHODTRAVEL COST METHODIllustrationIllustration
Application of the Zonal Travel Cost Approach
Step 1• Define a set of zones surrounding the site by
– concentric circles around the site, or – geographic divisions
• metropolitan areas or counties surrounding the site at differentdistances
Step 2• Collect information on
– the number of visitors from each zone– the number of visits made in the last year
• For this example, assume that staff at the site keep records of the number of visitors and their zip code, which can be used to calculate total visits per zone over the last year
TRAVEL COST METHODTRAVEL COST METHODIllustrationIllustration
Application of the Zonal Travel Cost Approach
Step 3• Calculate the visitation rates per 1,000 population in each zone• This is the total visits per year from the zone, divided by the zone’s
population in thousands
Zone Total Visits/Year Zone Population
Visits/1000
0 400 1,000 400
1 400 2,000 200
2 400 4,000 100
3 400 8,000 50
Beyond 3 0
Total visits 1,600
TRAVEL COST METHODTRAVEL COST METHODIllustrationIllustration
Application of the Zonal Travel Cost Approach
Step 4• Calculate the average round-trip travel distance and travel time to
the site for each zone• Using average cost per mile and per hour of travel time, calculate
the travel cost per trip– Assume that this cost per mile is USD 0.30.
• The cost of time calculated using the simplest approach involving the average hourly wage– Assume that it is 9 USD/hour, $0.15 USD/minute for all zones,
although in practice it is likely to differ by zone
Zone Round Trip Travel Distance
(miles)
Round TripTravel Time
(mins)
Distance times Cost/Mile ($.30)
(cost a)
Travel Time times Cost/Minute ($.15)
(cost b)
Total Travel (Cost/Trip)
0 0 0 0 0 0
1 20 30 $6 $4.50 $10.50
2 40 60 $12 $9.00 $21.00
3 80 120 $24 $18.00 $42.00
Application of the Zonal Travel Cost Approach
Step 5• Estimate the trip generation function using regression analysis
– This allows the researcher to estimate the demand function for the average visitor
– The analysis might include demographic variables, such as age, income, gender, and education levels, using the average values for each zone
– To maintain the simplest possible model, calculating the equation with only the travel cost and visits/1000
Visits/1000 = 330 – 7.755*(Travel Cost)
TRAVEL COST METHODTRAVEL COST METHODIllustrationIllustration
TRAVEL COST METHODTRAVEL COST METHODIllustrationIllustration
Application of the Zonal Travel Cost Approach
Step 6• Construct the demand function for visits to the site
– The first point on the demand curve is the total visitors to the site at current access costs
• 1,600 visits per year– The other points are found by estimating the number of visitors
with different hypothetical entrance fees• Example: start by assuming a $10 entrance fee
Plugging this into the estimated regression equation, V = 330 – 7.755C, gives the following:
Zone Travel Cost plus $10 Visits/1000 Population Total Visits
0 $10 252 1000 252
1 $20.50 171 2000 342
2 $31.00 90 4000 360
3 $52.00 0 8000 0
Total Visits 954
Application of the Zonal Travel Cost Approach
Step 6 (cont’d)• This gives the second point on the
demand curve—954 visits at an entry fee of $10. In the same way, the number of visits for increasing entry fees can be calculated
• These points give the demand curve for tripsto the site.
TRAVEL COST METHODTRAVEL COST METHODIllustrationIllustration
0
10
20
30
40
50
60
0 400 800 1200 1600 2000
Total visits
Add
ed c
ost p
er tr
ip
Entry Fee Total Visits
$20 409
$30 129
$40 20
$50 0
TRAVEL COST METHODTRAVEL COST METHODIllustrationIllustration
Application of the Zonal Travel Cost Approach
Step 7• Estimate the total economic benefit of the site to visitors by
calculating the consumer surplus, or the area under the demand curve.
• The total estimate of economic benefits from recreational uses of the site is around $23,000 per year, or around $14.38 per visit
• If the actions to protect the site cost less than $23,000 per year, the cost will be less than the benefits provided by the site
• If the costs are greater than this, the staff will have to decide whether other factors make them worthwhile.
TRAVEL COST METHODTRAVEL COST METHODIllustrationIllustration
Application of the Individual Travel Cost Approach
• Conduct a survey of visitors on – location of the visitor’s home – distance travelled to the site – how many times they visited the site in the past year or season – the length of the trip – the amount of time spent at the site – travel expenses – the person’s income or other information on the value of their time – other socioeconomic characteristics of the visitor – other locations visited during the same trip, and amount of time spent at
each – other reasons for the trip (is the trip only to visit the site, or for several
purposes) – fishing success at the site (how many fish caught on each trip) – perceptions of environmental quality or quality of fishing at the site – substitute sites that the person might visit instead of this site
TRAVEL COST METHODTRAVEL COST METHODIllustrationIllustration
Application of the Individual Travel Cost Approach (cont’d)
• Estimate the relationship between number of visits and travel costs and other relevant variables using regression analysis– Use individual data rather than data for each zone– The regression equation gives the demand function for the
“average” visitor to the site– The area below this demand curve gives the average consumer
surplus
• Multiply the average consumer surplus by the total relevant population in the region where visitors come from
to estimate the total consumer surplus for the site
TRAVEL COST METHODTRAVEL COST METHODIllustrationIllustration
Application of the Individual Travel Cost Approach (cont’d)
• Value estimates can be improved by adding other factors to the statistical model– additional data about visitors, substitute sites, and quality
of the site has been collected– Including information about the quality of the site allows
the researcher to estimate the change in value of the site if its quality changes
• two different demand curves would be estimated—one for each level of quality
• the area between these two curves is the estimate of the change in consumer surplus when quality changes
TRAVEL COST METHODTRAVEL COST METHODIllustrationIllustration
Application of the Random Utility Approach
• The agency might want to value the economic losses from a decrease in fish populations, rather than from loss of the entire fish stock
• The random utility approach focuses on choices among alternativesites which have different quality characteristics.
• The random utility approach assumes that individuals will pick the site that they prefer, out of all possible fishing sites.
• This model requires information on– all possible sites that a visitor might select– their quality characteristics– the travel costs to each site
TRAVEL COST METHODTRAVEL COST METHODIllustrationIllustration
Application of the Random Utility Approach (cont’d)
• Conduct a telephone survey of randomly selected residents of the state– Ask residents if they go fishing or not– If they do, it would then ask a series of questions
• how many fishing trips they took over the last year (or season)• where they went• the distance to each site• and other information similar to the information collected in our individual travel cost survey
– Might also ask questions about fish species targeted on each trip, and how many fish were caught.
• Estimate a statistical model that can predict– the choice to go fishing or not,– the factors that determine which site is selected
• If quality characteristics of sites are included, the model can estimate values for changes in site quality, for example the economic losses caused by a decrease in catch rates at the site
TRAVEL COST METHODTRAVEL COST METHODAdvantagesAdvantages
• It is based on real data rather than stated willingness to pay and as such provides true values
• It is relatively inexpensive to apply
• On-site surveys provide opportunities for large sample sizes, as visitors tend to be interested in participating
• The results are relatively easy to interpret and explain
TRAVEL COST METHODTRAVEL COST METHODIssues and limitations (1)Issues and limitations (1)
• The method assumes that people perceive and respond to changes in travel costs the same way that they would respond to changes in admission price
• The most simple models assume that individuals take a trip for the single purpose of visiting a specific recreational site– if a trip has more than one purpose, the value of the site may be
overestimated
• Defining and measuring the opportunity cost of time, or the value of time spent travelling, can be problematic– There is no consensus on how to account for time – Travel time may be a benefit if people enjoy the travel itself leading
to an overestimation of the value of the site
• The availability of substitute sites will affect values– Ex: if two people travel the same distance, they are assumed to
have the same value. However, if one person has several substitutes available but travels to this site because it is preferred, this person’s value is actually higher. Some of the more complicated models account for the availability of substitutes.
TRAVEL COST METHODTRAVEL COST METHODIssues and limitations (2)Issues and limitations (2)
• The assumption that travel costs reflect recreational value may not always be true– Those who value certain sites may choose to live nearby,
resulting in low travel costs, but high values for the site
• Visits to certain sites could be seasonal and thus survey results could be biased unless survey is conducted for a long period
• Interviewing visitors on site can introduce sampling biases to the analysis
• Measuring recreational quality and relating it to environmental quality can be difficult
• Standard travel cost approaches provides information about current conditions, but not about gains or losses from anticipated changes in resource conditions
TRAVEL COST METHODTRAVEL COST METHODIssues and limitations (3)Issues and limitations (3)
• The demand function requires enough difference between distances travelled to affect travel costs and for differences in travel costs to affect the number of trips made– it is not well suited for sites near major population centers where many
visitations may be from "origin zones" that are close to one another
• The travel cost method is limited in its scope of application because it requires user participation– It cannot be used to assign values to on-site environmental features and
functions that users of the site do not find valuable– It cannot be used to value off-site values supported by the site– It cannot be used to measure non-use values– It excludes non-users who may have significant values for the site
• Certain statistical problems can affect the results, including – Choice of the functional form used to estimate the demand curve– Choice of the estimating method– Choice of variables included in the model
TRAVEL COST METHODTRAVEL COST METHODCase application 1Case application 1: Environmental Conservation : Environmental Conservation
Background*• Hell Canyon on the Snake River separating Oregon
and Idaho– offers spectacular vistas and outdoor amenities to visitors – supports important fish and wildlife habitat
• It also has economic potential as a site to develop hydropower.
– Generating hydropower there would require building a dam– Dam and the resulting lake would significantly and
permanently alter the ecological and aesthetic characteristics of Hell Canyon
Challenge• Controversies regarding the future of Hell Canyon
during the 1970’s• Environmental economists were asked to develop
an economic analysis justifying the preservation of Hell Canyon in its natural state
www.bigfootoutfitters.com
www.colonelkern.com
* www.ecosystemvaluation.org
TRAVEL COST METHODTRAVEL COST METHODCase application 1Case application 1: Environmental Conservation : Environmental Conservation
Methodology• the net economic value (cost savings) of producing
hydropower at Hell Canyon was $80,000 higher than at the "next best" site which was not environmentally sensitive
• The recreational value of Hell Canyon was estimated via a low-cost/low precision travel-cost survey at about $900,000
• Even if the "true value" of recreation at Hell Canyon was ten times less than their estimate, it would still be greater than the $80,000 economic payoff from generating power there as opposed to the other site
Results• Based largely on the results of this non-market valuation
study, Congress voted to prohibit further development of Hell Canyon
www.windingwatersrafting.com/hell_rates.php
TRAVEL COST METHODTRAVEL COST METHODCase application 2Case application 2: Improvements in Water : Improvements in Water
QualityQualityBackground*• The costs to farmers and taxpayers of implementing
on-farm best management practices to reducesediment and nutrient runoff to the ChesapeakeBay are well known
• Controversies arose over the benefits ofresulting improvements in water quality
Challenge • To assess the economic benefits of water quality improvements to beach
users in the Chesapeake Bay area• To establish linkages between differences in water quality and
differences in willingness to pay for beach use- reflected in the travel costs to visitors to particular beaches
• The hypothesis to be tested – average willingness to pay was positively correlated with water quality
• If the hypothesis was correct the results would allow the estimation of the increase in willingness to pay of improving water quality at all beaches
www.chesapeakebaysampler.com/
* www.ecosystemvaluation.org
TRAVEL COST METHODTRAVEL COST METHODCase application 2Case application 2: Improvements in Water : Improvements in Water
QualityQualityMethodology• The concentration of nitrogen and phosphorous in the water at the
monitoring station nearest to the beach was selected as an index of water quality at the beach
– reflect s the level of objectionable visual and other characteristics that affect the value of beach use.
• A cross-sectional analysis of travel cost data was used– collected from 484 people at 11 public beaches – a 20% increase in water quality was assumed to be associated with a 20% reduction in total
nitrogen and phosphorus
Results• The average annual benefits to all Maryland beach users of the
improvements in water quality were estimated to be $35 million in 1984 dollars
• These were thought to be conservative for several reasons, including: – The value of improvements in water quality was only shown to increase the value of current
beach use– Improved water quality can also be expected to increase overall beach use – Estimates ignore visitors from outside the Baltimore-Washington statistical metropolitan
sampling area– The population and incomes in origin zones near the Chesapeake Bay beach areas are
increasing, which is likely to increase visitor-days and thus total willingness to pay
The Travel Cost MethodThe Travel Cost MethodCaseCase--study 1: Beach degradation in Moroccostudy 1: Beach degradation in Morocco
The situation*• The coastline of Morocco
– 3,500 km long, 13 coastal zones, 174 beaches
Coastal zone/ Coastal zone/ Beach Beach
degradationdegradation
In 2002, “Monitoring Bathing Beach Waters in Morocco”campaign showed that 28% of beaches were unfit for swimming28% of beaches were unfit for swimming
•Domestic and industrial wastewater discharge, industrial accidents
•Offshore pollution from ships and boat harbors
•Haphazard construction along the coast, etc.
* World Bank, 2003
The Travel Cost MethodThe Travel Cost MethodCaseCase--study 1: Beach degradation in Moroccostudy 1: Beach degradation in Morocco
The situation• Annual cost of coastal degradation
– Willingness to Pay (WTP) of foreign tourists and Moroccan nationals living abroad to improve the coast
– Loss of local fishing (sardines)
– Lost recreational value for Moroccan residents •• Value of additional travel costs (including time) incurred by Value of additional travel costs (including time) incurred by
Moroccan residents Moroccan residents to find beaches of “better” environmental quality
The Travel Cost MethodThe Travel Cost MethodCaseCase--study 1: Beach degradation in Moroccostudy 1: Beach degradation in MoroccoThe methodology
• Additional travel cost incurred– Longer distances traveled by car, bus or taxi to visit
“less degraded” beaches• For citizens using cars, additional travel costs per beach visit
include:– Fuel costs– Vehicle operating costs, and– Journey time lost
– Estimation conducted for cities of• Rabat• Tangiers• Casablanca
The Travel Cost MethodThe Travel Cost MethodCaseCase--study 1: Beach degradation in Moroccostudy 1: Beach degradation in Morocco
The methodology• Step 1: Estimation of additional travel cost for beach visits by car
– Number of visits to beach by car per household = 10-20– Assumption that 50% of households with cars visit more distant beaches for environmental
reasons– Additional travel cost by car per visit
• vehicle functioning = Dh 4.6/km• additional distance of 30 km (round trip)• additional time of 2 hrs estimated at Dh 15/hr• = (Dh 4.6/km x 30 km) + (Dh 15/hr x 2 hrs) = 168 Dh
Parameter ValueUrban households in Rabat-Tangiers-Casablanca 937,143Households with cars (20%) 187,400Households with cars that visit more distant beaches 93,700Number of yearly visits to beach by car per household 10 - 20Total number of yearly visits to beach by car 937,000 - 1,874,000Average additional travel cost by car per visit (Dh/visit)* 168Total additional yearly travel cost for beach visits by car (Dh) 157,416,000 - 314,832,000
The Travel Cost MethodThe Travel Cost MethodCaseCase--study 1: Beach degradation in Moroccostudy 1: Beach degradation in Morocco
The methodology• Step 2: Estimation of additional travel cost for beach visits by bus/taxi
– 20% of population visit beach by bus or taxi– 50% of population without cars visit more distant beaches for environmental reasons– Number of visits to beach by bus or taxi per person = 10-20– Average additional travel cost by bus or taxi is 10 Dh
Parameter ValueUrban population of Rabat-Tangiers-Casablanca 5,248,000Persons from Rabat-Tangiers-Casablanca visiting beaches by bus/taxi 1,049,600Persons visiting, by bus or taxi, more distant beaches 524,800Number of yearly visits to beach per person 10 - 20Total number of yearly visits to beach by bus or taxi 5,248,000 - 10,496,000Average additional travel cost by bus or taxi per visit (Dh/visit) 10Total additional yearly travel cost for beach visits by bus or taxi (Dh) 50,248,000 - 100,496,000
The Travel Cost MethodThe Travel Cost MethodCaseCase--study 1: Beach degradation in Moroccostudy 1: Beach degradation in Morocco
The methodology• Step 3: Assessing the total additional travel cost due
to beach degradation
The average total additional travel cost due to The average total additional travel cost due to beach degradation in Moroccobeach degradation in Morocco
Dh 311.5 million, 0.09 % of the GDPDh 311.5 million, 0.09 % of the GDP
Lower bound
Higher bound
Additional travel cost for beach visits by cars (million Dh) 157.4 314.8Additional travel cost for beach visits by bus/taxi (million Dh) 50.2 100.5Total additional travel cost (million Dh) 207.6 415.3Percent of GDP (%) 0.06 0.12
TRAVEL COST METHODTRAVEL COST METHODCaseCase--study 2: The value of forestry in study 2: The value of forestry in
BritainBritainSituation*• Estimate the total recreational
value of Forestry Commission woodland in Great Britain
Methodology– Define representative forest types
• Cluster analysis used• 14 similar groups of forests identified• Sample forests selected from each group
– Conduct interviews with visitors of 15 forests– Allocate visitors into 20 concentric distance zones at 5-
mile intervals• Those further than this were allocated together in a single zone
www.ecastles.co.uk/thetford.html
* Hodge, I. 1995
TRAVEL COST METHODTRAVEL COST METHODCaseCase--study 2: The value of forestry in study 2: The value of forestry in
BritainBritainMethodology (cont’d)
– Develop the Trip generation functionsby estimating the relationship betweenthe visit rate from each zone and thetransport cost• taking into account the socio-economic characteristics of the zones
– Use trip generation functions to estimate the consumer surplus or the total value of each visit
• Represented by the maximum willingness to pay minus the cost of each trip
– Estimate the total value for each site by summing up across all visitors to each site produced
www.avich-kilchrenan.co.uk/
TRAVEL COST METHODTRAVEL COST METHODCaseCase--study 2: The value of forestry in study 2: The value of forestry in
BritainBritain
Consumer surplus estimates fornon-priced recreation for forest districts
Consumer surplus per recreational visitor (£)
Consumer surplus per
hectare of forest(£/ha)
Annual number of visitors to the cluster of forests
(1000s)
Total consumer surplus
(£million)
New Forest 1.43 425 8,000 11,440
Loch Awe 3.31 <1 34 0.114
Brecon 2.26 27 2,117 4.784
South Lakes 1.34 31 1,968 2.637
Thetford 2.66 14 4,742 10.718
TRAVEL COST METHODTRAVEL COST METHODCaseCase--study 2: The value of forestry in study 2: The value of forestry in
BritainBritainResults• By summing up all estimates of
consumer surplus– The value of non-priced recreation
for Forestry Commission forests asa whole = £ 53 million
– This compares with £ 71 million income to Forestry Enterprise, the timber production arm of Forestry Commission from the sale of timber in 1988
– In this year, there was an annual net subsidy of £ 8.5 millionpaid on forestry recreation and amenity in terms of visitors centers, forest walks, wildlife, conservation, etc.
– Provision for non-priced recreation represents good value
EEnd of nd of SSession ession 55
Thank YouThank You
REGIONAL WORKSHOP REGIONAL WORKSHOP ONON
THE COST OF THE COST OF ENVIRONMENTAL ENVIRONMENTAL
DEGRADATION DEGRADATION METHODOLOGYMETHODOLOGY
Session 6THE HEDONIC PRICING METHOD
THE AVERTING BEHAVIOR METHOD
WORKSHOP ONWORKSHOP ON
COST OF ENVIRONMENTAL COST OF ENVIRONMENTAL DEGRADATION METHODOLOGYDEGRADATION METHODOLOGY
Session 6HEDONIC PRICING METHOD
AVERTING BEHAVIOR METHOD
Preferences
Revealedpreferences
StatedPreferences
MarketValues
Travel Cost Methods
HedonicMethod
Averting Behavior
ContingentValuation
ChoiceExperiments
USE VALUES USE + NON-USE VALUES
Dose Response Functions
Environmental Valuation Environmental Valuation MethodsMethods
HEDONIC PRICING METHODHEDONIC PRICING METHODOUTLINEOUTLINE
• Theory• Methodology• Illustration• Advantages• Issues and limitations• Case-study 1
Values of environmental amenities in Southold, Long Island
• Case-study 2Values of Environmental Amenities in Marickville and Rockdale, Sydney
• Case-study 3Effect of landfill sites on housing value, Minnesota
• Case-study 4Impact of Solid Waste Dumping on Land Prices in Tunisia
• Case-study 5Quarries in Mount Lebanon
HEDONIC PRICING METHODHEDONIC PRICING METHODTheoryTheory
• Used to estimate the value or price of an environmental feature by looking at actual markets where the attributes are traded
• Most commonly applied in relation to the public’s willingness to pay for housing/ property
• Also applied in labour markets for health economic valuation
HEDONIC PRICING METHODHEDONIC PRICING METHODTheoryTheory
Hedonism is the philosophy that pleasure is of ultimate importance, the most important pursuit. The name derives from the Greek word for delight.
Based on the assumption that people value the characteristics of a good, or the services it provides, rather than the good itself. Thus, prices will reflect the value of a set of characteristics, including environmental characteristics, that people consider important when purchasing the good– Ex: the price of a car reflects the characteristics of that car—
transportation, comfort, style, luxury, fuel economy, etc.• We can value the individual characteristics of a car or other good by
looking at how the price people are willing to pay for it changes when the characteristics change
HEDONIC PRICING METHODHEDONIC PRICING METHODTheoryTheory
• Assumes that– The price of a product is a function of its characteristics– The range of product choices is continuous– The choice is based on perfect information and with no mobility
restrictions– The amount of a particular characteristic can be varied
independently
• Relatively straightforward and uncontroversial to apply, because it is based on actual market prices and fairly easily measured data– If data are readily available, it can be relatively inexpensive to
apply– If data must be gathered and compiled, cost can increase
substantially
HEDONIC PRICING METHODHEDONIC PRICING METHODTheoryTheory
• Usually applied ex post, to examine the effects of developments and policies after implementation
• Can be used to estimate economic benefits or costs associated with– Environmental risk
• Ex: effect of information of different levels of earthquake damage on property values
– Environmental quality • Water pollution
– Ex: Impact on waterfront property• Air pollution• Noise
– Ex: Impact of highway noise and aircraft noise• Soil quality and erosion
– Environmental amenities• Aesthetic views, proximity to recreational sites, hazardous sites, waste
management sites, etc.
If all characteristics of houses and neighbourhoods in a given area were the same, except for the level of air pollution, then houses with better air quality would cost more. This higher price reflects the value of cleaner air to people who purchase houses in the area.
HEDONIC PRICING METHODHEDONIC PRICING METHODMethodologyMethodology
• Applying the Hedonic Pricing Method using housing prices– The price of a house is related to
• Structural characteristics of the house– Plot size, number of rooms, garage space, structural integrity, etc.
• Local socio-economic and public sector characteristics– Unemployment rate, social conditions, quality of schools, etc.
• Local amenity– Environmental quality, access to services, communications, etc.
– Upon controlling for non-environmental factors, any remaining differences in price can be attributed to differences in environmental quality
HEDONIC PRICING METHODHEDONIC PRICING METHODMethodologyMethodology
• Applying the Hedonic Pricing Method using housing prices– Collect the needed information
• Data requirements fall into 2 broad categories– Specific: Cross-section and/or time-series data on property values and
property and household characteristics for a well-defined market area» Structural and locational information» Details of purchase or tenancy (price, date, personal and financial
particulars of the purchasers)– Local: area where transaction occurred
» Neighbourhood, amenity, environmental, and socio-economic factors
» A measure or index of the environmental amenity of interest
• Data sources depend on country/ state involved– Government agencies, estate agents and realtors, mortgage granting
institutions, etc.– GIS, postcode classification of neighbourhood types, etc.
HEDONIC PRICING METHODHEDONIC PRICING METHODMethodologyMethodology
• Applying the Hedonic Pricing Method using housing prices (cont’d)– Analyze the data using regression analysis, relating
the price of the property to its characteristics and the environmental characteristics of interest
Output is a function linking property value to characteristics:
property value=a0+a1size+a2rooms+a3environmental quality+…
where property value is the dependent variablesize, rooms, environmental quality are independent
variables
HEDONIC PRICING METHODHEDONIC PRICING METHODMethodologyMethodology
• Applying the Hedonic Pricing Method using housing prices (cont’d)
• The analysis will indicate how much property values will change for a small change in each characteristic, holding all other characteristics constant
property value=a0+a1size+a2rooms+a3environmental quality• The analysis may be complicated by a number of factors
– The relationship between price and characteristics of the property may not be linear – prices may increase at an increasing or decreasing rate when characteristics change
– Multicollinearity:» many of the variables are likely to be correlated, so that
their values change in similar ways» this can lead to understating the significance of some
variables in the analysis
HEDONIC PRICING METHODHEDONIC PRICING METHODMethodologyMethodology
• Applying the Hedonic Pricing Method using housing prices (cont’d)– Different functional forms and model
specifications for the analysis must be considered
property value=a0+a1size+a2rooms+a3environmental quality+a4size2
log(property value)=a0+a1size+a2rooms+a3environmental quality
HEDONIC PRICING METHODHEDONIC PRICING METHODMethodologyMethodology
• Applying Hedonic Wage Models– Hedonic technique applied to wage rates
• An individual choice of job may be influenced by the job location if it improves access to desirable services
Hourly earnings=b0+b1location+b2firm size+b3education+b4experience
– Problems with this technique• High unemployment
– Individuals cannot satisfy their demand for environmental improvement due to unavailability of suitable jobs in areas of higher environmental quality
HEDONIC PRICING METHODHEDONIC PRICING METHODIllustration*Illustration*
• Agency staff want to measure the benefits of an open space preservation program in a region where open land is rapidly being developed
• The Hedonic Pricing Method is used because– Housing prices in the area appear to be related to proximity to
open space– Data on real estate transactions and open space parcels are
readily available
• Alternative Approaches– The travel cost method, if the open space of concern is used
mainly for recreation– Survey-based methods, like contingent valuation or contingent
choice, but are more difficult and expensive to apply
Adapted from www.ecosystemvaluation.org
HEDONIC PRICING METHODHEDONIC PRICING METHODIllustrationIllustration
• Step 1– Collect and compile data on residential property sales
in the region for a specific time period includingdependent variable:• Selling prices and locations of residential propertiesindependent variables:• Structural characteristics (lot size, number and size of rooms,
number of bathrooms)• Local socio-economic characteristics• Local amenity including the environmental characteristic of
concern- the proximity to open space
– Collect data on the amount and type of open space within a given radius of each property, noting the direct proximity of a property to open space
• data may be obtained from computer-based GIS maps
HEDONIC PRICING METHODHEDONIC PRICING METHODIllustrationIllustration
• Step 2– Statistically estimate a function that relates property values to the
property characteristics, including the distance to open space– The resulting function measures the portion of the property price
that is attributable to each characteristic– Estimate the value of preserving open space by looking at how
the value of the average home changes when the amount of open space nearby changes
• Step 3– Evaluate agency investments in open space preservation– Determine the benefits of preserving each parcel, which can
then be compared to the cost
HEDONIC PRICING METHODHEDONIC PRICING METHODAdvantagesAdvantages
• Can be used to estimate values based on actual behaviour and choices
• Property markets are relatively efficient in responding to information, so can be good indications of value
• Property records are typically very reliable
• Data on property sales and characteristics are readily available through many sources, and can be related to other secondary data sources to obtain descriptive variables for the analysis
• Versatile method that can be adapted to consider several possible interactions between market goods and environmental quality
HEDONIC PRICING METHODHEDONIC PRICING METHODIssues and LimitationsIssues and Limitations
• The scope of environmental benefits that can be measured is limited to things that are related to property values
• It will only capture people’s willingness to pay for perceived differences in environmental attributes, and their direct consequences– if people aren’t aware of the linkages between the
environmental attribute and benefits to them or their property, the value will not be reflected in home prices
• It assumes that people are free to select the combination of characteristics satisfying their preferences, given their income– However, the housing market may be affected by outside
influences, like taxes, interest rates, or other factors
HEDONIC PRICING METHODHEDONIC PRICING METHODIssues and LimitationsIssues and Limitations
• It is relatively complex to implement and interpret, requiring statistical expertise
• The results depend heavily on model specifications
• It is susceptible to multicollinearity i.e. a high degree of correlation among the variables under study which makes it difficult to estimate their individual effect– Ex: Air pollution measures where the levels of one form of
pollution (PM) is closely related to levels of another (NO2)
• All relevant variables must be included for the results to be valid
• Large amounts of data must be gathered and manipulated
• The time and expense to carry out an application depends on the availability and accessibility of data
HEDONIC PRICING METHODHEDONIC PRICING METHODCase Study 1: Case Study 1: Values of Environmental Values of Environmental
Amenities in Southold, Long Island*Amenities in Southold, Long Island*• Background
– The town of Southold, Long Island, New York has coastlines on both the Peconic Bay and Long Island Sound
– Southold is a relatively rural area, with a large amount of farmland
– Population and housing density are rapidly increasing in the town, resulting in development pressures on farmland and other types of open space
• The Challenge– The Peconic Estuary Program is considering various
management actions for the Estuary and surrounding land areas– A hedonic valuation study was conducted to assess some of the
values that may result from these management actions, using 1996 housing transactions.
*Adapted from ecosystemvaluation.org
HEDONIC PRICING METHODHEDONIC PRICING METHODCase Study 1: Case Study 1: Values of Environmental Values of Environmental
Amenities in Southold, Long IslandAmenities in Southold, Long Island
• Analysis– Variables relevant for local environmental management with
significant impact on property values in Southold
Location of properties % change in value as compared to similar properties elsewhere
Adjacent to open space 12.8% higher per-acre valueAdjacent to farmland 13.3% lower per-acre valueWithin 20 meters of a major road 16.2% lower per-acre valueWithin an area with two- or three-acre zoning
16.7% higher per-acre value
For every percentage point increase in the percent of a parcel classified as a wetland, the average per-acre value increased by 0.3%
HEDONIC PRICING METHODHEDONIC PRICING METHODCase Study 1: Case Study 1: Values of Environmental Values of Environmental
Amenities in Southold, Long IslandAmenities in Southold, Long Island
• Results – Calculate the value of preserving a parcel of
open space, by calculating the effects on property values adjacent to the parcel
• Ex: the value of preserving a 10 acre parcel of open space, surrounded by 15 “average”properties, was calculated as 410,907 USD
HEDONIC PRICING METHODHEDONIC PRICING METHODCase Study 2: Case Study 2: Values of Environmental Amenities Values of Environmental Amenities
in Marickville and Rockdale, Sydney*in Marickville and Rockdale, Sydney*• Data collected from house sales in 1973-1974 (1,414
observations)
• Information collected on 20 characteristics of each property and the local environment– Size, age, and construction of the house– Size of the plot of land– Type and amount of traffic on the road outside the house– Access to public transport and shops– Aircraft noise– Zoning and plans for road widening
• Some variable were measured directly (number of rooms) and others on a subjective scale (road traffic levels-noisy/normal/quiet)
*Adapted from Hodge (1995)
HEDONIC PRICING METHODHEDONIC PRICING METHODCase Study 2: Case Study 2: Values of Environmental Amenities Values of Environmental Amenities
in Marickville and Rockdale, Sydneyin Marickville and Rockdale, Sydney• Results
– Various types of statistical relationships between house prices and characteristics were tested
– Major determinants of prices were house quality and size and plot size
– Aircraft noise significant determinant of price in Marickville• $1,250 - 3,250 difference depending on house price
– Price of noisy road was $1,400 (5.6% of the house price)– $440 difference between poor and average view and $440
difference between poor and good view
• Limitations– Difficulties in measuring several house attributes– Prices estimated may not have been based on buyers’ informed
judgement
HEDONIC PRICING METHODHEDONIC PRICING METHODCase Study 3: Case Study 3: Effect of landfill sites on Effect of landfill sites on
housing value, Minnesota*housing value, Minnesota*• A sample of 708 single-family homes located
within close proximity of a landfill site
• House values rose by about 0.2 percent per mile from the landfill (when a linear specification is used)
• The effect on house value varied with distance• 12% for houses located at landfill boundary• 6% for houses located one mile from landfill boundary• 0% for houses located more than 2 miles from landfill
boundary(when a non linear specification is used)
Adapted from Hussen (1999); study by Nelson et al. (1992)
HEDONIC PRICING METHODHEDONIC PRICING METHODCaseCase--study 4:study 4: Impact of Solid Waste Dumping on Impact of Solid Waste Dumping on
Land Prices in TunisiaLand Prices in Tunisia
The situation
•Lack of municipal waste collection
•Accumulation of waste
•Presence of unauthorized dumpsites
•Lack of hazardous waste treatment
• Public health risks• Deterioration of
quality of life• Risks on natural
resources through the contamination of soil and water resources
HEDONIC PRICING METHODHEDONIC PRICING METHODCaseCase--study 4:study 4: Impact of Solid Waste Dumping on Impact of Solid Waste Dumping on
Land Prices in TunisiaLand Prices in Tunisia
The methodology• Step 1
Identify and characterize dumpsites
• Step 2Determine the area of land affected by each dumpsite
Ex: Agricultural Region– 1st affected zone: 30m radius– 2nd affected zone : 100m radius
• Step 3Conduct a survey to collect information on
– the value of land not affected by the dumpsite in the neighborhood
– The rate of land devaluation due to proximity to dumpsite
• Step 4Estimate the annual value of neighborhood land
– 10% in this caseEstimate the annual devaluation of land prices
Ex: Agricultural Region– 1st affected zone : 15%– 2nd affected zone : 10%
• Step 5Calculate the total annual loss in land prices
HEDONIC PRICING METHODHEDONIC PRICING METHODCaseCase--study 4:study 4: Impact of Solid Waste Dumping on Impact of Solid Waste Dumping on
Land Prices in TunisiaLand Prices in Tunisia
Parameter Grombalia Korba Beni Khaled Other TotalDumpsites total area (ha) 5 8 10 48 71Total area of 1st affected zone (ha) 2.7 3.3 3.6 20 29.6Total area of 2nd affected zone (ha) 8.4 9.9 10.7 60.5 89.5Value of land not affected by devaluation (DT/ha) 7,500 11,000 10,000 9,500
Annual value land not affected by devaluation (DT/ha) --10% of value of land 750 1,100 1,000 950
Annual loss of land prices in the 1st affected zone
303=2.7×750×15%
543=3.3×1,100
×15%547 2,853 4,236
Annual loss of land prices in the 2nd affected zone
630=8.4×750×10%
1,086 1,070 5,746 8,538
Total annual loss (DT/year) 12,774
Application- Agricultural region
HEDONIC PRICING METHODHEDONIC PRICING METHODCaseCase--study 4:study 4: Impact of Solid Waste Dumping on Impact of Solid Waste Dumping on
Land Prices in TunisiaLand Prices in Tunisia
Parameter Peri-urban Urban
Dumpsites total area (ha) 143 118Total affected area (ha) 543 47.2Average value of land not affected by devaluation (000 DT/ha) 700 1,700
Annual value of land not affected by devaluation (DT/ha) 70,000 170,000Percent annual loss of land prices (DT/year) 30% 35%Total annual loss (DT/year) 11,403,000 2,808,000
Application- Peri-urban & Urban region
Total land price losses due to solid waste dumping isTotal land price losses due to solid waste dumping is
14,224,000 DT/Year14,224,000 DT/Year
HEDONIC PRICING METHODHEDONIC PRICING METHODCaseCase--study 5: study 5: Quarries in Mount LebanonQuarries in Mount Lebanon
The situation• More than 700 quarries in Lebanon, of which > 50%
are in Mount Lebanon• Constructed with little consideration for the
environment and surrounding human settlements• Many of them are abandoned with minimal or no
rehabilitation
Destruction of natural vegetation and habitatsDestruction of natural vegetation and habitatsAir pollution from dustAir pollution from dust
Reduction in aesthetic value in and around sitesReduction in aesthetic value in and around sites
HEDONIC PRICING METHODHEDONIC PRICING METHODCaseCase--study 5: study 5: Quarries in Mount LebanonQuarries in Mount Lebanon
The methodology• Annual cost of environmental degradation due to
quarries– Loss in residential land value around quarries
– Loss in apartment values around quarries
Land/apartments in areas visually affected by quarriesexperience a decline in value
Cost of degradation associated with loss of Cost of degradation associated with loss of aesthetic valueaesthetic value
HEDONIC PRICE METHODHEDONIC PRICE METHODCaseCase--study 5: study 5: Quarries in Mount LebanonQuarries in Mount Lebanon
The methodology• A survey of impacts on surrounding areas around 4
quarries in Mount Lebanon was conducted• Additional impacts recorded to occur during quarries
operation:– Structural damage to buildings and infrastructures from
explosives used– Dust pollution– Traffic congestion due to quarry transport activities
• Additional impacts during operation are fraction of the losses in land and apartment values and not included in this assessment
HEDONIC PRICE METHODHEDONIC PRICE METHODCaseCase--study 5: study 5: Quarries in Mount LebanonQuarries in Mount Lebanon
The methodology• Step 1: Estimation of loss in land value around surveyed
quarries– Area of land affected ranged between 100,000 and 600,000 m2
– Decline in land price ranged between 7.5 and 125 US$/m2
* Total losses in land value were annualized at a discount rate f 10% over 20 to 100 years (high and low estimates)
Quarry Areas affected Land area affected (m2)
Decline in land price (US $/m2)
Loss in land value (US $ million)
Shnanaayer Shnanaayer municipality 600,000 125 75.0=600,000×125
Abou-Mizan Shirine, Bteghrine, and other villages 175,000 7.5 1.3Antelias Raboueh and Qornet Chehouane municipality 100,000 50 5.0
Total 875,000 93 81.3Annualized loss (“low”)* 8.1Annualized loss (“High”)* 9.6
Average annual loss in land value:Average annual loss in land value:8.85 US $ million8.85 US $ million
HEDONIC PRICE METHODHEDONIC PRICE METHODCaseCase--study 5: study 5: Quarries in Mount LebanonQuarries in Mount Lebanon
The methodology• Step 2: Estimation of loss in apartment values around
surveyed quarries– Area of apartments affected ranged between 8,000 and 36,000 m2
– Decline in apartment price ranged between 100 and 225 US$/m2
* Total losses in land value were annualized at a discount rate f 10% over 20 to 100 years (high and low estimates)
QuarryAreas affected Apartments
affected (m2)Decline in apartment
price (US $/m2)
Loss in apartment value (US $ million)
Shnanaayer Shnanaayer municipality 36,000 225 8.1Antelias Raboueh and Qornet Chehouane municipality 8,000 100 0.8
Total 44,000 202 8.9Annualized loss (“low”)* 0.9Annualized loss (“High”)* 1.0
Average annual loss in apartment value:Average annual loss in apartment value:0.95 US $ million0.95 US $ million
HEDONIC PRICE METHODHEDONIC PRICE METHODCaseCase--study 5: study 5: Quarries in Mount LebanonQuarries in Mount Lebanon
The methodology• Step 3: Estimation of land value occupied by other quarries (not
surveyed)– The total cost of degradation for >700 quarries is estimated based on the
value of land occupied by quarries– Estimated land value ranges between 3 and 5 US$/m2
– Average size of quarry ranges between 15,000 and 20,000 m2
* Total losses in land value were annualized at a discount rate f 10% over 20 to 100 years (high and low estimates)
Average annual value of land occupied by quarries:Average annual value of land occupied by quarries:5.45 US $ million, 0.035 % of the GDP5.45 US $ million, 0.035 % of the GDP
Lower bound
Higher bound
Number of quarries 710Average area of quarry (m2) 15,000 20,000Average land value (US $/m2) 3 5Total land value (US $ million) 207.6 415.3Annualized loss (US $ million/year)* 5.0 5.9Percent of GDP (%) 0.03 0.04
HEDONIC PRICE METHODHEDONIC PRICE METHODCaseCase--study 5: study 5: Quarries in Mount LebanonQuarries in Mount Lebanon
The methodology• Step 3: Assessing the total cost of degradation
due to quarries
The average total annual degradation cost due to The average total annual degradation cost due to quarries in Lebanon:quarries in Lebanon:
15.25 US $ million, 0.10 % of the GDP15.25 US $ million, 0.10 % of the GDP
Lower bound Higher boundLoss in land value around surveyed quarries (US $ million) 8.1 9.6Loss in apartment value around surveyed quarries (US $ million) 0.9 1.0Annual land value occupied by all quarries (US $ million) 5.0 5.9Total loss (US $ million) 14.0 16.5Percent of GDP (%) 0.08 0.10
AVERTING BEHAVIORAVERTING BEHAVIOROUTLINEOUTLINE
• Theory• Methodology• Issues to consider• Case-study 1
– Cost of pesticide contamination of drinking water
• Case-study 2– Consumption of Bottled Water in Lebanon
AVERTING BEHAVIORAVERTING BEHAVIORTheoryTheory
• Actions are taken to reduce or avoid the consequences/ cost of environmental damage– Water pollution
• Drinking bottled water • Purchasing water filters
– Air pollution• Frequent painting of dwellings due to smoke emissions from
a nearby factory • Moving away from a polluted location• Installing air purifiers• Staying indoors
– Noise• Installing soundproof walling to reduce noise
AVERTING BEHAVIORAVERTING BEHAVIORTheoryTheory
• In many cases, several types of aversive expenditures are undertaken simultaneously– Ex: Possible action in response to a noisy road
• Install double glazing• Move to another area
– Total benefits estimated by summing up all expenditures
Cost of avertingactions undertaken
People’s value for environmentalimprovement
≈
AVERTING BEHAVIORAVERTING BEHAVIORMethodologyMethodology
Application– Step 1: Identification of the environmental hazard and the
affected population• Monitoring equipment used to measure variables indicative of the
environmental hazard• Common sense to be adopted in defining the population at risk
– Step 2: Observation of the responses of individuals• Survey design should avoid biased sample, strategic bias, and self-
selection• Identify public expenditures
– Step 3: Measurement of the cost of taking action• Understand why the individual is taking a certain action• Understand if the chosen course is enough to avoid the hazard
AVERTING BEHAVIORAVERTING BEHAVIORIssues to considerIssues to consider
• Some actions are difficult to monetize– Moving house and leaving a familiar neighborhood
The cost of the action is a minimum estimate
• Some impacts have consequences with no possible averting actions– Air pollution on reduced visibility– Air pollution on lake acidification
The cost of the action is not accurate or complete
• Some goods provide additional non-environmental benefits– Bottled water tastes better– Air conditioning ameliorates room temperature
The should be accounted for to avoid overestimation of benefits
• Some are only partial substitutes for the environment– Double glazing partially reduces noise– Discomfort may still occur
The should be included in the analysis
AVERTING BEHAVIORAVERTING BEHAVIORCase Study 1: Case Study 1: The cost of solvent contamination The cost of solvent contamination
of drinking water*of drinking water*
• Background– Water supplies in Perkasie, Pennsylvania
contaminated with Trichloroethylene (TCE)• Detected TCE levels = 35 ppb• EPA TCE limit = 5 ppb
– No means of reducing contaminationWater consumers were notified of the
contamination
Adapted from Hodge, 1995
AVERTING BEHAVIORAVERTING BEHAVIORCase Study 1: Case Study 1: The cost of solvent contamination The cost of solvent contamination
of drinking waterof drinking water• Methodology
– Postal survey• A sample 1733 households• A response rate of 45%• Questionnaire inquired about actions to avoid
exposure to TCE– Increased purchase of bottled water– Installation of home water treatment systems– Bringing in water from other sources– Boiling water
– Estimation of the cost of actions
AVERTING BEHAVIORAVERTING BEHAVIORCase Study 1: Case Study 1: The cost of solvent contamination The cost of solvent contamination
of drinking waterof drinking water• Results
– In the absence of a clear logic for choosing the value to attach to the time spent on averting behavior, two approaches were considered
Actions undertaken Low estimatea
(USD)High estimateb
(USD)Increased purchase of bottled water 11,135 11,135New purchases of bottled water 17,342 17,342Home water treatment systemsc 4,691 4,691Hauling water 12,513 34,013Boiling water 15,633 64,135Total cost 61,313 133,334
a Time valued at minimum wage rate (3.35 USD/hr)b Time valued at estimated hourly wagec Because such a system would last for longer than the contamination period,
a proportion of the cost was included
AVERTING BEHAVIORAVERTING BEHAVIORCase Study 1: Case Study 1: The cost of solvent contamination The cost of solvent contamination
of drinking waterof drinking water• Results
– Represent a minimum estimate of the costs of chemical contamination
• Only 43% of respondents were aware of the contamination• Averting behavior did not remove all contamination• No allowance made for possible ecological impacts
– Analysis suggests that if contamination could be avoided for an expenditure of 60,000 USD, then it should be undertaken
Adapted from Hodge, 1995
AVERTING BEHAVIOR AVERTING BEHAVIOR CaseCase--study 2:study 2: Consumption of Bottled Water in Consumption of Bottled Water in
LebanonLebanonBackground Substandard quality and inadequate quantity of potable water
Inadequate sanitation facilities and sanitation practicesInadequate personal, food and domestic hygiene
Impact on human health and quality of life
Cost to societyCost to society
AVERTING BEHAVIOR AVERTING BEHAVIOR CCasease--study 2:study 2: Consumption of Bottled Water in Consumption of Bottled Water in
LebanonLebanonBackground
Individuals and communities at risk from waterborne illnesses and mortality resort to
Aversive expenditures such as purchase Aversive expenditures such as purchase of bottled waterof bottled water
Lebanon’s population consumes a large quantity of bottled water mostly due to the perception that municipal water is of a low quality. According to the State of the Environment Report (ECODIT, 2000), bottled water consumption is about 115 liters per capita per year
AVERTING BEHAVIOR AVERTING BEHAVIOR CCasease--study 2:study 2: Consumption of Bottled Water in Consumption of Bottled Water in
LebanonLebanonMethodology•Cost of municipal water of inferior quality could be estimated based on bottled water consumption •Cost is equivalent to the difference between
– actual bottled water consumption– estimated consumption associated with taste and lifestyle
preference
Cost of Environmental degradation Cost of Environmental degradation = =
Actual bottled water consumption Actual bottled water consumption –– Expected consumption Expected consumption associated with preferenceassociated with preference
AVERTING BEHAVIOR AVERTING BEHAVIOR CaseCase--study 2:study 2: Consumption of Bottled Water in Consumption of Bottled Water in
LebanonLebanonResults• Actual bottled water consumption
– According to the State of the Environment Report (SOER):• Bottled water expenditure represent 0.60% of total per capita
expenditure• The average price of one liter of bottled water is 0.23 US$
Unit ValuePer capita expenditures in Lebanon US$/capita/yr 4,465Per capita bottled water expenditures in Lebanon % 0.60Bottled water expenditure in Lebanon US$/capita/yr 26.8Average price of bottled water in Lebanon US$/liter 0.23Actual bottled water consumption in Lebanon Liter/capita/yr 115
AVERTING BEHAVIOR AVERTING BEHAVIOR CaseCase--study 2:study 2: Consumption of Bottled Water in Consumption of Bottled Water in
LebanonLebanonResultsExpected bottled water consumption associated with
preference• Bottled water consumption associated with preference
– taste, lifestyle, etc…
• Estimation based on bottled water consumption in Europe and the United States in the 1970’s – 1970 figures used because of the large increase in consumption in
1980’s and 1990’s due to perception of inferior municipal water quality
• Expected consumption adjusted for GDP per capita differentials and price differentials between several European countries (in the 1970) and Lebanon
AVERTING BEHAVIOR AVERTING BEHAVIOR CaseCase--study 2:study 2: Consumption of Bottled Water in Consumption of Bottled Water in
LebanonLebanonResultsExpected bottled water consumption associated with preference
– Estimate of expected bottled water consumption in Lebanon if consumers perceived no health risk of potable municipal water
Unit ValueLow High
GDP per capita 2000 (Western Europe and USA) US$/capita 27,750
GDP per capita 2000 (Western Europe and USA) US$/capita 17,253
GDP per capita 2000 in Lebanon US$/capita 3,875
Bottled water consumption in several European countries in 1970’s Liter/capita/yr 30 30
Income elasticity of bottled water demand 0.25 0.4
Price elasticity of bottled water demand (“low”) -1.5 -1.5
Price elasticity of bottled water demand (“High”) -2 -2
Average price of bottled water in European countries US$/liter 0.3 0.3
Average price of bottled water in Lebanon US$/liter 0.23 0.23
Expected bottled water consumption in Lebanon “Low” Liter/capita/yr 30 24Expected bottled water consumption in Lebanon “High” Liter/capita/yr 34 27
AVERTING BEHAVIOR AVERTING BEHAVIOR CaseCase--study 2:study 2: Consumption of Bottled Water in Consumption of Bottled Water in
LebanonLebanonResults• Estimation of bottled water consumption to protect against risk
– Equivalent to “actual” less “expected” (if perceived risk of illness from municipal water were zero)
Unit ValueLow High
Actual bottled water consumption in Lebanon Liter/capita/yr 115 115Expected bottled water consumption in Lebanon “Low” Liter/capita/yr 30 24
Expected bottled water consumption in Lebanon “High” Liter/capita/yr 34 27
Average expected bottled water consumption in Lebanon Liter/capita/yr 32 26
Bottled water consumption to protect against risk Liter/capita/yr 83 89Lebanese population in 2000 Million capita 4.2
Total bottled water consumption to protect against risk Million liter/yr 356 383
Total cost of bottled water consumption to protect against risk Million US$/yr 82=356×0.23
88=383×0.23
% GDP 0.49 0.53
Average annual cost of bottled water consumption = 85 million US$
= 0.51% of GDP
EEnd of nd of SSession ession 66
Thank YouThank You
REGIONAL WORKSHOP REGIONAL WORKSHOP ONON
THE COST OF THE COST OF ENVIRONMENTAL ENVIRONMENTAL
DEGRADATION DEGRADATION METHODOLOGYMETHODOLOGY
Sessions 7 & 8The Revealed Preference
ApproachGROUP EXERCISES
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SESSIONS 7-8
GROUP EXERCISE 1
Economic Valuation of the Environment and the Travel Cost Approach: The Case of Ayubia National Park
(Himayatullah, 2003)
Case description The Government of Pakistan is seeking to revitalize its nature-based tourism sector to an expanding system of national parks and reserves. The Government of Pakistan has, in recent years, felt a serious concern over the deforestation and has shown significant interest in the growth of a renowned national park system. Despite limited number of national parks and reserves their management is far from satisfactory. This may partly be because of insufficient governmental funds and open access of visitors to these places. There is a need for a thorough investigation of how these parks can be well managed and how these environmental resources can be valued. The present case aims at obtaining economic information about benefits that flow from recreational use of a national park, Ayubia National Park (ANP), Pakistan. Ayubia National Park is a small national park in the Murree hills, Pakistan. It is located North of Murree in the Himalayan Range Mountains. Ayubia consisting of four hill stations, namely, Khaira Gali, Changla Gali, Khanspur and Gora Dhaka is spread over an area of 26 kilometers. These hill stations have been developed into a hill resort known as Ayubia. The chairlifts provided at this place are a matter of great attraction. It is an important place from the viewpoint of wildlife, nature, ecotourism, and education. This park provides refuge to the elusive leopard and the black bear. Bird watching is excellent here. There are steep precipices and cliffs on one side and on the other are tall pine trees. The scenery is superb with huge pine forests covering the hills and providing shelter to the larger and smaller mammals. Wild animals are also found in the thick forests around. Mammals in the park include Asiatic leopard, Black bear, Yellow throated marten, Kashmir hill fox, Red Flying squirrel, Himalayan palm civet, Masked civet and Rhesus Macaque. Birds in the park are Golden eagle, Griffin vulture, Honey buzzard, Peregrine falcon, Kestrel, Indian sparrow hawk, Hill pigeon, Spotted dove and Collared dove. Note that the access to ANP is free of charge One of the objectives of this study is to estimate the consumer surplus and recreational value (benefits) of the ANP. 1. Why is the TCM selected in this case? Which values will it capture? ___________________________________________________________________________
___________________________________________________________________________
___________________________________________________________________________
2. What alternative method could have been used and why? ___________________________________________________________________________
___________________________________________________________________________
___________________________________________________________________________
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3. What are the three forms of a TCM?
a. _________________________________
b. _________________________________
c. _________________________________
4. For this case-study, the Individual Travel Cost Method was used. 5. What are the three most controversial aspects of the travel cost method?
a. _________________________________
b. _________________________________
c. _________________________________
6. Steps of the TCM process
A. Identify site ___________________________________________________________________________
___________________________________________________________________________
___________________________________________________________________________
B. Use an on-site questionnaire survey to collect data from visitors relating to:
a. _________________________________
b. _________________________________
c. _________________________________
d. _________________________________
The data used in this study were collected from 300 visitors by following systematic random sampling. The results showed the following:
− the sample respondents visited nature-based recreation about 7 times per year − The respondents’ mean yearly spending on recreation was Rs 5300 − The respondents’ mean monthly income is Rs 12,500 − About 61 percent of the respondents are male − 60 percent of the respondents were married − The average age of the respondents was 43 years − The average household size was about 6 − More than 76 percent were literate − Half of the respondents (50 percent) considered quality of the park as good − 60 percent of the visitors were from urban areas − more than 62 percent of the respondents wanted improvement in the quality of services of the
park − On the question about how more resources should be allocated for the park management, 38
percent of the respondents preferred an increase in entrance fee, 40 percent chose reallocation of government budget, 22 percent advocated voluntary donations towards parks’
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management funds. − The visitors visited the ANP for different reasons. More than two-third (80 percent) of visitors
came to Galliat for recreation purposes. Some 20 percent of visitors reported travelling as the reason for coming to Galliat.
− Regarding income distribution as many as 45 percent of sample households fall in income group of Rs 10,000–20,000 per month. More than one-fifth (22 percent) households have monthly income in the range of Rs 5,000-10,000. Some 19 percent households have income of Rs 20,000-50,000. Taken together 64 percent households fall in income range of Rs 5,000-20,000.
C. Specify trip-generation function: V = f( , , , ,…) Factors that influence the demand for visits include:
a. _________________________________
b. _________________________________
c. _________________________________
d. _________________________________
Would you expect the variables below to increase or decrease frequency of visitation? (Tick the appropriate box)
− Increased travel cost: Increases visitation Decreases visitation
− Increased travel time: Increases visitation Decreases visitation
− Advanced age: Increases visitation Decreases visitation
− Gender: Males more less likely to visit
− Increased education level: Increases visitation Decreases visitation
− Increased household income: Increases visitation Decreases visitation
− Improved quality of the site: Increases visitation Decreases visitation
D. Estimate travel cost model: The basic model used in this study depicts: vi = α0 + α1 TC + α2 Yi+ α3 STi+ α4 Ai+ α5 Ei+ α5+k ΣDk+ ei … …
where: vi = the number of visits by the ith individual to the Park per period of time TC = round trip total cost (Rs) to the site including travel time M = household income (Rs/month) ST = travel cost to and from a substitute site A = age of the visitor E = highest level of education gained by visitor FS = family size, D1 = 1 if male and 0 otherwise, D2 = 1 if urban dweller and 0 otherwise D3= 1 if the visitor’s perception about the site’s recreational facilities is good and 0 if bad.
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Econometric model used: Specification of the functional form is crucial to the benefit estimates obtained. In practice the choice of the functional form needs to be determined empirically. There is some consensus that a semi-log gives the best results namely regressing the logarithm of visitation rates against travel cost, etc. However, we will also use double log functional form of the above model to estimate (own- and cross) price and income elasticity of demand for visitation of the Ayubia National Park. The table below reports the results of the travel cost regression models in a linear fashion. In these models, most coefficients have the expected algebraic signs. The coefficient on travel costs is negative and statistically significant. As expected high travel costs incurred by individuals are inversely related to park visitation rate.
Estimated Results of Linear Regression Equations Variable Coefficients (t-stats)
Dependent variable # of visits, v
Intercept 2.41 (2.32)
Travel costs -0.06 (-2.58)***
Household income 0.0057 (2.23)**
Price of substitute 0.00025 (1.75)
Age -0.024 (-1.69)
Education 0.0059 (1.17)
Family size 0.0029 (0.35)
Dummy 1 0.332 (1.54)
Dummy 2 0.018 (1.40)
Dummy 3 0.045 (2.33)**
R2 0.47
F-statistics 13.5
** indicate significance at 5 percent level *** indicate significance at 1 percent level
E. Derive demand curve and obtain household consumer surplus estimates through
integrating under the demand curve. Two linear demand curves for ANP visitation were estimated from the survey data. The figure below shows the actual user demand for the Park and a hypothetical demand for the Park in case of improvement in the quality of park services. It implies that improvement in the quality of the services at the park would shift the demand curve upward to the right. In addition, the log-linear (semi-log) demand curve was also estimated. The semi-log demand curve is curvilinear and convex to the origin, which is relatively flat at low prices and steep at higher prices.
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Visits with improvement: vi = 35.14 – 0.013 tc (R2=0.6313) Visits without improvement: vi = 44.32 –0.018 tc (R2=0.5666)
ln vi = 4.56 e-0.0079tc (R2= 0.7878)
a. Linear demand curve b. Log-linear demand curve
7. Calculate aggregate consumer surplus for the site
The total recreational value equals the consumer surplus plus total cost of visit.
Recreational Value of the ANP
Consumer Surplus Recreational Value
Per Visitor (Rs) 240 1996
Total (Rs million) 24.0 200.6
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SESSIONS 7-8
GROUP EXERCISE 2
Forest Recreation Areas in Malaysia (FRAs) (Garrod and Willis, 2001)
Case description There are 74 Forest Recreation Areas in spread throughout the States of Peninsular Malaysia. FRAs are relatively small areas of natural virgin forest containing a variety of attractive landscape, fauna and flora, rivers and unique geological features, making them attractive as sites for outdoor recreation. They provide open access to non-priced recreation. Activities pursued in FRAs range from hiking, camping, swimming, etc. to more passive pursuits such as picnics, walks, observing the ecology, and enjoying the scenic attractions of the forests. The state government incurs costs for visitors facilities in terms of maintaining footpaths and toilets, collecting litter, providing information, and patrolling the site with park rangers. The objective of this study is to assess the value of the benefits of open access, non-priced recreation at FRAs. 1. Why is the TCM selected in this case? Which values will it capture? ___________________________________________________________________________
___________________________________________________________________________
___________________________________________________________________________
2. What alternative method could have been used and why? ___________________________________________________________________________
___________________________________________________________________________
___________________________________________________________________________
3. What are the three forms of a TCM?
a. _________________________________
b. _________________________________
c. _________________________________
4. For this case-study, the __________________form was used. 5. What are the three most controversial aspects of the travel cost method?
a. _________________________________
b. _________________________________
c. _________________________________
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6. Steps of the TCM process A. Identify site
___________________________________________________________________________
___________________________________________________________________________
___________________________________________________________________________
B. Use an on-site questionnaire survey to collect data from visitors relating to:
a. _________________________________
b. _________________________________
c. _________________________________
d. _________________________________
A random sample of visitors was interviewed on a next to sample basis. A sample size of 385 interviews was set at the Jeram Linang FRA.
C. Specify trip-generation function: V = f( , , , ,…) Factors that influence the demand for visits include:
a. _________________________________
b. _________________________________
c. _________________________________
d. _________________________________
Would you expect the variables below to increase or decrease frequency of visitation? (Tick the appropriate box)
− Increased travel cost: Increases visitation Decreases visitation
− Increased travel time: Increases visitation Decreases visitation
− Advanced age: Increases visitation Decreases visitation
− Gender: Males more less likely to visit
− Increased education level: Increases visitation Decreases visitation
− Increased household income: Increases visitation Decreases visitation
− Improved quality of the site: Increases visitation Decreases visitation
The dependent variable is: ________________________________
D. Derive demand curve and obtain household consumer surplus estimates through integrating under the demand curve
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Vij = f(Cij, Eij, Si, Yi, Ai, Hi, Ni, Mi) where: Vij = number of visits made by individual i to site j Cij = individual i's total cost of visiting site j Eij = individual i's estimate of the proportion of the day’s enjoyment which is attributable to the FRA Yi = income of individual i's household Ai = age of individual i Hi = size of individual i's household Ni = size of individual i's party Mi = dummy variable: whether individual i is a member of an outdoor organization The functional form used was the linear truncated Maximum Likelihood model, which took account of the truncated nature of the data which excluded individuals who chose not to visit the site over that time period. The model reported variables significant at the 0.15 statistical significance level. The variables made sense intuitively, whereby visits to FRA were: − negatively related to time and travel cost − positively related to being single and living with parents, being educated only to
primary and secondary levels, engaging in fishing at the site
The ML model for Jeram Linang FRA
Variable Coefficient Std. deviation T-ratio Prob:t:>x Mean of x
ONE -4.00525 1.25289 -3.197 0.00139 1.00000
Time and travel cost -0.64479 0.24658 -2.615 0.00893 2.34940
First visit -11.07460 1.64099 -6.749 0.00000 0.26216
Single- living with parents 5.78721 1.09867 5.267 0.00000 0.18919
Educated to primary level 6.04067 2.31138 2.613 0.00896 0.04594
Educated to secondary level 3.20342 1.17677 2.722 0.00648 0.13784
Other FRAs visited in last 6 months 0.48544 0.25220 1.925 0.05426 0.97297
Fished at the site 8.02514 3.22890 2.485 0.01294 0.00540
Engaged in nature walking -1.97990 1.10616 -1.790 0.07347 0.25135
E. Calculate aggregate consumer surplus for the site Consumer surplus estimates for individual visits to the sites are calculated by substituting values from the linear equation and integrating over the demand function.
The average economic benefit of the marginal visit for each visitor to FRA
FRA Consumer surplus per visit per adult
Jeram Linang (Kelantan) 0.78
Telok Bahang (Penang) 2.38
Gunung Pulai (Johor) 3.74
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SESSIONS 7-8
GROUP EXERCISE 3
Valuing Landscape and Amenity Attributes in Central England (Garrod and Willis, 2001)
Case description The study area consists of around 4,800 km2 in Central England offering a variety of landscape form and feature. The focus is on the County of Gloucestershire in addition to large areas of Hereford and Worcester and small areas of Gwent, Wiltshire, Oxfordshire, and Avon. The aim is to study the impact of individual landscape and amenity features on house prices. Questions 1. Why is the HPM selected in this case? Which values will it capture? ___________________________________________________________________________
___________________________________________________________________________
___________________________________________________________________________
2. What alternative method could have been used and why? ___________________________________________________________________________
___________________________________________________________________________
___________________________________________________________________________
3. What data need to be collected? Specific and local ___________________________________________________________________________
___________________________________________________________________________
___________________________________________________________________________
4. How can proximity to landscape and amenity features be defined? ___________________________________________________________________________
___________________________________________________________________________
___________________________________________________________________________
5. What are the possible data sources? ___________________________________________________________________________
___________________________________________________________________________
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___________________________________________________________________________
6. What type of analysis may be used for the collected data? What is the dependent
variable? What are the independent variables? Dependent variable: __________________________________________________________
Independent variables: ________________________________________________________
___________________________________________________________________________
7. What important factor needs to be accounted for? ___________________________________________________________________________
8. What types of functional forms may be used? ___________________________________________________________________________ 9. For what should the variables measuring proximity to landscape and amenity attributes be
measured?
− Statistical significance − Freedom from the effects of multicollinearity − Freedom from the effects of omitted variable bias − Variables measuring structural attributes of the model and socio-economic characteristics of the
study were permitted to enter the model even if they displayed some degree of collinearity 10. Empirical Results The following variables were statistically significant and robust in terms of estimation
Variable Definition
FOR20 0-1 variable: over 20% woodland in same 1-km2 as property
RIVER 0-1 variable: river or canal in same 1-km2 as property
SETTLEMENT 0-1 variable: rural settlement in same 1-km2 as property
WETLAND 0-1 variable: area of wetland in same 1-km2 as property
WOODVIEW 0-1 variable: probable woodland view in same 1-km2 as property
URBANVIEW 0-1 variable: probable urban view in same 1-km2 as property
SLOPE Predominant gradient of slope in same 1-km2 as property
ROAD Kilometers of road in same 1-km2 as property
RAIL Kilometers of rail track in same 1-km2 as property
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Coefficient values of the amenity variables and the marginal implicit price Variable Coefficient (t-value) Marginal Implicit Price
(Percent of sample average house value)
FOR20 0.0710 (2.53) 7.10
RIVER 0.0490 (2.74) 4.90
SETTLEMENT 0.0834 (5.34) 8.34
WETLAND -0.1800 (-1.75) 18.00
WOODVIEW -0.0735 (-3.10) 7.35
URBANVIEW -0.0580 (-3.55) 5.80
SLOPE -0.0030 (-2.50) 0.30
ROAD 0.0279 (3.66) 2.79
RAIL -0.0543 (-2.77) 5.43
Marginal implicit price was inferred directly from the coefficient values of the semi-log model. It was found that the factors inflating house prices were proximity to rivers and waterways, proximity to land with high woodland cover, and good reach of local amenities and communications. The factors that depressed house prices were proximity to wetlands, proximity to rail lines, and view on urban areas.
REGIONAL WORKSHOP ONREGIONAL WORKSHOP ON
THE COST OF ENVIRONMENTAL THE COST OF ENVIRONMENTAL DEGRADATION METHODOLOGYDEGRADATION METHODOLOGY
Sessions 7 & 8The Revealed Preference ApproachThe Revealed Preference Approach
GROUP EXERCISESGROUP EXERCISES
OUTLINEOUTLINE
Case study 1Case study 1Economic valuation of the Environment in AyubiaNational Park, PakistanCase study 2Case study 2Non-priced Forest Recreation Areas in MalaysiaCase study 3Case study 3Valuing Landscape and Amenity Attributes in Central England
Case study 1Case study 1Economic valuation of the Environment in Economic valuation of the Environment in
AyubiaAyubia National Park, PakistanNational Park, Pakistan
Case DescriptionCase DescriptionStudy areaStudy area
• Ayubia National Park (ANP), Pakistan
• 26-km2 park in the Murree Hills in the Himalayan Range Mountains
• Important place from the viewpoint of wildlife, nature, ecotourism, and education– Refuge for the elusive leopard & black
bear and other mammals such as Kashmir hill fox, Red flying squirrel, etc.
– Bird watching: Golden eagle, Griffin vulture, Hill pigeon, Indian sparrow hawk, etc.
– Superb scenery– Chairlifts
Case DescriptionCase DescriptionEcosystem threatsEcosystem threats
What are the factors affecting visitor’s WTP for recreational services of the park? What are the benefits of the park? Would the improvement in recreational benefits of the park lead to a
higher demand for park visitation?
• The park is threatened by various activities– Forest fires– Soil erosion– Human settlements inside park– Pollution caused by villagers or visitors – Encroachment by local villagers
• Unsatisfactory management– Insufficient governmental
funds– Open access⊕
Need for a thorough investigation of the value of the environmental resources and services provided by the park to prove the necessity of its revitalization & better management
Applied MethodApplied MethodTravel cost approach (1)Travel cost approach (1)
• The consumer maximizes utility subject to a budget constrained by his income, represented by the product of hours of work to wage rate. The algebraic form is:Max: U(x,v)Subject to: wL = pxx + p0vWhere U= utility, x= the market good, v= visits to the park, w= hourly wage rate, L= work hours, px= price of market good x, p0= out-of-pocket expenses for a visit to the park
• In addition to out-of-pocket expenses, the consumers take time to travel. Time has anopportunity cost. The time constraint has the following form:T = L + HvWhere T= total household time available, H= time associated with a single round trip to the park including time spent on site, L= hours of wage labour
• The maximization problem then takes the following form:Max: Max: U(x,v)Subject to: wT = pxx + [p0 + wH]v
• The Lagrange expression is:L = U(x,v) + λ(wT-pxx+pvv)Where pv is the price for visiting the park
• Solving these problems will yield the following demand function for visit to the park:V = f(pv, px, Y, Z)Where the consumer demand for a visit to the park depends on the price for a visit, the price for other goods (substitute sites), the income and other socio-economic variables
Applied MethodApplied MethodTravel cost approach (2)Travel cost approach (2)
• When the demand function is derived, next step is to derive a demand curve (number of trips to park at different travel costs)– by holding income & prices of substitutes constant– and varying the price of the travel cost of a single
round-trip to the park• Based on demand curve, total value of park can
be computed, and is referred to as consumer surplus
• Total recreational value of park = consumer surplus + travel cost
Applied MethodApplied MethodSurvey designSurvey design
• In-person questionnaire with 300 random visitors of the park
• Two parts: 1. General information: gender, education, marital
status, age, income, place of living, etc.2. Visitor’s recreational behaviour:
• If they wanted improvement? • What is the method of resource allocation they prefer
(increase in entrance fee, reallocation of government budget, voluntary donations, etc.)?
• Why they’re visiting the park?
ResultsResultsTravel cost econometric modelTravel cost econometric model
• Regression analysis yielded a model of the form:vi = α0 + α1TC + α2Mi + α3STi + α4Ai + α5Ei + α6FSi + α6+kDk + ei
Where vi= the # of visits of the ithindividual to the park per period of time, TC= round trip total cost, M= monthly household income, ST= travel cost to and from a substitute site, A= age of the visitor, E= level of education, FS= family size, D1= 1 if male & 0 otherwise, D2= 1 if urban dweller, D3= 1 if visitor’s perception about site’s recreational facilities is good
Variable Coefficients (t-stats)Dependent variable # of visits, v
Intercept 2.41 (2.32)
Travel costs -0.06 (-2.58)***
Household income 0.0057 (2.23)**
Price of substitute 0.00025 (1.75)
Age -0.024 (-1.69)
Education 0.0059 (1.17)
Family size 0.0029 (0.35)
Dummy 1 0.332 (1.54)
Dummy 2 0.018 (1.40)
Dummy 3 0.045 (2.33)**
R2 0.47
F-statistics 13.5
**, and *** indicate significance at 5% & 1% levels, respectively
ResultsResultsConclusions from econometric modelConclusions from econometric model
• High travel costs are inversely related to park visitation rate
• Household income has positive impact on recreational demand
• No significant relationship between cost of substitute & the demand for the park
• Education & age had positive & negative impact on demand, respectively; however their impact is insignificant
• Dummy variables had all a positive impact, with dummy 3 having a statistically significant influence → if quality of park services are improved, visitors would pay more visits to the park
ResultsResultsDemand curvesDemand curves
Improvement in the quality of the park services would shift the demand curve upward to the right
The semi-log demand curve is curvilinear & convex to the origin, which is relatively flat at low prices & steep at higher prices
ResultsResultsRecreational valueRecreational value
• Total recreational value of park = consumer surplus + travel cost
• The annual monetary value of the park is 200 million Indian rupee (Rs), projected to become 209 million in case of improvement
• ⇒ The park constitutes a valuable environmental resource (in terms use & non-use values) and can be a significant source of benefits with proper conservation & management
Consumer Surplus Recreational Value
Actual New scenario Actual New scenario
Per visitor (Rs) 240.0 320.0 1996.0 2082.4
Total (Rs million) 24.2 35.01 200.6 209.2
Total (USD million) 0.6 0.9 4.9 5.1
End of Case-Study
Thank You
Case study 2Case study 2NonNon--priced Forest Recreation Areas in priced Forest Recreation Areas in
MalaysiaMalaysia
www.cumbavac.org/Earth_Day.htm
Case DescriptionCase DescriptionForest Recreation Areas in MalaysiaForest Recreation Areas in Malaysia
• What are FRAs?– Small areas of natural virgin forest containing a variety of
• Attractive landscape• Fauna and flora• Rivers and unique geological features
– Activities pursued in FRAs• Hiking, camping, swimming, …• Picnics, walks, observing the ecology, enjoying the scenic
attractions, …– Government incurs costs for visitors facilities
• Maintaining footpaths and toilets• Collecting litter• Providing information• Patrolling the site with park rangers
• Throughout the State of Peninsular Malaysia – 74 FRAs– Provide open access, non-priced recreation
www.mymalaysiabooks.com
Applied MethodApplied MethodIndividual Travel Cost ModelIndividual Travel Cost Model
Individual TCMDefines the dependent variable as the number of visits to an FRA made by each visitor over a specified period
TCM can be used to estimate consumer surplus by observing the number of visits in relation to price and estimating the recreation demand curve
Applied MethodApplied MethodIndividual Travel Cost ModelIndividual Travel Cost Model
Integrating over this equation permits the calculation of consumer surplus
Applied MethodApplied MethodIndividual Travel Cost ModelIndividual Travel Cost Model
• Questionnaire survey collected info on– Visits to the FRA– Preferences and activities of visitors– Demographic details of visitors
• Questionnaire structured to allow visitors to think about– Their use of the FRAs– The availability and use of substitute sites and
activities• Random sample of visitors on a next-to-pass basis
– Sample size = 385 interviews– Respondents at the Jeram Linang FRA
wanzee.fotopages.com/?&page=20
Applied MethodApplied MethodIndividual Travel Cost ModelIndividual Travel Cost Model
Cost element Financial cost Economic costFuel cost 0.110 0.060
Lubricant oil 0.009 0.009
Tyre cost 0.009 0.008
Maintenance 0.053 0.045
Depreciation 0.062 0.051
TOTAL 0.243 0.173
Applied MethodApplied MethodIndividual Travel Cost ModelIndividual Travel Cost Model
Total annual number of trips to FRAsTotal annual number of trips to forests, countryside, mountains, and other sites
• The ML model for Jeram Linang FRA
– Model reported variables significant at the 0.15 statistical significance level
– Variables make sense intuitively whereby visits to FRA • negatively related to time and travel cost• positively related to being single and living with parents, being educated only to
primary and secondary levels, engaging in fishing at the site,
Variable Coefficient Std. deviation T-ratio Prob:t:>x Mean of x
ONE -4.00525 1.25289 -3.197 0.00139 1.00000
Time and travel cost -0.64479 0.24658 -2.615 0.00893 2.34940
First visit -11.07460 1.64099 -6.749 0.00000 0.26216
Single- living with parents 5.78721 1.09867 5.267 0.00000 0.18919
Educated to primary level 6.04067 2.31138 2.613 0.00896 0.04594
Educated to secondary level 3.20342 1.17677 2.722 0.00648 0.13784
Other FRAs visited in last 6 months 0.48544 0.25220 1.925 0.05426 0.97297
Fished at the site 8.02514 3.22890 2.485 0.01294 0.00540
Engaged in nature walking -1.97990 1.10616 -1.790 0.07347 0.25135
Applied MethodApplied MethodIndividual Travel Cost ModelIndividual Travel Cost Model
Applied MethodApplied MethodResultsResults
• Consumer surplus estimates for individual visits to the sites are calculated by substituting values fromthe linear equation and integrating overthe demand function
The average economic benefit of the marginal visitfor each visitor to FRA
FRA Consumer surplus per visit per adultJeram Linang (Kelantan) 0.78Telok Bahang (Penang) 2.38Gunung Pulai (Johor) 3.74
www.rrcap.unep.org/.../malaysia/results.html
End of Case-Study
Thank You
Case study 3Case study 3Valuing Landscape and Amenity Valuing Landscape and Amenity
Attributes in Central EnglandAttributes in Central England
www.cotswolds.info/gloucestershire/index.shtml
Case DescriptionCase DescriptionStudy AreaStudy Area
• Around 4,800 km2 in Central England offering a variety of landscape form and feature– Focus on County of Gloucestershire
• with large areas of Hereford and Worcester• Small areas of Gwent, Wiltshire,
Oxfordshire, and Avon
• Aim to study the impact of individual landscape and amenity features on house prices
Hedonic Price Model
http://www.gloucestershire-hotels.co.uk/tudorhousehotelgl205bh.html
Application MethodApplication MethodHedonic Price ModelHedonic Price Model
• Choice of study region• Identification of house sale
transactions– Data set of a large mortgage
lender– Post-code data to identify and
remove transactions within urban areas
– Local knowledgehttp://commons.wikimedia.org/wiki/Image:Middleyard_Gloucestershire_With_Branches.JPG
Nearly 2,000 mortgages processed by the lender between 1985 and 1989 to purchase properties within the non-urban part of the study region
Application MethodApplication MethodHedonic Price ModelHedonic Price Model
• Socio-economic data obtained from 1981 census and other sources
• Data on landscape features– Ordnance survey (OS) 1:50,000 map sheets
• Over 50 variables influencing house prices were obtained through a tedious process
• GIS not feasible due to copyright restrictions– Concentration on simple 0-1 variables
• Whether the 1 km OS map square containing the property of interest contained a particular feature of interest
– Rivers, wetlands, overhead cables– Post offices, public houses, country parks
– Some variables were continuous• Approximate land cover from forestry, buildings, open water, in the 1-Km2
• Approximate distance in kms to the nearest urban center, settlement, school, etc.
• Length of roads and rail tracks• The predominant aspect of the 1-Km2 with its average height above sea
level and degree of slope
Application MethodApplication MethodHedonic Price ModelHedonic Price Model
• Particular problems encountered– Defining the proximity of a property to forestry
• Wooded areas may change in size over a short period of time– The relationship between the selected variables and
incorporated houses was ill-defined• Data provided by OS maps give only an approximation of a given
property’s proximity to a landscape feature• Such an approximation was considered sufficient
• Accounting for market fluctuations and inflations over the 5-year period– The use of dummy variables reflecting the year and quarter
of sale– The use of socio-economic dummies and dummies reflecting
local authority areas
Application MethodApplication MethodEmpirical ResultsEmpirical Results
• A semi-log functional form to model the data– Variables measuring proximity to landscape and
amenity attributes subjected to rigorous examination with respect to
• Statistical significance• Freedom from the effects of multicollinearity• Freedom from the effects of omitted variable bias
– Variables measuring structural attributes of the model and socio-economic characteristics of the study were permitted to enter the model even if they displayed some degree of collinearity
Application MethodApplication MethodEmpirical ResultsEmpirical Results
• The following variables were statistically significant and robust in terms of estimationVariable Definition
FOR20 0-1 variable: over 20% woodland in same 1-km2 as property
RIVER 0-1 variable: river or canal in same 1-km2 as property
SETTLEMENT 0-1 variable: rural settlement in same 1-km2 as property
WETLAND 0-1 variable: area of wetland in same 1-km2 as property
WOODVIEW 0-1 variable: probable woodland view in same 1-km2 as property
URBANVIEW 0-1 variable: probable urban view in same 1-km2 as property
SLOPE Predominant gradient of slope in same 1-km2 as property
ROAD Kilometers of road in same 1-km2 as property
RAIL Kilometers of rail track in same 1-km2 as property
Application MethodApplication MethodEmpirical ResultsEmpirical Results
Variable Coefficient (t-value) Marginal Implicit Price(Percent of sample average house value)
FOR20 0.0710 (2.53) 7.10
RIVER 0.0490 (2.74) 4.90
SETTLEMENT 0.0834 (5.34) 8.34
WETLAND -0.1800 (-1.75) 18.00
WOODVIEW -0.0735 (-3.10) 7.35
URBANVIEW -0.0580 (-3.55) 5.80
SLOPE -0.0030 (-2.50) 0.30
ROAD 0.0279 (3.66) 2.79
RAIL -0.0543 (-2.77) 5.43
Application MethodApplication MethodEmpirical ResultsEmpirical Results
INFLATEDHOUSEPRICES
DEPRESSEDHOUSEPRICES
Application MethodApplication MethodDiscussionDiscussion
• Study failed to produce comprehensive estimate of the marginal value of landscape and other amenity attributes
• Limitations– Data used– Inaccuracies in linking properties to amenities
• Better linkage may be provided by using GIS• Lack of amenity value does not mean lack of non-
market value– Ex: Proximity to wetlands depressed market prices of
houses• Dampness, flooding, increased insurance and maintenance
costs• However wetlands offer a valuable habitat for a number of
important species
End of Sessions 7 & 8
Thank You
REGIONAL WORKSHOP REGIONAL WORKSHOP ONON
THE COST OF THE COST OF ENVIRONMENTAL ENVIRONMENTAL
DEGRADATION DEGRADATION METHODOLOGYMETHODOLOGY
Session 9THE CONTINGENT VALUATION
METHOD
REGIONAL WORKSHOP ONREGIONAL WORKSHOP ON
THE COST OF ENVIRONMENTAL THE COST OF ENVIRONMENTAL DEGRADATION METHODOLOGYDEGRADATION METHODOLOGY
Session 9THE CONTINGENT VALUATION METHOD
Preferences
Revealedpreferences
StatedPreferences
MarketValues
Travel Cost Methods
HedonicMethod
Averting Behavior
ContingentValuation
ChoiceExperiments
USE VALUES USE + NON-USE VALUES
Dose Response Functions
Environmental Valuation MethodsEnvironmental Valuation Methods
Contingent Valuation MethodContingent Valuation MethodOUTLINEOUTLINE
• Overview• Steps in a CVM procedure• Application• Associated biases• Illustration• Advantages• Issues and limitations• Sample applications• Case-studies
– Exxon-Valdez oil spill– Wilderness designation in Colorado– Beach degradation in Lebanon– Beach degradation in Morocco
Contingent Valuation MethodContingent Valuation MethodOverview Overview
• The CVM is the most widely used method for estimating non-use values
• The CVM uses interview techniques to ask individuals to place values on environmental goods and services
• It is called “contingent” valuation, because it is contingent on simulating a hypothetical market for the good in question
• It involves directly asking individuals– how much they would be willing to pay (WTP) to preserve or
use a given good or service OR– the amount of compensation they would be willing to accept
(WTA) to forgo specific environmental services• It is used to
– estimate economic values for all kinds of ecosystem and environmental services
– estimate both use and non use values
Contingent Valuation MethodContingent Valuation MethodOverview Overview
• It is the most controversial of the non-market valuation methods– many economists, psychologists and sociologists, for many different
reasons, do not believe the dollar estimates that result from CV are valid– Many jurists and policy-makers will not accept the results of CV.
• A carefully composed and tested study, where the circumstances are not too distant from the experience of the respondent and the issue is not too emotive, can produce answers of value
• Applications included estimates of the value of– Landscape– Recreation– Beaches– Water quality– Nature conservation– Endangered species– Visibility and air quality, etc
Contingent Valuation MethodContingent Valuation MethodSteps in a CVM ProcedureSteps in a CVM Procedure
Contingent Valuation MethodContingent Valuation MethodSteps in a CVM ProcedureSteps in a CVM Procedure
1. Setting up the hypothetical market• Devise a convincing CV scenario to demonstrate that
respondents are actually stating their values for these services when they answer the valuation questions
• Establish a reason for a good or service• Pictorial aids could be of use
2. Obtaining bids• Possible bid vehicles include income taxes, property
taxes, value added or sales tax, utility bills, entry fees, payments into a trust fund
• Bids obtained through a questionnaire survey
Contingent Valuation MethodContingent Valuation MethodSteps in a CVM ProcedureSteps in a CVM Procedure
2. Obtaining bids (cont’d)• Not all bid vehicles are viable options in a
given situation• Chosen bid vehicle should
– Have a plausible connection with the valued amenity
– Be perceived as fair and equitable• People have different views on the
acceptability of different types of taxes
Contingent Valuation MethodContingent Valuation MethodSteps in a CVM ProcedureSteps in a CVM Procedure
2. Obtaining bids (cont’d)• Focus groups
– Precede CV surveys– Provide insight on the respondents’ likely understanding of
and attitude towards the issue being investigated– Provide valuable information in framing and designing a
CV study and questionnaire survey– Drawn from a cross-section of the population, stratified by
social class– Meeting lasts between one to two hours– Around 8-10 participants in a focus group discuss
• Their understanding of the context of the good• The good itself, its value, who should provide it• How it should be paid for, whether they should contribute• How much they are willing to pay
Contingent Valuation MethodContingent Valuation MethodSteps in a CVM ProcedureSteps in a CVM Procedure
2. Obtaining bids (cont’d)• Concerns with focus groups
– Responses may be influenced by the person conducting the focus group
– Focus group participants have a longer time to think about the issue than in a typical CV survey
– Focus group participants have more information to base their judgment on
– Individuals behave differently in group situations compared to situations when they are alone
• Eliciting WTP/ WTA bids– Bids obtained through questionnaire survey and elicitation format
where respondents are asked to state their• Maximum WTP to increase quantity/ prevent quantity decrease of an
environmental good• Minimum WTA compensation to forgo an increase in the quantity/
accept less of the good– Various elicitation methods may be used
Contingent Valuation MethodContingent Valuation MethodSteps in a CVM ProcedureSteps in a CVM Procedure
2. Obtaining bids (cont’d) 2. Obtaining bids (cont’d)• Questionnaire surveys
– Three sets of information obtained from respondents
– Data on use, preferences and substitutes should be collected at the beginning of the questionnaire
– Respondents must be reminded of their budget constraints when eliciting their bids
• Attitudes to environmental goods in general and reference for the particular good under investigation
• Awareness of substitute goods
• Use of the good, in relation to other goods
• Perceived non-use benefits of the good
• WTP and/or WTA bids for the goods using one or more of the elicitation methods
• Questions exploring reasons for the bids which can be used to eliminate illegitimate responses
• Questions to gauge the respondent's ambivalence
• Socio-economic information on the respondent and his/her household
-Data gathered to assess:- Representativeness of the sample- The theoretical validity of the bids using regression models
Contingent Valuation MethodContingent Valuation MethodSteps in a CVM ProcedureSteps in a CVM Procedure
2. Obtaining bids (cont’d)Questionnaire administered in a number of ways
Contingent Valuation MethodContingent Valuation MethodSteps in a CVM ProcedureSteps in a CVM Procedure
2. Obtaining bids (cont’d)• Sample size
– Determines the precision of the sample statistics used(mean WTP/ WTA)
– The larger the sample the smaller the variation in mean WTP measured by
• Standard error• Confidence intervals
– Mitchell and Carson (1989) devised a system to determine sample size based on choice of acceptable deviation between the ‘true’ and estimated WTPs
• For a deviation of 5%, 95% of the time, a sample of 6,000 is needed• For a deviation of 20%, 90% of the time, a sample of 286 is needed
– Mitchell and Carson argue that a sample > 600 is needed for applications seeking to evaluate policy
• This ensures a deviation of 15%, 95% of the time
Contingent Valuation MethodContingent Valuation MethodSteps in a CVM ProcedureSteps in a CVM Procedure
3. Estimating mean and median WTP/WTA• WTP means, medians, modes, trimmed and modified
estimators, standards of deviation can be found from individual bids– Mean WTP, or trimmed or modified estimators based on mean
WTP are the most appropriate• Represent cardinal measures of the utility individuals derive from the
good– Median WTP
• is recommended because unaffected by large bids• is lower than mean WTP and may underestimate the value
– Trimmed estimator involves trimming the top and bottom 5% or 10% of the distribution of WTP observations
• Some true estimates of WTP may be omitted– Modified estimator provides the truest value
• Identifies and excludes biased and illegitimate responses by a series of questions included in the questionnaire
Contingent Valuation MethodContingent Valuation MethodSteps in a CVM ProcedureSteps in a CVM Procedure
3. Estimating mean and median WTP/WTA• Probit, logit and random utility models can be
used for close-ended referendum bids• Bid curves can also be estimated
– By regressing WTP against socio-economic variables
WTPi = f(Yi, Vi, Pi, Si, Ei)Y = income level; V = visitis; P = preferences = S = substitutes; E = socio-economic variables (age, education, etc.)
• Differentiating bid curves (dWTP/dV) provides demand curve for the good
• Area under the curve = consumer surplus
Contingent Valuation MethodContingent Valuation MethodSteps in a CVM ProcedureSteps in a CVM Procedure
4. Aggregating WTP or WTA amounts• Mean WTP/ WTA from the sample survey
are aggregated across the total population– TOTAL VALUE of the good/ service =
(mean WTP) × (# of population units)
• While mean WTP/ WTA may be modest for non-use benefits, the populations over which they are aggregated can be large
Contingent Valuation MethodContingent Valuation MethodSteps in a CVM ProcedureSteps in a CVM Procedure
5. Assessing the Validity of CV studies• Content validity
– The appropriate framing of the study and questions asked in relation to the good being valued
• Criterion validity– The comparison of CV estimates with actual market or
simulated market experience• Construct validity
– The convergence between a CV measure and other such as travel cost and hedonic price measures of the value of the same good
– The extent to which the findings of the CV study are consistent with theoretical expectations
Contingent Valuation MethodContingent Valuation MethodSteps in a CVM ProcedureSteps in a CVM Procedure
Contingent Valuation MethodContingent Valuation MethodApplication Application
Contingent Valuation MethodContingent Valuation MethodApplicationApplication
Contingent Valuation MethodContingent Valuation MethodApplicationApplication
• A good CV study will consider the following– Thoroughly pre-test the valuation questionnaire
for potential biases – Include validation questions in the survey
• to verify comprehension and acceptance of the scenario
• to elicit socioeconomic and attitudinal characteristics of respondents
• Make sure that survey results are analyzed and interpreted by professionals before making any claims about the resulting dollar values
Contingent Valuation MethodContingent Valuation MethodAssociatedAssociated Biases (1)Biases (1)
Contingent Valuation MethodContingent Valuation MethodAssociatedAssociated Biases (2)Biases (2)
Contingent Valuation MethodContingent Valuation MethodExamples of MinimizingExamples of Minimizing Biases (1)Biases (1)
Question Bias
a. I cannot afford to pay more water charges at present
b. I have no interest in having different flow levels in rivers
c. I would not pay anymore in water charges but I would be prepared to pay by some other means of payment
Payment vehicle
d. Someone else should pay rather than me Strategic
e. The water company should pay not customers Bid vehicle
f. Low levels in rivers are not a problem
g. I require more information to answer this question
h. Other reasons. Please specify
i. Don’t know
j. Refused to answer
Show card to elicit legitimate and illegitimate reason for NOT being WTP towards low flow alleviation in rivers
Contingent Valuation MethodContingent Valuation MethodExamples of MinimizingExamples of Minimizing Biases (2)Biases (2)
Question Bias
a. It was the most I could afford to pay
b. Rivers and beaches are important for recreation and I am happy to pay to ensure that they are well looked after
c. I would pay this much each year to ensure that rivers and beaches are protected for future generations
d. Rivers and beaches are important for wildlife and ecology and I am happy to pay to ensure that they are well looked after.
e. I wanted to show my support for environmental improvement in general Strategic
f. It’s an important issue and by saying I’d pay such a large sum each year I hope to get something done about it
Strategic
g. I’m very concerned about this issue and although I’m not sure I could afford to pay this much each year I wish I could
Hypothetical
h. Rivers and beaches are important for a number of reasons and I am happy to pay to ensure that they are well looked after
i. Other reason. Please specify;
j. Don’t know
k. Refuse to answer
Show card to elicit legitimate and illegitimate reason for being WTP towards low water quality
Contingent Valuation MethodContingent Valuation MethodIllustration Illustration
Hypothetical Scenario*• A remote site on public land provides important habitat
for several species of wildlife• The management agency in charge of the area must
decide whether to issue a lease for mining at the site– they must weigh the value of the mining lease against the
wildlife habitat benefits that may be lost if the site is developed
– non-use values are the largest component of the value for preserving the site because few people actually visit it, or view the animals that rely on it for habitat
*www.ecosystemvaluation.org
Contingent Valuation MethodContingent Valuation MethodIllustration Illustration
Application of the Contingent Valuation MethodStep 1• Define the valuation problem
– Determine what services are being valued• the resource to be valued is a specific site and the services it provides are
primarily wildlife habitat– Determine who the relevant population is
• Because it is federally owned public land, the relevant population would be all citizens of the U.S.
Step 2• Make preliminary decisions about the survey itself
– whether it will be conducted by mail, phone or in person– how large the sample size will be– who will be surveyed, etc. – The answers will depend, among other things, on
• the importance of the valuation issue• the complexity of the question being asked• the size of the budget
Contingent Valuation MethodContingent Valuation MethodIllustration Illustration
Step 2 (cont’d)• The researchers decided to conduct a mail survey
– they want to survey a large sample, over a large geographical area– They are asking questions about a specific site and its benefits, which
should be relatively easy to describe in writing in a relatively short survey
Step 3 • The actual survey design may take six months or more to complete• It is accomplished in several steps
– Starts with initial interviews and/or focus groups with the types of people who will be receiving the final survey, in this case the general public
• the researchers would ask general questions– about peoples’ understanding of the issues related to the site– whether they are familiar with the site and its wildlife– whether and how they value this site and the habitat services it provides
Contingent Valuation MethodContingent Valuation MethodIllustration Illustration
Step 3 (cont’d)• In later focus groups, the questions would get more detailed and
specific– to help develop specific questions for the survey– to decide what kind of background information is needed and how to
present it• People might need information on the location and characteristics of the site, the
uniqueness of species that have important habitat there, and whether there are any substitute sites that provide similar habitat.
• The researchers would also want to learn about peoples’ knowledge of mining and its impacts, and whether mining is a controversial use of the site. If people are opposed to mining, they may answer the valuation questions with this in mind, rather than expressing their value for the services of the site
– At this stage, different approaches to the valuation question and different payment mechanisms would be tested
– Questions that can identify any “protest” bids or other answers that do not reveal peoples’ values for the services of interest would also be developed and tested at this stage.
Contingent Valuation MethodContingent Valuation MethodIllustration Illustration
Step 3 (cont’d)• After a number of focus groups, pretesting of the survey is
started– The survey should be pretested with as little interaction with the
researchers as possible– Pre-testing will continue until a survey is developed that people
seem to understand and answer in a way that makes sense and reveals their values for the services of the site
Step 4• Actual survey implementation.
– Select the survey sample• the sample should be a randomly selected sample of the relevant
population, using standard statistical sampling methods– obtain a mailing list of randomly sampled U.S. Citizens– use a standard repeat-mailing and reminder method to get the greatest possible
response rate for the survey
Contingent Valuation MethodContingent Valuation MethodIllustration Illustration
Step 5• Compile, analyze and report the results
– data must be entered and analyzed using statistical techniques appropriate for the type of question
– The researchers also attempt to identify any responses that may not express the respondent’s value for the services of the site
– they can deal with possible non-response bias in a number of ways• The most conservative way is to assume that those who did not respond have
zero value
Results• Estimate the average value for an individual or household in the
sample, and extrapolate this to the relevant population in order to calculate the total benefits from the site– If the mean willingness to pay is $.10 per capita, the total benefits to all
citizens would be $26 million.
Contingent Valuation MethodContingent Valuation MethodAdvantages Advantages
• The most widely accepted method for estimating total economic value including use values and all types of non-use values
• Straightforward and highly flexible– can used to estimate the economic value of virtually anything– best suited to estimate values for goods and services that are easily
identified and understood by users and that are consumed in discrete units
• Requires few theoretical assumptions• The nature and results of CV studies are easy to analyze and
describe– Dollar values can be presented in terms of a mean or median value per
capita or per household, or as an aggregate value for the affected population.
• A great deal of research is being conducted to– improve the methodology– make results more valid and reliable– better understand its strengths and limitations
Contingent Valuation MethodContingent Valuation MethodIssues and Limitations (1)Issues and Limitations (1)
• Considerable controversy over whether CVM adequately measures people's willingness to pay for environmental quality– CV assumes that people understand the good in question and
will reveal their preferences in the contingent market just as they would in a real market
– Most people are unfamiliar with placing dollar values on environmental goods and services and may not have an adequate basis for stating their true value
• Expressed answers to a willingness to pay question may be biased
• Respondents may make associations among environmental goods that the researcher had not intended– For example, if asked for willingness to pay for improved visibility
(through reduced pollution), the respondent may actually answer based on the health risks that he or she associates with dirty air
Contingent Valuation MethodContingent Valuation MethodIssues and Limitations (2)Issues and Limitations (2)
• WTA very significantly exceeds WTP– this result may invalidate the CVM approach, showing responses to be
expressions of what individuals would like to have happen rather than true valuations
• The “ordering problem”– In some cases, people’s expressed willingness to pay for something has
been found to depend on where it is placed on a list of things being valued
• Difficulty to validate externally the estimates of non-use values
• When conducted appropriately, contingent valuation methods can be very expensive and time-consuming, because of the extensive pre-testing and survey work
• Many people, including jurists policy-makers, economists, and others, do not believe the results of CV
Contingent Valuation MethodContingent Valuation MethodSample application 1Sample application 1-- Mono Lake* Mono Lake*
Background
*www.ecosystemvaluation.org
Contingent Valuation MethodContingent Valuation MethodSample application 1Sample application 1-- Mono Lake Mono Lake
Initial Work • Initial mail survey where residents of California
– Were told that, according to biologists, the higher flows to thelake were needed to maintain food supplies for nesting and migratory birds
– Were asked whether they would pay more on their water bill for higher cost replacement water supplies, so that natural flows could once again go into Mono Lake
Results• Average WTP per household =
$13 per month = $156 per year• The total benefits exceeded the
$26 million cost of replacing thewater supply by a factor of 50.
http://www.ram.org/pictures/sights/cctrip/mono_lake.gif
Contingent Valuation MethodContingent Valuation MethodSample application 1Sample application 1-- Mono Lake Mono Lake
Follow-up Work • The State of California hired a consulting firm to perform a more
detailed CV survey• New survey
– Involved the use of photo-simulations showing what the lake would look like at alternative water levels
– Gave detailed information about effects of changing lake levels on different bird species
– Was conducted over the telephone, with people who had been mailed information booklets with maps and photo-simulations
– Survey respondents were asked how they would vote in a hypothetical referendum regarding Mono Lake.
• This study showed that the benefits of a moderately high (but not the highest) lake level were greater than the costs
• The California Water Resources Control Board reduced Los Angeles’ water rights by half, from 100,000 acre feet to about 50,000 acre feet, to allow more flows into Mono Lake
Contingent Valuation MethodContingent Valuation MethodSample application 2Sample application 2-- Water Over the FallsWater Over the Falls**
Background• The Federal Energy Regulatory Commission faced a licensing
decision regarding how much water the utility company should allow to flow over the falls at a recreation area
• Increasing the flow over the falls would result in less hydropower generated, but more water for recreation
• The previous license required only a minimum in stream flow of 50 cubic feet per second, which reduced the flow over the falls to a trickle
• A contingent valuation survey was developed to determine how much visitors to the falls would be willing to pay for increasedoverflow levels
*www.ecosystemvaluation.org
Contingent Valuation MethodContingent Valuation MethodSample application 2Sample application 2-- Water Over the FallsWater Over the Falls
Application • The survey
– included pictures of the falls at four different flow levels– was mailed to a sample of previous visitors to the site
• The key survey questions asked– how much individuals would pay to visit the falls with each of the
four flow levels depicted in the photos, and how many times theywould visit each year at the four different flow levels
Results• A statistical analysis of the survey results used to estimate a total
recreation benefit function– the economic value of additional flows in each month was calculated,
and compared to the economic value of the foregone hydropower required to allow the additional flows
• The resulting optimum flow level during the summer months, when visitation was high, was calculated as 500 cubic feet per second, which was ten times larger then the existing minimum in stream flow
Contingent Valuation MethodContingent Valuation MethodSample application 3Sample application 3-- Glen Canyon Dam*Glen Canyon Dam*
Background• In the early 1980’s it became clear that continued operation of the
Glen Canyon dam to provide peak-load power – adversely affecting the downstream ecosystem in the Grand Canyon– significantly reducing the quality of recreational rafting
• The valuation question of concern was how much recreational rafting was worth compared to the market value of the peak-loadpower supply
Application • The study attempted to quantify
how the value of rafting in theGrand Canyon would change withmore even base flows, as compared to reduced flows during peak-power periods
http://www.hdprint.co.uk/ftp/CanyonLands/212%20-%20Glen%20Canyon%20Dam%20from%20plane.jpg
*www.ecosystemvaluation.org
Contingent Valuation MethodContingent Valuation MethodSample application 3Sample application 3-- Glen Canyon DamGlen Canyon DamResults • Substantial economic values for rafting with increased water flows =
$2 million per year• CVM helped change perspectives about how economic tradeoffs should be
discussed– the challenge was now to find a release pattern that increased the economic value of
all uses of the river water• More even flows were put into place while the final environmental impact
studies were being prepared• The study represented one of the first federally-funded projects to estimate
non-use values
Additional Research • It became more obvious that citizens throughout the U.S., not just rafters,
cared about how dam operations affected the natural resources of the Grand Canyon
• The Bureau of Reclamation funded a major contingent valuation study of households throughout the U.S. to estimate their willingness to pay for flow regimes that would protect the natural resources in the Grand Canyon.
• Results showed strong support for a more natural flow regime
Contingent Valuation MethodContingent Valuation MethodSample application 4Sample application 4-- NonNon--commercial Fish* commercial Fish* Background• Rivers in the Four Corners Region provide 2,465 river
miles of critical habitat for nine species of fish that are listed as threatened or endangered
• Continued protection required habitat improvements to imitate natural water flows needed by fish– fish passageways– bypass releases of water from dams
• A CV survey was used to estimate the economic value for preserving the critical habitat
*www.ecosystemvaluation.org
Contingent Valuation MethodContingent Valuation MethodSample application 4Sample application 4-- NonNon--commercial Fish commercial Fish
Application • Sample
– Random sample of 800 households in the Four Corners states of Arizona, Colorado, New Mexico, and Utah (with the proportions based on the states’ relative populations).
– An additional 800 households from the rest of the U.S.• Survey respondents
– provided detailed maps that highlighted the areas designated as critical habitat units for the fish
– told that some State and Federal officials thought the combined costs of the habitat improvements and the restrictions on hydropower were too costly and had put forward a proposal to eliminate the critical habitat unit designation
– asked if they would contribute to the Four Corners Region Threatened and Endangered Fish Trust Fund
– told that efforts to raise funds would involve contributions from all U.S. Taxpayers
• If a majority of households voted in favor of the fund, the fish species would be protected from extinction
– through water releases from Federal dams timed to benefit fish– through the purchase of water rights to maintain in stream flows
Contingent Valuation MethodContingent Valuation MethodSample application 4Sample application 4-- NonNon--commercial Fishcommercial Fish
Application (cont’d)• Respondents were told that• within the next 15 years, three fish species would increase in population to the point that
they would no longer be listed as threatened species• if a majority of households in the U.S. voted not to approve the fund, the critical habitats
shown on the map would be eliminated, causing the extinction of four of the nine fish species in 15 years
• The exact wording on the questionnaire was:
Suppose a proposal to establish a Four Corners Region Threatened and Endangered Fish Trust Fund was on the ballot in the next nationwide election. How would you vote on this proposal? Remember, by law, the funds could only be used to improve habitat for fish. If the Four Corners Region Threatened and Endangered Fish Trust Fund was the only issue on the next ballot and it would cost your household $______ every year, would you vote in favor of it?
(Please circle one.) YES / NO
The dollar amount, blank in the above illustration, was filled in with one of 14 amounts ranging from $1-$3 to $350, which were randomly assigned to survey respondents.
Contingent Valuation MethodContingent Valuation MethodSample application 4Sample application 4-- NonNon--commercial Fishcommercial Fish
Results • The average WTP = $195 per household• When extrapolated to the general
population, the value of preserving the habitat areas was determined to be far in excess of the costs.
Contingent Valuation MethodContingent Valuation MethodSample application 5Sample application 5-- Salmon RestorationSalmon Restoration**
Background• The removal of dams blocking salmon migration
routes has been proposed– the Elwha and Glines dams on the Elwha River on the
Olympic Peninsula in Washington• 200-foot dams • very old • have no fish ladders• block migration of fish to 70 miles of pristine
spawning grounds in Olympic National Park– Dam removal would more than triple
salmon populations on the Elwha River– Cost to remove the dams and the 50 years of
sediment build-up behind them was estimated = $100-$125 million
seattletimes.nwsource.com/html/localnews/2001
*www.ecosystemvaluation.org
Contingent Valuation Method Contingent Valuation Method Sample application 5Sample application 5-- Salmon RestorationSalmon Restoration
Application • CVM survey developed to estimate the economic values associated
with the removal of the dams– Households in Washington and elsewhere were surveyed– Asked if they would vote in favour of removing the dams and restoring
the river, in order to triple salmon populations at an annual cost that varied across households.
Results • The estimated economic values per household ranged from $73 for
Washington households to $68 for the rest of the U.S. Households
• The economic value to Washington residents alone would nearly beenough to justify removing the dams and restoring the river– National willingness to pay was in excess of $1 billion
Contingent Valuation MethodContingent Valuation MethodCaseCase--study 1study 1-- Exxon Valdez Oil Spill* Exxon Valdez Oil Spill*
Background• In March 1989, the oil
tanker Exxon Valdezwent aground on Bligh Reef Prince William Sound, Alaska
• Around 11 million gallons of crude oil were spilled
• In 5 months,– Oil has moved across
nearly 10,000 square miles of water
– About 1,600 mile of the Sound’s shoreline was heavily oiled
http://menlocampus.wr.usgs.gov/50years/accomplishments/oil.html
http://menlocampus.wr.usgs.gov/50years/accomplishments/oil.html
* Hodge, I, 1995.
Contingent Valuation MethodContingent Valuation MethodCaseCase--study 1study 1-- Exxon Valdez Oil Spill Exxon Valdez Oil Spill
Spill Impact• On wildlife
– Over 20,000 dead birds recovered including 100 bald eagles
– Over 2,650 dead sea otters
– Seals and other species were also damaged or killed including plants and microorganisms
– None of the losses threatened species extinction
– Birds and mammal populations expected to recover within 3-5 years
http://www.alaska-in-pictures.com/data/media/4/exxon-victim_2901.jpg
www.channel6.dk/native/uk/page104.html
Contingent Valuation MethodContingent Valuation MethodCaseCase--study 1study 1-- Exxon Valdez Oil Spill Exxon Valdez Oil Spill
Spill Impact• On commercial and recreational fishing
and tourism– These impacts could be valued easily
• Non-use values: existence, options, and bequest values–– CVM study CVM study in connection with legal action by
State of Alaska against Exxon corporation
Contingent Valuation MethodContingent Valuation MethodCaseCase--study 1study 1-- Exxon Valdez Oil Spill Exxon Valdez Oil Spill
Methodology• Survey of residents across the US • Alaska excluded to focus on non-use values• In principle, survey should ask about the WTA compensation for the
damage arising from the spill• WTP approach adopted due to difficulty in survey design• Hypothetical market:
– Proposal for a scheme to prevent future oil spills of the sort that had been experienced
• Escort ships to accompany oil tankers through the Sound• Escort ships carry special booms to be used immediately in the case of an oil spill
to contain the damage• Spilled oil then skimmed off and taken for safe disposal
– Without the scheme, oil spill to occur within the next 10 years– Scheme financed from a special tax on oil company profits and from a
single tax on all households
Contingent Valuation MethodContingent Valuation MethodCaseCase--study 1study 1-- Exxon Valdez Oil Spill Exxon Valdez Oil Spill
Methodology• Survey
– Investigated respondents prior knowledge on the issue
– Provided respondents with info on the spill and its impacts
– Basic valuation question• Whether or not he/she would vote for a proposal to
implement the scheme given a specified level of a single one-time tax
– Tax values set at $10, $30, $60, and $120• If responded answered ‘yes’, the amount was raised and the
question asked just once more– Collected information on
• Interest in environmental issues, household composition, education and incomes
Contingent Valuation MethodContingent Valuation MethodCaseCase--study 1study 1-- Exxon Valdez Oil Spill Exxon Valdez Oil Spill
MethodologyExcerpts of the administered questionnaire:
“The only mammals killed by the spill were sea otters and harbour seals. This card shows information about what happened to Prince William Sound. According to scientific studies, about 580 otters and 100 seals in the Sound were killed by the spill. Scientists expect the population size of these two species to return to normal within a couple of years after the spill.
Many species of fish live in these waters. Because most of the oil floated on the surface of the water, the spill harmed few fish. Scientific studies indicate there will be no long-term harm to any of the fish populations.
#2. Of course, whether people would vote for or against the escort ship program depends on how much it will cost their householdAt present, government officials estimate the program will cost your household a total of $______. You would pay this in a special one-time charge in addition to your regular federal taxes. This money would only be used for the program to prevent damage from another oil spill in Prince William Sound.If the program cost your household a total of $______, would you vote for or against it?”
Contingent Valuation MethodContingent Valuation MethodCaseCase--study 1study 1-- Exxon Valdez Oil Spill Exxon Valdez Oil Spill
MethodologyExcerpts of the administered questionnaire:
“#3. What if the final cost estimate showed that the program would cost your household a total of $_______. Would you vote for or against the program?
#4. What is it about the program that made you willing to pay something for it?
#5. Before the survey, did you think the damage caused by the Valdez oil spill was more serious than was described to you, less serious, or about the same as described?
#6. Is anyone in your household an angler, birdwatcher, backpacker, or environmentalist?
#7. This card shows amounts of yearly incomes. Which category best describes the total income from all members of your family before.”
Contingent Valuation MethodContingent Valuation MethodCaseCase--study 1study 1-- Exxon Valdez Oil Spill Exxon Valdez Oil Spill
Results• 1,043 interviews completed successfully• Response rate = 75 percent• Proportion of respondents voting for the scheme
– Proportion decreases as cost of scheme increases– There is little difference between the $30 and $60
questions
Questionnaire version
Initial tax level per household (USD)
Percent of respondents willing to pay taxes
A 10 67
B 30 52
C 60 51
D 120 34
Positive response to alternative tax levels
Contingent Valuation MethodContingent Valuation MethodCaseCase--study 1study 1-- Exxon Valdez Oil Spill Exxon Valdez Oil Spill
Results• Median = 31 USD (adopted)• Mean = 94 USD (dismissed)
– Considered unreliable due to the nature of the questions asked
• One third were not willing to pay at either of the offered prices– They believed that oil companies should pay
• Total value for non-use values lost in the US:
31 USD 31 USD ×× 91 million households = 2.8 billion USD (CI: 2.491 million households = 2.8 billion USD (CI: 2.4--3.2)3.2)
Contingent Valuation MethodContingent Valuation MethodCaseCase--study 2study 2-- Wilderness designation in Colorado*Wilderness designation in Colorado*
Case• Evaluating increments of wilderness
designations in Colorado in Summer 1980
http://images.google.com/imgres?imgurl=http://lh3.google.com/_t45xPwpSIdI/RihTxMzwEeI/AAAAAAAAAhw/n7pXikvzgB0/s800/Pano%2B-%2BIMGP3464%2B-%2B3952x3754%2B-%2BPLIN%2B-%2BBlended%2BLayer.jpg&imgrefurl=http://picasaweb.google.com/lh/photo/S4znX1uzeyI6XzqK2vmmZQ&h=760&w=800&sz=109&hl=en&start=1&tbnid=gVAC_Q6WZm7qRM:&tbnh=136&tbnw=143&prev=/images%3Fq%3Dwilderness%2BColorado%26gbv%3D2%26hl%3Den
http://ridethegreatdivide.blogspot.com/2007/07/south-san-juan-wilderness.html
* Hussen, AM, 1999
Contingent Valuation MethodContingent Valuation MethodCaseCase--study 2study 2-- Wilderness designation in ColoradoWilderness designation in Colorado
Methodology• Mail survey• Sample size = 218 Colorado households• Participants shown 4 maps of the State of Colorado
– Map 1: • 1.2 million acres of land currently designated as wilderness• Represent 2 percent of the state land
– Map 2:• 2.6 million acres of land hypothetically designated as wilderness
– Map 3:• 5 million acres of land hypothetically designated as wilderness
– Map 4:• 10 million acres of land hypothetically designated as wilderness
• Participants provided with realistic and credible information about the hypothetical market
Contingent Valuation MethodContingent Valuation MethodCaseCase--study 2study 2-- Wilderness designation in ColoradoWilderness designation in Colorado
Methodology• Respondents asked to write their maximum annual
WTP four the preservation of the 4 maps• Respondents then asked to allocate their WTP
among four categories of value– Recreational use– Option demand– Existence demand– Bequest demand
• Data was gathered, processed, and a statistical demand analysis was employed to estimate preservation values
Preservation valueof wilderness
Contingent Valuation MethodContingent Valuation MethodCaseCase--study 2study 2-- Wilderness designation in ColoradoWilderness designation in Colorado
Results: Total annual consumer surplus (US$) from recreation use and preservation value
Value categories Map A(1.2 M acres)
Map B(2.6 M acres)
Map C(5 M acres)
Map D(10 M acres)
Recreation use valuePer visitor dayTotal, million
14.0013.2
14.0021.0
14.0033.1
14.0058.2
Option valuePer householdTotal, million
4.044.4
5.446.0
7.348.1
9.2310.2
Existence valuePer householdTotal, million
4.875.4
6.567.2
8.869.7
11.1412.3
Bequest valuePer householdTotal, million
5.015.5
6.757.4
9.1010.0
11.4612.5
Preservation value to Colorado residentsPer householdTotal, million
13.9215.3
18.7520.6
25.3027.8
31.8335.0
Total annual recreation use value and preservation value to Colorado households (million)28.5 41.6 60.9 93.2
Contingent Valuation MethodContingent Valuation MethodCaseCase--study 2study 2-- Wilderness designation in ColoradoWilderness designation in Colorado
Discussion:• Increasing the area of wilderness from 1.2 to 2.6
acres increase total value by 46 percent (28.5 to 41.6 million USD)
• For all wilderness designations, non-use values represented a significant portion of the total value
Contingent Valuation MethodContingent Valuation MethodCaseCase--study 3: Coastal Degradation of Jounieh study 3: Coastal Degradation of Jounieh
Beach, LebanonBeach, LebanonBackground •The coastal zones of Lebanon represent unique economic and recreational assets
• Coast line > 240 km• > 50% of population concentrated along the coast
•Untreated municipal wastewater disposal, seafront solid waste dumps, uncontrolled development of resorts and vacation homes, etc.
Coastal zone/Beach degradationCoastal zone/Beach degradation(Loss in ecological and non(Loss in ecological and non--use values of the beach)use values of the beach)
Contingent Valuation MethodContingent Valuation MethodCaseCase--study 3: Coastal Degradation of Jounieh study 3: Coastal Degradation of Jounieh
Beach, LebanonBeach, Lebanon
MethodologyA survey was conducted to estimate the WTP for
restoration of Jounieh beach as an ecological protected area
Cost of degradation associated with ecological Cost of degradation associated with ecological and nonand non--use value of coastal areas of Lebanonuse value of coastal areas of Lebanon
Results• WTP per household for restoration of Jounieh beach
– Survey respondents were asked about their WTP for Jounieh beach restoration with payments each year for 10 years
– The average WTP per year of survey respondents was adjusted to reflect average income of Lebanese households
– A regression analysis (with low and high coefficients) was undertaken to estimate WTP in relation to income
Contingent Valuation Method Contingent Valuation Method CaseCase--study 3: Coastal Degradation of Jounieh study 3: Coastal Degradation of Jounieh
Beach, LebanonBeach, Lebanon
Survey LebanonLow High
Number of survey responses 94
WTP in relation to income WTP per 500US$ monthly income 15.3 10Average WTP/yr for 10 years US$/household 80.05 57 66WTP/household over 10 years US$
10% discount rate 385.3 446.15% discount rate 462.1 535.1
Results• WTP per household for restoration of Jounieh beach
– Household WTP annualized over 30 years – Two discount rates applied:
• 5%, reflecting a combination of social rate of intertemporal substitution and opportunity cost of capital
• 10%, reflecting opportunity cost of capital
Contingent Valuation Method Contingent Valuation Method CaseCase--study 3: Coastal Degradation of Jounieh study 3: Coastal Degradation of Jounieh
Beach, LebanonBeach, Lebanon
Survey LebanonLow High
WTP/household over 10 years US$10% discount rate 385.3 446.15% discount rate 462.1 535.1
Annualized WTP/household US$
10% discount rate over 30 years 37.2 43.0
5% discount rate over 30 years 28.6 33.2
Results• Total WTP for restoration of Lebanese coast
– Number of Lebanese households: 935,000
Contingent Valuation Method Contingent Valuation Method CaseCase--study 3: Coastal Degradation of Jounieh study 3: Coastal Degradation of Jounieh
Beach, LebanonBeach, Lebanon
LebanonLow High
Annualized WTP/household US$
10% discount rate over 30 years 37.2 43.0
5% discount rate over 30 years 28.6 33.2
Lebanese households 935,000 935,000
Total annualized WTP US$ million (all Lebanon) 27 40% GDP 0.16 0.24
Average annual WTP = 33.5 million US$= 0.2% of GDP
Contingent Valuation MethodContingent Valuation MethodCaseCase--study 4: Beach degradation in Moroccostudy 4: Beach degradation in Morocco
Background• The coastline of Morocco: 3,500 km, 13 coastal
zones, and 174 beaches• Domestic and industrial wastewater discharge,
industrial accidents, offshore pollution from ships and boat harbors, haphazard construction along the coast, etc.
Coastal zone/Beach degradationCoastal zone/Beach degradationIn 2002, “Monitoring Bathing Beach Waters in
Morocco” campaign showed that 28% of beaches were unfit for swimming
Contingent Valuation Method Contingent Valuation Method CaseCase--study 4: Beach degradation in Moroccostudy 4: Beach degradation in Morocco
Methodology• Annual cost of coastal degradation
– Willingness to Pay (WTP) of foreign tourists and Moroccan nationals living abroad to improve the coast
Tourists are willing to pay an additional value for Tourists are willing to pay an additional value for ““unspoiled destinationsunspoiled destinations”” as opposed to as opposed to ““slightly slightly
spoiledspoiled”” or or ““very spoiledvery spoiled”” destinationsdestinations– Lost recreational value for Moroccan residents
– Loss of local fishing (sardines)
Contingent Valuation Method Contingent Valuation Method CaseCase--study 4: Beach degradation in Moroccostudy 4: Beach degradation in Morocco
Moroccan touristic statistics(Department of Tourism, Statistics, 2000, 2001, 2002)
Total tourists (foreigners and Moroccans living abroad) 4,113,037Total foreign nationalities 2,462,894
North Americans 155,388North and West Europeans 1,127,211Total North American and European tourists 1,282,599
Moroccan nationals living abroad 1,650,143Number of nights occupied by foreign tourists in classed hotels 13,539,586Average length of stay of foreign tourists (days) 5.5Total tourism expenses (million Dh) 21,644Average daily tourism expenses (Dh/per/day) 957
Contingent Valuation Method Contingent Valuation Method CaseCase--study 4: Beach degradation in Moroccostudy 4: Beach degradation in Morocco
Methodology• Step 1: Estimation of WTP by foreign tourists to conserve the coast
– Based on a study conducted by Huybers and Bernnett (2000)*, British touristsare willing to pay US$ 70 per day (or 35% of their daily tourist expenses) for “unspoiled destinations” as opposed to “slightly spoiled” or “very spoiled”destinations
– This same proportion was applied to European and North American tourists visiting the Moroccan coast
Low HighAverage stay of North American and European tourists on the coast, days(1/3 and 2/3 of average stay, 5.5 days)
2 4
Number of North American and European tourists 1,282,599Total number of North American and European tourist stay days, days 2,565,198 5,130,396WTP to improve the coast, Dh/per/day(35% of the average daily tourism expenses in Morocco, 957)
338
Total WTP by North American and European tourists to improve thecoast (Million Dh) 867 1,735
* Huybers, T and Bernnett, Impact of the Environment on Holiday Destination Choices for Tropical North Queensland, Tourism Economics, 6(1), pp. 21-46, 2000.
Contingent Valuation Method Contingent Valuation Method CaseCase--study 4: Beach degradation in Moroccostudy 4: Beach degradation in Morocco
Methodology• Step 2: Estimation of WTP by Moroccan nationals living
abroad to conserve the coast– The same approach applied to foreign tourists was applied to Moroccan
nationals living abroad, except:• WTP was applied to the household, since Moroccans normally visit their
country with the entire family (rather than individually, like foreign tourists)• Stays of Moroccan nationals are longer, averaging between 7 and 14 days
Low HighMoroccan nationals living abroad visiting country 1,650,143Average persons per household in Morocco 5.6Total number of Moroccan households living abroad visiting country 294,668
of which, households having similar economic conditions as NorthAmerican and European tourists (20% of total) 58,934
Average stay of Moroccan nationals on the coast, days 7 14Total number of stay days of Moroccan households living abroad, days 412,538 825,076WTP to improve the coast, Dh/household/day(35% of the average daily tourism expenses in Morocco, 957)
338
Total WTP by Moroccan nationals living abroad to improve the coast (Million Dh) 139.4 278.9
Contingent Valuation Method Contingent Valuation Method CaseCase--study 4: Beach degradation in Moroccostudy 4: Beach degradation in Morocco
Methodology• Step 3: Assessing the total WTP to improve the
coast, due to beach degradation
The average WTP to improve the coast, due to The average WTP to improve the coast, due to beach degradation in Morocco:beach degradation in Morocco:
Dh 1,510 million, 0.2 % of the GDPDh 1,510 million, 0.2 % of the GDP
Low HighWTP by foreign tourists, million Dh 867 1,735WTP by Moroccan nationals living abroad, million Dh 139.4 278.9Total WTP to improve the coast, million Dh 1,007 2,014Percent of GDP (%) 0.14 0.28
EEnd of nd of SSession ession 99
Thank YouThank You
REGIONAL WORKSHOP REGIONAL WORKSHOP ONON
THE COST OF THE COST OF ENVIRONMENTAL ENVIRONMENTAL
DEGRADATION DEGRADATION METHODOLOGYMETHODOLOGY
Session 10aTHE DISCRETE CHOICE METHOD
REGIONAL WORKSHOP ONREGIONAL WORKSHOP ON
THE COST OF ENVIRONMENTAL THE COST OF ENVIRONMENTAL DEGRADATION METHODOLOGYDEGRADATION METHODOLOGY
Session 10aTHE DISCRETE CHOICE METHOD
Preferences
Revealedpreferences
StatedPreferences
MarketValues
Travel Cost Methods
HedonicMethod
Averting Behavior
ContingentValuation
ChoiceExperiments
USE VALUES USE + NON-USE VALUES
Dose Response Functions
Environmental Valuation MethodsEnvironmental Valuation Methods
Discrete Choice MethodDiscrete Choice MethodOUTLINEOUTLINE
• Overview• Types of formats• Choice modelling• Illustration• Summary• Advantages• Issues and limitations• Case-studies
Discrete Choice MethodDiscrete Choice MethodOverviewOverview
• Contingent choice, also referred to as conjoint analysis, was developed in the fields of marketing and psychology to measure preferences for different characteristics or attributes of a multi-attribute choice
• The contingent choice method is similar to contingent valuation– asks people to make choices based on a hypothetical scenario– can be used to estimate economic values for any ecosystem or environmental service– can be used to estimate non-use as well as use values
• Differs from contingent valuation because– it requires people to evaluate several alternatives separately– it does not directly ask people to state their values in dollars
• values are inferred from the hypothetical choices or tradeoffs that people make
• Asks the respondent to state a preference between one group of environmental services or characteristics, at a given price or cost to the individual, and another group of environmental characteristics at a different price or cost
Discrete Choice MethodDiscrete Choice MethodOverviewOverview
• Is especially suited to policy decisions where a set of possible actions might result in different impacts– For example, improved water quality in a lake will
improve the quality of several services provided by the lake, such as drinking water supply, fishing, swimming, and biodiversity
• While contingent choice can be used to estimate dollar values, the results may also be used to simply rank options, without focusing on dollar values
• There are a variety of formats for applying contingent choice methods
Discrete Choice MethodDiscrete Choice MethodTypes of FormatsTypes of Formats
Discrete Choice MethodDiscrete Choice MethodChoice ModelingChoice Modeling
• Choice experiments are used to examine the response of the individual to changes in the attributes of the scenario as well as the scenario as a whole– Allows breaking down the relevant attributes of the
situation and determining preferences over attributes– Allows for more flexibility than CVM
• Choice experiments attempt to identify the utility the individuals have for the attributes of the goods and services by examining the tradeoffs that they make between them when making choice decisions
Discrete Choice MethodDiscrete Choice MethodChoice ModelingChoice Modeling
Discrete Choice MethodDiscrete Choice MethodChoice ModelingChoice Modeling
Discrete Choice MethodDiscrete Choice MethodChoice ModelingChoice Modeling
• Initial screening of the attributes– Crucial stage in study design– Attributes should be familiar and relevant to
respondents– Attribute levels should be measureable using
quantitative or qualitative scales– Ways for portraying attributes
• Verbal, pictorial, etc.– It is important to define an appropriate number of
attributes• Too many attributes burden the respondents• Too few cause problems with estimation and reliability
– Pre-testing and focus groups helpful in defining attributes and determining their numbers
Discrete Choice MethodDiscrete Choice MethodChoice ModelingChoice Modeling
• Experimental design– The specification of a factorial or fractional
factorial experimental design to estimate the utility for the good in question
• Use an orthogonal main-effects plan sampled from the complete factorial design to select the profiles to be used in the choice experiment
– Procedures in computer packages such as SAS and SPSS may be used to create an orthogonal matrix based on the attribute levels specified by the researcher
Discrete Discrete Valuation MethodValuation MethodChoice ModellingChoice Modelling
Survey designQuestionnaire administered in a number of ways
Discrete Choice MethodDiscrete Choice MethodChoice ModelingChoice Modeling
• Analysis of the choices– Random utility theory used to model the choices
as a function of attribute levels• Based on the hypothesis that individuals make choices
based on the attributes of the alternatives along with some degree of randomness
– Based on repeated observations of choice, one can examine how the levels of various attributes affect the probability of choice
• An assumption of normality leads to the binary probit model
• An assumption of a Gumbel distribution means that the multinomial or Mother Logit can be employed
Discrete Choice MethodDiscrete Choice MethodIllustrationIllustration
Background• A remote site on public land that provides important habitat for
several species of wildlife• The management agency in charge must decide whether to issue a
lease for mining at the site• Suppose that there are several possible options for preserving
and/or using the site– allowing no mining and preserving the site as a wilderness habitat area– various levels and locations for the mining operation, each of which
would have different impacts on the site• The contingent choice method selected because
– the outcomes of several policy options needs to be valued– Non-use values are the largest component of the value for preserving
the site• The TCM will underestimate the benefits of preserving the site• The CVM might also be used but the survey questions might
become very complicated
Discrete Choice MethodDiscrete Choice MethodIllustrationIllustration
Application• Contingent choice and contingent valuation have very similar
application – The main differences are in the design of the valuation
question(s), and the data analysis.
Step 1• Define the valuation problem
– Determine exactly what services are being valued, and who the relevant population is
• the resource to be valued is a specific site and the services it provides i.e. wildlife habitat
• because it is federally owned public land, the relevant population would be all citizens of the U.S.
Discrete Choice MethodDiscrete Choice MethodIllustrationIllustration
Step 2• Make preliminary decisions about the survey
– whether it will be conducted by mail, phone or in person,
– how large the sample size will be, who will be surveyed, and other related questions
– In this case, the researchers decided to conduct a mail survey
• Administered to a large sample• Over a large geographical area• Questions about a specific site and its benefits should
be relatively easy to describe in writing
Discrete Choice MethodDiscrete Choice MethodIllustrationIllustration
Step 3• Survey design is accomplished in several steps
– starts with initial interviews and/or focus groups with the types of people who will be receiving the final survey
– In the initial focus groups, the researchers would ask general questions• about peoples’ understanding of the issues related to the site• whether they are familiar with the site and its wildlife• whether and how they value this site and the habitat services it provides
– In later focus groups, the questions would get more detailed and specific• different approaches to the choice question are tested
– each choice might be described in terms of the site’s ability to support each of the important wildlife species.
– people will be making tradeoffs among the different species that might be affected in different ways by each possible choice of scenario
– Pre-testing the survey• People would be asked to assume that they’ve received the survey in the mail and to fill it out.• Then the researchers would ask respondents about how they filled it out, and let them ask
questions about anything they found confusing.– A mail pretest might be conducted.– This process is continued until a survey is developed that people seem to understand
and answer in a way that makes sense and reveals their values for the services of the site
Discrete Choice MethodDiscrete Choice MethodIllustrationIllustration
Step 4• Survey implementation
– Select the survey sample• Randomly selected sample from a mailing list of randomly sampled U.S.
citizens– Use a standard repeat-mailing and reminder method, in order to
get the greatest possible response rate for the survey
Step 5• Compile, analyze and report the results
– The statistical analysis for contingent choice is often more complicated than that for contingent valuation
• requiring the use of discrete choice analysis methods to infer willingness to pay from the tradeoffs made by respondents.
Discrete Choice MethodDiscrete Choice MethodIllustrationIllustration
Step 5 (cont’d)• Estimate the average value for each of the services of the site, for
an individual or household • Extrapolate to the relevant population in order to calculate the total
benefits from the site under different policy scenarios• The average value for a specific action and its outcomes can also be
estimated, or the different policy options can be ranked in terms of peoples’ preferences
• The results of the survey might show that– the economic benefits of preserving the site by not allowing mining are
greater than the benefits received from allowing mining• the mining lease might not be issued, unless other factors override these results
– the results might indicate that some mining scenarios are acceptable, in terms of economic costs and benefits
• rank different options and select the most preferred option
Discrete Choice MethodDiscrete Choice MethodSummarySummary
• Whatever format is selected,– choices that respondents make are
statistically analyzed using discrete choice statistical techniques, to determine the relative values for the different characteristics or attributes
– If one of the characteristics is a monetary price, then it is possible to compute the respondent’s willingness to pay for the other characteristics.
Discrete Choice MethodDiscrete Choice MethodSummarySummary
• A good contingent choice study will consider the following:
– Before designing the survey, learn as much as possible about how people think about the good or service in question
• Consider people’s familiarity with the good or service, as well as the importance of such factors as quality, quantity, accessibility, the availability of substitutes, and the reversibility of the change.
– Determine the extent of the affected populations or markets for the good or service in question, and choose the survey sample based on the appropriate population.
– The choice scenario must provide an accurate and clear description of the change in environmental services associated with the event, program, investment, or policy choice under consideration
• iI possible, convey this information using photographs, videos, or other multi-media techniques, as well as written and verbal descriptions
Discrete Choice MethodDiscrete Choice MethodSummarySummary
• A good contingent choice study will consider the following:
– The nature of the good and the changes to be valued must be specified in detail, and it is important to make sure that respondents do not inadvertently assume that one or more related improvements are included
– The respondent must believe that if the money was paid, whoever was collecting it could effect the specified environmental change
– Respondents should be reminded to consider their budget constraints – Specify whether comparable services are available from other sources,
when the good is going to be provided, and whether the losses or gains are temporary or permanent
– Respondents should understand • the frequency of payments required, for example monthly or annually,• whether or not the payments will be required over a long period of time in order to
maintain the quantity or quality change• who would have access to the good and who else will pay for it, if it is provided
Discrete Choice MethodDiscrete Choice MethodSummarySummary
• A good contingent choice study will consider the following– In the case of collectively held goods, respondents should
understand that they are currently paying for a given level of supply. The scenario should clearly indicate whether the levels being valued are improvements over the status quo, or potential declines in the absence of sufficient payments.
– If the household is the unit of analysis, the reference income should be the household’s, rather than the respondent’s, income
– Thoroughly pre-test the questionnaire for potential biases• test different ways of asking the same question• test whether the question is sensitive to changes in the description of
the good or resource being valued– Conduct post-survey interviews to determine whether
respondents are stating their values as expected.– Include validation questions in the survey
• to verify comprehension and acceptance of the scenario• to elicit socioeconomic and attitudinal characteristics of respondents
Discrete Choice MethodDiscrete Choice MethodAdvantages (1)Advantages (1)
• Can be used to value the outcomes of an action as a whole, as well as the various attributes or effects of the action
• it does not ask the respondent to make a tradeoff directly between environmental quality and money– the tradeoff process may encourage respondent introspection
and make it easier to check for consistency of responses.– respondents may be able to give more meaningful answers to
questions about their behavior (i.e. they prefer one alternativeover another), than to questions that ask them directly about the dollar value of a good or service or the value of changes in environmental quality
• Respondents are generally more comfortable providing qualitative rankings or ratings of attribute bundles that include prices, rather than dollar valuation of the same bundles without prices
Discrete Choice MethodDiscrete Choice MethodAdvantages (2)Advantages (2)
• Even if the absolute dollar values estimated are not precise, the relative values or priorities elicited by a contingent choice survey are likely to be valid and useful for policy decisions
• Minimizes many of the biases that can arise in open-ended contingent valuation studies where respondents are presented with the unfamiliar and often unrealistic task of putting prices on non-market amenities
• Has the potential to reduce problems such as expressions of symbolic values, protest bids, and some of the other sources of potential bias associated with contingent valuation
Discrete Choice MethodDiscrete Choice MethodIssues and LimitationsIssues and Limitations
• Respondents may find some tradeoffs difficult to evaluate, because they are unfamiliar
• The respondents’ behavior underlying the results of a contingent choice study is not well understood.
– Respondents may resort to simplified decision rules if the choices are too complicated, which can bias the results of the statistical analysis.
• If the number of attributes or levels of attributes is increased, the sample size and/or number of comparisons each respondent makes must be increased
• When presented with a large number of tradeoff questions, respondents may lose interest or become frustrated
• Contingent choice may extract preferences in the form of attitudes instead of behavior intentions
• By only providing a limited number of options, it may force respondents to make choices that they would not voluntarily make
• Contingent ranking requires more sophisticated statistical techniques to estimate willingness to pay.
• Translating the answers into dollar values, may lead to greater uncertainty in the actual value that is placed on the good or service of interest.
• Validity and reliability for valuing non-market commodities is largely untested.
Discrete Choice MethodDiscrete Choice MethodCaseCase--StudiesStudies
Discrete Choice MethodDiscrete Choice MethodCaseCase--study 1*study 1*-- Landfill Siting in Rhode IslandLandfill Siting in Rhode Island
Background• With its primary landfill nearing capacity, the State of Rhode Island
was faced with the need to choose locations for new landfills• Besides technical considerations, the State wanted to address the
social and economic tradeoffs and values related to the location of a landfill to avoid some of the controversy associated with landfill siting
Analysis• A contingent choice, paired comparison, survey was conducted
– The survey asked Rhode Island residents to choose between pairs of hypothetical sites and locations for a new landfill, described in terms of their characteristics
– The site comparisons described • the natural resources that would be lost on a hypothetical 500 acre landfill site• area surrounding the landfill
– Each comparison gave the cost per household for locating a landfill at each hypothetical site or location
*www.ecosystemvaluation.org
Discrete Choice MethodDiscrete Choice MethodCaseCase--study 1study 1-- Landfill Siting in Rhode IslandLandfill Siting in Rhode Island
Results• Used by the State to predict how residents would
vote in a referendum on different possible landfill locations– First, 59 possible sites were selected, based on
geological and public health criteria.• sites were ranked using the contingent choice survey results,
in order to come up with a short list of potential sites
• The final decision, based on geological, public health, public preferences, and political considerations, was to expand the existing landfill site
Discrete Choice MethodDiscrete Choice MethodCaseCase--study 2*study 2*-- Management of the Peconic Estuary Management of the Peconic Estuary
SystemSystemBackground• The environmental and natural resources of the Peconic
Estuary System provide many services to the public– the bay waters, beaches, wetlands, ecosystems, habitats, and
parks and watershed lands
• The Peconic Estuary Program – established under the National Estuary Program– Responsible for creating a conservation and
management plan for the environment and naturalresources of the Estuary
• Information was needed about the value that the public holds for the ecosystem services of the Estuary.
*www.ecosystemvaluation.org
Discrete Choice MethodDiscrete Choice MethodCaseCase--study 2study 2-- Management of the Peconic Estuary Management of the Peconic Estuary
SystemSystem
Analysis• Contingent choice survey to estimate the relative
preferences and economic values that residents and second homeowners have for preserving and restoring key natural and environmental resources– Open space– Farmland– Unpolluted shellfish grounds– Eelgrass beds– Intertidal salt marsh.
Discrete Choice MethodDiscrete Choice MethodCaseCase--study 2study 2-- Management of the Peconic Estuary Management of the Peconic Estuary
SystemSystemResults• The public has a strong attachment to environmental and amenity resources
of the Peconic Estuary, even if they do not use these resources directly• 97 percent of the respondents supported at least one hypothetical action to
protect resources, and indicated they would financially support such actions
• The survey results indicated that the resource priorities, or relative values of resources, are more reliable than are the dollar estimates of values,
– researchers recommended that relative values, rather than dollar values, be used in the process of selecting management actions.
Relative priorities for protecting natural resources
Per acre dollar values
Farmland $70 thousand Eelgrass $66 thousand Wetlands $54 thousand Shellfish $30 thousandUndeveloped land $13 thousand
Discrete Choice MethodDiscrete Choice MethodCaseCase--study 3*: Environmental Cost of Low River study 3*: Environmental Cost of Low River
Flows Flows
Background• South-west of England
encompasses– 176 beaches– 4,000 miles of rivers
• Abstraction for hydro-electric power stations
• Water imponded by reservoirs
• Abstraction by water companies from river or underlying aquifer
http://www.cornerwaysresidentialhome.co.uk/tavistock16.jpg
Low water flow
* Garrod and Willis, 2001
Discrete Choice MethodDiscrete Choice MethodCaseCase--study 3: Environmental Cost of Low River Flows study 3: Environmental Cost of Low River Flows
Background• Benefits of increased river flows comprise both use values
and non-use valuesExpressed preference approach most appropriate to elicit WTP
• Survey of general public will comprise a large proportion of non-users
Lack of familiarity makes it difficult to answer open-ended questions
• Choice experiment approach with the aim of estimating the marginal WTP of the general public for – unit improvements in low flow alleviation in rivers in south west
of England – unit improvements in the numbers of clean beaches in the area– unit improvements in the miles of unpolluted rivers in the area
Discrete Choice MethodDiscrete Choice MethodCaseCase--study 3: Environmental Cost of Low River Flows study 3: Environmental Cost of Low River Flows
Definitions• Non-use value arises from the knowledge
that the river remains healthy and viable and will persist
• Non-users were identified as those respondents who did not visit any of the flow rivers in the south west specified in the project
Discrete Choice MethodDiscrete Choice MethodCaseCase--study 3: Environmental Cost of Low River Flows study 3: Environmental Cost of Low River Flows
Questionnaire design• Series of focus groups undertaken
– Suggested that the public considered coastal and river pollutionto be most pressing problems in the south west
– When shown photographs, agreed that low flow was also important but not as pressing
• To obtain conservative welfare estimates that can be interpreted as lower-bound figures– A series of questions and statements reminded respondents of
other environmental issues that they might wish to support
• To introduce the notion of a multigood environment– Respondents asked about their donations to good causes and
their willingness to contribute more to these causes– Tested and refined over two separate pilot surveys
Discrete Choice MethodDiscrete Choice MethodCaseCase--study 3: Environmental Cost of Low River Flows study 3: Environmental Cost of Low River Flows
Questionnaire design• Respondents presented with a brochure
– Describing the Environmental Agency’s (EA) activities• Reducing river pollution• Monitoring marine pollution in coastal waters• Improving flows in low flow rivers
– Text kept to a minimum and illustrations used– Information limited to bullet points describing
• The problems being tackled• The causes and consequences• How EA was tackling the problem including the amount spent on a per
household• How much improvement has been achieved till now
• Survey sample limited to the south west where respondents relate better to familiar local issues
Discrete Choice MethodDiscrete Choice MethodCaseCase--study 3: Environmental Cost of Low River Flows study 3: Environmental Cost of Low River Flows
Questionnaire design• Survey used both
– Stated preference choice experiment– Dichotomous choice contingent valuation question
• Valuation scenario used– Whether or not respondents were willing to pay a specified amount to
increase the overall levels of environmental quality along rivers and beaches in the south west
• Environmental quality expressed as the level of three attributes
• In choice experiments, cards chosen randomly from an orthogonal set of 64 choice cards– Respondents given a card and asked to choose one of three choices– Then given three cards and asked to choose their preferred choice from
each
• Low flow embedded within a more holistic set of EA water qualityobjectives
Discrete Choice MethodDiscrete Choice MethodCaseCase--study 3: Environmental Cost of Low River Flows study 3: Environmental Cost of Low River Flows
Questionnaire design• Example of a choice experiment card:
CARD 06Please choose one column
CHOICE 1(current situation)
CHOICE 2 CHOICE 3
Increase in water charges needed to achieve targets
No increase £5 increase £10 increase
Beaches in the South West NOT MEETING European standards on cleanliness
9 beaches 5 beaches 3 beaches
Rivers in the South West WITHOUTgood quality water
990 miles 350 miles 350 miles
Rivers in the South West WITHOUTacceptable flow levels
130 miles 80 miles 60 miles
Discrete Choice MethodDiscrete Choice MethodCaseCase--study 3: Environmental Cost of Low River Flows study 3: Environmental Cost of Low River Flows
Empirical results• River usage by the general public
– Distance from rivers• Half the interviewed households live one mile or less from a
river• More than two-thirds lived within 2 miles of a river
– Recreational activities• 77 % of household regularly undertook recreational activities
along rivers• 88 % of the households had visited more than one river over the
past 12 months• Frequency of visits to beaches had the same frequency as visits
to rivers during the summer season
Discrete Choice MethodDiscrete Choice MethodCaseCase--study 3: Environmental Cost of Low River Flows study 3: Environmental Cost of Low River Flows
Empirical results• Public perception
– ¾ of respondents thought that rivers were an important source of water
– ½ thought too much water is being abstracted from rivers
• Public WTP for good causes– 80% prefer to see additional public expenditure
on the nature environment– 40% were willing to contribute more towards
‘good causes’
Discrete Choice MethodDiscrete Choice MethodCaseCase--study 3: Environmental Cost of Low River Flows study 3: Environmental Cost of Low River Flows
Empirical results• Responses from choice experiments used to
estimate discrete choice model of the probability Pr(i) of choosing a given alternative I
Pr(i) = exp (sVi)/Σexp(sVj)• Models were estimated using
– linear functional form• Used mainly for benefit estimation
– quadratic functional form• Some attribute coefficients were not statistically significant
– Coefficient values and t-statistics for various variables were estimated
Discrete Choice MethodDiscrete Choice MethodCaseCase--study 3: Environmental Cost of Low River Flows study 3: Environmental Cost of Low River Flows
Reduction Basic specification Extended specification
1 polluted beach £1.307 £1.431
1 mile of polluted river £0.017 £0.019
1 mile of low flow river £0.052 £0.058
Results
Discrete Choice MethodDiscrete Choice MethodCaseCase--study 3: Environmental Cost of Low River Flows study 3: Environmental Cost of Low River Flows
• Median welfare estimates for CVM scenarios
• Estimated using same models• Estimation involves
– an examination of how utility levels change as a result of a specified improvement
– calculating the magnitude of the associated increase in water charges that would be required to make the utility the same before and after the improvements
Model Annual welfare measure
Basic specifications £12.80
Extended specifications £15.36
Results
Discrete Choice MethodDiscrete Choice MethodCaseCase--study 3: Environmental Cost of Low River Flows study 3: Environmental Cost of Low River Flows
User and non-user populations for low-flow rivers from the south west
• The population of users:– all households who had visited a given low flow river in the two-year
period immediately preceding the survey• Nearly 45% of households in the south west are users
– Rivers are linear features– All rivers located in areas with scenic attractions
River User Households Non-user households
Miles affected by low flows
Allen 85,897 1,562,533 20Upper Avon 230,717 1,417,713 35Meavy 166,760 1,481,670 7Otter 157,982 1,490,448 5Piddle 157,854 1,490,576 16Tavvy 240,155 1,408,275 16Wylye 162,481 1,485,949 30
Results
Discrete Choice MethodDiscrete Choice MethodCaseCase--study 3: Environmental Cost of Low River Flows study 3: Environmental Cost of Low River Flows
Approximate aggregate annual benefits for improving low flows across the entire length of all low flow rivers in the south west
River Aggregate benefits for user Households
Aggregate benefits for visitor households
Aggregate benefits for non-user households
Allen £1,115,925 £130,563 £795,414
Upper Avon £1,952,868 £613,707 £1,391,975
Meavy £390,574 £88,716 £278,395
Otter £278,981 £60,033 £198,854
Piddle £892,740 £191,950 £636,331
Tavvy £892,740 £292,028 £636,331
Wylye £1,673,887 £370,457 £1,193,121
734,161 low-flow river users × length of river affected by low flow × £0.076 per mile
Results
Discrete Choice MethodDiscrete Choice MethodCaseCase--study 3: Environmental Cost of Low River Flows study 3: Environmental Cost of Low River Flows
• The costs of the cheapest available options for low flow alleviation estimated by ERM for each river
• Present value of the benefits of low flow alleviation estimated for the user sub-sample– Calculated by assuming a constant flow of benefits for the period
1997 to 2017 and discounting at 6%• Benefits exceeded costs by a wide margin
– Avon, Meavy, Wylye• Costs prohibitive on Otter• Benefits and costs similar for Allen
• Benefits based only on user samples and ignore benefits to non-users but include non-use benefits for low flow river visitors who do not visit the river in question
Results
Discrete Choice MethodDiscrete Choice MethodCaseCase--study 3: Environmental Cost of Low River Flows study 3: Environmental Cost of Low River Flows
Net present value of aggregate benefits for improving low flows across the entire length of all low flow rivers in the south west
River Present value of costs
Present value of aggregate user benefits
Net present value Benefit-cost ratio
Allen 11,867,000 13,915,000 2,048,000 1.17
Upper Avon 763,000 24,252,000 23,589,000 31.92
Meavy 80,000 4,870,000 4,790,000 60.88
Otter 34,430,000 3,480,000 -30,950,000 0.10
Piddle 5,471,000 11,132,000 5,661,000 2.03
Tavvy Unknown 11,132,000 - -
Wylye 224,000 20,873,000 20,649,000 93.18
Annual stream of costs and benefits discounted at 6% between 1997 and 2017
Results
Discrete Choice MethodDiscrete Choice MethodCaseCase--study 4*: Recreational Choice and Water study 4*: Recreational Choice and Water
QualityQuality
• Case study by Alberta Environment
• A combination of– Stated preference choice
experiment– Revealed preference
approach
• Choice experiment– Three options related to choice of
recreational activities• Recreation at standing water site• Recreation at running water site• Recreation at non-water site
* Garrod and Willis, 2001
Discrete Choice MethodDiscrete Choice MethodCaseCase--study 4: Recreational Choice and Water Qualitystudy 4: Recreational Choice and Water Quality
• Water-based recreation described using various attributes– Travel distance to reach the site– Water quality
• Presented as either good or bad– Terrain– Camping facilities– Presence of beach– Various attributes related to fishing
and other recreational activities
• Attributes of standing and running water alternatives– Treated as a collective factorial– An orthogonal main effects design
chosen which would vary all attribute levels simultaneously
http://www.hickerphoto.com/data/media/11/travel_alberta_T3258.jpg
http://www3.nationalgeographic.com/places/images/photos/photo_lg_alberta.jpg
Discrete Choice MethodDiscrete Choice MethodCaseCase--study 4: Recreational Choice and Water Qualitystudy 4: Recreational Choice and Water Quality
Recreational attributes offered in stated preference choice cardsAttribute Description Attribute Description
Fish size LargeSmall
Fish species
Still: Pike & PerchPickerel, Pike & Perch
Running: Mountain whitefishRainbow trout & Mountain whitefishRainbow trout, Mountain whitefish & Brown troutCutthroat trout, Mountain whitefish & Bull trout
Fish catch rate
1 fish per 4 hrs1 fish per 80 mins1 fish per 45 mins1 fish per 35 mins
Terrain Flat prairieRolling PrairieFoothillsMountains
Distance to site
25 km50 km100 km150 km
Facilities NoneDay-use onlyLimited facilities campsiteFully serviced campsite
Boating Still: NoneSmall craftsPower boats (limited)Unrestricted
Running: None
Swimming YesNo
Water feature
Still: Natural lakeReservoir
Running: RiverStream
Discrete Choice MethodDiscrete Choice MethodCaseCase--study 4: Recreational Choice and Water Qualitystudy 4: Recreational Choice and Water Quality
• Data collected using a telephone survey conducted by Alberta Environment– Respondents asked to participate in choice
experiment– Respondents asked to provide information to
be used in revealed preference model• 730 separate recreational trips in August 1991• Destinations characterized by the attributes under
study
Discrete Choice MethodDiscrete Choice MethodCaseCase--study 4: Recreational Choice and Water Qualitystudy 4: Recreational Choice and Water Quality
• Selected attribute coefficient values from choice experiment model
Attribute Standing water Running water
Distance(km)
-0.007(0.0004)
0.007(0.0004)
Catch rate(fish per unit time)
0.062(0.028)
0.105(0.026)
Fish size(large=1 vs. small=-1)
0.058(0.028)
0.090(0.0250
Water quality(good=1 vs. bad=-1)
0.394(0.027)
0.321(0.025)
Swimming(yes=1 vs. no=-1)
0.274(0.026)
0.158(0.025)
Beach(yes=1 vs. no=-1)
0.198(0.026)
0.123(0.024)
Boating N/A N/A
Discrete Choice MethodDiscrete Choice MethodCaseCase--study 4: Recreational Choice and Water Qualitystudy 4: Recreational Choice and Water Quality
• Empirical results (Choice Experiment)– Multinomial logit discrete choice model
• All parameters except distance estimated as interaction terms associated with standing or running water
– Model fit the observed data– Model has parameters with coefficients consistent with authors’
expectations– Factors with positive influence on utility
• Larger fish• Good water quality• Increased catch rates• Availability of swimming• Presence of beaches
– Respondents preferred upland topography to prairie– Respondents preferred higher diversity to fewer species of fish
• Most popular package: rainbow trout, mountain whitefish, and brown trout– Respondents preferred fully-serviced campsites– Differences noted between estimated coefficient values for parameters
between running water and standing water sites• Increased fish sites and catch rates preferred more in running water
Discrete Choice MethodDiscrete Choice MethodCaseCase--study 4: Recreational Choice and Water Qualitystudy 4: Recreational Choice and Water Quality
• Selected attribute coefficient values from revealed preference modelAttribute Standing water Running water
Distance(km)
-0.0282(0.001)
-0.0282(0.001)
Catch rate(fish per unit time)
2.0338(0.237)
2.0338(0.237)
Fish size N/A N/A
Water quality(poor=1 vs. good=0)
-0.8197(0.494)
-3.129(0.3749)
Swimming(yes=1 vs. no=0)
2.7477(0.290)
0.9148(0.251)
Beach(yes=1 vs. no=0)
0.9918(0.302)
-1.955(0.369)
Boating(unrestricted=1 vs. none=0
6.6620(1.024)
1.7335(0.289)
Discrete Choice MethodDiscrete Choice MethodCaseCase--study 4: Recreational Choice and Water Qualitystudy 4: Recreational Choice and Water Quality
• Empirical results (Revealed preference model)– Multinomial discrete choice model estimated for the site
choice decision• Travel cost and site attributes used to explain site choices
– Significant factors in explaining site choice include• Distance to be travelled• Water quality• Catch rates• Availability of swimming, fishing, and boating
• A joint version of the choice experiment and revealed preference was conducted– Data used from both models– Allows to improve quality of the estimates based on
revealed preference• Reduces collinearity
EEnd of nd of SSession ession 10a10a
Thank YouThank You
REGIONAL WORKSHOP REGIONAL WORKSHOP ONON
THE COST OF THE COST OF ENVIRONMENTAL ENVIRONMENTAL
DEGRADATION DEGRADATION METHODOLOGYMETHODOLOGY
Session 10bTHE BENEFIT TRANSFER
METHOD
REGIONAL WORKSHOP ONREGIONAL WORKSHOP ON
THE COST OF ENVIRONMENTAL THE COST OF ENVIRONMENTAL DEGRADATION METHODOLOGYDEGRADATION METHODOLOGY
Session 10bTHE BENEFIT TRANSFER METHOD
Benefit Transfer MethodBenefit Transfer MethodOUTLINEOUTLINE
• Overview• Methodology• Application• Illustration• Advantages• Issues and limitations• Case-applications• Case-study
Benefit TransferBenefit TransferOverviewOverview
• Represents another alternative for obtaining non-market values• Involves transferring values that have been estimated for a similar
good or service from another location/context to the current location/context– Estimating benefits for one context by adapting an estimate of benefits
from some other context• Represents a useful method under
– Budget constraints– Time constraints
• Has been applied to value the impact of improved water quality on– Recreation values– Public health
• Has been the normal procedure adopted in regulatory command and control mechanisms in which common standards are applied– EU assumes that benefits of environmental improvement are of equal
value in different areas of the EU• Benefit transfers can only be as accurate as the initial study
Benefit TransferBenefit TransferOverviewOverview
• The simplest type of benefit transfer is the unit day approach– existing values for activity days are used to value the same activity at
other sites– estimates are based on expert judgment in combining and averaging
benefit estimates from a number of existing studies– “unit day values” may be adjusted for characteristics of the study site
when they are applied.
• A more rigorous approach involves transferring a benefit function from another study– The benefit function statistically relates peoples’ willingness to pay to
characteristics of the ecosystem and the people whose values were elicited
– adjustments can be made for differences in these characteristics, thus allowing for more precision in transferring benefit estimates between contexts
Benefit TransferBenefit TransferMethodologyMethodology
• Approaches for applying benefit transfer and assessing the validity of the attempts– The ‘unit day value’ applied by the US Forest Service in the 70s and
80s• Federal guidelines in 1982 recommended
– $6.10-$17.90 per day for specialized recreation» Wilderness use, trout fishing, big-game hunting, white water boating
– $1.50-$4.50 per day for general recreation» Picnicking, swimming, small game hunting, camping, boating
• When applied to a new site, unit day values are adjusted on the basis of the demand functions of site-visitors
• Demand depends on site attributes such as– Congestion– Accessibility and parking conditions– Environmental quality; scenery, pests, water, air, climate– Socio-economic characteristics of recreationalists– Preferences– Price– Availability of substitute sites
• None of these factors will be identical across different sites• Expert judgment is required to assess what the benefits of a new site might be from a
range of possible values• Unit day values can be updated to account for
– Inflation– Observed changes in price and income elasticities for recreation over time
Benefit TransferBenefit TransferMethodologyMethodology
• Approaches for applying benefit transfer and assessing the validity of the attempts– Real-estate agents’ judgments
• To estimate utility loss associated with noise from the proposed airport site
• Some research suggested close correlation between estate agents’ estimates of total house price and estimates derived from an hedonic price model
• Other research revealed discrepancies
Benefit TransferBenefit TransferMethodologyMethodology
• Approaches for applying benefit transfer and assessing the validity of the attempts– Via TCM
• By transferring demand functions from existing facilities, resembling closely the prospective facility in the type of recreation provided
• If the catchment areas of the two sites are mutually exclusive– Existing site coefficients × values for independent variables of the
new site = estimates of number of visits and benefits attributable to the new site
– This approach expected to yield more accurate results than simply applying an average value of benefit per visitor day to the site
• If proposed facility situated within the catchment area of an existing facility
– Apply existing demand function to the new site as if unique– If new consumer surplus exceeds the existing one, the net gain
from having the new facility is the difference between the two
Benefit TransferBenefit TransferMethodologyMethodology
• Approaches for applying benefit transfer and assessing the validity of the attempts– Via TCM (cont’d)
• The lack of homogeneity in product mix may be remedied by valuing the different recreational activities separately and then aggregating, rather than developing a demand curve for the site as a whole
• Errors in BT via TCM– Choosing the wrong functional form– Selecting an incomplete or inappropriate set of arguments– Measuring arguments incorrectly
» Value of time, income, cost of access– Measuring the dependent variable with error– The presence of substitute sites
» Could be cancelled out if sites are randomly distributed via a simulation models
Benefit TransferBenefit TransferMethodologyMethodology
• Approaches for applying benefit transfer and assessing the validity of the attempts– Via CVM
• Application can be affected by– Ex ante- Ex post valuation perspective
» Some estimates elicited after the uncertainty about the good is removed are employed in an ex ante project appraisal
– Scale or quantity value» If the new good or policy is identical to the old and lies within the
same market area, then it represents an additional quantity of the good and should be valued less than the existing good at the site
– Sequential position of the supply of the good» Where goods are complements or substitutes, the sequence in
which a particular good is provided in relation to others determines its value
– Differences in attributes– Compositional effects
» When respondents have difficulty in disentangling the structure of the substitution and complementary interrelationships among attributes within the same holistic set
Benefit TransferBenefit TransferMethodologyMethodology
• Approaches for applying benefit transfer and assessing the validity of the attempts– Meta-analysis
• Uses data-based aids to explain variations in estimated benefits across different studies with the aim of applying past results to future resource policy decisions
• Attempts to assess environmental values by investigating the relationship between
– benefit estimates (WTP) – the features of the goods– the assumptions of the models
• Entails the systematic application of statistical methods to assess common features and variations across a wide range of prior studies
• Undertaken using a variety of techniques encompassing qualitative and quantitative econometric methods
• Relatively underdeveloped in the field of benefit transfer• Important as a means of investigating the factors and issues
involved in the derivation and construction of values
Benefit TransferBenefit TransferMethodologyMethodology
• Meta-analysis (illustration)– Study by Walsh et al. (1989) to explain variations in
net economic benefits per activity day in terms of site, location, and methodological variables
– 287 benefit estimates compared• 156 based on TCM• 129 based on CVMs• 2 based on HPMs
– Some main findings• Omitting travel time in TCM studies reduced benefit
estimates by 34%• ITCM estimates were about 46% greater than ZTCM
estimates using the same functional form• If TCM accepted as the standard for benefit estimation, then
CV estimates needed to be adjusted upwards by 20-30%
Benefit TransferBenefit TransferMethodologyMethodology
• Different standards for benefit transfer may be applied in different contexts– a higher standard of accuracy may be required when the costs of
making a poor decision are higher– a lower standard of accuracy may be acceptable when costs are lower
• when the information from the benefit transfer is only one of a number of sources of information, or when it is used as a screening tool for the early stages of a policy analysis.
• The benefit transfer method is most reliable– when the original site and the study site are very similar in terms of
• quality, location, and population characteristics– when the goods/services in both sites have similar characteristics– when the original valuation study has been carefully conducted and
used sound valuation techniques– when values in original study have not been valuated a long time ago
since preferences change over time
Benefit TransferBenefit TransferMethodologyMethodology
• Three tests have been suggested to determine the accuracy of benefit transfer
– Comparing benefit transfer values with primary data values obtained from the policy site
– Determining whether different populations have the same preferences for the same non-market good, after controlling for differences in socio-economic characteristics
– Determining whether transfers are stable over time
Benefit TransferBenefit TransferApplicationApplication
1. Identify existing studies or values that can be used for the transfer– There are a number of valuation databases that can be
useful2. Evaluate the existing values to determine whether they
are appropriately transferable– Consider whether:
• the service being valued is comparable to the service valued in the existing studies
– Site features– Site qualities– Availability of substitutes.
• the characteristics of the relevant population are comparable– Demographics– Peoples’ preferences
Benefit TransferBenefit TransferApplicationApplication
3. Evaluate the quality of studies to be transferred– The better the quality of the initial study, the more accurate and
useful the transferred value will be– Requires professional judgment of the researcher
4. Adjust the existing values to better reflect the values for the site under consideration, using available and relevant information
– Supplemental data may need to be collected • survey key informants• talk to the investigators of the original studies• get the original data sets• collect some primary data at the study site to use to make
adjustments5. Estimate the total value by multiplying the transferred values
by the number of affected people
Benefit TransferBenefit TransferIllustration*Illustration*
Background• A park being upgraded to provide
additional recreational opportunities– A proposal is to add a swimming beach
to the lake– The benefits of the new beach needs to
be explored – Limited budget for valuation study
• Benefit Transfer Method preferred because – No large budget available for site-
specific benefits studies– Values for recreational uses are
relatively easy to transfer
*www.ecosystemvaluation.org
http://www.inetours.com/England/London/images/Parks/Hyde/Hyde_Park_9466.jpg
Benefit TransferBenefit TransferIllustrationIllustration
Methodology• Step 1
– Identify existing studies or values that can be used for the transfer– Look for studies that value beach use, specifically for lake beaches if
possible• Assume that the researcher has found two travel cost studies that estimated
values for swimming at lake beaches
• Step 2– Decide whether the existing values are transferable by examining
various criteria– The existing values or studies would be evaluated based on several
criteria, including: • Is the service being valued comparable to the service valued in the existing
studies?– similar types of sites (e.g., lake beaches in a park)– similar quality of sites (e.g., water quality and facilities)– similar availability of substitutes (e.g., the number of other lake beaches nearby)
• Are characteristics of the relevant population comparable?– are demographics similar – if not, are data available to make adjustments
Benefit TransferBenefit TransferIllustrationIllustration
Methodology (cont’d)• Step 2 (cont’d)
– In the example, the first study is for a similar lake beach• The beach is also in a park, has comparable water quality and facilities,
and a similar number of substitute sites in the area• It is located in an urban area, while the beach being valued is in a rural
area– The characteristics of visitors can be expected to be different for the two sites
– The second study is in a rural area with similar types of visitors, but the lake has many more available substitutes.
• Step 3: – Evaluate the quality of studies to be transferred
• In this example, the researcher has decided that both studies are acceptable in terms of quality
Benefit TransferBenefit TransferIllustrationIllustration
Methodology (cont’d)• Step 4• Adjust the existing values to better reflect the values for the site
under consideration– In this case, the sites valued in each of the existing studies differ from
the site of interest• The researcher might adjust the values from the first study by applying
demographic data to adjust for the differences in users• If the second study has a benefit function that includes the number of substitute
sites, the function could be adjusted to reflect the different number of substitutes available at the site of interest
• Because the beach will be new, the researcher will need to estimate how many people will use the beach– Survey of park visitors, asking whether they would use a beach on the
lake, and how many times they would use it– Then multiply these visitation estimates by the value per day for beach
use (adjusted for differences in population and site characteristics), to get an estimate of the economic benefits for the new beach
Benefit TransferBenefit TransferAdvantagesAdvantages
• Less costly than conducting an original valuation study
• Economic benefits estimated faster than when undertaking an original valuation study
• Can be used as a screening technique to determine if a more detailed, original valuation study should be conducted
• The method can easily and quickly be applied for making gross estimates of recreational values– The more similar the sites and the recreational
experiences, the fewer biases will result.
Benefit TransferBenefit TransferIssues and LimitationsIssues and Limitations
• Lack of accuracy, except for making gross estimates of recreational values, unless the sites share all of the site, location, and user specific characteristics
• Unavailability of good studies for the policy or issue in question• Difficulty in finding appropriate studies, since many are not
published• Reporting of existing studies may be inadequate to make the
needed adjustments• Difficulty in assessing the adequacy of existing studies• Extrapolation beyond the range of characteristics of the initial study
is not recommended• Benefit transfers can only be as accurate as the initial value
estimate• Unit value estimates can quickly become dated
http://www.duckboats.net/images/poison13.jpg
Benefit TransferBenefit TransferCaseCase--application 1*: application 1*: Wetlands Wetlands
Restoration in Saginaw Bay, Michigan Restoration in Saginaw Bay, Michigan
Background• The State of Michigan is considering plans
to protect and restore coastal wetlands along the southern shore of Saginaw Bay
• The State must estimate the potential benefits from protecting and restoring the wetlands
• A survey asked people about their support for restoring wetlands, but did not include a valuation question
• The researchers used benefit transfer methods to estimate the value of protecting and restoring wetlands around the Bay
www.fws.gov/midwest/alpena/images/sagbay.jpg
*www.ecosystemvaluation.org
Benefit TransferBenefit TransferCaseCase--application 1: application 1: Wetlands Restoration Wetlands Restoration
in Saginaw Bay, Michigan in Saginaw Bay, Michigan Methodology• A valuation study for proposed wetlands protection and restoration
of Ohio’s Lake Erie coastal wetlands was used for the benefit transfer
• Researchers assumed that the values estimated for Ohio were similar enough to be transferable to Michigan– The study valued similar programs and quantities of wetlands to those
proposed in Michigan– However, coastal residents were not surveyed
• the transfer of values from the Ohio study to coastal residents in Michigan requires the assumption that coastal residents have values similar to those of residents of other areas of the drainage basin
Results• Estimates of wetland values for Michigan, based on the Ohio study
– $500 - $9,000 per acre for residents of the drainage basin– $7,200 - $61,000 per acre for residents of the State of Michigan
Benefit TransferBenefit TransferCaseCase--application 2*: Benefits of Water application 2*: Benefits of Water
Pollution Controls on Pulp and Paper MillsPollution Controls on Pulp and Paper Mills
Background• The Clean Water Act provides standards for water quality that
affect the pulp and paper industry
• The industry must implement technological improvements to bring water quality up to standards
• Researchers attempted to assess the benefits of water quality improvements in a particular set of stream segments where pulp and paper mills discharge effluent
• This determines downstream water quality, which in turn affects benefits to recreational users of the streams, as well as non-use benefits from improved water quality.
*www.ecosystemvaluation.org
Benefit TransferBenefit TransferCaseCase--application 2: Benefits of Water application 2: Benefits of Water
Pollution Controls on Pulp and Paper MillsPollution Controls on Pulp and Paper MillsMethodology• Researchers used benefit transfer to estimate the economic benefits of
improved water quality– streams affected by 68 mills were selected for the study– data on existing water quality and pollution control costs for the streams was collected – feasible uses assigned for each stream, based on existing water quality
• The benefits transfer was based on three studies of other rivers that valued changes in water
– the Charles River in Boston– the Monongahela River in western Pennsylvania quality– Two were contingent valuation studies, and one was a travel cost study.
• Both recreational and non-use benefits were considered.
Results • Even using the upper bound estimate of benefits ($66 million), total
benefits for the 68 mills were only two-thirds of the costs to these mills ($95.5 million)
• The total costs to the entire pulp and paper industry were estimated at $310 million
BENEFIT TRANSFER METHODBENEFIT TRANSFER METHOD
Case studyCase studyTransferability of WTP estimatesTransferability of WTP estimates
Valuation of water quality improvements Valuation of water quality improvements in Jaco and Puntarenas along the Pacific in Jaco and Puntarenas along the Pacific
Coast of Costa Rica Coast of Costa Rica
Case DescriptionCase DescriptionStudy areaStudy area
• The study tests the transferability of WTP estimates of improvements in coastal water quality:– Between two urban areas: Jaco and
Puntarenas– Within Puntarenas between 3 city
districts: Centre, Chacarita and Baranca
• Jaco:– Small town in rural area (3000
inhabitants, 840 households)– Dedicated to sun and sea tourism
• Puntarenas:– Second largest airport (65500
inhabitants, 14770 households)– National tourist attraction
Case DescriptionCase DescriptionEcosystem deteriorationEcosystem deterioration
• Puntarenas:– Deteriorating water quality drove visitors to other beaches such as Jaco– In Baranca, a wastewater treatment plant was constructed in 1992
(6000 households) → saturation of available treatment capacity– Rest of City: septic tanks & direct outfalls
• Jaco:– Septic tanks & direct outfalls are used
• General problems:– Surface and groundwater pollution – High water tables– Frequent flooding of septic tanks in rainy season– Deterioration of local sanitary conditions
What is people’s WTP for improvements in coatsal water quality???
Are the estimates transferable between different areas?
Applied MethodApplied MethodContingent ValuationContingent Valuation
• In-person survey: 380 households in Jaco & 1049 in Puntarenas
• Presentation of maps showing– Current quality of sea water, river and estuarine water, and well and
groundwater– Water quality deterioration at the ‘without treatment’ scenario after 5
years– Water quality deterioration at the ‘with treatment’ scenario after 5 years
(new wastewater treatment plant + connection of all households to network)
• WTP question– Respondents were asked whether they would vote ‘for’ or ‘against’ a
wastewater treatment plan– If voting ‘for’, were asked if they would be WTP a monthly sewage fee to
the local water authority– If voting again ‘for’, a double-bounded WTP question was asked
Applied MethodApplied MethodDescription of water quality situation Description of water quality situation
& scenarios& scenarios
Puntarenas sample was divided to 2 subsamples:
1.Full improvement scenario: to highest improvement level2.Partial improvement scenario: river & estuarine water level 2, the rest to highest
levels (inefficiency in wastewater treatment in the proposed plant
Classification level used in showcards
Coastal water resources
Seawater (A-C)
River & estuarine water (1-3)
Well & groundwater (I-III)
Class A/1/I Fit for swimming all year
Fit for human contact all year
Potable well water: no faecal pollution in groundwater
Class B/2/II Fit for swimming dry season
Fit for human contact dry season
Potable well water: contamination risk from faecal pollution in surrounding groundwater
Class C/3/III Not fit for swimming all year
Not fit for human contact all year
Well water not potable: faecal pollution in groundwater
Current classification X: Jaco X: Puntarenas
X
X
X
X X X
Applied MethodApplied MethodBenefit transfer reliabilityBenefit transfer reliability
• Benefit transfer = the application of primary non-market valuation estimates to a secondary setting for which the original study was not expressly designed
• Estimates from the original ‘study site’ are applied to a target ‘policy site’ at a different time and/or place
• Four hypotheses were tested
H1.1 Unadjusted transfer: Benefits transferred are robust to differences in site characteristics
H1.2 Simple adjusted transfer: Values generated at the study site are identical to those at the policy site after adjustment for changes in consumer prices & average differences in income
H2 Benefit function adjusted transfer: The values generated with the coefficients of the WTP regression function estimated at the study site, & the policy site characteristics, are identical to the values that would be obtained from a primary study at the policy site
H3 Slope coefficients of benefit function: Estimated benefit functions at the policy site and study site are drawn from the same population
ResultsResultsWTP responsesWTP responses
The least conservative WTP estimates are 65% (Jaco) & 193% (Puntarenas) higher
than the most conservative estimates
Jaco Puntarenas
Population (hh) sample frame
840 14770
Sample size 380 1049
Sample non-response
83 (21%) 273 (26%)
Water quality scenario
Full improveme-nt
Full improveme-nt
Partial improveme-nt
Freq % Freq % Freq %
= sample response 297 100 398 100 378 100
- protest bids 13 4 6 2 3 1
- Incomplete/ do not know 3 1 16 4 13 3
= valid WTP reponses 281 95 376 94 362 96
- Zero WTP 18 6 25 6 22 6
= item responses (WTP>0)
263 89 351 88 340 90
Valuation approach Estimated WTP
Bid format*
Distribution assumption
Data treatment
Jaco sample Puntarenas pooled sample
Mean Median Mean Median
DC-DB Truncated normal
All zeros included
3085 2598 2347 1966
DC-DB Truncated normal
Only true zeros included
3080 2764 2382 2096
DC-DB Truncated normal
No zeros3089 2963 2404 2268
DC-DB Lognormal No zeros 3168 2557 2467 1918
DC-SB Lognormal No zeros 4789 3247 6617 3093
Sensitivity of WTP to responses treatmentSample sizes and response rates
*DC: dichotomous DB: double bounded SB: single bounded
ResultsResultsBenefit transfer Benefit transfer –– RuralRural--urban testsurban tests
• There are significant differences between the two sites• Full models indicated that socio-demographics mainly
explained WTP in Puntarenas, while sanitation, resource use & environmental attitudes were important in Jaco
Model Transfer error factor at policy site
Jaco Greater Puntarenas Absolute average transfer error %
No covariates -22.5%H1.1 rejected
29.0%H1.1 rejected 25.8
Income adjusted -10.4%H1.2 not rejected
11.7%H1.2 rejected 11.1
Socio-demographic covariates
-20.7%H2 rejectedH3 not rejected
28.1%H2 rejectedH3 not rejected
24.4
Full model covariates
-20.3%H2 rejectedH3 rejected
-1.6%H2 not rejectedH3 rejected
11.0
Note
Transfer error % = 100 (wp/s –ws/s) / Ws/s
Where W is the WTP estimate, p is the policy site, & s is the source site
Transfers are rejected when errors are in the range 11-26%
ResultsResultsBenefit transfer Benefit transfer –– IntraIntra--urban testsurban tests
• Unexpectedly! Absolute transfer errors have not been reduced by geographical proximity relative to the urban-rural transfer
• The simple income-adjusted method outperformed the more sophisticated methods
Model Transfer error factor at policy site
Jaco Greater Puntarenas Absolute average transfer error %
No covariates -22.8%H1.1 rejected
29.5%H1.1 rejected 26.2
Income adjusted -16.3%H1.2 rejected
19.5%H1.2 rejected 17.9
Socio-demographic covariates
-20.9%H2 rejectedH3 not rejected
29.1%H2 rejectedH3 not rejected
25.0
Full model covariates
-22.6%H2 rejectedH3 rejected
28.4%H2 not rejectedH3 rejected
25.5
Note
Transfer error % = 100 (wp/s –ws/s) / Ws/s
Where W is the WTP estimate, p is the policy site, & s is the source site
Transfers are rejected when errors are in the range 11-26%
ResultsResultsBenefit transfer Benefit transfer –– General remarksGeneral remarks
• Populations who have similar socio-demographic characteristics may be different while sanitation & recreation practices, environmental & institutional attitudes are considered
• Having information on socio-economic differences across sites e.g. census data may be a necessary but not sufficient condition for successful benefit transfer
• There are significant & differences in variables explaining WTP between different districts of the same area → very localised phenomena can play large role in determining WTP
EEnd of nd of SSession ession 10b10b
Thank YouThank You
REGIONAL WORKSHOP REGIONAL WORKSHOP ONON
THE COST OF THE COST OF ENVIRONMENTAL ENVIRONMENTAL
DEGRADATION DEGRADATION METHODOLOGYMETHODOLOGY
Session 11Stated Preference Approach
GROUP EXERCISES
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SESSION 11
GROUP EXERCISE 1
Air Quality Improvement Estimation and Assessment using Contingent Valuation Method: A Case Study in Beijing
(Wang et al., 2006)
Case description Beijing has been experiencing a rapid economic development, with a GDP growth rate of more than 9% per year since 1995, and a maximum of 10.2% in 1999. However, as a negative result of the rapid economic growth, Beijing’s environmental quality has deteriorated significantly, especially for air quality in the urban area. Because air pollution may impact many aspects of society, including human health, agriculture yield and industrial production, it is a difficult task to measure the benefit of air quality improvement. According to the Beijing Statistical Bureau, there are around 2,351,000 households in Beijing. The aim of the study is to estimate and assess residents’ willingness to pay to improve air quality in the urban area of Beijing using the Contingent Valuation Method (CVM). 1. Why is the CVM selected in this case? ___________________________________________________________________________
___________________________________________________________________________
2. What alternative method (s) could have been used and why? ___________________________________________________________________________
___________________________________________________________________________
3. Work through the steps of the CVM process to estimate the WTP to improve air quality in
Beijing.
A. Set up the hypothetical market (a convincing scenario, aids, …) ________________________________________________________________________
________________________________________________________________________
________________________________________________________________________
________________________________________________________________________
B. Obtain the bids
a. Select a method for obtaining a bid (income taxes, property taxes, value added or sales tax, utility bills, entry fees, payments into a trust fund)
________________________________________________________________________
________________________________________________________________________
________________________________________________________________________
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b. Select the type of questionnaire survey to be adopted (In-person survey, mail
survey, phone survey, etc.): ________________________________________________________________________
c. Types of information obtained
i. What are the various types of information to be obtained via the questionnaire? − _____________________________________________________________
− _____________________________________________________________
− _____________________________________________________________
ii. How can you help the interviewee understand the question, and reduce the tension
during the interview − _____________________________________________________________
iii. Would you use an open or close-ended question to elicit the WTP, and why?
− _____________________________________________________________
− _____________________________________________________________
iv. What wording would you use to elicit the WTP?
− What would your household be willing to pay annually during the next 5 years in order to fulfill the goal of air quality improvement in Beijing (reducing the concentration of air pollutants by 50% in urban areas)?
v. How would you convince the interviewee that his answer will influence the decision-making process − _____________________________________________________________
d. Sample size: Total sample size was 1,500 in 8 sampling districts. The number of households targeted in each of the eight districts was proportional to the household density of that district (the total number of households divided by the total area). Each district was divided into a number of communities according to the number of targeted households in it.
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Figure 1. Eight sampling districts in Beijing City
e. What is an important step in questionnaire development and administration?
_____________________________________________________________
f. How long in your opinion should the duration of the questionnaire be?
_____________________________________________________________________
C. Estimate the mean WTP/WTA
Willingness to pay for improving air quality in Beijing
WTP in RMB (in USD) /year # of interviewees Percentage (%)
0 460 33.6
≤ 10 (1.4) 65 4.7
11-50 (1.5-7.0) 161 11.7
51-100 (7.2-14.1) 302 22.0
101-500 (14.2-70.3) 331 24.1
501-1000 (70.4-140.5) 42 3.1
≥ 1001 (140.7) 10 0.7
Total 1371 100
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Statistical description of the willingness to pay WTP/year
Sample Mean in RMB
(in USD) SD
(RMB) Median (RMB)
Maximum (RMB)
N=1371 (whole) 143 (20.1) 346 50 7000
N=911 (positive) 215 (30.2) 406 100 7000
D. Aggregate WTP/WTA amount
____________________________________________________________
___________________________________________________________________________
___________________________________________________________________________
_________________________________________________________
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SESSION 11 GROUP EXERCISE 2
Applying contingent valuation in China to measure the total economic value of
restoring ecosystem services in Ejina region (Zhongmin et al., 2003)
Case description Ejina lies in the lower reaches of Hei River, one of the two largest inland river basins in China, and is situated south of Monogolia and western Inner Mongolia. The Ejina oasis covers an overall area of 3115.88 km2, which is a detached island oasis encompassed by peripheral desert. With a current population of near 16 thousand, Ejina is one of the world’s most sparsely populated district in the world’s most populated country. The Ejina region also has an extreme and harsh natural environment. The climate of the area is characterized by frequent and severe droughts and large differences in temperature. Mean annual temperature at Ejina is 8.2 °C, with a maximum of 41 °C (July) and a minimum of -36.4 °C (January). Mean annual precipitation is only 36.6 mm. The Hei River’s water resources are the basis of the Ejina environment, economic development and people lives. Water use has grown rapidly over the past 40 years due to economic growth and population increasing in the middle of the Hei River. The flow of the Hei River into the lower reaches in the Zhengyi Xia has decreased by 44.4%, from 11.90 × 108 m3 year-1 in the 1950s to 6.9 × 108 m3 year-1 or so in 1995. The drying up of runoff directly threatens the existence of Ejina ecosystem. About 3.07 × 104 ha of cultivated land in 1960 has now been reduced to only 0.3 × 104 ha and the rest of the cultivated oasis has turned into desert. The area of degraded forest and harsh desert grassland has increased by 35.09 × 104 ha since 1960. The shape of the Ejina oasis has been reduced to three riverine areas: West River, East River and Gurinai. Due to the desert area increasing and oasis area decreasing in Ejina, sandstorms have increased recently in the middle of the Hei River. This deterioration of the Ejina ecosystem has a huge influence on much of northern China. In the spring of 2000, an unprecedented heavy sandstorm event took place in Beijing, Tianjin and their neighboring areas. This storm had adverse effects on the environment, as well as other aspects of people’s daily life and work. The Ejina oasis is the first barrier to sandstorms in the middle of the Hei River valley and north-western China. As a result, the government and the Hei River management bureau decided to adopt conservation measures to restore Ejina’s ecosystem. These measures include restoring the natural vegetation to establish an effective ecological protective shield in Ejina and to reduce the magnitude of this problem. Restoring Ejina ecosystem could allow for controlling soil erosion and reducing sandstorms, provide habitat for wildlife, natural purification of water, dilution of wastewater, and curbing land salinization. It is estimated that this restoration effort will cost approximately 600 million RMB in total over 5 years. The five key ecosystem services that restoring Ejina ecosystem could provide, which are (1) control soil erosion and reducing sandstorms, (2) provide habitat for wildlife, (3) natural purification of water, (4) dilution of wastewater, and (5) curb land salinization.
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Fig. 2. Sketch of restoring Ejina ecosystem The aim of the study is to assess whether these costs are worth the benefits to Chinese people living in this area. 1. Why is the CVM selected in this case? ___________________________________________________________________________
___________________________________________________________________________
2. What alternative method (s) could have been used and why? ___________________________________________________________________________
___________________________________________________________________________
3. Work through the steps of the CVM process to estimate the WTP to improve ecosystem
services in Ejina.
A. Set up the hypothetical market (a convincing scenario, aids, …) ________________________________________________________________________
________________________________________________________________________
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________________________________________________________________________
________________________________________________________________________
________________________________________________________________________
B. Obtain the bids
a. Select a method for obtaining a bid (income taxes, property taxes, value added or sales tax, utility bills, entry fees, payments into a trust fund)
________________________________________________________________________
________________________________________________________________________
________________________________________________________________________
________________________________________________________________________
b. Select the type of questionnaire survey to be adopted (in-person, mail, phone, etc.):
_____________________________________________________________________
c. Types of information obtained
vi. What are the various types of information to be obtained via the questionnaire? − _____________________________________________________________
− _____________________________________________________________
− _____________________________________________________________
vii. The people living in the upland rural western area of China are still not familiar with
the market prices. Accordingly, how would you elicit their WTP? − _____________________________________________________________
viii. What wording would you use to elicit the WTP?
− If the majority of households vote in favor of restoring Ejina ecosystem, the Ejina’s ecosystem will be restored to the level of the early age of 1980s.
− If a majority vote against, the Ejina ecosystem will remain the conditions and deteriorated as is the current tendency, at last, it has the likelihood to disappear in the world like the historic country ’LouLan’.
− If the project of restoring Ejina ecosystem is at the stage of raising capital, if you vote in favor of it, please draw a circle around the maximum amount your household would vote for and draw a line under the lowest amount your household will switch (i.e. to a no) each year in the following 20 years.
− 0 2 5 10 20 35 50 75 100 200 300 − If current raising capital is a lump-sum payment, would your household be in favor
of cost _____ (yuan) to restoring the Ejina’s ecosystem. (Please fill in the blank).
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ix. How would you convince the interviewee that his answer will influence the decision-making process − _____________________________________________________________
_____________________________________________________________
d. Sample size:
Total sample size was 700 households in Hei valley. To save travel time, randomized cluster sampling was adopted. 24 villages and towns were chosen randomly by region as the sampling site. The relative sample amount in each region is determined by population density. Response rates were beyond 99% among main valley and surrounding district.
e. How can you detect and account for protests against the suggested bid vehicle? _____________________________________________________________________
_____________________________________________________________________
A series of follow-up check questions were asked after the WTP question to determine if those refusing to pay represent a valid representation of their value or reflect a protest about some feature of the simulated referendum.
Table 1. Distribution of survey willingness to pay responses (vote for)
Percent of respondents Response
Main Valley % (n)
Surrounding district % (n)
Willing to pay some amount 92.37 (448) 92.09 (198)
‘Restoring ecosystem service is not worth this money to me’ 0.00 (0) 0.00 (0)
‘I can’t afford to pay this amount’ 1.03 (5) 0.93 (2)
‘It is unfair to expect me to pay for increasing ecosystem services’ 2.06 (10) 3.26 (7)
‘Restoring Ejina ecosystem services cannot get expected effect’ 1.65 (8) 0.00 (0)
‘I am opposed to paying for this government program’ 2.27 (11) 2.79 (6)
Other reasons (protest response) 0.62 (3) 0.93 (2)
Total 100.00 (485) 100.00 (215)
Deleted as protest 6.60 6.98
f. What is an important step in questionnaire development and administration? _____________________________________________________________
g. How long in your opinion should the duration of the questionnaire be?
_____________________________________________________________________
Regional Training Workshop on the Cost of Environmental Degradation Methodology July 1‐5, 2008 Crowne Plaza Hotel, Beirut, Lebanon
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C. Estimate the mean WTP/WTA. Time discounting was used by researchers in this case.
Frequency distribution of respondents by bid amount they would vote in favor WTP amount (RMB) 0 2 5 10 20 35 50 75 100 200
Frequency distribution (%) 7.3 8.5 10.4 22.4 17.2 8.2 11.8 2.3 8.5 3.4 Median WTP per household is 19.37 RMB/year (2.72 USD/year) in Hei Valley; ranging between 20.78 RMB (2.92 USD) in Main Valley and 16.41 RMB (2.31 USD) in the Surrounding District. Accordingly, it can be inferred that people living in different areas view differently the services provided by an ecosystem. D. Aggregate WTP/WTA amount by completing the table below (fill in the highlighted
cells)
Total benefits of households in Hei valley Regions Household
annual median WTP
Number of households
Number of households which have WTP
Annual aggregate WTP (millions)
Discount rate (%)
Time scale (year)
Present value aggregate benefits (million RMB)a
Main valley 20.78 223,895 222,187 15 20 28.90
Surrounding
district
16.41 259,328 257,277 15 20 26.43
Total 55.33
Note that the WTP was aggregated on time scale by adopting the mean environment discount rate (15%) based on compounding interest. The aggregate present value of benefits (55.33 millions over a 5-year period) is less than the present value of restoration cost (400 millions), calculated from 600 millions, at the 15% discount rate, over 5 years.
E. Assess the validity of the CV study Three full statistical models including all survey demographic and attitude variables were estimated by maximum likelihood regression. − Respondent’s education & income level were positively correlated with WTP and were significant − Suburban and urban residents have higher willingness to pay than rural/farm residents − On the average, WTP amounts of 20 and 100 represent 1 and 5% of per capita yearly income,
respectively.
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GROUP EXERCISE 3
Economic valuation of environmental services sustained by water flows in the
Yaqui River Delta (Ojeda et al., 2007)
Case description The Yaqui River is located in a trans-boundary 72,540 km2 basin, largely situated in the Mexican State of Sonora and a small part in Chihuahua, as well as small portions of Arizona and New Mexico in the United States. The Yaqui River Basin is within one of the driest hydrologic regions in Mexico. The predominant climate is arid and semi-arid throughout the Basin, except in the eastern portion where the high mountains are located. The average annual rainfall in the area is 527 mm. The majority of the precipitation falls in the months of July to September and is dominated by the North American Monsoon. The runoff from precipitation is captured by several reservoirs on the Yaqui River and its tributaries, and is used mainly for irrigation purposes. The Yaqui River Delta occurs where the River meets the Gulf of California, also called the Sea of Cortez. The Delta is the location of two of the more important ecosystems in the lower part of the Yaqui River Basin: the riparian ecosystem, and the coastal wetlands and estuaries. The Yaqui Valley farming region, which is encompassed within the Delta, is the most important agricultural area (more than 250,000 ha) in Sonora State. Agriculture is the largest user of water, representing more than 96% of the total water withdrawal in the Delta. Water demand from cities and towns of more than 800,000 inhabitants in the entire Basin is increasing due to the accelerated migration of rural inhabitants to nearby cities. Other significant economic activities that exert a water demand in the Delta include manufacturing, animal husbandry, aquaculture and fisheries. The environmental concerns associated with water management in the Yaqui River Delta are clearly linked to a decrease in water flows and deterioration of water quality. These concerns can be summarized by five major problems: salinity intrusion, agrochemical pollution, deterioration of wetlands and estuaries, habitat destruction, and loss of biodiversity. After completion of Oviachic Dam in 1952, the majority of the flow in Yaqui River has been used for irrigation. As a result, the Yaqui River has not reached the Gulf of California for several decades. This situation has deteriorated the quality of the environmental services provided by the ecosystems that depend on the water flows in the Yaqui River Delta. Until the Oviachic Dam began its operations, the Delta consisted of lush, riparian forests of mezquite, alamo, willows and coastal scrubs. This vegetation, however, has effectively disappeared over the last few decades. The loss of riparian vegetation, coupled with the loss of wetlands and estuaries because of desiccation and the expansion of aquaculture farms, has reduced the habitat for resident and migratory birds and other animals, including several protected species. The lack of water in the rivers has also greatly reduced the deposition of silt that formerly replenished the wetlands and estuaries with nutrients. The reduction in freshwater flow in the Yaqui River Delta has also reduced the influx of nutrients to the Gulf of California, one of the world's most productive marine ecosystems, and has reduced critical nursery habitat for fisheries that thrive in the upper portion of the Gulf. The lack of flow in the River downstream of the Oviachic Dam has also reduced recharge of the aquifers in the Delta. The reduction of recharge, combined with the groundwater extraction for irrigation could generate the saline intrusion problems that have occurred in several neighboring aquifers. Water rights have been allocated in the Rio Yaqui basin to municipal, industrial and agricultural users, with the majority of the water rights being allocated to agriculture (95%). In Mexico, water rights law has been historically based on the principle that water resources are the property of the state and thus should be a free, constitutional right for every citizen. Recent reforms, however, have been designed to promote private water rights and to allow for water rights to be traded and leased by users.
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The objective of this study is to estimate non-market values for water in the Yaqui River Delta, Sonora, Mexico, based on residents' willingness-to-pay for existing or potential environmental services sustained by water flows in the Yaqui River. 1. Why is the CVM selected in this case? ___________________________________________________________________________
___________________________________________________________________________
2. What alternative method (s) could have been used and why? ___________________________________________________________________________
___________________________________________________________________________
3. Work through the steps of the CVM process to estimate the WTP to improve air quality in
Beijing.
A. Set up the hypothetical market (a convincing scenario, aids, …) ________________________________________________________________________
________________________________________________________________________
________________________________________________________________________
________________________________________________________________________
B. Obtain the bids
a. Select a method for obtaining a bid (income taxes, property taxes, value added or sales tax, utility bills, entry fees, payments into a trust fund). Given that all farmers in the Yaqui Valley are organized into irrigation districts which hold water rights for almost 3,000 million m3/year. All water diverted for irrigation purposes is controlled by the irrigation districts.
________________________________________________________________________
________________________________________________________________________
________________________________________________________________________
________________________________________________________________________
b. Select the type of questionnaire survey to be adopted (In-person survey, mail survey,
phone survey, etc.): ________________________________________________________________________
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c. Types of information obtained x. What are the various types of information to be obtained via the questionnaire?
− _____________________________________________________________
− _____________________________________________________________
− _____________________________________________________________
xi. Would you use an open or close-ended question to elicit the WTP, and why? − The WTP elicitation format consisted of a single-bound dichotomous choice (DC)
bid followed by an open-ended question eliciting maximum WTP. − The bid amount X was assigned randomly to the respondents and came from a set
of 15 possible values in the range of 10 to 150 pesos per month, in increments of 10 pesos. The maximum bid amount was estimated based on data on the distribution of typical household expenditures, the purchase of agriculture water rights in Sonora, and average water bills in Ciudad Obregon.
xii. What wording would you use to elicit the WTP? − The respondents faced a single DC question of the form “Are you willing to pay X
monthly for the next five years?
xiii. What is the main type of bias that could be associated with this form of WTP elicitation? − _____________________________________________________________
xiv. How would you convince the interviewee that his answer will influence the decision-
making process − _____________________________________________________________
− _____________________________________________________________
d. Sample size: 197 households
g. What is an important step in questionnaire development and administration?
_____________________________________________________________
e. How long in your opinion should the duration of the questionnaire be?
_____________________________________________________________________
C. Estimate the mean WTP/WTA
Bid level in pesos
# of respondents per given bid level
# of respondents agreeing to bid level
# of respondents not agreeing to bid level
10 8 8 0
20 8 7 1
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30 10 9 1
40 9 8 1
50 9 5 4
60 10 5 5
70 11 10 1
80 10 6 4
90 7 7 0
100 6 5 1
110 7 5 2
120 8 4 4
130 8 6 2
140 7 4 3
150 7 3 4
Total 125 92 33
− 23 responses were excluded: 3 because of lack of confidence by the interviewer, 2
unrealistically large WTP, 18 ‘protest zeros’ − 125 respondents: 5% non protest zero WTP, 95% non-zero
DC question: ∑=
=N
i ii yXN
MeanWTP1
1 = ___________________________________
Where N is the total number of responses, Xi the bid level, and yi the number of yes responses to that bid level Open ended question mean WTP = 73 pesos/month (6.8 USD/month) D. Assess validity of the CV exercise Multivariate statistical analyses were performed to understand households’ determinants of WTP responses: Significant determinants were:
− initial bid amount (- correlation) − # of years of formal education (+ correlation) − # of children in household younger than 15 yrs (+ correlation) − Household monthly income (+ correlation)
Results from linear and logit models were relatively similar ⇒ robust WTP-determinant relationships
REGIONAL WORKSHOP ONREGIONAL WORKSHOP ON
THE COST OF ENVIRONMENTAL THE COST OF ENVIRONMENTAL DEGRADATION METHODOLOGYDEGRADATION METHODOLOGY
Session 11Stated Preference ApproachStated Preference Approach
GROUP EXERCISESGROUP EXERCISES
CASECASE--STUDIESSTUDIES
1. Coastal Ecosystems in Phang Nga Bay, Thailand
2. Air quality in Beijing
3. Ecosystem services in Ejina, China
4. Environmental Services in the Yaqui River Delta, Mexico
5. Sustainable development in Swedish coastal zone
Case study 1Case study 1Economic Valuation of Coastal Ecosystems Economic Valuation of Coastal Ecosystems
in Phang Nga Bay, Thailandin Phang Nga Bay, Thailand
Case DescriptionCase DescriptionStudy areaStudy area
• Phang Nga Bay, Thailand: large bay in Andaman Sea, covering costs of Phuket, Phang Nga and Krabi provinces
• Habitat for– 60228 ha mangrove area– Coral reefs– Sea-grass beds
• Intensive aquaculture activities: shrimps, cockles, oysters, bivalves
• Distinctive & attractive tourism assets: beaches, islands, parks, etc.
Case DescriptionCase DescriptionEcosystem deteriorationEcosystem deterioration
• Reduction of mangrove forests in all Thailand:– From 367000 ha to less than 168676
ha in the period 1961-1993– Converted to other uses:
aquaculture, mining, settlement sites, ports & roads, salt ponds, marine shrimp aquaculture
• Damages to coral reefs:– Natural forces– Increased tourism activities such as
snorkeling• Dangers on fauna: mangroves and
coral reefs provide habitat for fish & migratory birds as well as rare & endangered plant & animal species Major mangroves and reefs
in Thailand
Case DescriptionCase DescriptionEcosystem deterioration & threatsEcosystem deterioration & threats
What is the economic value of changes to the quality of the mangroves & coral reefs
ecosystems in the Bay???
• The Bay was designated as an area for the Southern Seaboard Development Project which– Is intended to capitalize on natural resources to
attract foreign development– Consists of: 2 deep-sea ports, industrial estates,
urban centres & highways• Some people are arguing that net benefits of
planned developments exceeded those of mangrove forests
Applied MethodApplied MethodConjoint analysisConjoint analysis
• Face-to-face interviews with randomly selected 300 thais from 2 areas: Phang Nga Bay & other major provinces
• Surveyors received a training• Four ecosystem attributes were valuated: living coral
cover, income from fishery, flood occurrence, area protected
• Payment method: increase in income tax• The survey (pre-tested with 60 individuals) included 4
parts:– General attitudes towards the environment (ranking exercise)– Background information on current use of mangroves & reefs
(illustrated with maps & graphics)– The WTP question in the form of a choice experiment– Socio-economic characteristics
Applied MethodApplied MethodThe WTP experimentThe WTP experiment
• Intended to estimate the value resource users place on ecosystem quality changes from its present average level (status quo) to good(plan A) & excellent (plan B) for the 4 selected attributes
• Cost values – Were determined based on pre-tests: a payment card
where respondents were asked to tick the amount they were sure they would pay & to cross the amount they were sure they would not pay
– Varied between 200 & 1500 Baht (5 & 37.5 USD)
Applied MethodApplied MethodThe WTP experiment The WTP experiment –– Alternative choicesAlternative choices
Set 1 2 3 4 Cost (Baht)
1 Good Good Good Ave 200
2 Good Good Exc Ave 200
3 Good Good Ave Good 1000
4 Good Good Ave Exc 1000
5 Good Exc Good Exc 1500
6 Good Exc Good Exc 700
7 Good Exc Exc Good 1500
8 Good Exc Exc Ave 700
9 Good Ave Good Good 1000
10 Good Ave Exc Good 1500
11 Good Ave Ave Exc 700
12 Good Ave Ave Ave 200
13 Exc Good Good Good 700
14 Exc Good Good Ave 1500
15 Exc Good Exc Exc 1500
16 Exc Good Exc Exc 1000
17 Exc Good Ave Ave 1500
18 Exc Exc Good Good 200
19 Exc Exc Good Ave 1000
20 Exc Exc Exc Good 700
Set 1 2 3 4 Cost (Baht)
21 Exc Exc Exc Ave 200
22 Exc Exc Ave Good 1000
23 Exc Ave Good Exc 200
24 Exc Ave Exc Exc 200
25 Exc Ave Ave Good 700
26 Exc Ave Ave Ave 1500
27 Ave Good Good Good 1500
28 Ave Good Good Good 200
29 Ave Good Exc Good 200
30 Ave Good Exc Ave 700
31 Ave Good Ave Exc 700
32 Ave Exc Good Exc 1500
33 Ave Exc Exc Ave 1000
34 Ave Exc Ave Good 200
35 Ave Exc Ave Exc 200
36 Ave Exc Ave Ave 1500
37 Ave Ave Good Ave 1000
38 Ave Ave Good Ave 700
39 Ave Ave Exc Good 1500
40 Ave Ave Exc Exc 1000
Attributes Level
1- Increased living coral cover
Average (no change), Good (25%), Excellent (65%)
2- Increased income from fishery
Average (no change), Good (35 %), Excellent ( 60%)
3- Flood occurrence
Average (every year), Good (every 2 years), Excellent (every 4 years)
4- Increased area protected
Average (no change), Good (20 %), Excellent (50 %)
Increased income tax in 2002 (Baht)
0, 200, 700, 1000, 1500
Respondents were asked to chose among the following alternative choices
ResultsResultsAttitudes on use of the BayAttitudes on use of the Bay
Problems Rank
Protecting natural habitats and wildlife 35% (1)
Reducing water pollution 23% (2)
Improving quality of education 16% (3)
Increasing agricultural productivity 12% (4)
Inflation 9% (5)
Other social and environmental problems 6% (6)
Problems Rank
Degraded mangroves and coral reefs 44% (1)
Deforestation 22% (2)
Floods 11% (3)
Other environmental problems 11% (3)
Water pollution 10% (5)
Air pollution 2% (6)
4 8 %
2 6 %
2 0 %3 % 3 % 1
2
3
4
5
5 0 %3 0 %
1 4 % 4 % 2 % 1
2
3
4
5
Ranking of social & environmental problems
Ranking of environmental problems
We have a duty to protect the environment
from development regardless of the cost
We should minimize environmental damage
for the benefit of our grandchildren
1= Strongly agree 2=Agree 3=No opinion 4=Disagree
5=Strongly disagree
ResultsResultsAttitudes on use of the BayAttitudes on use of the Bay1 4 %
1 5 %
1 4 %1 3 %
4 4 %
1
2
3
4
5
Thailand needs to develop her forests, sea, and land to increase jobs and incomes, regardless of
the environmental damage
7 0 %
1 8 %
8 % 2 % 1
2
3
4
5
2 %
2 4 %
3 2 %
3 0 %
7 % 7 % 1
2
3
4
5
Mangroves and coral reefs should be protected because rare birds and marine lives depend on
them
I should pay for the protection of parks and nature reserves even if I do not visit them
2 7 %
3 6 %
2 7 %
6 % 4 % 1
2
3
4
5
Even if I do not use the mangroves and coral reefs now, I am prepared to pay now to protect them in case I want
to use them in the future
3 9 %
3 4 %
1 9 %5 % 3 % 1
2
3
4
5
It is worth spending money to protect mangroves because they help to protect
agricultural productivity in the area
9 %1 4 %
1 8 %2 0 %
3 9 %
1
2
3
4
5
We have more important things to think about than the loss of the mangroves and coral reefs
1= Strongly agree 2=Agree 3=No opinion 4=Disagree 5=Strongly disagree
ResultsResultsWTP estimationWTP estimation
• Diversity of flora & fauna is the most important attribute
• Aggregate WTP is 5784 million Baht (144.6 million USD)per year (computed by multiplying by number of beneficiary people
Attributes (Baht/person/year)
Average Good Excellent
Flora and fauna -699 265 434
Local livelihood -257 257 -
Ecological function -252 - 252
Rare and endangered species 46 -204 158
Attributes WTP Baht (USD)/person/yr
Percent(%)
Flora and fauna(from average to excellent)
434 – (-699)= 1,133 (28)
50
Local livelihood(from average to good)
257 – (-257)= 514 (13)
22
Ecological function(from average to excellent)
252 – (-252)= 504 (13)
22
Rare and endangered species(from average to excellent)
158 – 46 = 112 (3)
6
Total 2,263 (57) 100
End of Case Study Case study 2Case study 2Economic valuation of air quality Economic valuation of air quality
improvement in Beijing, Chinaimprovement in Beijing, China
Case DescriptionCase DescriptionStudy areaStudy area
• 8 districts of Beijing, China:– 4 urban (Dongcheng, Xicheng, Chongwen and
Xuanwu)– 4 suburban (Chaoyang, Fengtai, Shijingshan and
Haidian)
Case DescriptionCase DescriptionEcosystem deteriorationEcosystem deterioration
• Beijing has been experiencing a rapid economic development:– GDP growth rate of more than 9% per year since 1995– Maximum of 10.2% in 1999
• Significant deterioration of environmental quality, especially air quality
• Impacts on:1. Human health 2. Agricultural yield 3. Industrial production
What is Beijing’s residents WTP to improve air quality in its urban areas???
Applied MethodApplied MethodContingent ValuationContingent Valuation
• In-person 15-20 min interviews on WTP to improve air quality, with a sample of 1500 households distributed among districts proportionally to their household density
• Steps taken to reduce common biases in the contingent valuation method:
– Part-whole bias: interviewee was asked about the payment his household would do annually, to eliminate biases related to individual/household payments and time horizon
– To get a conservative estimate: open-ended question about WTP estimate was used (generally leads to lower mean WTP than other types of questions)
• Interviewees were told that their WTP answers would contribute to air quality improvement where they live and work and influence the decision-making process
• A follow-up question was used at the end of the interview regarding degree of understanding of the survey: 70.3% fully understood, 15.9% partially understood, 13.8% didn’t understand
Applied MethodApplied MethodQuestionnaire designQuestionnaire design
• Three parts (revised through pre-tests):1. The general attitudes of interviewees toward the
environmental quality in Beijing (willing or unwilling to pay, and why?)
2. The WTP of residents to improve air quality in Beijing: designed question‘What would your household be willing to pay annually during the next 5 years in order to fulfil the goal of air quality improvement in Beijing (50% reduction in air pollution levels)?’Note: before responding, the interviewee was shown some pictures of ‘deteriorated air’ and some of ‘improved air’
3. The social and economic features of interviewees: age, gender, employment, income, household population, etc.
ResultsResultsWTP responses (1)WTP responses (1)
• 1371 out of 1500 questionnaires were recovered
Proposed area for expenditure Ratio (%)
Scientific research on air quality improvement
28.9
Air quality improvement project (e.g. improve energy consumption)
53.2
Compensation to the unemployed workers due to the closure of enterprises which cause air pollution
16.8
Pay for the environmental management expenditure (e.g. air quality monitoring system development)
15.9
Improvement of gas exhaust equipment of vehicles
18.3
Assisting the air pollution enterprises renovation/relocation
24.0
WTP in RMB (in USD) /year
# of interviewees
Percentage (%)
0 460 33.6
≤ 10 (1.4) 65 4.7
11-50 (1.5-7.0) 161 11.7
51-100 (7.2-14.1) 302 22.0
101-500 (14.2-70.3) 331 24.1
501-1000 (70.4-140.5) 42 3.1
≥ 1001 (140.7) 10 0.7
Total 1371 100
WTP/yearSample
Mean in RMB (in USD)
SD (RMB)
Median (RMB)
Maximum (RMB)
N=1371 (whole) 143 (20.1) 346 50 7000
N=911 (positive) 215 (30.2) 406 100 7000
Includes true zero and protest zero WTP ⇒ conservative estimationLess than 1% of household income
ResultsResultsWTP responses (2)WTP responses (2)
• Aggregate annual WTP (by multiplying the mean WTP per household per year by total # of households in survey area):– Conservative: 3.36 billion RMB (0.5 billion USD) per
year– Upper limit: 4.98 billion RMB (0.7 billion USD) per
year
• Beijing residents prefer better air quality and have a clear idea about the trade-off between economic growth and environmental protection
ResultsResultsStatistical analysisStatistical analysis
• 4 variables were found to have significant influence on WTP:– Household income
(+ correlation)– Education
(+ correlation)– Household population
(- correlation)– Age
(- correlation)
End of Case Study
Case study 3Case study 3Restoration of ecosystem services Restoration of ecosystem services
in Ejina region, Chinain Ejina region, China
Case DescriptionCase DescriptionStudy areaStudy area
• Ejina region, China • 3116 km2 oasis, surrounded by
desert in Hei River Basin• Sparsely populated (16000)• Temperature extremes: average
8.3°C (range: -36.4 to 41°C)• Hei River’s water resources
are the basis of the environment, economic development and people lives
• Ejina oasis is the first barrier to sandstorms originating in the middle of Hei River Valley andn orth Western China
Case DescriptionCase DescriptionEcosystem deteriorationEcosystem deterioration
• Decrease in water flow over past 40 years as a result of:
– Low mean annual precipitation (36.6 mm)
– Increase in water use as a result of economic growth and increase in population
– Stop in water flow from May to July as a result of agriculture production peak
– Drying up of runoff after November
Cultivated land has been reduced from 3.07x104 ha in 1960 to 0.3x104 ha in 2000, the rest turned down into desertArea of degraded forest and harsh desert grassland has increased by 35.09x104
ha since 1960Ejina oasis has been reduced to 3 riverine areas: West River, East River and Gurina (figure)
Case DescriptionCase DescriptionImpacts of ecosystem Impacts of ecosystem
deteriorationdeterioration• Increase of desert area and decrease of oasis area in Ejian
resulted in the increase of sandstorms in the middle of the Hei River, which reached sometimes Northern China (Beijing, Tianjin and neighboring areas). These storms:– Generated thick dust and created traffic problems – Resulted in economic losses: reduced sunlight to cultivated land
caused a decrease in production– Reduced the visibility: increased traffic hazard– Adversely affected mental health of the population
• Cost of restoration of Ejina’s ecosystem to prevent sandstorms was estimated at 600 million RMB (Renminbi, ~85 million USD) over 5 years
• Is this cost worth the benefits to people living in the area???
Applied MethodApplied MethodContingent ValuationContingent Valuation
• In-person 30-min interviews on WTP estimation for ecosystem restoration, with a sample of randomly chosen 700 households in Hei Valley
• Steps taken to reduce common biases in the contingent valuation method:– Providing a 2 RMB (~0.3 USD) currency bill as appreciation – Printing questionnaire on good quality paper bound in booklet form– Providing background information on Ejina ecosystem– Deciding the bid range (range of WTP amounts) by pretest and adopting
the ‘payment card’ (PC) method– Keeping responses anonymous
• Respondents were told that feedback from survey will be used as input by the government in its study of restoring Ejina ecosystem
Applied MethodApplied MethodQuestionnaire designQuestionnaire design
• Four major parts:1. Background on Ejina region: maps showing location and condition of
the ecosystem; history of the area2. Card listing the 5 services that restoring Ejina ecosystem could provide:
• Control soil erosion & reducing sandstorms• Provide habitat for wildlife • Natural purification of water• Dilution of wastewater• Curb land salinization
3. Valuation portion: • Portrayal of ecosystem to be valued• Choice of payment vehicle: donation, ecological protection tax, water bill, a
fourth option left as blank to fill by a method preferred by respondent• Payment Card: used to elicit respondent’s RMB amount of WTP
4. Series of questions on respondent’s personal & socio-economic information
Applied MethodApplied MethodExact wording of Payment CardExact wording of Payment Card
If the majority of households vote in favor of restoring Ejina ecosystem, the Ejina’s ecosystem will be restored to the level of the early age of 1980s.If a majority vote against, the Ejina ecosystem will remain the conditions
and deteriorated as current tendency, at last, it has the likelihood to disappear in the world like the historic country ‘LouLan’.
If the project of restoring Ejina ecosystem is at the stage of raising capital, if you vote in favor of it, please draw a circle around the maximum amount your household would vote for and draw a line under the lowest amount
your household will switch (i.e. to a no) each year in the following 20 years.
0 2 5 10 20 35 50 75 100 200 300
If current raising capital is a lump-sum payment, would your household be in favor of cost …………. (RMB) to restoring the Ejina’s ecosystem. (Please
fill in the blank)
1% of per capita yearly income
ResultsResultsWTP responses (1)WTP responses (1)
Response Percent of respondents (%)
Main Valley Surrounding district
Willing to pay some amount 92.37 (448) 92.09 (198)
‘Restoring ecosystem service is not worth this money to me’ 0.00 (0) 0.00 (0)
‘I can’t afford to pay this amount’ 1.03 (5) 0.93 (2)
‘It is unfair to expect me to pay for increasing ecosystem services’ 2.06 (10) 3.26 (7)
‘Restoring Ejina ecosystem services cannot get expected effect’ 1.65 (8) 0.00 (0)
‘I am opposed to paying for this government program’ 2.27 (11) 2.79 (6)
Other reasons (protest response) 0.62 (3) 0.93 (2)
Total 100.00 (485) 100.00 (215)
Deleted as protest 6.60 6.98
WTP amount (RMB) 0 2 5 10 20 35 50 75 100 200
Frequency distribution (%) 7.3 8.5 10.4 22.4 17.2 8.2 11.8 2.3 8.5 3.4
5% of per capita yearly income
ResultsResultsWTP responses (2)WTP responses (2)
• Median WTP per household is 19.37 RMB/year (2.72 USD/year) in Hei Valley; ranging between 20.78 RMB(2.92 USD) in Main Valley and 16.41 RMB (2.31 USD) in the Surrounding District ⇒ People living in # areas view differently the services provided by an ecosystem
• Respondent’s education & income level were positively correlated with WTP and were significant
• Suburban and urban residents have higher willingness to pay than rural/farm residents
ResultsResultsTime Discount for WTPTime Discount for WTP
• Economic theory requires that the utility of a lump sum be equal to that of a series of annual payments as a result of a discount rate:A(PVIFAei,n) = FVn1(PVIFr,n1)Where A is the annual payment (32.18 RMB as per survey results); PVIFAei,n is the present value interest factor for ei and n (n=20); ei is the interest rate of environment goods (?); FVn1 is the future value lump sum investment at the beginning or end of n1 years; PVIFr,n1 is the present value interest factor for r and n, r is the risk-free interest rate (2.25%) and n1 is the time lump sum investment provided (20 years).
• If lump sum is provided at the end of the 20th year:32.18x(PVIFAei,20) = FV20(PVIF2.25%,20)⇒ ei = 19.8%
• If lump sum is provided at the beginning of 1st year ⇒ ei = 11.5%• ei = 11.5-19.8% ⇒ High discount rate for environmental goods!!
– Encourages public to underestimate the importance of future benefit– Demonstrates that humans should take action on environmental restoration & protection
ResultsResultsExpansion from sample to populationExpansion from sample to population
• The following steps were taken:– Providing a conservative estimate of WTP: non-respondents and protests
have a zero WTP– Using the median annual WTP per household of Main Valley and
surrounding district– Multiplying the median by the number of households in the respective
regions– Aggregating WTP on time scale by adopting the mean environment
discount rate (15%)• Aggregate present value of benefits: 55.33 millions over a 5-year
period • Less than present value of restoration cost: 400 millions
(calculated from 600 millions, at the 15% discount rate, over 5 years)
• Implications: – Limitations of using WTP approach in less developed countries– Need to determine if there are additional benefits in other regions
End of Case Study
Case study 4Case study 4Economic valuation of environmental Economic valuation of environmental
services of water flows in the services of water flows in the Yaqui River Delta, MexicoYaqui River Delta, Mexico
Case DescriptionCase DescriptionStudy areaStudy area
• Yaqui River basin, largely in Sonora, Mexico, small part in Chihuahua, Mexico, and small portions in Arizona and New Mexico in US
• 72540 km2 basin, in driest hydrologic regions of Mexico
• 800000 inhabitants• The delta occurs where River meets
the gulf of California: location of 2 important ecosystems, the riparian ecosystem, and the coastal wetlands and estuaries
• Home of most important agricultural area in Sonora State: > 250000 ha of wheat, soybeans, cotton, maize, sorghum, and alfalfa; withdraws 96% of delta water
Case DescriptionCase DescriptionEcosystem deteriorationEcosystem deterioration
• Decrease in water flow and deterioration of water quality:– Low annual precipitation (527
mm)– Increase in water demand in
urban centres of the basin: migration of rural inhabitants to nearby cities
– Economic activities exerting water demand: manufacturing, animal husbandry, aquaculture and fisheries
Disappearance of riparian vegetation, loss of wetlands and estuaries – habitat for resident and migratory birds and several protected species –Reduction of the influx of nutrients to the Gulf of CaliforniaReduction of critical nursery habitat for fisheriesReduction of the recharge of the aquifers in the Delta, coupled to groundwater extraction for agriculture ⇒ saline intrusion problems
What is the WTP for restoring in-stream flows in the Yaqui River delta???
Applied MethodApplied MethodContingent ValuationContingent Valuation
• Face-to-face interviews on WTP estimation for water flows restoration, with a sample of 197 households
• Steps taken to reduce common biases in the contingent valuation method:– Sample selection bias: next available house was approached
immediately after end of each interview– Sampling frame bias: a full range of survey sites were used– Starting point bias: was assessed by determining the dependence of the
WTP on bid starting point (yes-saying bias)– Potential sponsor bias: respondents were told the research was
sponsored by a university – a neutral body –– Interviewer and misspecification biases: interviewers were trained on
CVM surveys
Applied MethodApplied MethodSurvey designSurvey design
• Major parts (revised through pre-tests):– Presentation of background on the Yaqui River Delta: geographic
information, agricultural activity, environmentally sensitive issues (+ visual aids)
– Presentation of information on environmental services sustained by Delta if in-stream flows are restored:
• Preservation of habitat for birds and other fauna• Maintenance of local fisheries• Dilution of pollutants• Recreation• Non-use values: existence & cultural values, use value for future
generations– Scenario description: explaining how ecosystem functions under
current conditions versus with increased ecosystem services– Payment vehicle description: water bill increase to purchase water
from farmers– WTP elicitation– Collection of demographic information (gender, age, income, etc)
Applied MethodApplied MethodWTP elicitation formatWTP elicitation format
1. Single dichotomous choice (DC) format question (yes/no):‘Are you willing to pay X monthly for the next five years?’X randomly lying between 10 and 150 pesos (~1 and 14 USD) in increments of 10 pesos
2. Open-ended question eliciting maximum WTP(N.B: a main rule was the avoidance of repeated questioning and iteration)
ResultsResultsDC question responsesDC question responses
• 148 out of 197 households (75%) responded:
– 23 responses were excluded: 3 because of lack of confidence by the interviewer, 2 unrealistically large WTP, 18 ‘protest zeros’
– 125 respondents: 5% non protest zero WTP, 95% non-zero
•
= 52 pesos/month (4.9 USD/month)Where N is the total number of responses, Xi the bid level, and yi the number of yes responses to that bid level
Bid level in pesos
# of respondents per given bid level
# of respondents agreeing to bid level
# of respondents not agreeing to bid level
10 8 8 0
20 8 7 1
30 10 9 1
40 9 8 1
50 9 5 4
60 10 5 5
70 11 10 1
80 10 6 4
90 7 7 0
100 6 5 1
110 7 5 2
120 8 4 4
130 8 6 2
140 7 4 3
150 7 3 4
Total 125 92 33
∑==
N
1iiiyX
N1MeanWTP
ResultsResultsOpenOpen--ended question responsesended question responses
• Mean WTP = 73 pesos/month (6.8 USD/month)
• Higher than that obtained with DC question because:– respondents accepting the initial
bid added a maximum WTP estimate significantly higher than the initial bid
– respondents rejecting the initial bid chose a slightly lower WTP
WTP (pesos/month)
Freq
uenc
y
Distribution of WTP responses
Normal distribution
ResultsResultsStatistical analysisStatistical analysis
• Multivariate statistical analyses were performed to understand households’ determinants of WTP responses:– Significant determinants were:
• initial bid amount (- correlation)• # of years of formal education (+ correlation)• # of children in household younger than 15 yrs (+ correlation)• Household monthly income (+ correlation)
– Results from linear and logit models were relatively similar ⇒ robust WTP-determinant relationships
End of Case Study
Workshop on Workshop on the Cost of Environmental Degradationthe Cost of Environmental Degradation
Case study 5Case study 5Economic valuation for sustainable Economic valuation for sustainable
development in the Swedish Coastal Zonedevelopment in the Swedish Coastal Zone
Case DescriptionCase DescriptionStudy areaStudy area
• The Swedish coastal zone• Open-access conditions &
public nature of provided services ⇒ conflicting interests– Between people of remote coastal
areas interested in coastal ecosystem goods & services, & the urban population interested in high quality recreation facilities
– Between those who demand coastal ecosystem goods & services (e.g. swimmers) and those influencing their supply (e.g. emitters of nutrients)
Case DescriptionCase DescriptionEcosystem deteriorationEcosystem deterioration
What is people’s WTP for environmental improvements or for avoiding environmental damage???
• Emission of nutrients– Agriculture and forestry in catchment
areas– Municipal wastewater treatment plants– Atmospheric deposition (e.g. from
traffic)
• Open access to fishing grounds– Increased harvest– High fishing pressure in commercial
catches in the North Sea– By-catches from bottom trawling
• Deterioration of marine water quality
Decreased fish stocks, e.g. cods & blue skates
Increase in nitrogen load to seawater → decrease in water transparency →Eutrophication
Frequent violation of water quality standard; Medium biological diversity; Low average cod catch per trawling hour
Case Study 1Case Study 1Reduced eutrophication of the Reduced eutrophication of the
Stockholm ArchipelagoStockholm Archipelago• Nutrient emissions in catchment area → Increased N
concentration in coastal water → eutrophication• Do the benefits of reduced eutrophication outweigh the costs
of reduced eutrophication effects?• Cost of mitigation:
– 1-m increase in the average water transparency → 40% reduction in N load (annual reduction of 2725 tonnes of nutrients) → increased sewage water treatment & reduced fertilizer use ⇒ 57 million SEK (~9.5 million USD) per year
• Benefits: – Recreational benefits were estimated by travel cost method– Other benefits were captured by contingent valuation method (5500
random mail questionanires in Stockholm & Uppsala)– ⇒ 60 million SEK per year (travel cost)
+ 500 million SEK per year (CV)= 560 million SEK (~93 million USD) per year
Case Study 2Case Study 2Improved coastal fisheries in SwedenImproved coastal fisheries in Sweden
• Open access to fishing grounds → decreased fish stocks• Do the benefits of increased fish stock outweigh the cost of
underlying support to fish reproduction?• Study is on-going• Benefits:
– Travel cost method: 2500 random questionnaires in Stockholm & Uppsala counties to collect info on sites visited by respondents, the distance travelled, travel time, travel costs, catch rates, etc.
– Average response rate was 55% – Preliminary results:
• Positive relationship between probability that a fishing is chosen & the catch of fish
• Negative relationship between probability that a site is chosen & travel cost• Based on these results, economic benefits of improved fishing in the
archipelago; they will be compared to mitigation costs to assess actual profitability
Case Study 3Case Study 3Improved water quality at the Swedish Improved water quality at the Swedish
WestcoastWestcoast• Deterioration of sea water
quality → decrease in biodiversity and fish stock and violation of water quality standards
• What are people’s preferences for improved water quality?
• A choice experiment framework was used:– Water quality was represented
by 3 attributes– People were asked about their
WTP for a change in the attributes from current level to the highest level
Attribute Description Levels*
Bathing water quality (%)
Frequency of west-coast sites violating the quality standard
12, 10, 5
Biodiversity Biological diversity or ecosystem balance
Low, Medium, High
Cod stock (kg)
Catch per trawling hour with a research vessel
2, 25, 100
Cost (SEK) The total cost for an individual for each alternative
0, 120, 240, 600, 960, 1800
WTP (SEK) for a change from current level to highest level
MWTP*
Attribute
Water Cod High biod
600 1200 600
*marginal willingness to pay
*present level is in bold format
End of Session 11
Thank YouThank You
REGIONAL WORKSHOP REGIONAL WORKSHOP ONON
THE COST OF THE COST OF ENVIRONMENTAL ENVIRONMENTAL
DEGRADATION DEGRADATION METHODOLOGYMETHODOLOGY
Session 12Miscellaneous Case-studies
REGIONAL WORKSHOP ONREGIONAL WORKSHOP ON
THE COST OF ENVIRONMENTAL THE COST OF ENVIRONMENTAL DEGRADATION METHODOLOGYDEGRADATION METHODOLOGY
Session 12aPolitical Economy of the Coastal Zone
in Northern Lebanon
OutlineOutline
• Background• Study Objective• Study Scope and Methodology• Main Drivers and Pressures• Municipal Capacity• Economic Activity• Willingness to Preserve & CZ Intention• Conclusion and Discussion
BackgroundBackground
• The Mediterranean coast experienced drastic changes over the last decades:
• based on the increased pressures from drivers such as population and economic growth, globalization and trade, urbanization, industrialization, tourism, fisheries, extraction and agriculture
• with impacts on environmental health, sustainable development (air, water, soil and biota), land-use, encroachment on natural habitat, ecosystems, agricultural areas, watersheds and pristine areas; climate change
BackgroundBackground
Source: Plan Bleu (2006).
Unplanned development disrupted the coastal “striped”slopes and altered the land-use hence putting more pressures on most coastal zones
BackgroundBackground
• due to poor CZ regulatory framework/instruments across most East/South Med countries since the 1960s (Plan Bleu)
• With a regional response led by the EC (Plan Bleu, MAP, PAP/RAC, etc.) in conjunction with UNEP, World Bank-METAP and other Donors to reduce the land-based pollution of the coast, improve the integrated management of the coastal zones, etc. (1995 Barcelona Convention and its Protocols including Land-based and ICZM)
Objective Objective
Gauge the political economy of improving the management of the northern coastal zone by:
In a First Phase (EC-SMAP III and University of Balamand):- Determining drivers and coastal pressures in conjunction with fiscal and human resource municipal capacity, and economic activity- Assessing the willingness to preserve the coast (DD for change)
Objective Objective
In a Second Phase (EC-SMAP III and METAP):- Assessing the legal/institutional framework - Valuing the coastal environmental degradation and remedial actions- Suggesting policy (ways to achieve change) and institutional (instruments to achieve change) reforms
ObjectiveObjectiveThe objective of the First Phase will be
achieved through:
1. Analyzing the human resource and financial capacity of the coastal municipalities
2. Determining the coastline (including the municipalities) Gross Domestic Product (GDP)
3. Calculating the direct & indirect value of the northern coast and dweller ICZM intentions (Survey)
ScopeScope
Each coastal zone definition is meant to answer a specific purpose
The cadastre boundaries of the coastal municipalities were retained for this exercise
MethodologyMethodology
• Coastal municipalities: fiscal analysis based on surveys and budgets
• Coastal GDP: VAT, rapid surveys, etc. used to generate the value added based on National Account Input/Ouput ratios
• Coastal direct/indirect (UN Millennium Ecosystem Assessment) and dweller ICZM intention based on surveys (CVM and Behavior Theory of Collective Action)
Drivers and PressuresDrivers and Pressures
Coastal Population: 413,000 to 567,000Density: 390-1,000 population/km2
Northern Population 1997-2030: +41%GDP net growth: +6% (04) +2% (05-11)Urbanization: 74%; air, solid/liquid wasteIndustrialization: cement and fertilizersTrade: Tripoli port serving the hinterlandTourism: 42 beaches, resorts and hotelsFisheries: unsustainable practicesExtraction: salt marshes: a dying activityAgriculture: land erosion, water qualityWatersheds: municipal effluents; runoffMountain: deforestation; terrace collapse
MunicipalitiesMunicipalitiesThree typologies of municipalities are available:•• Four Cities/Towns (population: 312,000):Four Cities/Towns (population: 312,000):
Minieh, Tripoli, El Mina and Batroun
•• 17 Villages (population: 98,000):17 Villages (population: 98,000):Qlayaat, Qobet Shamra, Bebnin, El Mhamra, Bhanine, Deir Ammar, Bedawi, Ras Maska, Kalamoun, Kelhat, Anfeh, Chekka, El Herri, Hamat, Selaata, Koubba and Kfar Abida
•• Two Federations of Municipalities (population: 338,000)Two Federations of Municipalities (population: 338,000)Minieh Federation (Minieh, Deir Ammar, Bhanine) Fayha’a Federation (Tripoli, El Mina and Beddawi)
Villages w/o municipalities (Mohafaza Jurisdiction)•• Three orphaned Villages (population: 3,000):Three orphaned Villages (population: 3,000):
Arida, Cheikh Zennad and Rmoul
MunicipalitiesMunicipalitiesMohaf. /Casa
City/Village (north to south)
Number of Municipal Council members
Actual Number of Staff
Number of Staff Authorized by Law
Arida Under Mohafaza Jurisdiction Cheikh Zennad Under Mohafaza Jurisdiction Rmoul Under Mohafaza Jurisdiction Qleiat 12 3 6 Qoubbet Chamra 9 0 3 Bebnin 18 2 13
Akkar
Al Mehamra 10 2 5 Minieh Federation 3 NA NA Bhanine 15 2 6 Minieh 21 11 12 Deir Ammar 15 3 7
Minieh- Dennieh
Beddawi 15 30 42 Fayha’a (Tripoli) Federation 3 35 240 Tripoli 24 640 1,000 Tripoli El Mina 21 63 132
Koura Ras Maska 9 4 5 Tripoli Qalamoun 15 8 9
Kelhat 9 2 2 Koura Anfeh 15 5 5 Chekka 15 8 8 El Herry 9 2 7 Hamat 12 2 8 Selaata 8 4 7 Koubba 9 2 3 Batroun 15 15 20
Batroun
Kfar Abida 9 1 3 Total 291 844 1,543 Source: Municipal Budget Statements (2004-06); and study’s compilation.
Aggregate Municipal Budgets Aggregate Municipal Budgets
Municipal Revenues
Direct RevenuesCity: 39%
Village: 25%
Indirect RevenuesCity: 42%
Village: 52%
Taxes e.g. wastewater network
and sidewalkmaintenance tax ($2/capita/year)
Government transfers are decreasing/
backloggedCity: 36%
Village: 43%
Utility transfers are decreasing/ backlogged
City: 6%Village: 9%
Aggregate Municipal Revenues Aggregate Municipal Revenues
Municipal Expenses
Administrative ExpensesCity: 70%
Village: 19%
Maintenanceand Investments
City: 17%Village: 67%
MaintenanceCity: 8%
Village: 45%
InvestmentsCity: 9%
Village: 22%
Extra Budgetary Investments (CDR)
??
Aggregate Municipal Expenses Aggregate Municipal Expenses
Municipal ServicesMunicipal Services
Solid Waste:Solid Waste:Solid waste is being mishandled across the board except in:
1.Tripoli has a sanitary landfill under CDR implementation with possible carbon funding
2.Minieh (sorting and composting) under CDR implementation
3.Beddawi (sorting and composting) under CDR implementation
4.Hamat (sorting but unsanitary landfill)
Municipal ServicesMunicipal ServicesWaste Water Treatment:Waste Water Treatment:
With few exceptions, effluents are unloaded without any treatment into the sea or river beds.
1. A small wastewater treatment plant is operational in Batroun (old city)
2. Waiting to be connected to the sewer network in Chekka
3. Being built in Greater Tripoli4. Being planned in Bebnin and Batroun
Air Pollution:Air Pollution:No serious efforts at curbing air pollution from point and non-point sources, except in Chekka
Municipal Qualitative AssessmentMunicipal Qualitative Assessment•• Promising & GrowingPromising & Growing in Bebnin, Minieh & Ras
Maska - try to improve their urban environmental health with their meager means
•• Well establishedWell established in Tripoli & El Mina – TEDO funded under SMAP II to collect environmental indicators on air pollution to help decision-makers make informed choices
•• OpportunisticOpportunistic in Batroun- first coastal treatment plant funded by SMAP I and World Bank
•• ControversialControversial in Chekka & Selaata an industrial cluster –may greatly impact the environment &other stakeholders of the coastal zone
•• FrustratedFrustrated Anfeh cannot capitalize on its cultural heritage (salt marshes), because of bureaucratic complexity
Municipal Assessment SummaryMunicipal Assessment SummaryAlthough there is a municipal will to preserve the
commons, create healthy environments and ensure livelihoods:
• Decentralization and Land use Strategy are on the back burner; poor governance; financial dependability (unclear policy to borrow, backlog, no powers to change taxes and fees); uncoordinated investments; etc.
• Narrow financial base: Limited revenues/funds (especially small municipalities)
• Limited municipal environmental services• Limited environment-related human resource
capacity except for Al Fayha’a (TEDO)
Coastline Economic ActivityCoastline Economic Activity
The partial GDP of the northern coast was estimated at $292.5 million in 2005:
- Industrial sector 57.5 % - Energy & Water Supply 14.5 %- Market Services mainly tourism 12.1 %- Agriculture (fishing & extraction) 7.5 %- Government mainly municipalities 6.8 %-Transportation & Communications 1.7 %-Construction N.A. except for Tripoli Port-Trade N.A.
Source: MoET (2007); and Author.
Selected Coastline Economic Selected Coastline Economic Activity Activity
ActivityActivity CharacteristicsCharacteristics Output Output Impact(2005)Impact(2005)
Household Household Income(2005)Income(2005)
Employment Employment (2005)(2005)
Beaches/MarinasBeaches/Marinas/Resorts/Resorts
On of the main contributors to the coastal economic activity
US$ 39.9 million/year Not obtained Not obtained
Fishing ActivityFishing Activity4 major fishing ports: Abdeh
(Bebnin), El Mina, Qualamoun, & Batroun
US$ 27.7 million/year US$ 14.4 million/year 3,347 fishermen
Traditional Salt Traditional Salt ExtractionExtraction
7,000 tons/yearbought at about US$ 20/ ton &
sold at US$ 50/ ton
US$ 0.14 million/year US$ 0.12 million/year 60 workers
BoatingBoating
seasonal activity in El Mina mainly between May and Nov.
Trip costs US$ 100/day, 30 boats, passenger capacity 30,
3 crew members
US$ 0.12 million/year US$ 0.09 million/year 90 sailors
Boat Boat ConstructionConstruction
performed on the El Mina quayside and consists of
wooden and fiberglass boats
US$ 0.33 million/year US$ 0.13 million/year 30 craftsmen
Selected Coastline Economic Selected Coastline Economic ActivityActivity
Industry in 2005:Industry in 2005:A.A. Cement industry in Chekka:Cement industry in Chekka: 2 major players
supplying Lebanon, Cyprus, Syria, Iraq, etc. • $100 million in value-added• 4,500 million tons• 918 employees
B.B. Fertilizer Industry in Selaata:Fertilizer Industry in Selaata: The Lebanon Chemicals Company (LCC) operates in a free zone and exports exclusively to Europe.
• $68 million in value-added• 664,000 ton/year of sulfuric acid,
180,000 ton/year of phosphoric acid &85,000 tons/year of phosphatic fertilizers
• N.A. employees
Economic Activity SummaryEconomic Activity Summary• Coastal Area hosts a variety of economic activities:
industries, tourism (boating, marinas), agriculture, resource extraction, etc.
• National GDP main contributor is tourism; coastline GDP main contributor is industries, which give them some leverage (free loader)
• The fishing sector is the single largest employer on the coast second to the tourism sector (unavailable labor statistics)
• Trade-offs between stakeholders are distorted: Industry vs. Tourism vs. Extraction; Community vs. Municipality; Community vs. Industry/Tourism, etc.
DirectDirect--Indirect Resource UseIndirect Resource UseThe survey targeted several issues:
1. Relative importance of the CZ
2. CZ risk perception
3. The entity most suited to managing the CZ
4. Trust among community members for collaboration on a hypothetical ICZM program
5. Willingness to pay to preserve the CZ yearly value on the CZ in general and the marine resource in particular
And performed regressions
DirectDirect--Indirect Resource UseIndirect Resource UseBut first let us define the total economic value of a
resource:
1. Direct-use consumptive (goods and services consumed by users in terms of resource extraction such fish, oil, gas, sand, salt, pearls, etc.)
2. Direct-use non-consumptive (services such as recreational, educational, etc.)
3. Indirect use (services provided by ecological systems)
4. Passive use (option and bequest to endow the resource to future generations)
5. Intrinsic value (all organism valuable regardless of the monetary value placed by society)
DirectDirect--Indirect Resource UseIndirect Resource Use
• Sample: 382 Dwellings: 95% confidence level; ±5% confidence interval
• Male (67%); Female (33%); HHH (73%)
• Education > secondary (60%); < secondary (40%)
• Income > relative poverty (42% -close to IMF 2005); < relative poverty (58% -close to 2002 USJ)
• Village Dweller (26%); City Dweller (74%)
DirectDirect--Indirect Resource UseIndirect Resource Use
• ICZM knowledge: 23% knew about it
• Relative CZ importance: DCU (74%); DNCU (80%); IU (83%); EH (93%)
• Combined risk perception of the CZ is very high (96%) with minimal variation across determinants
• Liquid/solid waste fee = $7 per capita from the survey whereas it is only $2 per capita from actual municipal budgets
DirectDirect--Indirect Resource UseIndirect Resource Use
4 ICZM Choices were suggested
Non-Gov Mgt
PS: 37%
NGO: 6%
Other: 3%
Distrust in Community: 39%
DirectDirect--Indirect Resource UseIndirect Resource UseWTP Acceptability rate is 64%; WTP represents 0.5% of
income and 0.4% (truncate WTP at 88%)WTP Mean: $41/year/HH; $12/year/per capitaWTP Median: $12.9/year/HH; $2.4/year/per capitaIncome ε of mean WTP: 0.62 with 0.51 (Non-Gov)
DirectDirect--Indirect Resource UseIndirect Resource Use
Regression results:• 9 predictors determined ¼ of the WTP results• Risk perception significantly predicted non-Gov WTP• Risk perception suggestively predicted other 3 choices• In a distrust intention, odds are the highest for WTP
choices against non-WTP, i.e., the more distrust, the highest the odds of having a choice with WTP:– Odds of 4.4 selecting choice GovWTP over GovnonWTP– Odds of 2 selecting choice nonGovWTP over GovnonWTP– Odds of 2.4 selecting choice WTP over nonWTP
Direct & Indirect Res. Use Direct & Indirect Res. Use SummarySummary
• Although people are aware of the CZ risks:Median WTP per capita ≈ Waste Fee per capita
• This warrants an awareness campaign to sensitize the population on CZ risks and management responsibilities
• There is a distrust across the board: municipality in themselves to manage the commons (financial/HR constraints); the community in the government to manage the CZ (governance); the community in other members and stakeholders among themselves (vested interest).
ConclusionConclusion• There is a clear demand for change from the
population, however, there is a distrust: in the government to deliver (devolve resp.); and other members to participate in an ICZM program
• There is land-use competition between urbanization, tourism, industry & agriculture along the coast
• The trade-off between economic development/growth, social equity and the protection of the commons is poorly considered
• The government (at the central and municipal level) is constrained financially and does not have a federative approach: CDR is an executing agency
ConclusionConclusion• How do we resolve the policy (ways to achieve
change) and institutional (instruments to achieve change) and market failures that are leading to the CZ problems in this context?
• Is the introducing a tax for CZ conservation appropriate given the circumstances?
• Does building trust in an informal forum and starting discussing trade-offs among various stakeholders a solution?
• What are the appropriate ways and instruments of reform?
Discussion!Discussion!
Paper available on:Paper available on:www.balamand.edu.lb/english/IMAC.asp?ID=www.balamand.edu.lb/english/IMAC.asp?ID=
87638763
EEnd of nd of SSession ession 12a12a
Thank YouThank You
REGIONAL WORKSHOP ONREGIONAL WORKSHOP ON
THE COST OF ENVIRONMENTAL THE COST OF ENVIRONMENTAL DEGRADATION METHODOLOGYDEGRADATION METHODOLOGY
Session 12bClimate Change Adaptation in the Water Sector in the Middle East & North Africa
Region: A Review of Main Issues
ContentContent
• What is Climate Change (CC)?
• What is the MENA Water Sector State (WS)?
• How Will CC Affect the MENA WS State?
• What are the Suggested Responses?
What is Climate Change?What is Climate Change?• CC is any long-term significant change in
the average temperature of the Earth's near-surface air and oceans that a given region experiences
• CC is human-made: science established a causal effect between the acceleration of Green House Gas (GHG) emissions and CC effects in the IPCC 4
• GHG (CO2, CH4 and N2O) emissions shot past a safe level of 350 ppm by the end of the 80s and stand at 385 ppm per volume in the Earth’s atmosphere
What is Climate Change?What is Climate Change?• Six scenarios with different assumptions
were developed to simulate GHG projections and their effects on CC until 2100
Source: IPCC 4 (2007).
What is Climate Change?What is Climate Change?• Main GHG emission effects on CC are:
-Average global surface temperature will likely rise between 0.6° to 4° Celsius by 2100
Source: IPCC 4 (2007).
What is Climate Change?What is Climate Change?• Increases in the amount of precipitation are
very likely in high-latitudes, while decreases are likely in most subtropical land and semi-arid regions (by as much as about 20% in the A1B scenario in 2100
• In semi-arid areas, droughts will increase and runoffs will decrease
• The ice cap will shrink and sea level will rise by a likely range between 0.18 and 0.59 meter by 2100
What is the MENA Water Sector What is the MENA Water Sector State?State?
• 3 aspects of the water sector are covered:-Renewable Water (RW) Availability in 2004-Water Use in 2004-Water Services in 2004
• But first, a definition of RW availability:-Water security: ≥ 1,700 m3 pc pa of RW-Water stress: ≥ 1,000 and < 1,700 m3 pc pa of RW-Water scarcity: ≥ 500 and < 1,000 m3 pc pa of RW-Water absolute scarcity: < 500 m3 pc pa of RW
What is the MENA Water Sector What is the MENA Water Sector State?State?
RW Availability. MENA region: • Most water stressed region in the world (1,100 m3)• 3 water groups: arid, hyper-arid and transboundary
RW
PC
PA
RW PC PA
Source: FAO-AQUASTAT (2002) compiled in World Bank (2007a).
What is the MENA Water Sector What is the MENA Water Sector State?State?
RW Availability. MENA region is characterized by• Aridity, desertification and coastal density; and
by
Source: FAO-AQUASTAT (2002) compiled in World Bank (2007a).
What is the MENA Water Sector What is the MENA Water Sector State?State?
• low precipitation, high evaporation, and increased droughts, flooding and weather extreme
People Affected by Floods, Droughts and Extreme WeatherMENA Region 1988-07 (000')
0
10
1,000
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
Year
Peop
le A
ffect
ed
(log
sca
le)
FloodDroughtExtreme Weather
Source: FAO-AQUASTAT (2002) compiled in World Bank (2007a); and Author.
What is the MENA Water Sector What is the MENA Water Sector State?State?
Water Use. MENA region is characterized by:• Highest RW withdrawal region (75%); and by
Water Use Share Total Water Withdrawal to Total Renewable
Source: FAO-AQUASTAT (2002) compiled in World Bank (2007a).
What is the MENA Water Sector What is the MENA Water Sector State?State?
• An important share allocated to the agriculture sector (±85%) with low value-added GDP per km3 (US$ 701) and low yield
• An increased reliance on desalination to augment water supply
Sector Water Use
Source: FAO-AQUASTAT (2002) compiled in World Bank (2007a).
What is the MENA Water Sector What is the MENA Water Sector State?State?
Water Services are characterized by:• Inadequate governance (accountability, planning,
financing, organizational capacity, etc.) affecting both access (87%) and water-related diseases (22 death per 100,000 from diarrhea mainly in rural)
• Poor utility performance (water losses between 30 and 60% and operating cost coverage ratio less than 1; and
• Low agricultural water requirement ratio that measures the agricultural efficiency and ranges between 0.3 and 0.5.
How Will CC Affect the MENA WS How Will CC Affect the MENA WS State?State?
Source: IPCC 4 (2007).
Impact on 5categories but we willfocus onwater
and health
How Will CC Affect the MENA WS How Will CC Affect the MENA WS State?State?
• The CC effects in the MENA region by 2050 are (figures should be used with care):– Higher temperatures by +2.5 degree C– Lower precipitation by >-10.5%– Lower runoffs between -20 and -30%– Sea level rise by 0.39 meter.– Accelerating drought cycle especially in NAfrica– Burden of disease marginal increase (water-
related, cardio-respiratory and vector-borne diseases, malnutrition and injuries)
How Will CC Affect the MENA WS How Will CC Affect the MENA WS State?State?
• Demographic growth (+2% in 2000s) will put more pressure on RW with an urban population increasing by 93% between 1995-2050
• RW pc pa will decrease by more than half to less than 550 m3 putting the region in water absolute scarcity state
• Water Use: Domestic share will exceed 20% putting additional stress on the agriculture sector
• Water Services: all governance, access, efficiency and water-related disease indicators will deteriorate
How Will CC Affect the MENA WS How Will CC Affect the MENA WS State?State?
2050 MENA RW: M3 Per Capita
-
500
1,000
1,500
2,000
2,500
3,000
Iran
Leba
non
Morocc
o
Tunisi
a
Algeria
Djibouti
Oman
WB & Gaz
aYem
enJo
rdan
Bahrai
nLib
ya
Saudi
Arabia
Qatar
UAEKuw
aitIra
qSyri
aEgy
pt
Arid Hyper-Arid Transboundary
M3 p
er c
apita
2050 RW PC
Without CC With CC
Source: FAO-AQUASTAT (2002); United Nations (2007); and Author
2050 MENA RFW with -20% CC Effects: M3 Per Capita
-
500
1,000
1,500
2,000
2,500
3,000
Iran
Leba
non
Morocc
o
Tunisi
a
Algeria
Djibouti
Oman
WB & Gaz
aYem
enJo
rdan
Bahrai
nLib
ya
Saudi
Arabia
Qatar
UAEKuw
aitIra
qSyri
aEgy
pt
Arid Hyper-Arid Transboundary
M3 p
er c
apita
2050 RW PC
2004 MENA RFW: M3 Per Capita
-
500
1,000
1,500
2,000
2,500
3,000
Iran
Leba
non
Morocc
o
Tunisi
a
Algeria
Djibouti
Oman
WB & Gaz
aYem
enJo
rdan
Bahrai
nLib
ya
Saudi
Arabia
Qatar
UAEKuw
aitIra
qSyri
aEgy
pt
Arid Hyper-Arid Transboundary
M3 p
er c
apita
2004 RW PC
How Will CC Affect the MENA WS How Will CC Affect the MENA WS State?State?
Runoff Reduction by 2100
Source: IPCC 4 (2007).
Drought Severity by 2100
What are the Suggested What are the Suggested Responses?Responses?
• The MENA region public and private human, social, capital, natural and cultural assets at stake from future CC effects
• Three responses are suggested:– Knowledge response– Mitigation response– Adaptation response
What are the Suggested What are the Suggested Responses?Responses?
• Better knowledge response-Transparent awareness campaign (proactive
media and universities) could help ensure an inclusive and participatory CC mitigation/ adaptation planning and implementation process
-Mainstream CC in school and university curriculum-Adapt/set up knowledge-based CC infrastructure
(GIS, meteorological indicators, hydrological cycle, etc.)
What are the Suggested What are the Suggested Responses?Responses?
• Better adaptation response– MENA region contributes between 3.5 and
5% to the global GHG emissions but the emissions growth has outpaced all the other regions (1995-2004)
– Opportunity to improve energy efficiency (electricity and energy) by tapping carbon funding mechanism and switching to abundant renewable energies (solar and wind in some regions)
What are the Suggested What are the Suggested Responses?Responses?
• Better mitigation response requires climate-proof sector-wide water reforms by:– Balancing water demand (water allocated to
its highest use value) and supply (e.g., drip irrigation, water reuse, desalination) and build-in system responsive to variations
What are the Suggested What are the Suggested Responses?Responses?
-Improving governance (e.g., integrated planning, organization, decision-making, management and resource mobilization), equity, justice and preservation of the commons
-Increasing efficiency (agriculture, domestic)
-Enhancing natural disaster and health service preparedness
What are the Suggested What are the Suggested Responses?Responses?
• Water sector reforms could already help contain, delay and mitigate CC effects (Morocco has embarked on a long term programmatic reform with the World Bank)
• Looking at reducing the distortions of drivers could also help increase the effectiveness of water sector reforms (coherent growth strategy that encompasses population, poverty, urbanization, tourism and agriculture drivers) and increase the climate-proofing efforts
EEnd of nd of SSession ession 12b12b
Thank YouThank You
Introduction of the Carbon Funding of Introduction of the Carbon Funding of Waste Emission PresentationWaste Emission Presentation
Source: IPCC 4 (2007).
Global GHG emissions (in Giga tons or billion of tons) are illustrated by compound and sector over the 1970-2004 period.
REGIONAL WORKSHOP ONREGIONAL WORKSHOP ON
THE COST OF ENVIRONMENTAL THE COST OF ENVIRONMENTAL DEGRADATION METHODOLOGYDEGRADATION METHODOLOGY
Session 12cCarbon Finance Instrument to Improve Coastal Zone Solid Waste Management
Waste and ICZMWaste and ICZM
• Situation for solid waste? – Collection of municipal solid waste; – Waste separation/recycling;– Controlled sanitary landfills & composting
Collection of MSWCollection of MSW Waste separation / recyclingWaste separation / recycling
Controlled sanitary landfillsControlled sanitary landfills The real world is differentThe real world is different
Challenges Challenges • Need to design and enact adequate financial
and economic incentives to encourage behavioral changes in human activities in the coastal areas
• Self-standing ICZM capacity building interventions often do not accomplish much
• Support for institutional strengthening, restructuring, and policy reform works best in the context of a holistic, longer-term programmatic operation that links policy interventions with tangible benefits on the ground
• Catalyzing and sustaining ownership at the national, local, and community levels
How can CF solve some of How can CF solve some of these problems?these problems?
• Promoting environmental protection and sustainable economic activities
• By providing revenues for:– Improvements in solid waste management;– Improvements in sewage systems.
• By channeling revenues at the local level (Municipalities)
The Kyoto ProtocolThe Kyoto Protocol• Kyoto commitments
– In 1997, 38 Industrialized Countries committed to reduce GHG emissions by 5% below 1990’levels (entered into force in 2005)
• Kyoto targets are basically achieved by – Domestic reduction of GHG emissions– Trading emission permits (“allowances”) among
companies (EU-ETS) and Assigned Amounts Units (“AAUs”) among governments
– Purchase GHG emission reductions from projects
» In developing countries (Clean Development Mechanism – CDM)
» In economies in transition (Joint Implementation)
Carbon Finance is NOT about Carbon Finance is NOT about ……• CF is NOT about carbon only, but 6 Greenhouse Gases (GHGs):
– Carbon dioxide (CO2), – Methane (CH4) = 21x more potent than CO2, – Nitrous oxide (N2O) = 310x,– Sulphurhexafluoride (SF6) = 23,900x,– Hydrofluorocarbons (HFCs) HFC23 = 1,300x,– Perfluorocarbons (PFCs) CF = 46,500x, C2F = 69,200x– To promote understanding and facilitate calculations, all GHGs are
measured in tons of CO2 equivalents (CO2-e): 1 ton CO2-e = 1 “carbon credit”
• CF is NOT about Finance:– No loan, no grant, no line of credit, but PURCHASE
• CF is NOT about Financing (i.e., promoting) Carbon, but:– Purchase of GHGs REDUCTION, mainly through long-term agreements
(ERPAs)• GHGs can be avoided (e.g., CH4 avoidance in composting projects),• GHGs can be mitigated (e.g., CO2 mitigation in RE/EE projects) or• GHGs can be sequestered (e.g., CO2 sequestration in LULUCF activities)
Industrialized country with an emissions cap
Baseline em
issions
Baseline Scenario
Developing country/economy in
transition with no emissions cap
EmissionReductions (ERs)
Project em
issions
Project Scenario
Emissions target
Developing country/economy in transition benefits from technology
and financial flows
$$
ER
Purchase of ERs
Domestic action
Carbon CreditsCarbon Credits How does Carbon Finance work How does Carbon Finance work for a landfill?for a landfill?
• Baseline Scenario = generation of CH4• Capture of CH4:
– Avoided emissions = emission reductions (ER)• ER will be generated during the lifetime of the
landfill• ER can be sold: additional revenues to
improve IRR and cash flow • Works also with composting, wastewater
treatment, etc.• Incentive to collect and operate the landfill
adequately, otherwise no ER will be generated
BORG EL ARAB & EL HAMMAM BORG EL ARAB & EL HAMMAM LANDFILLS, ALEXANDRIA EGYPTLANDFILLS, ALEXANDRIA EGYPT
© Veolia Propreté/Onyx
LandfillsLandfills
• Before
• After
Description of the ProjectDescription of the Project• 18 districts within the city covering a 7,200km2 area• The services provided under the contract include:
– Street Cleaning Program: daily manual and mechanical sweeping covering over 12,000 km of city streets and roadways
– Household waste collection: collection of 1 million tons of waste per year
– Waste Transfer: 3 transfer stations were put in service to limit the vehicle number transporting waste from the city to treatment centers
– Landfills : 2 modern landfills were constructed– Composting : 3 composting centers are operated
and produce over 120,000 tons of compost pa
Environmental Benefits of Environmental Benefits of controlled landfillscontrolled landfills
• Flaring of the collected LFG does not only destroy methane, but also destroys compounds in the LFG, such as volatile organic compounds and ammonia.
• Prevention of risks associated with landfill gas at uncontrolled landfills:– Risk of explosion– Risk of fire– Unpleasant odor nuisances– Potential atmospheric pollution– Damage to vegetation by asphyxia
Benefits of the ProjectBenefits of the Project• Environmental Benefits:
– Preservation of water resources – Uncontrolled dumps have been replaced by engineered modern landfills with fully lined disposal areas for leachate (wastewater produced by the landfill) containment
– Fight against desertification and depleted soil – The local production of compost provides much needed organic soil amendments
• Social benefits:– Improvement of environmental health– Employee training
• Economical benefits:– Creation of 4,500 job opportunities– Retrocession of a percentage of the value of the
generated credits to the Governorate of Alexandria
CF: What is next ?CF: What is next ?• Project by
project: higher transaction costs, lower predictability for project owners, and non-transformational impact on emissions
• Programmatic:larger scale, better planning environment for project owners, and transformational impact on emissions
Future of Carbon FinanceFuture of Carbon Finance
• New methodologies, including small scale• Post 2012 regime?• Carbon Partnership Facility: sustaining the
market under transitional phase and increase investments by ensuring long-term C-revenues. Open to consider future assets and regimes
EEnd of nd of SSession ession 12c12c
Thank YouThank You
REGIONAL WORKSHOP REGIONAL WORKSHOP ONON
THE COST OF THE COST OF ENVIRONMENTAL ENVIRONMENTAL
DEGRADATION DEGRADATION METHODOLOGYMETHODOLOGY
Session 13COST BENEFIT ANALYSIS
REGIONAL WORKSHOP ONREGIONAL WORKSHOP ON
THE COST OF ENVIRONMENTAL THE COST OF ENVIRONMENTAL DEGRADATION METHODOLOGYDEGRADATION METHODOLOGY
Session 13COST BENEFIT ANALYSIS
COST BENEFIT ANALYSISCOST BENEFIT ANALYSISIntroductionIntroduction
• One of the most widely used techniques for project appraisal in the public sector
• Represents a framework for policy decision-making
“Measure a hundred times but cut only once” Proverb
• A technique to evaluate the worth of an idea or project
• A comparison of alternatives• An aid to decision making• A means of looking back to
evaluate choices that have been made
COST BENEFIT ANALYSISCOST BENEFIT ANALYSISIntroductionIntroduction
• Origins of Cost Benefit Analysis: US Flood Control Act of 1936– The Federal government should improve or
participate in the improvement of navigable waters and their tributaries, including watersheds thereof, for flood control purposes if benefits to whomsoever they may accrue are in excess of the estimated costs, and if the lives and social security of people are otherwise adversely affected.
COST BENEFIT ANALYSISCOST BENEFIT ANALYSISTheoryTheory
• Measures of benefit– Demand curve also
referred to as marginal benefit curve
• Indicates the benefit of consuming one extra unit of a good
• Provides an idea of changes in ‘utility’ or level of satisfaction
B0
A
Demand Curve
Quantity
Pric
e pe
r un
it C
D
The price one is willing to pay for a good depends on the satisfaction one derives from consuming it, which is taken
as a MEASURE OF BENEFITS
E
COST BENEFIT ANALYSISCOST BENEFIT ANALYSISTheoryTheory
• Measures of benefit– For environmental goods
the benefit or WTP exceeds the market price (if it exists)
– Valuation methods discussed earlier are used to obtain estimates of WTP
B0
A
Demand curve
Quantity
Pric
e pe
r un
it C
D
E
Total benefits = Total Revenue + Consumer Surplus= Area of 0CED + Area of ΔACE
COST BENEFIT ANALYSISCOST BENEFIT ANALYSISTheoryTheory
The concept of costs– Opportunity cost (OC) to carrying out the
investment
– Under perfect competition, the OC of a good is the same as the market price of that good
– For environmental goods, there is no market-price
• Alternative methods to be used to measure OC
COST BENEFIT ANALYSISCOST BENEFIT ANALYSISTheoryTheory
The concept of Net Social Benefits– It is important to distinguish between a social CBA and a
private CBA• Social CBA
– conducted from a society’s perspective– Referred to as economic analysis
• Private CBA– Carried out from an individual investor’s view point– Referred to as financial analysis
• A project may be financially viable but socially undesirable
– The objectives of a social CBA is to determine whether a project is socially beneficial
• Net Social Benefit (NSB) = WTP – OC > 0
– If NSB > 0, then the state can use the surplus to compensate the losers
COST BENEFIT ANALYSISCOST BENEFIT ANALYSISSteps in Conducting an SCBASteps in Conducting an SCBA
Case Case descriptiondescription
COST BENEFIT ANALYSISCOST BENEFIT ANALYSISSteps in Conducting an SCBASteps in Conducting an SCBA
CEA Vs. CBA
CaseCase--StudyStudyBintuli Wastewater Treatment ProjectBintuli Wastewater Treatment Project
• City of Bintuli in the Republic of Kabastan– Center of commerce and industry– Main industries include
• Metal manufacturing• Coal extraction• Chemical manufacturing• Construction• Paper making• Food processing
– Value of industrial output estimated at 200 million USD in 1990 as compared to 16 million USD for agriculture
CaseCase--StudyStudyBintuli Wastewater Treatment (WWT) ProjectBintuli Wastewater Treatment (WWT) Project
• Quantities of domestic and industrial effluents in water bodies increased– Total industrial effluent = 163,700 m3/day– Total effluent including domestic WW = 271,700 m3/day– 30% of industrial effluent treated– 0% of domestic effluent treated
• River courses in the city turned black and emit unpleasant odors
• Proposal to build a WWT facility with pumping stations and drainage networks– To treat 28% of industrial waste and the remaining domestic
waste– Treated effluent discharged in river to be used by industries and
agriculture
COST BENEFIT ANALYSISCOST BENEFIT ANALYSIS1. Defining objectives and project scope1. Defining objectives and project scope
• Objective often specified by decision-makers in the bureaucracy
• Objective should be clear and unambiguous
• Bintuli WWT Project– Objectives:
• To improve the health of the community• To increase economic activity by improving
wastewater treatment facilities in the city
COST BENEFIT ANALYSISCOST BENEFIT ANALYSIS2. Identifying and screening alternatives2. Identifying and screening alternatives
• List all possible options for reaching objectives• The ‘do nothing’ option should be considered• Preliminary screening of alternatives
• Bintuli Wastewater Treatment Project– Alternatives:
• Maintaining the status quo• Expanding the existing WWT facilities
– Ruled out because it uses outdated technology and would be difficult to maintain
• Building a new WWT facility• Various locations and site options
– Only one potential site considered in this application
COST BENEFIT ANALYSISCOST BENEFIT ANALYSIS3a. Identifying benefits and costs3a. Identifying benefits and costs
• Costs and benefits differ for an SCBA as compared to private investors– Benefit in an SCBA
• An outcome resulting in an increase in an individual’s utility– Cost in an SCBA
• An outcome resulting in a decrease in an individual’s utility
• Important notes– An incremental approach adopted in assessing costs and
benefits• Identify and value costs and benefits of the project• Compare with the situation to prevail without the project• The difference is the net incremental benefit arising from the project• Only additional changes in costs and benefits are considered, and not
total costs and benefits
COST BENEFIT ANALYSISCOST BENEFIT ANALYSIS3a. Identifying benefits and costs3a. Identifying benefits and costs
• Important notes (cont’d)– Sunk costs and benefits incurred before project commencement
must be excluded• Previous costs are not an opportunity cost as they do not represent a
loss of future income from an alternative use of resources
– Transfer payments must be excluded• Taxes, subsidies, loans, and debt services do not result in an increase
in net benefits• Taxes by foreign investors should be included
– Depreciation and interest are excluded from the cost in a SCBA• SCBA involves discounting values of capital items at their opportunity
costs– Including depreciation as a cost will result in double counting
• The discount rate in an SCBA already takes into account the interest– Including interest as a cost will result in double counting
COST BENEFIT ANALYSISCOST BENEFIT ANALYSIS3a. Identifying benefits and costs3a. Identifying benefits and costs
• Costs and benefits are normally classified into– Primary costs and benefits
• Related directly to the project– Secondary costs and benefits
• Arise from events and activities triggered by the project• Should be handled with care as they could exaggerate
estimates– Opportunity cost must be used as a guideline– Resources are sometimes merely transferred from one part of the
economy to another
• Costs and benefits may also be classified into – Market costs and benefits– Non-market costs and benefits
COST BENEFIT ANALYSISCOST BENEFIT ANALYSIS3a. Identifying benefits and costs3a. Identifying benefits and costs
Costs• Primary
– Investment• Construction of a pumping
station, office building, WWT facilities
• Purchase of equipment– Operation and
maintenance• Wages and salaries• Fuel and chemical costs• Other costs (project
management, preparation, training and commissioning
Benefits• Primary
– Economic • User charges
– Reduction in health costs and mortality rates
– Reduction in costs of treating increasingly polluted water supplies
– Increase in labor productivity due to reduction in absence from work due to illness
• Secondary– Benefits to industry and
agriculture from using recycled water
– Additional revenues from re-afforestation
– Increase in reed harvesting for the paper mill industry
Bintuli WWT Project
COST BENEFIT ANALYSISCOST BENEFIT ANALYSIS3b. Valuing benefits and costs3b. Valuing benefits and costs
• Allows comparison between alternatives• Valuation should be done according to the opportunity cost
principle– Prices of inputs that do not reflect their true value to the society
are adjusted- shadow pricing• Comparison of costs and benefits should focus on the with vs
without the project, rather than before vs. after the project
Valuing the costs• Find market prices for the inputs and outputs• All costs may be in present day or constant prices
– Costs incurred over the project lifetime must be valued at prices prevailing at the time of the project appraisal
– Assumes that annual costs increase at the inflation rate
COST BENEFIT ANALYSISCOST BENEFIT ANALYSIS3b. Valuing benefits and costs3b. Valuing benefits and costs
Valuing the costs• Residual values
– For assets with an economic life that exceeds the planning horizon or project life
• Economic life is the estimate of the duration of the operation of an asset before it requires refurbishment
– The residual or salvage value of the asset must be included as a cash inflow at the end of the planning horizon
– Calculated using• Linear method• Diminishing value method
COST BENEFIT ANALYSISCOST BENEFIT ANALYSIS3b. Valuing benefits and costs3b. Valuing benefits and costs
Valuing the costs• The linear method
– Assumes that the asset value declines linearly over time
Residual value at time t is (1-t/n)PWhere t = time; n = economic life; P = initial price
Ex: an asset purchased at $100,000 and has an economic life of 20 years, at the end of the planning period of 15 years, its residual value is (1-15/20)*100,000 = $25,000
• The diminishing value method– Assumes that the asset value declines by a fixed
proportion of the beginning of year value per annum Residual value at time t is (1-1/n)t P
COST BENEFIT ANALYSISCOST BENEFIT ANALYSIS3b. Valuing benefits and costs3b. Valuing benefits and costs
Valuing the costs• Land and pre-existing building and plant
– Property already owned by operating authority must be valued at opportunity costs– Opportunity costs should be current variations based on the most profitable alternative
uses• Staged construction
– When a project is to be constructed in stages• Only the portion of investment and operating costs to satisfy demand in the current planning
horizon must be attributed to the project• Working capital
– Often constitutes 2% of the total capital outlays– Must be considered as cash outflow at the time when capital expenditures are made
and cash inflow at the end of the project• Operating costs
– Include labor, utilities, supplies, repairs and maintenance, equipment hiring and leasing, insurance and administrative overheads
– To be estimated on an annual basis• Implicit costs
– Opportunity costs and social costs• Use of land, buildings, plants, already purchased by the local authority• Time spent on project by agency staff
COST BENEFIT ANALYSISCOST BENEFIT ANALYSIS3b. Valuing benefits and costs3b. Valuing benefits and costs
Bintuli WWT Project
Item Cost (million USD)
Investment costsBuildings and structures 3.42
Equipment and supplies 13.15
Total investment cost 16.57
O&M costsElectricity 0.68
Salaries 0.09
Chemicals 0.06
Maintenance 0.58
Other 0.21
Total O&M costs 1.62
COST BENEFIT ANALYSISCOST BENEFIT ANALYSIS3b. Valuing benefits and costs3b. Valuing benefits and costs
Valuing the benefits• Benefits of the Bintuli WWT project include
– Revenues from user charges– Economic benefits derived from WWT
• Reduced mortality• Productivity gained from reduced morbidity• Water treatment cost savings• Sale of recycled waster• Afforestation benefits• Reed harvesting
COST BENEFIT ANALYSISCOST BENEFIT ANALYSIS3b. Valuing benefits and costs3b. Valuing benefits and costs
Valuing the benefits• User charges
– New charges• Based on the principle of full cost recovery
– Estimated at 6.9 cents/m3
– 54.75 million m3/year of effluent treated– Annual revenue = 3.78 million USD per year
• Existing charges– 11.4 million m3/year already being treated– User charged set at 6.9 cents/m3
– Annual revenue = 0.61 million USD per year
Net incremental sales revenue 3.17 million USD by year 6 when the new plant is at full capacity
COST BENEFIT ANALYSISCOST BENEFIT ANALYSIS3b. Valuing benefits and costs3b. Valuing benefits and costs
Valuing the benefits• Recycled water benefits
– 60% of treated wastewater will be reused for irrigation and industrial purposes
– Opportunity cost estimated at 10 cents/m3
– Economic benefits = 66,000 USD at year 4– Economic benefits = 3.29 million USD per year by year 8
• Afforestation benefits– Pine and hard wood species planted on 142.8 ha– Net return for experimental plots =689 USD– Net benefit = 10,000 USD in year 8– Net benefit = 100,000 USD by year 17
• Reed harvesting– Reed harvesting for the paper mill industry over an area of 95.25 ha– Net returns = 258.4 USD per ha– Net benefit = 20,000 USD starting Year 6
COST BENEFIT ANALYSISCOST BENEFIT ANALYSIS3b. Valuing benefits and costs3b. Valuing benefits and costs
Valuing the benefits• Reduced mortality benefits
• Total income benefits– 10,000 USD in Year 4– 110,000 USD by the end of the project– Note that only half of the morbidities and mortalities were considered since the
project is planned to serve 50% of the Bintuli population
COST BENEFIT ANALYSISCOST BENEFIT ANALYSIS3b. Valuing benefits and costs3b. Valuing benefits and costs
COST BENEFIT ANALYSISCOST BENEFIT ANALYSIS3b. Valuing benefits and costs3b. Valuing benefits and costs
YearRecycled
water AfforestationReed
harvestingReduced mortality
Reduced morbidity
Water treatment
cost savings
Incremental economic benefits
1234 0.66 0.01 0.18 0.11 0.965 0.99 0.02 0.38 0.11 1.506 1.64 0.02 0.03 0.57 0.11 2.377 2.63 0.02 0.05 0.76 0.11 3.578 3.29 0.01 0.02 0.06 0.95 0.11 4.449 3.29 0.02 0.02 0.06 1.00 0.11 4.5010 3.29 0.03 0.02 0.06 1.06 0.11 4.5711 3.29 0.04 0.02 0.07 1.11 0.11 4.6412 3.29 0.05 0.02 0.07 1.17 0.11 4.7113 3.29 0.06 0.02 0.07 1.23 0.11 4.7814 3.29 0.07 0.02 0.08 1.30 0.11 4.8715 3.29 0.08 0.02 0.08 1.37 0.11 4.9516 3.29 0.09 0.02 0.09 1.44 0.11 5.0417 3.29 0.10 0.02 0.09 1.51 0.11 5.1218 3.29 0.10 0.02 0.10 1.59 0.11 5.2119 3.29 0.10 0.02 0.10 1.68 0.11 5.3020 3.29 0.10 0.02 0.11 1.76 0.11 5.39
Incremental economic benefits of Bintuli WWT project (million USIncremental economic benefits of Bintuli WWT project (million USD)D)
COST BENEFIT ANALYSISCOST BENEFIT ANALYSIS4. Calculating discounted cash flows and 4. Calculating discounted cash flows and
project performance criteriaproject performance criteria• Involves reducing future streams of benefits
and costs to their present values to enable comparisons to be made between alternatives
• Given a stream of benefits (B0, B1…Bn) and a stream of costs (C0, C1…Cn),
Net Present Value
where r = discount rate
∑= +
−=
+
−+
+
−+
+
−+−=
n
t nrnCnB
nrnCnB
r
CBrCB
CBNPV0 )1()1(
...2)1(22
111
00
COST BENEFIT ANALYSISCOST BENEFIT ANALYSIS4. Calculating discounted cash flows and 4. Calculating discounted cash flows and
project performance criteriaproject performance criteriaChoice of discount rate• Discount rate in SCBA reflects society’s preferences between
present and future consumption– High discount rate
• implies that society has a stronger preference for present consumption over future consumption
– Low discount rate• implies that society has a stronger preference for future consumption
over present consumption– Choice of discount rate controversial– Environmentalists argue against high discount rates– Economists tended to use long-term interest rates on
government bonds as a measure of opportunity cost of capital• Rate of 10 percent in US• Rate of 8 percent in Australia
• Discount rate must be real rate– Interest rate minus inflation rate
COST BENEFIT ANALYSISCOST BENEFIT ANALYSIS4. Calculating discounted cash flows and 4. Calculating discounted cash flows and
project performance criteriaproject performance criteriaPeriod of analysis• Planning period varies with nature of project
– Should be determined by a period within which estimates are made with a certain degree of confidence
– Should correspond to the economic life of the projectChoice of project performance criteria• These include
– Net present value (NPV)– Benefit-cost ratio (BCR)– Internal rate of return (IRR)– Payback period
COST BENEFIT ANALYSISCOST BENEFIT ANALYSIS4. Calculating discounted cash flows and 4. Calculating discounted cash flows and
project performance criteriaproject performance criteriaChoice of project performance criteria• BCR
– the ratio of the present value of project benefits to the present value of the project costs
• Payback period– The number of years required for a project to recover its costs
• Discriminates against projects with high capital expenditures and long-term benefits
• Not recommended as a measure of project worth
∑=
+
∑=
+=
++
++
++
++
++
++
= n
tnrnC
n
tnrnB
nrC
r
Cr
CC
nrB
r
Br
BBBCR
n
n
0)1(
0)1(
)1(...2)1(10
)1(...2)1(10
21
21
COST BENEFIT ANALYSISCOST BENEFIT ANALYSIS4. Calculating discounted cash flows and 4. Calculating discounted cash flows and
project performance criteriaproject performance criteriaChoice of project performance criteria• IRR is the discount rate at which the present value of
project benefits equals the present value of project costs– It represents the maximum interest rate at which a project
could recover the investment and operating cost and still break even
– May not exist or may not be unique– Difficult to calculate– Trial and error method must be used
0)1(
...2)1(22
111
00 =+
−+
+
−+
+
−+−
ninCnB
i
CB
i
CBCB
COST BENEFIT ANALYSISCOST BENEFIT ANALYSIS4. Calculating discounted cash flows and 4. Calculating discounted cash flows and
project performance criteriaproject performance criteriaChoice of project performance criteria• The rule is to accept a project when
– NPV ≥ 0– BCR ≥ 1– IRR > the social OC of capital
• NPV most preferred criterion because it provides an estimate of the size of the Pareto improvement
• If two or more projects have NPVs > 0, then IRR can be used to rank them
COST BENEFIT ANALYSISCOST BENEFIT ANALYSIS4. Calculating discounted cash flows and 4. Calculating discounted cash flows and
project performance criteriaproject performance criteriaBintuli WWT project• Discount rate
– Real rate of 12%
• Planning period– 20 years
• NPV at the 12% discount rate = 12.08 million USD
• IRR = 21% which is above the opportunity cost of capital of 12 %
• The project is economically viable
YearIncremental
economic costsIncremental
sales revenue
Incremental economic benefits
Incremental net benefits
1 2.01 -2.012 8.45 -8.453 6.11 -6.114 2.42 1.91 0.96 0.455 1.62 1.91 1.5 1.796 1.62 3.17 2.37 3.927 1.62 3.17 3.57 5.128 1.62 3.17 4.44 5.999 1.62 3.17 4.50 6.05
10 1.62 3.17 4.57 6.1211 1.62 3.17 4.64 6.1912 1.62 3.17 4.71 6.2613 1.62 3.17 4.78 6.3314 1.62 3.17 4.87 6.4215 1.62 3.17 4.95 6.5016 1.62 4.43 5.04 7.8517 1.62 4.43 5.12 7.9318 1.62 4.43 5.21 8.0219 1.62 4.43 5.30 8.1120 -0.02 4.43 5.39 9.84
Incremental economic benefits of Bintuli WWT project (million USIncremental economic benefits of Bintuli WWT project (million USDD
COST BENEFIT ANALYSISCOST BENEFIT ANALYSIS5. 5. Conduct a sensitivity analysis and/or Conduct a sensitivity analysis and/or
risk analysisrisk analysis• Risk
– Potential outcome whose magnitude and probability of occurrence are known or can be determined
• Uncertainty– Situation where the magnitude of the outcome may or may
not be known and the probability of occurrence is unknown• Distinction between the two may not be clear-cut• Common methods for accounting for risk and
uncertainty– Sensitivity analysis– Break-even analysis– Cross-over values– Risk analysis
COST BENEFIT ANALYSISCOST BENEFIT ANALYSIS5. 5. Conduct a sensitivity analysis and/or Conduct a sensitivity analysis and/or
risk analysisrisk analysisSensitivity analysis• Used to assess the possible impact of uncertainty by posing
‘what if’ questions• Highlights the critical factors affecting the project’s viability• Parameters subjected to sensitivity analysis include
– Discount rate– Length of project planning horizon– Different timing of the project’s operation– Changes in the capital outlays– Changes in the price of non-market goods– Changes in social and environmental benefits and costs
• Carried out by recalculating project performance criteria using a range of values for the uncertain parameter
• Project performance criteria commonly used are NPV and IRR
COST BENEFIT ANALYSISCOST BENEFIT ANALYSIS5. 5. Conduct a sensitivity analysis and/or Conduct a sensitivity analysis and/or
risk analysisrisk analysisSensitivity analysis• Methodology
– Determine a realistic range of values for the variables that are subject to uncertainty.
• Example– Capital cost ± 30 percent– O&M costs ± 30 percent– Product prices ± 30 percent
– Calculate the effect of possible changes on the project selection criteria, while varying one variable and holding the others constant
– Reconsider the economic viability of the project in light of the performed calculations
COST BENEFIT ANALYSISCOST BENEFIT ANALYSIS5. 5. Conduct a sensitivity analysis and/or Conduct a sensitivity analysis and/or
risk analysisrisk analysisBreak-even analysis• Break even value is the value of the discount rate at which the NPV
is zero or the value at which the entire costs will be recovered• On the benefit side
– If a variable appears to be higher than the break-even level, that increases confidence in the project’s viability
• On the cost side– An estimate lower than the break-even level means that the project is
likely to be economically viable
Switching (cross-over) values• Is the discount rate at which the ranking of two projects changes• Recommended when considering only one uncertain variable
COST BENEFIT ANALYSISCOST BENEFIT ANALYSIS5. Conduct a sensitivity analysis and/or 5. Conduct a sensitivity analysis and/or
risk analysisrisk analysisBintuli WWT project• Conducting sensitivity analysis
– Critical uncertain variables chosen for analysis• Changes in capital and O&M costs• Changes in the net incremental economic benefits
– Results indicate that• IRR is robust
– 30% decline in economic benefits reduce IRR to 17% assuming no change in capital and O&M costs
– 30% increase in capital costs assuming no change in economic benefits reduces the IRR to 17%
– 30% increase in operating costs reduces IRR to 19%– The estimate is insensitive to large changes in the
projected economic costs and benefits
COST BENEFIT ANALYSISCOST BENEFIT ANALYSIS5. Conduct a sensitivity analysis and/or 5. Conduct a sensitivity analysis and/or
risk analysisrisk analysisBintuli WWT project
Change in net economic benefit
Changes in Capital costs
-30% -15% 0% +15% +30%-30% 23 25 27 29 31-15% 20 22 24 25 270% 17 19 21 23 24
+15% 15 17 19 21 22+30% 14 16 17 19 20
Changes in O&M costs
-30% 19 21 23 25 26-15% 18 20 22 24 250% 17 19 21 23 24
+15% 16 18 20 22 23+30% 15 17 19 21 22
COST BENEFIT ANALYSISCOST BENEFIT ANALYSIS5. 5. Conduct a sensitivity analysis and/or Conduct a sensitivity analysis and/or
risk analysisrisk analysisRisk analysis• Suitable in the cases where the values of several parameters are
uncertain• Involves the use of the probabilities of occurrence of the key
variables as weights to recompute the project performance criteria• Carried out using special purpose computer packages (@RISK)
– Generates probability distributions for NPV and IRR• A major difficulty is obtaining probability estimates• Common probability distributions include
– Uniform• Requires minimum and maximum estimates
– Triangular• Requires most pessimistic (minimum), most likely (mode), and most optimistic
(maximum)– Beta
COST BENEFIT ANALYSISCOST BENEFIT ANALYSIS6. Recommendations6. Recommendations
• Water pollution in Bintuli is a serious problem– 70% of untreated effluent dumped in rivers– Project implementation urgently required to
• Protect health of the community• Reduce environmental degradation
• Project would yield substantial economic benefits– IRR estimated at 21%– Sensitivity and risk analysis indicate that estimate
insensitive to costs and benefits
• Recommended to implement the project– With the institution of a good monitoring program
COST EFFECTIVENESS COST EFFECTIVENESS ANALYSIS (CEA)ANALYSIS (CEA)
• CEA may be used when– It is impossible to value a project's major benefits in
dollar terms– two projects have similar economic benefits,– For example, if the decision problem is to choose
between building two hospitals, a CEA would be appropriate since the social benefits in either case would be similar .
• Both CBA and CEA are based on the principle of economic efficiency and therefore do not consider equity or distributional issues.
COST EFFECTIVENESS COST EFFECTIVENESS ANALYSIS (CEA)ANALYSIS (CEA)
• CEA looks only at financial costs– A CEA takes the objective as given, and then works out the
costs of the alternative ways of achieving that objective
• The decision on whether to use CEA instead of CBA will depend on a number of factors including the following: – The size and complexity of the project; – The extent to which there are quantifiable benefits; and – The extent to which the benefits can be valued in monetary
terms.
• Unlike CBA, CEA does not have absolute criteria by which to judge the economic viability of projects– CEA not recommended when a decision about the level of
output or service to be provided is at issue
COST EFFECTIVENESS COST EFFECTIVENESS ANALYSIS (CEA)ANALYSIS (CEA)
• Examples of situations in which CEA could be used:– Given a desirable pollution abatement standard, what will
be the least cost, out of various alternatives, of achieving the standard?
– Can buying up all the property rights in a flood plain and moving people out by constructing dykes save the same number of lives more cheaply?
– Given two parks with similar recreation benefits, which should be developed? Park A requires extensive filling and flood control and Park B involves buying warehouse sites.
– Choosing between alternative ways of constructing a town's water supply system.
COST EFFECTIVENESS COST EFFECTIVENESS ANALYSIS (CEA)ANALYSIS (CEA)
The steps involved in a CEA similar to CBA:
COST BENEFIT ANALYSISCOST BENEFIT ANALYSISCASECASE--STUDYSTUDY
The Effect of Food Waste Disposers on The Effect of Food Waste Disposers on Municipal Waste and Wastewater Municipal Waste and Wastewater
ManagementManagement
OUTLINEOUTLINE
Introduction
GBA ExistingConditions
Study Objectives & Methodology
Results
IntroductionIntroduction
Rapid urbanization ++ associated industry & services growth key feature of economic & demographic development in many developing countries
Cities are absorbing 2/3 of total population amount of solid waste generated surpasses the capacity of municipalities to handle it
Limited areas for landfilling ++ social acceptance ++political conflict need to consider other waste minimization alternative, Food Waste DisposersFood Waste Disposers
Food Waste Disposers / Garbage Food Waste Disposers / Garbage Grinders Grinders
MSW stream
Sewage stream
Grinding by mechanical means + tap water
Food Food wastewaste
Other Other wastewaste
Food Waste Disposers (FWD)Food Waste Disposers (FWD)
Literature ReviewLiterature Review-- FWD FWD
Extra water use amount to 4.3 L/c/d ~ 2.2% of total household water use
21-month pilot project in NY:FWD are used 2-3 times/d for a total of 0.6 min.Using industry upper limit of 2 min/d, the most common ½ HP FWD consumes <75 Watt light bulb uses in 10 min
Increased loadings by: 50% for BOD and SS (Sweden)12% for TN and neg. for P (100% MP)
Literature ReviewLiterature Review-- FWDFWD
Optimal usage for 15 yrs did not exhibit operational problems within plumbing system
Theoretical calculations showed a 57% increase in sludge at WWTP, affecting bio-stage & sludge treatment
Galil & Yaacov (2001): increase sludge by 60-62% Vs.Vs. 18.1% for WMR (1994)
AdvantagesAdvantages of FWDof FWD
Dispose of almost all types of biodegradable food waste
Eliminate nuisance from waste handling & storage, smell and risk of exposure to disease-spreading vectors
Advantages of FWD (contAdvantages of FWD (cont’’d)d)
Leave mostly better quality recyclables stored nuisance and risk-free
Reduce volume of garbage to be disposed of in Landfills
Reduce acidic leachate produced in the landfill & greenhouse gases emitted (CH4)
Ground food waste is quickly and cleanly transported through the sewer system to sewage treatment plants
Gases produced at the plants can be collected and used as an energy source
FWDs are among the safest household appliances
Advantages of FWD (contAdvantages of FWD (cont’’d)d) Questions raisedQuestions raised??????
Installation cost of grinders??
Amount of additional water required for the transfer of the particles??
Change of raw sewage quality in terms of Suspended solids & Organic substances??
Influence of additional loads on the treatment plants??
Greater Beirut Area (GBA) Greater Beirut Area (GBA) under studyunder study
Solid Waste Generation
Collection and Transport
Recyclables Organic Bulky Rejects
Warehousestorage
Composting(Coral)
Landfill (1)(Bsalim)
Industries Farmers
Landfill (2)(Naameh)
Emergency Plan for the SWM in Emergency Plan for the SWM in the GBAthe GBA
Implemented since 1997
Transfer/Processing(1)(Amroussieh)
Transfer/Processing(2)(Karantina)
System Performance EvaluationSystem Performance Evaluation
ISMW targets
(tonnes/d)
Actual Achievements LACECO(1999)
(tonnes/d)
LACECO(2002)
(tonnes/d)Total wastes received at transfer/processing plants
1,700 1,922 2,085
Waste handling meansComposting 850 216 300Recycling 160 99 143Landfilling 690 1,607 1,640
Majority of the waste generated is disposed of at the landfill !!!
Costs of the SWM systemCosts of the SWM system
Activity Cost (USD/tonne)
Collection/Transport 59Sorting 18Baling 12Wrapping 9Hauling to Coral composting plant 4Composting 18-40Landfill disposal 25-35
> 119 USD/tonne
Low market demand oncompost & recyclables+Difficulty in locating new landfillsfor municipal waste disposal along
Lebanese coast (High Cost + Limited Suitable Land +High Social & Political Oppositions) ⇓the need for OTHER ALTERNATIVES
…… GBA MSW CharacteristicsGBA MSW Characteristics
15
106 3 2 1
63
Food waste Paper and cardboardPlastic Glass/chinaMetal FabricOther
70% 70% water water
2,000 tonnes/d2,000 tonnes/d
GBA WW CharacteristicsGBA WW CharacteristicsParameter 2005Population projections (×1,000 persons) 1,782Wastewater generation rates (m3/d) 257,609BOD (kg/d) (1) 114,378COD (Kg/d) (2) 162,294SS (Kg/d) (3) 146,837(1) Based on an average of 444 mg/L(2) Based on an average of 630 mg/L(3) Based on an average of 570 mg/L
No wastewater treatment plants exist. Many are planned to comply with the GoL signed protocol for the protection of the Mediterranean.
Objectives of this StudyObjectives of this Study
Examine the feasibility of introducing food disposers as a waste management option in GBA
Assess FWD operational impacts on
Solid waste stream
Wastewater stream quality and treatment options
Assess FWD economic impacts
MethodologyMethodology
OPERATIONAL IMPACTSOPERATIONAL IMPACTS
Solid waste composition & distribution
Domestic water consumption
Wastewater loadings & flow
Methodology (contMethodology (cont’’d)d)
S1S125% marketpenetration
S2S250% marketpenetration
S3S375% marketpenetration
75% 95% 75% 95% 75% 95%
% of food ground% of food ground
Laboratory InvestigationLaboratory Investigation
Collected from 3 households over weekend
Mixed thoroughly
3 batches of blended food
Methodology (contMethodology (cont’’d)d)
ECONOMIC IMPACTS
Costs (conventional + environmental)
Savings (conventional + environmental)
Benefits
Breakeven Points
Economy of Scale
Capital & Operating cost of
FWD
Wastewater secondary
treatment cost of added wastewater volume (min-max)
Sludge treatment cost of added
wastewater volume for most common used technologies
(min-max)
Cost of increased domestic waste consumption
Cost of sludge treatment(min-max)
Cost forgone of management of food wastes diverted from solid waste stream
Cost foregone of leachate remediation
Cost forgone of abating pollutant discharge from management of food wastes
++
++
++
++Cost of electricity
negligible
Foregone earnings from potential energy recovery from food waste insignificant particularly in anaerobic digestion
Conventional Costs
Environmental Costs
Conventional Savings
Environmental Savings
Capital & Operating cost of FWDAnnual cost of 43 US$/unit/yr assuming average cost/unit of
US$ 400 with expected life span of 12 yrs & 5 % opportunity cost/household
Wastewater secondary treatment cost of added wastewater volumeMin Max
0.03 US$/kg of added BOD 0.25 US$/kg of added SS
0.22 US$/kg of added BOD 0.48 US$/kg of added SS
Sludge treatment cost of added wastewater volume for most common used technologies *
Min Max39 US$/dry tonne 292 US$/dry tonne
* Examined technologies: centrifuge thickening & dewatering; belt filter press; composting; recessed-plate filter; aerobic digestion; anaerobic digestion; alkaline stabilization; thermal aerobic pre-treatment & anaerobic digestion; pre-pasteurization & anaerobic digestion; reactor composting; anaerobic digestion & thermal drying; & incineration.
Cost of increased domestic water consumptionDomestic water charging rate of 150 US$/m3-d/yr
CONVENTIONAL COSTSCONVENTIONAL COSTS
ENVIRONMENTAL COSTSENVIRONMENTAL COSTS
Cost of sludge treatmentMin Max
45 US$/dry tonne 336 US$/dry tonne
Equivalent to 15% of conventional cost Equivalent to 15% of conventional cost
MinMin--Max CONVENTIONAL COSTSMax CONVENTIONAL COSTS++ MinMin--Max ENVIRONMENTAL COSTSMax ENVIRONMENTAL COSTS
= Min= Min--Max TOTAL COSTSMax TOTAL COSTS
CONVENTIONAL CONVENTIONAL SAVINGSSAVINGSCost forgone of management of food wastes diverted from solid
waste stream119 $/tonne of municipal waste
ENVIRONMENTAL SAVINGSENVIRONMENTAL SAVINGSCost foregone of leachate remediation
Equivalent to 46.46 $/tonne
Cost foregone of abating pollutant discharge from management of food waste
Equivalent to 7.5% of conventional management cost of solid waste
CONVENTIONAL SAVINGS + ENVIRONMENTAL CONVENTIONAL SAVINGS + ENVIRONMENTAL SAVINGS SAVINGS = TOTAL SAVINGS= TOTAL SAVINGS
865
455
1,215
228 288
577 683
33
6358 56
4752
43
0
250
500
750
1,000
1,250
Food wastegeneration
in 2005
S1a S1b S2a S2b S3a S3b0
25
50
75
100Food groundPercent composition of food waste
% w
eigh
t
tonn
es/d
ay
25% MP 50% MP 75% MP
Food Waste Composition after Installation of FWDs Food Waste Composition after Installation of FWDs (2005 values)(2005 values)
ResultsResults
Scenario %Reduction in solid waste
to be managed
% Increase in domestic
waterconsumption
% Increase in wastewater
flow
% Increase in BOD loading
% Increase
in SS loading
25% MP + 75% food ground 11.8 0.7 1.1 16.9 1.9
25% MP + 95% food ground 14.7 0.8 1.4 21.3 2.4
50% MP + 75% food ground 23.0 1.3 2.3 33.4 3.8
50% MP + 95% food ground 29.1 1.6 2.9 42.0 4.8
75% MP + 75% food ground 34.3 1.9 3.4 49.5 5.6
75% MP + 95%food ground 43.4 2.4 4.4 62.2 7.1
Impacts of introducing food disposers on SWM and Impacts of introducing food disposers on SWM and WWM schemes WWM schemes (2005 values)(2005 values)
Scenario %Reduction in solid waste
to be managed
% Increase in domestic
waterconsumption
% Increase in wastewater
flow
% Increase in BOD loading
% Increase
in SS loading
25% MP + 75% food ground 11.8 0.7 1.1 16.9 1.9
25% MP + 95% food ground 14.7 0.8 1.4 21.3 2.4
50% MP + 75% food ground 23.0 1.3 2.3 33.4 3.8
50% MP + 95% food ground 29.1 1.6 2.9 42.0 4.8
75% MP + 75% food ground 34.3 1.9 3.4 49.5 5.6
75% MP + 95% food ground 43.4 2.4 4.4 62.2 7.1
Impacts of introducing food disposers on SWM and Impacts of introducing food disposers on SWM and WWM schemes WWM schemes (2005 values)(2005 values)
4.6
0.4
0.6
0.1
4.6
2.4
1
0.15
1.6
6
9.9
0.02
4.2
8.7
0 2 4 6 8 10 12
Cost of food disposer units
Cost of added volume of domestic water
Cost of wastewater treatment
Conv. cost of sludge mangt
Env. cost of sludge mangt
Conv. solid waste savings
Env. solid waste savings
Net Benefts based on Conv.Costs/Savings
Net Benefits based on Conv. & Env.Costs/Savings
Million US$/yr
Costs, Savings & Benefits achieved underCosts, Savings & Benefits achieved underS1aS1a (25% MP+ 75% food ground)(25% MP+ 75% food ground)
CostsCosts
SavingsSavings
BeneBenefitsfits
13.7
1.5
2.3
0.5
37.6
17.4
9.0
3.8
0.60.1
9.6
26.436.8
19.5
0 10 20 30 40
Cost of food disposer units
Cost of added volume of domestic water
Cost of wastewater treatment
Conv. cost of sludge mangt
Env. cost of sludge mangt
Conv. solid waste savings
Env. solid waste savings
Net Benefts based on Conv.Costs/Savings
Net Benefits based on Conv. & Env.Costs/Savings
Million US$/yr
Costs, Savings & Benefits achieved underCosts, Savings & Benefits achieved underS3bS3b (75% MP+ 95% food ground)(75% MP+ 95% food ground)
CostsCosts
SavingsSavings
BeneBenefitsfits
Benefits achieved under Benefits achieved under S1aS1a (25% MP+ 75% food (25% MP+ 75% food ground) & ground) & S3bS3b (75% MP + 95% food ground) (75% MP + 95% food ground)
as as % of existing SWM cost% of existing SWM cost
1.9 3.7
12.29.0
28.8
49.4
5.0
10.4 7.2
23.3
11.5
44.0
31.6
6.8
16.9
37.0
0
10
20
30
40
50
1
%
based on min conventional costbased on max conventional costbased on min conventional and environmental costbased on max conventional and environmental cost
20052005 20202020
S1a S3b S1a S3b
68.757.1
-10
0
10
20
30
0 40 80 120
US$/tonne
Ben
efit
s
S1a S3b
Breakeven points for Breakeven points for S1a S1a (25% MP + 75% food (25% MP + 75% food ground) & ground) & S3bS3b (75% MP + 95% food ground) (75% MP + 95% food ground)
taking into consideration the lower & upper range of taking into consideration the lower & upper range of costs costs (2005 values) (2005 values)
(a) Based on MIN. CONVENTIONAL costs(a) Based on MIN. CONVENTIONAL costs
(MU
S$/y
r)
Breakeven points for Breakeven points for S1aS1a (25% MP + 75% food (25% MP + 75% food ground) &ground) & S3bS3b (75% MP + 95% food ground) (75% MP + 95% food ground)
taking into consideration the lower & upper range of taking into consideration the lower & upper range of costs costs (2005 values) (2005 values)
(b) Based on MIN. CONV. + ENV. costs(b) Based on MIN. CONV. + ENV. costs
13.92.4
-10
0
10
20
30
0 40 80 120
US$/tonne
Ben
efit
s
S1a S3b
(MU
S$/y
r)
50
100.188.5
-10
0
10
20
30
0 40 80 120
US$/tonne
Ben
efit
s
S1a S3b
Breakeven points for Breakeven points for S1aS1a (25% MP + 75% food (25% MP + 75% food ground) & ground) & S3bS3b (75% MP + 95% food ground) (75% MP + 95% food ground)
taking into consideration the lower & upper range of taking into consideration the lower & upper range of costs costs (2005 values) (2005 values)
(c) Based on MAX. CONV. costs(c) Based on MAX. CONV. costs
(MU
S$/y
r)
46.935.3
-10
0
10
20
30
0 40 80 120
US$/tonne
Ben
efit
s
S1a S3b
Breakeven points for Breakeven points for S1aS1a (25% MP + 75% food (25% MP + 75% food ground) &ground) & S3bS3b (75% MP + 95% food ground) (75% MP + 95% food ground)
taking into consideration the lower & upper range of taking into consideration the lower & upper range of costs costs (2005 values) (2005 values)
(d) Based on MAX. CONV. + ENV. costs(d) Based on MAX. CONV. + ENV. costs
(MU
S$/y
r)
Dynamics of Economy of ScaleDynamics of Economy of Scale
To define the cost of managing the remaining solid waste generated ‘X’ (US$/tonne) after integration
of FWD at which the proposed system would breakeven Savings = Costs OR Benefits = 0
worst case scenario [100% MP + 100% food ground]was assessed
ARGUMENTARGUMENTCost of managing the remaining solid waste wouldif total quantity waste to be managed
Total savings achieved from the SWM scheme as a result of integrating FWD
Excluding environmental externalities, FWD remain profitable until cost/tonne of managing remaining solid waste reaches
US$ 223/tonne = 1.8 US$ 223/tonne = 1.8 ×× current charging ratecurrent charging rate
Including environmental externalities, FWD will still be profitable up to a management cost of
US$ 315/tonne = 2.6 US$ 315/tonne = 2.6 ×× current charging ratecurrent charging rate
Dynamics of Economy of ScaleDynamics of Economy of Scale
Certainly, it is not expected that the cost of Certainly, it is not expected that the cost of SWM would reach such levels in study area in SWM would reach such levels in study area in near future, which justifies the adoption of near future, which justifies the adoption of FWDFWD
EEnd of nd of SSession ession 1313
Thank YouThank You
Waste Manage Res 2005: 23: 20–31Printed in UK – all right reserved
Copyright © ISWA 2005Waste Management & Research
ISSN 0734–242X
20 Waste Management & Research
The effect of food waste disposers on municipal waste and wastewater management
This paper examines the feasibility of introducing food wastedisposers as a waste minimization option within urban wastemanagement schemes, taking the Greater Beirut Area(GBA) as a case study. For this purpose, the operational andeconomic impacts of food disposers on the solid waste andwastewater streams are assessed. The integration of foodwaste disposers can reduce the total solid waste to be man-aged by 12 to 43% under market penetration rangingbetween 25 and 75%, respectively. While the increase indomestic water consumption (for food grinding) and corre-sponding increase in wastewater flow rates are relativelyinsignificant, wastewater loadings increased by 17 to 62%(BOD) and 1.9 to 7.1% (SS). The net economic benefit ofintroducing food disposers into the waste and wastewatermanagement systems constitutes 7.2 to 44.0% of the existingsolid waste management cost under the various scenariosexamined. Concerns about increased sludge generation per-sist and its potential environmental and economic implica-tions may differ with location and therefore area-specificcharacteristics must be taken into consideration when con-templating the adoption of a strategy to integrate food wastedisposers in the waste–wastewater management system.
Natasha Marashlian Mutasem El-FadelDepartment of Civil and Environmental Engineering, AmericanUniversity of Beirut, Lebanon.
Keywords: Food waste disposers, solid waste/wastewater management: wmr 708-1
Corresponding author: M. El-Fadel, American University ofBeirut, Faculty of Engineering and Architecture, Bliss Street, POBox 11-0236, Beirut, Lebanon
Tel: 961 3 228 338; fax: +961 1 744 462; e-mail: [email protected]
DOI: 10.1177/0734242X05050078
Received 12 September 2003; accepted in revised form 14 October 2004
Introduction
Rapid urbanization coupled with the associated growth ofindustry and services constitute a key feature of economicand demographic development in many developing coun-tries. Cities are currently absorbing two-thirds of the totalpopulation increase throughout the developing world(UNCSD 1999). An important environmental concern ofurbanization is the amount of solid waste that is generated ata rate that surpasses the capacity of municipal authorities tomanage it, resulting in potential adverse impacts on theenvironment, human health, and the quality of urban life.With limited land areas around many urban centrers, thesearch for environmentally safe as well as socially and politi-cally acceptable sites for landfills has become a perennial
problem, and for several cities, seemingly unsolvable, thuscreating the need to consider other waste minimization alter-natives at the source. In this context, the use of food wastedisposers enables the separation of a considerable fraction offood-waste ingredients out of the entire municipal solidwaste (MSW) stream by grinding the waste using mechani-cal means with the addition of tap water, and allowing themixture into the sewage system. This paper evaluates therole of food waste disposers within the waste managementsystem of urban areas, taking the Greater Beirut Area (GBA)as a case study. Background information on food waste dis-posers is first presented followed by an examination of theirimpact on the solid waste and wastewater management
Effect of food waste disposers on municipal waste and wastewater management
Waste Management & Research 21
schemes with emphasis on operational and economic feasi-bilities taking area-specific characteristics into considera-tion.
Background
A garbage grinder or a food waste disposer unit is a kitchenappliance that is mounted directly under the kitchen sinkand connected to the sewer pipe. These units are designed togrind biodegradable organics such as meat scraps, vegetables,fruit pits, citrus fruit peelings, coffee grounds and small bones(Nilsson et al. 1990).
Food waste disposers were first introduced back in the1930s in the US where their usage evolved to reach morethan 94% of all cities and they are included as a standarditem in more than 80% of new home construction and arefound in almost half of all US households (Macnair 2000).This use, however, was surrounded by scepticism in certainlarge cities. New York City for instance, had banned wastegrinders for a long time because of concerns that the city’sold sewer infrastructure could not handle the additionalload. It was not until 1995 when the City started to worrymore about where it was going to dispose of its garbage afterthe closure of its major landfill, that it commissioned themost comprehensive pilot project ever conducted to investi-gate the impact of food grinders on the sewer system. Basedon the positive outcome of the study, the City lifted the banand legalized the installation of food waste grinders in resi-dential buildings in 1997 (Dunham 2001). Today, food wastedisposers are sold to households under limited or no restric-tions in approximately 50 countries including England, Ire-land, Italy, Spain, Japan, Canada, Mexico and Australia.Although a ban was in effect in France, it was lifted in 1986after another in-depth investigation by the French authori-ties (Nilsson et al. 1990).
Although food waste disposers allow diversion of organicwaste from the solid waste stream and hence save on theirassociated management costs, their use raises numerous ques-tions regarding the additional energy required to run theseunits, the amount of additional tap water required for thetransfer of particles into sewage, the alteration of sewagequality in relation to the addition of suspended solids andorganic substances, and the additional loads on the sewagesystem and wastewater treatment plants. Various studieshave been conducted to investigate these issues.
The extra water use due to disposers is reported to be neg-ligible, amounting to 4.3 L/capita per day on average andrepresenting 2.2% of the total household water use (Nilssonet al. 1990, Waste Management Research Unit 1994, Ketzen-berger 1995, New York City DEP 1997, Wainberg, et al.2000,The Plumbing Foundation City of NY 2001).
Further, it has been widely reported that the cost of elec-tricity to run food disposers and its associated pollution is rel-atively insignificant. The most comprehensive study in thiscontext is the 21-month pilot project in New York where itwas estimated that food waste disposers are used two to threetimes a day for a total of 0.6 min. If, to be conservative, usingthe industry upper limit of 2 min/day, the most common0.5 hp motor of a food waste disposer consumes less than a75 W light bulb uses in 10 min (The Plumbing FoundationCity of NY 2001).
On the other hand, it is expected that the quantity oforganic material and suspended solids will exhibit radicalchange with the use of food disposers as the idea with thedisposer is after all to move as much organic material fromthe solid waste to wastewater stream. In a pilot study, Nilssonet al. (1990) reported that the biochemical oxygen demand(BOD) and suspended solids (SS) increased by almost 50%after integrating disposers in the city of Staffanstorp in Swe-den, whereas the increase in total nitrogen was 12% andnegligible for phosphorus. In contrast, a study examining theimpacts of food waste disposal units and compost bins used inthe Ashmore suburb of the Goald City Coast in Queenslandshowed an increase of 16.5% for BOD, 3.0% for total nitro-gen and 4.6% for total phosphorus (based on a 100% marketpenetration) (Waste Management Research Unit 1994).Similarly, a study conducted in the town of Shurammar inSweden showed no increase in the amount of incomingBOD, nitrogen or phosphorus. Only an increase in the BOD/nitrogen was detected (Sudo 2000).
In long-term testing for clogs, Nilsson et al. (1990)showed that a stimulated optimal usage of disposers for aperiod of 15 years did not exhibit operational problemswithin the plumbing system. Regular inspection and yearlyvideotaping of the piping system revealed that the outersewage pipes function well during the use of food disposersand the buildup of sewage was reported at the water levelwith a width of 2–3 cm along the envelope surface and athickness of 0.5–1.5 cm. Similar results were reported bySinclair Knight (1990), Waste Management and ResearchUnit (1994), Koning & Van Der Graaf (1996), NYCDepartment of Environmental Protection (1997) and Strutz(1998).
At the wastewater treatment plants, theoretical calcu-lations showed that the amount of sludge increases by57% due to usage of food disposers, affecting primarily thebio-stage and sludge treatment (Nilsson et al. 1990). Simi-lar theoretical estimations by Galil & Yaacov (2001)reported that the contribution of garbage disposers isexpected to increase the weight of raw sludge by about60% in the case where biological treatment is applied and62% in the case of primary sedimentation followed by bio-
N. Marashlian, M. El-Fadel
22 Waste Management & Research
logical treatment. In contrast, a study by Waste Manage-ment Research Unit (1994) indicated an increase of only18.1% in sludge production due to the introduction offood disposers. Concerns about increased sludge genera-tion persist and its potential environmental and economicimplications may differ with location and therefore area-specific characteristics must be taken into considerationwhen contemplating the adoption of a strategy to inte-grate food waste disposers in the waste-wastewater man-agement system.
Existing conditions
At present, MSW in the study area is managed through anintegrated solid waste management system (ISWM) involv-ing: (1) collection and transport of raw municipal waste;(2) sorting and processing of raw municipal waste at twotransfer facilities; (3) recycling of the waste fraction com-posed of glass, metals, papers and plastics; (4) compostingof the waste that is rich in highly biodegradable organic
content; and (5) transport and disposal of sorted/baled aswell as bulky waste at two old nearby quarries converted tolandfills (Fig. 1).
At nearly US$ 120 per tonne (UNEP 2000, MoE &LEDO 2001), the ISWM has suffered from many deficienciessince its implementation, the major ones being at the treat-ment and disposal levels. Indeed, the system has failed toachieve its targets, with more than 80% of the total wastesgenerated routed to the landfills, raising into question thepurpose of the sorting-processing–composting facilities aswell as the recycling programme (Table 1).
Apparently, the market demand for compost and recycla-ble materials may be either less than the generation rate ornot economically competitive. Thus, whether viewed as ahierarchy or as complementary components, the currentwaste management activities, particularly source separationand recycling have not measured up favorably with the stepsoutlined in an ISWM system (El-Fadel & Chahine 1999).On the other hand, the difficulty associated with locatingand approving a suitable site for landfilling has been increas-
Fig. 1: Current integrated solid waste management scheme of the Greater Beirut Area (El Fadel & Khoury 2001).
Table 1: Performance of adopted ISWM.
Actual achievements
ISWM targets (1997) LACECO (1999) LACECO (2002)
tonnes/day tonnes/day tonnes/day
Total wastes received at transfer/processing plants 1700 1922 2085
Waste handling means
Composting 850 216 300
Recycling 160 99 143
Landfilling 690 1607 1640
Effect of food waste disposers on municipal waste and wastewater management
Waste Management & Research 23
ing continuously, which dictates the adoption of policies thatwill minimize the amount of waste to be disposed of in alandfill. Therefore, solid waste minimization alternativessuch as food waste disposers are examined in this study.
The waste stream in the study area is characterized by a highproportion of food waste (63%) (Table 2), and has a projectedsolid generation rate exceeding 2000 tonnes/day. With morethan 70% moisture content in typical food waste (Tchoba-noglous et al. 1993), processing such waste at a wastewater treat-ment plant appears to be a suitable approach, if technically andeconomically feasible. Currently, while no wastewater treat-ment plants exist in the study area, many are planned to complywith the Government’s signed protocol for the protection of theMediterranean (MoE & LEDO 2001). The implementation ofplanned investments in wastewater treatment is still in its earlyphase, so that an increase in capacity is feasible at the designlevel. The projected wastewater generation in the study area issummarized in Table 3 with corresponding loadings.
Methodology
The operational impacts associated with the integration offood waste disposers include primarily: (1) solid waste com-position and distribution; (2) domestic water consumption;and (3) wastewater loading. Six scenarios (Fig. 2) wereexamined using a variable market penetration rate (25 to75%). The latter covers all the possible market penetrationscenarios reviewed in the literature with 25 and 50% beingthe most realistic ones since after 60 years of marketing gar-bage disposers in the US (which is considered the oldestmarket worldwide), their distribution reached a maximum of
50% (Galil & Yaacov 2001). A variable amount of foodground at the household level was adopted (75 to 95%). Thelowest value (75%) was reported by Wainberg et al. (2000).The upper range (95%) was used since only a limited numberof food wastes could not be ground including highly fibrouswastes and shells of certain seafood.
The current and anticipated future loadings to wastewatertreatment plants from the use of food waste disposers wasestimated based on a laboratory investigation that was con-ducted to assess the BOD and SS contents of ground foodwaste from the study area. The investigation was performedat the Environmental Engineering Research Center at theAmerican University of Beirut (AUB). Kitchen food wasteconsisting of vegetable, fruit, meat and other food waste con-stituents was collected from several households. The wastewas mixed thoroughly and divided into three batches ofequal size. The three batches were blended with tap water. Avolume of 11.7 L of water was used to grind 1 kg of foodwaste (Hartmann 2000, Wainberg et al. 2000). The resultingmixtures were then analysed for BOD and SS using StandardMethods for the Examination of Water and Wastewater (APHA1998). Each of the experiment was duplicated to assure repli-cability and consistency of the results.
Economic impacts entailed the evaluation of the conven-tional (tangible or direct) and environmental (non-tangibleor indirect) costs/savings for all scenarios. The conventionalcosts included the capital and operating cost of food disposerunits, the cost of wastewater and sludge treatment of theadded wastewater volume (loadings and flow), and the costof increased domestic water. As indicated in the backgroundsection, the cost of electricity needed to run food waste dis-
Table 2: Average solid waste composition in the study area.
Waste category Waste composition (%)
Food waste 63
Paper and cardboard 15
Plastic 10
Glass/china 6
Metal 3
Fabric 2
Other 1
Source: Ayoub et al. (1996); Baldwin et al. (1999); El-Fadel & Khoury (2001); MoE & LEDO (2001).
Fig. 2: Scenarios examined.
Table 3: Projected municipal wastewater generation rates in the study area.
Parameter 2005
Population projections (× 1000 persons) 1782
Wastewater generation rates (m3/day) 257 609
BOD (kg/day) 1 114 378
COD (kg/day) 2 162 294
SS (kg/day) 3 146 8371Based on an average of 444 mg/L (MoE & LEDO 2001); 2Based on an average of 630 mg/L (Khatib & Alami 1994); 3Based on an aver-age of 570 mg/L (El Fadel & Abou Ibrahim 2002).
N. Marashlian, M. El-Fadel
24 Waste Management & Research
posers was considered as negligible. Similarly, foregone earn-ings from potential energy recovery from food waste wereassumed to be insignificant particularly in cases where thewastewater treatment process involves anaerobic digestion.The conventional savings included the costs forgone due toreduced management requirements of food wastes divertedfrom the solid waste stream. Environmental costs/savings areassociated with potential impacts that are usually notdirectly perceived by the community. Due to the complexityand the inter-connection of the environmental media (air,water, soil and humans), the valuation of these environmen-tal impacts is difficult. Nonetheless, they can be estimatedusing the abatement cost method in which costs required toabate pollution resulting from solid waste management
(SWM) alternatives are used to estimate the value of poten-tial damages (Fig. 3). Note that all values used in the presentanalysis are at constant year zero therefore inflation was nottaken into consideration.
Results
The variation of the food waste composition in the studyarea as a result of introducing food disposers is summarized inFig. 4. Naturally, the integration of food disposers is expectedto reduce the total food waste generated and collected. Thepercentage of food waste within the MSW stream decreasesfrom 63 to 58% under S1a (25% market penetration with75% of the food ground), and down to 33% under S3b (75%
Fig. 3: Methodology for costs/savings estimation. 1Adopted from reported values in Carawan (1996), Union Sanitary District-California (2003) and WSC (2003). 2Examined technologies include centrifuge thickening and dewatering; belt filter press; composting; recessed-plate filter; aero-bic digestion; anaerobic digestion; alkaline stabilization; thermal aerobic pre-treatment and anaerobic digestion; pre-pasteurization and anaero-bic digestion; reactor composting; anaerobic digestion and thermal drying; and incineration. Adopted from Hallvard et al. 2001; EC 2002; Minett & Fenwick 2001; US EPA 2000a, b, c. 3Current domestic water charging rate as assigned by the Beirut Water Authority. 4Adopted from the European Commission (2002). 5Adopted from Massoud (2000) and MoE & LEDO (2001). 6Adopted from CIWMB (1990). 7Equal to: Min conven-tional costs + min environmental costs. 8Equal to: Max conventional costs + max environmental costs.
Effect of food waste disposers on municipal waste and wastewater management
Waste Management & Research 25
market penetration with 95% of the food ground), whichtranslates into 12 to 43% reduction in wastes to be landfilled(Table 4). Consistent with values reported in the literature(USEPA 1980, Nilsson et al. 1990, Waste ManagementResearch Unit 1994, Ketzenberger 1995, New York CityDEP 1997, Wainberg, et al. 2000, The Plumbing Foundationof New York 2001), the increase in water consumption is rel-atively insignificant, ranging from 0.72 to 2.35% under S1a(25% market penetration with 75% of food ground) to S3b(75% market penetration with 95% of food ground). Thecorresponding increase in the wastewater flow is equallyinsignificant accounting for 1.1 to 4.4% under the same sce-narios. The anticipated increase in sewage loadings from theuse of food waste disposers was based on the laboratory inves-tigation that indicated BOD and SS concentrations of 7042and 1537 mg/L, respectively. The anticipated increaseranged from 17 to 62% in terms of BOD loading under S1a(25% market penetration with 75% of food ground) to S3b(75% market penetration with 95% of food ground) andfrom 1.9 to 7.1% for SS loading under the same scenarios.
Measurements of the output from food waste disposersshow that about 98% of the input is reduced in size to
< 0.20 cm (CIWEM 2003). Kitchen sewer connection pipesin the study area are of standard size of 3.18 and 5.08 cminner diameter (ID). On the other hand, the ID of the sew-age connection system ranges from 0.4 to 2 m. Thus, no clog-ging is expected to occur in the plumbing connectionswithin households or in sewers, which is consistent with theabsence of clogging problems in cities where food waste dis-posers were installed (Nilsson et al. 1990, Strutz 1998, Sudo1998, Galil & Yaacov 2001).
Table 5 presents the details of the cost-saving analysisassociated with the integration of food waste disposers intothe solid waste/wastewater management schemes. The bene-fits achieved constitute 1.9 to 5.0% of the existing solidwaste management cost under S1a (25% market penetrationwith 75% of food ground) and 11.5 to 23.3% under S3b(75% market penetration with 95% of food ground), respec-tively. The benefits increased with the inclusion of environ-mental externalities to reach 7.2 to 10.4% of the existingsolid waste management cost under S1a (25% market pene-tration with 75% of food ground) and 31.6 to 44.0% underS3b (75% market penetration with 95% of food ground),respectively. Figure 5 illustrates the savings achieved with
Fig. 4: Food waste composition after installation of food disposers (2005 values).
Fig. 5: Benefits achieved under S1a (25% market penetration + 75% of food grinded) and S3b (75% market penetration + 95% of food grinded) as percentage of existing SWM cost.
N. Marashlian, M. El-Fadel
26 Waste Management & Research
the integration of food waste disposers as percentages of theexisting SWM cost, based on the minimum and maximumtotal costs (conventional and environmental) for 2005 and2020. It indicates that using current costs of solid waste andwastewater management, the benefits of integrating foodwaste disposers would increase with time as the quantities ofsolid waste to be managed increase.
The above analysis assumes that the cost of managing1 tonne of MSW will remain constant at the current charg-ing rate of US$ 119 per tonne. Locally, this cost is perceived
as relatively high and efforts are directed towards reducing itthrough competitive tendering by the private sector. Hence,the savings and net benefits that are achieved from the inte-gration of food disposers are expected to decrease. Abreakeven analysis would allow decision makers to define thepercentage reduction required under which the integrationof food waste disposers within the management schemewould become non-profitable. Assuming that all other val-ues are constant, the breakeven points for S1a (25% marketpenetration with 75% of the food ground), and for S3b (75%
Table 4: Impacts of introducing food disposers on SWM and WWM schemes (2005 values).
Scenario % Reduction in solid waste to be managed
% Increase in domestic water consumption
% Increase in wastewater flow
% Increase in BOD loading
% Increase in SS loading
(1) (2) (3) (4) (5)
S1a 11.8 0.7 1.1 16.9 1.9
S1b 14.7 0.8 1.4 21.3 2.4
S2a 23.0 1.3 2.3 33.4 3.8
S2b 29.1 1.6 2.9 42.0 4.8
S3a 34.3 1.9 3.4 49.5 5.6
S3b 43.4 2.4 4.4 62.2 7.1
(1)
(2)
(3)
(4)
(5)
YTXaYFoodb
YFoodGroundmgS
RLWT
cWFoodGroundw
IWVWWeVFoodGround
MCIWWXNewBODXBODWW
XBODFood
VwwVFoodMFood MExpFood VExpFood IBODXNewSSXSSWWXSSFood
ISS
=====
====
==
===
====
====
=
=========
=
Total solid waste generated in the GBA in 2005 (tonnes/day)Estimated population in 2005 (capita)Average daily solid waste generation rate (kg/capita per day)Food waste generated (tonnes/day)% Composition of food waste in waste stream (assuming con-stant waste composition)Food waste ground (tonnes/day)% Market penetration of food waste disposers (25, 50 or 75%)Estimated food ground (75 or 95%)Solid waste expected to be landfilled if the current ISWM scheme remains operational (without integration of food waste disposers) (tonnes/day)% Reduction in solid waste to be landfilledEstimated total water demand for GBA in 2005 (without integra-tion of food waste disposers) (m3/day)Average daily water demand rate (L/capita per day)Amount of water needed to grind food waste (m3/day)Amount of water needed to grind 1 Kg of organic food (11.7 L/kg)% Increase in domestic water consumptionEstimated wastewater flow for the GBA in 2005 (m3/day)Average daily wastewater generation rate (L/capita per day)Volume of food waste ground expected to be disposed down the drain (m3/day)Moisture content (%)% Increase in wastewater flowNew BOD loading after installation of food disposersBOD loading of the current wastewater sewage of the GBA (mg/L)Average BOD of food waste based on experimental results (7042 mg/L)Total volume of the wastewater generation in the GBA (m3/d)Volume of food ground (in m3/day)Mass of food disposed in the sink (tonnes/day)Mass of food sample used in the experiment (500 g)Volume of the food sample used in the experiment (6.5 L)% increase in BOD loading after integration of food disposersNew SS loading after installation of food disposersSS loading of the current wastewater sewage of the GBA (mg/L)Average BOD of food waste based on experimental results (1537 mg/L)% increase in SS loading after integration of food disposers
YT X a×=
YFood YT b×=
YFoodGround YFood m g××=
RL 100 YFoodGround S÷( ) 100×[ ]–=
WT X c×=
WFoodGround w YFoodGround×=
IW WFoodGround WT÷[ ] 100×=
VWW X e×=
VFoodGround YFoodGround MC WFoodGround+×=
IWW VFoodGround VWW÷( ) 100×=
XNewBOD
XBODWW VWW×( ) XBODFood VFood×( )+
VWW VFood+( )------------------------------------------------------------------------------------------------------=
VFood
MFood VExpFood×( )MExpFood
----------------------------------------------=
IBOD
XNewBOD XBODWW–( )XBODWW
--------------------------------------------------------- 100×=
XNewSS
XSSWW VWW×( ) XSSFood VFood×( )+
VWW VFood+( )---------------------------------------------------------------------------------------------=
ISS
XNewSS XSSWW–( )XSSWW
------------------------------------------------ 100×=
Effect of food waste disposers on municipal waste and wastewater management
Waste Management & Research 27
market penetration with 95% of the food ground), takinginto consideration minimum and maximum conventional
costs, are depicted in Fig. 6a and c, respectively. Thebreakeven points for the same scenarios, taking into consid-
Table 5: Economic benefit of food waste integration (2005 values).
Scenario S1a S1b S2a S2b S3a S3b
% of market penetration 25 25 50 50 75 75
% of food ground 75 95 75 95 75 95
Costs (MUS$/year) Cost of food disposer units (1) 4.6 4.6 9.1 9.1 13.7 13.7
Cost of added volume of domestic water (2) 0.4 0.5 0.8 1.0 1.2 1.5
Cost of wastewater treatment (3) 0.6–2.4 0.8–3.0 1.2–4.7 1.6–6.0 1.8–7.1 2.3–9.0
Conventional cost of sludge management (4) 0.1–1.0 0.2–1.3 0.3–2.0 0.3–2.5 0.4–3.0 0.5–3.8
Environmental cost of sludge management (5) 0.02–0.15 0.03–0.19 0.04–0.30 0.05–0.38 0.06–0.45 0.08–0.57
Conventional costs (6) 5.7–8.3 6.0–9.3 11.4–16.6 12.0–18.6 17.1–25.0 18.0–28.0
Environmental and conventional (7) 5.7–8.5 6.0–9.5 11.5–16.9 12.1–19.0 17.2–25.4 18.1–28.5
Savings (MUS$/year) Conventional solid waste savings (8) 9.9 12.5 19.8 25.1 29.7 37.6
Environmental solid waste savings (9) 4.6 5.8 9.1 11.6 13.7 17.4
Net benefits (MUS$/year) Based on conventional costs/savings (10) 1.6–4.2 3.2–6.5 3.1–8.4 6.4–13.0 4.7–12.5 9.6–19.5
% of existing SWM cost (12) 1.9–5.0 3.8–7.8 3.8–10.0 7.7–15.6 5.6–15.0 11.5–23.3
Based on conventional and environmental costs/savings (11) 6.0–8.7 8.8–12.3 12.0–17.5 17.6–24.6 18.0–26.2 26.4–36.8
% of existing SWM cost (12) 7.2–10.4 10.5–14.7 14.3–20.9 21.0–29.3 21.5–31.3 31.6–44.0
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
(12)
H
fAPinCFWD
CW
hBODdMinCWW
MinCBOD
MaxCWW
MaxCBOD
SSMinCSS
MaxCSS
Sll
MinCSl
MinCST
MaxCSl
MaxCST
MinECSl
MaxECSl
MinCMaxCMinECMaxECCSp
NEBmin
NEBmax
Pmin
Pmax
EPmin
EPmax
=
============
==
==
=
==
=====
=
======
=
=
=
=
=
=
Expected number of food waste disposers to be installed under studied scenarios (disposer unit)Number of capita/householdAnnual cost of a food waste disposer unit (US$) Initial cost of the food waste disposer unit (assumed to be US$ 400)Opportunity cost per household (5% per household) (US$)Expected economic life of a disposer (12 years – Wainberg et al. 2000)Total cost of food disposer units (MUS$/year)Cost of added domestic water consumption (MUS$/year)Annual domestic water charge rate (refer to Fig. 3).Added BOD loading (kg/day)Water density (1000 L/tonne)Total minimum cost of wastewater treatment (MUS$/year)Minimum cost of secondary wastewater treatment per kg of BOD (refer to Fig. 3) (US$/kg)Total maximum cost of wastewater treatment (MUS$/year)Maximum cost of secondary wastewater treatment per kg of BOD (refer to Fig.3) (US$/kg)Added SS loading (kg/day) Minimum cost of secondary wastewater treatment per kg of SS (refer to Fig. 3) (US$/kg)Maximum cost of secondary wastewater treatment per kg of SS (refer to Fig. 3) (US$/kg)Generated sludge due to integration of food disposers (tonnes/day):Average settable solids of the food waste adopted from the literature (3327 mg/L: Wainberg et al. 2000) Minimum conventional cost of sludge treatment (MUS$/year)Minimum cost of sludge treatment per dry tonne (refer to Fig. 3) (US$/dry tonne)Maximum conventional cost of sludge treatment (MUS$/year)Maximum cost of sludge treatment per dry tonne (refer to Fig. 3) (US$/dry tonne)Minimum environmental cost associated with sludge treatment (refer to Fig. 3) (MUS$/year)Maximum environmental cost associated with sludge treatment (refer to Fig. 3) (MUS$/year)Minimum conventional costs (MUS$/year)Maximum conventional costs (MUS$/year)Minimum environmental & conventional costs (MUS$/year)Maximum environmental & conventional costs (MUS$/year)Conventional savings (MUS$/year)Cost of managing 1 tonne of food waste under current ISWM scheme(collection, transportation, sorting, baling, and landfill disposal) (US$/tonne)Net benefits based on minimum environmental and conventional savings/costs (MUS$/year)Net benefits based on maximum environmental and conventional savings/costs (MUS$/year)% of existing SWM cost based on minimum conventional savings/costs (MUS$/year)% of existing SWM cost based on maximum conventional savings/costs (MUS$/year)% of existing SWM cost based on minimum environmental and conventional sav-ings/costs (MUS$/year)% of existing SWM cost based on maximum environmental & conventional sav-ings/costs (MUS$/year)
H X f+( ) m×=
A P A/P i n, ,( ) A→ Pi 1 i+( )n
1 i+( )n 1–---------------------------= =
CFWD A H×=
CW VW h×=
BOD VFoodGround XBODFood d××=
SS VFoodGround XSSFood d××=
MinCWW BOD MinCBOD SS MinCSS×+×[ ] 365×=
MaxCWW BOD MaxCBOD SS MaxCSS×+×[ ] 365×=
Sl VFoodGround l d××=
MinCSl Sl MinCST× 365×=
MaxCSl Sl MaxCST× 365×=
MinECSl MinCSl 0.15×=
MaxECSl MaxCSl 0.15×=
MinC CFWD CW MinCWW MinCSl+ + +=
MaxC CFWD CW MaxCWW MaxCSl+ + +=
MinEC CFWD CW MinCWW MinCSl MinECSl+ + + +=
MaxEC CFWD CW MaxCWW MaxCSl MaxECSl+ + + +=
CS YFoodGround p 365××=
ES YFoodGround q 365××=
NBmin CS MinC–=
NBmax CS MaxC–=
NEBmin CS ES+( ) MinEC–=
NEBmax CS ES+( ) MaxEC–=
Pmin NBmin YFood r 365××( )÷[ ] 100×=
Pmax NBmax YFood r 365××( )÷[ ] 100×=
EPmin NEBmin YFood r 365××( )÷[ ] 100×=
EPmax NEBmax YFood r 365××( )÷[ ] 100×=
N. Marashlian, M. El-Fadel
28 Waste Management & Research
eration the maximum conventional and total (conventionaland environmental) costs, are depicted in Fig. 6b and d.Clearly, the introduction of food waste disposers under thelowest market penetration S1a, excluding environmentalexternalities, becomes non-profitable if the current cost ofSWM decreases by 52% (to reach US$ 57.1 per tonne)(Fig. 6a), taking into consideration the minimum conven-tional costs defined in Fig. 3 and Table 5. However, if themaximum conventional costs for wastewater and sludgemanagement were considered, the proposed system becomesnon-profitable if the current cost of SWM decreases by 26%only or down to US$ 88.5 per tonne (Fig. 6c). With theinclusion of externalities, the introduction of food disposersunder the same scenario (S1a) remains largely profitableeven if the cost of SWM decreases by 70% to reach US$ 35.3per tonne (if minimum costs were assumed) (Fig. 6d) or 98%to reach US$ 2.4 per tonne (if maximum costs wereassumed) (Fig. 6b). On the other hand, using the highestmarket penetration S3b, the proposed system becomes non-profitable under higher SWM cost reductions ranging from42% (reaching US$ 68.7 per tonne) (Fig. 6a) to 16% (reach-ing US$ 100.1 per tonne) (Fig. 6c), taking into considera-tion minimum and maximum conventional costs, respec-tively. With the inclusion of externalities, the margin ofsafety is higher and the proposed system remains profitableeven if the current SWM charging rate decreases by 60%(reaching US$ 46.9 per tonne) (Fig. 6b) to 88% (reachingUS$ 13.9 per tonne) (Fig. 6d).
Conversely, decision makers should consider the dynam-ics of economy of scale whereby it can be argued that the
cost of managing the remaining solid waste will increase ifthe total quantity of the waste to be managed has decreased.This will ultimately affect the total savings achieved fromthe SWM scheme as a result of integrating food waste dispos-ers. In this context and in order to define the cost of manag-ing the remaining solid waste generated ‘X’ (US$ per tonne)after the integration of food waste disposers at which the pro-posed system would breakeven, the worst case scenario interms of economy of scale (100% market penetration with100% food ground) was assessed. Excluding environmentalexternalities, the integration of food waste disposers willremain profitable until the cost/tonne of managing theremaining solid waste reaches 1.8 times the current chargingrate (US$ 223 per tonne). If environmental externalities areincluded, the integration of food waste disposers will still beprofitable up to a management cost of US$ 315 per tonne(2.6 times the current charging rate). Certainly, it is notexpected that the cost of SWM would reach such levels inthe study area in the near future, which justifies the adoptionof food waste disposers.
Limitations
Accomplishing the penetration levels assessed in this studyconstitutes the main constraint in the analysis presentedabove. The study assumes that food waste disposers are useddaily for the adopted market penetrations. This may not bethe case when residents are travelling or dine outsidealthough it is reasonable and relatively easier to integratefood waste disposers in restaurants. Furthermore, the labora-
Fig. 6: Breakeven points for S1a (25% market penetration + 75% of food grinded) and S3b (75% market penetration + 95% of food grinded) tak-ing into consideration the lower and upper range of costs (2005 values) (a) Based on minimum conventional costs; (b) Based on minimum total (conventional + environmental) costs; (c) Based on maximum conventional costs; (d) Based on maximum total (conventional + environmental) costs.
Effect of food waste disposers on municipal waste and wastewater management
Waste Management & Research 29
tory investigation was conducted using a relatively smallnumber of food waste samples, which may not be statisticallyrepresentative of the waste stream in the study area. Thefood waste was blended instead of ground, resulting in SSconcentrations that are lower than those reported in the lit-erature (Table 6). However, if the highest values for BODand SS loadings reported in Table 6 (Koning & Van derGraaf 1996) were considered in the economic analysis, theintegration of food waste disposers in the study area wouldremain beneficial. More explicitly, the net benefits achieved(2005 values) would constitute 7.5 to 32.7% of the existingSWM cost, taking into consideration the lower and upperrange of market penetration based on the minimum (con-ventional and environmental) total costs. The net benefitswould range from 0.5 to 6.3% of the existing SWM cost,based on the maximum total costs.
Concluding remarks
This study revealed that a reduction of 12 to 43% in the totalsolid waste stream could be achieved by integrating foodwaste disposers under market penetration ranging between25 and 75%, respectively. While no significant increase indomestic water consumption (for food grinding) and waste-water flow rates were expected, wastewater loadingsincreased by 17 to 62% (BOD) and 1.9 to 7.1% (SS). Con-cerns about increased sludge generation persist and its poten-tial environmental and economic implications may differwith location and therefore area-specific characteristics mustbe taken into consideration when contemplating the adop-tion of a strategy to integrate food waste disposers in thewaste-wastewater management system. In this study, theintroduction of food disposers into the waste and wastewater
Table 6: Effluent quality from food waste disposers.
Source Suspended solids (mg/L)4 BOD5 (mg/L)4
Wainberg et al. (2000)1 5834 11150
Koning and Van der Graaf (1996)2 10667 11648
Waste Management Research Unit (1994)1 10369 7524
NYC DEP (1990)1 5634 8078
Sinclair Knight (1990)3 6356 4000
Current study 1537 70421 Based on experimental works. 2Based on generic literature values. 3Based on theoretical calculations. 4Average of two experiments with triplicate analysis per experiment. BOD5, Biochemical Oxygen demand – 5 day.
Fig. 7: Proposed action plan for the integration of food disposers within an urban area.
N. Marashlian, M. El-Fadel
30 Waste Management & Research
management systems led to net economic benefits thatranged between 7.2 and 44.0% of the current solid wastemanagement cost. Food waste disposers can constitute a via-ble option (economically and environmentally) that couldreduce the load on the solid waste stream and minimize theamount of end waste requiring landfilling. The main techni-cal constraint lies in the ability to increase the loadingcapacity of wastewater treatment plants. Administratively, aproper action plan is needed to integrate food waste disposerswithin the SWM scheme of an urban area. Inadequate legis-lative and administrative frameworks and limited institu-tional capacity, as is the case in many developing countries,coupled with overlapping responsibilities of line Ministries,necessitate the role definition of the various parties involvedwhere such a policy is to be adopted. In this context, themain components that are required include: (1) Legislation,which entails the promulgation of a law for integrating food
waste disposers within new homes in form of building coderequirements; (2) Implementation, which comprises activi-ties or processes associated with law implementation withcorresponding responsibilities of line Ministries; and (3)Monitoring which consists of supervising the proper imple-mentation of the law. Equally important is a public awarenesscampaign with the first two phases of the plan. Figure 7depicts a typical action plan for the integration of food dis-posers within an urban setting taking into consideration thecurrent institutional framework in the study area.
Acknowledgements
Special thanks are extended to the United States Agency forInternational Development for its support to the Environ-mental Program and the Water Resources Center at theAmerican University of Beirut.
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REGIONAL WORKSHOP REGIONAL WORKSHOP ONON
THE COST OF THE COST OF ENVIRONMENTAL ENVIRONMENTAL
DEGRADATION DEGRADATION METHODOLOGYMETHODOLOGY
Session 14THE VALUE OF LIFE AND
HEALTH
REGIONAL WORKSHOP ONREGIONAL WORKSHOP ON
THE COST OF ENVIRONMENTAL THE COST OF ENVIRONMENTAL DEGRADATION METHODOLOGYDEGRADATION METHODOLOGY
Session 14aThe Value of Life and HealthThe Value of Life and Health
Burden of DiseaseBurden of Disease
Useful referencesUseful references
• Quantifying Environmental Health Impacts & Environmental Burden of Disease Series published by World Health Organization (WHO) @ www.who.int/quantifying_ehimpacts/en/
• Global Burden of Disease Methodology and Documentation @ www.who.int/whosis/en/
• WHO 2002. World Health Report 2002- reducing risks, promoting healthy life. Geneva, World Health organization. @ www.who.int/whr/2002/en/
(Figure 2.1 from EBD Series no. 1)
Environmental hazards/risk factorsEnvironmental hazards/risk factorsEnvironmental hazards/risk factorsEnvironmental hazards/risk factors
• Examples of environment-related health problems– Noise Hearing loss; Cardiovascular (?)– Biologically-contaminated water Diarrhea– Air pollution Exacerbation of asthma– Pesticide Acute poisoning; Neurotoxicity– Asbestos Lung cancer– Lead Neurocognitive deficits– Lack of safety Fatal and non-fatal injuries
Environmental hazards/risk factorsEnvironmental hazards/risk factors
Health is not the absence of disease and disability but the attainment of physical, mental, and social well-
being.
The role of environment becomes more significant if the holistic definition of health is adopted
• How does the environment affect health?– Direct effect
• Agent causes health problem– Indirect effect
• Reduction of immunity• Exacerbation of an existing health problem
Environmental hazards/risk factorsEnvironmental hazards/risk factors
CAUSAL WEBDistal social & economic causes
A causal web for lead exposureA causal web for lead exposure
(Figure 2.4 from EBD Series no. 1)
Health burden of environmentHealth burden of environment
We ask:We ask:
1. What fraction of the national 1. What fraction of the national burden of disease is attributable to burden of disease is attributable to environmental risk factors? environmental risk factors?
2. What is the burden of disease 2. What is the burden of disease attributable to a specific attributable to a specific environmental risk factor?environmental risk factor?
Measuring Health Impacts Measuring Health Impacts
• Two links to be established in estimating monetary values of changes in human health associated with environmental changes
1.Link between environmental change and change in health status• Establishing DRRs• Establishing DALYs
2.Link between change in health status and its monetary equivalent • Establishing a WTP
Link 1
Link 2
Measuring Health ImpactsMeasuring Health Impacts
• Health impacts of pollution may be well recognized– Air pollution
• From itchy eyes and chest discomfort• To chronic bronchitis, asthma attacks, and premature death
– Inadequate water supply and sanitation• Diarrhea, intestinal nematodes and other diseases
• Health impacts measured via– Various types of studies including
• Epidemiology and field studies• Human clinical studies• Laboratory and toxicology studies
• Epidemiologic studies allow the establishments of– Dose-response relations (DRR) linking environmental variables
with observable health effects• DRRs established for air pollutants
– Burden of disease in terms of DALYs
Measuring Health ImpactsMeasuring Health Impacts
• Types of studies that provide evidence of the impacts of exposure to pollutants– Epidemiology and field studies
• Involve estimating a statistical relationship between the frequency of specific health effects observed in a study population and measured levels of pollutants
• Types of studies– Cohort studies
» Analyze the incidence of health effects in a sample of identified individuals usually selected specifically for the study
» Allows better control of risk factors since characteristics of individuals are well known
– Population studies» Rely on the data available for the population as a whole rather
than tracking the effects on specific individuals» Readily available and cost-effective
Measuring Health ImpactsMeasuring Health Impacts
• Types of studies that provide evidence of the impacts of exposure to pollutants– Epidemiology and field studies
• Advantages– Provide sufficient information to infer a concentration-
response function used to predict a change in the number of cases of a given health effect and pollutant concentration
– Define health effects in terms of factors that can be directly related to perceived welfare
» Risks of premature death» Days with noticeable symptoms
• Limitations– Uncertainty about whether the causal factors for the
observed association with health effects has been fully and accurately specified
Measuring Health ImpactsMeasuring Health Impacts
• Types of studies that provide evidence of the impacts of exposure to pollutants– Human clinical studies
• Examine response of human subjects to pollutant exposure in a controlled laboratory setting
• Can provide evidence of causation because confounding variables are well controlled
• Advantages– Provides more accurate dose-response information
• Limitations– Limited to considerations of short-term reversible health
effects that can be induced on purpose in human subjects– Requires assumptions to link human exposure in real life to
health effect
Measuring Health ImpactsMeasuring Health Impacts
• Types of studies that provide evidence of the impacts of exposure to pollutants– Laboratory and toxicology studies
• Use animal subjects and human tissue or cells to study biological responses to pollutants in a controlled laboratory setting
• Provide important information about specific biological pathwaysand mechanisms by which pollutants cause harm to living organisms
• Advantages– Pollutant exposures well-controlled and variations in confounding
factors reduced– Can consider both long term and short term exposures
• Limitations– Requires analysis and assumptions to link human exposure in real-life
to laboratory exposure – Uncertainty in extrapolating data from animal subjects to human
populations– Sometime focus on health effects that are difficult to interpret in terms
of specific symptoms
Measuring Health ImpactsMeasuring Health Impacts
• DRRs– Correlate mortality and morbidity outcomes for susceptible
population groups with ambient concentration of a given air pollutant
– Epidemiological studies associated with air pollution• Time series• Cross-sectional
– Most studies have focused on mortality effects
Measuring Health ImpactsMeasuring Health Impacts• DRRs- Example
Estimated increments in annual health effects associated with unit change in pollutantsOutcome PM10
(10μg/m3)SO2
(10μg/m3)Ozone(pphm)
Lead(1.0 mg/m3)
NO2(pphm)
Premature mortality (% change) 0.96 0.48
Premature mortality/ 100,000 6.72
Respiratory hospital admissions/100,000 12 7.7
Emergency room visits/100.000 235.4
Restricted activity days/person 0.575
Lower respiratory illness/child 0.016
Asthma symptoms/asthmatic 0.326 0.68
Respiratory symptoms/person 1.83 0.55
Chronic bronchitis/100,000 61.2
Minor restricted activity days/person 0.34
Respiratory symptoms/1,000 children 0.18
Respiratory symptoms per adults 0.1 0.1
Eye irritations/person 0.266
Burden of Disease (Burden of Disease (BoDBoD))
• BoD study– aims to quantify the burden of premature mortality and disability
for major diseases or disease groups– Uses a summary measure of population health (DALY) to
combine estimates of the years of life lost and years lived withdisability
– Data are broken down by age, sex, and region
• Global Burden of Disease (GBD)– Constituted the most comprehensive set of estimates of mortality
and morbidity yet produced (Murray and Lopez, 1996)– WHO now regularly develops BoD estimates at regional and
global level for a set of more than 135 causes of disease and injury
– National BoD studies involve obtaining country-specific estimates for input to national policy
Measuring the Measuring the Burden of Disease Burden of Disease
is a TOOL for is a TOOL for setting health prioritiessetting health priorities
Why do we need robust processes Why do we need robust processes for setting priorities?for setting priorities?
• To ensure that health care resources are used in the most appropriate manner
• To achieve maximum health benefits using available resources
Prioritize actions
Other uses of measures of Other uses of measures of Burden of DiseaseBurden of Disease
• Evaluating health interventions• Predicting health gains from interventions• Evaluating policy programs• Estimating performance indicators and
assessing trends over time • Making comparison between regions• Identifying high risk groups
Criteria/ information used in Criteria/ information used in setting health prioritiessetting health priorities
• Goals for population health• Current and projected estimates of
burden of disease• Human, financial, and logistic resources• Historical trends in policy focus• Interest & pressure groups (local and
international)
Indicators that can be used to Indicators that can be used to assess theassess the Burden of DiseaseBurden of Disease
• Incidence• Prevalence
• Mortality• Morbidity• Disability
Cost:– Medical care– Lost productivity– Social burden
PrevalencePrevalence• Prevalence is the number of existing
cases in a given population over a specified time period
– Number of diabetics per 100,000 in 2007– Number of asthmatics per 1000 children less
than 5 years old in 2007
Old + New cases in a given population
IncidenceIncidence• Incidence is the number of new cases in a
given population over a specified time period
– Number of new cases of diabetes in 2007 among 100,000 who had no diabetes on January 1, 2007
– Number of new cases of asthma in 2007 among 1,000 children less than 5 years old with no asthma on January 1, 2007
Challenges to interpretationChallenges to interpretation
• How does a death at the age of 20 years compare with a death at the age of 70 years?
• How do 200 acute respiratory infections compare to 400 cases of infectious diarrhea?
(EBD Series no. 1; page 4)
None of the individual None of the individual indicators is sufficient. indicators is sufficient. There is a need for a There is a need for a
composite indexcomposite index to assess BODto assess BOD
A summary measure of life lost due to disease plus disability associated with
living with the disease relevant to a measure of expected population health
Burden of Disease (Burden of Disease (BoDBoD))
Disability Adjusted Life Years (DALY)– Measures health gaps as opposed to health
expectancies, using time measures– Measures the difference between
• a current situation and an ideal situation
An ideal situation is where “everyone lives up to the standard life
expectancy and in perfect health”
Burden of Disease (Burden of Disease (BoDBoD)) Burden of Disease (Burden of Disease (BoDBoD))
Disability Adjusted Life Years (DALY)– YLL
• Corresponds to the number of deaths multiplied by the standard life expectancy at the age at which death occursYLL = N × L
Where:N = number of deathsL = standard life expectancy at age of death in years
Burden of Disease (Burden of Disease (BoDBoD))
Disability Adjusted Life Years (DALY)– YLD
• Estimated by measuring the incidence of disability and the average duration of each disability
• Number of disabilities is multiplied by the average weight factor that reflects the severity of the disease on a scale from 0 (perfect health) to 1(dead)
• Years of Life with Disability (without applying social preferences):
YLD = I × DW × LWhere:
I = number of incident casesDW = disability weightL = average duration of disability (years)
Burden of Disease (Burden of Disease (BoDBoD))Disability Adjusted Life Years (DALY)
– Disability weights• Quantify societal preferences for different health states• DO NOT represent the lived experience of any disability or
health state• DO NOT imply any societal value for the person in the disability• Example
– A weight for paraplegia of 0.57– Does NOT mean
» Person in this health state is half dead» Person experience life as half way between life and death» Society values them less as a person compared to healthy people
– It means» Society judges a year with blindness (0.43) to be preferable than a
year with paraplegia» Society would prefer living for 3 years followed by death (1.7 lost
healthy years) than have one year of good health followed by death (2 lost healthy years)
Burden of Disease (Burden of Disease (BoDBoD))
Disability Adjusted Life Years (DALY)– Disability weights example (Murray and Lopez, 1996)
Disease Mean disability weight
Disease Mean disability weight
AIDS 0.5 Asthma, cases 0.10
Infertility 0.18 Deafness 0.22
Diarrhea disease, episode 0.11 Brain injury, long term 0.41
Measles episode 0.15 Spinal cord injury 0.73
Tuberculosis 0.27 Sprains 0.06
Malaria episode 0.20 Burns (> 60%) long term 0.25
Cancer, terminal stages 0.81 Congestive heart failure 0.32
Parkinson disease cases 0.39 Benign prostatic hypertrophy 0.04
Alzheimer disease cases 0.64
Birth 80 years60 years
2. Cerebrovascular death at age 60expected lifetime - age at death
Birth 60 years50 years
1. Stroke at age 50 with paraplegia (death 60)duration of disability x severity weight
20 YLL
10 x 0.7 YLD
TOTAL DALYs for this person=YLD + YLL= 7 + 20 = 27
Burden of Disease (Burden of Disease (BoDBoD))
1 DALY = one lost year of healthy life
Burden of Disease (Burden of Disease (BoDBoD))
• Challenges/ Ethical issues– What is the ideal condition? What is perfect health?– How sensitive are measures to gender and regional
differences?– Are all years of life equivalent?
• Age weighting: young adulthood more valuable than infancy and old age
• Discount rate: a year of perfect health today is more valuable than a year of perfect health 10 years later
– Is there an “objective” measure of disability?
Burden of Disease (Burden of Disease (BoDBoD))
Disability Adjusted Life Years (DALY)– Other social values
• Age weightsA year of healthy life lived at younger and older ages was weighted lower than for other ages
– Various studies have shown a broad social preference to value a year lived by a young adult more than a year lived by a young child or lived at older ages
– Age weights in DALYs are controversial• Time discounting
The net present value of lives lost was estimated using a 3% discount rate
– Studies have shown that people prefer a healthy year of life immediately, rather than in the future
– BoD studies may or may not include time discounting and age weights depending on local preference
Burden of Disease (Burden of Disease (BoDBoD))
Disability Adjusted Life Years (DALY)– Calculating DALYs with a 3% discount rate
• YLL:
• YLD:
)1( e rL
rNYLL −−=
Where:N = number of deathsL = standard life expectancy at age of deathr = discount rate (0.03)
)1( e rL
rLDWIYLD −−
××=
Where:I = number of incident casesDW = disability weightL = duration of disability in yearsr = discount rate (0.03)
Burden of Disease (Burden of Disease (BoDBoD))
Disability Adjusted Life Years (DALY)– Calculating DALYs with age weight and a 3%
discount rate• YLL:
)1(1]]1)([]1))(([[)(
)())((2 e rLaraLr
ra
rKareaLre
rKCeYLL −+−++− −
−+−+−−−++−
+= ββ
βββ
Where:a = age of death (years)r = discount rate (0.03)β = age weight ing constant (Ex: β = 0.04)K = age weighting modulation constant (Ex: K =1)C= adjustment constant for age-weights (Ex: C = 0.1658)L = standard life expectancy at age of death (years)
Burden of Disease (Burden of Disease (BoDBoD))
Disability Adjusted Life Years (DALY)– Calculating DALYs with age weight and a 3%
discount rate• YLD:
)}1(1]]1)([]1))(([[)(
{ )())((2 e rLaraLr
ra
rKareaLre
rKCeDWYLD −+−++− −
−+−+−−−++−
+= ββ
βββ
Where:a = age of death (years)r = discount rate (0.03)β = age weighting constant (Ex: β = 0.04)K = age weighting modulation constant (Ex: K =1)C= adjustment constant for age-weights (Ex: C = 0.1658)L = duration of disability (years)DW = Disability weight
Burden of Disease (Burden of Disease (BoDBoD))
• Disability Adjusted Life Years (DALY)– Example
YLL for diarrhea
Burden of Disease (Burden of Disease (BoDBoD))
• Disability Adjusted Life Years (DALY)– Example
YLD for Alzheimer
Burden of Disease (Burden of Disease (BoDBoD))
• Other issues to remember– Priorities are not decided on the basis of
numbers only– DALY measure is health focused– other gains
are not considered
Same principles for..Same principles for..
• Global Burden of Disease (GBD) studies• National Burden of Disease (NBD) studies
• Nationally:– Sub-regional data– Modify disability weights, adjustment rates,
life expectancy, etc. for national purposes– Comparison to other countries requires
adherence to universal method
Illustration from the Illustration from the National Burden of Disease National Burden of Disease
Study in LebanonStudy in Lebanon
The case of Coronary The case of Coronary Heart Disease (CHD)Heart Disease (CHD)
Presented at the “Fighting Together Cardiovascular Diseases” ConferenceLebanese Order of Physicians, BeirutFebruary 19-21, 2004
CHD: Flow chartCHD: Flow chart
Lebanese population
CHD: Prevalence/ incidence
Angina Myocardial infarction
HospitalizationComplications
Mortality/ Survival rate
Social burden
Surgical intervention
What do we need?What do we need?• Prevalence data by age, sex, and region.• Proportion hospitalized• Long-term survival Cohort• Complications studies
Need for gender and social analysis
Prevalence of CHD (%) Prevalence of CHD (%)
< 40 40-49
50-59
60-69
>=70 All ages
Beirut 1994(Nuwayhid et al., 1997)
M 0.0-0.9 4.6 11.7 15.0 24.1 4.3F 0.2-0.9 3.2 8.2 16.4 24.4 3.9
NHHEUS 1999 M + + + + + 3.8F + + + + + 3.3
Prostate screening 1997-98
M + + + 15
Several hospital-based studies:Male hospitalized patients toFemale hospitalized patients = 3-4
CHD: Flow chartCHD: Flow chart
Lebanese population
CHD: Prevalence/ incidence
Angina MI
HospitalizationComplications
Mortality/ Survival rate
Social burden
Surgical intervention
Hospital admissionsHospital admissions
• 4500 out of 60000 (7.5%) hospital discharge diagnoses in Beirut were due to CHD.
• 13% of all 3981 hospital admissions were due to vascular/circulatory diseases (NHHEUS 1999)
CHD: Flow chartCHD: Flow chart
Lebanese population
CHD: Prevalence/ incidence
Angina MI
HospitalizationComplications
Mortality/ Survival rate
Social burden
Surgical intervention
Hospital survivalHospital survival• 201 MI patients in 1993 (Jazra et al., 1995):
– 29 (18 M) died within 1 week (14.4%)– Death rate increased with age
• 443 MI admissions in 1996 (Sawaya et al., 1999): – 99 Females– Mortality rate (males): 7%, 5%, 11%, and 13% for
<=50, 51-60, 61-70, and >70– Mortality rate (females): 8%, 12%, 16%, and 25% for
<=50, 51-60, 61-70, and >70
Proportionate CVD mortality Proportionate CVD mortality (1966(1966--1996)1996)
Study (year) % CVD mortality
Beirut (1966-67):Death certificates 48.4Beirut (1983-84):Household survey 17.2Beirut (1992-93): F/U HH survey 42.4Beirut (1998): Death certificates 32.0Beirut (PHS 1996): Household survey 39.4Lebanon (PHS 1996): HH survey 34.9
PopulationPopulation--based mortality based mortality rate rate (Sibai et al., 2001) (Sibai et al., 2001)
• 1567 (50+ years) men and women (Beirut- 1983)
• Follow-up in 1993• Total deaths in 10 years = 416
– 40% ischemic heart disease– 13% Cerebrovascular disease– 7% Other CVD
PopulationPopulation--based mortality based mortality rate (continued) rate (continued) (Sibai et al., 2001)(Sibai et al., 2001)
• Total deaths in 10 years = 416• Mortality rate due to IHD:
– 16.2 per 1000 person-years (95% CI 3.5-19.5) for males
– 7.6 per 1000 person-years (95% CI 5.8- 9.9) for females
CHD: Can we calculate its CHD: Can we calculate its DALY?DALY?
Lebanese population
CHD: Prevalence/ incidence
Angina MI
HospitalizationComplications
Mortality/ Survival rate
Social burden
Surgical intervention
Global Burden of Disease Global Burden of Disease (WHO)(WHO)
Selected results
Results Results -- global leading causes of global leading causes of deaths deaths …… and and …………DALYsDALYs
Cardiovascular 29%Neoplasms 13%Injuries 9% Respiratory 7%HIV/AIDS 5% Perinatal 4%Diarrhoea 4%TB 3%Malaria 2%Traffic accidents 2%Depression <1%
Cardiovascular 10%Neoplasms 5% Injuries 12%Respiratory 6% HIV/AIDS 6% Perinatal 7%Diarrhoea 4%TB 3%Malaria 3%Traffic accidents3%Depression 5%
2001 data, World Health Report 2002
Projected Change in Rank Order:2020 vs. 1990
Burden of Disease and Injury Attributable to Selected Risk Factors in the World in 1990
Environmental Burden of DiseaseEnvironmental Burden of Disease
We ask:We ask:
1. What fraction of the national 1. What fraction of the national burden of disease is attributable to burden of disease is attributable to environmental risk factors? environmental risk factors?
2. What is the burden of disease 2. What is the burden of disease attributable to a specific attributable to a specific environmental risk factor?environmental risk factor?
What is attributable risk?What is attributable risk?
(Figure 2.2 from EBD Series no. 1)
Attributable risk is the excess risk that can be attributed to a specific exposure
(risk among exposed - background risk i.e., risk among non-exposed)
More on attributable riskMore on attributable risk
• If the specific exposure is controlled, then the excess risk attributed to it will be reduced
• However, the excess risk can be attributed to more than one risk factor– For example, lung cancer is attributed to cigarette
smoking and ambient air pollution
• Hence, if one exposure is controlled, the fraction of the remaining excess risk attributed to the other exposure will change
Two types of attributionsTwo types of attributions
• Categorical attribution– Event attributed to a single cause even if it is
associated with multiple causes (e.g., death can result from a combination of malnutrition and measles, but the case of death is attributed to either malnutrition or measles)
– Used in GBD and NBD studies
• Counterfactual attribution– The scenario with (e.g., 50% of population smoke) is
compared to the scenario without (e.g., none smoke)– Used in Environmental Burden of Disease studies
and the like
Why measure the Environmental Why measure the Environmental Burden of Disease (EBD)?Burden of Disease (EBD)?
• To set action priorities in health and the environment• To plan for preventive action• To assess performance• To compare/ contrast benefits from different actions• To identify high-risk populations• To plan for future needs• To predict impact of future environmental changes• To set research priorities in health and the environment• To guide policy making
Environmental Burden of Disease Series, No. 1Introduction and methods: Assessing the environmentalBurden of disease at national and local levels. WHO, 2003
Conceptual frameworkConceptual framework
*
Health Outcome
Risk factor A
Risk factor B
Risk factor C
Environmental risk factor
* Proportion attributed to environmental risk factor
ExamplesExamples
• What fraction of asthmatic cases can be attributed to air pollution?
• What proportion of cancer can be attributed to smoking? Asbestos?
• What proportion of diarrhea can be attributed to lack of hygiene and sanitation?
• What proportion of new cases of malaria can be attributed to climate change?
Sources of evidence on association Sources of evidence on association between environmental risk factor between environmental risk factor
and health outcome is neededand health outcome is needed
• Epidemiological (population-based) studies • “Natural” experimental studies
– Intentional and non-intentional incidents– Disasters (human-made or natural)
• Designed experimental studies– Human– Animal
Key information neededKey information needed
1. Indicators for selected environmental problems/areas
Examples of Examples of environmental indicatorsenvironmental indicators
• Water, sanitation and hygiene
• Ambient air pollution
• Lead
• Climate change (coastal floods)
• Water supply coverage• Sanitation coverage
• PM10 (annual mean)
• Blood lead
• Sea level rise• Frequency of coastal
floods
Key information neededKey information needed
1. Indicators for selected environmental problems/areas
2. Data on these indicators (regularly)
Key information neededKey information needed
1. Indicators for selected environmental problems/areas
2. Data on these indicators (regularly)3. Health indicators
Examples of health indicatorsExamples of health indicators
• Water supply coverage• Sanitation coverage
• PM10 (annual mean)
• Blood lead
• Sea level rise• Frequency of coastal
floods
• Diarrhea
• Mortality from cardiopulmonary disease
• Mental retardation• Loss of IQ points• Anemia
• Deaths and injuries
Key information neededKey information needed
1. Indicators for selected environmental problems/areas
2. Data on these indicators (regularly)3. Health indicators4. Data on health indicators
Key information neededKey information needed
1. Indicators for selected environmental problems/areas
2. Data on these indicators (regularly)3. Health indicators4. Data on health indicators5. Fraction of health outcomes attributed to
the environmental hazard
Causal web for fecalCausal web for fecal--oral transmission: oral transmission: which indicator to use?which indicator to use?
(Figure 4.3 from EBD Series no. 1)
Practical approachPractical approach
• Complicated causal pathways are simplified
• Easier parameters are used more
Main global findings Main global findings (Pruss(Pruss--Ustun et al. 2008)Ustun et al. 2008)
• 13-37% of countries’ disease burden (about 13 million deaths per year) can be prevented by environmental improvements– 4 million deaths could be prevented by
improving water, sanitation, and hygiene• Environmental DALYs = 14 – 316 per
1000 capita per year
The Burden of The Burden of Outdoor Air PollutionOutdoor Air Pollution
Ostro B. Environmental Burden of Disease Series, No. 5.
Outdoor air pollution: Assessing the environmentalburden of disease at national and local levels.
WHO 2004.
Global burden of Global burden of Outdoor Air PollutionOutdoor Air Pollution
• 1.4% of total mortality• 0.4% of all DALYs• 2% of all cardiopulmonary
disease
Indicators (markers)Indicators (markers)
• Indicator for air pollution (environmental)– Particulate matter (PM10 or PM2.5)
• Health indicator– Mortality
• Mainly older people (with pre-existing cardiovascular and respiratory disease) and infants
– Morbidity• Hospitalization and emergency room visits• Asthma attacks, bronchitis, respiratory symptoms• Lost work and school days
Sources of evidenceSources of evidence
• Smog incidents in cities in Europe and the USA
• Epidemiological studies– Fixed monitor sites (hot spots might be
missed)– Limited to large cities (> 100,000)– Most limited to PM (many excluded ozone
and other air pollutants)– Most limited to PM10 not PM2.5
Increase of daily total mortality Increase of daily total mortality per 10 ug/mper 10 ug/m33 PM10PM10
• 0.8% (0.5-1.1%) (Schwartz et al. 1996)
• 0.7% (0.2-1.2%) (Burnett et al. 2000)
• 0.6% (Katsouyanmi et al. 2001)
• 0.27% (Dominici et al. 2002)
0.8% (0.5-1.6%) for the USA
• 0.6% for Europe (WHO 2004)
• 0.4-0.6% for Asia (HEI 2004)
Increase of daily total mortality Increase of daily total mortality per 10 ug/mper 10 ug/m33 PM10 PM10
in nonin non--Western countries and citiesWestern countries and cities
• Bangkok: 1.7% (1.1-2.3%) • Mexico City : 1.83% (0.9-2.7%)• Santiago: 1.1% (0.9-1.4%)• Inchon (S. Korea): 0.8% (0.2-1.6%)
In some cities, the air pollution is very high with PM10 exceeding 200 ug/m3. Recommended to cap the range for the assumption of linearity
PM2.5= 0.5 PM2.5= 0.5 –– 0.65 PM100.65 PM10
Model inputs for determining cityModel inputs for determining city--specific PM10 concentrationsspecific PM10 concentrations
• Energy consumption• Atmospheric and geographical factors • City and national population density• Local urban population density• Local intensity of economic activity• National income per capita• Time trends• Binary variable for each country
Relative risk functions for Relative risk functions for mortality and lung cancermortality and lung cancer Relative Risk (RR)= exp [Relative Risk (RR)= exp [ββ (X(X--XX00)] )]
Child and infant mortality Child and infant mortality related to PM10related to PM10
Steps 1Steps 1--55• Assess ambient exposure of the population to
PM (PM10 or PM2.5)– Fixed monitoring vs. Modeling– Need for background concentration (comparison
region)• Determine size of population groups exposed to
PM10 and PM2.5• Determine type of health effect of interest
(Cardiopulmonary diseases and Lung cancer)• Estimate the incidence of health effect• Use concentration-response functions
(epidemiological studies) that relate ambient concentrations of PM to selected health effects
Step 6Step 6• Estimate the following:
– Number of cases of premature mortality and DALYs (cardiopulmonary and lung cancer) attributed to long-term exposure to PM2.5 for people > 30 years old
– Number of cases of premature mortality and DALYs from respiratory diseases attributed to short-term exposure to PM10 for children < 5 years old
– Number of cases of premature mortality from all causes from short-term exposure to PM10
EEnd of nd of SSession ession 14a14a
Thank YouThank You
REGIONAL WORKSHOP ONREGIONAL WORKSHOP ON
THE COST OF ENVIRONMENTAL THE COST OF ENVIRONMENTAL DEGRADATION METHODOLOGYDEGRADATION METHODOLOGY
Session 14bThe Value of Life and HealthThe Value of Life and Health
Value of Life and HealthValue of Life and HealthIntroductionIntroduction
• Two links to be established in estimating monetary values of changes in human health associated with environmental changes
1.Link between environmental change and change in health status• Establishing DRRs• Establishing DALYs
2.Link between change in health status and its monetary equivalent • Establishing a WTP
Link 1
Link 2
Value of Life and Health Value of Life and Health Valuating Health ImpactsValuating Health Impacts
Methods for valuing health impacts
Value of Life and Health Value of Life and Health Human Capital Approach (HCA)Human Capital Approach (HCA)
• Considers individuals as units of human capital that produce goods and services for society
• Measures loss of productivity resulting from an individual’s – death (Work Loss Days-WLD)– injury (Restricted Activity Days-RAD)
• Human life and time spent ill or recovering are valued using forgone earnings
• WLD and/or RAD estimated for– specific individuals in a detailed study– average individuals, which is most commonly applied
• HCA usually provides a lower-bound estimate
HCA =(# of Life Years Lost due to premature death or due to illness)
×(Average Wage Rate)
Value of Life and Health Value of Life and Health Human Capital ApproachHuman Capital Approach
• Values calculated are dependent on income, skill level, and country of residence
• Considered as the most difficult and controversial aspect of valuing health effects associated with environmental changes
Age group (yrs) Life years lost Mortality cost (1992 US$)
< 5 75 502,4215-14 68 671,88915-24 57 873,09625-44 42 785,58045-64 25 278,35065+ 10 22,977
Human capital and mortality cost by age in the US
Cost estimates are based on life-expectancy at the time of death and includelabor-force participation rates, average earnings, the value of home-makingservices, and a 6% discount rate
Value of Life and Health Value of Life and Health Human Capital ApproachHuman Capital Approach
• Applying HCA1. Specify the type of economy for the population of
interest2. Specify the characteristics of the economy for the
population of interest3. Specify the family and community structure4. Specify the unit of analysis5. Specify the desired measure of productivity changes6. Estimate the maximum loss in productive time as a
result of the health outcome• Requires information as to the groups of patients that are
working• Requires decisions about value of time of children and retired
people
Value of Life and Health Value of Life and Health Human Capital ApproachHuman Capital Approach
• Problems with HCA– Faces difficulty in accurately estimating forgone earnings
• Employee’s compensation includes more than wages– Pension plans, health insurance, flexible hours
– Does not provide information about the individual’s WTP to reduce probability of loss of life
– Does not measure net contribution to society• Assumes full employment and no substitutability of labor• Assumes a dominant cash economy where there exists market prices
which is not the case in developing countries– Ignores non-market activities important to individuals– Undervalues retired people, children, and home-makers– Estimated value highly depends on discount rate used
• The higher the discount rate, the lower the economic value of children– Does not value pain and suffering, the individual’s own well-
being and preferences, and the sentiments of the society
Value of Life and Health Value of Life and Health Human Capital ApproachHuman Capital Approach
Value of Life and Health Value of Life and Health Cost of Illness (COI) ApproachCost of Illness (COI) Approach
COI provides a lower-bound estimate
Value of Life and Health Value of Life and Health Cost of Illness (COI) ApproachCost of Illness (COI) Approach
Direct costs• Useful economic tool as it indicates the direction and
magnitude of the economic flows resulting from health shocks to the economy
• Easily understood and often readily available being based on available market and expenditure data
• COI provides an estimate of an individual welfare loss– Direct expenditures do not correspond to a drop in income
or consumption for the economy as a whole, but constitute a redirection of economic activity, with some sectors benefiting from increased activity
Value of Life and Health Value of Life and Health Cost of Illness (COI) ApproachCost of Illness (COI) Approach
Direct costs• COI does not provide a direct measure of disease severity
– Direct medical expenditures are influenced by income distribution
• Increased income is accompanied with increased consumption of health care
– Direct medical expenditures reflect the ability of current medical techniques to treat the disease under consideration
• Example treatment of malaria is expected to generate fewer expenditures than treatment of cold because the former has few remedies as compared to the latter
• COI not only measures disease severity but also the population’s education, skill level, income, insurance coverage, types of medical interventions currently available, etc.
Value of Life and Health Value of Life and Health Cost of Illness (COI) ApproachCost of Illness (COI) Approach
Direct costs• Issues pertaining to its application
– Difficulty to disaggregate hospital payments• Drugs administered on the premise• Salaries paid to health professionals and staff…
– Inaccuracies in hospital diagnostic data and the fact that expenses might not be attributed to the correct illness
– A number of illnesses may be grouped under one diagnostic code making it hard to decipher individual expenses
– Large data sets assume the same charge for all types of physician services
• A visit for a routine checkup does not cause the same as a visitfor cancer
– Treatment of multiple conditions where all expenses are allocated to the patient’s primary condition
Value of Life and Health Value of Life and Health Cost of Illness ApproachCost of Illness Approach
• Estimation of direct cost of medical care (WASH, 1991)1. Estimate proportion of those affected at each level of severity of the
disease2. Estimate the proportion of those desiring treatment who have access
to treatment3. Specify the process of treatment for each level of severity of the
disease• Resource use• Number of inpatient days• Outpatient visits
4. Estimate the unit costs of resources used for treatment and the side effects for each level of severity of the disease taking into account that many fixed costs are not affected by reductions in the use of the health service
5. Estimate total treatment costs for each level of severity of the disease without intervention
6. Determine the proportion of the costs that can be avoided in theshort- and long-run
7. Determine the direct costs that would have been avoided
Value of Life and Health Value of Life and Health Hedonic PricingHedonic Pricing
• Involves the valuation of incremental morbidity or mortality by identifying wage differentials due to risk differences
• Based on the assumption that there is a fixed supply of jobs and a freely functioning job market where individuals choose jobs based on perfect information and with no mobility restrictions
• Based on the theory that workers have to be paid a premium to undertake jobs that are inherently risky, which can be used to estimate the implicit value individuals place on sickness or premature death
• Estimates of VOSL in the US– 1.9-10.7 million USD (1990 dollars)
Value of Life and Health Value of Life and Health Hedonic PricingHedonic Pricing
Where: P = payment rate for a given jobS = vector of skills required to do the jobJ = vector of other job-related attributes (working hours, holiday, sickness benefits)R = risk of death
Value of Life and Health Value of Life and Health Hedonic PricingHedonic Pricing
• Issues and limitations– Difficulty in assessing an objective measure of
the risk of death– Contains a high degree of uncertainty– Requires considerable data sets for
regression analysis, containing data on all relevant and confounding variables
– Results are not transferable between countries due to differences in attitudes to risk and incomes
Value of Life and Health Value of Life and Health Contingent Valuation MethodContingent Valuation Method
Value of Life and Health Value of Life and Health Contingent Valuation MethodContingent Valuation Method
Value of Life and Health Value of Life and Health Contingent Valuation MethodContingent Valuation Method
• Benefit transfer• Values may be adopted from the other countries by
adjusting for per capita income as follows
Per capita income of country i = Xi
⇒ Income ratio Xj/Xi
Per capita income of country j = Xj
⇓
Value of mortality or morbidity outcome in country i = Yi
⇒ Multiply Yi by Xj/Xi ⇒
Value of mortality or morbidity outcome in country j = Yj
Value of Life and Health Value of Life and Health Contingent Valuation MethodContingent Valuation Method
• Advantages of a CVM– Can take into account non-use values– Can be designed to include only the variables or
characteristics of the market relevant to the objective of the study
– Allows individuals to consider the true costs to themselves of a particular injury or illness
– CVM results are repeatable• In terms of similarity in results across different settings• Using a test-retest methodology
Value of Life and Health Value of Life and Health Contingent Valuation MethodContingent Valuation Method
• Problems associated with CVM– Does not require cash transactions– Biases: Strategic, design, hypothetical, etc.– Survey responses cannot be verified except
through comparison with actual behavior following survey
– WTP vs. WTA– Short time given to respondents to think about the
answer– In developing countries, questionnaires need to
be adapted carefully and trained researchers are required to administer the surveys
Value of Life and Health Value of Life and Health Contingent Valuation MethodContingent Valuation Method
• Issues to consider– WTP questions should be clear and unambiguous– Respondents must be familiar with the valued
commodity• Health risk studies involving common, mild illnesses
have a greater chance of being understandable, meaningful, plausible, than severe, rare diseases
– Respondents should have prior valuation/ choice experience with respect to consumption levels of the commodity in order to give it well-formed values
Value of Life and Health Value of Life and Health Disability Adjusted Life Years (DALY)Disability Adjusted Life Years (DALY)
• The VOSL obtained from wage differential and contingent valuation studies may be linked with the corresponding number of DALYs lost in a specific study and so estimate the implicit value per DALY
• The cost of a DALY lost valued by two approaches– DALY (yrs) × GDP/capita (USD/year)
• Based on the rationale that the economic value of a year lost to illness or early death is the productive value of that year, which is approximated by GDP per capita
• Usually represents the lower bound estimate• Has nothing to do with the non-economic value of life in general
– DALY (yrs) × WTP for mortality reduction• Based on the willingness-to-pay (WTP) by an individual to reduce the
risk of death.• Valuations arrived at, in studies in the United States and Europe that
apply WTP, are substantially higher than the GDP per capita approach (at least for adults)
Value of Life and Health Value of Life and Health Valuating Health ImpactsValuating Health Impacts
Types of benefits Market value(COI, HCA)
Avertive expenditure
Hedonic pricing
Contingent valuation
Improved health-related quality of life
Improved life expectancy
Medical cost avoided ( )Reduced time spent in care ( )Reduced travel expenses to care ( )Reduced avertive expenditure ( ) ( )Increased productivity ( )Reduced sick leave ( )
= preferred method; ( ) = second best method
Recommended methods of valuation for health-related benefits of environmental health interventions
EEnd of nd of SSession ession 1414
Thank YouThank You
REGIONAL WORKSHOP REGIONAL WORKSHOP ONON
THE COST OF THE COST OF ENVIRONMENTAL ENVIRONMENTAL
DEGRADATION DEGRADATION METHODOLOGYMETHODOLOGY
Sessions 14 & 15Valuation of Life and Health
CASE-STUDIES
REGIONAL WORKSHOP ONREGIONAL WORKSHOP ON
THE COST OF ENVIRONMENTAL THE COST OF ENVIRONMENTAL DEGRADATION METHODOLOGYDEGRADATION METHODOLOGY
Sessions 14 & 15Valuation of Life and HealthValuation of Life and Health
CASECASE--STUDIESSTUDIES
CaseCase--StudiesStudies
• Drinking Water Quality: A health-based socio-economic assessment
• Socio-Economic Benefits of Leaded Gasoline Phase-out, Lebanon
• PM in urban areas: health-based economic assessment, Lebanon
• Economic Benefits of Reducing Particulate and Sulfate Emissions from the Cement Industry, Lebanon
Drinking Water Quality: A Drinking Water Quality: A healthhealth--based sociobased socio--
economic assessmenteconomic assessment
CASE DESCRIPTIONCASE DESCRIPTIONOutlineOutline
SOCIO-ECONOMICBURDENS
UNCLEANwater
Water-related DISEASES
INADEQUATEwater supply
&
CASE DESCRIPTION CASE DESCRIPTION Public Water Supply in BeirutPublic Water Supply in Beirut
• Falls under the responsibility of 2 water authorities under the jurisdiction of the MEW– Beirut Water Authority
• Serves Beirut Municipal District and Northern Suburbs
– Ain El Delbe Water Authority• Serves the Southern Suburbs of Beirut and
Damour
• Water supply situation in Beirut is inadequate
Intermittent supply in most areas&
Lack of piped water for a large number of the poor
CASE DESCRIPTION CASE DESCRIPTION Existing conditions of water supplyExisting conditions of water supply
Weak water utilities+
Water scarcity
22 % of the population are NOT connectedto the public water supply system -mainly in the suburbs(CDR, 1998; CAS, 1997)
CASE DESCRIPTION CASE DESCRIPTION Other Sources of Water SupplyOther Sources of Water Supply
• Two main supplementary water sources are– private wells and/or on water vending
• Water Vending– Consumers, in the direct southern suburbs of
Beirut, resort to small-scale private water providers – Water Vendors
– Around 800 water shops are distributed randomly all over Lebanon
– The majority of shops operate without any regulatory authorization
CASE DESCRIPTIONCASE DESCRIPTIONForms of water vendingForms of water vending
Mobile water trucks
Water tanks within shops Water tanks providedby political organizations
CASE DESCRIPTIONCASE DESCRIPTIONWater Quality in LebanonWater Quality in Lebanon
• Various studies were conducted to examine the quality of water in Lebanon– Analyses by Central Laboratory– Study on vended vs. bottled water– Study on water quality in pilot area
• The studies revealed that– Water quality in the Lebanese public supply
system is variable– Quality of vended water is unacceptable
CASE DESCRIPTION CASE DESCRIPTION Analyses by Central LaboratoryAnalyses by Central Laboratory
• 2001 statistics reported by the Central Laboratory, revealed pollution of water supply
Water source TotalBottled water Network water Groundwater
Samples exhibiting microbiological pollution
97 (24%) 345 (24%) 450 (37%) 892 (36%)
Total number of samples analyzed
403 863 1215 2481
CASE DESCRIPTION CASE DESCRIPTION Study on Vended Water Vs. Bottled WaterStudy on Vended Water Vs. Bottled Water
• Samples included– 65 samples from water vending shops– 23 samples of bottled water
• Analysis conducted at AUB– pH, Conductivity, Salinity– Total Hardness, Nitrates– Total and Fecal Coliform
• Results– Poor quality of some samples of Vended Water with
respect to microbiological indicators– Acceptable quality of Bottled Water
Percent of samples exceeding MOI bottling Percent of samples exceeding MOI bottling water guidelineswater guidelines
• 15 samples were collected from the public supply– Main station along the coast, the two reservoirs
uphill and dead ends in the network– Household taps, after being stored in roof tanks
to be used for domestic purposes– Public locations
• Results– Acceptable quality in terms of physico-chemical
and microbiological characteristicsNo microbiological contamination
CASE DESCRIPTION CASE DESCRIPTION Study on the water quality in a pilot Study on the water quality in a pilot
areaarea
CASE DESCRIPTION CASE DESCRIPTION Study on the water quality in a pilot area Study on the water quality in a pilot area
(cont(cont’’d)d)• 20 private wells were randomly sampled• Results of analysis
Percent of samples exceeding USEPA drinking water guidelines
CASE DESCRIPTION CASE DESCRIPTION Health Impacts of Water PollutionHealth Impacts of Water Pollution
Polluted water + Water shortage + Unsanitary living conditions
• 2.3 billion people in the world suffer from water-borne diseases
with over 12 million death per year
• Water-related health impacts in Lebanon
Short & Long-term HEALTH RISKS
Hence, providing clean water & ensuring proper sanitation facilities reduces prevalence of water-related diseases
Disease Geographic extent Number of cases a Deaths per year WATER-BORNE DISEASES
Diarrheal disease Worldwide 500 million/yr 3-4 million
Cholera South America, Asia, Africa 384,000/yr 20,000
Hepatitis A Worldwide 600,000 – 3 million/yr 2,400-12,000
Paratyphoid & typhoid
80% in Asia, 20% in Latin America, Africa 16 million currently 600,000
Polio 66% in India, 34% in Near East, Asia, Africa 82,000 currently 9,000
WATER-BASED DISEASES Ascariasis Africa, Asia, Latin America 250 million currently 60,000
Clonorchiasis Southeast Asia 28 million currently None reported
Dracunculiasis (guinea worm)
78% Sudan, 22% in other Sub-Saharan Africa, and few cases in India and Yemen
153,000/yr None reported
Paragonimiasis Far East, Latin America 5 million currently None reported
Schistosomiasis (bilharzias)
Africa, Near East, rain forest belt in Central Africa, Western Pacific, Cambodia, Laos
200 million currently 20,000
WATER-RELATED VECTOR DISEASES
Dengue Tropical environments, concentrated in Asia, Central and South America
50-100 million/yr 24,000
Filariasis Africa, Eastern Mediterranean, Asia, South America
120 million currently None reported
Malaria Africa, Southeast Asia, India, South America 300-500 million/yr (clinical)
2 million
Onchocerciasis Sub-Saharan Africa, Latin America 18 million currently None reported b
Rift Valley Fever (RVF)
Sub-Saharan Africa NA c 1% of cases
Major WaterMajor Water--Related DiseasesRelated Diseases(Muller & (Muller & MoreraMorera, 1994; WHO, 1996, 1998), 1994; WHO, 1996, 1998)
CASE DESCRIPTION CASE DESCRIPTION Health impacts of water pollution in Health impacts of water pollution in
LebanonLebanon• Lebanon suffers from adverse health
impacts as a result of water pollution• Prevalent water related-diseases include
– Diarrhea– Typhoid & paratyphoid– Hepatitis A
• Data are limited due to absence of proper disease reporting mechanism– Mortality data– Morbidity data
CASE DESCRIPTION CASE DESCRIPTION Mortality dataMortality data
“Each child under 5 is exposed, on average, to 3.5 incidents of diarrhea each year, causing the death of 750 children per year”
(UNDP, 1990)Note: This value may be an overestimation due to improvement in
water supply & sanitation
CASE DESCRIPTION CASE DESCRIPTION Morbidity dataMorbidity data
Average annual number of reported incidents for the years 1995-2000(Ministry of Health, Directorate of Preventive Medicine)
CASE DESCRIPTION CASE DESCRIPTION Mitigating adverse waterMitigating adverse water--related related
health impactshealth impacts
• Several studies examined the impact of improved water supply and sanitation– Expected reduction in morbidity rates
– Variation of effect of intervention with type of disease
Expected reductions in morbidity from water & Expected reductions in morbidity from water & sanitation improvements (sanitation improvements (EsreyEsrey et al., 1991; et al., 1991;
Dougherty & Hall, 1995)Dougherty & Hall, 1995)
Disease Percent reduction in morbidity Diarrheal diseases 26-50 Typhoid 80 Paratyphoid 40 Infective hepatitis 10 Ascariasis 29-40 Cholera 90 Dracunculiasis 78 Onchoserciasis 20? Hookworm infection 4 Schistosomiasis 60-77 Trachoma 27-60 Guinea worm 100
Potential relations between water and sanitation Potential relations between water and sanitation interventions and morbidity from selected diseases interventions and morbidity from selected diseases
((EsreyEsrey et al., 1991)et al., 1991)
Disease Intervention
Improved drinking water
Water for domestic hygiene
Water for personal hygiene
Sanitation
Ascariasis +1 ++2 -3 ++
Diarrhea + ++ ++ ++
Dracunculiasis ++ - - -
Hookworm infection
- - - ++
Schistisomiasis - ++ ++ ++
Trachoma - + ++ - 1 + = strong impact; 2++ = stronger impact; 3- = little or no impact
ECONOMIC VALUATION OF ECONOMIC VALUATION OF HEALTH IMPACTSHEALTH IMPACTS
• Associated with few constraints– Actual identification and measurement of health
impacts– Estimation of monetary values for associated
mortality and morbidity– Establishing dose response functions (DRFs)
“it is not ambient water quality per se that affects health but access to clean drinking water and adequate sanitation along with household level of income and education”
ECONOMIC VALUATION OF ECONOMIC VALUATION OF HEALTH IMPACTSHEALTH IMPACTS
• Methods of economic valuation– Economic valuation of mortality effects
• Human Capital Approach (HCA)• Willingness to Pay (WTP)/Willingness to Accept
(WTA) Approach– Economic valuation of morbidity effects
• Cost of Illness Approach (COI)• WTP/WTA Approach
• Economic valuation of health impacts in Lebanon
APPLIED METHODAPPLIED METHODHuman Capital Approach (HCA)Human Capital Approach (HCA)
• Measures loss of productivity resulting from an individual’s death or injury
HCA provides a lower-bound estimate.Yet, it is the best alternative in the absence of WTP data
HCA =(# of Life Years Lost due to premature death)
×(Average Wage Rate)
Advantages Disadvantages• Easily measured • Biased against groups with low wages
• Assigns no value to lives of old and retired
• Assigns no value to leisure time
APPLIED METHOD APPLIED METHOD WTP/WTA ApproachWTP/WTA Approach
• Assesses from market behavior– WTP for reduced risks of increased
mortality/morbidity– Or WTA increased risk of increased
mortality/morbidityTotal Benefit/Cost= ∑WTP of all concerned members of the society
= Value of Statistical Life (VOSL)
Advantages Disadvantages
• Correct valuation method• Captures the value of less
tangible changes in productivity
• Difficult to collect data
APPLIED METHOD APPLIED METHOD Cost of Illness (COI) ApproachCost of Illness (COI) Approach
• Measures the direct cost of morbidity in terms of– Medical expenditure for treatment– Lost wages during days spent in bed– Days missed from work, etc.
• Compared to the WTP approach,
COI provides a lower-bound estimate.Yet, it is the best alternative in the absence of WTP data
Advantages Disadvantages
• Required data generally obtained with more accuracy
• Obtained estimates can be better communicated
• Incomplete due to insufficient information
• Does not include non-tangible entities
RESULTSRESULTSEconomic Assessment of water quality Economic Assessment of water quality
in Lebanonin Lebanon
• Mortality estimation using HCA
• Mortality estimation using WTP
• Morbidity estimation using COI
• Estimation of mortality and morbidity reduction
• Uncertainty
RESULTS RESULTS Mortality estimation using the HCA Mortality estimation using the HCA
approachapproach• Assumptions– Average Lebanese monthly salary = 400 USD– Productivity age range = 20-65 years
• Reported mortality– 750 deaths/year– Children less than five years of age
• Calculation– (400 USD/month) × (12 months/year) × (45 years of lost
productivity) = 216,000 USD per case
According to the HCA, the total economic cost of premature death incurred in Lebanon, and caused by water pollution is 162 million USD, assuming the same number of premature deaths as reported by the UNDP in 1995
RESULTS RESULTS Mortality estimation using the WTP Mortality estimation using the WTP
approachapproach
• WTP data are lacking in Lebanon• Values are adopted from the US as
followsPer capita income of country i = Xi
⇒ Income ratio Xj/Xi
Per capita income of country j = Xj
⇓
Value of mortality or morbidity outcome in country i = Yi
⇒ Multiply Yi by Xj/Xi ⇒
Value of mortality or morbidity outcome in country j = Yj
RESULTS RESULTS Mortality estimation using the WTP Mortality estimation using the WTP
approach (contapproach (cont’’d)d)
• WTP estimates range between 0.6-13.5 MUS$
• Ratio of GNP per capita in Lebanon to US = 0.1 (World Bank, 1999)
• Value of statistical life in Lebanon ranges between 0.06-1.35 MUS$
The total cost of mortality ranges from 45 to 1,012.5 MUS$
RESULTS RESULTS Morbidity estimation using the COI Morbidity estimation using the COI
approachapproach• COI incurred by society from water-related
diseases consists of several elements– Cost of hospitalization– Cost of medication– Lost productivity– Cost of transportation
• The diseases are restricted to– Dysentery– Hepatitis A– Typhoid & Paratyphoid
• Total of COI
RESULTS RESULTS Morbidity estimation using the COI Morbidity estimation using the COI
approach (contapproach (cont’’d)d)
• The water-related illnesses are gastroenteritic in nature– They have the same hospitalization cost
per day– Cost varies with class of admission
Admission class Social Security Third class Second class First classPhysician visits (USD per day)
13.3 24 40 64
Hospital room (USD per day)
22.5 33 56 90
Laboratory (USD per stay)
127 218 240 285
Variation of hospitalization cost with class of admission
• Length of hospital stay, recovery at home, and medication cost vary with type and severity of disease
Hospital stay Recovery at home Length of stay
(days) Medication
cost (USD per day)
Length of stay (days)
Medication cost
(USD per day) Range Average Range Average Dysentery 2-4 3 15 0-1 1 0 Hepatitis A 3-7 5 10 7-14 10 10 Typhoid 3-7 5 40 5-10 7 30
Average length of stay and medication cost per disease
RESULTS RESULTS Morbidity estimation using the COI Morbidity estimation using the COI
approach (contapproach (cont’’d)d)
• Productivity loss– Productivity loss per day of leave from work = 18.2 USD
(per capita GDP = 400 USD; working days per month = 22)
– 52.2 % of cases are in the productive age(Based on age distribution of Lebanese population)
– Productivity loss of care-providers was disregarded• Transportation costs
– Roundtrip visit costs 1-3 USD– 3 roundtrips conducted per day of illness
RESULTS RESULTS Morbidity estimation using the COI Morbidity estimation using the COI
approach (contapproach (cont’’d)d)
Total # of days of restricted activity
Lost productivity (USD/case)
Transportation cost (USD/case)
Dysentery 2-5 36.4-91 6-45 Hepatitis A 10-21 182-382.2 30-189 Typhoid 8-17 145.6-309.4 24-153
Lost productivity & transportation costs per disease
RESULTS RESULTS Morbidity estimation using the COI Morbidity estimation using the COI
approach (contapproach (cont’’d)d)• Upon summing up all input data, the total
COI incurred by society from the water-related diseases under study ranges between 613,295 - 2,664,502 USD
Number of reported cases
Cost of illness per case (USD/case)
Total cost of illness (USD)
Dysentery 529 254-1,054 134,366-557,566 Hepatitis A 287 389-1,822 111,643-522,914 Typhoid 809 454-1,958 367,286-1,584,022 Total 613,295-2,664,502
RESULTSRESULTSEstimation of Mortality & Morbidity Estimation of Mortality & Morbidity
ReductionsReductions• Estimates the benefits associated with the reduction in
prevalence of diseases/mortality upon provision of clean water supply and ensuring proper sanitation
Estimated benefit =Reported # of cases × Expected % reduction × Cost per case
Parameter Diarrhoeal diseases
Typhoid paratyphoid
Infective hepatitis
Mortality
Number of cases 529 809 287 750 Percent reduction (%) 26-50 60 10 55 Number of cases avoided 138-264 485 29 412
Cost per case (USD) 254-1,054 454-1,958 389-1,822 (0.06-1.35) × 106 Economic benefit (million USD/year)
0.035-0.278
0.220-0.949
0.011-0.053 25-557
RESULTS RESULTS Summary of socioSummary of socio--economic benefits due to economic benefits due to
provision of clean water & proper provision of clean water & proper sanitationsanitation
Endpoint Number of cases avoided
Total economic benefits (MUS$/yr)
Mortality 412 25-557 Morbidity 652-778 0.27-1.28 Total 1,064-1,190 25.27-558.28
RESULTS RESULTS UncertaintyUncertainty
• Absence of population-based vital and disease registries
• Assumptions adopted related to transportation costs, age distribution of ill, cost of lost productivity
• The reliance on epidemiological studies reviewed in the literature (WTP)
• The assumption that all diarrhea, typhoid, paratyphoid, and hepatitis A are due to water pollution
• The disregard of effects of other water contaminants
EEnd of nd of CCasease SStudytudy
Thank YouThank You
SocioSocio--Economic Benefits of Economic Benefits of Leaded Gasoline PhaseLeaded Gasoline Phase--out, out,
LebanonLebanon
Case DescriptionCase DescriptionStudy area Study area -- LebanonLebanon
• Relatively old vehicle fleet → high pollutant emission rates
• Prior to August 2002, leaded gasoline (max 0.66 g/l lead (Pb)) predominantly used
• Physiological effects of Pb:– Biochemical effects (anemia, interference with enzyme
synthesis)– Neurobehavioral effects (IQ deficiency, mental
retardation, hyperactivity) in children– Increased probability of hypertension & cardiovascular
diseases
Correlation Between Lead used and BLL in the US
Correlation betweengasoline lead contentand airborne leadlevels in the US
0
30
60
90
120
150
180
1974 1976 1978 1980 1982 1984
Lead
con
sum
ed in
gas
olin
e (1
000
tons
)
0
0.25
0.5
0.75
1
1.25
1.5
Com
posi
te m
axim
um q
uarte
rly a
vera
ge le
ad
leve
ls (m
g/m3
)
lead in gasoline Lead in air
9
10
11
12
13
14
15
16
17
1976 1977 1978 1979 1980 1981
Aver
age
BLL
(mg/
dl)
40
50
60
70
80
90
100
110
Tota
l lea
d us
ed p
er
6 no
nths
(100
0 to
ns)
BLL Lead used in Gasoline
Correlation betweengasoline lead contentand airborne leadlevels in the US
Case DescriptionCase DescriptionPb levels measurement in LebanonPb levels measurement in Lebanon
Air (μg/m3) Blood (μg/dl)
WHO 0.5-1 20
US 1.5 10
EU 2 NA
Australia 1.5 10
Canada 5 10
Regulations for Pb in air & blood (Hashisho and El-Fadel, 2001)
12.6
21.4
37
17.513.4
20.3 19.5
44
14.3 13.5
2215.8 15.8
0
20
40
60
Ret
ail S
hop
Mec
hani
cs
Rad
iato
r
Aut
obod
y
Car
ele
ctric
Grin
ding
/Iron
Car
lice
nce
plat
es
Smel
ting
Gas
Sta
tions
Car
pent
ry/W
ood
Fact
ory
Veh
icle
/Stre
et
Ave
rage
Workplace
Blo
od le
ad le
vels
(g/
dl)
Average Standard Deviation
BLL for working adults: Mean BLL = 15.8 μg/dl
BLL in 10-17 year old Mean BLL = 9.75 μg/dl for students; 11.36 for
working students; 13.54 for workers
0
20
40
60
<5 5-9 10-14 15-19 >=20BLL (μg/dL)
Perc
ent w
ithin
BLL
rang
e
Students Students/workers Workers
0
20
40
60
80
<5 5-9 10-14 15-16BLL (μg /dL)
Perc
ent
with
in B
LL ra
nge
BLL in 1-3 year old healthy children: Mean BLL = 9.75 μg/dl
Manual job of the father
Living in an area with traffic jams
Low income
Applied methodApplied methodImpact assessment & CBAImpact assessment & CBA
• Impact of use of leaded gasoline was examined: using dose-response functions for children & adults derived by the USEPA
• Cost benefit analysis of Pb phase out was conducted: using income-adjusted mortality and morbidity figures from US
Per capita income of country i = Xi
⇒ Income ratio Xj/Xi
Per capita income of country j = Xj
⇓
Value of mortality or morbidity outcome in country i = Yi
⇒ Multiply Yi by Xj/Xi ⇒ Value of mortality or morbidity outcome in country j = Yj
Applied methodApplied methodValuation techniquesValuation techniques
• Costs– Cost of switching consists of:
cost of lubricant additives, additional transportation costs to access new suppliers
– 0.01-0.02 USD/liter(worldwide experience)
– Not adjusted for income as driven by international market
– Distribution system adjustment costs are minor & can be neglected (same system is used but once-and-for-all cleaned, different pump nozzle size)
• Benefits– Mortality: WTP approach– Morbidity: COI approach– Morbidity & mortality values
estimated for the US in the year 1990 were used
– Figures were adjusted for• Inflation to the year 1998 (by
multiplication with an inflation factor of 1.2547)
• Income (using an income ratio of 0.12, as GNP in 1999 was 29340 USD for USA, & 3560 USD for Lebanon)
Applied MethodApplied MethodAssumptions Assumptions
• Population of major urban areas only are considered (about 1,639,000)
• Lebanese population age distribution• Population within each age group evenly distributed by age• BLLs independent of age in children and adults• Average BLL in women 64 percent of that in men• BLL in pregnant women the same as that in non-pregnant ones
80 60 40 20 0 20 40 60 80
0-4
10-14
20-24
30-34
40-44
50-54
60-64
70-74
>80
Age distribution per thousand personsMale Female
ResultsResultsHealth impact assessmentHealth impact assessment
• Tables show respectively health impact assessment in– Children: number of
avoided cases for a 77% reduction in BLL
– Adults: number of avoided cases for a 78% reduction in BLL
EffectNumber of cases
Average Range
Total IQ point loss (points) 42,689 35,176 - 48,495
Mental retardation (cases) 167 NA
Child Mortality (cases) 31 NA
Effect Age group
Number of cases
Mean Minimum Maximum
Hypertension men 20 - 74 1,688.3 NA NA
CHD men 40 - 59 54.6 15.3 133.0
60 - 64 24.1 10.0 482.6
65 - 74 30.7 3.3 152.4
CHD women 45 - 74 46.8 12.2 122.2
CA men 45- 74 42.7 7.7 162.5
CA women 45 - 74 22.9 4.6 77.3
BI men 45 - 74 26.5 3.8 127.4
BI women 45 - 74 16.8 3.0 63.3
Mortality men 40 - 54 50.9 21.1 0.01
55 - 64 36.1 6.8 121.2
65 - 74 12.9 5.4 78.0
Mortality women 45 - 74 25.0 5.3 75.8
ResultsResultsHealth benefitsHealth benefits
Health outcomeCost per case
(1998 USD)Cost (1998 USD) x 1000
Average RangeTotal IQ Loss 450 19,217.5 13,414.7 – 25,175.5
Mental retardation 8,023 1,069.3 NA
Child Mortality 730,754 22,427.0 NA
Total - 42,713,8 36,911.0 – 48,671.8
Effect Cost per case (1998 USD)
Average cost(1998 USD) x 1000
Cost range (1998 USD) x 1000
Hypertension men 104 175.0 NA
CHD men 7,916 867.5 226.3 – 6,079.7
CHD women 7,916 370.8 96.4 – 967.7
CA men 30,448 1,301.2 233.6 – 4,947.1
CA women 22,836 521.9 104.2 – 1,766.4
BI men 30,448 808.2 114.6 – 3,880.6
BI women 22,836 384.2 69.4 – 1,444.4
Mortality men 730,754 66,799.7 21,796.8 – 145,578.9
Mortality women 730,754 18,286.6 3,836.7 – 55,379.5
Total - 89,514.2 26,653.1 – 220,219.3
Children
Adults
ResultsResultsCar related benefitsCar related benefits
• In the US, car maintenance savings from the use of unleaded gasoline are about 0.003 to 0.024 USD/Liter
• Cost savings from improved fuel efficiencyare about 0.0024 USD/Liter
Car-related maintenance Leaded UnleadedSpark plug changes Every year Every other year
Oil changes and filter Twice per year One per year
Muffler replacements Twice per 5 years One per 5 years
Exhaust pipe replacements One per 5 years None
ResultsResultsCBA CBA –– Summary tableSummary table
Economic parameters
Costs(1998 million USD)
Benefits*(1998 million USD)
Capital investments 11.3 7.6 - 15.1 NA NAHealth
Not applicable
132.2 63.6 - 268.9Car maintenance 1.4 0.3 - 2.4 Energy efficiency 0.3 NATotal per capita benefit (USD/capita) 35.9 17.2 - 72. 9
LEAD PHASE OUT IS ECONOMICALLY HIGHLY FEASIBLE
*Previous values were adjusted for income
EEnd of nd of CCasease SStudytudy
Thank YouThank You
PM in urban areas: healthPM in urban areas: health--based economic based economic
assessment, Lebanonassessment, Lebanon
Case DescriptionBackground
• PM is recognized as most important air pollutant in terms of health impacts, reportedly associated with:
– Increase in cardiac and respiratory mortality;– Decrease in levels of pulmonary lung function in children and adults;– Increase in daily prevalence of respiratory symptoms in children and adults;– Increase in functional limitations (school absenteeism, restricted activity days);– Increase in physician and emergency department visits for asthma and other
respiratory conditions.
International Standard Long-term (μg/m3) Short-term (μg/m3)1
PM10 BS TSP PM10 BS TSP
EU limit values NA2 80 150 NA 250 300
EU guide values NA 40-60 NA NA 100-150 NA
USEPA 50 NA 260 150 NA 75
WHO guidelines NA 40-60 60-90 NA 100-150 150-230
WHO guidelines for Europe NA 50 NA 70 125 120
1 24 hours2 NA = not available
Case DescriptionCase DescriptionStudy area - Lebanon
• Air quality measurements showed that:– TSP concentrations range
from 102 to 291 μg/m3 (with an average of 166 μg/m3)
– High levels– Contributed by:
• Vehicle-induced emissions• Vehicle movement on dusty
roads• On-going construction
activities• Anthropogenic sources• Dry climate (→ high dust
levels in the atmosphere)
0 1 2 3Km
SAMPLING LOCATION
NORTH
NORTH
9
87
26
131 4
1 2
3
1110
212019
17
18
1
22
5
4
16
MED
ITE
RR
AN
EA
N S
EA
0
100
200
300
1 2 3 4 6 8 9 10 11 12 14 16 17 18 19 20 21 22
TSP,
g/
m3
Average166 μg/m3
USEPA 24-hr standard
Applied methodApplied methodHealth assessment & valuationHealth assessment & valuation
• Assessment of health impacts– Average levels of ambient concentrations are related
to health effects through dose-response functions(DRFs)
– DRFs are related to the population at risk• Assessment of associated monetary value:
unit economic values are applied to the cases avoided by a 10 μg/m3 reduction in PM10 values using the following approaches– Human capital approach– COI approach: does not include the less tabgible
impacts to the individual’s well-being– WTP approach
Applied methodApplied methodWorldwide health impacts DRFsWorldwide health impacts DRFs
Particulate Percent increasein mortality
Percent increasein morbidity
Morbidity Type
Increase of 10 μg/m3 in PM10 0.1-4.6 0.2-2.90.8-11.50.2-6.40.6-1.20.4-6.00.3-0.41.1-24.90.4-13.01.6-17.6
Pneumonia hospital admissionsCOPD1 hospital admissionsRespiratory hospital admissionsCardiac hospital admissionsEmergency cases of asthmaBronchitis hospital admissionsLRI2 symptomsURI3 symptomsCough symptoms
Increase of 10 μg/m3 in PM2.5 0.4-3.7 0.41-24.63.7-20.9
Respiratory hospital admissionsAsthma hospital admissions
Increase of 10 μg/m3 in BS NR4 0.07-18.20.3-5.31.2-16.5
Respiratory hospital admissionsAsthma hospital admissionsCOPD hospital admissions
Increase of 100 μg/m3 in TSP 3.3-8.3 NR NR1 COPD = chronic obstructive pulmonary disease2 LRI = lower respiratory illness3 URI = upper respiratory illness4 NR = not reported
Applied methodApplied methodData for mortality assessment in Data for mortality assessment in
Lebanon Lebanon –– HC approachHC approach
Sex1 Age group2
0-9 10-19 20-39 40-59 60-69 >70 Unknown TotalMale (51) 5.54 2.67 9.60 18.31 21.35 37.48 5.07 100.00
Female (49) 6.50 2.91 4.00 13.30 17.18 51.13 5.00 100.00
Total (100) 5.93 2.77 7.31 16.27 19.66 43.03 5.03 100.00
Sex Age group0-9 10-19 20-39 40-59 60-69 >70 Unknown Total
Male (51) 0-17 0-8 1-30 1-58 1-67 3-118 0-16 6-314
Female (49) 0-20 0-9 0-12 1-40 1-52 3-155 0-15 5-303
Total (100) 0-37 0-17 1-42 2-98 2-119 6-273 0-31 11-617
Percent distribution of death in Lebanese households
Distribution of predicted lives saved per year for a 10 μg/m3 reduction in PM10
The annual death rate of 8.2 deaths/1000 persons was multiplied by the urban Lebanese population of 1.64 million → 13440 deaths multiplied by the percent distribution of Lebanese population by age
group and sex
Applied methodApplied methodData for mortality assessment in Data for mortality assessment in
Lebanon Lebanon –– WTP approachWTP approach
Study 1 Valuation/ case(MUS$/yr)2
Study Valuation/ case(MUS$/yr)
R. S. Smith 1974 7.2 Herzog & Schlottman 1987 9.1
R. S. Smith 1976 4.6 Leigh 1987 10.4
V.K. Smith 1976 4.7 Gerking et al 1988. 3.6
Viscusi 1978 4.1 Moore and Viscusi 1988 2.5
Olson 1981 5.2 Moore and Viscusi 1988 7.3
Viscusi 1981 6.5 Gaten 1988 13.5
Marin et al. 1982 2.8 Cousineau et al. 1988 3.6
Butler 1983 1.1 Jones-Lee3 1989 3.8
Leigh and Folson 1984 9.7 Kneisner and Leeth 1991 0.6-7.6
Smith and Gilbert 1984 0.7 Miller and Guria3 1991 1.2
Dillingham 1985 0.9-3.9 Viscusi et al. 1991 2.7
Gegax et al.3 1985 3.31 Labor market estimate; 2 1990 dollar value; 3 Contingent valuation estimate
Values from US studies; to be adjusted for country GNP
Applied methodApplied methodData for morbidity assessment in Data for morbidity assessment in
Lebanon Lebanon –– COI approachCOI approachTotal hospital admissions per year
LebanonBeirutOther urban areas
400,000133,000
53,200
Type of hospital admission per year
Emergency visits in BeirutEmergency visits in other urban areasa. Respiratory and cardiac hospital admissions (%)b Respiratory admissions (% of a)c. COPD admissions (% of b)d. Pneumonia admissions (% of b)
145,00058,000
15373763
Percent decrease in morbidity due to 10 μg/m3 reduction in PM10
Pneumonia hospital admissionsCOPD hospital admissionsEmergency visits
0.2-2.90.8-11.50.3-12.6
Endpoint Change Total Cases avoided
Respiratory hospital admissions/100,000 6.6-17.3 108-284
Emergency department visits/100,000 116.0-354.0 1,902-5,806
Lower respiratory illness/child/asthmatic 0.010-0.024 4,756-11,414
Asthma attacks/person 0.33-1.96 541,200-3,214,400
Respiratory symptoms/person 0.8-2.56 1,312,000-4,198,400
Chronic bronchitis/100,000 30.0-93.0 492-1,525
Restricted activity days/person 0.29-0.58 475,600-951,200
Number of hospital admissions per health endpoint (as obtained from literature) was multiplied by the % decrease in endpoint hospital admissions due to a 10 μg/m3
reduction in PM10
Applied methodApplied methodData for morbidity assessment in Data for morbidity assessment in
Lebanon Lebanon –– WTP approachWTP approachValues from US studies; to be adjusted for country health care rates
1 1990 dollar value (USEPA, 1997)2 Lebanese valuation is obtained by multiplying the US valuation by the health care ratio (0.24)3 Lebanese valuation is obtained by multiplying the US valuation by the per capita GNP ratio (0.1)
Endpoint US Valuation (US$ / case)1
Hospital admission2
COPD 8,100
Pneumonia 7,900
All respiratory 6,100
Respiratory illness or symptom3
Chronic bronchitis 260,000
Acute bronchitis 45
Acute asthma 32
Acute respiratory symptoms 18
Upper respiratory symptoms 19
Lower respiratory symptoms 12
Restricted activity day3
Work loss days 83
Mild restricted activity days 38
Applied MethodApplied MethodAssumptions Assumptions
• There is no threshold below which PM10 is harmless or not a cause of mortality.
• No difference in susceptibility or exposure between different populations.
• Reviewed studies are of similar quality and need not be weighted for difference in methodology or sample size.
• Where an age-specific DRF is unavailable, the estimate for all age groups will be applied to the baseline number of deaths in each age group.
• The estimations are not restricted to a particular or an average value but ranges of values are considered in order to ensure a broader perspective of the subject.
ResultsResultsMortality benefits for 10 Mortality benefits for 10 μμg/mg/m33
reduction in PMreduction in PM1010
• Human capital approach– By multiplying average productivity years (25 to 69) by
average monthly salary (400 USD in 1998)– Average benefit per case is 0.055 million USD
Age group
# of lives saved
Average productivity years
Benefit(MUS$/yr)
40-59 2-102 20 0.2-9.7
60-69 3-122 5 0.07-2.9
Total 0.27-12.6
Average per case1 0.0551 Average total economic benefit divided by the average total number of
lives saved
HC Approach• WTP approach
– Values from US studies were adjusted for country GNP using a ratio of 0.1
– Average benefit per case ranges between 0.06 and 1.35 million USD
ResultsResultsMorbidity benefits for 10 Morbidity benefits for 10 μμg/mg/m33
reduction in PMreduction in PM1010• Cost of illness
– By multiplying # of cases avoided by corresponding health endpoint cost
– High benefits can be generated
Endpoint Avergae Stay(Days) 1
Average cost(US$/day) 1
Economic benefit(MUS$/yr)
COPD 6.6 261 0.06-0.9
Pneumonia 10 207 0.03-0.4
Emergency visit - 76 0.05-1.9
Total 0.14-3.21 Based on survey data from the American University Hospital
and insurance companies (Djoundourian et al., 1998)
ResultsResultsMorbidity benefits for 10 Morbidity benefits for 10 μμg/mg/m33
reduction in PMreduction in PM1010• WTP approach
– US values were adjusted using a health care ratio of 0.24 (obtained by comparing cost of COPD & pneumonia in Lebanon & US; higher than income ratio → health care is expensive in Lebanon)
Endpoint US Valuation (US$ per case)1 Lebanese Valuation (US$ per case)
Hospital admission2
COPD 8,100 1,944
Pneumonia 7,900 1,896
All respiratory 6,100 1,464
Respiratory illness or symptom3
Chronic bronchitis 260,000 26,000
Acute bronchitis 45 5
Acute asthma 32 3
Acute respiratory symptoms 18 2
Upper respiratory symptoms 19 2
Lower respiratory symptoms 12 1
Restricted activity day3
Work loss days 83 8
Mild restricted activity days 38 4
1 1990 dollar value (USEPA, 1997b)
2 Lebanese valuation is obtained by multiplying the US valuation by the health care ratio (0.24)
3 Lebanese valuation is obtained by multiplying the US valuation by the per capita GNP ratio (0.1)
ResultsResultsSummary table Summary table
Endpoint Number of cases avoided
Total Economic benefit(MUS$/yr)
COI1 WTP2
Mortality3 11-617 0.27-12.6 3.5-157.9
All COPD 31-441 0.06-0.9 0.98-13.9
All Pneumonia 13-189 0.03-0.4 0.05-0.7
Emergency visits 609-25,578 0.05-1.9 NA4
Total 0.41-15.8 4.53-172.5
Percent of GDP5 0.003-0.1 0.03-1.06
Percent of adjusted GDP6 0.03-1 0.3-10.61 COI = cost of illness; 2 WTP = willingness to pay; 3 Human capital approach; 4 NA = not available; 5 World Bank, 19986 Adjusted GDP assuming that the construction and transportation sectors are the main sources of particulate emissions in urban areas and
accounting for source/sector contribution to GDP and percent of urban population exposed as compared to total country population.
Benefits of reducing PM concentration in the air can be significant; they are dominated by mortality valuation although the number of
mortality cases is relatively small.
EEnd of nd of CCasease SStudytudy
Thank YouThank You
Economic Benefits of Economic Benefits of Reducing Particulate and Reducing Particulate and
Sulfate Emissions from the Sulfate Emissions from the Cement Industry, LebanonCement Industry, Lebanon
0
1
2
3
4
5
1993 1994 1995 1996 1997 1998 1999 2000
Cem
ent d
eliv
erie
s (M
illio
n to
ns)
0 200 400 600 800 1000 1200 1400
USA, 1995
Switzerland, 1995
Norway, 1995
New Zealand, 1995
Lebanon, 1999
Lebanon, 1995
Latvia, 1995
Jordan, 1995
Iceland, 1995
Germany, 1995
Egypt, 1999
Canada, 1995
Australia, 1995
Cou
ntry
Cement production (106 ktons/capita/year )
Case DescriptionStudy area - Lebanon
• Cement industrial complex, Chekka, Lebanon
• 60% of country cement production• Over years, production peaked in
1995; Lebanon had one of the highest per capita production worldwide
• Contributes 77.2% of country’s industrial emissions
• Chronic public complaints• Media coverage suggested a
correlation between emissions & adverse health impacts
Applied MethodApplied MethodHealth & air quality assessmentHealth & air quality assessment
• Health– Questionnaire related to health outcomes– 159 randomly selected households in 2 groups
• Group 1: 0 to 4 km from Chekka, 80 households• Group 2: 4 to 7 km from Chekka, 79 households• More focus on children than on adults
• Air quality– Continuous 5-min measurement of CO, NO2 & SO2 (4
locations, 4 to 7 days)– Gravimetric sampling of PM10 & less + analysis for
priority metals
Applied MethodApplied MethodHealth impact & economic valuationHealth impact & economic valuation
• Health impact assessment– Benefits due to reduction of PM10 & SO2 in the form of SO4
2-
were estimated based on studies developed for the US– Potential lives saved = % change in mortality or respiratory
systems avoided due to reduction x local occurrence rates x the exposed population number
• Economic valuation– Mortality: HC approach– Morbidity: COI approach, using US values adjusted for:
• Inflation (1990 → 1998): factor of 1.2547• Income: ratio of 0.12 (based on GNP comparison)• Health care: ratio of 0.24 (based on comparison of cost of COPD &
pneumonia in Lebanon & US)
ResultsResultsHealth & air quality Health & air quality
• Higher prevalence of health complaints among Group 1
• Exceedence of 24-hr AAQS at all locations
Outcomes Group1 (%)
Group2 (%)
Chronic bronchitis 15 11
Asthma 10 6
Other respiratory problems 15 6
Hospitalization during the past year
Respiratory 11 9
Non-respiratory 59 30
Cough with colds 74 43
Cough apart from colds 13 6
Chronic cough 10 6
Phlegm & congestion with colds 36 20
Phlegm & congestion apart from colds 8 3
Chronic phlegm & congestion 6 1
Episodes of increased phlegm & congestion for 1 week/year 23 5
Chest colds every year 19 4
Wheezing 53 32
Chest illness that kept child off his activities in the past 3 years 25 11
Asthma 4 1
Bronchitis 10 8
Chest illness before age 2 years 9 5
Hospitalization due to chest illness before age 2 3 3
Constituent Concentration range
AAQS
CO (ppm) < 2 9 (8-hour average)
NO2 (ppm) 6.4 - 10.1 0.053 (annual average)
TSP (μg/m3) 67 - 316 260 (24-hour average)b
75 (annual average)b
PM10 (μg/m3) 36.8 – 173.8 b 150 (24-hour average)
50 (annual average)b
SO2 (ppm) 0.45 - 0.7 0.14 (24-hour average)
0.03 (annual average)
ResultsResultsHealth benefits Health benefits –– PMPM1010 reductionreduction
• For 10 μg/m3
reduction in PM10– Mortality
• Size of exposed population was multiplied by death rate
• A 0.1 to 4.6% decrease in mortality was applied
• 0 to 34 lives saved– Morbidity
• DRFs from industrialized regions were multiplied by exposed population
Endpoint Change(Pearce &
Croward, 1996)
Total cases avoided
Respiratory hospital admissions (RHA)/100,000
6.6-17.3 1 – 16
Emergency department visits/100,000
116.0-354.0 33 – 319
Lower respiratory illness (LRI)/ asthmatic child
0.010-0.024 10 – 78
Asthma attacks/person
0.33-1.96 9,652 –176,577
Respiratory symptoms/person
0.8-2.56 23,400 –230,630
Chronic bronchitis (CB)/100,000 (incidence)
30.0-93.0 8 – 84
Restricted activity days (RAD)/person
0.29-0.58 8,482 –52,253
Morbidity Results
ResultsResultsHealth benefits Health benefits –– SO4
2- reduction reduction • For 10 μg/m3 reduction in
SO42-
– Mortality• Expressed by the equation
(Chestnut and HaglerBailly Consulting, 1995): LΔS = a x P x ΔSLΔS = annual # of lives saved P = exposed peopleΔS = change in concentrationa = constant (8-112)x10-6
• 2 to 101 lives saved– Morbidity
• Similar equation with different ‘a’ values
Endpoint a Number of cases avoided
CB (0.5 - 2.0)x10-4 14-181
RHA (1.3 - 1.8)x10-5 3-17
CHA (cardiac hospital admissions)
(1.0 - 1.7)x10-5 2-16
ASD (asthma symptom days)
(3.3 - 9.9)x10-1 4,536-41,919
RAD* (4.7 - 14.6)x10-2 8,523-81,550
LRS* (6.6 - 23.0)x10-2 11,969-128,469
Morbidity Results
* Cases of RAD and LRS are computed using adults 18 years of age and above as the exposed population, which constitutes around 62 percent of the total population (US Bureau of the Census, 2001)
Applied MethodApplied MethodMortality related benefitsMortality related benefits
• Multiplying average productivity years (20 to 35 years) by the average income (US$313/month)
• Economic benefit for a 10 μg/m3 reduction in PM10 & SO4
2- is equivalent to 0 to 0.027% & 0 to 0.08 % of the GDP, respectively
PM10 SO42-
Number of lives saved
Economic benefit (US$/year)
Number of lives saved
Economic benefit (US$/year)
Total economic benefit 0 – 34 0 – 4,469,640 2-101 150,240 – 13,277,460
Equivalent percent of GDP 0 – 0.027 0 – 0.08
Average per case* 131,460 131,640* Average total economic benefit divided by the average total number of lives saved
Applied MethodApplied MethodMorbidity related benefits (1)Morbidity related benefits (1)
• Multiplying predicted # of cases avoided due to reduction in pollutant concentrations by cost of corresponding health endpoints
• To avoid double counting in adding up costs, overlapping categories were subtracted assuming the following:– Incidence is proportional to age distribution: 62% of the
population is 18 years and older;– Each RHA averages 6.8 days & each CHA averages 6.9 days;– All days in the hospital and all asthma symptom days are also
RADs & therefore are subtracted from the latter;– RADs are also acute respiratory symptom days & therefore a
fraction of RADs is subtracted from LRSs;– 28% of acute respiratory symptoms are lower respiratory tract
Applied Method Applied Method Morbidity related benefits (2)Morbidity related benefits (2)
Endpoint US valuation (US$/case)a
Lebanesevaluation
(US$/case)
PM10 SO4
Cases avoided
Total cost (US$) Cases avoided
Total cost (US$)
RHA (Respiratory hospital admissions)
6,100 1,837b 1 – 16 1,837 – 29,392 3 – 17 5,511 – 31,229
CHA (Cardiac hospital admissions)
6,100 1,837b - - 2 – 16 3,674 – 29,392
CB (Chronic bronchitis) 260,000 32,622c 8 – 84 260,976 – 2,740,248 14 – 181 456,708 – 5,904,582
ASD (Asthma symptom days)
32 4c 9,652 –176,577
38,608 – 706,308 4,536 –41,919
18,144 – 167,676
Net RAD (Restricted activity days)
38 4.8c 2,493 –11,685
11,966 – 56,088 5,689 –55,420
27,307 – 266,016
Net LRS (Lower respiratory symptoms)
12 1.5c 4,712 –18,296
7,068 – 27,444 9,582 –105,635
14,373 – 158,453
Total 320,455 – 3,559,480 525,717 – 6,557,348
Per capita benefit (US$/capita)
3.5 – 122 5.8 – 224
Percent of per capita incomed
0.09 – 3.16 0.15 – 5
a 1990 Dollars (USEPA, 1997)b Lebanese valuation is obtained by multiplying the US valuation by the health care ratio (0.24), after adjustment for inflation.c Lebanese valuation is obtained by multiplying the US valuation by the per capita GNP ratio (0.1), after adjustment for inflation.d GDP = 16.6 billion US$; per capita capita = US$ 3860 (World Bank, 2001).
EEnd of nd of SSessions essions 14 14 && 1515
Thank YouThank You
A health-based socio-economicassessment of drinking waterquality: the case of LebanonM. El-Fadel, R. Maroun, L. Semerjian and H. HarajliDepartment of Civil and Environmental Engineering, American
University of Beirut, Beirut, Lebanon
Keywords Water, Health, Economics, Lebanon
Abstract Water-related diseases are a human tragedy, resulting in millions of deaths each year,preventing millions more from leading healthy lives, and undermining development efforts byburdening the society with substantial socio-economic costs. This problem is of great significance indeveloping countries, where polluted water, water shortages, and unsanitary living conditionsprevail. This paper presents a case study on a health-based socio-economic assessment of drinkingwater quality in Lebanon, based on relevant valuation approaches and available country-specificdata. The assessment revealed that the potential health and economic benefits due to water andsanitation improvements can be significant (0.15-3.35 percent of GDP).
IntroductionHistorically, the provision of urban environmental services in general, andpiped water in particular, has been the responsibility of the public sector.However, due to the rapid increase in urban populations, governments are oftenfacing major difficulties in meeting the citizens’ basic needs (Bennet, 1998).This issue is of major concern in developing countries, where existingconditions of the water supply infrastructure is poor, services are inferior, andfinancial resources for the construction and maintenance of infrastructure areinadequate (Gidman et al., 1995). In this context, theWorld Health Organization(WHO) estimates that 20-30 percent of urban residents in Latin America,Africa, and Asia lack access to potable water. Experience during the lastdecade confirms that the solution to these problems is not merely to expandcapacity, but rather to better manage service delivery to meet user’s demand,via the establishment of public-private partnerships (PPP) (Gidman et al., 1995).Four groups can be identified to play a role in PPPs:
(1) the government at the national, regional, or local level;
(2) the formal private sector;
(3) non-governmental organizations/community-based organizations; and
(4) the informal private sector.
The Emerald Research Register for this journal is available at The current issue and full text archive of this journal is available at
http://www.emeraldinsight.com/researchregister http://www.emeraldinsight.com/1477-7835.htm
Special thanks are extended to the United States Agency for International Development for itssupport to the Environmental Engineering and Science Programs at the American University ofBeirut.
Drinking waterquality
353
Management of EnvironmentalQuality: An International Journal
Vol. 14 No. 3, 2003pp. 353-368
q MCB UP Limited1477-7835
DOI 10.1108/14777830310479441
In recent years, the role of the informal private sector has been gaining muchattention, because it is seen to be most accountable to the low-incomepopulation. More specifically, the informal private sector is widely involved inthe provision of water through what is commonly known as “water vending”,which is defined as the act of providing water through tanker trucks or mobilewater vendors, stand-pipes, and water shops, with the exclusion of the “bottledwater” industry (World Health Organization and United Nations ChildrenFund, 2000). In most developing countries where public water and sanitationnetworks are not trusted or are altogether absent, consumers resort toalternative sources of freshwater, such as small-scale water vendors. As such,water vending is an old tradition worldwide, and in some African cities, forinstance, it has become the major mode of access to drinking water (see Table I).
The proportion of the population served through vendors and tanker trucksvaries significantly between different urban and rural areas, with urbanpopulations being the largest consumers (see Table II). In Lebanon, watersupply through vendors is becoming substantial, particularly in the southern
CityPublic connection
(%)Private standpipes
(%)Other private providers
(%)
Kampala-Uganda 36 5 59Dar Es Salam-Tanzania 31 0 69Conakry-Guinea 29 3 68Nouakchott-Mauritania 19 30 51Cotonou-Benin 27 0 73Ouagadougou-Burkina Faso 23 49 28Bamako-Mali 17 19 64
Source: Collignon and Vezina (2000)
Table I.Mode of access todrinking water inselected Africancities in 1999
Country Year Source of water Urban population (%) Rural population (%)
Angola 1996 Tanker truck 25.2 0.8Cambodia 1998 Vendor 16 3.5Chad 1997 Vendor 31.5 0.5Ecuador 1990 Tanker truck 16 7Eritrea 1995 Tanker truck 30.5 1.4Jordan 1997 Tanker truck 1 10.6Libya 1995 Tanker truck 6.8 13.9Mauritania 1996 Vendor 53 0.9Mongolia 1996 Vendor 16 1Niger 1998 Vendor 2.4 1.9Syria 1997 Tanker truck 4.1 11.3
Source: World Health Organization and UNICEF United Nations Children Fund (2000)
Table II.Percentage ofselected populationconsuming vendedwater
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suburbs of Beirut, as a response to the inadequate public water supply system.Yet, it is difficult to estimate the exact numbers and locations of thesesmall-scale entrepreneurs due to the absence of official registries, and to theillegal status of the majority (Al-Safir Newspaper, 2002).
Recently, water vending is being acknowledged more by researchers andpolicy makers, and linked with an increased interest in cost recovery andprivatization. However, the main concern regarding this service is thequality of the supplied water and its associated health risks. In fact, scarceand unclean water supplies represent critical public health problems inmuch of the world. Polluted water, water shortages, and unsanitary livingconditions are associated with various short- and long-term health risks.Water-related diseases are indeed a human tragedy, whereby about 2.3billion cases are estimated with over 12 million deaths per year.Furthermore, some 60 percent of all infant mortality is linked to infectiousand parasitic diseases, most of them are water-related (Hinrichsen et al.,1997). In most countries, the main risks to human health associated withthe consumption of polluted water are microbiological in nature. However,the importance of chemical contamination should not be underestimated(World Health Organization, 1997). Table III summarizes majorwater-related diseases prevalent worldwide.
The present study assesses the problems associated with unclean andinadequate water supply in Lebanon. The quality of vended water at a typicalarea (Beirut southern suburbs) where the informal sector plays a pivotal role inproviding drinking water to the local population is presented. Water-relatedhealth impacts in terms of increased mortality and morbidity rates areassessed, and corresponding socio-economic burdens are estimated.
The Lebanese contextHistorically, Lebanon has always been distinguished in the region to be blessedwith relatively adequate water resources; however, available resources areunevenly distributed geographically and seasonally (El-Fadel et al., 2000),leading to problems of water shortage that are prominent in over-populatedcities, such as the capital Beirut and its suburbs (Yamout, 2002). Beyond theimpact of population growth, water demand has been rising in response toindustrial development, increased reliance on irrigated agriculture, massiveurbanization, and rising living standards. On the other hand, high“unaccounted-for water” (UFW) volumes, estimated at an average of 40percent, further aggravate the problem of water shortage as well as waterquality (Environmental Resource Management, 1995). Recent attempts atestimating water demands, availability, and deficit for Beirut reveal asignificant water deficit in the city (see Table IV).
Evidently, the water supply situation in Beirut cannot meet the demand. Thecombination of weak water utilities and water scarcity at the source leads tointermittent supply in most areas (10 hours of supply every other day), and to a
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355
Disease
Geographicextent
Number
ofcasesa
Deathsper
year
Water-bornediseases
Diarrhealdisease
Worldwide
500million/year
3-4million
Cholera
South
America,Asia,Africa
384,000/year
20,000
HepatitisA
Worldwide
600,000–3million/year
2,400-12,000
Paratyphoidandtyphoid
80percentin
Asia,20
percentin
Latin
America,
Africa
16million
currently
600,000
Polio
66percentin
India,34percentin
NearEast,Asia,
Africa
82,000
currently
9,000
Water-baseddiseases
Ascariasis
Africa,Asia,Latin
America
250million
currently
60,000
Clonorchiasis
Southeast
Asia
28million
currently
Nonereported
Dracunculiasis(guinea
worm)
78percentSudan,22percentinotherSub-Saharan
Africa,andfew
casesin
India
andYem
en153,000/year
Nonereported
Paragonim
iasis
Far
East,Latin
America
5million
currently
Nonereported
Schistosomiasis(bilharzias)
Africa,NearEast,rain
forest
beltin
Central
Africa,Western
Pacific,Cam
bodia,Laos
200million
currently
20,000
Water-relatedvector
diseases
Dengue
Tropical
environments,concentrated
inAsia,
Central
andSouth
America
50-100
million/year
24,000
Filariasis
Africa,Eastern
Mediterranean,Asia,South
America
120million
currently
Nonereported
Malaria
Africa,Southeast
Asia,India,South
America
300-500million/year(clinical)
2million
Onchocerciasis
Sub-Saharan
Africa,Latin
America
18million
currently
Nonereportedb
RiftValleyFever
(RVF)
Sub-Saharan
Africa
NAc
1percentof
cases
Notes:a
Number
ofcasesisreportedas
incidence
(“per
year”)–thenumber
ofnew
casesoccurringin
ayear–or
asprevalence
(“currently”)–
thenumber
ofcasesexistingat
apointin
time
bNodeathsbutcauses270,000reportedcasesof
blindnessannually
cNA¼not
available
Source:Muller
andMorera(1994);World
HealthOrganization(1996,1998)
Table III.Major water-relateddiseases
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lack of piped water supply for a large number in poor urban areas (Saghir et al.,2000). It is estimated that about 22 percent of the total population are not evenconnected to the public water supply system, with the highest proportion ofunconnected households being located in the southern suburbs (Council forDevelopment and Reconstruction, 1998; Central Administration of Statistics,1997). In response to the shortage/absence of public piped-water supply,consumers in some quarters of Beirut, especially in the southern suburbs, relyon their own resources to meet their water requirements. Many resort topumping water from private wells, or purchasing water from small-scaleprivate water providers, more commonly known as water vendors. While it isdifficult to estimate the exact numbers and locations of these small-scaleentrepreneurs in the absence of official registries, the majority operates withoutany regulatory authorization (Al-Safir Newspaper, 2002).
Water quality indicatorsRecent statistics reported by the Central Laboratory, affiliated with theMinistry of Health, revealed the microbiological contamination of 24 percent of403 samples collected from water vending companies and 40 percent of 863samples collected from the potable water network in various regions acrossLebanon[1]. Moreover, of 450 samples collected from groundwater and springs,37 percent were microbiologically contaminated (see Table V).
As part of the present study, water quality from 65 water-vending shopslocated in the Beirut southern suburbs was examined. The analysis revealedthe poor quality of some samples, particularly with respect to microbiologicalindicators (see Figure 1).
The statistical significance of the sample size is limited, as the number ofsamples and the frequency of sampling need to be increased and spread over awider geographical area to draw more accurate conclusions and ascertain
1995 2000 2005 2015
Beirut City population 600,000 608,000 612,000 628,000Northern suburbs population 546,000 591,000 637,000 695,000Southern suburbs population 698,000 820,000 939,000 1,258,000Total population 1,844,000 2,019,000 2,188,000 2,581,000Domestic water demand (Ml/d) 371 418 466 580Non-domestic water demand (Ml/d) 121 134 149 174Water losses (Ml/d) 266 241 212 208Total consumption & loss (Ml/d) 758 793 827 962Minimum water available (Ml/d)a 315 575b 575b 575b
Maximum water available (Ml/d)a 415 675b 675b 675b
Maximum water deficit (Ml/d) 443 218 252 387
Notes: a Water resources vary throughout the yearb Includes the planned construction of a water supply reservoir south of the citySource: Council for Development and Reconstruction (1998)
Table IV.Predicted maximum
population, waterdemand,
availability, anddeficit for Beirut
City
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357
trends within some statistical confidence. Nevertheless, these data arealarming, owing to the fact that polluted water is associated with various shortand long-term health risks, which translate into a socio-economic burden.
Health impactsSimilar to worldwide trends, Lebanon suffers from adverse health impacts as aresult of water pollution. Data pertaining to water-related mortality andmorbidity in the country are limited due to the absence of a proper diseasereporting mechanism. Available data are restricted to prevalent knownwater-related diseases, including diarrhea, typhoid and paratyphoid, andhepatitis A. In terms of mortality, a study conducted by the United NationsDevelopment Program (UNDP) in 1990 stated that each child under five isexposed, on average, to 3.5 incidents of diarrhea each year, causing the death of750 children per year (United Nations Development Program, 1995). While morerecent data are unavailable today, this value may be an over-estimation,especially now that substantial efforts for the improvement of water supply andsanitation have been ongoing. As for morbidity, the average annual number ofreported incidents of dysentery, hepatitis A, and typhoid and paratyphoid forthe years 1995 to 2000, as compiled by the Directorate of Preventive Medicine ofthe Ministry of Health (MoH), were 529, 287, and 809, respectively (see Figure 2).
Economic valuation of water-related health impactsThe health costs of water pollution and the benefits of improvements in waterand sanitation in Lebanon are assessed based on international experience and
Water sourceBottled water Network water Groundwater Total
Samples exhibitingmicrobiological pollution 97 (24 percent) 345 (24 percent) 450 (37 percent) 892 (36 percent)Total number of samplesanalyzed 403 863 1,215 2,481
Source: Al-Safir Newspaper (2002)
Table V.Results of wateranalysis by thecentral laboratory
Figure 1.Percentage/number ofsamples exceedingUSEPA drinking waterguidelines
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available country-specific data. Refined estimates can be obtained withelaborate and updated local data such as statistics about mortality andmorbidity and their corresponding unit costs.
Health-related costs of water pollutionGenerally, the economic valuation of health impacts proceeds by conductingepidemiological studies in order to establish dose-response relationships(DRRs) linking environmental variables with observable health effects.However, in the case of water pollution, establishing dose-response functions(DRFs) is complicated and less advanced than is the case of evaluating healthimpacts from air pollution, for instance. This is due to the fact that “it is notambient water quality per se that affects health but access to clean drinkingwater and adequate sanitation along with the household’s level of income andeducation” (The World Bank Group, 1998).
Valuing the health costs of water pollution depends on country-specificfactors such as the cost of labor, labor productivity, capital and medical care,life expectancy, people’s value of health and life, and their willingness to acceptrisk. Hence, concrete valuation is limited by the availability of such data as wellas the level of uncertainty in the adopted approximations.
Valuation techniques. Several methods are available for valuing mortalityand morbidity costs associated with water pollution. These methods cangenerally be grouped in two categories:
(1) methods that measure only the loss of direct income such as lost wages;and
(2) approaches that attempt to capture the willingness to pay (WTP) ofindividuals for avoiding or reducing the risk of death or illness.
The first category does not include inconvenience, suffering, losses in leisureand other less tangible impacts to individual and family well being. They mayalso underestimate the health cost of people who are not members of the laborforce. Therefore, these methods indicate only the lower bound of social costs.
Figure 2.Average number of
reported cases per yearfor the period 1995-2000
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Mortality valuation. Typical methods used for valuing mortality outcomesinclude the human capital approach and the willingness to pay (WTP)approach:
(1) The human capital approach. The human capital approach, also knownas the forgone-earnings approach, measures the loss of productivity (netpresent value of productivity) resulting from an individual’s death orinjury (Lesser et al., 1997). This approach considers individuals as unitsof human capital that produce goods and services for society. As such,the value of a premature death is obtained by multiplying the number oflife years lost by the average wage rate in the country in question. In thecase of Lebanon, the total socio-economic cost due to prematuremortality was estimated based on two main assumptions including:. The average Lebanese monthly salary is US$400[2].. Productivity age ranges between 20 and 65 years.
As such, considering that the mortality rate is 750 cases per year (UnitedNations Development Program, 1995), all pertaining to children less thanfive years of age, the total economic cost of premature death caused bywater pollution is estimated at US$162 million[3].
(2) The WTP approach. Unlike the human capital approach that measurestangible changes in productivity, the WTP approach captures intangibleaspects. It involves asking people directly through surveys – contingentvaluation studies – or assessing from market behavior, their WTP forreduced risks of increased mortality (or their willingness to accept theincreased risk of increased mortality). The total value of the benefit orcost in question is then estimated by averaging theWTP of all concernedmembers of society. In case original data on the WTP are lacking, onecan use income adjusted mortality values from other countries aftercompensating for income difference. In this study, individual WTPvalues estimated in the USA have been adopted (see Table VI), wherebyUS mortality values estimated for the year 1990 have been adjusted forthe Lebanese context based on income ratio as depicted in Figure 3 witha ratio of about 0.1 (World Bank, 1999).
Hence, on adjusting the range of WTP estimates (US$0.6-13.5 million) to theLebanese context, the value of a statistical life in Lebanon would range betweenUS$0.06-1.35 million. The corresponding total cost of mortality would rangefrom US$45 to 1,012.5 million, constituting 0.2 to 6.1 percent of the GDP inLebanon for the year 2000. This range encompasses the value calculated usingthe human capital approach (US$162 million).
Morbidity valuation. To assess the morbidity outcomes, the methodstypically used include the cost of illness (COI) approach, and the WTPapproach. The choice of the method to be used depends on the availability of
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data. In this study, the cost of water-related diseases was estimated using theCOI approach, whereby the direct cost of morbidity is measured in terms ofmedical expenditure for treating an illness (physician care, drugs, andhospitalization costs), and in terms of lost wages during days missed fromwork, and other days when activities are significantly restricted due to illness.The diseases were restricted to dysentery, hepatitis A fever, typhoid andparatyphoid, being the only water-related illnesses reported to the Ministry ofHealth. The actual medical expenditure on hospitalization requirements forthese diseases and the associated number of days of restricted activity wasobtained through surveys of medical personnel. Transportation costs wereapproximated based on average round trip to hospital and associated cost offuel, while productivity loss was estimated by assuming equal age distributionbetween the reported cases and the Lebanese population (see Figure 4).
The total cost per case was found to vary with type and severity of diseaseas well as the class of hospital admission, as depicted in Table VII.
StudyaValuation/case(MUS$/year)b Studya
Valuation/case(MUS$/year)
R.S. Smith (1974) 7.2 Herzog and Schlottman (1987) 9.1R.S. Smith (1976) 4.6 Leigh (1987) 10.4V.K. Smith (1976) 4.7 Gerking et al. (1988) 3.6Viscusi (1978) 4.1 Moore and Viscussi (1988) 2.5Olson (1981) 5.2 Moore and Viscussi (1988) 7.3Viscusi (1981) 6.5 Gaten (1988) 13.5Marin et al. (1982) 2.8 Cousineau et al. (1988) 3.6Butler (1983) 1.1 Jones-Leec (1989) 3.8Leigh and Folson (1984) 9.7 Kneisner and Leeth (1991) 0.6-7.6Smith and Gilbert (1984) 0.7 Miller and Guriac (1991) 1.2Dillingham (1985) 0.9-3.9 Viscussi et al. (1991) 2.7Gegax et al.c (1985) 3.3
Notes: a Labor market estimateb 1990 dollar valuec Contingent valuation estimateSource: El-Fadel and Massoud (2000)
Table VI.Summary of
mortality valuationestimates in the
USA
Figure 3.Transfer of mortalityand morbidity values
across countries
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361
Accordingly, the total COI incurred by society from the reported water-relatedcases is estimated to range between US$613,295 and US$2,664,502 (seeTable VIII). This provides a conservative estimate of the real costs as itexcludes the value of pain, suffering, diet, and behavior modification inaddition to the side effects of medications.
Benefits of improved water supply and sanitation. Providing clean water andensuring proper sanitation facilities have been shown to reduce the prevalenceof water-related diseases. Several studies examined the health benefitsassociated with water and sanitation interventions. Despite the mix of both
Number ofreported cases
Cost of illness per case(US$/case)
Total cost of illness(US$)
Dysentery 529 254-1,054 134,366-557,566Hepatitis A 287 389-1,822 111,643-522,914Typhoid 809 454-1,958 367,286-1,584,022Total 613,295-2,664,502% GDP 0.003-0.02
Table VIII.Total COI incurreddue to water-relatedillnesses
COI per admission class (US$/case)Social security Third class Second class First class
Dysentery 254-423 387-599 487-777 658-1,054Hepatitis A 389-836 544-1,076 683-1,371 902-1,822Typhoid 454-972 609-1,212 748-1,507 967-1,958
Table VII.Variation of thetotal COI per casewith type of diseaseand class ofadmission
Figure 4.Age distribution of theLebanese population
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positive and negative results towards the improvements in one or morecomponents of water supply and sanitation, the overwhelming evidence is infavor of positive impacts, with the exception of hookworm infection. Expectedreductions in morbidity rates from improved water and sanitation for selectedwater-related diseases are summarized in Table IX. The mechanisms throughwhich improved water and sanitation can promote health vary from onedisease to another as depicted in Table X.
Economic valuation of health benefits associated with the provision of cleanwater supply and ensuring proper sanitation facilities can be estimated usingsimilar health costs derived in the previous section. This is calculated by firstmultiplying the reported number of cases by the expected percent reduction inprevalence for each disease (see Table IX) to obtain the number of casesavoided. Then, the economic benefit is estimated by multiplying the number ofcases avoided by the COI per case. Table XI outlines the application ofeconomic valuation of water-related health benefits in the context of Lebanon.
Intervention
DiseaseImproved
drinking waterWater for
domestic hygieneWater for
personal hygiene Sanitation
Ascariasis + ++ 2 ++Diarrhea + ++ ++ ++Dracunculiasis ++ 2 2 2Hookworm infection 2 2 2 ++Schistisomiasis 2 ++ ++ ++Trachoma 2 + ++ 2
Notes: + ¼ strong impact; ++ ¼ stronger impact; 2 ¼ little or no impactSource: Esrey et al. (1991)
Table X.Potential relationsbetween water and
sanitationinterventions andmorbidity from
selected diseases
Disease Percent reduction in morbidity
Diarrheal diseases 26-50Typhoid 80Paratyphoid 40Infective hepatitis 10Ascariasis 29-40Cholera 90Dracunculiasis 78Onchoserciasis 20?Hookworm infection 4Schistosomiasis 60-77Trachoma 27-60Guinea worm 100
Source: Esrey et al.(1991); Dougherty and Hall (1995)
Table IX.Expected reductions
in morbidity forselected diseasesfrom water and
sanitationimprovements
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363
Hence, based on the reported percent reduction in cases, high economic benefitsare expected to result from improving the quality of the water supply andsanitation, ranging between US$25 and US$558 million per year, constituting0.15 to 3.35 percent of the GDP in Lebanon for the year 2000. In other words,around 55 percent of the incurred costs calculated above (US$45-1,0125 million)can be avoided. However, the true relation between the degree of improvementin water supply and sanitation and the expected reduction in diseaseprevalence and mortality still needs to be ascertained.
Limitations of the studyLimitations in this study can be classified into three categories:
(1) limitations in the available data;
(2) limitations in the health impact assessment; and
(3) limitations in the economic assessment.
Limitations in the available data, particularly data pertaining to morbidity andmortality rates, are mainly attributed to the absence of population-based vitaland disease registries. Limitations in the health impact assessment are mainlydue to the absence of DRFs for water-related health effects and the assumptionthat all reported diarrhea, typhoid, paratyphoid and hepatitis-A fever cases arewater-related. In contrast, underestimation in the number of cases is expected,since many remain unreported. The limitations in the economic assessmentresult from uncertainties in mortality valuations, the adjustment ofinternational values by the income ratio between countries, and theassumptions adopted in the absence of better estimates of specific datarelated to productivity loss, transportation costs, etc.
Summary and conclusionsScarce and unclean water supplies represent critical public health problems inmuch of the world, particularly in developing countries. In Lebanon, watershortages, weak public utilities, and poor management of available waterresources have forced the public to rely on water sources and supply practiceswhich are often polluted, posing significant health risks, welfare and financiallosses. In some quarters of Beirut, especially in its southern suburbs,consumers rely on small-scale private water providers, more commonlyreferred to as water vendors. An investigation of the quality of vended water inthis area revealed serious microbiological contamination.
Various valuation methods were used in the economic assessment of thehealth impacts of water pollution. The human capital and WTP approacheswere applied to estimate mortality costs, and the COI approach was used toestimate morbidity costs. The WTP values were adjusted by the income ratiobetween the USA and Lebanon. Estimated health costs ranged between US$45and US$1,025 million per year (0.2-6.1 percent of the GDP in the country for theyear 2000), dominated by mortality costs. Economic benefits of improvement in
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Param
eter
Diarrhoeal
diseases
Typhoid/paratyphoid
Infectivehepatitis
Mortality
Total
Number
ofcasesa
529
809
287
750
2375
Percentreductionb(%
)26-50
60c
1055
d
Number
ofcasesavoided
e138-264
485
29412
Costper
case
(US$)f
254-1,054
454-1,958
389-1,822
(0.06-1.35)£
106
Econom
icbenefit(US$million/year)
0.035-0.278
0.220-0.949
0.011-0.053
25-557
25-558
Percentof
GDP
(0.2-1.7)£
1023
(1.3-5.7)£
1023
(0.06-0.3)
£10
23
0.15-3.34
0.15-3.35
Notes:aRefer
toFigure
2bRefer
toTableIX
c Averagepercentreduction
dReductionin
childmortality
from
water-related
diseasesas
reportedin
Esrey
etal.(1991)
e Number
ofcases£
percentreduction
f Refer
toTableVIII
Table XI.Estimated economicbenefit derived fromwater and sanitation
improvements
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365
water and sanitation were approximated based on reduction in prevalence andmortality as reported in epidemiological studies. They are expected to reducethe incurred costs by 55 percent.
Based on these estimates, actions to improve the water and wastewaterinfrastructure are imperative. Economic health benefits should be incorporatedwithin the cost analysis of water and sanitation infrastructure projects. Thismust be coupled with proper quality/quantity water resources managementand planning policies to overcome the water problems and constraintscommonly encountered by governments. Strategies should emphasize properresource allocation and water quality (for example instituting water qualitymonitoring systems, protecting watersheds, regulating wastewater discharge,imposing sanctions for abuse and pollution) in addition to resourcedevelopment and increasing water quantity. While these strategies aremedium to long-term, immediate efforts should be directed towards managingthe water vending sector as an intermediary solution to water deprivation inlow-income areas.
Notes
1. Note that these samples were collected from houses and not from the network itself,indicating that the source of pollution could have occurred at any spot between the point ofdelivery from the network to the point of collection.
2. Based on the per capita GDP in Lebanon for the year 2000 (Banque Audi, 2000).
3. At the 2002 dollar value < 1,500 LP.
References
Al-Safir Newspaper (2002), “Official examinations confirm water pollution”, in Al-SafirNewspaper, 14 February (in Arabic).
Banque Audi (2000), Lebanon Facts and Figures 1998-2000, Banque Audi.
Bennet, E.B. (1998), Public-private Cooperation in the Delivery of Urban Infrastructure Services(Water and Waste), Yale-United Nations Development Program-Public PrivatePartnerships (UNDP-PPP).
Central Administration of Statistics (1997), Mount Lebanon in 1996: Census of Buildings andHouseholds, Central Administration of Statistics, Beirut, Lebanon.
Collignon, B. and Vezina, M. (2000), “Independent water and sanitation providers in Africancities: full report of a ten-country study”, Water and Sanitation Program, UNDP-WorldBank, Washington, DC.
Council for Development and Reconstruction (1998), Awali-Beirut Water Conveyor Project: PhaseI Interim EA Report, Project No. 1026, Council for Development and Reconstruction,Beirut, Lebanon.
Dougherty, T.C. and Hall, A.W. (1995), “Environmental impact assessment of irrigation anddrainage projects”, Irrigation and Drainage Paper 53, FAO, UK, available at:wwwfaoorg/docrep/V8350E/v8350e00htm
El-Fadel, M. and Massoud, M. (2000), “Particulate matter in urban areas: health based economicassessment”, The Science of Total Environment, Vol. 257 No. 2-3, pp. 133-46.
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El-Fadel, M., Zeinati, M. and Jamali, D. (2000), “Water resources in Lebanon: characterization,water balance, and constraints”, Journal of Water Resources Development, Vol. 16 No. 4,pp. 619-42.
Environmental Resource Management (1995), Lebanon: Assessment of the State of theEnvironment, Mediterranean Environmental Technical Assistance Program (METAP)and Ministry of Environment (MoE), Beirut, Lebanon.
Esrey, S.A., Potash, J.B., Roberst, L. and Shiff, C. (1991), “Effects of improved water supply andsanitation on ascariasis, diarrhea, dracunculiasis, hookworm infection, schistosomiasisand trachoma”, Bulletin of the World Health Organization, Vol. 69 No. 5, pp. 609-21.
Gidman, P., Blore, I., Lorentzen, J. and Schuttenbelt, P. (1995), Public-private Partnerships inUrban Infrastructure Services, UMP Working Paper Series 4, UNDP/Habitat/World Bank,Nairobi.
Hinrichsen, D., Robey, B. and Upadhyay, U.D. (1997), Solutions for a Water-Short World,Population Reports, Series M, No. 14, Population Information Program, Johns HopkinsSchool of Public Health, Baltimore, MD.
Lesser, J.A., Dodds, D.E. and Zerbe, R.O. Jr (1997), Environmental Economics and Policy,Addison-Wesley, Reading, MA.
Ministry of Health (2000), Compilation of Lebanese Epidemiological Newsletter, EpiNews1995-2000.
Muller, R. and Morera, P. (1994), “Helminthoses”, in Lankinen, K.S., Berstrom, S., Makela, P.H.and Peltomaa, M. (Eds), Health and Disease in Developing Countries, Macmillan Press,London.
Saghir, J., Schiffler, M. and Woldu, M. (2000),Urban Water and Sanitation in the Middle East andNorth Africa Region: The Way Forward, World Bank, Middle East and North Africa.
United Nations Development Program (1995), Online, available: www.undp.org.lb/programme/governance/advocacy/hdr97/chp31.pdf
World Bank (1999), Lebanon at a glance, available at: www.worldbank.org/data/countrydata/aag/lbn_a ag.pdf
The World Bank Group (1998), Pollution Prevention and Abatement Handbook 1998: TowardCleaner Production, The World Bank Group, Washington, DC.
World Health Organization (1996), The World Health Report 1996: Fighting Disease, FosteringDevelopment, World Health Organization, Geneva.
World Health Organization (1997), Guidelines for Drinking-water Quality: Surveillance andControl of Community Supplies, Vol. 3, 2nd ed., World Health Organization, Geneva,available at: www.who.int/ water_sanitation_health/GDWQ/PDF_docs/ gdw3.pdf
World Health Organization (1998), Division of Control of Tropical Disease homepage, availableat: wwwwhoch/ctd/
World Health Organization and UNICEF (United Nations Children Fund) (2000), Global WaterSupply and Sanitation Assessment 2000 Report, World Health Organization, Geneva,available at: wwwwhoint/water_sanitation_health/ Globassessment/GlobalTOChtm
Yamout, G. (2002), “An optimization model for water supply multi-sectoral allocation in theGreater Beirut area”, MS thesis, Department of Civil and Environmental Engineering,American University of Beirut, Lebanon.
Drinking waterquality
367
Further reading
Cairncross, S. and Kinnear, J. (1991), “Water vending in urban Sudan”, Water ResourcesDevelopment, Vol. 7 No. 4, pp. 267-73.
Kjellen, M. (2000), “Complementary water systems in Dar es Salaam, Tanzania: the case of watervending”, Water Resources Development, Vol. 16 No. 1, pp. 143-54.
Seckler, D., Barker, R. and Amarasinghe, U. (1999), “Water scarcity in the twenty-first century”,Water Resources Development, Vol. 15 No. 1/2, pp. 29-42.
United States Environmental Protection Agency (2001), National Primary Drinking WaterStandards, EPA 816-F-01-007, Office of Water, available at: wwwepagov/safewater
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Leaded gasolinephase-out:
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Environmental Management andHealth, Vol. 12 No. 4, 2001,
pp. 389-406. # MCB UniversityPress, 0956-6163
Socio-economic benefits ofleaded gasoline phase-out
The case of LebanonZ. Hashisho and M. El-Fadel
Department of Civil & Environmental Engineering,American University of Beirut, Lebanon
Keywords Leaded gasoline, Lead health effects, Health economics, Blood lead levels, Lebanon
Abstract Lead emissions from vehicles using leaded gasoline is a serious environmentalproblem in urban areas. While leaded gasoline has been completely phased out in many developedcountries, it is still the predominant fuel grade in most developing countries. This paper presentsan estimation of the health and economic benefits and costs of the transition from leaded tounleaded gasoline in Lebanon based on relevant dose-response functions and available country-specific data. Comparing the potential costs of the phase-out and the predicted benefits, it wasconcluded that such action is economically highly justified.
1. IntroductionLead is a toxic heavy metal. Even at low exposure level, it is associated withserious health hazards such as cardiovascular problems in adults andneurological disorders in children. Lead emissions from leaded gasolinecombustion is a significant source of atmospheric lead, accounting for morethan 90 percent where no lead phase-out measures have been implemented(Lovei, 1998). The reduction in blood lead levels (BLL) will reportedly reducehealth hazards associated with lead exposure, which is directly translated intoa lower health expenditure. In the USA, annual health benefits from reducingthe population's BLL by 1�g/dl were estimated at 6.9 and 9.9 billion USD forchildren and adults respectively (Schwartz, 1994). Similarly, in Russia, theannual environmental benefit from the complete phase-out of leaded petrol isestimated at about 1.44 billion USD (SCEP, 1997). As a result, many countrieshave implemented (Antigua and Barbuda, Argentina, Austria, Bahamas,Bolivia, Brazil, Canada, Columbia, Costa Rica, Denmark, Dominican Republic,El Salvador, Finland, Germany, Guatemala, Haiti, Honduras, Hungary, Japan,Mexico, Nicaragua, Norway, Saba, Slovak Republic, St Eustasius, Thailand, theUSA) or are implementing ± EU countries, Egypt ± a lead phase-out program(Lovei, 1999). Even some countries, such as China and India, have switched tounleaded gasoline in major urban cities as a direct solution for the problem oflead pollution.
The research register for this journal is available athttp://www.mcbup.com/research_registers
The current issue and full text archive of this journal is available athttp://www.emerald-library.com/ft
The authors would like to thank Dr I. Nuwayhid, Faculty of Health Sciences, AmericanUniversity of Beirut, for providing data on blood lead levels in Lebanon. Special thanks areextended to the United States Agency for International Development for its support to theEnvironmental Engineering and Science Programs at the American University of Beirut.
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Lead particles emitted to the atmosphere from the combustion of leadedgasoline are dispersed into various environmental media from where they canenter the human body, mainly through inhalation and ingestion[1]. While theformer is the major exposure route for adults, ingestion of lead-contaminatedwater, food, dust, and soil, can be more significant in children. In the humanbody, lead is accumulated mainly in the mineralizing tissue for long periods,thus allowing for latent exposure, even after the cessation of the externalexposure, as a result of decalcification processes (WHO, 1995).
1.1 Physiologic effectsAlthough health effects of exposure to high doses of lead have been well knownfor at least some 5,000 years[2], it was not until the 1970s that it was establishedthat exposure to low levels of lead can have significant implications on humanhealth. In fact, advancements in edpidemiology, toxicology, and laboratorytechnologies allowed for better detection, identification, and characterization ofthe effects of lead exposure in systems not known to be vulnerable, and atlevels lower than previously acknowledged.
In this context, the health impacts of lead exposure are diversified andhighly dependent on several factors, including age, individual susceptibility,health conditions, and exposure level. Although the exposure dose to lead fromvehicle emissions might be low, it is aggravated by the chronic and cumulativenature of exposure. Irrespective of the route, the physiologic effects of leadexposure are the same and include biochemical effects (such as anemia, andinterference with enzyme synthesis), and neurobehavioral effects (such as IQdeficiency, mental retardation, hyperactivity) in children. In adults, lead isstrongly correlated with increased probability of hypertension andcardiovascular diseases. Despite the long known adverse effects of exposure tolead, many countries are still adding lead to gasoline because it is the cheapestway to boost the octane content in gasoline and lubricate vehicle engines.
1.2 Standards and regulationsStandards for blood lead levels have been continuously reviewed and reducedas emergent studies showed the inadequacy of previous standards (ATSDR,1995; IOMC, 1998; WHO, 1995) (see Table I). While a firm consensus on themaximum permissible concentration of lead in blood has not been reached, the
Table I.Summary of standardsand regulations forlead in air and blood(IOMC, 1998)
Air (�g/m3) Blood (�g/dl)
WHO 0.5-1.0 20US 1.5a 10b
EU 2.0c NAd
Australia 1.5 10Canada 5.0 10
Notes: a Annual average; b Action level for children; c Quarterly average; d NA = notavailable
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amount of lead considered to cause lead poisoning continues to be reduced asnew toxicological and epidemiological evidences are becoming available. In1980, the World Health Organization (WHO) recommended a health-basedblood lead level (BLL) of 40�g/dl for workers and a limit of 30�g/dl for womenof childbearing age (WHO, 1980). Subsequent WHO standards have been basedon keeping levels in the vast majority of the population below 20 �g/dl (WHO,1995). The US Centers for Disease Control (CDC) have repeatedly revised itsstandard (Figure 1). Today, although a 10�g/dl is adopted, several studies haverevealed some health effects associated even with lower levels. In fact, theremay be no safe level below which no negative health effects are observed(ATSDR, 1995).
This paper assesses the problem of lead emissions from the combustion ofleaded gasoline in Lebanon. Available information on BLL, and gasolineconsumption and characteristics are presented. The benefits of the switch fromleaded to unleaded gasoline in urban areas is evaluated using available dose-response relationships developed by the US Environmental Protection Agency(EPA) for selected health endpoints. The potential costs of the transition tounleaded gasoline in addition to the benefits from health and car-relatedsavings are estimated by relying on previous phase-out initiatives withadjustment for income difference.
2. The Lebanese contextThe Lebanese vehicle fleet mainly comprises of passenger cars and ischaracterized by relatively old (14 years average age), deteriorated and poorlymaintained vehicles, resulting in high pollutant emission rates (Kaysi andSalvucci, 1993). In the absence of direct governmental intervention, leadedgasoline (maximum lead content of 0.66g/l) is the predominant grade of fuelused. In 1997, total gasoline import was about 1,319 thousand tons, of which530 thousand, were of the regular grade, 631 thousand of the premium grade,and 158 thousand of the unleaded grade (UNDP, 1999).
Figure 1.Historical recommended
action level for bloodlead level in children in
the USA
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Measurements of blood lead levels have been conducted in adults and children(Nuwayhid, 1999). One study conducted in 1993 measured BLL in maleworking adults (Figure 2). The distance commuted to work along withoccupation type and smoking habit were associated to a mean BLL of 15.8�g/dl(Nuwayhid, 1999), which is comparable to values reported in European andAmerican countries before phase-out programs were implemented (Figure 3).
Another study measured BLL in more than 70 working children (10-17 yearsold) and compared it to children who are studying but working part-time andchildren who are only studying (Figure 4). Mean BLL was 9.75�g/dl forstudents, 11.36�g/dl for working students and 13.54�g/dl for workers.
Measurements of BLL among 284 healthy babies and children (1-3 years old)presenting to the AUB medical center for routine checkup have also beenconducted in 1998. Mean BLL was 6.6�g/dl; 14 percent had a BLL of 10 mg/dl
Figure 2.Blood lead levels forworking adults inLebanon
Figure 3.BLL in Lebanese adultmales in comparison tointernational reportedtrends
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or more. This was associated with manual job of the father, living in an areawith traffic jams, and low income.
Measurements of BLL among school children revealed that 15-18 percent oftested children have BLL greater than or equal to 10�g/dL. Highest BLL wereabout 17-18 �g/dL (Figure 5).
As is the case with adults, children's BLL are comparable to values reportedin countries in the 1970s and 1980s when leaded gasoline was the predominantfuel grade (Figure 6).
3. Impact assessmentAlthough the association between the phase-out of leaded gasoline and thedrop in blood lead levels is evident, it is difficult to quantify the impacts oflead exposure. As such, precise assessment of health outcomes of the phase-out of leaded gasoline is difficult to make. This is mainly due to factors such
Figure 4.BLL in 10-17 year old
working andnon-working children in
Lebanon
Figure 5.BLL in 1-3 year oldhealthy children in
Lebanon
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as the lack of a dose-response relationship for some exposure outcomes, orthe uncertainty associated with available ones. In this context, dose-responserelationships have been derived for only few outcomes associated with BLL.This section presents the methodology used to estimate harmful healthendpoints associated with elevated BLL. Dose-response functions andsummary of health impacts for each affected group are presented.
3.1 MethodologyThe impact assessment of the predominant use of leaded gasoline in Lebaneseurban areas was conducted using dose-response functions for children andadults derived by the USEPA (USEPA, 1997) based on available epidemiologicstudies.
3.1.1 Potential health impacts in children. Lead induces neurobehavioraldeficiency in young children, including hyperactivity, behavioral and attentiondifficulties, as well as mental, motor and perceptual skill deficits. Limitedeffects can be quantified and expressed in IQ tests and scores due to lack ofdata. Currently, available data permit the quantifying of the relationshipbetween BLL and IQ points loss, mental retardation, and mortality. A highlysignificant relationship (p < 0.0001) suggests that a 1�g/dl increase in BLLresults in a decrease of 0.245 � 0.039 IQ points. Accordingly, the total IQ pointsloss for each group can be expressed by equation (1). Note that the populationof children up to age six was divided by seven in order to avoid multiplecounting, assuming even distribution by age.X
IQ � 0:25��E�x� � P
7�1�
Figure 6.BLL in Lebanesechildren in comparisonto international trendsbefore lead phase out
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395
where�E�x� = change in the mean of BLL distributionP = total population of children up to age six
In addition, lead increases the incidence of mentally retarded children (IQscores < 70). Assuming that the population of children have blood leaddistributions defined by some geometric mean and geometric standarddeviation, and that the population has a normalized IQ point distribution with amean of 100 and a standard deviation of 15, the proportion of populationexpected to have an IQ < 70 is determined by:
�PIQ<70� � ��znoÿcontrol� ÿ ��zcontrol� � ��znoÿcontrol� ÿ 0:02775 �2�
��z� � 1�����2�p
�zÿ1
eÿz2
2 dz �3�
where� (z) = standard distribution function� PIQ < 70 = change in the probabilty of children having IQ < 70zcontrol = standard normal variate
For an IQ score of 70, with mean IQ score of 100 and standard deviation of 15, Zis computed as:
z � 70ÿ 100
15� ÿ2
z�noÿcontrol� �70ÿ ÿ100� 0:25��PbB
�15
�4�
�PbB = change in the average BLL, �g/dl
Multiplying the probability change �P (IQ<70) by the exposed population ofchildren yields the number of children with mental retardation due to increasein BLL. As in equation (1), this relation is applicable to children up to age six,and the population is divided by seven to avoid multiple counting.
Maternal blood lead levels were correlated with several adverse healthimpacts on fetuses including decreased gestational age, induced birth weight,late fetal death, and increased rate of infant mortality. To estimate the changesin infant mortality, gestational age was linked to maternal BLL and infantmortality was linked to gestational age. Accordingly, the risk of infantmortality decreased by 10-4 for each 1�g/dl decrease in maternal BLL.
3.1.2 Potential health impacts in adults. Quantified health effects in adults arerelated to the effects of lead on blood pressure, including increased probability ofhypertension, initial coronary heart disease (CHD), strokes, and premature
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mortality. Elevated BLL has been related to high blood pressure in adults. Formen aged between 20 and 74 years a dose-response relationship for hypertension(defined as diastolic blood pressure above 90 mmHg) is expressed as[3]:
�Pr�HYP� � 1
1� e2:744ÿ0:793�ln x1� ÿ1
1� e2:744ÿ0:793�ln x2� �5�
where� Pr(HYP) = change in the probabilty of hypertension[4]x1 = BLL in the control scenario, �g/dlx2 = BLL in the no-control scenario, �g/dl
In addition to increased probability of hypertension, increased blood pressureincreases the probability of initial occurrence and reoccurrence of coronaryheart disease (CHD), initial cerebrovascular accidents (CA), initialatherothrombotic brain infarctions (BI), and premature mortality. Accordingly,changes in BLLs are related to changes in blood pressure which are in turnrelated to changes in the probability of occurrence of these effects. Thus formen, the change in diastolic blood pressure can be expressed as:
�DBPmen � 1:4� In
�x1
x2
��6�
where� DBPmen = changes in men's diastolic blood pressure, mmHg
For women, results of several studies suggested that the effect on bloodpressure of a decrease of BLL from 10 to 5�g/dl is about 60 percent of the effectof the same change observed in men.
�DBPwomen � �0:6� 1:4� � ln
�x1
x2
��7�
where� DBPwomen = changes in women's diastolic blood
The general form of the change of probability of occurrence of the above effectsin adults is expressed as:
�Pr � 1
1� e�ÿ��ln DBP1� ÿ1
1� e�ÿ��ln DBP2� �8�
where�Pr = change in the probabilityDBP1 = mean diastolic blood pressure in the control scenario, mmHgDBP2 = mean diastolic blood pressure in the no-control scenario, mmHg�= empirical constant� = Does-response coefficient
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Table II presents a summary of dose-response coefficients used in theprobability distribution to estimate lead health effects in adults. Note that thedose-response coefficients for CHD and strokes account only for non-fatalcases. It was reported that two-thirds of the CHD and 70 percent of the strokesare non-fatal. Fatal CHD and strokes were accounted for in the mortalitycoefficients.
3.2 Summary of health impactsUsing the above dose response relationships, the impact of vehicular leademissions on adult and children in major urban regions in Lebanon isestimated. Due to limitation in data availability, several assumptions have beenmade:
(1) Population of major urban areas only are considered (about 1,639,000(ERM, 1995)) since it is expected that in such locations vehicularemissions would constitute a significant source of lead pollution withhigh exposure potential.
(2) Age distribution of the studied population is assumed to be the same asthat of the whole Lebanese population distribution (Figure 7).
(3) Population within each age group is assumed to be evenly distributedby age.
(4) Blood lead levels are assumed to be independent of age in children andadults.
(5) Based on average levels reported in several studies, average BLL inwomen is assumed to be 64 percent of that in men (COWI, 1998a;Wietlisbach et al., 1995).
Table II.Summary of dose-
response coefficientsfor two-year
probability distribution
�
Health effect Age group � meanStandarddeviation
CHDmena 40-59 4.996 0.03036 0.003586
60-64 5.19676 0.023531 0.02865-74 4.90723 0.02031 0.00901
CHDwomen 45-74 6.9401 0.03072 0.00385BImen 45-74 8.58889 0.04066 0.00938BIwomen 45-74 9.07737 0.04287 0.00754CAmen 45-74 9.9516 0.04840 0.00711CAwomen 45-74 10.6716 0.0544 0.00637Mortalitymen
b 40-45 5.3158 0.03516 0.1659655-64 4.89528 0.01866 0.0053365-74 3.05723 0.00547 0.00667
Mortalitywomen 45-74 5.40374 0.01511 0.00419
Notes: a ten-year probability; b 12-year probability
Source: USEPA (1997)
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(6) The phase-out of leaded gasoline will result in a 77 percent reduction inBLL of children and 78 percent reduction in BLL of men and women(Pirkle et al., 1994).
(7) BLL in pregnant women is assumed to be the same as that in non-pregnant ones.
The results of the health impact assessment for children and adults arepresented in Tables III and IV respectively.
4. Cost-benefit analysis of lead phase-outThe costs and benefits of switching from leaded to unleaded gasoline inLebanese urban areas are assessed based on international experience. Refinedestimates can be obtained with elaborate and updated local data and detailedanalysis of country-specific characteristics such as blood lead levels, ambientair lead monitoring, statistics about mortality and morbidity as well as theircorresponding unit costs, and maintenance savings unit costs.
Figure 7.Age distribution of theLebanese population
Table III.Impact of vehicularlead emissions onchildren in Lebaneseurban areas
Number of casesEffect Average Range
Total IQ point loss (points) 42,689 35,176-48,495Mental retardation (cases) 167 NAChild mortality (cases) 31 NA
Notes: NA = Not applicable
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4.1 Costs of lead phase-outWorldwide experience showed that phasing out lead from gasoline istechnically feasible, and the costs are generally modest. In general, the costs ofremoving lead from gasoline are grouped into: first, costs of refineryadjustments and gasoline additives; and second, costs of the distributionsystem adjustments.
4.1.1 Unleaded gasoline and lead additives. In gasoline importing countries,phase-out of leaded gasoline can be easily accomplished without substantialcost. In fact, the incremental cost of switching to unleaded gasoline isdetermined by the difference in price between unleaded and leaded gasoline ontheir main import markets. Frequently, unleaded gasoline prices have beenlower for some octane grades (for example, 95 RON) than leaded gasoline, dueto structural over-capacities in production. The cost of switching from leaded tounleaded gasoline for importers is expected to be very low, consisting mainly ofthe costs of lubricant additives and additional transportation costs to accessnew suppliers if necessary (Lovei, 1997).
World-wide experience and hypothetical estimates indicate that annualizedinvestment expenditures and added operating costs associated with theremoval of lead from gasoline are typically about 0.01-0.02 USD per liter.Although these estimates were made for specific refineries, the numbers arerelatively comparable and within the same order of magnitude. Hence, theyprovide a reasonable estimate of the expected costs of actions and measuresassociated with lead phase-out programs.
In Lebanese urban areas, annual gasoline consumption is estimated at 0.65million tons (equal to the 1997 import of leaded gasoline multiplied bypercentage of vehicles in urban areas). Taking gasoline density to be equal to0.785kg/l, the annual cost difference between unleaded and leaded gasoline isabout 7.6-15.1 million USD for a unit cost of 0.01-0.02 USD/l.
Table IV.Impact of vehicular
lead emissions onadults in Lebanese
urban areas
Number of casesEffect Age group Mean Minimum Maximum
Hypertension men 20-74 1,688.3 NA NACHD men 40-59 54.6 15.3 133.0
60-64 24.1 10.0 482.665-74 30.7 3.3 152.4
CHD women 45-74 46.8 12.2 122.2CA men 45-74 42.7 7.7 162.5CA women 45-74 22.9 4.6 77.3BI men 45-74 26.5 3.8 127.4BI women 45-74 16.8 3.0 63.3Mortality men 40-54 50.9 21.1 0.01
55-64 36.1 6.8 121.265-74 12.9 5.4 78.0
Mortality women 45-74 25.0 5.3 75.8
Notes: NA = Not applicable
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4.1.2 Distribution system adjustments. Typically, adjustments to thedistribution system do not entail major expenditure, particularly in developingcountries (where labor is significantly cheaper), since the same system can beused for distributing unleaded gasoline after phasing out leaded gasoline.These costs are attributed to the once-and-for-all cleaning of tank lorries, pipes,pumps, and underground storage tanks which can be performed by one to twoworkers for one work day (Naranong, 1995). In the transition period duringwhich leaded and unleaded gasoline are both distributed, unleaded gasolinecan replace one grade of leaded gasoline without the need for additionaldistribution infrastructure, except for different pump nozzle sizes for leadedand unleaded grades. Overall, distribution costs are minor and can be neglectedin comparison to the cost of refinery adjustments, when assessing the cost oflead removal from gasoline.
4.2 Benefits of lead phase-outGenerally, the benefits associated with phasing out lead from gasoline can begrouped into: health-related benefits; and car-related benefits. In the USA, thebenefits of lead phase-out from gasoline are estimated to exceed its costs bymore than ten times (Schwartz, 1994). Similarly, estimated benefits of leadremoval exceeded the costs by three to six times in Nizhny Novgorod, RussianFederation (Lovei, 1997).
4.2.1 Health benefits. Valuing the benefits of lead phase-out depends oncountry-specific factors such as the cost of labor, labor productivity, capital andmedical care, life expectancy, people's values of health and life, and theirwillingness to accept risk. Therefore, concrete valuation of the health benefitsof the phase-out of leaded gasoline is difficult to make due to the lack ofcountry-specific data. The situation is worsened by the uncertainty associatedwith the parameters and functions used in estimating the health outcomes oflead exposure. Nevertheless, this process provides a rough estimate of themagnitude of the health benefits associated with switching to unleadedgasoline.
4.2.1.1 Valuation techniques. Several methods are available for valuing thehealth benefits of removing lead from gasoline. Typical methods used forvaluing mortality outcomes include the human capital approach and thewillingness to pay (WTP) approach. In case original data on the WTP arelacking, one can use income adjusted mortality values from other countriesafter compensating for income difference (see Figure 8).
To assess the morbidity outcomes, methods typically used include the costof illness (COI) approach, and the WTP approach. The choice of the method tobe used depends on several factors, particularly the availability of data for themethod used. In this study, COI values estimated for the US population havebeen used to estimate morbidity outcomes of lead exposure. To estimatemortality costs, WTP values estimated in the USA have been used. USmorbidity and mortality values estimated for the year 1990 (USEPA, 1997)have been adjusted for inflation to the year 1998 (by multiplication with an
Leaded gasolinephase-out:
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inflation factor of 1.2547 (CJR, 1999) and for the Lebanese context based onincome ratio as depicted in Figure 8, where a ratio of about 0.12 has beenestimated based on a gross national per capita product (GNP) of 29,340 USD forthe USA (World Bank, 1999b) and 3,560 USD for Lebanon (World Bank, 1999a)for the year 1998. Note that the income ratio method was not applied in theestimation of the phase-out costs since they are based on unit costs, which relyto a large extent on the international market.
. Valuing benefits of lead phase-out for children. For children, IQ reductionis expected to result in reduced present value of expected lifetime earningsand increased educational expenditure on an infant who becomesmentally disadvantaged or is in need of compensatory education. Table Vpresents the estimated benefits resulting from decreased BLL in children.
. Valuing health benefits of lead phase-out for adults. Benefits fromreduced morbidity in adults can be approximated by medical costs(physician care, drugs, and hospitalization costs) and costs of restrictedactivity or work loss days (Table VI). This provides a conservativeestimate of the real costs as it excludes the value of pain, suffering, diet,and behavior modification in addition to the side effects of medications.
4.2.1.2 Application to Lebanon. Using the methodology outlined above andapplied on estimated reduction in adverse health outcomes from Tables III andIV, the monetized benefits of phasing out leaded gasoline are presented inTables VII and VIII. While these costs exhibit wide variations and are forselected age groups and for some health effects, they provide a conservative
Figure 8.Transfer of mortalityand morbidity values
across countries
Table V.Monetized benefits
from reducingchildren's BLL in the
USA
Cost per caseHealth outcome (1990 USD)a (1998 USD)b
Lost IQ points (per point) 2,957 3,710IQ < 70 (per case) 42,000 52,697Infant mortality (per case) 4,800,000 6,022,560
Notes: a (USEPA, 1997); b Inflation factor = 1.2547 (CJR, 1999)
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estimate of the benefits expected from switching to unleaded gasoline. Clearly,mortality costs constitute the major contributor to the estimated benefits fromthe reduction in BLL.
4.2.2 Other benefits of lead phase-out. In addition to the human healthbenefits, shifting from leaded to unleaded gasoline results in important costsavings associated with reduced car maintenance from lead induced corrosionof exhaust systems and engines. Switching from leaded to unleaded gasolinemay increase engine life by as much as 150 percent (Faiz et al., 1996). Thesavings can be attributed to (Walsh and Shah, 1997):
Table VI.Monetized benefitsfrom reducing adultBLL in the USA(USEPA, 1997)
Cost (1990 USD per case)a Cost (1998 USD per case)b
Health outcome Men Women Men Women
Hypertension 681 - 854CHD 52,000 52,000 65,244 65,244Stroke 200,000 150,000 250,940 188,205Mortality 4,800,000 4,800,000 6,022,560 6,022,560
Notes: a USEPA (1997); b Inflation factor = 1.2547
Source: CJR (1999)
Table VII.Monetized benefitsfrom reducingchildren's BLL inLebanese urban areas
Cost per case Cost (1998 USD) � 1,000Health outcome (1998 USD) Average Range
Total IQ loss 450 19,217.5 13,414.7-25,175.5Mental retardation 8,023 1,069.3 NAChild mortality 730,754 22,427.0 NATotal ± 42,713.8 36,911.0-48,671.8
Note: NA = Not applicable
Table VIII.Monetized benefitsfrom reducing adultBLL in Lebanese urbanareas
EffectCost per case(1998 USD)
Average cost(1998 USD) � 1,000
Cost range(1998 USD) � 1,000
Hypertension men 104 175.0 NACHD men 7,916 867.5 226.3-6,079.7CHD women 7,916 370.8 96.4-967.7CA men 30,448 1,301.2 233.6-4,947.1CA women 22,836 521.9 104.2-1,766.4BI men 30,448 808.2 114.6-3,880.6BI women 22,836 384.2 69.4-1,444.4Mortality men 730,754 66,799.7 21,796.8-145,578.9Mortality women 730,754 18,286.6 3,836.7-55,379.5Total 89,514.2 26,653.1-220,219.3
Note: NA = Not applicable
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. longer intervals between spark plug changes (every other year insteadof every year);
. longer intervals between oil and filter changes (once a year instead oftwice a year);
. reduced need for muffler replacement (twice per five years instead ofonce per year);
. reduced need for exhaust pipe replacement (none opposed to once everyfive years);
. reduced need for carburetor servicing.
Car maintenance savings from switching from leaded to unleaded gasoline inCanada were estimated at about 0.017 USD per liter of gasoline (1980 prices)corresponding to about 27 USD per year per car (Walsh and Shah, 1997).Savings estimates for the USA are about 0.003-0.024 USD per liter of petrol(Hirshfeld and Kolb, 1995). If similar unit cost savings are assumed forLebanon, the estimated total benefits in car maintenance savings fromswitching to unleaded gasoline in Lebanese urban areas range from 2.5 to 19.9million USD after accounting for inflation till the year 1998. However, theseestimates seem to over-predict real values since part of these savings areassociated with labor costs which vary among countries, particularly betweenLebanon and the USA. On the other hand, using the income ratio approachwould provide the minimum cost savings because car maintenance involvesboth labor and spare parts. The latter is typically at the same price, if not moreexpensive, in non-manufacturing countries. Accordingly, the minimum carmaintenance savings from switching to unleaded gasoline range from 0.3 to 2.4million USD.
In addition to cost savings from reduced maintenance costs, the phase-out oflead from gasoline improves fuel economy in three ways:
(1) increasing the energy content of petrol through more intense processing;
(2) reducing the fouling of oxygen sensors in mis-fuelled late-modelvehicles; and
(3) reducing the fouling of spark plugs.
Monetized estimates of the cost savings attributable to improved petrol energydensity from shifting from leaded to unleaded petrol are estimated at 0.0024USD per liter of petrol (COWI, 1998b). For the case of Lebanon, using unleadedgasoline in urban areas [5] will result in a cost saving from improved fuelefficiency of about 2 million USD, which when multiplied by income ratioresults in 0.25 million USD. These values are conservative estimates since theincome ratio approach reflects minimal savings in this case.
Generally, the costs of modifying the vehicle fleet to operate on unleadedpetrol or the cost of the addition of lubricants may be comparable to thesavings in maintenance costs and the increased fuel economy from phasing outlead (COWI, 1998b). Comparing the estimated benefits and costs of the phase-
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out of leaded gasoline, it is evident that such action is economically justified.However, several measures should be adopted to accelerate the transition fromleaded to unleaded gasoline.
5. LimitationsLimitations in this study can be classified into three categories:
(1) limitations in the available data;
(2) limitations in the health impact assessment; and
(3) limitations in the economic assessment.
Limitations in the available data are mainly attributable to BLL values as theyreflect only recent exposure at a single point in life, and to the relatively smallsample size. Limitations in the health impact assessment are mainly incurredfrom the absence of dose-response functions for several health effects of leadexposure and the uncertainties in the available ones, as well as in theassumptions adopted in the absence of better estimates of specific data, such asthe assumption of even age distribution within each age group, independenceof BLL of age in children and adults, population estimation, relation betweenmen's and women's BLL values, etc. The limitations in the economicassessment result not only from uncertainties in the mortality and morbidityvalues estimated in the USA, but also in the extrapolation of these values bythe multiplication by the income ratio between countries. The application ofincome ratio in the estimation of car maintenance savings limits the usefulnessof this method to lower bounds rather than real estimates.
6. Summary and conclusionsLead emission constitutes a significant environmental health concern,particularly in urban congested areas. Although vehicles are not the onlysource of lead emissions, they are often the main one in these areas. In Lebanon,leaded gasoline is the predominant fuel grade used (88 percent). Availableinformation reveals that average BLL in Lebanese babies one to three years old(6.6�g/dl), children 10-17 years old (9.75 to 13.54�g/dl), and adults (15.8�g/dl)are comparable to those previously reported in other countries before thephase-out of leaded gasoline, and are expected to drop with the implementationof such a program.
Based on previous lead phase-out initiatives, BLL are expected to decrease inexcess of 75 percent in children and adults. Using dose-response relationshipsdeveloped on the basis of epidemiologic studies, selected health benefits from adecline in BLL are estimated for children and adults in Lebanese urban areas.In children, a 77 percent reduction in BLL will prevent the loss of 42,689 IQpoints, the occurrence of 167 cases of mental retardation, and 31 cases ofpremature mortality. In adults a 78 percent reduction in BLL will prevent theoccurrence of 1,688 cases of hypertension in adult males, 157 cases of coronaryheart disease, 44 cases of brain infarctions, 66 cases of cerebrovascular
Leaded gasolinephase-out:
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405
accidents, and 125 cases of premature mortality in both males and females. Thecost of illness and willingness to pay values derived for the USA are used toestimate morbidity and mortality cost savings respectively after adjustment forincome difference between the USA and Lebanon. Estimated cost savings areabout 42.7 million USD for children and 89.5 million USD for adults. Thesebenefits will translate to nearly 40 USD per capita per year for the entirepopulation. Additional cost savings can be accrued from reduced carmaintenance and improved fuel efficiency. The comparison of the expected costsavings from phasing out leaded gasoline with the potential costs indicates thatsuch action is economically highly justified.
Notes
1. While organic lead such as gasoline lead additives can be easily absorbed through theskin, dermal absorption of inorganic lead, the predominant form of vehicular leademissions, is negligible (WHO, 1995).
2. Symptoms described by Hippocrates at about the fourth century BC for lead intoxicationare the same as those classified today.
3. Elevated BLL is associated with hypertension in both men and women; however, no dose-response function for hypertension in women is currently available.
4. Due to lack of averaging time, the number of annual cases of hypertension was estimatedby dividing the total number of cases by 55 (74 ± 20 +1).
5. Costs and savings for cars outside urban areas were not included to restrict the cost-benefitanalysis to urban areas.
References
ATSDR (Agency for Toxic Substances and Disease Registry) (1995), Case Studies inEnvironmental Medicine: Lead Toxicity, US Department of Health and Human Services(US DHHS), Atlanta, GA.
CJR (Columbia Journalism Review) (1999), ` CJR dollar conversion calculator'', CJR. http://www.cjr.org/resources/inflater.asp
COWI Consulting Engineers and Planners (1998a), UN/ECE Task Force to Phase-out LeadedPetrol: Country Assessment Report, Danish Environmental Protection Agency (DEPA),Copenhagen.
COWI Consulting Engineers and Planners (1998b), UN/ECE Task Force to Phase-out LeadedPetrol: Main Report, Danish Environmental Protection Agency (DEPA), Copenhagen.
Earth Summit Watch (1997), ` Four in '94: accessing national actions to implement agenda 21'',http://www.earthsummitwatch.org/4in94.html
ERM (Environmental Resources Management) (1995), Lebanon: Assessment of the State of theEnvironment, Ministry of the Environment, Beirut.
Faiz, A., Weaver, C.S. and Walsh, M.P. (1996), Air Pollution from Motor Vehicles, World Bank,Washington DC.
Hirshfeld, D. and Kolb, J. (1995), ` Phasing out lead from gasoline: feasibility and costs. A study ofthe refining sector in Romania'', in series of Implementing the Environmental ActionProgramme for Central and Eastern Europe, World Bank, Washington, DC, cited in Lovei,M. (1998), Phasing out Lead from Gasoline: Worldwide Experience and Policy Implications,World Bank, Washington DC.
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IOMC (Inter Organization Programme for the Sound Management of Chemicals) (1998), GlobalOpportunities for Reducing the Use for Leaded Gasoline, United Nations, Geneva.
Kaysi, I. and Salvucci, F. (1993), Passenger Transportation Options for a Revitalized Beirut, AUB/MIT Collaborative Program on Science, Technology, and Development, AmericanUniversity of Beirut, Beirut.
Lovei, M. (1997), Phasing out Lead from Gasoline in Central and Eastern Europe, Health Issues,Feasibility, and Policies, World Bank, Washington DC.
Lovei, M. (1998), Phasing out Lead from Gasoline: Worldwide Experience and Policy Implications,World Bank, Washington DC.
Lovei, M. (1999), Eliminating a Silent Threat: World Bank support for the Global Phaseout of Leadfrom Gasoline, World Bank, Washington, DC.
Naranong, A.A. (1995), ` An analysis of potential policies for reducing lead in gasoline inBangkok'', PhD Dissertation, Faculty of Graduate School, Vanderbilt University, TN.
Nuwayhid, I. (1999), ` Faculty of health sciences'', American University of Beirut, Beirut, personalcommunication.
Pirkle, J.L., Brody, D.J., Gunter, E.W., Kramer, R.A., Paschal, D.C., Flegal, K.M. and Matte, T.D.(1994), ` The decline in blood lead levels in the United States. The National Health andNutrition Examination Surveys (NHANES)'', Journal of American Medical Association,Vol. 272 No. 4, pp. 284-91.
SCEP (State Committee for Environmental Protection of the Russian Federation) (1997), WhitePaper: Lead Contamination of the Environment in the Russian Federation and its Effect onHuman Health, Moscow.
Schwartz, J. (1994), ` Societal benefits of reducing lead exposure'', Environmental Research,Vol. 66 No. 1, pp. 105-24, cited in Lovei, M. (1997), Phasing out Lead from Gasoline inCentral and Eastern Europe, Health Issues, Feasibility, and Policies, World Bank,Washington DC.
UNDP (United Nations Development Programme) (1999), Climate Change, UNDP, Beirut.
USEPA (United States Environmental Protection Agency) (1997), Benefits and Costs of the CleanAir Act, Final Report to Congress on Benefits and Costs of the Clean Air Act, 1970 to 1990,USEPA, Office of Air and Radiation, EPA 410-R-97-002.
Walsh, M. and Shah, J. (1997), Clean Fuels for Asia. Technical Options for Moving TowardUnleaded Petrol and Low-Sulfur Diesel, World Bank, Washington DC.
WHO (World Health Organization) (1980), Recommended Health Based Limits in OccupationalExposure to Heavy Metals: Report of a WHO Study Group, Geneva, WHO, TechnicalReport Series N0. 647, cited in WHO (1995), Environmental Health Criteria 165: InorganicLead, United Nations Environment Programme, International Labour Organization, andWHO, Geneva.
WHO (World Health Organization) (1995), Environmental Health Criteria 165: Inorganic Lead,United Nations Environment Programme, International Labour Organization, and WHO,Geneva.
Wietlisbach, V., Rickenbach, M., Berode, M. and Guillemin, M. (1995), ` Time trend anddeterminants of blood lead levels in a Swiss population over a transition period (1984-1993)from leaded to unleaded gasoline use'', Environmental Research, Vol. 68 No. 2, pp. 82-90.
World Bank (1999a), Lebanon at a Glance, World Bank, http://www.worldbank.org/data/countrydata/aag/lbn_aag.pdf.
World Bank (1999b), United States at a Glance, World Bank, Washington, DC, http://www.worldbank.org/data/countrydata/aag/usa_aag.pdf
30 Noise Control Eng. J. 50 (1), 2002 Jan–Feb © 2002 Institute of Noise Control Engineering
1. INTRODUCTION
Aircraft traffic is a major source of community concerndue to aircraft noise emissions, particularly in locations closeto airports and aircraft flight tracks. The effects of noise onhumans can range from minor annoyance, sleep disruption,and speech interference, to hearing damage.1-3 Noise impactsare typically dependent on the duration and level of the noiseexposure. As a result, noise exposure criteria have beendeveloped by many organizations using various noiseindicators (Table 1).
While noise is best known for its disruptive effects suchas loss of sleep, decrease in productivity, and loss of hearing,these effects are very hard to quantify in monetary terms.However, since noise is associated with a place, its socialcost has been commonly related to a loss in property value.10
In this context, the hedonic price method has been extensivelyused to evaluate social cost due to noise pollution. In thismethod, the evaluation of the cost of noise can depend onseveral variables ranging from locational traits (access tocentral business district), land use characteristics (zoningcodes), and site peculiarities (width of the frontal road).11
While hedonic methods have become the best-suitedtechniques for estimating noise damage cost,12 they requiresignificant amounts of hard to acquire data to conduct ameaningful cost estimation. Another method for the evaluationof noise cost is through the determination of the willingnessto pay (WTP) for environmental benefits. This methodconsists of asking people if they are willing to pay for areduction of noise in their neighborhood for example, or howmuch they want as a compensation for deterioration inenvironmental conditions such as increased noise.13 Simplermethods based on international field surveys relating socialcosts to travel distance have also been reported.10 In this study,
the hedonic price method was applied and compared withinternational survey results. The WTP approach was deemedinappropriate because of the illegal nature of major settlementsin the immediate vicinity of the airport where it is not feasibleto conduct an economic survey to define the WTP.
A. Hedonic price method
The cost of noise can be best estimated by the decline in aproperty value affected by noise generated from aircraft traffic.This is reinforced by the fact that people are ready to paymore for a property in order to avoid high noise levels.14 Mostestimates are developed using hedonic pricing methods whichassume that an item’s value (property or house) is composedof a number of factors (area, age, location, neighborhood,environmental quality, etc.). The contribution of eachparameter can be obtained by regression analysis.10 Toestimate the implicit cost of noise due to aircraft traffic, thedecline in the price of a property is modeled as a function ofambient noise.15 For this purpose a noise depreciation indexor the percent reduction in a house price per A-wtd soundpressure level (in dB) above a reference background value isused. Using this method, the annual cost of noise impactscan be estimated from Eq. (1).12
C I P (N N ) Hn NDI v ai
i
0 i= ◊ ◊ - ◊ (1)
Where INDI
is the noise depreciation index, Pv is the annual
average house rent in the area, Nai is the noise for the ith section
of the noise contour, N0 is the background noise, H
i is the
number of residences in the ith section.Research has shown that the I
NDI has an average value of
0.62 percent and an A-wtd background sound pressure levelof 50 dB is typical in urban areas.10 International surveysconstitute a more simplified process that can be used for noisevaluation. This method is based on field surveys in which thecost of noise is evaluated as a function of passengers andkilometers traveled as shown in Table 2.
In this paper, both approaches were compared in
a) American University of Beirut, Faculty of Engineering and Architec-ture, Bliss Street, P.O. Box 11-0236, Beirut, Lebanon; Fax: 961-1744-462; E-mail: [email protected].
Case History: An assessment of the economic impact of airport noise emissionsnear Beirut International Airport
M. El-Fadela) and M. Chahinea)
(Received 2001 January 15; revised 2001 October 04; accepted 2001 October 12)
This paper presents a socio-economic assessment of noise impacts from aircraft traffic oncommunities near the Beirut International Airport. Mathematical modeling was conducted tosimulate aircraft-induced noise emissions and delineate noise contour zones. An economicvaluation of noise-impacted areas was performed using model-delineated noise contour zonescoupled with population and home rental statistics. The same aircraft traffic data were alsoused to evaluate the effects of a different runway configuration to minimize the impacted areasand corresponding noise cost. When the current runways were used a total social cost of noiseimpact was evaluated at 16.9 million USD per year or 0.0038USD/passenger/km traveled. It isestimated that an 87 percent reduction in social cost could be accomplished by changing therunway configuration. © 2002 Institute of Noise Control Engineering.
Primary subject classification: 67.1; Secondary subject classification: 76.1.1.3
31Noise Control Eng. J. 50 (1), 2002 Jan–Feb
conducting the economic valuation of aircraft noise impactsat the Beirut International Airport (BIA), which is located onthe southern periphery of the city of Beirut, about 8 km fromthe city center, occupying a coastal site bordered by mountainsas shown in Fig. 1. For this purpose, noise modeling was firstperformed to delineate noise-impacted areas by aircraft trafficand an economic valuation of noise impacts was thenperformed using the hedonic approach and a comparison withinternational surveys. The same aircraft traffic data were alsoused to evaluate the effects of changing the runwayconfiguration on minimizing the impacted areas andcorresponding noise cost.
2. AIRCRAFT NOISE MODELING
A. Existing conditions
The airport has two intersecting runways, the easternrunway (21-03) for take-off, and the western runway (36-18)for landing. A new maritime runway extending into the seawas completed in summer 2000. This maritime runway wouldreplace the presently used western runway as shown in Fig.2. This study focuses on delineating, through modelsimulations, the change in noise impacted areas due to theintroduction of the new runway using an economic valuationapproach that correlates noise-impacted areas withcorresponding house rental statistics.
At present, the airport serves a number of regional andinternational airlines, in addition to two local airlines. The
Table 1 – Worldwide criteria for noise exposure.
A. World Health Organization annoyance criteria in residential areas 4
Impact Characterization Daytime Leq
(dB) Nighttime Leq
(dB) Approximate DNL (dB)
Serious Annoyance 55 45 55
Moderate Annoyance 50 40 50
B. World Bank Group 5
Receptor Time Period Time Period Leq
Equivalent DNL (dB)
Residential, institutional, educational Daytime 55 55
Nighttime 45
Industrial, commercial Daytime 70 —
Nighttime 70
C. International Organization for Economic Co-operation and Development6
Land Area Time Period Time Period Leq
(dB) Equivalent DNL (dB)
Urban Daytime 55 55
Nighttime 45
Rural Daytime 50 50
Nighttime 40
D. US National Bodies
D.1 US Department of Transportation, Federal Highway Administration Noise Abatement Criteria7
Activity Leqa (dB) Description of Category
Category
A 57 (exterior) Land on which serenity and quiet are of extraordinary significance and serve an important public need and where the
preservation of those qualities is essential if the area is to continue to serve its intended purpose
B 67(exterior) Picnic areas, recreational areas, playgrounds, active sports areas, parks, residences, motels, hotels, schools, libraries, and hospitals
C 72(exterior) Developed land, properties and activities not included in categories A or B
D — Undeveloped land
E 52(interior) Residences, motels, hotels, schools, libraries, public meeting rooms, churches, auditoriums, and hospitals
a A-wtd equivalent noise level
D.2 US Environmental Protection Agency 8
Level requisite to protect health and welfare with an adequate margin of safety DNL 55 dB
D.3 National Research Council 9
Residential areas DNL of 55 dB
32 Noise Control Eng. J. 50 (1), 2002 Jan–Feb
most common types of aircraft using the airport are the AirbusA310 and A320. Other types of commercial jet aircraft includethe Boeing B707, B727, B737, B767, B777, and the TupolevTU54 as summarized in Table 3. There are still a few dailyoperations of the aging Boeing 707 for cargo shipments. Theaverage number of daily operations is 78 landings anddepartures. The estimated current number of passengers usingBIA is 2.2 million per year and is expected to reach 6 millionpassengers by the year 2015.16
B. Noise simulation
The Integrated Noise Model (INM) developed by theFederal Aviation Administration (FAA) was used to simulateaircraft noise emissions. Day-night noise level (DNL)contours, which are the most widely used metric for the
analysis and development of compatible land use,17 wereadopted as indicators to delineate noise-impacted areas dueto aircraft traffic. The DNL metric is a member of a group ofexposure metrics obtained from the noise level expressed as:
LE = 10 log (W
1E
1 + W
2E
2 ) – 10 log (T), (2)
where LE is the A-weighted equivalent noise level, W
1 and
W2 are weighting factors for day and night time periods, E
1
and E2 are noise exposure ratios for day and night time periods,
and T is averaging time over a reference time of one second.The area around the airport was divided into six DNL
values, which would produce five A-weighted noise contourranges: 55-60, 60-65, 65-70, 70-75, and 75-80 dB. Aircraftfleet composition and daily arrival and departure scheduleswere obtained from airport authorities. Figure 3 depicts thearrival and departure noise contours at standard INM landingand take-off weights and flight operation procedures forpresent airport activities. A total developed area of 27 km2
Table 2 – Noise cost generated from aircraft traffic.10
Average cost$/ passenger/km traveled
Country 1995 1999
Canada 0.0039 0.0043
Germany 0.0049 0.0054
Italy 0.0079 0.0087
Holland 0.0099 0.0108
Sweden 0.0014 0.0015
Switzerland 0.0017 0.0019
France 0.0030 0.0033
United Kingdom 0.0018 0.0020
Average 0.0043 0.0047
Fig. 1 – Location of the Beirut International Airport relative toBeirut City (note that North is down in the photograph).
NMed
iterr
anea
n S
ea0 100 250 500 m
Fig. 2 – Runway configuration at the Beirut International Airport.
33Noise Control Eng. J. 50 (1), 2002 Jan–Feb
was affected by noise generated from aircraft traffic. Notethat noise contours generated from departing aircraft aremostly above the sea.
3. ECONOMIC VALUATION
The area surrounding the airport and falling under theaircraft flight path was subdivided into three zones, shown inFig. 4, corresponding to economic affluence based on a surveyof household average annual income and house rentalstatistics. Table 4 summarizes the total number of residences
and average annual rents in areas exposed to aircraft-inducednoise with corresponding noise exposure levels. The averageannual rent was adjusted for an average house lifetime of 30years and a mortgage interest of 6 percent. Using the hedonicprice method (Eq. 1), the corresponding total social cost dueto noise was estimated at 16.9 million USD per year.
Using annual travel activities (number of passengers andthe travel distance to each destination as obtained from airportauthorities)20 and the social cost incurred by applying thehedonic price method, the equivalent average cost will be0.0038 $/passenger/km traveled which is consistent with therange reported in the literature for international cost-basedsurveys (see Table 2).
4. EFFECT OF RUNWAY CONFIGURATION
Day-night average sound levels (DNL) contours weregenerated for the same aircraft traffic, but using the newrunways configuration whereby the western runway wasreplaced by the maritime runway. The simulated noisecontours are depicted in Fig. 5 and a comparison (with respectto the old runway) of the affected areas is shown in Fig. 6.While the total noise-impacted areas decreased by 5.5 percent(Fig. 6), using the hedonic price method (Eq. 1) the estimatedcost of noise was reduced by nearly 87 percent or 2.2 million
Table 3 – Average daily traffic at BIA.
Arrival Departure
Aircraft type Daya Eveningb Nightc Daya Eveningb Nightc
A310 9 1 2 10 0 2
A320 6 5 4 8 1 6
B707 2 0 0 2 0 0
B727 1 0 0 0 0 1
B737 0 0 3 0 0 3
B767 0 0 1 0 0 1
B777 2 0 0 2 0 0
MD82 1 0 1 1 0 1
TU54 1 0 0 1 0 0
Total 22 6 11 24 1 14
Grand Total 39 39
a 7:00 A.M.–7:00 P.M. b 7:00 P.M.–10:00 P.M. c 10:00 P.M.–7:00 A.M.
Med
iterr
anea
n S
eaN
0 1 2 3 Km
Fig. 3 – Day-night-level noise contours for the year 2000 trafficand existing runway.
Med
iterr
anea
n S
ea
N
0 1 2 3 Km
Fig. 4 – Zone subdivision of noise impacted areas.
34 Noise Control Eng. J. 50 (1), 2002 Jan–Feb
USD per year. This sharp reduction is mainly due to the factthat when the new maritime runway is used, the most affluentand heavily populated zones A and B are no longer affectedby aircraft noise, as shown in Table 5.
Currently a night surcharge of 184 USD is applicable foreach movement (landing or take-off) at BIA.21 Based on thedaily average traffic, the yearly charges are 2.1 million USDper year. However this surcharge is for the usage of the runwayand apron lights only, and is not related to the noise categoryof the aircraft or its weighted noise impact increase.
Other operational measures that can be adopted to reduceaircraft noise include flight scheduling control andenforcement of environmental regulations. At present, about30 percent of the daily flights occur at night (between 10:00PM and 7:00 AM). Noise during the night is known to causea high level of annoyance. The DNL metric adds a 10 dBnight operation penalty to account for this fact. Most airportsin Europe and the US restrict the number of operations duringthe night, and many airports are charging additional fees foraircraft landing at night in accordance with its acoustic noise
category.12 At the BIA, international airline companies arethe main night operators. This can be attributed in part to thegeographic location of Beirut, which dictates its use as a transithub for the region. Another reason may be that the airlines inquestion are avoiding airports that ban night operations, andaccordingly they switch to airports with less stringentstandards on night operations. In addition, existingenvironmental standards are not generally enforced at the BIA.Many aircraft operating at the airport are not in compliancewith international noise standards. While Chapter 2 aircraft(such as the Boeing 747-200) are being phased out in severalairports22 and Chapter 1 (such as the Boeing 707) aircraft arebanned from most airports, they are still in use at the BIA.These aircraft are known to contribute to excessive noisepollution and they must be replaced.
5. SENSITIVITY ANALYSIS
Important parameters that directly affect noise contourswere examined to evaluate 1) how the results might change ifimportant parameters were varied; and 2) mitigationalternatives such as modifying aircraft operations or types.The fleet mix, the breakdown of day and night operations,and airport operations are the parameters considered in thissensitivity analysis. For this purpose the current traffic of 78operations per day (landing and departure), and the currentrunway configurations were used in two additionalsimulations. In the first scenario, all Chapter 1 aircraft (B707and B737) were replaced with Chapter 2 aircraft (B767-300)of comparable weight and capacity. Chapter 1 aircraft, whichare banned at most international airports, are still in operation
Table 4 – Residences within noise contours.
Zone Total number Average annual Percent of area in noise contour (A-wtd. level contours)
of residences18 rent (USD)19
55-60 dB 60-65 dB 65-70 dB 70-75 dB 75-80 dB 80-85 dB
A 42,849 18,150 26.3 — — — — —
B 54,173 10,890 17.9 10.7 1.2 — — —
C 18,876 3,630 19.4 11.9 9.4 9.4 2.5 1.3
Med
iterr
anea
n S
ea
N
0 1 2 3 Km
Fig. 5 – Day-night-level noise contours for the year 2000 trafficand new runway configuration.
20
16
12
8
4
0 – – –
– – –
Y 2000 old runways
Y 2000 new runways
Are
a (k
m2 )
55-60 dB 60-65 dB 65-70 dB 70-75 dB
15.5
11.9
6.96.0
3.6 2,7
1.0 0.9
Fig. 6 – Variation in noise impacted areas with new maritime run-way.
35Noise Control Eng. J. 50 (1), 2002 Jan–Feb
(12 daily operations) at the BIA. It is expected that theseaircraft would be replaced in the coming two years by Chapter2 and 3 airplanes. In the second scenario, all night operationswere replaced by day operations. Night operations (between10:00 P.M. and 7:00 A.M.) are known to cause the highestlevel of annoyance in communities near an airport, and theDNL metric accounts for this by applying a 10 dB night-timepenalty. Finally, in the third scenario, the departure and arrivaltrack paths were swapped: the western runway was used fortaking-off, while the eastern runway was used by approachingaircraft.
The DNL metric was used as an indicator in this sensitivityanalysis, when simulating the areas of noise contours. Theexclusion of Chapter 1 aircraft resulted in a 5 to 16 percentdecrease in noise-affected areas and the total social cost wasevaluated at 15.5 million USD as summarized in Table 6.Banning night operations would decrease the affected areasmore significantly reaching 60 to 69 percent and a total costof 6 million USD. This is mainly due to the high number ofnight operations (31 percent) and the 10 dB weighting factorapplied in the DNL metric. On the other hand, the change inthe runways operations resulted in minimal increase in theoverall impacted area (total social cost of 17.2 million USD).However, in the basic simulation a major part of the noisecontours from departing aircraft was over the sea, while thesecontours would be mainly above zone A residential-commercial area if the departure and arrival track paths areswapped.
6. STUDY LIMITATIONS
Despite recent improvements in INM simulation accuracy,the results should be considered carefully. Several elementsthat may attenuate the exposure of individuals to aircraft noisearound airports (i.e. topography of the area, existence ofbuildings, vegetation, and other types of sound barriers nearthe airport) are not yet fully considered in the INM.23 Inaddition, atmospheric conditions (i.e. humidity, winddirection, turbulence, etc.) are not simulated in the INMcalculations although it is well established that theseconditions have a direct effect on noise propagation.24 Thevalidity of the noise contours generated is a function of theaccuracy of the input data. While these data may be known tosome extent, unpredictable airline and airport decisions canlargely affect these variables. In addition, noise contours weredeveloped for an average 24-hour day, and actual dailyconditions may differ from the average conditions considered.
In calculating the cost of noise using the hedonic pricemethod (Eq. 1), the Noise Depreciation Index (I
NDI) value was
taken as 0.62 percent based on previous studies which maynot be representative of the characteristics of the study area.The cost of noise may have also been reduced if thebackground noise level was taken into account. On the otherhand, an A-weighted background noise level of 50 dB wasassumed as an average value for day and nighttime. Extensivenoise measurements are necessary to better assess temporalvariations, validate model simulations, and define a moreaccurate value for the background noise level. Also, in thehedonic economic valuation method, it is not usual, if notrare, that the buyer is informed, the relations between variablesare linear, or the variables are independent. In fact, noise may
Table 5 – Percent of area within noise contours when using new runways.
Zone Total number Average annual Percent of area in noise contour (A-wtd. level contours)
of residence18 rent (USD)19
55-60dB 60-65 dB 65-70 dB 70-75 dB 75-80 dB 80-85 dB
A 42,849 18,150 — — — — — —
B 54,173 10,890 6.0 3.6 0.6 — — —
C 18,876 3,630 15.6 8.1 7.5 8.8 1.9 1.3
Table 6 – Effects of Changing the Fleet Mix, Removing Night Operations, and Changing Runways Operation.
Fleet mix:No Chapter 1a No night operations Change runways operationNoise contour zone Do nothing
(A-wtd)(dB) area(km2) Area(km2) Difference(%) Area(km2) Difference(%) Area(km2) Difference(%)
55-60 23.43 22.32 5 8.80 62 23.60 -1
60-65 11.91 10.04 16 3.64 69 12.16 -2
65-70 4.90 4.61 6 1.72 65 5.15 -5
70-75 2.12 1.86 12 0.84 60 2.24 -6
Total Cost
(Million USD) 16.9 15.5 6.0 17.2
a Chapter 1 aircraft: licensed before 1970 (ICAO classification)
36 Noise Control Eng. J. 50 (1), 2002 Jan–Feb
correlate directly with variables that can increase an asset’sworth such as distance from the airport. Last but not least,the social cost does not include occupational related expensesdue to employee potential illness, absenteeism, or reducedefficiency due to exposure to elevated and prolonged noiselevels inside the airport.
7. SUMMARY AND CONCLUSIONS
An economic assessment of aircraft noise impacts wasconducted at the Beirut International Airport. The FAA INMwas applied to simulate aircraft induced noise and to delineatenoise-affected areas for the current runway configuration, andwhen a new maritime runway is utilized. The hedonic pricemethod was adopted to estimate the social cost generated fromaircraft noise (in both simulations) and the cost was comparedto an international survey relating social cost to travel distance.Based on the hedonic price method, the social cost (excludingpotential occupational costs) attributed to aircraft traffic noisereached 16.9 million USD/year or 0.0038 $/passenger/kmtraveled which is within the range reported in internationalsurveys for many countries. The estimated cost of noiseimpacts was reduced significantly when the new maritimerunway is introduced (87 percent reduction). While there is anight surcharge on aircraft movements, this surcharge is notrelated to the noise category of the aircraft. Further noise/cost reduction could be attained by phasing out Chapter 2aircraft (such as Boeing 747-200) and Chapter 1 (such as theBoeing 707) aircraft.
8. ACKNOWLEDGMENTS
The study was funded by the Lebanese National Councilfor Scientific Research and the University Research Board atthe American University of Beirut. Special thanks areextended to the United States Agency for InternationalDevelopment for its continuous support of the EnvironmentalEngineering and Sciences Programs at the AmericanUniversity of Beirut.
9. REFERENCES1 K. Kryter, “Community annoyance from aircraft and ground vehicle noise,”
J. Acoust. Soc. Am. 72(4), 1222-1242 (1982).2 S. Lang, “Kids near airports don’t read as well because they tune out
speech,” Cornell Science News (April 28, 2997).3 A. Suter, “Noise and its effects,” Administrative Conference of the United
States (Nov. 1991).4 Guidelines for Community Noise, Edited by Birgitta Berglund, Thomas
Lindvall, and Dietrich Schwela (World Health Organization, Geneva,Switzerland, 1999).
5 Pollution Prevention and Abatement Handbook, General EnvironmentalGuidelines (World Bank Group, 1998)
6 Environmental Criteria for Sustainable Transport, Report on Phase 1 ofthe Project on Environmentally Sustainable Transport (EST) (Organizationfor Economic Co-Operation and Development, OCDE/GD(96)136, Paris,France, 1996).
7 Highway Traffic Noise Analysis and Abatement Policy and Guidance(Federal Highway Administration, Office of Environment and Planning,Noise and Air Quality Branch, Washington DC, 1995).
8 Information on Levels of Environmental Noise Requisite to Protect PublicHealth and Welfare with an Adequate Margin of Safety (US EnvironmentalProtection Agency, Office of Noise Abatement and Control (ONAC), ReportEPA550/9-74-004, Washington D.C., 1974).
9 Guidelines for Preparing Environmental Impact Statements on Noise(National Research Council, Assembly of Behavioral and Social Sciences,Committee on Hearing, Bioacoustics and Biomechanics (CHABA),Washington DC, 1977).
10 D. Levinson, D. Gillen, A. Kanafani, and J. M. Mathieu, The Full Cost ofIntercity Transportation—A Comparison of High Speed Rail, Air andHighway Transportation in California (Institute of Transportation Studies,University of California at Berkeley, 1996).
11 T. Morioka, T. Fujita, and N. Yoshida, “Performance and shortcomings oftypical environmental pollution control programs for automobile traffic inKobe City and surrounding areas. Social cost evaluation of noise pollutionby Hedonic Price Method,” The Science of the Total Environment 189/190, 99-105 (1996).
12 P. Morell and C. Lu, Social Costs of Aircraft Noise and Engine Emissions—A Case Study of Amsterdam Airport Schiphol (In Preprint CD ROM,Transportation Research Board, 79th Annual Meeting, Washington, DC,January 2000.
13 K. Saelensminde, “Stated choice valuation of urban traffic air pollutionand noise,” Transportation Research Part D 4, 13-27 (1999).
14 D. Haling and D. Cohen, “Residential noise damage costs caused by motorvehicles,” In Transportation Research Record 1559, TRB, NationalResearch Council, Washington, D.C., 84-93 (1996).
15 M. Delucchi and S. L. Hsu, “The external damage cost of noise emittedfrom motor vehicles,” J. Trans. Stat. 1(3) 1-24 (1998).
16 Dar Al-Handassah Shair and Partners, “Beirut international airport:Feasibility study,” (Council for Development and Reconstruction, Beirut,Lebanon, January 1994).
17 A. Filho, J. Braaksma, and J. Phelan, “Interpreting airport noise contours,”Transportation Research Record 1475, TRB, National Research Council,Washington, DC, 66-69 (1995).
18 Team International in association with IAURIF and SOFRETU, “GreaterBeirut Transportation Plan. Household Survey Results,” (Council forDevelopment and Reconstruction, Beirut, Lebanon, November 1994).
19 Lebanon Opportunities, Real Estate Average Market Prices per m2, April1999–April 2000.
20 1998 Passenger Traffic, Beirut International Airport. http://www.beirutairport.gov.lb/airport/statistics/statistics.htm. Accessed July 15, 2000.
21 Airport Charges, Beirut International Airport. http://www.beirutairport.gov.lb/airport/parking/parking.htm. Accessed July 15, 2000.
22 W. Meyer and W. Willkie, “A noise contour comparison of stage 3 Hushkitoptions for the Boeing 727-200” (In Preprint CD ROM, TransportationResearch Board, 79th Annual Meeting, Washington, DC, January 2000).
23 FAA, Integrated Noise Model (INM) User’s Guide; version 6.0 (1999)(Federal Aviation Administration, Office of Environment and Energy, AEE99-03, 1999).
24 TRC (Transportation Research Circular), Aircraft Noise Modeling(Transportation Research Board, National Research Council, No. 473, May1997).
Ž .The Science of the Total Environment 257 2000 133]146
Particulate matter in urban areas: health-basedeconomic assessment
M. El-FadelU, M. MassoudDepartment of Ci il & En¨ironmental Engineering, American Uni ersity of Beirut, Beirut, Lebanon
Received 1 February 2000; accepted 31 March 2000
Abstract
The interest in the association between human health and air pollution has grown substantially in recent years.Based on epidemiological studies in several countries, there is conclusive evidence of a link between particulate airpollution and adverse health effects. Considering that particulate matter may be the most serious pollutant in urbanareas and that pollution-related illness results in financial and non-financial welfare losses, the main objective of thisstudy is to assess the economic benefits of reducing particulate air pollution in Lebanese urban areas. Accordingly,the extent and value of health benefits due to decreasing levels of particulate in the air are predicted. Health impactsare expressed in both physical and monetary terms for saved statistical lives, and productivity due to different typesof morbidity endpoints. Finally, the study concludes with a range of policy options available to mitigate particulate airpollution in urban areas. Q 2000 Elsevier Science B.V. All rights reserved.
Keywords: Particulate matter; Health impacts; Dose]response function; Economic assessment
1. Introduction
Ž .Ambient particulate matter PM is composedof a heterogeneous mixture of particles varying insize and chemical composition. Particles differ in
U Corresponding author. American University of Beirut,Faculty of Engineering and Architecture, 850 Third Avenue,New York, NY 10022, USA. Fax: q1-961-1-744-462.
Ž .E-mail address: [email protected] M. El-Fadel .
sources, size ranges, formation mechanisms, andchemical composition and are characterized byvarious physical and chemical properties. Whilephysical properties affect the transport and depo-sition of particles in the human respiratory sys-tem, chemical composition determine their im-pact on health. A wide range of natural andanthropogenic emission sources contribute to PMconcentrations in the atmosphere such as wind-blown soil dust, marine and biogenic aerosol,road traffic and off-road vehiclesrmachines, sta-
0048-9697r00r$ - see front matter Q 2000 Elsevier Science B.V. All rights reserved.Ž .PII: S 0 0 4 8 - 9 6 9 7 0 0 0 0 5 0 3 - 9
( )M. El-Fadel, M. Massoud r The Science of the Total En¨ironment 257 2000 133]146134
tionary combustion processes, industrial and con-struction processes, and combustion of agricul-tural waste. Particles can be emitted directly fromsuch sources and are commonly referred to asprimary particulates, or formed in the atmo-sphere from gaseous precursors and are calledsecondary particulates. The chemical complexityof PM requires that sources of a large number ofprimary and secondary components be consideredŽ .De Nevers, 1995 .
Suspended particulate matter is ubiquitouslyrecognized as the most important air pollutant interms of human health effects considering thatmany epidemiological studies substantiate sig-nificant associations between concentration of PM
Žin the air and adverse health impacts USEPA,.1997; Vedal, 1997 . Fine particulates are likely to
be the most significant contributors to theobserved health effects, owing to their ability toaccumulate and reach the lower regions of therespiratory system. While the effects of PM varyconsiderably depending on its composition andsize distribution, generally, exposure to inhalablePM can cause an increase in cardiac and respira-tory mortality, a decrease in levels of pulmonarylung function in children and adults with obstruc-tive airways disease, an increase in daily preva-lence of respiratory symptoms in children andadults, an increase in functional limitations asreflected by school absenteeism or restricted ac-tivity days, and an increase in physician and emer-gency department visits for asthma and other
Žrespiratory conditions COMEAP, 1998; Miche-.lozzi et al., 1998 .
The best evidence that particulate air pollutionis causally associated with human adverse healthimpacts is provided by the mass of existing epi-demiological data. A number of time-series stud-
Žies using various measures of PM TSP, PM ,102y.1PM , COH, BS, SO have been widely re-2.5 4
ported in the literature. A relatively large numberof these studies adopted PM as an indicator.10The severity of health disorders is directly related
1Abbre¨iations: TSP, total suspended particualtes; PM ,10PM-10 mm in aerodynamic diameter; PM , PM of the 2.52.5mm size and less; COH, coefficient of haze; SO2y, sulfate.4
to the concentration of particulates in ambientair, which is often expressed in dose]response
Ž .functions DRFs that correlate mortality andmorbidity outcomes of susceptible populationgroups with ambient concentrations of a certainair pollutant. DRFs can also be derived for lesserhealth impacts, such as respiratory hospitaladmissions, emergency admissions, bed disabilitydays, restricted activity days, asthma attack, acuterespiratory symptoms, chronic bronchitis, lowerrespiratory illness, and others. Table 1 representsa summary of health impact DRFs for PM ,10PM , BS, and TSP as derived from an array of2.5worldwide literature-based sources. Sensitivegroups that appear to be at a greater risk forparticulate air pollution include the elderly, thosewith pre-existing respiratory conditions and car-dio-pulmonary diseases such as asthma, smokers,and children.
Global annual deaths as a result of air pollu-tion are estimated at more than 2.7 million, with
Žcities accounting for approximately 33% WHO,.1997 . Approximately 1.4 billion urban residents,
mostly in developing countries, may be exposed toair with borderline or unacceptable levels of par-
Žticulates ALA, 1998; Gamble, 1998; AEAT,.1999 . This paper assesses the health impacts of
particulate air pollution in Lebanese urban areas.The economic benefits due to decreasing levels ofambient air particulates are estimated. Healthimpacts are expressed in both physical and mone-tary terms for saved statistical lives, and produc-tivity due to various morbidity endpoints. Thestudy concludes with a range of policy optionsand mitigation measures to minimize TSP levelsin the air.
2. TSP measurements in Lebanon
Air samples collected from several locations inŽ .Beirut Fig. 1 revealed that TSP concentration
ranges from 102 to 291 mgrm3 with an average3 Ž .value of 166 mgrm Fig. 2 . In addition to vehi-
cle-induced emissions, movement of motor vehi-cles on dusty roads and on-going constructionactivities are generally the major potential sourcesfor particulates. Anthropogenic sources coupled
( )M. El-Fadel, M. Massoud r The Science of the Total En¨ironment 257 2000 133]146 135
Table 1aŽ .Summary ranges of worldwide health impacts DRFs for PM , PM , BS, and TSP Vedal, 199710 2.5
Change in PM Percent increase Percent increase Morbidity typebŽ . Ž .concentration in mortality % in morbidity %
3Increase of 10 mgrm in PM 0.1]4.6 0.2]2.9 Pneumonia hospital admissions100.8]11.5 COPD hospital admissions0.2]6.4 Respiratory hospital admissions0.6]1.2 Cardiac hospital admissions0.4]6.0 Emergency cases of asthma0.3]0.4 Bronchitis hospital admissions1.1]24.9 LRI symptoms0.4]13.0 URI symptoms1.6]17.6 Cough symptoms
3Increase of 10 mgrm in PM 0.4]3.7 0.41]24.6 Respiratory hospital admissions2.53.7]20.9 Asthma hospital admissions
3Increase of 10 mgrm in BS NR 0.07]18.2 Respiratory hospital admissions0.3]5.3 Asthma hospital admissions1.2]16.5 COPD hospital admissions
3Increase of 100 mgrm in TSP 3.3]8.3 NR NR
aAbbre¨iations: COPD, chronic obstructive pulmonary disease; LRI, lower respiratory illness; URI, upper respiratory illness; NR,not reported.
b Morbidity } the incidence of respiratory andror cardiovascular symptoms and diseases.
with the nature of the dry Lebanese climate,particularly during the summer, results in high
Ž .dust levels in the atmosphere ERM, 1995 . Whilethe measurements serve to give a general indica-tion of particulates at various urban junctions, theclear implication is that anthropogenic activitiescontribute substantially to these levels.
2.1. Air quality standards
Based on clinical, toxicological and epidemio-logical evidence, guideline values of ambient par-ticulate concentrations were established by de-termining concentrations with the lowest observedadverse effect and adjusted by an arbitrary mar-gin of safety factor to allow for uncertainties inextrapolation. Generally, the most frequently usedreference guidelines for PM are those set by the
Ž .World Health Organization WHO , the Euro-Ž .pean Union EU , and the United States Environ-
Ž . Ž .mental Protection Agency USEPA Table 2 .While WHO guidelines are based on health con-siderations only, standards determined by the EU
and USEPA reflect the technological feasibility ofattainment as well. Many countries adopted theseguidelines or else they established their own am-bient air quality standards.
In Lebanon, ambient air quality standards havebeen proposed within the 1994 Urgent Draft Lawconcerning the determination of the specifica-tions and levels for the prevention of air, water
Ž .and soil pollution MOE, 1996 . However, it hasnot been approved to date. These standards seemto be political or administrative settings only.They do not provide a scientifically representative
Žpicture of particulate standards Staudte et al.,.1997 . The limit values are lower than some inter-
national standards and seem to be unreachableunder current emission practices where no con-trol is enforced.
3. Economic valuation of health impacts
Valuing the health impacts of air pollution is amajor problem facing policy makers. It comprisesthe actual identification and measurement of
( )M. El-Fadel, M. Massoud r The Science of the Total En¨ironment 257 2000 133]146136
Fig. 1. Air quality sampling locations in Beirut.
Fig. 2. Average particulates concentrations at various locations in Beirut.
( )M. El-Fadel, M. Massoud r The Science of the Total En¨ironment 257 2000 133]146 137
Table 2aŽ .Reference standards and guidelines of average ambient particulate concentration USEPA, 1996; WHO, 1997; RECCEE, 1998
3 3 bŽ . Ž .International Long-term mgrm Short-term mgrmstandard PM BS TSP PM BS TSP10 10
EU limit values NA 80 150 NA 250 300EU guide values NA 40]60 NA NA 100]150 NAUSEPA 50 NA 260 150 NA 75WHO guidelines NA 40]60 60]90 NA 100]150 150]230WHO guidelines NA 50 NA 70 125 120
for EuropeLebanon NA NA NA 80 NA 120
a NA, not available.b24 h.
health impacts and the estimation of monetaryvalues for associated premature mortality andmorbidity. Generally, health damage studiesproceed by establishing average levels of ambientconcentration of a pollutant and then relatingthose concentrations to health effects throughDRFs. Local or country-specific epidemiologicalstudies are the most appropriate indicators ofhealth impacts associated with air pollution in agiven region. These studies establish DRFs linkingenvironmental variables to observed health ef-fects. However, given the time and cost involvedin such studies as well as the problems encoun-tered with data availability, DRFs established inother countries can be adopted assuming thathuman reaction is similar in different locations.Consensus DRFs are possible if there are numer-ous reliable studies that appear to converge, asappears to be the case for PM. The next step is torelate the DRF to the population at risk and then
Žapply unit economic values USGAO, 1994;Calthrop and Maddison, 1996; Pearce and
.Crowards, 1996; Hartman et al., 1998 .Methods used in various studies to value health
costs associated with environmental pollution canŽ .generally be grouped into two categories: 1 those
that measure only the loss of direct income suchŽ . Ž .as lost wages or cost of illness COI ; and 2
approaches that attempt to capture the willing-Ž .ness to pay WTP individuals for avoiding or
reducing the risk of death or illness. The firstcategory does not include inconvenience, suffer-ing, losses in leisure and other less tangible im-pacts to the individuals well being. They may also
underestimate the health cost of people who arenot members of the labor force. Thus, thesemethods indicate only the lower bound of thesocial cost and understate the total cost to indi-
Ž .viduals Larssen et al., 1997 . A summary of vari-ous valuation methods of health effects resultingfrom air pollution is represented in Table 3.
4. Health assessment
The first step in a health assessment is toestablish a DRF between an increase in PM andadverse health effects. Considering that the datawere acquired from studies worldwide, severalassumptions were employed in this assessmentincluding:
v there is no threshold below which PM is10harmless or not a cause of mortality;
v there is no difference in susceptibility or expo-sure between different populations;
v reviewed studies are of similar quality andneed not be weighted for differences inmethodology or sample size;
v where an age-specific DRF is unavailable, theestimate for all age groups will be applied tothe baseline number of deaths in each agegroup; and
v the estimations are not restricted to a particu-lar or an average value but ranges of valuesare considered in order to ensure a broaderperspective of the subject.
( )M. El-Fadel, M. Massoud r The Science of the Total En¨ironment 257 2000 133]146138
Table 3aEconomic valuation methods for the health effects of environmental pollution
Valuation method Description
Mortality effectsHuman capital The human capital approach places a value on a premature death. It is based on the
economic productivity of an individual and values life according to the net presentvalue of productivity of an individual. As such, individuals are considered as units ofhuman capital that produce goods and services for society. The value of each unitof human capital is equivalent to the present value of the future output, in the formof earning, that might have been generated had the individual not died prematurely.In the absence of WTP estimates, this approach provides the best availablealternative for valuing loss in productivity.
WTP Unlike the human capital approach that measures tangible changes in productivity,the WTP captures intangible aspects. The WTP consists of asking people directlywhat they would be willing to pay for reduced risk of increased mortality.
Morbidity effectsCOI The COI approach applies mostly to morbidity and is consistent with or similar to the human
capital approach. The direct cost of morbidity can be divided into two categories:Ž . Ž .1 Medical expenditure for treating illness; and 2 lost wages during days spent in bed,days missed from work, and other days when activities are significantly restricted to illness.Most COI estimates fall short of being full estimates because of insufficientinformation. Even full COI estimates will understate total WTP because they do notinclude the value of avoiding the pain and suffering associated with the illness thatnecessitates hospital admission.
WTP The WTP approach is a more theoretically sound measure of morbidity effects. Itestimates what people would be willing to pay to avoid illness and can be inferred
Ž .using two different methods: 1 The averting behavior method, which is based on thenotion that the time and money spent by an individual to avoid exposure to airpollution or avoid illness is indicative of a lower bound value hershe attaches to
Ž .avoid it. 2 The contingent valuation method, which uses survey information todetermine what people are willing to pay to avoid a certain symptom or illness.Unit valuations that rely exclusively on the contingent valuation method includechronic bronchitis, respiratory related diseases, minor restricted activity days, andvisibility.
aAbbre¨iations: COI, cost of illness; WTP, willingness to pay.
4.1. Mortality characterization
Total lives saved due to a reduction in PM
concentration in the air is dependent on thebaseline number of deaths in the country, whichis calculated by multiplying the size of the ex-
Table 4Percent distribution of death in Lebanese households
a bSex Age group
0]9 10]19 20]39 40]59 60]69 )70 Unknown Total
Ž .Male 51 5.54 2.67 9.60 18.31 21.35 37.48 5.07 100.00Ž .Female 49 6.50 2.91 4.00 13.30 17.18 51.13 5.00 100.00
Ž .Total 100 5.93 2.77 7.31 16.27 19.66 43.03 5.03 100.00Total number of deaths 808 375 921 2131 2593 5935 677 13 440
a Ž .US Bureau of the Census 1999 .b Ž .MSA 1996 .
( )M. El-Fadel, M. Massoud r The Science of the Total En¨ironment 257 2000 133]146 139
Table 53Distribution of predicted lives saved per year due to 10 mgrm reduction in PM10
Sex Age group
0]9 10]19 20]39 40]59 60]69 )70 Unknown Total
Ž .Male 51 0]17 0]8 1]30 1]58 1]67 3]118 0]16 6]314Ž .Female 49 0]20 0]9 0]12 1]40 1]52 3]155 0]15 5]303
Ž .Total 100 0]37 0]17 1]42 2]98 2]119 6]273 0]31 11]617
posed population with the death rate. Based on adeath rate of 8.2 deathsr1000 person per yearŽ .MSA, 1996 and a total population correspond-ing to the Lebanese urban areas of approximately
Ž .1.64 million ERM, 1995 , the baseline number ofdeaths is calculated to be approximately 13 440.Multiplying the value of total deaths with thepercent distribution of death in Lebanese house-hold by age and sex, results in the total number of
Ž .deaths by age group Table 4 .The calculation of the number of lives saved by
age group involves multiplying the values of base-line number of deaths in each age group with thepercent change in the number of cases due to aspecific reduction in PM , which is assumed to10be 10 mgrm3 in this study. As mentioned previ-ously, where age-specific DRFs are not available,the estimate for all age groups will be applied tothe baseline number of deaths in each age group.Based on epidemiological time series studiesŽ .Vedal, 1997; Gamble, 1998 , the decrease inmortality due to 10 mgrm3 reduction in PM10ranges between 0.1 and 4.6%. Accordingly, thepredicted total number of lives saved in Lebanese
Ž .urban areas ranges between 11 and 617 Table 5with average values depicted in Fig. 3. Note thatwhile it is preferable to use DRFs from country-specific studies, these are not available for mostdeveloping countries.
4.2. Morbidity characterization
The assessment was performed on the effect ofdecreasing 10 mgrm3 of PM in the air with10pneumonia, COPD and emergency visits as end-points. Similar to mortality assessment, morbiditycalculations are performed in two steps. First, thetotal number of hospital admissions of each healthendpoint is determined by multiplying the total
number of hospital admissions in urban areaswith the percent of health endpoint hospitaladmissions. The data used in order to performthese calculations are summarized in Table 6.Second, multiplying the value obtained in the firststep by the percent decrease in health endpointhospital admissions due to a 10 mgrm3 reductionin PM provides the total number of cases10avoided. Accordingly, the ranges of pneumoniaand COPD cases avoided per 10 mgrm3 reduc-tion in PM are 15]214 and 35]498, respectively10Ž .Table 7 . Similarly the number of emergencyvisits avoided ranges between 609 and 25 578cases.
Considering that there are no adequate datafor all morbidity effects, morbidity DRFs per per-son due to a 10 mgrm3 reduction in PM can be10used to compute the morbidity cases avoided inurban areas. The assumption again is that suchDRFs can be transferred across societies. In thiscase, DRFs are multiplied by the total urban
Ž .population 1.64 million given that the impact ismeasured per person. Thus, Table 8 representsthe predicted values of morbidity effects.
Fig. 3. Predicted average number of lives saved due to 10mgrm3 reduction in PM .10
( )M. El-Fadel, M. Massoud r The Science of the Total En¨ironment 257 2000 133]146140
Table 6Data used to perform morbidity health assessment
Total hospital admissions per Lebanon 400 000ayear Beirut 133 000
Other urban areas 53 200
Type of hospital admission Emergency visits in Beirut 145 000bper year Emergency visits in other urban areas 58 000
Ž . Ž .a Respiratory and cardiac hospital admissions % 15Ž . Ž .b Respiratory admissions % of a 37Ž . Ž .c COPD admissions % of b 37Ž . Ž .d Pneumonia admissions % of b 63
Percent decrease in Pneumonia hospital admissions 0.2]2.93morbidity due to 10 mgrm COPD hospital admissions 0.8]11.5
creduction in PM Emergency visits 0.3]12.610
a Ž .Total number of hospital admissions in Lebanon is obtained from the Central Bank of Lebanon 1998 Annual Report,whereby one-third of the total hospital admissions occurred in Beirut. The hospital admissions in other urban areas is assumed tobe proportional to the ratio of inhabitants in Beirut and other urban areas.
b Total number of emergency room visits per day is extracted from a project conducted by senior medical students at theAmerican University of Beirut in 1993. The percentage of patients admitted to hospitals for respiratory and cardiovascular diseases
Žwas estimated by contacting three major hospitals in Beirut. Respiratory diseases include COPD bronchitis, chronic bronchitis,. Žemphysema, asthma, bronchiectasis, and chronic airway obstruction all pneumonias pneumococcal, other bacterial, infectious
.diseases, and bronchopneumonia , acute laryngitis and tracheitis, acute upper respiratory infections, and acute bronchitisŽ .Djoundourian et al., 1998 .
c Literature-based time series studies.
5. Economic assessment
5.1. Mortality calculations using human capitalapproach
Air quality-related mortality typically occurs ata late age due to a long period of chronic expo-sure to inferior air quality. Therefore, most stud-ies measure compensation of mortality risks forindividuals who are, on average, approximately 40years of age. In the present study, the total socio-economic cost due to premature mortality in ur-ban areas was predicted assuming that:
Table 73Morbidity cases avoided per year due to 10 mgrm reduction
in PM10
Endpoint Cases Casesoccurringryear avoidedryear
COPD 4334 31]441Pneumonia 7379 13]189Emergency visits 203 000 609]25 578
v Based on the per capita GDP in Lebanon forthe year 1998, the average Lebanese monthly
Žsalary is approximately US$400 Audi Bank,.1998 .
v Productivity age ranges between 25 and 69years.
v The two age groups 40]59 and 60]69 arerepresentative death ages with correspondingaverage lost productivity years of 20 and 5,respectively.
v The estimations are not restricted to a partic-ular or average value but ranges of values areconsidered in order to ensure a broader per-spective of the subject.
Based on the health assessment, the ranges oflives saved per 10 mgrm3 reduction in PM for10the age groups 40]59 and 60]69 are 2]10 and3]122, respectively. Multiplying average produc-tivity years by the average income yields the total
Ž .economic benefits Table 9 . Therefore, it is ben-eficial to control particulate emissions, as it con-stitutes a significant productivity source relative
( )M. El-Fadel, M. Massoud r The Science of the Total En¨ironment 257 2000 133]146 141
Table 83 Ž .Change in morbidity effects per 10 mgrm reduction in PM Pearce and Crowards, 199610
Endpoint Change Total cases avoided
Respiratory hospital 6.6]17.3 108]284admissionsr100 000
Emergency department 116.0]354.0 1902]5806visitsr100 000
aLower respiratory illnessr 0.010]0.024 4756]11 414asthmatic child
Asthma attacksr 0.33]1.96 541 200]3 214 400person
Respiratory symptomsr 0.8]2.56 1 312 000]4 198 400person
Chronic bronchitisr 30.0]93.0 492]1525100 000
Restricted activity 0.29]0.58 475 600]951 200daysrperson
a Ž . Ž .Taking 29% of the total urban population 1.64 million between 0 and 14 US Bureau of the Census, 1999 .
Ž .to country economic resources up to 1% of GDP .While the change in PM seems small in terms ofhealth risk, they signify a substantial number ofavoidable deaths due to the size of the populationimpacted.
5.2. Morbidity calculations using cost of illnessapproach
The predicted number of cases avoided due to10 mgrm3 reduction in PM multiplied by the10cost of the corresponding health endpoint resultsin the total economic benefits due to morbidity
Ž .avoidance Table 10 . Similar to mortality, mor-bidity calculations imply a considerable increasein economic benefits.
5.3. Mortality calculations using willingness to payapproach
Generally, WTP estimates are lacking in mostcountries. Consequently, the value of a statisticallife from several US studies is adjusted by the percapita GNP ratio which is approximately 0.1 based
Ž .on country-specific data World Bank, 1999 .Table 11 represents a summary of mortality valu-ation estimates based on the individual WTP forsmall reductions in mortality risk.
Each study provides an estimate of the meanWTP to avoid a statistical premature death. Mul-tiplying the per capita GNP ratio by the range of
Ž .WTP estimates 0.6]13.5 MUS$ , the value of astatistical life in Lebanon would range between0.06 and 1.35 MUS$. It is reasonable to obtainsuch a relatively high range considering that theWTP captures the value that an individual assignsto measurable and less tangible effects.
5.4. Morbidity calculations using willingness to payapproach
Willingness to pay to avoid a day of specificmorbidity endpoint has been estimated by only asmall number of studies. However, total benefitsassociated with any reduction in pollutant con-centrations is determined largely by the benefitassociated with the corresponding reduction inmortality risk because the dollar value associatedwith mortality is significantly greater than anyother valuation estimate. In the case of hospitaladmissions, the COI substitutes for the WTPestimates due to lack of information regardingthe latter. These COI estimates are likely tosubstantially understate the total WTP to avoidan illness or a particular hospital admission. Theaverage ratio of health care in Lebanon to that in
( )M. El-Fadel, M. Massoud r The Science of the Total En¨ironment 257 2000 133]146142
Table 93Mortality related economic benefits due to a 10 mgrm reduction in PM10
Age group likely Number of Average productivity Economic benefitŽ .to be affected lives saved years MUS$ryear
40]59 2]102 20 0.2]9.760]69 3]122 5 0.07]2.9Total 0.27]12.6
aAverage per case 0.055
aAverage total economic benefit divided by the average total number of lives saved.
Table 103Economic benefits due to reduced morbidity per 10 mgrm reduction in PM10
Endpoint Average stay Average cost Economic benefita aŽ . Ž . Ž .days US$rday MUS$ryear
COPD 6.6 261 0.06]0.9Pneumonia 10 207 0.03]0.4Emergency visit ] 76 0.05]1.9Total 0.14]3.2
a Ž .Based on survey data from the American University Hospital and insurance companies Djoundourian et al., 1998 .
the US is estimated at approximately 0.24. Thisratio was obtained by comparing the cost of COPD
Žand pneumonia in Lebanon Djoundourian et al.,. Ž .1998 and the US USEPA, 1997 . On the other
hand, the per capita GNP ratio of Lebanon andŽ .the US is 0.1 World Bank, 1997 , reflecting that
in Lebanon the cost of health care is relativelyvery expensive in comparison to income. Conse-quently, the COI estimates in the US are multi-plied by the ratio of health care in the two coun-tries, resulting in approximate estimates forLebanon. Similarly, in the case of work loss days,mild restricted activity days, chronic bronchitis,and respiratory-related illnesses or symptoms,which rely exclusively on the contingent valuationmethod, the per capita GNP ratio in the twocountries is used to obtain a value for LebanonŽ .Table 12 .
Table 11Ž .Summary of mortality valuation estimates USEPA, 1997
Study type ValuationrcaseaŽ .MUS$ryear
Labour market 0.6]13.5Contingent valuation 1.2]3.3
a1990 Dollar value.
5.5. Limitations and uncertainty
In evaluating epidemiological studies as a
Table 12Health effect unit valuation
Endpoint US valuation LebaneseaŽ .valuation US$ per case valuation
Ž .Us$ per case
bHospital admissionCOPD 8100 1944Pneumonia 7900 1896All respiratory 6100 1464
cRespiratory illness or symptomChronic bronchitis 260 000 26 000Acute bronchitis 45 5Acute asthma 32 3Acute respiratory symptoms 18 2Upper respiratory symptoms 19 2Lower respiratory symptoms 12 1
cRestricted acti ity dayWork loss days 83 8Mild restricted activity days 38 4
a Ž .1990 Dollar value USEPA, 1997 .b Lebanese valuation is obtained by multiplying the US
Ž .valuation by the health care ratio 0.24 .c Lebanese valuation is obtained by multiplying the US
Ž .valuation by the per capita GNP ratio 0.1 .
( )M. El-Fadel, M. Massoud r The Science of the Total En¨ironment 257 2000 133]146 143
whole, many issues arise, primarily associated withcausality. While the mortality effects attributed toPM have generally been consistent, disagreementremains as to whether these effects can be at-tributed entirely to fine particles. The fact thatnegative correlations between PM exposure anddifferent health endpoints have been indicated incertain studies raises uncertainty about the truedose]response relationship. Associations foundin a particular study may reflect chance, bias, orcause. In addition, epidemiological studies wereconducted in various cities under a broad rangeof environmental conditions, by a number of dif-
Žferent investigators Frey, 1998; Rabl and.Spadaro, 1999 . Real world exposures involve
combinations of potentially toxic materials thatmay be inhaled together or sequentially underdifferent conditions. Possible interactions thatmay result from the inhalation of a mixture oftoxicants can include simply additive, synergisticor antagonistic effects. Further uncertainties inthe evidence of a causal relationship in theobserved association between adverse health im-pacts and increase in airborne particles includeŽ .Larssen et al., 1997; Lipfert and Wyzga, 1997 :
v lack of an accepted biologically demonstratedmechanism;
v lack of quantitative support from experimen-tal animal andror human clinical studies;
v confounding, and difficulty of separating ef-fects of co-occurring pollutants;
v misclassification of personal exposure to am-bient particles;
v estimates relate to all PM regardless of10source; and
v differences in socio-demographic factors andthe health status of the exposed population.
The problems in extrapolating DRFs are alsoexacerbated by potential inaccuracy in estimatingeconomic health impacts. The economic costs ofmortality and morbidity were predicted on thebasis of epidemiological studies reviewed in theliterature. This is attributable to the fact thatLebanon, similar to many countries, lacks popula-tion-based vital and disease registries. The associ-
ated uncertainty includes both selection of scien-tific studies and statistical uncertainty from theoriginal studies. Similarly, range of estimates formonetized benefits is based on the quantifieduncertainty associated with the health effects esti-mates and the unit valuations applied to them.Moreover, due to the lack of affluence and publicperception, the WTP approach cannot be per-formed and thus, increasing the uncertainty bytransferring estimates across countries.
Uncertainty about the true dose]response rela-tionship of PM and health endpoints and theuncertainty regarding the extrapolation should notdelay the implementation of control measures,particularly that the true association may likely bestronger than that observed in epidemiologicalstudies. Moreover, even a small effect such asincrease in total mortality associated with a 10mgrm3 increase in daily PM would have a large10impact at the population level.
6. Air quality management
Particulate emission reduction will have multi-dimensional benefits considering the adverse ef-fect of particulate air pollution on health and theenvironment. In addition to the improved healthstatus of the population, a decrease in pollution
Žlevels will reduce work absence arising from.health problems , and the costs of health insur-
ance. Thus, new, stricter and enforced standardswill provide increased health protection due tosaved lives, lower hospital admissions and emer-gency room visits, reduced risk of symptoms asso-ciated with chronic bronchitis and asthma, andreduced risk of respiratory symptoms in children.In many developing countries, there is a lack ofinstitutional capacity and technical expertise toadequately address environmental issues. Newlegislation may fail to meet its objective unlessseveral combinations of measures are simultane-ously implemented alongside.
Proper air quality management requires an in-tegrated approach that encompasses coordinationand consensus building across sectors, identifica-tion of technically feasible abatement options,
( )M. El-Fadel, M. Massoud r The Science of the Total En¨ironment 257 2000 133]146144
and introduction of policies and instruments tosupport implementation. A clear set of objectivesand priorities for the environmental policy needto be determined and related to overall develop-ment and growth goals. Identifying a target groupof serious polluters that can be regulated effec-tively constitutes the basis of any environmentalmanagement program. Improving environmentalperformance of identified polluters requires theadoption and enforcement of updated environ-mental standards. These standards have to be ofrealistic nature in order to attain higher levels ofcompliance and polluters should be given ade-quate time before standard implementation is
Ž .effective Califano, 1996 .Incentives and economic instruments such as
charge systems, fiscal and financial instruments,property rights, market creation, and liability sys-tems are essential for medium term application ofa comprehensive environmental strategy. For in-stance, a wide range of market-based instrumentsare applicable at the level of the transportationsector such as taxes on emissions from fuel andprivate vehicle ownership. Moreover, measures tomitigate the negative effects of pollution mayfocus on separating pollution sources and recep-tors, reducing the pollution activity, and its char-acteristics, and controlling emissions with airquality control devices. Implementing alternativesof emissions reduction vary across pollutionsources. Mitigation measures that should beadopted to reduce air pollution, particularly PMinclude:
v Improving fuel quality or introducing fuel al-ternatives and compulsory vehicle testing andmaintenance at state controlled and certifiedgarages.
v Adopting proper construction measures suchas site enclosure, on-site mixing and unloadingoperations, adequate maintenance and repairof construction machinery, minimal trafficspeed on-site, and proper water spraying whennecessary.
v Installing proper end-of-pipe control tech-nologies at industrial facilities such as elec-trostatic precipitators and baghouses.
7. Summary and conclusions
Epidemiological studies conducted in severalcountries show consistent associations of expo-sure to ambient particulates with adverse healtheffects including increased mortality, hospitaliza-tion for respiratory or cardiovascular diseases,and respiratory symptoms and decreased lungfunction. Based on epidemiological time seriesstudies, dose]response functions were identifiedbetween an increase in PM and adverse healtheffects. Accordingly, mortality and morbidityeconomic valuations were performed forLebanese urban areas.
Overall, the assessment showed that potentialhealth and economic benefits of reducing PMconcentration in the air can be significant. Asummary of the average economic benefit for themain health endpoints is represented in Table 13.These benefits can be dominated by mortalityvaluation. While the number of mortality cases isrelatively small, the wide range of monetary valuecan result in large monetary benefits. The rangesare indicative of the uncertainties inherent insuch an exercise within a specific methodologyand across methodologies. Despite such limita-tions, the striking feature of these estimates isthat high benefits could result from reductions inconcentrations of PM in the air.
Implementation of monitoring and setting ofŽenforceable regulations i.e. ambient air quality
.and emission standards are necessary to initiatea comprehensive air quality management pro-gram. Monitoring activities and regulations mustbe developed, taking into consideration localsocio-economic and technical characteristics.Moreover, it is essential to develop a strategy thatcan be used to evaluate the willingness to pay torefine the economic valuation of exposure to PM.
Acknowledgements
The authors wish to express their gratitude toMr E. Bou Zeid and Mr H. Sbayte at the Depart-ment of Civil and Environmental Engineering,
( )M. El-Fadel, M. Massoud r The Science of the Total En¨ironment 257 2000 133]146 145
Table 133 aEconomic benefit due to 10 mgrm reduction in PM10
Ž .Endpoint Number of cases Total economic benefit MUS$ryearavoided COI WTP
b cMortality 11]617 0.27]12.6 3.5]157.9All COPD 31]441 0.06]0.9 0.98]13.9All pneumonia 13]189 0.03]0.4 0.05]0.7Emergency visits 609]25 578 0.05]1.9 NATotal 0.41]15.8 4.53]172.5
dPercent of GDP 0.003]0.1 0.03]1.06ePercent of adjusted GDP 0.03]1 0.3]10.6
aAbbre¨iations: COI, cost of illness; WTP, willingness to pay; NA, not available.b Human capital approach.c Determined by multiplying the value of a statistical life in Lebanon by the number of cases avoided between the age groups
40]59 and 60]69 in order to compare with the human capital approach value.d Ž .World Bank 1999 .eAdjusted GDP assuming that the construction and transportation sectors are the main sources of particulate emissions in urban
areas and accounting for sourcersector contribution to GDP and percent of urban population exposed as compared to total countrypopulation.
American University of Beirut, for conductingfield measurements used in this study. Specialthanks are extended to the United States Agencyfor International Development for its continuoussupport to the Environmental Engineering andScience programs at the American University ofBeirut.
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REGIONAL WORKSHOP REGIONAL WORKSHOP ONON
THE COST OF THE COST OF ENVIRONMENTAL ENVIRONMENTAL
DEGRADATION DEGRADATION METHODOLOGYMETHODOLOGY
Sessions 16 &17The Value of Life and Health
GROUP EXERCISES
Regional Training Workshop on the Cost of Environmental Degradation Methodology July 1‐5, 2008 Crowne Plaza Hotel, Beirut, Lebanon
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SESSIONS 15-16
GROUP EXERCISE 1
Impact of Water Quality on Health in Syria (World Bank, 2004)
Case description Syria is a relatively water scarce country. According to the World Bank statistics, renewable freshwater resources per capita are around 2,700 cubic meters. While this is higher than average for the countries of the Middle East and North Africa, it is less than a third of the world average. Moreover, water availability is unevenly distributed across the country in relation to population centers and irrigated agricultural land, resulting in local pressures on water resources, declining groundwater tables, and water quality problems. In terms of water and sanitation services, Syria reported that only 64 percent of the rural population had access to an improved water source in 2000. For urban areas, the water coverage rate was 94 percent, but water is being pumped from distant sources for some major urban centers due to local water quality and scarcity problems. For sanitation, nearly 20 percent of the rural population was reported as lacking access to hygienic sanitation facilities. The aim of this study is to estimates environmental damage costs associated with the health impacts of low quality potable water, inadequate sanitation and hygiene, and the economic impacts of water resources pollution. 1. Calculate the number of DALYs from child diarrheal disease deaths: Given: Live births per year = 401,000 thousand Child mortality = 20.2 per 1,000 live births Child diarrheal disease deaths = 13.0% of child mortality rate DALYs per child death = 35 discounted years of life lost
DALYs from child diarrheal disease deaths = __________________________________________
__________________________________________________________________________________
2. Calculate the number of DALYs from child diarrheal disease morbidity: Given: Child population (0-4 yrs) = 2.106 million 4.5% of children under 5 suffered from diarrhea in the last 24 hrs A severity weight of 0.2 assigned to diarrhea (DALYs lost from one day of diarrhea = 0.2/365) DALYs from child diarrheal disease morbidity = _______________________________________
__________________________________________________________________________________
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3. Calculate the monetary loss from the DALYs calculated above for both mortality and morbidity using the human capital approach. Perform the calculations at 50% and 100% of the GDP. Report the value in terms of SYP/year and in terms of % of GDP.
Given: GDP (2001) = 920 billion SYP GDP/capita (2001) = 55,000 SYP Mortality (based on 50% of GDP): _______________________________________________ SYP
___________________________________________ % GDP
(based on 100% of GDP) _______________________________________________ SYP
___________________________________________ % GDP
Morbidity (based on 50% of GDP): ______________________________________________ SYP
___________________________________________ % GDP
(based on 100% of GDP) _______________________________________________ SYP
___________________________________________ % GDP
Total: _______________________________________________________________________ SYP
___________________________________________________________________ % GDP
4. Calculate the Cost of Illness for severe cases of diarrhea treated in public and private clinics Given: Reported cases of diarrhea in public clinics = 130,000 Reported cases of diarrhea in private clinics = 390,000 Cost of doctor visit per treatment = 200 SYP/case Cost of medication per treatment = 600 SYP/case Assumed that 1 day is lost by caregiver per case of severe diarrhea Value of one day lost to caregiver = 175 SYP Cost of treating severe diarrhea =_________________________________________________ SYP
Cost of lost time due to care giving = ______________________________________________ SYP
Total cost of treating severe diarrhea cases= _______________________________________ SYP
Regional Training Workshop on the Cost of Environmental Degradation Methodology July 1‐5, 2008 Crowne Plaza Hotel, Beirut, Lebanon
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5. Calculate the Cost of Illness for mild cases of diarrhea treated by Oral Rehydration Therapy Given: 8.1 million mild cases of diarrhea per year 43.5 % of mild cases treated by ORT at home Unit cost of ORT treatment = 75 SYP/case Total cost of ORT treatment = ___________________________________________________ SYP 6. Calculate the Cost of Illness for mild cases of diarrhea treated by private doctors and with
medication Given: 8.1 million mild cases of diarrhea per year 50 % of mild cases treated by private doctor Cost of doctor visit per treatment = 200 SYP/case Cost of medication per treatment = 500 SYP/case Total cost of treatment by private doctors and medication = __________________________ SYP 7. Calculate the total COI in terms of SYP/year and in terms of % of GDP. Given: GDP (2001) = 920 billion SYP GDP/capita (2001) = 55,000 SYP Total cost of diarrheal illness = __________________________________________________ SYP
Total cost of diarrheal illness = _______________________________________________ % GDP
Regional Training Workshop on the Cost of Environmental Degradation Methodology July 1‐5, 2008 Crowne Plaza Hotel, Beirut, Lebanon
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GROUP EXERCISE 2
Impact of Water Quality on Health in Tunis and Sfax
(Sarraf et al., 2004)
Case description Sub-standard quality and an inadequate quantity of potable water for drinking and hygiene purposes, inadequate sanitation facilities and sanitary practices and inadequate personal, food and domestic hygiene have a cost to society. It is well known that these factors are associated with waterborne illnesses and mortality. The most common of these illnesses is diarrhea. The impact assessment presented below is linked mainly to mortality and morbidity in children younger than five years due to diarrheal diseases. The aim of this study is to estimates environmental damage costs associated with the health impacts of low quality potable water, inadequate sanitation and hygiene, and the economic impacts of water resources pollution. 1. Calculate the number of DALYs from child diarrheal disease deaths: Given: Annual child deaths from all causes= 5,392 per year Child diarrheal disease deaths = 10.0% of child mortality DALYs per child death = 35 discounted years of life lost DALYs from child diarrheal disease deaths = __________________________________________
__________________________________________________________________________________
2. Calculate the number of DALYs from child diarrheal disease morbidity: Given: Child population (0-14 yrs) = 2.9 million Diarrheal episode per child per year = 2.8 Average duration per episode = 96 hrs A severity weight of 0.2 assigned to diarrhea DALYs from child diarrheal disease morbidity = _______________________________________
__________________________________________________________________________________
__________________________________________________________________________________
Regional Training Workshop on the Cost of Environmental Degradation Methodology July 1‐5, 2008 Crowne Plaza Hotel, Beirut, Lebanon
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3. Calculate the monetary loss from the DALYs calculated above for both mortality and morbidity using the human capital approach. Perform the calculations at 50% and 100% of the GDP Report the value in terms of DT/year and in terms of % of GDP.
Given: GDP (2001) = 24 billion DT GDP/capita (2001) = 2,634 DT
Mortality (based on 50% of GDP): _______________________________________________ DT
___________________________________________ % GDP
(based on 100% of GDP) _______________________________________________ DT
___________________________________________ % GDP
Morbidity (based on 50% of GDP): _______________________________________________ DT
___________________________________________ % GDP
(based on 100% of GDP) _______________________________________________ DT
___________________________________________ % GDP
Total: _______________________________________________________________________ DT
___________________________________________________________________ % GDP
4. Calculate the Cost of Illness for mild cases of diarrhea treated by Oral Rehydration Therapy Given: 2.52 million mild cases of diarrhea per year 94.8 % of mild cases treated by ORT at home Unit cost of ORT treatment = 2 DT/case Total cost of ORT treatment = _________________________________________________DT
Regional Training Workshop on the Cost of Environmental Degradation Methodology July 1‐5, 2008 Crowne Plaza Hotel, Beirut, Lebanon
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5. Calculate the Cost of Illness for severe cases of diarrhea treated by private doctors and with medication
Given: Child population (0-4 yrs) = 0.9 million Percentage of severe diarrhea cases of children (0-4 yrs) = 5.75% If the average duration of a severe diarrhea case is 10 days, the number of cases per child per year is 1 (lower bound) If the average duration of a severe diarrhea case is 7 days, the number of cases per child per year is 1.5 (upper bound) Cost of doctor visit per treatment = 16 DT/case Cost of medication per treatment = 15.5 DT/case Assumed that 1 day is lost by caregiver per case of severe diarrhea Value of one day lost to caregiver = 11.5 DT Cost of treating severe diarrhea (include lower and upper bound) =________________________
_____________________________________________________________________________ DT
Cost of lost time due to care giving (include lower and upper bound) = =____________________
_____________________________________________________________________________ DT
Total cost of treating severe diarrhea cases (include lower and upper bound) =
_____________________________________________________________________________ DT
6. Calculate the total COI in terms of DT/year and in terms of % of GDP. Given: GDP (2001) = 24 billion DT GDP/capita (2001) = 2,634 DT Total cost of diarrheal illness = ___________________________________________________ DT
Total cost of diarrheal illness = _______________________________________________ % GDP
Regional Training Workshop on the Cost of Environmental Degradation Methodology July 1‐5, 2008 Crowne Plaza Hotel, Beirut, Lebanon
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SESSIONS 15-16
GROUP EXERCISE 3
Impact of Air Quality on Health in Syria (World Bank, 2004)
Case description Significant sources of air pollution in Syria include power stations, residential furnaces, industry and traffic. Excessive emissions from traffic are in part due to Syria’s ageing vehicle fleet that is 15 to 20 years old. There is substantial research evidence from around the world that outdoor urban air pollution has significant negative impacts on public health and results in premature deaths, bronchitis, respiratory disorders, and cancer. The air pollutant that has shown the strongest association with these health endpoints is particulate matter (PM), and especially fine particulates of less than 10 microns in diameter (PM10) or smaller. The gaseous pollutants (SO2, NOx, CO, and ozone) are generally not thought to be as damaging. This study therefore focuses on PM10, the smallest measure of PM for which data is available in Syria. The aim of this study is to estimates environmental damage costs associated with the health impacts of poor air quality, particularly elevated levels of PM10. There are three main steps to quantifying the health impacts from air pollution. Step 1. The pollutant needs to be identified and its concentration measured. Monitoring data from nine cities was used: Damascus, Aleppo, Homs, Hama, Lattakia, Dier-Azzour, Al-Raka, Al-Sweida, and Tartous. For each city, four to ten monitoring sites had data available from the Syrian Atomic Energy Commission (SAEC) and the Higher Institute of Applied Sciences and Technology (HIAST). All data is for 2001 with the exception of Lattakia and Hama where data was collected in 1994 and 1992 respectively. Step 2. Calculate the number of people exposed to the pollutant. City population estimates were taken from the Central Bureau of Statistics (2001). It was assumed that 100 percent of the city’s population is exposed to air pollution. Using expert advice from HIAST, the number of people living or spending most of their time near each monitoring site was estimated. The remainder of the city’s population not living near a monitoring site were assumed to be exposed to the average PM10 levels measured in the residential and background location monitoring sites. Some health outcomes affect only certain segments of the population such as adults or children. As only total population data is available at the city level the number of adults and children in each city had to be estimated. This was done by applying the percentage of Syria’s population that is under fifteen years of age to the city population data. A sample of Steps 1 and 2 for Damascus are presented in the table below.
Regional Training Workshop on the Cost of Environmental Degradation Methodology July 1‐5, 2008 Crowne Plaza Hotel, Beirut, Lebanon
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Monitoring site Commercial center
Major Roundabout
Heavy traffic & industrial workshop
Residential Residential Other pop
Crude death rate (per 1,000) 4.8 4.8 4.8 4.8 4.8 4.8
Annual average PM10 (μg/m3) 222 304 437 120 102 111
Exposed total population (millions) 0.15 0.02 0.08 0.35 0.28 1.83
Exposed adult population (≥15 yrs) (millions)
0.10 0.01 0.05 0.22 0.18 1.16
Exposed children population (≤14 yrs) (millions)
0.05 0.01 0.03 0.13 0.10 0.66
Step 3. Estimate the health impacts from this exposure based on epidemiological information. For this, the study relied upon scientific literature. Scientific studies estimate a dose-response coefficient linking PM10 concentrations with mortality and morbidity outcomes. The health endpoints considered as well as the dose-response coefficients are presented in the table below. The dose-response coefficients are taken from Lvovsky et al (2000). Health categories Units Impacts per 1μg/m3 Annual cases in Syria
Premature mortality % change in crude mortality rate 0.084 3,513
Chronic bronchitis Per 100,000 adults 3.06 16,970
Hospital admissions Per 100,000 population 1.2 10,454
Emergency room visits Per 100,000 population 23.54 205,073
Restricted activity days Per 100,000 adults 5,750 31,887,775
Lower respiratory illness in children Per 100,000 children 169 535,054
Respiratory symptoms Per 100,000 adults 18,300 101,486,312
Regional Training Workshop on the Cost of Environmental Degradation Methodology July 1‐5, 2008 Crowne Plaza Hotel, Beirut, Lebanon
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Step 4. Quantify the health impacts and estimate the value of this damage. 1. Calculate the number of DALYs from premature mortality and morbidity associated with elevated
PM levels by completing the table below (Fill in the grey cells). Given the number of DALYs per case adopted from Lvovsky et al. (2000) and the annual cases in Syria.
Health categories DALYs/ 10,000 cases Annual cases Syria Annual DALYs Syria
Premature mortality 100,000 3,513
Chronic bronchitis 12,037 16,970
Hospital admissions 264 10,454
Emergency room visits 3 205,073
Restricted activity days 3 31,887,775
Lower respiratory illness in children 3 535,054
Respiratory symptoms 3 101,486,312
Total DALYs lost per year
2. Calculate the monetary loss from the DALYs calculated above for both mortality and morbidity.
For mortality estimations, use the HCA approach for lower bound calculations and the WTP approach for upper bound calculations. For morbidity estimations, use only HCA approach:
Given: GDP/capita (2001) = 55,000 SYP GDP (2001) = 920 billion SYP WTP = 320,000 SYP/year (adopted from studies in Europe and US and then adjusted for GDP per capita differentials for Syria) Mortality (HCA-lower bound): __________________________________________________ SYP
Mortality: (WTP- upper bound): __________________________________________________ SYP
_____________________________ - ______________________ % GDP
Morbidity: ______________________ SYP
______________________ % GDP
Regional Training Workshop on the Cost of Environmental Degradation Methodology July 1‐5, 2008 Crowne Plaza Hotel, Beirut, Lebanon
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3. Calculate the Cost of Illness for health impacts caused by urban air pollution by completing the table below.
Given: Hospital admissions:
Two days of hospitalization Two work days lost
ER visits: Cost of ER visits Half a day of work lost
RADs: 1 work day lost per 10 RADs
Chronic bronchitis: Monthly doctor visit for 25% of individuals with CB Twice a year doctor visit for 65% of individuals with CB Emergency doctor visit once a year for 30% of individuals Average 6 day hospitalization for 2.5% of individuals 5 working days lost pr year for 35% of individuals Costs discounted at 10% for 15 years to reflect chronic nature of illness Data based on studies from US and Europe
Unit costs Chronic
bronchitis Hospital admissions
Emergency room visits
RAD Total cases
Annual cases 16,970 10,454 205,073 31,887,775 32,120,273
COI (million SYP/yr)
Hospitalization 2,000 SYP/day 43
Doctor visits 400 SYP/visit 244
ER visits 200 SYP/visit 9
Lost work days 200 SYP/day 50
Total COI (million SYP/yr) 345
4. Calculate the total COI in terms of SYP/year and in terms of % of GDP. Total COI = _____________________________________________________________ (SYP/yr)
______________________________________________________________ % GDP
Regional Training Workshop on the Cost of Environmental Degradation Methodology July 1‐5, 2008 Crowne Plaza Hotel, Beirut, Lebanon
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GROUP EXERCISE 4
Impact of Air Quality on Health in Tunis and Sfax (Sarraf et al., 2004)
Case description There is substantial research evidence from around the world that outdoor/urban air pollution have significant negative impacts on public health and result in premature deaths, chronic bronchitis, respiratory disorders, and even cancer. The most significant air pollutant in terms of impacts on health is most commonly found to be particulate matter, especially fine particulates (PM10 or smaller). No study that statistically links urban air pollution and health, based on local health and ambient air monitoring data, has been carried out in Tunisia. However, applying findings from international studies to the local air pollution situation in Tunisia can produce an estimate. The aim of this study is to estimates environmental damage costs associated with the health impacts of poor air quality, particularly elevated levels of PM10. There are three main steps to quantifying the health impacts from air pollution. Step 1. The pollutant needs to be identified and its concentration measured. The annual average of PM10 considered, is a result of monthly averages of 9 months recorded by CITET (Centre International des Technologies de l’Environnement de Tunis) and reported in 1998. Step 2. Calculate the number of people exposed to the pollutant. City population estimates were taken from WDI, World Bank (2001). It was assumed that 80% of the population is exposed to air pollution. The population was broken-down by age-groups applying percentages of Tunisia’s population. A sample of Steps 1 and 2 for Tunis and Sfax are presented in the table below.
Parameter Tunis Sfax
Crude death rate (per 1,000) 5.6 5.6
Annual average PM10 (μg/m3) 65 65
Exposed total population (80% of Total population) (millions) 1.3 0.6
Exposed adult population (≥15 yrs) (millions) 0.9 0.4
Exposed children population (≤14 yrs) (millions) 0.4 0.2
Step 3. Estimate the health impacts from this exposure based on epidemiological information. For this, the study relied upon scientific literature. Scientific studies estimate a dose-response coefficient linking PM10 concentrations with mortality and morbidity outcomes. The health endpoints considered as well as the dose-response coefficients are presented in the table below. The dose-response coefficients are taken from Lvovsky et al. (2000).
Regional Training Workshop on the Cost of Environmental Degradation Methodology July 1‐5, 2008 Crowne Plaza Hotel, Beirut, Lebanon
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Health categories Units Impacts per 1μg/m3 DALYs per 10,000 cases
Premature mortality % change in crude mortality rate 0.084 100,000
Chronic bronchitis Per 100,000 adults 3.06 12,037
Hospital admissions Per 100,000 population 1.2 264
Emergency room visits Per 100,000 population 23.54 3
Restricted activity days Per 100,000 adults 5,750 3
Lower respiratory illness in children Per 100,000 children 169 3
Respiratory symptoms Per 100,000 adults 18,300 3
Step 4. Quantify the health impacts and estimate the value of this damage. 1. Calculate the number of DALYs from premature mortality and morbidity associated with elevated
PM levels by completing the table below (Fill in the grey cells). Given the number of DALYs per case adopted from Lvovsky et al. (2000) and the annual cases in Tunis and Sfax.
Health categories DALYs per 10,000 cases
Cases in Tunis
Cases in Sfax
Total cases Tunis & Sfax
Annual DALYs Tunis & Sfax
Premature mortality DALY 100,000 391.4 195.7
Chronic bronchitis 12,037 1,771 885
Hospital admissions 264 998 499
Emergency room visits 3 19,585 9,793
Restricted activity days 3 3,327,627 1,663,814
Lower respiratory illness in
children
3 42,805 21,402
Respiratory symptoms 3 10,590,535 5,295,267
Morbidity DALY
Total DALYs lost per year
2. Calculate the monetary loss from the DALYs calculated above for both mortality and morbidity.
For mortality estimations, use the HCA approach for lower bound calculations and the WTP approach for upper bound calculations. For morbidity estimations, use only the HCA approach:
Regional Training Workshop on the Cost of Environmental Degradation Methodology July 1‐5, 2008 Crowne Plaza Hotel, Beirut, Lebanon
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Given: GDP (2001) = 24 billion DT GDP/capita (2001) = 2,634 DT WTP = 6,440 DT (adopted from studies in Europe and US and then adjusted for GDP per capita differentials for Tunisia) Mortality (lower bound): ________________________________________________________ DT
Mortality: (upper bound): ________________________________________________________ DT
_________________________ - _______________________ % GDP
Morbidity: _________________________________________________________________ DT
_______________________________________________________________ % GDP
3. Calculate the Cost of Illness for health impacts caused by urban air pollution by completing the
table below. Given: Treatment costs used are adopted from averages in Lebanon and Morocco and then adjusted for GDP per capita differentials for Tunisia Hospital admissions
Two days of hospitalization Two work days lost
Emergency Room (ER) visit estimation is based on: Cost of consultation Half a day of work lost
Restricted Activity Days (RADs) 1 work day lost per 10 RADs
Chronic bronchitis Average 6 day hospitalization for 2.5% of patients Monthly doctor visit for 25% of patients Twice a year visit for 65% of patients Emergency doctor visit once a year for 30% of patients 5 working days lost per year for 35% of patients Costs discounted at a rate of 10% for 15 years to reflect chronic nature of illness Data based on studies from US and Europe
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Unit costs Chronic
bronchitis Hospital admissions
Emergency room visits
RAD Total cases
Annual cases 2,656 1,498 29,378 4,991,441 32,120,273
Annual COI (million DT / year)
Hospitalization DT 250 / day 0.8
Doctor visits DT 25 / visit 2.4
ER visits DT 65 / visit 0.4
Lost work days DT 30 / day 1.2
Total COI (million DT/yr) 4.8
4. Calculate the total COI in terms of DT/year and in terms of % of GDP. Total COI = _________________________________________________________________ (DT/yr)
_________________________________________________________________ % GDP
REGIONAL WORKSHOP ONREGIONAL WORKSHOP ON
THE COST OF ENVIRONMENTAL THE COST OF ENVIRONMENTAL DEGRADATION METHODOLOGYDEGRADATION METHODOLOGY
Sessions 16 &17The Value of Life and HealthThe Value of Life and Health
GROUP EXERCISESGROUP EXERCISES
CASECASE--STUDIESSTUDIES
1. Impact of water quality on health in Syria2. Impact of urban air quality on health in Syria3. Impact of water quality on health in Tunis and
Sfax4. Impact of urban air quality on health in Tunis
and Sfax5. Impact of water quality on health in Egypt6. Impact of urban air quality on health in Egypt7. Impact of water quality on health in Morocco8. Impact of urban air quality on health in Morocco9. Impact of water quality on health in Lebanon10. Impact of urban air quality on health in Lebanon
CaseCase--study 1:study 1:Impact of Water Quality on Impact of Water Quality on
Health in SyriaHealth in Syria
Value of Life and HealthValue of Life and HealthCaseCase--study 1:study 1: Impact of Water Quality on Health Impact of Water Quality on Health
in Syriain Syria
Background
• Syria is water scarce• Renewable freshwater
resources = 2,700 m3
• Less than a third of the world average
• Water availability unevenly distributed
• Local pressure on water resources
• Declining groundwater tables
• Water quality degradation
According to WHO/UNICEF (2000)•64 % of rural population had access to an improved water source•94 % of urban areas covered with water supply network•20 % of rural population lacking access to hygienic sanitation facilities
Value of Life and Health Value of Life and Health CCasease--study 1:study 1: Impact of Water Quality on Health Impact of Water Quality on Health
in Syriain SyriaBackground
The lack of safe drinking waterInadequate hygiene and sanitation
water pollution
Impact on human health and quality of life through diarrheal diseases (mainly children)
Cost to societyCost to society
Value of Life and Health Value of Life and Health CCasease--study 1:study 1: Impact of Water Quality on Health Impact of Water Quality on Health
in Syriain SyriaMethodologyMortality•DALY/ HCA approach
Morbidity•DALY/ HCA approach
+•Cost of illness approach
• Severe diarrhea• Medication costs• Lost time for caregivers
• Mild diarrhea• Medication costs
• Oral rehydrationtherapy
• Private doctor visits
Value of Life and Health Value of Life and Health CaseCase--study 1:study 1: Impact of Water Quality on Health Impact of Water Quality on Health
in Syriain SyriaResults• DALYs- Mortality
– 13% of all deaths in children under five attributable to diarrheal disease (MoH)
– Death of a child under 5 represents a loss of 35 DALYs (Global Burden of Disease)
Parameter ValueChild population (0-4 yrs) 2.106 millionLive births per year 401 thousandChild mortality 20.2 per 1,000 live birthsAnnual child deaths (all causes) 8,100 per yearChild diarrheal disease deaths 13.0% of child mortality rateChild diarrheal disease mortality rate 2.6 per 1,000Annual child diarrheal disease deaths 1053DALYs per child death 35 discounted years of life lostDALYs from child diarrheal disease deaths 36,856
Value of Life and Health Value of Life and Health CaseCase--study 1:study 1: Impact of Water Quality on Health Impact of Water Quality on Health
in Syriain SyriaResults• DALYs – Morbidity
– Based on household surveys by MoH• 8.6 million cases of diarrhea per year• 4.5% of children under 5 suffered from diarrhea in the last 24 hrs
– A severity weight of 0.2 assigned to diarrhea• DALYs lost from one day of diarrhea = 0.2/365
Parameter ValueChild population (0-4 yrs) 2.106 millionDiarrheal prevalence in children (0-4 yrs) in last 24 hrs 4.5%Total diarrhea days per year 34.6 millionDALY (disability severity weight) 0.2DALYs from child diarrheal disease morbidity 18, 954 per year
Value of Life and Health Value of Life and Health CaseCase--study 1:study 1: Impact of Water Quality on Health Impact of Water Quality on Health
in Syriain Syria
Parameter ValueMortality
Total number of DALYs 36,900Price per DALY 27,500-55,000 SYP/yrMonetary loss 1,015 - 2,030 million SYP/yr% of GDP 0.11 – 0.22 %
MorbidityTotal number of DALYs 19,000Price per DALY 27,500-55,000 SP/yrMonetary loss 523 – 1,045 million SYP/yr% of GDP 0.06 – 0.11 %
Value of Life and Health Value of Life and Health CaseCase--study 1:study 1: Impact of Water Quality on Health Impact of Water Quality on Health
in Syriain SyriaResults• COI- Severe cases of diarrhea
– Severe cases often treated in health clinic– 130,000 diarrhea cases per year in public clinics (MoH)– Ratio of private to public clinics according to NEAP = 3:1– Assumed that 1 day is lost by caregiver per case of severe diarrheaParameter ValueReported cases of diarrhea, public 130,000Reported cases of diarrhea, private clinics 390,000Total cases of reported diarrhea 520,000Cost of doctor visit per treatment 200 SYPCost of medication per treatment 600 SYPTotal cost of treatment 800 SYPCost of treating severe diarrhea 416 million SYPValue of one day lost to caregiver 175 SYPCost of lost time due to care giving 91 million SYP
Value of Life and Health Value of Life and Health CaseCase--study 1:study 1: Impact of Water Quality on Health Impact of Water Quality on Health
in Syriain Syria
Results• COI- Mild cases of diarrhea treated by Oral
Rehydration Therapy– 8.6 million cases -0.5 million severe cases = 8.1
million mild cases of diarrhea per year– 44 % of mild cases treated by ORT at home– Average length of diarrheal episode = 4 days
Parameter ValueNumber of diarrhea cases per year in children (0-4 yrs) 8.1 millionPercent of cases treated with ORT 43.5 %Cases treated with ORT 3.53 millionUnit cost of ORT treatment 75 SYP/caseTotal cost of ORT treatment 264 million SYP
Value of Life and Health Value of Life and Health CaseCase--study 1:study 1: Impact of Water Quality on Health Impact of Water Quality on Health
in Syriain SyriaResults• COI- Mild cases of diarrhea treated by private
doctors and with medication
Total COI = 3.6 billion SYP/year= 0.4% of GDP
Parameter ValueNumber of diarrhea cases per year in children 0-4 8.1 millionPercent of cases treated by private doctors 50%Cost of doctor visit per treatment 200 SYPCost of medication per treatment 500 SYPTotal cost of treatment 700 SYPCost of treating non-severe diarrhea 2,835 million SYP
CaseCase--study 2:study 2:Impact of Urban Air Quality Impact of Urban Air Quality
on Health in Syriaon Health in Syria
Value of Life and Health Value of Life and Health CaseCase--study 2:study 2: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in SyriaHealth in SyriaBackground• Sources of air pollution in Syria
– Power stations– Residential furnaces– Industry– Ageing vehicle fleet that is 15-20 yrs old
Value of Life and Health Value of Life and Health CaseCase--study 2:study 2: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in SyriaHealth in Syria
Methodology
Value of Life and Health Value of Life and Health CaseCase--study 2:study 2: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in SyriaHealth in SyriaMethodology- Identify pollutant and measure its
concentration• Monitoring data from 9 cities used
• 4-10 monitoring sites per city from– Syrian Atomic Energy Commission– Higher Institute of Applied Science and Technology
• Data for 2001 except Lattakia (1994) and Hama (1992)
• In all cities, one monitoring station collected both PM10and TSP– PM10 data inferred from remaining monitoring data by
calculating the ratio PM10:TSP
-Damascus -Aleppo -Tartous-Homs -Hama -Al-Sweida-Lattakia -Deir-Azzour -Al-Raka
Value of Life and Health Value of Life and Health CaseCase--study 2:study 2: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in SyriaHealth in SyriaMethodology- Determine exposed population• City population estimates taken from Central Bureau of
Statistics (2001)
• Assumed that 100% of the city’s population exposed to air pollution
• Using expert advice from HIAST– Number of people living or spending most of their time near each
monitoring site estimated– Remaining population assumed to be exposed to average PM10
levels measured in residential and background locations
• Population broken-down by age-groups applying percentages of Syria’s population
Value of Life and Health Value of Life and Health CaseCase--study 2:study 2: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in SyriaHealth in Syria
Methodology-Sample for Damascus
Monitoring site Commercial center
Major Roundabout
Heavy traffic & industrial workshop
Residential Residential Other pop
Crude death rate (per 1,000) 4.8 4.8 4.8 4.8 4.8 4.8
Annual average PM10 (μg/m3) 222 304 437 120 102 111
Exposed total population (millions)
0.15 0.02 0.08 0.35 0.28 1.83
Exposed adult population (≥15 yrs) (millions)
0.10 0.01 0.05 0.22 0.18 1.16
Exposed children population (≤14 yrs) (millions)
0.05 0.01 0.03 0.13 0.10 0.66
Value of Life and Health Value of Life and Health CaseCase--study 2:study 2: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in SyriaHealth in Syria
Methodology- Estimate health impacts from exposure
• Relied on dose-response coefficients reported in the literature by Lvovsky et al. (2000)
• Limitation: reported DRR from developed countries
Health categories Units Impacts per 1μg/m3
Premature mortality % change in crude mortality rate 0.084Chronic bronchitis Per 100,000 adults 3.06Hospital admissions Per 100,000 population 1.2Emergency room visits Per 100,000 population 23.54Restricted activity days Per 100,000 adults 5,750Lower respiratory illness in children Per 100,000 children 169Respiratory symptoms Per 100,000 adults 18,300
Value of Life and Health Value of Life and Health CaseCase--study 2:study 2: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in SyriaHealth in Syria
Mortality•DALY/ HCA approach•DALY/ WTP approach
Morbidity•DALY/ HCA approach
+•Cost of illness approach
• Chronic bronchitis• Hospital admissions• Emergency room visits• Restricted activity days
Methodology- Valuate health impacts from exposure
Value of Life and Health Value of Life and Health CaseCase--study 2:study 2: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in SyriaHealth in SyriaResults- Mortality and Morbidity• Health outcomes converted to DALYs• DALYs adopted from Lvovsky et al. (2000)• Data calculated per city and then aggregated
Health categories DALYs per 10,000 cases
Annual cases Syria
Annual DALYsSyria
Premature mortality 100,000 3,513 35,126Chronic bronchitis 12,037 16,970 20,427Hospital admissions 264 10,454 276Emergency room visits 3 205,073 62Restricted activity days 3 31,887,775 9,566Lower respiratory illness in children 3 535,054 161Respiratory symptoms 3 101,486,312 30,446Total DALYs lost per year 96,062
Value of Life and Health Value of Life and Health CaseCase--study 2:study 2: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in SyriaHealth in SyriaResults• DALYs –Valuation
– Mortality• Low estimate at
GDP/capita (2001) = 55,000 SYP
• High estimate at WTP adopted from studies in Europe and US and then adjusted for GDP per capita differentials for Syria
• Adjusted WTP then modified to reflect approximate number of DALYs lost due to air pollution relative to DALYslost in WTP studies
– 10 DALYs per case usually considered for air pollution
– Morbidity• Low estimate at
GDP/capita (2001)= 55,000 SYP
Parameter ValueMortality
Total number of DALYs 35,100Price per DALY 55,000 – 320,000 SYP/yrMonetary loss 1,931 – 11,232 million
SYP/yr% of GDP 0.21 – 1.22 %
MorbidityTotal number of DALYs 60,900Price per DALY 55,000 SP/yrMonetary loss 3,350 million SYP/yr% of GDP 0.36 %
Value of Life and Health Value of Life and Health CaseCase--study 2:study 2: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in SyriaHealth in SyriaResults- COI approach- Basis for cost estimates• Chronic bronchitis
– Monthly doctor visit for 25% of individuals with CB– Twice a year visit for 65% of individuals with CB– Emergency doctor visit once a year for 30% of individuals– Average 6 day hospitalization for 2.5% of individuals– 5 working days lost pr year for 35% of individuals– Costs discounted at 10% for 15 years to reflect chronic nature of illness– Data based on studies from US and Europe
• Hospital admissions– Two days of hospitalization– Two work days lost
• ER visits– Cost of ER visits– Half a day of work lost
• RADs– 1 work day lost per 10 RADs
Value of Life and Health Value of Life and Health CaseCase--study 2:study 2: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in SyriaHealth in Syria
Results- COI approach
Total COI = 1.1 billion SYP/year= 0.12% of GDP
Unit costs Chronic bronchitis
Hospital admissions
Emergency room visits
RAD Total cases
Annual cases 16,970 10,454 205,073 31,887,775 32,120,273
COI (million SYP/yr)Hospitalization 2,000 SYP/day 43 42
Doctor visits 400 SYP/visit 244
ER visits 200 SYP/visit 9 41
Lost work days 200 SYP/day 50 4 21 638
Total COI (million SYP/yr) 345 46 62 638 1,090Cost per case (SYP) 20,331 4,400 300 20 33.9
CaseCase--study 3:study 3:Impact of Water Quality on Impact of Water Quality on
Health in Tunis and Health in Tunis and SfaxSfax
Value of Life and Health Value of Life and Health CaseCase--study 3:study 3: Impact of Water Quality on Health Impact of Water Quality on Health
in Tunis and in Tunis and SfaxSfaxBackgroundThe lack of: safe drinking water
& sanitation& water pollution
Impact on human health and quality of life through diarrheal diseases (mainly children)
Mortality and MorbidityMortality and Morbidity
Value of Life and Health Value of Life and Health CCasease--study 3:study 3: Impact of Water Quality on Health Impact of Water Quality on Health
in Tunis and in Tunis and SfaxSfaxMethodologyMortality•DALY/ HCA approach
Morbidity•DALY/ HCA approach
+•Cost of illness approach
• Severe diarrhea• Medication costs• Private doctor visits• Lost time for caregivers
• Mild diarrhea• Oral rehydration therapy
Value of Life and Health Value of Life and Health CaseCase--study 3:study 3: Impact of Water Quality on Health Impact of Water Quality on Health
in Tunis and in Tunis and SfaxSfaxResults• DALYs- Mortality
– 10% of all deaths in children under five attributable to diarrheal disease – Death of a child under 5 represents a loss of 35 DALYs (Global Burden
of Disease)
Parameter ValueChild population (0-4 yrs) 0.9 millionChild mortality 30 per 1,000 live birthsAnnual child deaths (all causes) 5,392 per yearChild diarrheal disease deaths 10.0% of child mortality rateChild diarrheal disease mortality rate 2.9 per 1,000Annual child diarrheal disease deaths 539DALYs per child death 35 discounted years of life lostDALYs from child diarrheal disease deaths 18,865
Value of Life and Health Value of Life and Health CaseCase--study 3:study 3: Impact of Water Quality on Health Impact of Water Quality on Health
in Tunis and in Tunis and SfaxSfaxResults• DALYs – Morbidity
– A severity weight of 0.2 assigned to diarrhea• DALYs lost from one day of diarrhea = 0.2/365
Parameter ValueChild population (0-14 yrs) 2.9 millionDiarrheal episode per child per year 2.8Total number of episodes per year 8.12 millionAverage duration per episode 96 hrsTotal diarrhea hrs per year 780 millionTotal diarrhea duration in years per year 89,000DALY (disability severity weight) 0.2DALYs from child diarrheal disease morbidity 17,808 per year
Value of Life and Health Value of Life and Health CaseCase--study 3:study 3: Impact of Water Quality on Health Impact of Water Quality on Health
in Tunis and in Tunis and SfaxSfax
Parameter ValueMortality
Total number of DALYs
18,865Price per DALY 1,315-2,630 DT/yrMonetary loss 24.81 – 49.61 million DT/yr% of GDP 0.10 – 0.20 %
MorbidityTotal number of
DALYs17,808
Price per DALY 1,315-2,630 DT/yrMonetary loss 23.41 – 46.83 million DT/yr% of GDP 0.10 – 0.20 %
Value of Life and Health Value of Life and Health CaseCase--study 3:study 3: Impact of Water Quality on Health Impact of Water Quality on Health
in Tunis and in Tunis and SfaxSfaxResults• COI- Severe cases of diarrhea
– If the average duration of a severe diarrhea case is 10 days, the number of cases per child per year is 1 (lower bound)
– If the average duration of a severe diarrhea case is 7 days, the number of cases per child per year is 1.5 (upper bound)
– Assumed that 1 day is lost by caregiver per case of severe diarrhea
Parameter ValueChild population (0-4 yrs) 0.9 millionPercentage of severe diarrhea cases of children < 5 5.75Number of severe diarrhea cases per year (lower bound) 0.9 millionNumber of severe diarrhea cases per year (lower bound) 1.3 millionCost of doctor visit per treatment 16 DTCost of medication per treatment 15.5 DTTotal cost of treatment 31.5 DTCost of treating severe diarrhea 28.31- 40.95 million DTValue of one day lost to caregiver 11.5 DTCost of lost time due to care giving 10.3 - 13.93 million DT
Value of Life and Health Value of Life and Health CaseCase--study 3:study 3: Impact of Water Quality on Health Impact of Water Quality on Health
in Tunis and in Tunis and SfaxSfaxResults• COI- Mild cases of diarrhea treated by Oral
Rehydration Therapy– 94.8 % of mild cases treated by ORT at home
Total COI = 43.4 – 59.66 million DT/year= 0.16-0.25 % of GDP
Parameter ValueNumber of diarrhea cases per year in children (0-4 yrs) 2.52 millionPercent of cases treated with ORT 94.8 %Cases treated with ORT 2.4 millionUnit cost of ORT treatment 2 DT/caseTotal cost of ORT treatment 4.78 million DT
CaseCase--study 4:study 4:Impact of Urban Air Quality Impact of Urban Air Quality on Health in Tunis and on Health in Tunis and SfaxSfax
Value of Life and Health Value of Life and Health CaseCase--study 4:study 4: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in Tunis and Health in Tunis and SfaxSfaxBackground
• No air pollution impact studies has been undertaken in Tunisia. The present study considers international studies results adjusted for Tunisian conditions.
Value of Life and Health Value of Life and Health CaseCase--study 4:study 4: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in Tunis and Health in Tunis and SfaxSfaxBackground
• The annual average of PM10 is a result of monthly averages of 9 months recorded by CITET (Centre International des Technologies de l’Environnement de Tunis) and reported in 1998
Tunis Sfax
Crude death rate (per 1,000) 5.6 5.6
Annual average PM10 (μg/m3) 65 65
Exposed total population (80% of Total population) (millions) 1.3 0.6
Exposed adult population (≥15 yrs) (millions) 0.9 0.4
Exposed children population (≤14 yrs) (millions) 0.4 0.2
Value of Life and Health Value of Life and Health CaseCase--study 4:study 4: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in Tunis and Health in Tunis and SfaxSfax
Mortality•DALY/ HCA approach•DALY/ WTP approach
Morbidity•DALY/ HCA approach
+•Cost of illness approach
• Chronic bronchitis• Hospital admissions• Emergency room visits• Restricted activity days
Methodology- Valuate health impacts from exposure
Value of Life and Health Value of Life and Health CaseCase--study 4:study 4: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in Tunis and Health in Tunis and SfaxSfaxThe Results• Estimate the DALY per Health Category
• DALY estimations relied on dose-response coefficients reported in international studies
Health categories Units Impacts per 1μg/m3
DALYs per 10,000 cases
Premature mortality % change in crude mortality rate 0.084 100,000
Chronic bronchitis Per 100,000 adults 3.06 12,037
Hospital admissions Per 100,000 population 1.2 264
Emergency room visits Per 100,000 population 23.54 3
Restricted activity days Per 100,000 adults 5,750 3
Lower respiratory illness in children Per 100,000 children 169 3
Respiratory symptoms Per 100,000 adults 18,300 3
Value of Life and Health Value of Life and Health CaseCase--study 4:study 4: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in Tunis and Health in Tunis and SfaxSfaxThe Results • Calculate the number of DALYs lost due to urban air
pollutionHealth categories DALYs per
10,000 cases
Cases in Tunis
Cases in Sfax
Total cases Tunis & Sfax
Annual DALYsTunis & Sfax
Premature mortality DALY 100,000 391.4 195.7 587.1 5,871Chronic bronchitis 12,037 1,771 885 2,656 3,197
Hospital admissions 264 998 499 1,497 40
Emergency room visits 3 19,585 9,793 29,378 9
Restricted activity days 3 3,327,627 1,663,814 4,991,441 1,497
Lower respiratory illness in children 3 42,805 21,402 64,207 19
Respiratory symptoms 3 10,590,535 5,295,267 15,885,802 4,766
Morbidity DALY 9,528
Total Total DALYsDALYs lost per yearlost per year 15,39915,399
Value of Life and Health Value of Life and Health CaseCase--study 4:study 4: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in Tunis and Health in Tunis and SfaxSfaxThe Results • Valuate the lost DALYs
–Low estimate at GDP/capita (1999) = 2,630 DT
–High estimate at WTP adopted from studies in US and then adjusted for GDP per capita differentials for Tunisia = 6,440 DT
Lower Bound
Upper Bound
Total DALYs lost per year 15,399
Price per DALY (DT)GDP / capita WTP
2,630 6,440Total Annual monetary loss (million DT)
40.5 99.2
The Average Annual DALY Losses Due to Urban The Average Annual DALY Losses Due to Urban Pollution represent 0.2Pollution represent 0.2--0.4% of the GDP0.4% of the GDP
Value of Life and Health Value of Life and Health CaseCase--study 4:study 4: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in Tunis and Health in Tunis and SfaxSfaxThe Results Cost of Illness (COI) assumptions
• Treatment costs used are adopted from averages in Lebanon and Morocco and then adjusted for GDP per capita differentials for Tunisia
• Chronic bronchitis– Average 6 day hospitalization for 2.5% of patients– Monthly doctor visit for 25% of patients– Twice a year visit for 65% of patients– Emergency doctor visit once a year for 30% of patients– 5 working days lost per year for 35% of patients– Costs discounted at a rate of 10% for 15 years to reflect chronic nature of illness– Data based on studies from US and Europe
• Hospital admissions– Two days of hospitalization– Two work days lost
• Emergency Room (ER) visit estimation is based on: – Cost of consultation– Half a day of work lost
• Restricted Activity Days (RADs)– 1 work day lost per 10 RADs
Value of Life and Health Value of Life and Health CaseCase--study 4:study 4: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in Tunis and Health in Tunis and SfaxSfax
Unit costs Chronic bronchitis
Hospital admissions ER visits RADs Total
Annual cases 2,656 1,498 29,378 4,991,441
Annual COI (million DT / year)
Hospitalization DT 250 / day 0.8 0.7
Doctor visits DT 25 / visit 2.4
ER visits DT 65 / visit 0.4 1.9
Lost work days DT 30 / day 1.2 0.1 0.4 15.0
Total Cost of Treatment (million DT per year) 4.8 0.8 2.3 15.0 22.9
Cost per case (DT) 1,807 534 78 3
Results Cost of Illness (COI) calculations
The Annual Cost of Illness Due to Urban Pollution The Annual Cost of Illness Due to Urban Pollution representsrepresents
22.9 million DT or 0.09 % of the GDP22.9 million DT or 0.09 % of the GDP
CaseCase--study 5:study 5:Impact of Water Quality on Impact of Water Quality on
Health in EgyptHealth in Egypt
Value of Life and Health Value of Life and Health CCasease--study 5:study 5: Impact of Water Quality on Health Impact of Water Quality on Health
in Egyptin EgyptBackground
The lack of safe drinking waterInadequate hygiene and sanitation
water pollution
Impact on human health and quality of lifeIntestinal work infections, Intestinal work infections, schistosomiasesschistosomiases, , diarrhealdiarrheal diseasesdiseases
17,000 children 17,000 children die annually from die annually from diarrhealdiarrheal diseasesdiseases
Cost to societyCost to society
Value of Life and Health Value of Life and Health CCasease--study 5:study 5: Impact of Water Quality on Health Impact of Water Quality on Health
in Egyptin EgyptMethodologyMortality•DALY/ HCA approach
Morbidity•DALY/ HCA approach
Value of Life and Health Value of Life and Health CaseCase--study 5:study 5: Impact of Water Quality on Health Impact of Water Quality on Health
in Egyptin EgyptResults• DALYs- Mortality
– 20% of all deaths in children under five attributable to diarrhealdisease
– Death of a child under 5 represents a loss of 35 DALYs (Global Burden of Disease)
– Base data are from WDI, World Bank 2001
Parameter ValueChild population (0-4 yrs) 8.15 millionAnnual child deaths (all causes) 88,020 per yearChild diarrheal disease deaths 20.0% of child mortalityAnnual child diarrheal disease deaths 17,604DALYs per child death 35 discounted years of life lostDALYs from child diarrheal disease deaths 616,140 per year
Value of Life and Health Value of Life and Health CaseCase--study 5:study 5: Impact of Water Quality on Health Impact of Water Quality on Health
in Egyptin EgyptResults• DALYs – Morbidity
– Estimates based on children only because of their high incidence rate– A severity weight of 0.2 assigned to diarrhea
• Base data are from WDI, World Bank 2001Parameter ValueChild population (0-14 yrs) 22 millionDiarrheal episodes per child per month 1Total episodes per year 264 millionAverage duration per episode 10 hrsTotal duration per year (hrs) 2,640 millionTotal duration per year (yrs) 301,370DALY (disability severity weight) 0.2DALYs from child diarrheal disease morbidity 60,274 per year
Value of Life and Health Value of Life and Health CaseCase--study 5:study 5: Impact of Water Quality on Health Impact of Water Quality on Health
in Egyptin Egypt
Parameter ValueMortality
Total number of DALYs 616,140Price per DALY 2,400-4,800 LE/yrMonetary loss 1,478 - 2,957 million LE/yr% of GDP 0.49 – 0.98 %
MorbidityTotal number of DALYs 60,274Price per DALY 27,500-55,000 LE/yrMonetary loss 145– 289 million LE/yr% of GDP 0.05 – 0.1 %
Value of Life and Health Value of Life and Health CaseCase--study 5:study 5: Impact of Water Quality on Health Impact of Water Quality on Health
in Egyptin Egypt
ResultsMore than 657,000 657,000 DALYsDALYs lost lost each
year due to diarrheal diseases amounting to a damage cost of
0.50.5--1.1 % of GDP per year1.1 % of GDP per year
CaseCase--study 6:study 6:Impact of Urban Air Quality Impact of Urban Air Quality
on Health in Egypton Health in Egypt
Value of Life and Health Value of Life and Health CaseCase--study 6:study 6: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in EgyptHealth in Egypt
Background
Value of Life and Health Value of Life and Health CaseCase--study 6:study 6: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in EgyptHealth in Egypt
Methodology
Value of Life and Health Value of Life and Health CaseCase--study 6:study 6: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in EgyptHealth in EgyptMethodology- Identify pollutant, measure its concentration,
determine exposed population
– Annual average concentrations of PM10 in Greater Cairo– Rough estimates of PM10 from Alexandria– No study in Egypt statistically linking urban pollution and health
based on local health data
Parameter Egypt Greater Cairo AlexandriaPopulation (million) 63 14.9 3.3
Adult population ≥15 yrs) (millions) 41 9.7 2.1
Children population (≤14 yrs) (millions) 22 5.2 1.2
Crude death rate (per 1,000) 7 7 7
Annual average PM10 (μg/m3) 270 100
Exposed total population (millions) 11.92 2.64
Exposed adult population (≥15 yrs) (millions) 7.8 1.7
Exposed children population (≤14 yrs) (millions) 4.2 0.9
Value of Life and Health Value of Life and Health CaseCase--study 6:study 6: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in EgyptHealth in Egypt
Methodology- Estimate health impacts from exposure
• Relied on dose-response coefficients from international studies (Lvovsky et al., 2000)
• Limitation: reported DRR from developed countries
Health categories Units Impacts per 1μg/m3
Premature mortality % change in crude mortality rate 0.084Chronic bronchitis Per 100,000 adults 3.06Hospital admissions Per 100,000 population 1.2Emergency room visits Per 100,000 population 23.54Restricted activity days Per 100,000 adults 5,750Lower respiratory illness in children Per 100,000 children 169Respiratory symptoms Per 100,000 adults 18,300
Value of Life and Health Value of Life and Health CaseCase--study 6:study 6: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in EgyptHealth in Egypt
Mortality•DALY/ HCA approach•DALY/ WTP approach
Morbidity•DALY/ HCA approach
Methodology- Valuate health impacts from exposure
Value of Life and Health Value of Life and Health CaseCase--study 6:study 6: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in EgyptHealth in EgyptResults- Mortality and Morbidity• Health outcomes converted to DALYs• DALYs adopted from Lvovsky et al. (2000)
Health categories DALYsper 10,000 cases
Annual cases Greater Cairo
DALYsGreater Cairo
Annual cases Alexandria
DALYsAlexandria
Annual DALYsSyria
Premature mortality 100,000 18,924 189,242 1,552 15,523 204,765
Chronic bronchitis 12,037 64,092 77,148 5,257 6328 83,476
Hospital admissions 264 38,621 1,020 3,168 84 1,103
Emergency room visits 3 757,611 227 62,146 19 246
Restricted activity days 3 120,434,571 36,130 9,879,048 2,964 39,094
Respiratory symptoms 3 383,296,114 114,989 31,440,000 9,432 124,421
Lower respiratory illnessin children
3 1,899,367 570 155,802 47 617
Total DALYs lost per year 419,326 34,397 453,722
Value of Life and Health Value of Life and Health CaseCase--study 6:study 6: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in EgyptHealth in EgyptResults• DALYs –Valuation
–Mortality• Low estimate at
GDP/capita (2001) = 4,800 LE
• High estimate at WTP = 28,000 LE – adopted from studies in
Europe and US and then adjusted for GDP per capita differentials for Egypt
– Adjusted WTP then modified to reflect approximate number of DALYs lost due to air pollution relative to DALYs lost in WTP studies» 10 DALYs per case usually
considered for air pollution–Morbidity
• Low estimate at GDP/capita (2001)= 4,800 LE
Parameter ValueMortality
Total number of DALYs 200,000Price per DALY 4,800 – 28,000 LE/yrMonetary loss 960 – 5,600 million LE/yr% of GDP 0.32– 1.86 %
MorbidityTotal number of DALYs 250,000Price per DALY 4,800 LE/yrMonetary loss 1,200 million LE/yr% of GDP 0.4 %
Value of Life and Health Value of Life and Health CaseCase--study 6:study 6: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in EgyptHealth in Egypt
ResultsMore than 450,000 450,000 DALYsDALYs lost lost each
year due to urban air pollution amounting to a damage cost of
0.7 0.7 -- 2.3 % of GDP per year2.3 % of GDP per year
CaseCase--study 7:study 7:Impact of Water Quality on Impact of Water Quality on
Health in MoroccoHealth in Morocco
Value of Life and Health Value of Life and Health CCasease--study 7:study 7: Impact of Water Quality on Health Impact of Water Quality on Health
in Moroccoin MoroccoBackground
The lack of safe drinking waterInadequate hygiene and sanitation
water pollution
Impact on human health and quality of life through diarrheal diseases (mainly children)
Cost to societyCost to society
Value of Life and Health Value of Life and Health CCasease--study 7:study 7: Impact of Water Quality on Health Impact of Water Quality on Health
in Moroccoin MoroccoMethodologyMortality•DALY/ HCA approach
Morbidity•DALY/ HCA approach
+•Cost of illness approach
• Severe diarrhea• Medication costs• Lost time for caregivers
• Mild diarrhea• Medication costs
• Oral rehydrationtherapy
Value of Life and Health Value of Life and Health CaseCase--study 7:study 7: Impact of Water Quality on Health Impact of Water Quality on Health
in Moroccoin MoroccoResults• DALYs- Mortality
– 20% of all deaths in children under five attributable to diarrheal disease (National Survey on the Health of Mother and Child, ENSME, 1997)
– Death of a child under 5 represents a loss of 35 DALYs (Global Burden of Disease)
Parameter ValueChild population (0-4 yrs) 3.038 millionChild mortality rate 46 per 1,000 live birthsAnnual child deaths (all causes) 27,951 per yearChild diarrheal disease deaths 20.0% of child mortality rateChild diarrheal disease mortality rate 9.2 per 1,000Annual child diarrheal disease deaths 5,590DALYs per child death 35 discounted years of life lostDALYs from child diarrheal disease deaths 186,868
Value of Life and Health Value of Life and Health CaseCase--study 7:study 7: Impact of Water Quality on Health Impact of Water Quality on Health
in Moroccoin MoroccoResults• DALYs – Morbidity
– Based on the National Survey on the Health of Mother and Child
• 9% of children under 5 suffered from diarrhea in the last 24 hrs– A severity weight of 0.2 assigned to diarrhea
• DALYs lost from one day of diarrhea = 0.2/365
Parameter ValueChild population (0-4 yrs) 3.038 millionDiarrheal prevalence in children (0-4 yrs) in last 24 hrs 9%Total diarrhea days per year 99.8 millionDALY (disability severity weight) 0.2DALYs from child diarrheal disease morbidity 64,887 per year
Value of Life and Health Value of Life and Health CaseCase--study 7:study 7: Impact of Water Quality on Health Impact of Water Quality on Health
in Moroccoin Morocco
Parameter ValueMortality
Total number of DALYs 196,000Price per DALY 6,150-12,300 Dh/yrMonetary loss 1,205 - 2,411 million Dh/yr% of GDP 0.34 – 0.68 %
MorbidityTotal number of DALYs 55,000Price per DALY 6,150-12,300 Dh/yrMonetary loss 338 – 677 million Dh/yr% of GDP 0.10 – 0.19 %
Value of Life and Health Value of Life and Health CaseCase--study 7:study 7: Impact of Water Quality on Health Impact of Water Quality on Health
in Moroccoin MoroccoResults• COI- Severe cases of diarrhea
– Severe cases often treated in health clinic– Cost of treatment obtained Moroccan doctors’ consultation– Assumed that 1 day is lost by caregiver per case of severe diarrhea– Value of a work day based on average rural income = Dh1,500/ month
Parameter ValueCases of diarrhea treated in public hospitals (20% of cases) 4,191,780Cases of diarrhea treated in private clinics (7% of cases) 1,357,338Total cases of reported diarrhea 5,549,118Cost of doctor visit per treatment 70 DhCost of medication per treatment 100 DhTotal cost of treatment 170 DhCost of treating severe diarrhea (< 5 yrs) 943 million DhValue of one day lost to caregiver 60 DhCost of lost time due to care giving 333 million Dh
Value of Life and Health Value of Life and Health CaseCase--study 7:study 7: Impact of Water Quality on Health Impact of Water Quality on Health
in Moroccoin Morocco
Results• COI- Mild cases of diarrhea treated by Oral
Rehydration Therapy– 30% of mild cases treated by ORT at home– Average length of diarrheal episode = 5 days
Parameter ValueTotal number of diarrheal days/yr in children < 5yrs 99.8 millionAverage duration of a diarrheal case 5 daysNumber of diarrhea cases per year in children (0-4 yrs) 19.9 millionPercent of cases treated with ORT 30 %Cases treated with ORT 5.99 millionUnit cost of ORT treatment 60 Dh/caseTotal cost of ORT treatment 359 million Dh
Value of Life and Health Value of Life and Health CaseCase--study 7:study 7: Impact of Water Quality on Health Impact of Water Quality on Health
in Moroccoin Morocco
Results
Total cost of treatment= 1,635 million Dh
= 0.46 % of GDP
CaseCase--study 8:study 8:Impact of Urban Air Quality Impact of Urban Air Quality
on Health in Moroccoon Health in Morocco
Value of Life and Health Value of Life and Health CaseCase--study 8:study 8: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in MoroccoHealth in MoroccoBackground• Sources of urban air pollution in Morocco
– Ageing diesel vehicle fleet (in 2000, 808,000 diesel vehicle, of which 74% are 10 years or older)
– Low quality oil products– Industry not converted to cleaner technologies:
• Thermal energy centers and oil refineries• Chemical and para-chemical industries• Textile and leather industries• Agro-industries• Electrical and electronic industries• Metal and metallurgical industries
– Power stations
Value of Life and Health Value of Life and Health CaseCase--study 8:study 8: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in MoroccoHealth in Morocco
MethodologyMeasure the concentrationof atmospheric pollutants
Identify populationsvulnerable to pollution
Assess the effect on health withthe dose-response coefficients
Valuate Morbidity
Assess mortality risk
Step 1
Step 2
Step 3
Step 4
Step 5
Value of Life and Health Value of Life and Health CaseCase--study 8:study 8: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in MoroccoHealth in MoroccoMethodologyStep 1: Measure the concentration of atmospheric pollutants• Air quality monitoring data are available from:
– Casablanca– The urban prefecture of Rabat-Sale– Cities of Safi– Fes, Marrakech and Tangiers (by analogies with other
Moroccan cities) • 2 to 7 monitoring sites per city reported in:
– Casa Airpol, 2000: Etude de la pollution atmosphérique et de son impact sur la santé des populations à Casablanca
– REEM, 2001 (Status of Environment Report in Morocco)– Ministry of Public Health,1998: Etude de la pollution
atmosphérique et de son impact sur la santé de la population de Safi
Value of Life and Health Value of Life and Health CaseCase--study 8:study 8: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in MoroccoHealth in MoroccoMethodologyStep 1: Measure the concentration of atmospheric pollutants
• Lower estimate for PM10 in Casablanca is based on a conversion factor between PM2.5 and PM10 equivalent to 0.35
• Lower estimates for PM10 in Rabat-Sale and Safi is based on expert judgements• Higher estimates for PM10 in Casablanca, Rabat-Sale and Safi is based on the average PM
concentration converted to PM10 on the basis of a ratio of 0.5• For Fes, Marrakech and Tangiers air pollution is mainly due to the transport sector, as in
Rabat. The lower value of PM10 for the city of Rabat was allocated to these cities (70).
City PM (μg/m3)Average level
PM3 (μg/m3)Average level
PM10 (μg/m3)Low level
PM10 (μg/m3)High level
Casablanca 244 33 94 122
Rabat - Sale 246 - 70 123
Safi 277 - 70 139
Fes, Marrakech & Tangiers - - 70
Value of Life and Health Value of Life and Health CaseCase--study 8:study 8: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in MoroccoHealth in MoroccoMethodologyStep 2: Identify populations vulnerable to pollution
• Population data were taken from the Ministry of Public Health (Santé en chiffres, 2001)• The demographic distribution of the six cities was estimated by extrapolation from national
averages• Certain impacts affect more particularly a certain portion of the population (for example, the elderly
and children under five years of age).
Cities Casablanca Rabat-Sale Safi Fes, Marrakech & Tangiers
Crude death rate (per 1,000) 4.9 4.9 4.9 4.9
Low level PM10 (μg/m3) 94 70 7070
High level PM10 (μg/m3) 122 123 139
Exposed total population (millions) 3.31 1.44 0.43 1.72
Exposed adult population (≥15 yrs) (millions) 2.16 0.94 0.28 1.12
Exposed population (≤14 yrs) (millions) 1.15 0.50 0.15 0.60
Exposed children population (≤5 yrs) (millions) 0.27 0.15 0.05 0.18
Value of Life and Health Value of Life and Health CaseCase--study 8:study 8: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in MoroccoHealth in MoroccoMethodologyStep 3: Assess the effect on health with the help of dose-response coefficients
• Relied on dose-response coefficients reported in the literature by Lvovskyet al. (2000)
Health categories Units Impacts per 1μg/m3
Premature mortality % change in crude mortality rate 0.084
Chronic bronchitis Per 100,000 adults 3.06
Hospital admissions Per 100,000 population 1.2
Emergency room visits Per 100,000 population 23.54
Restricted activity days Per 100,000 adults 5,750
Lower respiratory illness in children Per 100,000 children 169
Respiratory symptoms Per 100,000 adults 18,300
Value of Life and Health Value of Life and Health CaseCase--study 8:study 8: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in MoroccoHealth in MoroccoMethodologyStep 3: Assess the effect on health with the help of dose-response coefficients
Cases / city
Health categories
Casablanca Rabat-Sale Safi Fes, Marrakech, Tangiers
Total cases
Low High Low High Low High Low High
Premature mortality 1281 1662 416 731 125 248 496 2,318 3,137
Chronic bronchitis 6217 8069 2020 3549 607 1205 2410 11,254 15,233
Hospital admissions
3734 4846 1213 2131 365 724 1447 6,759 9,148
Emergency room visits
73242 95059 23794 41810 7151 14201 28392 132,579 179,462
Restricted activity days 11682529 15162431 3794846 6668087 1140556 2264818 4528061 21,145,992 28,623,397
Lower respiratory illness in children 182462 236812 59290 104180 17820 35285 70745 330,317 447,022
Respiratory symptoms 37180919 48256086 12077511 21221913 3629944 7208032 11411045 64,299,419 88,097,076
Value of Life and Health Value of Life and Health CaseCase--study 8:study 8: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in MoroccoHealth in MoroccoMethodologyStep 3: Assess the effect on health with the help of dose-response coefficients
• DALY approach is used to compare and assess the number of years lost due to disabilities
Health categories DALYs per 10,000 cases
Annual cases Morocco Annual DALYs MoroccoLow High Low High
Premature mortality 100,000 2,318 3,137 23,180 31,370 Chronic bronchitis 12,037 11,254 15,233 13,546 18,336
Hospital admissions 264 6,759 9,148 178 242
Emergency room visits 3 132,579 179,462 40 54
Restricted activity days 3 21,145,992 28,623,397 6,344 8,587 Lower respiratory illness in children 3 330,317 447,022 99 134
Respiratory symptoms 3 64,299,419 88,097,076 19,290 26,429 Total Morbidity 39,497 53,782
Total DALYs lost per yearTotal DALYs lost per year 62,677 62,677 85,152 85,152
Value of Life and Health Value of Life and Health CaseCase--study 8:study 8: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in MoroccoHealth in MoroccoResultsStep 4: Assess mortality risk
• Two common approaches were used:– Human Capital (HC) approach
as a lower bound estimate1 DALY = GDP/capita= 12,308 Dh
– Willingness To Pay (WTP)approach as a higher bound estimate; adopted from studies in US and then adjusted for GDP differentials for Morocco = 63,324 Dh
Lower Bound
Upper Bound
Total Annual Mortality DALYs 23,180 31,370
One DALYmonetary value (Dh)
GDP / capita WTP
12,308 63,324
Total Annual Mortality DALYs value (million Dh) 285.3 1,986.5
Average Annual Mortality Average Annual Mortality DALY value (million Dh)DALY value (million Dh) 1,135.91,135.9
The Average Annual Mortality Losses Due to Urban The Average Annual Mortality Losses Due to Urban Pollution Represents 0.32% of the GDPPollution Represents 0.32% of the GDP
Value of Life and Health Value of Life and Health CaseCase--study 8:study 8: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in MoroccoHealth in Morocco
MethodologyStep 5: Valuate Morbidity
Two approaches used1. Assess on DALY at GDP per capita to account for
people’s suffering associated with respiratory illnesses
2. Medical Cost of Treatment of respiratory diseases such as chronic bronchitis and lower respiratory illnesses in children
Value of Life and Health Value of Life and Health CaseCase--study 8:study 8: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in MoroccoHealth in Morocco
MethodologyStep 5: Valuate Morbidity
Assess DALY at GDP per capita to account for people’s suffering associated with respiratory illnesses
Lower Bound
Upper Bound
Total Annual Morbidity DALYs 39,497 53,782
One DALYmonetary value (Dh) 12,308
Total Annual Morbidity DALYs value (million Dh) 486.1 661.9
Average Annual Morbidity DALY Average Annual Morbidity DALY value (million Dh)value (million Dh) 574.0574.0
Value of Life and Health Value of Life and Health CaseCase--study 8:study 8: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in MoroccoHealth in MoroccoMethodologyStep 5: Valuate Morbidity - Cost of Treatment
• Chronic bronchitis estimates are based on:– Average 6 day hospitalization for 2.5% of patients– Monthly doctor visit for 25% of patients– Two visit per year for 65% of patients– Emergency consultation once a year for 30% of patients– 5 working days lost per year for 35% of patients– Costs are converted into annual numbers and discounted rate of 10% over a
period of 15 years to take into account the nature of chronic bronchitis– Data based on studies conducted in the US and Europe
• Hospital admissions– Two days of hospitalization– Two work days lost
• Emergency Room (ER) visit estimation is based on:– Cost of consultation– Half a day of work lost
• Restricted Activity Days (RADs)– 1 work day lost per 10 RADs
Value of Life and Health Value of Life and Health CaseCase--study 8:study 8: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in MoroccoHealth in MoroccoMethodologyStep 5: Valuate Morbidity - Cost of Treatment
Unit costsChronic bronchitis
Hospital admissions ER visits RADs
Low High Low High Low High Low High
Annual cases 11,254 15,233 6,759 9,148 132,579 179,462 21,145,992 28,623,397
Annual COI (million Dh / year)
Hospitalization Dh 1200/ day 16.7 22.6 16.6 22.4
Doctor visits Dh 70/ visit 28.6 38.7
ER visits Dh 300/ visit 8.7 11.8 40.6 55.0
Lost work days Dh 115/ day 19.1 25.8 1.8 2.5 7.4 10.0 243.1 327.9
Total Cost of Treatment (million Dh per year) 73.1 98.9 18.4 24.9 48.0 65.0 243.1 327.9
Cost per case (Dh) 6,569 2,741 362 11.5
Total cost of treatment ranges between 383 and 517 million Dh/yeTotal cost of treatment ranges between 383 and 517 million Dh/yearar
Value of Life and Health Value of Life and Health CaseCase--study 8:study 8: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in MoroccoHealth in Morocco
ResultsStep 5: Valuate Morbidity
The average The average annual morbidity annual morbidity losses due to losses due to urban pollution urban pollution represents 0.29% represents 0.29% of the GDPof the GDP
Lower Bound
Upper Bound
Total Annual Morbidity DALYs value (million Dh) 486.1 661.9
Total Annual Cost of Treatment (million Dh) 382.6 516.7
Total Annual Morbidity Cost (million Dh) 868.7 1,178.6
Average Annual Morbidity Cost (million Dh) 1,023.651,023.65
CaseCase--study 9:study 9:Impact of Water Quality on Impact of Water Quality on
Health in LebanonHealth in Lebanon
Value of Life and HealthValue of Life and HealthCCasease--study 9:study 9: Impact of Water Quality on Health Impact of Water Quality on Health
in Lebanonin LebanonBackground Substandard quality and inadequate quantity of potable water
Inadequate sanitation facilities and sanitation practicesInadequate personal, food and domestic hygiene
Impact on human health and quality of life through diarrheal diseases (mainly children)
Cost to societyCost to society
Value of Life and Health Value of Life and Health CCasease--study 9:study 9: Impact of Water Quality on Health Impact of Water Quality on Health
in Lebanonin LebanonMethodologyMortality•DALY/ HCA approach
Morbidity•DALY/ HCA approach
+•Cost of illness approach
– Treatment costs• Doctor and medical
facilities visits• Medicines• Oral Rehydration Therapy
– Time cost for caregivers of severe cases
Value of Life and Health Value of Life and Health CaseCase--study 9:study 9: Impact of Water Quality on Health Impact of Water Quality on Health
in Lebanonin LebanonResults• DALYs- Mortality
– 10% of all deaths in children under five attributable to diarrheal disease (based MoH, 1996 and CBS/Unicef, 2001)
– Death of a child under 5 represents a loss of 35 DALYs (Global Burden of Disease)
Parameter ValueChild population (0-4 yrs) 0.44 millionChild mortality rate in 2000 30 per 1,000 live birthsAnnual child deaths (all causes) 2,640 per yearChild diarrheal disease deaths 10.0% of child mortality rateChild diarrheal disease mortality rate 3 per 1,000Annual child diarrheal disease deaths 264DALYs per child death 35 discounted years of life lostDALYs from child diarrheal disease deaths 9,240 per year
Value of Life and HealthValue of Life and HealthCaseCase--study 9:study 9: Impact of Water Quality on Health Impact of Water Quality on Health
in Lebanonin LebanonResults• DALYs – Morbidity
– Based on Lebanese Mother and Child Health Census by MoH• Average duration of diarrhea case is 4 days• 2.0 million cases of diarrhea per year• 5.0% of children under 5 suffered from diarrhea in the last 24 hrs
– A severity weight of 0.2 assigned to diarrhea• DALYs lost from one day of diarrhea = 0.2/365
Parameter ValueChild population (0-4 yrs) 0.44 millionDiarrheal prevalence in children (0-4 yrs) in last 24 hrs 5.0 %Total diarrhea days per year 8.0 millionTotal diarrhea duration in years per year 22,000DALY (disability severity weight) 0.2DALYs from child diarrheal disease morbidity 4,400 per year
Value of Life and HealthValue of Life and HealthCaseCase--study 9:study 9: Impact of Water Quality on Health Impact of Water Quality on Health
in Lebanonin Lebanon
Parameter ValueMortality
Total number of DALYs 9,240Price per DALY 1,950-3,900 US$/yrMonetary loss 18.01 – 36.2 million US$/yr% of GDP 0.11 – 0.22 %
MorbidityTotal number of DALYs 4,400Price per DALY 1,950-3,900 US$/yrMonetary loss 8.5 – 17.1 million US$/yr% of GDP 0.05 – 0.10 %
Results• DALYs – Valuation
– Valuation per DALY:• High, 100% of Lebanese GDP per capita, 3,900 US$/yr• Low, 50% of Lebanese GDP per capita, 1,950 US$/yr
Value of Life and HealthValue of Life and HealthCaseCase--study 9:study 9: Impact of Water Quality on Health Impact of Water Quality on Health
in Lebanonin LebanonResults• Cost of illness approach
– According to MoH, 1996:• 48% of diarrhea cases are treated by doctors or medical facilities; and• 9% by pharmacies
– According to CBS/Unicef, 2001:• 44% of diarrhea cases are treated by Oral Rehydration Therapy (ORT)
– Average cost (Beirut and small town) of doctor or medical facility visit is 30 US$/visit (information from doctors in Lebanon)
– Cost of medicines for diarrhea treatment is 12 US$/case (information from doctors in Lebanon)
– Cost of ORT is 1.5 US$/case– Assumed that 1 day is lost by caregiver per case of severe diarrhea– Value of 1 day lost by caregiver (based on low-skilled wage rate) is
10.0 US$/day
Value of Life and Health Value of Life and Health CaseCase--study 9:study 9: Impact of Water Quality on Health Impact of Water Quality on Health
in Lebanonin LebanonResults• COI- Valuation of treatment costs
Parameter ValueTotal diarrhea cases per year (all children 0-4 years) 2.01 million
Percent of cases treated (doctor, medical facilities) 48%
Total cases treated (doctor, medical facilities) per year 0.96 millionCost of doctor/medical facilities visit 30 US$/visit
Total cost of doctor and medical facilities per year 28.9 million US$Percent of cases treated at pharmacy 9%
Total cases required medicines (cases treated at doctors and pharmacy, 57%) per year
1.14 million
Cost of medicines per case 12 US$
Total cost of medicines per year 13.8 million US$Percent of cases treated by ORT 44%
Total cases treated by ORT 0.88 millionCost of ORT per case 1.5 US$
Total cost of ORT per year 1.3 million US$
Value of Life and Health Value of Life and Health CaseCase--study 9:study 9: Impact of Water Quality on Health Impact of Water Quality on Health
in Lebanonin LebanonResults• COI- time cost of care giving for severe cases
– According to CBS/Unicef, 2001, 0.76 million of severe diarrheacases per year
– 1 day is lost by caregiver per case of severe diarrhea
Parameter ValueNumber of severe diarrhea cases per year 0.76 millionValue of day lost by caregiver 10.0 US$Total cost of lost time by caregivers 7.63 million US$
Value of Life and Health Value of Life and Health CaseCase--study 9:study 9: Impact of Water Quality on Health Impact of Water Quality on Health
in Lebanonin Lebanon
Results• COI- Total cost of diarrheal illness
Total COI = 51.6 million US$/year= 0.31% of GDP
Parameter ValueTotal cost of doctor and medical facilities visits per year
28.9 million US$
Total cost of medicines per year 13.8 million US$Total cost of ORT per year 1.3 million US$Total cost of lost time by caregivers 7.63 million US$Total cost of diarrheal illness 51.63 million US$
CaseCase--study 10:study 10:Impact of Urban Air Quality Impact of Urban Air Quality
on Health in Lebanonon Health in Lebanon
Value of Life and Health Value of Life and Health CaseCase--study 10:study 10: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in LebanonHealth in Lebanon
Background• Sources of air pollution in Lebanon
– Power stations– Industries– Vehicle induced emissions
Urban air pollutionespecially PM10and Lead (Pb)
Negative impacts on public health
- Premature deaths- Chronic bronchitis- Respiratory disorders- Cancer- Hypertension- IQ loss
Value of Life and Health Value of Life and Health CaseCase--study 10:study 10: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in LebanonHealth in Lebanon
Methodology
Value of Life and Health Value of Life and Health CaseCase--study 10:study 10: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in LebanonHealth in LebanonMethodology- Identify pollutant and measure its
concentration
• Impacts of PM10 concentrations in Greater Beirut and Tripoli areas were considered
• Data for pollutant concentrations:– PM10 in Greater Beirut area from El-Fadel et. al (2002).
Monitoring data after the ban of vehicle diesel fuel. Annual average of 55 μg/m3
– Annual average PM10 concentration in Tripoli was assumed equivalent to 55 μg/m3.
Value of Life and Health Value of Life and Health CaseCase--study 10:study 10: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in LebanonHealth in LebanonMethodology- Determine exposed population
• City population estimates taken from WDI, World Bank (2001)
• Assumed that 80% of the population exposed to air pollution
• Population broken-down by age-groups applying percentages of Lebanon’s population
Value of Life and Health Value of Life and Health CaseCase--study 10:study 10: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in LebanonHealth in Lebanon
Methodology-Data for Greater Beirut and Tripoli
Key Parameter Unit Lebanon Greater Beirut area
Tripoli
Total population Million 4.3 1.3 0.35
Adult population (≥15 yrs) Million 2.95 0.89 0.24
Children population (≤14 yrs) Million 1.35 0.41 0.11
Exposed population (80% of total) Million 1.04 0.28
Exposed adult population (≥15 yrs) Million 0.7 0.2
Exposed children population (≤14 yrs) Million 0.3 0.1
Crude death rate Per 1,000 6 6 6
Annual average PM10 μg/m3 55 55
Value of Life and Health Value of Life and Health CaseCase--study 10:study 10: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in LebanonHealth in Lebanon
Methodology- Estimate health impacts from exposure• Relied on dose-response coefficients reported in the
literature by Ostro (1994) and Lvovsky et al. (2000)
Health categories Units Impacts per 1μg/m3
Premature mortality % change in crude mortality rate 0.084Chronic bronchitis Per 100,000 adults 3.06Hospital admissions Per 100,000 population 1.2Emergency room visits Per 100,000 population 23.54Restricted activity days Per 100,000 adults 5,750Lower respiratory illness in children Per 100,000 children 169Respiratory symptoms Per 100,000 adults 18,300
Value of Life and Health Value of Life and Health CaseCase--study 10:study 10: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in LebanonHealth in Lebanon
Mortality•DALY/ HCA approach•DALY/ WTP approach
Morbidity•DALY/ HCA approach
+•Cost of illness approach
• Chronic bronchitis• Hospital admissions• Emergency room visits• Restricted activity days
Methodology- Valuate health impacts from exposure
Value of Life and Health Value of Life and Health CaseCase--study 10:study 10: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in LebanonHealth in LebanonResults- Mortality and Morbidity• Health outcomes converted to DALYs• DALYs adopted from Lvovsky et al. (2000)• Data calculated per city and then aggregated
Health categories DALYs per 10,000 cases
Cases Greater Beirut
DALYs Greater Beirut
Cases Greater Tripoli
DALYs Greater Tripoli
DALYs Total
Premature mortality 100,000 288 2,883 78 776 3,659
Chronic bronchitis 12,037 1,201 1,445 323 389 1,835
Hospital admissions 264 686 18 185 5 23
Emergency room visits 3 13,465 4 3,625 1 5
Restricted activity days 3 2,256,407 677 607,494 182 859
Lower respiratory illness in children
3 30,349 9 8,171 2 12
Respiratory symptoms 3 7,181,260 2,154 1,933,416 580 2,734
Total DALYs lost per year 7,191 96,062 1,936 9,127
Value of Life and Health Value of Life and Health CaseCase--study 10:study 10: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in LebanonHealth in LebanonResults• DALYs –Valuation
– Mortality• Low estimate at
GDP/capita (2001) = 3,857 USD
• High estimate at WTP adopted from studies in Europe and US and then adjusted for GDP per capita differentials for Lebanon
• Adjusted WTP then modified to reflect approximate number of DALYs lost due to air pollution relative to DALYs lost in WTP studies
– 10 DALYs per case usually considered for air pollution
– Morbidity• Low estimate at
GDP/capita (2001)= 3,857 USD
Parameter ValueMortality
Total number of DALYs
3,650Price per DALY 3,857 – 21,000 USD/yrMonetary loss 14.2 – 76.6 million USD/yr% of GDP 0.08 – 0.46 %
MorbidityTotal number of
DALYs5,480
Price per DALY 3,857 USD/yrMonetary loss 21.37 million USD/yr% of GDP 0.12 %
Value of Life and Health Value of Life and Health CaseCase--study 10:study 10: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in LebanonHealth in Lebanon
•Cost of illness approach• Chronic bronchitis• Hospital admissions• Emergency room visits• Restricted activity days (RADs)
Methodology- Valuate health impacts from exposure
Value of Life and HealthValue of Life and HealthCaseCase--study 10:study 10: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in LebanonHealth in LebanonResults- COI approach- Basis for cost estimates• Chronic bronchitis
– Monthly doctor visit for 25% of individuals with CB– Twice a year visit for 65% of individuals with CB– Emergency doctor visit once a year for 30% of individuals– Average 6 day hospitalization for 2.5% of individuals– 5 working days lost pr year for 35% of individuals– Costs discounted at 10% for 15 years to reflect chronic nature of illness– Data based on studies from US and Europe
• Hospital admissions– Two days of hospitalization– Two work days lost
• ER visits– Cost of doctor visits– Half a day of work lost
• RADs– 1 work day lost per 10 RADs
Value of Life, Health, Risk & SafetyValue of Life, Health, Risk & SafetyCaseCase--study 10:study 10: Impact of Urban Air Quality on Impact of Urban Air Quality on
Health in LebanonHealth in LebanonResults- COI approach
Unit costs* Chronic bronchitis
Hospital admissions
Emergency room visits
RADs Total cases
Annual cases 1,524 871 17,090 2,863,901 2,883,386
COIHospitalization 600 US$/day 1,148 1,045
Doctor visits 50 US$/visit 2,742
ER visits 100 US$/visit 383 1,709
Lost work days 60 US$/day 1,339 105 513 17,183
Total COI (Million US$/yr) 5.61 1.15 2.22 17.18 26.16Cost per case (US$) 3,681 1,320 130 6.0 9.1
Total COI = 26.16 Million US$/year= 0.16% of GDP
* Cost of illness based on information from doctors in Lebanon
End of Sessions 16 & 17
Thank You
REGIONAL WORKSHOP REGIONAL WORKSHOP ONON
THE COST OF THE COST OF ENVIRONMENTAL ENVIRONMENTAL
DEGRADATION DEGRADATION METHODOLOGYMETHODOLOGY
Session 18aEconomic Assessment of
Environmental Degradation due to the July 2006 Hostilities
REGIONAL WORKSHOP ONREGIONAL WORKSHOP ON
THE COST OF ENVIRONMENTAL THE COST OF ENVIRONMENTAL DEGRADATION METHODOLOGYDEGRADATION METHODOLOGY
Session 18aEconomic Assessment of Environmental Economic Assessment of Environmental
Degradation due to the July 2006 Hostilities Degradation due to the July 2006 Hostilities
OUTLINEOUTLINE
• Introduction• Oil Spill• Demolition, Military, and Medical Waste• Water Degradation• Quarries• Air Pollution• Forest Fires
INTRODUCTIONINTRODUCTION
• The 34-day hostilities in Lebanon started on July 12, 2006 and continued until August 14, 2006– killed close to 1,200 people– left more than 4,400 injured– displaced more than a quarter of the population– damaged severely the country’s infrastructure – had a devastating impact on the country’s fragile environment
and people’s health• destruction of infrastructure left enormous amounts of debris and
rubble• bombing of a power plant in Jiyeh caused the spill of about 12,000-
15,000 tons of oil into the Mediterranean Sea• widespread fires and oil burning deteriorated the air quality,
especially in Southern Beirut
INTRODUCTIONINTRODUCTION• This study aims at assessing the cost of environmental
degradation caused by the 2006 hostilities in Lebanon• Valuation methods used
Impacts Method used1.Oil spill - Impact on birds and turtles1
- Beach resorts, hotels, restaurant, marinas, fishing, ...Restoration cost modelMarket price2
2. Waste- Impact of demolition waste on environment- Impact of UXOs on health- Impact of UXOs on agriculture- Impact of medical waste
Cost of transport and disposalDALYs3
Market priceCost of disposal
3. Water Cost of alternative sources
4. Quarries Hedonic price method
5. Air Not estimated
6. Forests- Impact on forests- Impact on national reforestation program
Market price4, substitute goods5, cost-based methods6
Restoration costs
INTRODUCTIONINTRODUCTION
• The overall estimated cost of environmental degradation
Impacts US$ million(Min)
US$ million(Max)
US$ million(Average)
% of GDP1
Waste 206.8 373.5 290.2 1.4Oil spill 166.3 239.9 203.1 1.0Water 131.4 131.4 131.4 0.6Quarries 15.4 175.5 95.5 0.5Forests 7.0 10.8 8.9 0.0Air n.e. n.e.Total environmental cost caused by hostilities 526.9 931.1 729.0 3.6%
Based on an estimated GDP for 2006 of US$20.5 billion (Economic Intelligence Unit, 2006)
OIL SPILLOIL SPILL
Oil SpillOil Spill
• Bombing of Jiyeh power utility, located 30 km south of Beirut, led to burning and spilling of heavy oil into the Mediterranean Sea– About 12,000 to 15,000 tons of oil– Air and naval blockade limited
mitigation before two months• According to MEDSLIK from the
Oceanography Centre, University of Cyprus– spilled oil moved northward and onto
the shoreline, with heaviest impacts occurring between Jiyeh and Beirut, then between Byblos and Chekka, and onto the Palm Islands offshore
• Other areas showed patchy impacts• Oil reached the shoreline at Tartus,
Syria
Oil SpillOil Spill
• Initial shoreline assessment by the MOE indicated that– heavy pooled oil existed in coastal coves and harbors– sand and gravel beaches south of Beirut and around Byblos to
the north showed surface and buried oil– several observations of oil on the bottom
during this spill, probably a result of • oil burning• heavy oil concentrations mixing with
sediment to form oil mats on the bottom
• This type of oil has relatively low impact potential on fisheries and invertebrates, due to the low content of (acute) toxic hydrocarbons– Environmental problems are mainly caused by the oil’s physical
properties, such as the tendency to stick to objects and surfaces
Oil SpillOil Spill
• Major impact on marine biodiversity, including – shoreline biota– subtidal bottom communities
birds– marine reptiles– marine mammals– Fish– Nature reserves, particularly the Palm Islands Nature Reserve in
the North• These impacts were impossible to valuate within the
scope of the study• Impact of the oil spill on water quality
– laboratory analysis did not show contamination of groundwater through seawater intrusion, which could have occurred in densely fissured zones
Oil SpillOil Spill
• Estimates the environmental damages caused by the oil spill on the coastal zone– users’ forgone benefits through the differences between
the expected and actual benefits derived from activities on the coast
• Expected benefits: the level of environmental benefits which would have been enjoyed, had the oil spill not occurred
• Actual benefits: those currently provided after the outbreak of the conflict.
– A 3-year time frame was adopted for the analysis, during which the losses will gradually subside
• conservative time frame, as it does not capture potential effects not yet probed or that may occur over an extended period of time
Oil SpillOil Spill• In the absence of primary surveys several assumptions were made
to arrive at damage estimates
• The assumptions for 2006 rely on the baseline information and, consequently, vary from one activity to another
• For 2007 and 2008, conservative assumptions based on the experts’best knowledge at the time of valuation
Impacts on 2006 2007 2008Jul‐Aug1 Sep ‐Dec Jan‐Dec Jan‐Dec
% of expected incomeCommercial fishing 0 50a 5‐10 0‐5Shore‐side fishing 0 50a 5‐10 0‐5Hotels 0 10‐20 5‐10 0‐5World Heritage Site 0 25‐50 5‐10 0‐5Beach resorts and chalets 0 25‐50 5‐10 0‐5Nature Reserve 0 75‐100 5‐10 0‐5Restaurants 0 75‐100 5‐10 0‐5Sport Services 0 75‐100 5‐10 0‐5
Damages caused by the oil spill
1all losses during July-August are assumed to be caused by the hostilities themselves
Oil SpillOil Spill
• The following impacts were valuated– Hotels and furnished apartments
– Beach resorts, chalets and public beaches
– Marinas sports activities
– Palm Islands Nature Reserve
– Byblos World Heritage Site
– Restaurants
– Fishing
– Oil fuel burnt and spilled in Jiyeh
– Oil spill clean-up operations
Oil SpillOil SpillHotels and Furnished ApartmentsHotels and Furnished Apartments
• A drop in the occupancy rate of hotels and furnished apartments along the coast– In 2006 significant reduction due to visual signs of oiled beaches and
contaminated water– The Syndicate of Hotel Owners (2006) lists 54 licensed hotels located
on the coast • about 3,500 rooms• room rates US$40 to US$300/night, averaging to US$100/night• additional hotel revenue is US$50/day for meals, phone and laundry• the average hotel income is about US$150/person/day
– 97 furnished apartment establishments are located on the coast• 2,800 apartment units• daily price per apartment on average assumed that the net price of one furnished
apartment is about US$220/night
• With a damage cost of 5-10% of expected income in 2007 and 0-5% in 2008, total forgone income due to the oil spill ranges between US$23-60 million, with an average of US$41 million
Oil SpillOil SpillBeach Resorts and ChaletsBeach Resorts and Chalets
• The Lebanese coast hosts about 68 beach resorts• Many beach resorts made low income, while others closed for the
whole season• According to discussions with the Syndicate of Maritime
Establishments– about 500 daily visitors/beach resort during peak season – around 300 visitors/beach/day during the rest of the season.– daily spending per visitor averages US$20/day– the expected income of beach resorts in September 2006 was
estimated at US$12 million, while the expected seasonal income is about US$55.4 million
• In September 2006, the hostilities and the oil spill altogether caused a decline in the expected income of about 80% in September 2006.
– The oil spill alone likely contributed a loss of about 25-50% to the expected income in September 2006
– As in other cases, considerably lower share of 5-10% is assumed for 2007 – 0-5% for 2008
• Total forgone income due to the oil spill falls between US$5-13 million
Oil SpillOil SpillBeach Resorts and ChaletsBeach Resorts and Chalets
• Twenty-five chalet complexes can be found on the Lebanese coast, all located north of Jiyeh– The high season for renting chalets covers May-October– Each chalet complex has about 200 chalets– Chalet rent is about US$1,000/month– Thus, the monthly income from renting chalets averages to
US$5 million– The chalets closed during hostilities and re-opened at the
beginning of September 2006• expected income after re-opening
– US$10 million in 2006– US$30 million in each of 2007 and 2008
– Assuming that the oil spill contributes to the income decline in a similar way as in the case of beach resorts, total forgone income to chalets is about US$4 - 9 million
Oil SpillOil SpillBeach Resorts and ChaletsBeach Resorts and Chalets
• About 15 public beaches in Lebanon, covering a total length of 10-12 km– peak season from July to September– oil spill affected only 9 beaches– as entrance is free, it is assumed that the individual benefit is
about half of that enjoyed by visitors to beach resorts, i.e. US$10/day
• Expected monthly benefits from using public beaches during high-season = US$2.6 million– Public beaches closed during hostilities and re-opened
beginning of September 2006• Expected income after re-opening is estimated at US$2.6 million in
2006 and US$7.8 million in each of 2007 and 2008• Assuming oil spill contributes to the decline in benefits from
public beaches in a similar way as in the case of beach resorts, the present value of total forgone income is about US$0.7-1.5 million
Oil SpillOil SpillBeach Resorts and ChaletsBeach Resorts and Chalets
• Beach resorts and chalet complexes organize weddings and other social events from May to October– Social events count about 300 participants and cost US$40/person– Beach resorts can organize events during warm months
• 4 events/week during 4 months– Chalets complexes can arrange such events during half of the year
• 3 events/week during 6 months– About 6,000-6,700 events per season, providing an income of about
US$71-80 million per year• Income decline in 2006 is considered to be due to hostilities• Assuming that in 2007 and 2008 the oil spill contributes to the
decline in the income from events in a similar way as in the case of beach resorts– the present value of forgone income to events is about US$3-11 million.
Overall, forgone income to beach resorts, chalets, public beaches and events falls within US$13-35 million, with an average of
US$24 million
Oil SpillOil SpillMarine Sports ActivitiesMarine Sports Activities
• Marinas offer recreational services to public such as– Boating– Diving– Water-skiing– Docking– Maintenance of private boats
• In 2006, oil pollution of seawater, boatsand its effects on health prevented most marinas to resume their boat rental and water sports activities
• Based on field interviews, the total revenue of marinas is estimated about US$1 million per year, assume that– Income during May-June is equal to September-October, i.e.
about 25% of total annual income– As recreational activities resumed in September 2006, the
expected income for the rest of the year was US$250,000
Oil SpillOil SpillMarine Sports ActivitiesMarine Sports Activities
• Assume that– Income during May-June is equal to September-October, i.e. about 25%
of total annual income– As recreational activities resumed in September 2006, the expected
income for the rest of the year was US$250,000
• Assume that– oil spill caused about
75-100% drop in incomein September-October 2006.
– loss is about 5-10%of annual income in 2007 and 0-5% in 2008
• Loss from recreational activities in marinas ranges between US$0.23-0.38 million, with an average of US$0.3 million
Min(‘000 UsD)
Max(‘000 UsD)
Expected income:- in 2006 (Sept-Oct) 250 250- in 2007 (May-Oct) 1,000 1,000- in 2008 (May-Oct) 1,000 1,000Forgone income due to oil- in 2006 (Sept-Oct) 188 250- in 2007 (May-Oct) 50 100- in 2008 (May-Oct) 0 50PV of forgone income 238 377
Oil SpillOil SpillMarine Sports ActivitiesMarine Sports Activities
• Pollution of private leisure boats docked in marinas and fishingboats docked in fishing ports – limited the owners’ benefits from using their boats in the period following
the hostilities until the end of 2006 – imposed additional costs of cleaning the boats
• Loss of the recreational benefit from private leisure boats equal to– annual depreciation of the boat – cost of upkeep and docking in marinas
• Assuming that only 890 boats actually oiled (50% of 1,775)– Average price for common boat (6-12 m) = US$30,000– Considering a lifetime of about 20 years
• annual value of a boat = US$1,500.– Assuming an annual cost of US$300/m/season and the average size of
a boat of 9 m• Annual cost of upkeep and docking is about US$2,700
• The total loss to owners of private leisure boats = US$3.7 million.
Oil SpillOil SpillMarine Sports ActivitiesMarine Sports Activities
• To estimate the loss due to oiled fishing boats, annual maintenance costs used as proxy– 20 oiled fishing boats– annual maintenance costs = US$2,700
• Accordingly, loss due to oiled fishing boats amounts to US$54,000
Total loss to private owners of leisure and fishing boats = US$3.8 million
Overall losses to marinas’ sports activities = US$4 to US$4.2 million, with an average of US$4.1
million
Oil SpillOil SpillPalm IslandsPalm Islands’’ Nature ReserveNature Reserve
• The loss to tourism in 2006 estimated by the difference between– the expected number of tourists (averaging 22,500)– actual arrivals (about 1,700)
• Forgone benefits– losses in revenues from boat transportation of individuals and groups to the islands – rentals of chairs and umbrellas
• The tourist season is about 13 weeks (July-September) of which only three remained after the end of blockade
• Considering that tourists are evenly distributed in time throughout the season, and assuming that the oil spill will contribute to the forgone income between
– 75-100% in 2006– 5-10% in 2007 – 0-5% in 2008
• Loss in tourism due to oil spill is estimated at about US$15,400-27,600NATURE RESERVE Min Max NotesForgone annual income (13 weeks) 72.4 91.1Forgone income due to the oil spill % of expected income:- in 2006 (3 weeks) 12.5 15.8 75-100% - in 2007 (13 weeks) 3.6 9.1 5-10%- in 2008 (13 weeks) 0 4.6 0-5%PV of forgone income (‘000 USD) 15.4 27.6
Oil SpillOil SpillPalm IslandsPalm Islands’’ Nature ReserveNature Reserve
• A long term monitoring program is foreseen for the reserve and other ecologically significant sites affected by the spill– 7-10 years duration– US$1.2-1.7 cost
• Part of this cost is directly related to the oil spill damage, while the rest being an expression of WTP for future information
• Assumed that 50% of the total impact assessment and monitoring cost is due to the oil spill damage, ie. US$600,000-850,000
• The overall impact of the oil spill on the Palm Islands Nature Reserve and other ecologically sensitive areas amounts to US$0.7-1.2 million
• Assigning a monetary value to the loss of biodiversity was not possible due to lack of such studies
Oil SpillOil SpillByblos World Heritage SiteByblos World Heritage Site
• Oil spill heavily contaminated– the harbor– two medieval towers at the entrance– other ancient ruins located below the archaeological Tell in
Byblos
• Absence of information on the willingness-to-pay loss of historical value using restoration cost method– UNESCO team recommended a procedure to clean the oiled
archaeological remains• Assuming stones cleaned manually with a specially prepared solution• Total cleanup cost of operations = US$100,000 as the minimum bound
of the damage caused by the oil spill
• Loss in recreational value estimated in terms of forgone benefits due to decrease in number of visitors during 2006-2008
Oil SpillOil SpillByblos World Heritage SiteByblos World Heritage Site
• Visits to Byblos take place throughout the year and are organized both by tour operators and private individuals
• Annual income from all visits to Byblos = US$144,000• Assuming the oil spill contributes
25-50% of the September-December income in 2006, 5-10%in 2007 and 0-5% in 2008
• Damage to tourism inByblos and other historical townsranges between US$15,300-42,800.
Min MaxExpected annual income 144.0 144.0Forgone income due to oil spill- in 2006 (Sept-Dec 9.0 24.0- in 2007 (Jan-Dec) 7.2 14.4- in 2008 (Jan-Dec) 0.0 7.2PV of forgone income 15.3 42.8
Tours•Average number of visitors by tours is about 300/year•Fee is about US$30/person if meals are excluded•The annual income of tour operators from organizing visits to Byblos is about US$72,000
Private individuals• There are twice as many visitors to
Byblos by private cars as those coming through tour operators
• The average spending is US$15/person
•The annual income from individual trips would be about US$72,000
Total estimated damages to Byblos US$115,300Total estimated damages to Byblos US$115,300--142,800142,800
Oil SpillOil SpillRestaurantsRestaurants
• Oil spill affected negatively the activity of these restaurants, mainly due to fears of negative impacts of contaminated fish on human health
• According to the Syndicate of Restaurant Owners– 170 restaurants specialized in fish– Annual turnover ranges between US$200,000 and US$ 600,000
• Assuming average turnover of a fish restaurant is US$400,000/year (US$33,000/month) expected income during September – December 2006 would be about US$133,000 per restaurant
RESTAURANTS Min MaxNo. of fish restaurants 170 170Annual turnover (000 US$/rest./ yr.) 400 400Monthly turnover (000 US$/rest/mth) 33.3 33.3Expected income in Sept-Dec 2006 (000 US$/rest.)
133.3 133.3
Forgone income due to the oil spill- in 2006 (million US$) 17.0 22.7- in 2007 (million US$) 3.4 6.8- in 2008 (million US$) 0 3.4PV of forgone income to oil spill (million US$)
19.5 31.1
• In 2006, 75-100% of the expected income loss• In 2007-2008, successful cleanup of oil
and gradual return to normal life• potential effects on human health
reduce the restaurants’ expected profitsby 5-10% in 2007 and by 0-5% in 2008
Present value of forgone benefits ranges between Present value of forgone benefits ranges between US$19.5US$19.5--31.1 million with average at US$25.3 million31.1 million with average at US$25.3 million
Oil SpillOil SpillFishingFishing
• Fishing supports about 30,000 fishermen who catch on average 8,000 ton of fish per year
• Oil spill caused– direct damages to the boats and gears and ultimately a partial decline of fish supply– indirect damages whereby the actual fish contamination or the perception of its effects
on health reduced the overall demand for fish consumption• In commercial fishing, fish catch varies largely across seasons
– 30% of annual catch in spring– 42% in summer– 22% in autumn – 8% in winter
• Annual income from fishing is about US$31 million• Applying the seasonal catch factor to the total income, the expected fish
income during September-December 2006 was US$7.4 million. • It is estimated that the hostilities and oil spill caused the income of
fishermen to drop by 45%.• Assuming that only 50% of this drop is owing to oil spill, the associated
damage cost in 2006 is about US$1.3 million• Assuming oil spill causes a 5-10% decline in 2007 and 0-5% in 2008, the
present value of damages to commercial fishing falls between US$3-6 million
Oil SpillOil SpillFishingFishing
• Recreational fishing– Impacts assumed to be similar to commercial ones– Oil affected 2,600 anglers– Value of shore-side fishing includes the consumption and recreational value of fish– Using an average catch of 2 kg/day for a minimum of 50 days and an average price of
US$4/kg (FAO, 2006), the consumption value of fish is US$1 million/year• Assuming recreational value of anglers in Lebanon is similar to the value of
recreation on public beaches (US$10/day), the recreational value of anglers is US$1.3 million/year
• Overall, the annual value of shore-side fishing is about US$2.3 million. • Considering that fish catch varies seasonally in the same proportion as in
the case of commercial fishing– expected fish income during September-December 2006 was estimated at about
US$0.7 million• Estimating the impact of the oil spill on shore-side fishing uses the same
percentages adopted for commercial fishing for 2006-2008,– the present value of forgone benefits ranges between US$260,000-472,000
Overall, the impact of the oil spill on commercial and shore-side fishing amounts to US$3.2-6.5 million, with an average of US$5 million
Oil SpillOil SpillOil Fuel Burnt and Spilled in JiyehOil Fuel Burnt and Spilled in Jiyeh
• In addition to environmental damages the loss of an estimated 44,000 tons of stored IFO 150 at Jiyeh electrical power plant represent an economic loss– Loss in resources due to the spill and burning of the
Jiyeh fuel = US$ 20 million (US$450/ ton)– Cost of hiring three floating tankers to replace burnt
tanks = US$ 4 million– Transfer of fuel from different plants to Jiyeh power
plan and soil test of soil in burnt tanks’ location = US$ 15 million
• In total, the burning and spilling of Jiyeh fuel oil due to the hostilities resulted in a direct economic loss estimated at US$ 39 millionUS$ 39 million.
Oil SpillOil SpillOil Spill CleanOil Spill Clean--up Operationsup Operations
• MOE estimated the cost of oil spill clean-up in the range of US$137-205 million (US$13,800/t)
• Approximately US$4 million was provided as equipment and materials by international community– Considering depreciation from use with this oil type – Considering that much of the material was provided
as expendable supplies • 25% of the total supplied, or USD 1 million, will be available
for use after this incident and therefore is deducted from the total mitigation cost
Oil SpillOil SpillOil Spill CleanOil Spill Clean--up Operationsup Operations
• Estimated amount of oiled waste generated by Phase I clean up operation– 1,030 m3 of liquid waste– 6,250 m3 of polluted waste
• sand, garbage, debris and equipment• Cost of oil waste removed during Phase I based on the waste
management options considered by the MOE– Cost of liquid waste re-processed at Zahrani refinery = US$
92,000– Cost of treating non-liquid oil-polluted waste = US$ 47 million
• 25% includes low-to-medium contaminated sand – 25% of low-to-medium contaminated sand will be re-used in cement, construction
or asphalt industries– At a unit cost of US$10/m3 and a transport cost of US$80,000, the total cost of
transporting and treating the low-to medium contaminated sand is estimated at US$96,000
• 75% represents heavily contaminated sand and pebbles– 4,700 m3 of heavily contaminated sand and pebbles to be shipped under Basel
convention at a cost of US$10,000/ m3
Oil SpillOil SpillOil Spill CleanOil Spill Clean--up Operationsup Operations
• The estimated cost of transporting and treating the oiled waste resulting from Phase I cleaning operation is US$ 47.1 million
• Phase II of oil spill clean up will generate 4,500 m3 of solid waste
• Additional costs include– 1 million USD for Phase II of the clean-up and monitoring
operations in Palm Islands Nature Reserve– 0.5 million USD for sampling and analysis of water, sediments,
biota and fish species in 9 sites along the Lebanese coast over a period of three years
Overall, the cost of oil clean-up, treatment of oiled waste and monitoring the Lebanese coast is estimated at US$
63.5 million
Oil SpillOil SpillSummarySummary
• Overall damage and clean-up cost due to the oil spill is conservatively estimated at US$203 million, or 1.0% of GDP in 2006
• Value represents lower bound of real costs– does not capture several damage costs
• effects on health (skin diseases)• effects on ecosystem services (loss in habitat for spawning)• effects on marine biodiversity
– fails to cover the cost of many future clean-up operations– tends to reflect only partially the real cost of the oil spill for many
impacts, as a result of the conservative assumptions adopted forvaluation
• Overall estimate and breakdowns should be regarded with care, as many of the assumptions are subjective and debatable due to lack of accurate data
Oil SpillOil SpillEstimated costs of damage and cleanEstimated costs of damage and clean--up up
due to the oil spilldue to the oil spillParameter Estimated Cost (million $)
Min Max MeanDamage- Hotels 22.8 59.6 41.2- Beach resorts, chalets, public beaches 13.2 34.8 24.0- sports activities 4.0 4.2 4.1- Nature Reserve 0.7 1.2 1.0
0.1 0.1 0.1- Restaurants 19. 5 31.1 25.3- Commercial fishing 3.0 5.9 4.4- Sea‐shore fishing 0.3 0.5 0.4- Cost of oil fuel burnt 39.1 39.1 39.1
Sub‐total 102.8 176.4 139.6Oil spill clean up- Expenses already made 14.9 14.9 14.9- Oiled waste 48.2 48.2 48.2- Monitoring expenses 1.5 1.5 1.5
Sub‐total 63.5 63.5 63.5Total 166.3 239.9 203.1
CONSTRUCTION, DEMOLITION CONSTRUCTION, DEMOLITION AND MILITARY WASTEAND MILITARY WASTE
Construction & Demolition WasteConstruction & Demolition Waste
• Construction and Demolition (C&D) waste concentrated in three areas:– Southern Suburbs of Beirut– Districts of the South– Baalbek El Hermel region
• Typical C&D debris constituents:– Primary inert fractions
• Asphalt, brick, glass, plastic pipes, etc.– High organic based fractions
• Ceiling tiles, insulation-treated cellulose, plywood, etc.– Composite materials
• Carpeting, gypsum wallboard, electrical fixtures, etc.
Construction & Demolition WasteConstruction & Demolition WasteGeneral QuantitiesGeneral Quantities
• Beirut Southern Suburbs• 100-200 residential buildings completely
destroyed• 28 partially blasted• 70 damaged
• Districts of the South and Baalbek El Hermel– 11,140 units destroyed– 1,249 units partially destroyed– 81,000 units lightly damaged
• Actual quantities of rubble and demolition waste
Regions Quantities (million m3)Beirut Southern Suburbs 1.43
South 3.32
Bekaa 1
Total 5.75
Construction & Demolition WasteConstruction & Demolition WasteHandling, transport & disposalHandling, transport & disposal
• Beirut Southern Suburbs– Waste disposed at 4 sites
• 2 in low-lying areas by the sea• 1 in Choueifat• 1 temporary along the airport
road– Waste dumped haphazardly– Slope reached 1:1– Where sea encroachment
occurs, the bulky C&D waste gives a good angle of stability
Construction & Demolition WasteConstruction & Demolition WasteHandling, transport & disposalHandling, transport & disposal
• The South– Waste used to fill depressions– Waste dumped on nearby lands and
in valleys (Khyam)– Waste dumped in an abandoned
pond in Aytaroun– Associated damage difficult to
quantify• Ecosystem damage and visual intrusion• Hydrology and hydrogeology• Opportunity cost associated with land-
use
Construction & Demolition WasteConstruction & Demolition WasteHandling, transport & disposalHandling, transport & disposal
• Baalbek El Hermel– Waste used to rehabilitate
depressions– Waste dumped in abandoned
quarries– Sorting of asbestos mats,
construction steel, and concrete bricks at dumpsites
– Asbestos only in Baalbek El Hermel
• Limited short-term exposure
Construction & Demolition WasteConstruction & Demolition WasteHandling, transport & disposalHandling, transport & disposal
Estimated cost of loading and transport of C&D wasteEstimated cost of loading and transport of C&D wasteDescription Rate
Waste Haulinga
Dozer charging rateb ($/day) 400
Filling capacity of 3 dozersc (Truck/day) 30
Daily volume of C&D waste loaded (m3/day) 540
Cost of Loading each Truck per m3 of DW ($/m3) 0.07Waste Transporta
Truck charging rateb ($/day) 250
Daily number of round trips 6
Loading capacity per truck (m3) 18
Daily Volume of DW Transported per Truck (m3/day) 108
Cost of Transport per m3 of DW ($/m3) 2.31Total Unit Cost ($/m3) 2.38Cost in Beirut S. Suburbs ( millions $) 3.4
Cost in the South (millions $) 7.9
Cost in Baalbek El Hermel (millions $) 2.4
Total Cost (million $) 13.7
a Based on field surveys, expert opinion, and GIS analysis
b Range accounts for degree of intervention and thickness damaged
Construction & Demolition WasteConstruction & Demolition WasteRoad depreciationRoad depreciation
• In South and Baalbek El Hermel– Damage due to military aggression– No damage from waste transport
• In Beirut- cost of road depreciationDescription RateAverage road length (km)a 2-3Average road width (m)a 6-8Average road area (m2) 12,000-24,000Cost of road refurbishment ($US/ m2)a
40 cm of compacted gravel10 cm of asphalt
20-30b
Total cost of road depreciation (US$) 240,000-720,000
a Based on field surveys, expert opinion, and GIS analysisb Range accounts for degree of intervention and thickness damaged
Construction & Demolition WasteConstruction & Demolition WasteTraffic DelaysTraffic Delays
• In South and Baalbek El Hermel, delays not encountered– Traffic management and rerouting away from
city center– Dumpsites located in outskirts
• In Beirut, 1 to 3 hrs of traffic delays– Difficult to differentiate between delays due to
waste transport and delays due to bombarded roads
Construction & Demolition WasteConstruction & Demolition WasteTraffic DelaysTraffic Delays
Estimated cost of traffic delaysEstimated cost of traffic delaysDescription Rate
Average extra time spent in traffic (hr/day)a 2
Average hourly wage (US$/hr)b 2.5
Number of working days per monthc 22
Fraction of lost productive timea 0.5
Duration of waste removal (months) 6-8
Opportunity cost of time (US$/ person/6-8 month) 330-440
Average daily number of affected commutersd 115,150
Opportunity Cost of Time (US$ million) 38-51Fuel consumption per hr in traffic (L/hr)a 1
Unit cost of fuel ($US/L)a 0.8
Cost of fuel spent per person per month ($US/month) 35.2
Number of affected vehiclesd 60,000
Cost of gasoline spent per person per 6-8 months ($US/person)
211-282
Total cost of gasoline spent per 6-8 months ($US million) 13-17
Total cost of traffic delay (US$ million) 51-68
a Based on field surveys and expert opinion;
b Based on a GDP of 5,300 US$/capita;
c Peak travel delays are assumed to occur 22 working days/month;
d Based on DMJM+HARRIS, 2003-Refer to Annex 3
Construction & Demolition WasteConstruction & Demolition WasteCost of land for waste disposalCost of land for waste disposal
• Assumptions– All waste in each area is disposed in one
equivalent landfill– Height of landfill = 25 m– Unit cost of land adopted is average to low
Region Waste volume(000m3)
Landfill height (m)
Area of waste
(000m2)
Landfill area
(000m2)
Cost of land1
($/m2)Cost of
land (million $)
Beirut 1,430 25 57.2 74.4 1,000 74.4
South 3,320 25 132.8 172.6 10 1.72
Baalbek 1,000 25 40.0 52.0 15 0.781 Based on real estate information and expert opinion
Construction & Demolition WasteConstruction & Demolition WasteDepreciation of land surrounding dumpsitesDepreciation of land surrounding dumpsites
• Waste disposal represents to surrounding neighborhood– Health hazard– Visual intrusion
• Damage assessment was not possible
Construction & Demolition WasteConstruction & Demolition WasteSummarySummary
Parameter Damage cost (million US$)Beirut South Baalbek Total
Waste hauling and transport 3.4 7.9 2.4 13.7Road maintenance 0.2-0.7 - - 0.2-0.7Traffic delays 51 - 68 - - 51 - 68Land for disposal 74.4 1.7 0.8 76.9Land depreciation - - - -
Subtotal 129-146.5 9.6 3.2 142-159
Estimated total damage cost of C&D waste
Military Waste (Unexploded Ordnances)Military Waste (Unexploded Ordnances)IntroductionIntroduction
• 864 cluster bomb strike locations in South Lebanon
Military Waste (Unexploded Ordnances)Military Waste (Unexploded Ordnances)IntroductionIntroduction
• One million UXOs on 34 million square meters
• Demining– Costs 5.5 million USD per year– Will need a period of two years
• Impact of UXOs– Death and injuries– Preventing access and exploitation of
agricultural lands
Military Waste (Unexploded Ordnances)Military Waste (Unexploded Ordnances)Deaths and InjuriesDeaths and Injuries
• Casualties from August 14 2006 to April 03 2007 (MACCSL, 2007)– 29 deaths – 195 injuries
• UXO casualties by the end of the two-year demining period was projected
102
43
2316
24
8 6 4 4 4 4 4 4 4 3 3 3 2 2 2 2 2 2 2 20
20
40
60
80
100
120
Num
ber o
f cas
ualti
es
Current P ro jec ted
Military Waste (Unexploded Ordnances)Military Waste (Unexploded Ordnances)Deaths and InjuriesDeaths and Injuries
• DALY methodology applied– Disability weight for death = 1– Disability weight for injuries resulting from UXO (leg
or arm amputation) = 0.3• DALY approaches
– Human Capital Approach• 5,300 USD as GDP per capita in 2006
– Value of Statistical Life (VSL)• 42,000 based on the VSL divided by a time horizon of 25
years and discount rate of four percent • Total damage cost of casualties resulting from
US$ 14 and 109 million over a period of two years.
Military Waste (Unexploded Ordnances)Military Waste (Unexploded Ordnances)Deaths and InjuriesDeaths and Injuries
Age group Current nb of casualtiesa
Current and projected nb. of casualtiesb
DALYs per
casec
DALY($ VSL)
Current & projected economic loss (million
US$/ age-group)
MORTALITY0-12 2 2.5 33 5,300-42,000 0.43 – 3.40
13-18 4 4.9 36 5,300-42,000 0.94 – 7.43
19+ 23 28.2 20 5,300-42,000 2.99 – 23.72
SubTotal 29 35.6 4.36 – 34.55MORBIDITY
0-12 24 29.5 9.9 5,300-42,000 1.55 – 12.25
13-18 39 47.9 10.8 5,300-42,000 2.74 – 21.72
19+ 132 162.1 6 5,300-42,000 5.15 -40.84
SubTotal 195 239.4 9.44 – 74.81Total 224 275 13.80 – 109.35
Estimated damage cost of UXOsEstimated damage cost of UXOs
a MACCL, 2007b Based on Figure 3.8 and the assumption that percent distribution of projected vs. current casualties is the samec Murray and Lopez, 1996
Military Waste (Unexploded Ordnances)Military Waste (Unexploded Ordnances)Access to Agricultural LandsAccess to Agricultural Lands
• Limited access to agricultural lands in the South will impact on agricultural production and farmer livelihoods for at least two years
• Farmers may respond by – burning their orchards to get rid of UXOs, losing
plantations in the process– doing nothing and wait for their lands to be cleared
from UXOs– migrating to urban areas and adding to the poverty
situation in urban belts. • It is difficult to assign a monetary value on these
types of behaviors.
Military Waste (Unexploded Ordnances)Military Waste (Unexploded Ordnances)Access to Agricultural LandsAccess to Agricultural Lands
• Assessing the productivity loss due to lack of access to agricultural lands.
Crop typeCultivated area (du) a Production rate b
Total production Value b Total value
South Nabatiye Total (Tonne/du) (Tonnes) (USD/tonne) (USD)
Cereals 37,638 59,525 97,163 0.28 26,781 297 7,965,069
Legumes 2,096 5,869 7,966 0.54 4,270 565 2,413,839
Fruit trees 123,304 20,768 144,073 1.26 181,973 746 135,786,268
Olives 89,340 116,124 205,464 0.29 58,759 1,268 74,525,973
Oleaginous trees 5,806 3,836 9,642 0.10 931 2,083 1,939,556
Vegetables 20,753 12,141 32,894 3.19 104,871 251 26,276,441
Raw tobacco 14,625 40,026 54,652 0.12 6,395 2,988 19,110,223
Total 268,017,000
Military Waste (Unexploded Ordnances)Military Waste (Unexploded Ordnances)Access to Agricultural LandsAccess to Agricultural Lands
• Scenarios adopted and associated costs
Scenario Damage cost
1) 25% of the agricultural area (evenly distributed among crop categories in
the 2 Mohafazas) will not be accessible for a whole year
67 million US$ per year
2) 10% of the agricultural area (evenly distributed among crop categories in
the 2 Mohafazas) will not be accessible for a whole year
27 million US$ per year
3) 5% of the agricultural area (evenly distributed among crop categories in
the 2 Mohafazas) will not be accessible for a whole year
13 million US$ per year
Military Waste (Unexploded Ordnances)Military Waste (Unexploded Ordnances)SummarySummary
• Scenarios adopted and associated costs
Damage cost (million $US)Minimum Maximum
Casualties 14 109Loss in agricultural opportunities 40 94De-mining 11 11
Total 65 214
Medical WasteMedical WasteSummarySummary
• Hostilities caused– 1,200 deaths– 4,400 injuries
• Around 200-250 tons of medical waste generated• All generated waste is assumed to be infectious
requiring sterilization• Handling cost of medical waste estimated at 0.015-0.045
million USD– Sterilization cost = 60 USD/ton– Disposal cost at an operational landfill = 15-120 USD/ton
• Cost of disposal of unwanted pharmaceuticals could not be estimated due to lack of data
WATER DEGRADATIONWATER DEGRADATION
Water DegradationWater DegradationImpacts on Water ResourcesImpacts on Water Resources
• Strikes on industrial facilities– Damage of Choueifat Industrial Area
• Pollution of Ghadir stream with waste residue, contaminated soil, ash
• Groundwater contaminated with heavy metals and toxic benzene
• Strikes on water and wastewater infrastructure– Affected mostly the Beirut Southern Suburbs and the South– Caused a high risk of cross-contamination and a disruption of
water and sanitation services– Imposed additional costs of securing clean water
• Destruction of bridges over the Litani River– Obstruction of flow– Risk of flooding in neighboring areas– Excessive erosion and destruction of stream banks
• Destruction of irrigation canals
Water DegradationWater DegradationDamage to Water ResourcesDamage to Water Resources
• Impact on water quality– Requires establishment of dose-response
functions– Absence of pre-conflict monitoring– Absence of data regarding water use changes
and waterborne disease incidences– No monetary estimate could be made
Water DegradationWater DegradationDamage to Water ResourcesDamage to Water Resources
• Impact on water quantity– 52 water reservoirs damaged– 100s of kms of water and wastewater
networks– About 150,000 people directly affected
• Assumptions– Water reservoirs provide 50% of total water
supply– Average daily water consumption
• 1 liter/capita for drinking• 79.5 liter/capita for other uses
Water DegradationWater DegradationDamage to Water ResourcesDamage to Water Resources
• Reservoir restoration– 82,900 people were gradually served by 48
reservoirs during Sept-Dec 2006 – 62,100 people were expected to be supplied
with water gradually during Jan-Dec 2007.– It is expected that 5,000 people will be served
by June 2007
Water DegradationWater DegradationDamage to Water ResourcesDamage to Water Resources
• Sample calculations:– Additional costs of getting water during September-December 2006
Sep Oct Nov Dec Total
Population affected (‘000) 83 62 41 21
Cost of bottled water a (USD/liter) 0.7 0.7 0.7 0.7 …
Cost of water tanksa (USD/liter) 0.06 0.06 0.06 0.06 …
Number of days 30 31 30 31 …
Cost of drinking waterb (million USD) (1) 0.2 0.1 0.1 0.1 0.5
Cost of water for other usesc (million USD) (2) 11.3 8.7 5.6 3.0 28.6
Cost if hostilities had not occurredd (million USD) (3) 0.1 0.09 0.06 0.03 0.3
Additional cost (million USD) (1) + (2) - (3) 11.4 8.8 5.6 3.0 28.8
Notes: a market price observed during the field visit (April 2007); b based on a drinking water consumption of about 0.5 liter/capita/day; 16% of population relies on bottled water and the remaining on water tanks; c based on a consumption of 79.5 liters/capita of water for other uses; all population relies on water tanks; d assumes that 50% of the daily consumption would have been satisfied by water reservoir.
Water DegradationWater DegradationDamage to Water ResourcesDamage to Water Resources
• Total additional cost of getting water = 99.4 million USD– 64.4 million USD for the 62,100 people
expected to gradually receive water during Jan-Dec 2007
– 6.2 million USD for the remaining 5,000 residents expected to be served by June 2007.
• Additional cost of repairing the water infrastructure = 33 million USD
QUARRIESQUARRIES
QuarriesQuarriesMethodologyMethodology
• Pressure on quarrying activity to supply the needed aggregate and sand for reconstruction
• Adopted methodology– estimate the amount of aggregate and sand needed
for the reconstruction, based on the amount of debris and demolition waste;
– estimate the distribution of quarrying activities by Mohafazah;
– estimate the impact of quarrying activities during operation on the surrounding environment
– non-rehabilitating quarries after completion of exploitation on the surrounding environment
QuarriesQuarriesAggregate and Sand QuantitiesAggregate and Sand Quantities
• Based on the amount of debris and rubble generated by the hostilities
Location Aggregate and sand (m3)
Beirut
Demolition waste generated a 1,430,000
Of which agg & sand (35-50%) b 501,000 715,000
Of which concrete (35-50%) b 501,000 715,000
Equivalent in agg & sand c 356,000 508,000
Sub-total (i) 857,000 1,223,000
South and Bekaa
Demolition waste generated a 4,320,000
Of which agg & sand (30-40%) b 1,296,000 1,728,000
Of which concrete (40-60%) b 1,728,000 2,592,000
Equivalent in agg & sand c 1,227,000 3,568,000
Sub-total(ii) 2,523,000 3,568,000
Average sub-total (i)+(ii) 4,086,000
Total Aggregate & Sand (adding 15% loss of raw material at quarry) 4,700,000
QuarriesQuarriesAggregate and Sand QuantitiesAggregate and Sand Quantities
• Based on the amount of debris and rubble generated by the hostilities
Location Aggregate and sand (m3)
Beirut
Demolition waste generated a 1,430,000
Of which agg & sand (35-50%) b 501,000 715,000
Of which concrete (35-50%) b 501,000 715,000
Equivalent in agg & sand c 356,000 508,000
Sub-total (i) 857,000 1,223,000
South and Bekaa
Demolition waste generated a 4,320,000
Of which agg & sand (30-40%) b 1,296,000 1,728,000
Of which concrete (40-60%) b 1,728,000 2,592,000
Equivalent in agg & sand c 1,227,000 3,568,000
Sub-total(ii) 2,523,000 3,568,000
Average sub-total (i)+(ii) 4,086,000
Total Aggregate & Sand (adding 15% loss of raw material at quarry) 4,700,000
QuarriesQuarriesDistribution of Activities by MohafazaDistribution of Activities by Mohafaza
• Based on the number of short administrative extensions granted by the Ministry of Interior and Municipalities according to the council of ministers decision #6 dated January 4, 2007 – South & Nabathieh 32%– North & Akkar 24%– Bekaa &Baalback Hermel 31%– Mount Lebanon 14%
• Assuming the scale of excavation is evenly distributed, the distribution of aggregate and sand is as follows:– South & Nabthieh 1,494,000 m3
– North & Akkar 1,105,000 m3
– Bekaa &Baalback Hermel 1,447,000 m3
– Mount Lebanon 654,000 m3
– Total 4,700,000 m3
QuarriesQuarriesEnvironmental Impacts of Quarries in Environmental Impacts of Quarries in
Mount LebanonMount Lebanon• Threats to the environment
– Destruction of natural vegetation and habitat– Air pollution from dusts– noise pollution– traffic from trucks carrying aggregates– Deterioration of road condition– Irreversible long-term visual/aesthetic impact
• Hedonic Price Method previously conducted– 4 quarrying sites in Mount Lebanon
• the depreciation in real estate price resulting from quarrying activities for the Nahr Ibrahim quarry = 4 USD/m3 of extracted aggregate and sand
• the change in property price due to the non-rehabilitation of the three other quarries at the end of operation
– Land prices: 0.13 - 40.0 USD/m3 of extracted aggregate and sand– Apartment prices: 0.4 - 5.0 USD/m3 of extracted aggregate and sand
QuarriesQuarriesEnvironmental Impacts of Quarries in Environmental Impacts of Quarries in
Mount LebanonMount LebanonQuarry 1 Nahr Ibrahim (Impact during operation)Estimated quarry area (m2)a 96,830Estimated excavated volume (m3)b 4,115,000Land area affected by the quarry (m2)c 2,000,000Decline in Land price (US$/m2) in 2002c 7.0Decline in Land price (US$/m2) in 2006d 8.2Total decline in land price 2006 16,400,557Decline in land price US$/ m3 4.0
Quarry 3 Abu Mizan (Impact after closure)Estimated quarry area (m2) in 3 locationa 276,930Estimated excavated volume (m3)b 11,769,525Land Area affected by the quarry (m2)c 175,000Decline in Land price (US$/ m2) in 2002c 8Decline in Land price (US$/ m2) in 2006d 9Total decline in land price 2006 1,537,552Decline in land price US $/ m3 0.13
Quarry 2 Shnanaayer (Impact after closure)Estimated quarry area (m2) in 2 locations a 48,370Estimated excavated volume (m3)b 2,056,000Land Area affected by the quarry (m2)c 600,000Decline in Land price (US$/m2) in 2002c 125Decline in Land price (US$/m2) in 2006d 146Total decline in land price 2006 87,860,125Decline in land price US $/ m3 43Apartments affected by quarry (m2)c 36,000Decline in apartment price (US$/ m2) in 2002c 225Decline in apartment price (US$/ m2) in 2006d 264Total decline in apartment value 2006 9,488,894Decline in apartment value US$/m3 5
Quarry 4 Antelias (Impact after closure)Estimated quarry area (m2) in 1 location a 51,577Estimated excavated volume (m3) b 2,192,000Land Area affected by the quarry (m2) c 100,000Decline in Land price (US$/ m2) in 2002 c 50Decline in Land price (US$/ m2) in 2006 d 59Total decline in land price 2006 5,857,342Decline in land price US$/m3 3Apartments affected by quarry (m2) c 7,500Decline in apartment price (US$/ m2) in 2002 c 100Decline in apartment price (US$/ m2) in 2006 d 117Total decline in apartment value 2006 878,601Decline in apartment value US$/m3 0.40
QuarriesQuarriesRelative price of land and apartments Relative price of land and apartments
by Mohafazaby Mohafaza• Land and apartments prices compiled to derive
a price of land per Mohafazah– 90 districts in Mount Lebanon– 15 districts in the Bekaa– 41 districts in the North– 10 districts in the South.
Mohafazah Relative price of land (USD/m2)
Relative price of apartments(USD/m2)
Mount Lebanon 1 1Bekaa 0.19 0.58North 0.68 1.03South 1.11 0.99
QuarriesQuarriesImpact of quarrying activities for Impact of quarrying activities for
reconstructionreconstruction• Computed as if all impacts were to happen in
2006• Alternatively, the impact should have been
– spread over a few years and than discounted back to 2006 (using a 4% discount rate).
– taking into account the inflation rate (varying between 3.5 and 4.8%)
– Hence the overall impact is likely to have been the same as if it was computed for 2006 only
• Estimated overall damage15 - 175 million USD (average = 95.5 million USD)
QuarriesQuarriesImpact of quarrying activities for Impact of quarrying activities for
reconstructionreconstructionSouth & Nabatieh min max avg
Needed aggregate (million m3) 1.5
Impact during quarrying operation on land price (million US$) 6.6
Impact of non rehabilitating quarries on land price (million US$) 0.2 71.0 35.6
Impact of non rehabilitating quarries on apartment price (million US$) 0.6 6.8 3.7
Sub Total 46.0
North & Akkar min max avg
Needed aggregate (million m3) 1.1
Impact during quarrying operation on land price (million US$) 3.0
Impact of non rehabilitating quarries on land price (million US$) 0.1 32.3 16.2
Impact of non rehabilitating quarries on apartment price (million US$) 0.5 5.3 2.9
Sub Total 22.1
Bekaa & Baalback Hermel min max avg
Needed aggregate (million m3) 1.4
Impact during quarrying operation on land price (million US$) 1.1
Impact of non rehabilitating quarries on land price (million US$) 0.0 11.9 6.0
Impact of non rehabilitating quarries on apartment price (million US$) 0.3 3.9 2.1
Sub Total 9.2
Mount Lebanon min max avg
Needed aggregate (million m3) 0.7
Impact during quarrying operation on land price (million US$) 2.6
Impact of non rehabilitating quarries on land price (million US$) 0.1 27.9 14.0
Impact of non rehabilitating quarries on apartment price (million US$) 0.3 3.0 1.6
Sub Total 18.3
AIR POLLUTIONAIR POLLUTION
Air PollutionAir PollutionSources of PollutionSources of Pollution
• Dust from reconstruction sites and quarrying activities• Increased emissions from transport sector due to
reduced average speed in affected roads or highways• Emissions from burning of petroleum products (mainly
heavy fuel oil, kerosene, gasoline, and diesel)• Emissions from forest fires• Emissions from damaged industrial facilities• Emissions from exploded weapons and ammunitions.• Other sources of air pollution such as those generated
by waste disposal and burning of dead carcasses, rotten vegetables/fruits, municipal and health care waste
Air PollutionAir PollutionImpact AssessmentImpact Assessment
• Air pollution from site clearing and removal, hauling, transport, and disposal of demolition wastes in the Beirut Southern Suburbs– Estimated using the Fixed Box Model– Total Suspended Particulates (TSP) concentration range from
190 μg/m3 under typical scenario to 860 μg/m3 under worst-case scenario
– Both values exceed the Lebanese, EU, USEPA, and WHO 24-hour standards
• Emissions from the transport sector due to decrease in average vehicle speed – Estimated to increase by a factor of 6 to 7, particularly at
hotspots
Air PollutionAir PollutionImpact AssessmentImpact Assessment
• Air pollution from the burning of around 60,000 m3 (55,764 tonnes) of fuel oil at the Jiyeh Thermal Power Plant over a period of 12 days. – Generated pollutants
• sulfur dioxide, nitrogen oxides, carbon monoxide,soot, particulate matter, semi-volatile organic compounds including polycyclic aromatic hydrocarbons (PAHs) and dioxins and furans, volatile organic compounds, such as benzene, and other compounds resulting from incompletecombustion of the oil and oil products.
– Quantities of released pollutants were calculated– The generated plume trajectory was estimated using the ALOFT-FT (A Large
Outdoor Fire Plume Trajectory- for Flat Terrains) model– The model indicated that
• Particle concentrations at their highest concentrations near the pool of fire, reaching approximating 34 mg/m3 (vertical elevation 0 m).
• Concentrations drop to 217 –295 µg/m3 at 1 to 4 km downwind and vertical elevation of 695 m
• concentrations at 20 km downwind indicate a range of particulate concentrations between 21 and 29 µg/m3 (vertical elevations 780 m and 350 m respectively).
Air PollutionAir PollutionImpact AssessmentImpact Assessment
Pollutant Emission Factors Estimated Emissions
Sulfur dioxide (SO2) 40 g/kg 2.2 Gga
Nitrogen oxides (NOx) 5 g/kg 0.3 GgParticles 15 g/kg 0.8 GgSoot 5 g/kg 0.3 GgOrganic carbon 8 g/kg 0.5 GgPolyaromatic hydrocarbons (PAHs) 0.8 g/kg 0.04 Gg
Polychlorinated Dibenzodioxins (PCDDs)2.6 µg TEQ/TJb
6 mg TEQ
Volatile organic compounds (VOCs) 7 g/kg 0.4 Gg
Carbon Monoxide (CO) 5 g/kg 0.3 GgSource : UNDP, 2007 a 1 Gg = 1,000 tonnes; b TEQ/TJ = Toxic Equivalents/ Terajoule
Emission factors and estimated emissions from the Jiyeh oil fire
Air PollutionAir PollutionImpact AssessmentImpact Assessment
• Air pollution from the burning of 40,000 tonnes of kerosene at the Rafiq Hariri International Airport.
• Pollutants released include– nitrogen oxides, particulate matter,
formaldehyde, volatile organic compounds, and polycyclic aromatic hydrocarbons
– Quantities of released pollutants were calculated
– Generated plume trajectory was estimatedusing the ALOFT model• Particulate matter concentrations are at their highest concentrations
near the pool of fire, reaching almost 3.1 mg/m3 (vertical elevation 0 m)
• Concentrations drop to 30.3 µg/m3 at 3 km downwind and vertical elevation of 725 m.
• Concentrations at 20 km downwind indicate a range of particulateconcentrations between 1 µg/m3 and 3.2 µg/m3 (vertical elevations 260 m and 725 m respectively)
Air PollutionAir PollutionImpact AssessmentImpact Assessment
Emission factors and estimated emissions from the Airport tanks fire
Pollutant Emission Factors Estimated EmissionsNitrogen oxides (NOx) 11 g/kg 441 tonnesVolatile organic compounds (VOCs) 0.133 g/kg 5.3 tonnesCarbon Monoxide (CO) 2.8 g/kg 112 tonnesSulfur Dioxide (SO2) 4 g/kg 160 tonnesPM10 1.4 g/kg 56 tonnesPolychlorinated Dibenzodioxins (PCDDs) 4.3 x 10-9 172 mgMethane (CH4) 0.02 0.8 tonnes
Air PollutionAir PollutionImpact AssessmentImpact Assessment
• The impact of the burning of– 1,000 ha of forests in Mount Lebanon– 800 ha in South Lebanon– Main pollutants released
• particulate matters, carbon monoxide, total hydrocarbons or volatile organics, and nitrogen oxides
– Emissions estimated
Pollutant Emission Factors (kg/Mg)
Estimated Emissions (Mg)
PM10 8.5 88.1CO 70 725.6VOCs as methane 12 124.4NOx 2 20.7
Air PollutionAir PollutionHealth Impact AssessmentHealth Impact Assessment
• Much of the emissions are short-term and their impacts are hard to quantify
• PM the most significant remaining pollutant• Impacts include:
– Increase in cardiac and respiratory mortality– Decrease in levels of pulmonary lung function in children and adults with
obstructive airway disease– Increase in daily prevalence of respiratory symptoms in children and
adults– Increase in functional limitations as reflected by school absenteeism or
restricted activity days– Increase in physician and emergency visits for asthma and other
respiratory conditions• A task force formed by the NSCR, AUB, and USJ is monitoring
PM10 levels in the Southern suburbs during the reconstruction period.– Generally, the recorded levels are high, exceeding national and
international air quality standards
Air PollutionAir PollutionEconomic ValuationEconomic Valuation
• Data available for long-term exposure to increased ambient concentrations of PM10
• Extrapolation for short-term exposure is difficult
FOREST FIRESFOREST FIRES
Forest FiresForest FiresIntroductionIntroduction
• Impacts of hostilities on forests– direct impacts
• accidental fires, resulting from direct bombing or fallen flares
• deliberate fires from burning the land to clear unexploded ordnances
– indirect impacts• the occurrence of summer forest fires raging
unchecked because attention was focused on humanitarian ai
• the limited accessibility to and utility from unburnt forest sites where UXOs had not been cleared
Forest FiresForest FiresImpacts on forests Impacts on forests
• The best available estimate of burnt forest area during the 34 day hostilities = 2,930 ha– Assuming that most fires occur during the three-month summer
season, the area burnt during one month = 400 ha– The area burnt due to the hostilities = 2,530 ha
• Value of damages caused by forest fires depends on the value of the forest benefits lost.– Intensive fires may cause a complete loss of benefits – Lighter fires may cause only partial losses– The degree of damage and the period over which the impacts of
fires persist depend on the intensity of fires• No accurate information on these issues has been
reported for Lebanon• 10-20 years considered time-frame for forest regeneration
Forest FiresForest FiresImpacts on forests Impacts on forests
• Based on Sattout 2005 the total economic value of one hectare of forests is least 465 USD per year
• This is a high estimate because – it represents the
forests’ gross benefit, which is higher than their net benefit
– the valuation is based on the actual instead of the sustainable rate of extraction
– the limited forest area in Lebanon contributes to obtaining very high averages per hectare of forests
Types of values Quantity Value(000 $)
Value ($/ha)
Use valuesFirewood (m3) 82,300 2,011 15
Charcoal (m.t.) 11,400 2,011 15
Honey and wax n.s. 12,928 96
Pine nuts (t) 600 13,000 96
Medicinal and aromatic plants n.s. 17,717 130
Fodder for grazing (mil. FU) 9.6 1,022 8
Carob (t) 2,000 625 5
Hunting (no. hunters) 600,000 12,769 95
- Legal hunting 200,000 6,384 48
- Illegal hunting 400,000 6,384 48
Recreation in reserves (no. visits) n.s. 287 2
Non-use valuesBiodiversity conservation (ha) n.s. 919 7
TEV 63,300 465
Forest FiresForest FiresImpacts on forests Impacts on forests
• Because of high intensity of fires, it is assumed
– Forest benefits are completely lost in 2006
– Benefits will gradually recover within 10-20 years
– Benefits recover linearly– A discount rate of 4% is used
• The Present Value of losses on 1 hectare of burnt forest ranges between 2,200 – 3,700 USD
• The total damage on 2,540 ha of forests ranges between 5.6 – 9.4 million USD
• The cost of cleaning of burned broadleaves forest = 600 USD/Ha
0
50
100
150
200
250
300
350
400
450
500
1 3 5 7 9 11 13 15 17 19 21Years
annual lo
sses
of benefits
(US$/h
a)
The total damage on 2,540 ha of forests ranges between 6.4 – 10.2 million USD
Forest FiresForest FiresImpacts on protected areasImpacts on protected areas
• Al-Shouf Cedars Biosphere Nature Reserve affected– Decline in tourism activities and sales of local
products caused a loss of 150,000 USD– This impact affects the conservation effort of
protected areas in the near future
Forest FiresForest FiresImpacts on the National Reforestation Impacts on the National Reforestation
ProgramProgram• The MOE’s reforestation program impacted in several ways:
– direct impacts: • direct shelling and bombing leading to partial or total burning of the site• lack of access due to scattered UXOs
– indirect impacts• wilting of newly planted saplings because watering schedules were
interrupted• termination of all contracts• halting of maintenance of other areas (~ 360 ha) for 1.5 years until re-
contracting, thus losing saplings and a 5-year equivalent of forest benefits• At least 5 sites in the cazas of the South and Nabatiyeh were
impactedSite Caza Area (ha) Post-conflict statusMarwanieh South 15 Not assessed yet
Rihane South 20 At least 60% burnt
Markaba Nabatiyeh 15 At least 50% burnt
Khirbet Silem Nabatiyeh 15 Not assessed yet
Zawtar el Charkieh Nabatiyeh 15 100% burnt
Forest FiresForest FiresImpacts on the National Reforestation Impacts on the National Reforestation
ProgramProgram• The replacement cost method used
– the long-term benefits provided by forests will be higher than the costs of reforestation
– Damages to saplings on burnt areas• Each reforestation site has an average density of 750 saplings/ha and an
average total cost of US$6/sapling• All the saplings in South Lebanon died as a result of the hostilities, this loss
= 360,000 USD– Cleaning the burnt sites
• The MOE will incur the costs of cleaning broadleaved burnt sites• Assuming that burnt area covered by broadleaves is proportional to that at
national level (55%), i.e., about 44 ha• At a cost of US$600/ha, the cost of cleaning operations on burnt
broadleaved forests = 26,400 USD– Forgone forest benefits
• If the saplings planted in 2004 had continued growing, the resulting forest would have provided benefits earlier than any new planting will be able
• As the burnt stands were less than 2 years old when hostilities started, and assuming reforestation at these sites is undertaken relatively quickly (~5 years)
• The present value of the delayed forest benefits is probably relatively small
Forest FiresForest FiresImpacts on the National Reforestation Impacts on the National Reforestation
ProgramProgram• As burnt stands cannot be reforested for at least 5 years,
the forgone carbon credits are a potential damage to Lebanon in this period. – Average carbon increment is 1.3tC/ha of broadleaved and 0.8tC/ha
of conifers – 45% of forest area is coniferous and 55% is broadleaved– Assuming the same distribution of forest types on the 80ha and a
market price of US$42/tC, the annual damage due to carbon loss is about US$3,300.
– The present value of this loss for the next 5 years is about US$14,600.
• Overall, the replacement costs of burnt forests = US$401,000– This figure is conservative, as it does not include
• loss of access to forests because of UXOs• cost of cleaning UXOs• loss of forgone benefits during 5 years of halted reforestation, etc.
EEnd of nd of SSession ession 18a18a
Thank YouThank You
REGIONAL WORKSHOP REGIONAL WORKSHOP ONON
THE COST OF THE COST OF ENVIRONMENTAL ENVIRONMENTAL
DEGRADATION DEGRADATION METHODOLOGYMETHODOLOGY
Session 18bPOLICY IMPLICATIONS AND
CONCLUSIONS
REGIONAL WORKSHOP ONREGIONAL WORKSHOP ON
THE COST OF ENVIRONMENTAL THE COST OF ENVIRONMENTAL DEGRADATION METHODOLOGYDEGRADATION METHODOLOGY
Session 18bPOLICY IMPLICATIONS AND CONCLUSIONS
POLICY IMPLICATIONS AND POLICY IMPLICATIONS AND CONCLUSIONSCONCLUSIONS
Assess costs and benefits via environmental valuation
IntuitiveIntuitiveDecisionDecision--makingmaking
CalculatedCalculatedDecisionDecision--makingmaking
POLICY IMPLICATIONS AND POLICY IMPLICATIONS AND CONCLUSIONSCONCLUSIONS
• EIA– Quantifies and describes the physical impact of projects and
policies– Documents complexity of an environmental issue– Fails to help the decision-maker who has little knowledge of how
environmental changes affect the utility of the individual
• Environmental valuation– Gives the ‘true’ value of environmental resources to the society– Tends to remove ambiguity and vagueness in the decision-
making process
• Environmental valuation should NOT be applied– To maximize benefits in order to justify a policy– To minimize the estimated externality values of a project to
ensure its approval
POLICY IMPLICATIONS AND POLICY IMPLICATIONS AND CONCLUSIONSCONCLUSIONS
• Environmental impacts should be valued in monetary terms in order that they are given due and proper weight in the decision-making process
• The non-monetization of environmental impacts may mean that either they are under-valued or over-valued in the intuitive decision-making process
• Monetization will permit the comparison of various environmentalmanagement proposals
• Many studies revealed the inconsistency of intuitive decision-making compared with a more structured approach– The numerous cognitive psychological biases in intuitive decisions
renders rational choice problematic
POLICY IMPLICATIONS AND POLICY IMPLICATIONS AND CONCLUSIONSCONCLUSIONS
Setting priorities for decisionSetting priorities for decision--making in making in environmental management environmental management
• Priority setting is essential because of– Limited money– Limitless problems– Limited political and public attention– Limited time– Limited managerial time and attention
• It is essential to clearly identify and set priorities for action (& investments)
POLICY IMPLICATIONS AND POLICY IMPLICATIONS AND CONCLUSIONSCONCLUSIONS
Setting priorities for decisionSetting priorities for decision--making in making in environmental management environmental management
• Important questions– What criteria and approaches can be used to rank
environmental problems (and thus set priorities)?
– What are the advantages and limitations of different economic methods for defining priorities? (e.g. BCA, CEA, other methods [e.g. multicriteria approaches])
– What are the principles of and key lessons in environmental priority-setting?
POLICY IMPLICATIONS AND POLICY IMPLICATIONS AND CONCLUSIONSCONCLUSIONS
Setting priorities for decisionSetting priorities for decision--making in making in environmental management environmental management
• General principles for setting priorities for environmental investments/ policies – Narrow down the range of problems to be addressed
(the initial screening)
– Choose clear selection criteria with respect to types of impacts (e.g. economic, ecological, social, equity, others) and ranking or evaluating alternatives (BCA/ CEA/ MCA?)
– Consider both benefits and costs of any action/ intervention whenever possible
POLICY IMPLICATIONS AND POLICY IMPLICATIONS AND CONCLUSIONSCONCLUSIONS
Setting priorities for decisionSetting priorities for decision--making in making in environmental management environmental management
• Priority Setting in the real world– In a “first best” world all costs and benefits can be
valued in monetary terms and an economic efficiency criterion used to rank actions
– In a “second best” world all benefits cannot be valued and a cost-effectiveness criterion may be necessary (based on cost information)
– In a “third best” situation with little information, time or resources, qualitative ranking approaches are the best recourse
POLICY IMPLICATIONS AND POLICY IMPLICATIONS AND CONCLUSIONSCONCLUSIONS
A hypothetical exampleA hypothetical example-- setting priorities setting priorities for environmental interventions with for environmental interventions with
increasing levels of information increasing levels of information
• Collecting information takes time and costs money
• Public perceptions of what are priorities are not always well-informed
• Priorities often change with increased information• The challenge is to avoid wasting money
(resources), time, and political will
POLICY IMPLICATIONS AND POLICY IMPLICATIONS AND CONCLUSIONSCONCLUSIONS
A hypothetical exampleA hypothetical example-- setting priorities for setting priorities for environmental interventions with increasing environmental interventions with increasing
levels of information levels of information
Given this information, what is the priority area for investment/ intervention??
Parameter Impacts on economic growthAir quality mediumWater quality highWaste management mediumCongestion highNoise low
POLICY IMPLICATIONS AND CONCLUSIONSPOLICY IMPLICATIONS AND CONCLUSIONSA hypothetical exampleA hypothetical example-- setting priorities for setting priorities for
environmental interventions with increasing levels environmental interventions with increasing levels of informationof information
Adding information on distributional impacts: what is the priority now?? Problems and Issues:• How to compare a waste management project with a noise reduction one? Both rate “high”.• Weighting (emphasis) among the various problems may depend on political considerations.• It is possible to use experts’ opinion (Delphi technique) to identify degrees of impacts, and their relative importance to society.
Parameter Impacts on economic growth
Distributional impacts (equity concerns)
Air quality medium high
Water quality high high
Waste management medium high
Congestion high medium
Noise low high
POLICY IMPLICATIONS AND CONCLUSIONSPOLICY IMPLICATIONS AND CONCLUSIONSA hypothetical exampleA hypothetical example-- setting priorities for setting priorities for
environmental interventions with increasing levels environmental interventions with increasing levels of informationof information
Problems and Issues:
•It is necessary to define the spacial and time limits of the analysis:
• short-term vs. Long-term, • on-site vs. off-site, • financial analysis vs.
economic analysisWhat does “high” or “low”mean?
•Pollution can have different impacts:
• Productivity• Health• Recreation• Ecology
Which are the most important?
Parameter Impacts on economic growth
Distributional impacts (equity concerns)
Health effects
Air quality medium high high
Water quality high high high
Waste management
medium high medium
Congestion high medium low
Noise low high low
Adding health effects: do priorities change now??
POLICY IMPLICATIONS AND CONCLUSIONSPOLICY IMPLICATIONS AND CONCLUSIONSA hypothetical exampleA hypothetical example-- setting priorities for setting priorities for
environmental interventions with increasing levels of environmental interventions with increasing levels of informationinformation
• When information is qualitative, one can use multiple criteria approaches to rank problems:– Qualitative ranking of problems using Delphi-techniques where
quantitative data is unavailable.• Delphi is an expert-based, non- confrontational approach.
– Simple qualitative approaches rank problems by multiple criteria without using trade-off considerations
– Scoring and weighting of criteria offers a qualitative approach to evaluating the relative severity of problems
POLICY IMPLICATIONS AND CONCLUSIONSPOLICY IMPLICATIONS AND CONCLUSIONSA hypothetical exampleA hypothetical example-- setting priorities for setting priorities for environmental interventions with increasing environmental interventions with increasing
levels of informationlevels of information
Parameter Impacts on economic growth
Distributional impacts (equity concerns)
Health effects
Annual management costs
Air quality medium high high 1000
Water quality high high high 800
Waste management
medium high medium 900
Congestion high medium low 1500
Noise low high low 1200
When economic data on costs are available to help identify priorities for action:Cost-effective analysis (CEA) is used
POLICY IMPLICATIONS AND CONCLUSIONS POLICY IMPLICATIONS AND CONCLUSIONS A hypothetical exampleA hypothetical example-- setting priorities for setting priorities for environmental interventions with increasing environmental interventions with increasing
levels of informationlevels of information
Parameter Impacts on economic growth
Distributional impacts
Health effects
Annual management
costs
Annual benefits
Annual Net Benefits (benefits
minus costs)
Air quality medium high high 1000 1300 300
Water quality high high high 800 900 100
Waste management
medium high medium 900 1150 250
Congestion high medium low 1500 1300 (200)
Noise low high low 1200 1100 (100)
Conduct the full Benefit Cost Analysis when both benefits and costs are known
POLICY IMPLICATIONS AND CONCLUSIONSPOLICY IMPLICATIONS AND CONCLUSIONSSelecting the appropriate valuation technique Selecting the appropriate valuation technique ––
a valuation flow charta valuation flow chart Environmental Impact
Measurable change in production
Change in environmental quality
Yes
Nondistorted market prices available?
Use change-in-productivity approach
Use surrogate market approaches, apply shadow prices to changes in production
Yes No
Habitat
Opportunity-cost approach
Replacement cost approach
Land value approaches
Contingent Valuation
Air and water quality
No
Cost-effectiveness of prevention
Preventive expenditure
Replacement/ relocation costs
Health effects
Sickness Death
Medical costs
Loss of earnings
Human capital
CEA of prevention
Recreation
Contingent valuation
Travel cost
Aesthetic, Biodiversity, Cultural, Historical assets
Contingen Valuation
Contingent Valuation
Hedonic wage approach
Contingent Valuation
POLICY IMPLICATIONS AND POLICY IMPLICATIONS AND CONCLUSIONSCONCLUSIONS
The Limits of Economic AnalysisThe Limits of Economic Analysis
• Areas where economic analysis is often weak include the following:– Incremental impacts– Uncertainty (especially with regards to the future)– Irreversible impacts– The value of genetic material (or biodiversity)– Preferences of future generations (and projects with
long time horizons)– Distributional effects across social sectors
POLICY IMPLICATIONS AND POLICY IMPLICATIONS AND CONCLUSIONSCONCLUSIONS
• Much can be done with the available tools of economic analysis at both the macro and micro level
• Both environmental policies and investment projects can be analyzed using the tools of environmental economics
• The hard valuation areas (e.g. recreational demand, cultural values, genetic materials, biodiversity, others) are also often the same things that we care the most about in the environment
POLICY IMPLICATIONS AND POLICY IMPLICATIONS AND CONCLUSIONSCONCLUSIONS
• Factors for limited use of environmental values in decision-making– Skepticism towards environmental valuation methods– Lack of environmental economists within government agencies– Absence of a legal requirement to undertake a CBA of projects
or policies– Uncritical acceptance of other methods such as
• Effect on production• Dose response• Opportunity cost approaches
– Suspicion of non-use values– Distorted perceptions of the valuation methods by non-
economist– Large variance associated with mean WTP and WTA values
POLICY IMPLICATIONS AND POLICY IMPLICATIONS AND CONCLUSIONSCONCLUSIONS
Prevailing Situation• Environmental values are less routinely
incorporated into policy and project appraisal in a systematic way
• Environmental changes tend to be assessed through EIAs in the US and EU rather than through economic valuation and CBA
• The World Bank and the Asian Development Bank advocate the use of valuation methods to estimate the welfare effects of environmental changes
POLICY IMPLICATIONS AND POLICY IMPLICATIONS AND CONCLUSIONSCONCLUSIONS
Prevailing Situation• Environmental valuation studies in different European
countries were undertaken spasmodically with varying degrees of influence on decisions and with marked variations between countries– Switzerland
• Highest number of academic/ scientific studies employing TCMs, HPMs, CVMs
– Germany• Proportionately fewer and more policy oriented
– UK• Shift away from TCMs to HPMs and CVMs due to nature of goods
being valued– Netherlands
• Demand for valuation studies by governments and organizations is low– Norway
• Benefit estimation studies provided support for environmental decision-making but had not played a crucial role in the process
POLICY IMPLICATIONS AND POLICY IMPLICATIONS AND CONCLUSIONSCONCLUSIONS
Prevailing Situation• In some cases the environmental valuation process is formalized
and fairly explicit and institutionally incorporated in the decision-making process– US Forest Service
• Application of ‘unit day values’ of recreational opportunities and resources
– CERCLA• Type A assessment of natural resource damage from pollution spills
– Using an existing economic database• Type B assessment for major pollution incidents
– Requires a site specific investigation
– US Department of Interior authorized methods for environmental valuation
• Market price where applicable• Uniform Appraisal Standards for Federal Law Acquisition• Use values may be measured via
– TCM, HPM, unit values, CVM, and stated preference techniques• Non-use values may only be measured via
– CVM and SP
POLICY IMPLICATIONS AND POLICY IMPLICATIONS AND CONCLUSIONSCONCLUSIONS
The future
• Environmental valuation will witness a search for – More accurate and robust semi- and non-parametric estimators– Improved understanding of the psychology of making choices
and decisions– The analysis of the non-stationarity of environmental values– The application of other theories and techniques from other
branches of economics• Bayesian perspectives• Game theory
• Desire to establish formal benefit transfer methods by governments and agencies
• Advocacy of the use of benefit transfer by organizations
Environmental valuation methods becoming• more institutionalized•more routinely included in CBAs
POLICY IMPLICATIONS AND POLICY IMPLICATIONS AND CONCLUSIONSCONCLUSIONS
• Effort should be directed in the MENA region to – Increase awareness on environmental valuation– Build capacity on COED methodology– Institutionalize COED methodology in decision-
making process– Establish a database for environmental valuation
studies in the region
• Various databases on environmental valuation could be of help
POLICY IMPLICATIONS AND POLICY IMPLICATIONS AND CONCLUSIONSCONCLUSIONS
Name of database
Web host Purpose of the database Number of studies
Regions covered
Available languages
Environmental Valuation Reference Inventory
Environment Canada on behalf of the EVRI Club1 http://www.evri.ca
To help policy analysts using the benefits transfer approach to estimate economic values for changes in environmental goodsand services or human health
1,500 International English,French
Envalue New South WalesEnvironment Protection Authority http://www.epa.nsw.gov.au/envalue
To help stakeholders value changes in environmental quality
400 International English
Ecosystem Services Database
Gund Institute forEcological Economics, University of Vermonthttp://esd.uvm.edu
To provide a data and analysis portal to assist in the informed estimation of the economic values of ecosystem services
300 International English
Review of Externality Data
European Commissionhttp://www.red-externalities.net
To assist policy makers in capturing the effects of externalities from new policies that have sustainable development as their core concern
200 International English
Main features of selected valuation databases (McComb et al, 2006)
POLICY IMPLICATIONS AND POLICY IMPLICATIONS AND CONCLUSIONSCONCLUSIONS
Name of resource Web host Database purpose Overview
New Zealand Non-market Valuation Database
Lincoln University, Canterbury, New Zealandhttp://oldlearn.lincoln.ac.nz.markval
To help researchers identify nonmarket valuation studies undertaken in New Zealand
Searchable database with 100 primary studies from New Zealand
ValuebaseSwe Beijer International Institute of Ecological Economics, and the Swedish Env. Protection Agency http://www.beijer.kva.se/valuebase.htm
To provide a survey of empirical economic valuation studies on environmental change in Sweden
Database with 200 primary studies from Sweden
Beneficial Use Values database
Department of Agricultural and Resource Economics, University of California, Davis http://buvd.ucdavis.edu/
A guide for decision makers, policy analysts, and others interested in valuation of water resources
Database of economic values for beneficial uses of water. Varietyof sources
Sportfishing Values database
Industrial Economics, Incorporated under contract to the U.S. Fish and Wildlife Servicehttp://www.indecon.com/fish/default.asp
To provide a detailed account of the contents of numerous recent non-market valuation studies
One hundred non-market valuation studies of sports fishing activity
Main features of selected valuation databases (McComb et al, 2006)
POLICY IMPLICATIONS AND POLICY IMPLICATIONS AND CONCLUSIONSCONCLUSIONS
Name of resource
Web host Database purpose Overview
Biodiversity Economics
IUCN-The World Conservation Union and WWF http://www.biodiversityeconomics.org/
To encourage and assist in the use of economics in support of biodiversity conservation and sustainable development
Library of 100 non-market environmental valuation studies and a host of others on incentives, and business and consumer relations
National OceanEconomics Project (NOEP)
U.S. National Oceanic and Atmospheric Administration http://noep.csumb.edu/
The creation and distribution to the public of a spatially and temporally consistent data set that will support a wide range of economic, scientific and resource management activities
Library of 200 non-market valuation studies and a database of market values from around the world
Ecosystem valuation
D. King (U. of Maryland) and M. Mazzotta (U.of Rhode Island), funded by the U.S. Department of Agriculture and National Oceanographic and Atmospheric Administration, U.S. http://www.ecosystemvaluation.org
For non-economists who need answers to questions about the benefits of ecosystem conservation, preservation or restoration
Clear, non-technical description of ecosystem valuation concepts, methods and applications
Environmental damagevaluation and cost-benefit news
Editor and Publisher: Kenneth Acks http://envirovaluation.org/
Newsletter on valuation of environmental damages
Legal, academic, and regulatory developments pertaining to the valuation of environmental amenities and disamenities
Main features of selected valuation databases (McComb et al, 2006)
EEnd of nd of SSession ession 18b18b
Thank YouThank You
Regional Training Workshop on the Cost of Environmental Degradation Methodology July 1‐5, 2008 Crowne Plaza Hotel, Beirut, Lebanon
LIST OF PARTICIPANTS
Name Country Position Institution Email Phone
1. Abboud, Mazen
Lebanon President Union of the Northern Associations for Development, Environment and Patrimony
[email protected] Phone: +961 5467128 Mobile:+961 3283642
2. Abdul Samad, Lama
Lebanon Environmental specialist
COSV ‐ Lebanon [email protected] [email protected]
Phone: +961‐5‐452 838 Mobile:+961‐3‐937 950
3. Akl, Georges
Lebanon Forest engineer Ministry of Environment [email protected] Phone: +961‐1‐976 555 Ext. 452 Mobile: +962‐3‐614 303
4. Al Daia, Roula
Lebanon Acting director Institute of the environment‐ Environmental economics program‐ University of Balamand
[email protected] Phone: 961‐930250 ext. 3966 Mobile: 961‐3‐152 726
5. Al‐Oran, Raeda Jordan Environmental officer
Ministry of Municipal Affairs, Regional Planning Department, Project Management Team of the Regional and Local Development Project (RLDP)
[email protected] Phone: +962 6 5235585 Mobile:+962 795059649
6. Asfour, Feras
Syria Head of Planning Section
Ministry of Local Administration and Environment
ferasenv@scs‐net.org Phone: +963‐11 4465905 Mobile: +963‐944‐380810
7. Batta, Shareef
Jordan/ West Bank
Director of internal auditing
Environmental Quality Authority/ Palestine
[email protected] [email protected]
Phone: +970 599674797‐Palestine Phone: +962 53992179‐ Jordan
8. Beainy, Nada
Lebanon Program Officer Italian Cooperation ‐ Lebanon [email protected] Phone: +961‐5‐451494 Mobile:+961‐3‐909 744
Regional Training Workshop on the Cost of Environmental Degradation Methodology July 1‐5, 2008 Crowne Plaza Hotel, Beirut, Lebanon
Name Country Position Institution Email Phone
9. Bou Jawdeh, Issam
Lebanon Consultant Self‐Employed [email protected] Phone: +961‐4‐808 097
10. Chaabi, Ali
Tunisia Sub‐director Ministry of Agriculture‐ Office de developpment SYLVO‐PASTORAL DU NORD OUEST
[email protected] Phone: 216 78 655 810 Mobile: 216 98 500 920
11. El Hajj, Rana
Lebanon Project Coordinator AFDC [email protected] Phone: 961 1 752670 Mobile: 961 3 404625
12. El‐Shalakamy, Mohamed
Egypt Environmental Specialist & EPAP PMU staff
Egyptian Environmental Affairs Agency
[email protected] Phone:+202 22723172 Mobile: +201 01011235
13. Fanous, Ramzi
Lebanon Statistician Ministry of Environment [email protected] Phone: +961‐1‐976 555 ext. 459 Mobile: +961‐3‐594 283
14. Ghanimeh, Sophia
Lebanon Instructor and PhD candidate
Notre Dame University, Faculty of Engineering
[email protected] Mobile: +961‐3‐874 380
15. Ghannouchi, Sana
Tunisia Ingénieur principal Observatoire Tunisien de l'Environnement et du Développement Durable
[email protected] Phone: +216 22 519 725
16. Ghosn, Sabine
Lebanon Engineering Management Specialist
Ministry of Environment [email protected] Phone: +961‐1‐976 555 ext. 437 Mobile: +961‐3‐740 171
Regional Training Workshop on the Cost of Environmental Degradation Methodology July 1‐5, 2008 Crowne Plaza Hotel, Beirut, Lebanon
Name Country Position Institution Email Phone
17. Hakimi, Abdurrahman
Libya METAP National Focal Point
Environment General Authority (EGA)
[email protected] Mobile: +218 21 3612836
18. Hassan, Mahgoub
Sudan National environmental expert
Ministry of Environment and Physical Development
[email protected] Mobile: +249912310284
19. Higazy, Mamdouh
Egypt Environmental specialist & EPAPII‐ PMU staff
Egyptian Environmental Affairs Agency
[email protected] Phone: +202 26355507 Mobile: +201 01583878
20. Lichaa El‐Khoury, Dany
Lebanon Environmental & land use planning expert
[email protected] Mobile:+961‐3‐858 943
21. Mawla, Darine
Lebanon Environmental Specialist
[email protected] Phone: +961‐4‐531173 Mobile: 961 3 682147
22. Mitri, Ghada
Lebanon Development Specialist
Ministry of Environment [email protected] Phone: +961‐1‐976 555 ext. 435 Mobile: +961‐3‐562 441
23. Nasr, Raoul
Jordan Agricultural Economist
Jordan University of Science and Technology, College of Agriculture
[email protected] Phone: +962‐2‐7201000 ext 22242 Mobile: +962‐79‐5580296
24. Omeira, Nada
Lebanon Member Green Line Association [email protected] Phone: +961‐1‐746 215 Mobile: +961‐3‐351 821
Regional Training Workshop on the Cost of Environmental Degradation Methodology July 1‐5, 2008 Crowne Plaza Hotel, Beirut, Lebanon
Name Country Position Institution Email Phone
25. Rachid, Grace
Lebanon Environmental specialist
Ministry of Environment [email protected] Phone: +961‐1‐976 555 ext. 510 Mobile: +962‐3‐947 341
26. Roukoz, Salim
Lebanon Engineer Ministry of Agriculture [email protected] Phone: +961‐1‐849 623 Mobile: +961‐3‐665 719
27. Saliba, Salah
Lebanon Coordination officer UNDP / UNRC [email protected] Phone: +961‐9‐932 650 Mobile:+961‐3‐318 093
28. Sattout, Elsa
Lebanon Environmental specialist
[email protected] Mobile: +961‐3‐601767
29. Slika, Marwan
Syria Ministry of Local Administration and Environment, General Commission for Environment Affairs
[email protected] Phone: +963‐11 4465905 Mobile: 0932215790
30. Shatnawi, Malak
Jordan Head of section Cities and villages development bank
[email protected] Phone: +962 6 5682690 Mobile:+962 777787110
31. Al Duaij, Samia Kuwait Operation analyst METAP [email protected]
Regional Training Workshop on the Cost of Environmental Degradation Methodology July 1‐5, 2008 Crowne Plaza Hotel, Beirut, Lebanon
AUB and World Bank teams
Name Country Position Institution Email Phone
32. Bou Fakhreddine Raja
Lebanon Environmental consultant
American University of Beirut rboufaldeen@sets‐lb.com Mobile: +961‐3‐575 229
33. Chaaban, Jad
Lebanon Assistant Professor American University of Beirut [email protected] Phone: +961‐1‐350 000 Ext. 4067
34. Dobardzic, Saliha
METAP Officer World Bank [email protected]
35. Doumani, Fadi
Lebanon Economist METAP consultant [email protected] Phone: +12022232623 Mobile: +12022151722
36. El‐Fadel, Mutasem
Lebanon Professor American University of Beirut [email protected] Phone: +961‐1‐350 000 Ext. 3470 Mobile: +961‐3‐228 338
37. Hindi, Khalil
Lebanon Professor American University of Beirut [email protected] Phone: +961‐1‐350 000 Ext. 3950
38. Jamali, Dima
Lebanon Associate professor American University of Beirut [email protected] Phone: +961‐1‐350 000 Ext. 3727
39. Lotayef, Dahlia
METAP Coordinator World Bank [email protected]
40. Maroun, Rania
Lebanon Environmental consultant
American University of Beirut rmaroun@sets‐lb.com Mobile: +961‐3‐396 318
41. Nuwayhid, Iman
Lebanon Professor American University of Beirut [email protected] Phone: +961‐1‐350 000 Ext. 4627
42. Salti, Nisreen
Lebanon Assistant Professor American University of Beirut [email protected] Phone: +961‐1‐350 000 Ext. 4068