Working paper 15/2014 Research Project€¦ · urban agglomerations with populations over 10 million, and a ... studies, the research can then develop scenarios of sustainable urban

Megacities: comparative analysis of urban macrosystems

Iain STEWART, Chris KENNEDY, Angelo FACCHINI

Working paper 15/2014

Research Project

Metabolism of megacities:

a review and synthesis

of the literature

Enel Foundation Working paper 15/2014

Research project

Megacities: comparative analysis of urban macrosystems

Metabolism of megacities:

a review and synthesis

of the literature

Iain STEWART1, Chris KENNEDY

1, Angelo FACCHINI2

1University of Toronto, Department of Civil Engineering

2Enel Foundation

ISSN 2282-7188 (Printed Version)

ISSN 2282-7412 (Online Version)

Acknowledgements

Working paper of the research project ‘Megacities: Comparative analysis of urban macrosystems, jointly undertaken

by University of Toronto and Enel Foundation.

Metabolism of megacities: a review and synthesis of the literature

2

Research project

Megacities: comparative analysis of urban

macrosystems

By 2020, there will be an estimated 38 megacities on this planet, with a combined population

of approximately 685 million people. Compared to 2010, this constitutes an addition of 12

urban agglomerations with populations over 10 million, and a 50 % increase in the total

population of megacities. The majority of the world’s current and future megacities are in

developing regions of the world, particularly in Asia. The development challenges that these

megacities face in an era of climate change are immense. In spite of their huge populations,

the multi-jurisdictional governance structures of megacities have thwarted comparative study

and understanding of these urban regions. The resource flows into megacities, and the wastes

produced, likely have environmental impacts on a planetary scale. Unlike nations, however,

the quantification of resource and waste flows associated with these massive urban regions is

rarely undertaken. Lack of such data on the world’s megacities may significantly hamper policy

development; therefore, research seeking to understand the sustainable development of

megacities is critical.

The research project has two main objectives, to be addressed in two phases:

1. Conduct urban metabolism (UM) studies of a selected number of the world’s current

megacities, collecting data on a small number of UM parameters, specifically energy (all

sources), water, materials and waste flows. From such data it will be possible to identify

a set of general biophysical characteristics that are independent of the specific urban

system, and that can be used to compare megacities (one example of a biophysical

characteristic is population density, which is known to impact, among others,

transportation energy use). In conducting the UM studies, particular focus will be given

to the role of utilities (electricity, natural gas, water, etc.), and how they can affect the

urban metabolism.

2. Conduct more detailed analysis of the UM of 5 megacities, including extension to

appropriate socio-economic sustainability indicators. For these more detailed UM

studies, the research can then develop scenarios of sustainable urban evolution, as well

as outlining a more general roadmap to sustainable urban development. In this second

phase, the objective is to extend the analysis beyond the biophysical UM to include

measures of quality of life and other social indicators. The scenarios will then assess the

future role of utilities in megacities looking, for example, at how integrated

infrastructure solutions, electric mobility and energy efficiency can impact the UM and

quality of life in megacities.

This publication is the third working paper of the research project: "Megacities: comparative

analysis of urban macrosystems".


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Table of Contents

Abstract .......................................................................................................... 5

Introduction.................................................................................................... 6

1 Methods .................................................................................................... 8

2 Review of the urban metabolism literature ............................................. 10

2.1 Europe ................................................................................................ 10

2.1.1 London .......................................................................................... 10

2.1.2 Paris .............................................................................................. 10

2.2 Russia ................................................................................................. 11

2.2.1 Moscow .......................................................................................... 11

2.3 North America ...................................................................................... 12

2.3.1 New York City ................................................................................. 12

2.3.2 Los Angeles .................................................................................... 13

2.4 Middle America ..................................................................................... 13

2.4.1 Mexico City ..................................................................................... 13

2.5 South America ...................................................................................... 14

2.5.1 Rio de Janeiro ................................................................................. 14

2.5.2 São Paulo ....................................................................................... 15

2.5.3 Buenos Aires .................................................................................. 15

2.6 Sub-Saharan Africa ............................................................................... 16

2.6.1 Lagos ............................................................................................ 16

2.7 North Africa / Southwest Asia ................................................................. 16

2.7.1 Cairo ............................................................................................. 16

2.7.2 Tehran ........................................................................................... 18

2.7.3 Istanbul ......................................................................................... 18

2.8 South Asia ........................................................................................... 19

2.8.1 Dhaka ............................................................................................ 19

2.8.2 Karachi .......................................................................................... 20


4

2.8.3 Delhi ............................................................................................. 20

2.8.4 Mumbai .......................................................................................... 21

2.8.5 Kolkata .......................................................................................... 22

2.9 Southeast Asia ..................................................................................... 23

2.9.1 Manila ............................................................................................ 23

2.9.2 Jakarta .......................................................................................... 23

2.10 East Asia ............................................................................................. 24

2.10.1 Seoul ............................................................................................. 24

2.10.2 Tokyo ............................................................................................ 24

2.10.3 Osaka ............................................................................................ 25

2.10.4 Beijing ........................................................................................... 25

2.10.5 Shanghai ........................................................................................ 26

2.10.6 Guangzhou ..................................................................................... 28

2.10.7 Shenzhen ....................................................................................... 28

3 Global synthesis of the urban metabolism literature ............................... 29

4 Closing remarks ...................................................................................... 34

References .................................................................................................... 35


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Abstract

In the past half-century, megacities of more than 10 million people have become a global

phenomenon. The need for urban metabolism studies in these giant cities is critical because

they consume a disproportionate share of the world’s resources. However, the full extent to

which the urban metabolism has been documented in megacities is largely unknown.

In this paper, we take stock of the metabolism literature in megacities and search for

geographical and historical themes therein. We procured more than 100 English-language

studies on the energy, material, waste, and water flows in the world’s biggest cities, and

through review and synthesis of this work, we extracted three generalizations. First, the

metabolism of megacities has been investigated for changes across temporal scales (diurnal,

monthly, annual), which testifies to the dynamic nature of urban energy and material flows.

Second, the metabolism of megacities is equally well documented for changes across spatial

scales (local, regional, global), revealing disparities in resource flows and quality of life within

and among megacities. Third, literature on the metabolism of megacities in low/middle income

regions is characteristically recent, with much of the research produced in the past 10 years

and focused primarily on municipal solid waste. The role of the informal sector to help reduce

solid waste flows is an important subtheme of that literature. This review will enhance

understanding and awareness of the urban metabolism — especially in low/middle income

regions—and help to facilitate research into sustainable urban development in megacities.

Keywords: urban metabolism, megacity, energy, utilities

JEL Codes: Q4,L94,L95,L98

Corresponding Author

Chris Kennedy

University of Toronto

Department of Civil Engineering

35 St. George Street

Toronto, ON.

CANADA M5S 1A4

Email: [email protected]

Disclaimer

The findings, interpretations and conclusions expressed in this publication are those of the author and do not

necessarily reflect the positions of Enel Foundation and University of Toronto, nor does citing of trade names or

commercial processes constitute endorsement.


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Introduction

Literature on the urban metabolism has grown steadily since the first study of energy and

material flows by Abel Wolman in 1965. His study highlights the serious environmental

conditions in U.S. cities in the 1960s, and inspired many similar investigations of urban

metabolism worldwide. Coincident with this growth in metabolism literature has been the

emergence of ‘megacities’ as a global phenomenon. Since 1970, the number of ‘megacities’—

or urban agglomerations of more than 10 million people—has grown from 7 to 27 (based on

Thomas Brinkhoff’s Major Agglomerations of the World). The implications of this growth are

alarming, especially when one considers the flows of energy, water, waste, and materials

through these cities, and their effects on greenhouse gas (GHG) emissions, urban

sustainability, and quality of life (Newman, 1999; Kennedy et al., 2007). Metabolism studies

are therefore critically needed in all megacities.

An early step to meet this need is to review existing work on the metabolism of megacities,

and in particular the quantification of energy, water, and material inputs, as well as waste

outputs. The full extent of that work has never before been assessed. Standard reviews of

urban metabolism literature have been conducted by Decker et al. (2000), Sahely et al.

(2003), Kennedy et al. (2007), Kennedy et al. (2011), Broto et al. (2012), and Zhang (2013).

Decker et al. conducted a lengthy review of the available data and models on urban

metabolism in the world’s 25 biggest cities.

Few primary data on the actual material and energy flows of those cities were reported, and

the authors concluded that such data are scarce at the city level. Sahely et al. (2003) and

Kennedy et al. (2007) described a small selection of well-known urban metabolism studies,

while Kennedy et al. (2011) surveyed the growth of urban metabolism literature through the

1970s, 80s, and 90s. Broto et al. (2012) explored various interdisciplinary approaches and

perspectives on the study of urban metabolism. Zhang (2013) summarized the metabolism

literature from its historical roots and reviewed research methodologies commonly used in

urban metabolism studies.

The objective of this working paper is to review and synthesize literature on the metabolism of

megacities, and to locate relevant data to support the metabolism surveys of Working Paper

2/2014 (An urban metabolism survey design for megacities). The review covers widely cited

studies of urban metabolism in megacities, as well as lesser-known works of consultants,

government departments, and local researchers.

It describes current knowledge on the subject and reveals overarching patterns and trends in

the metabolism of megacities. Generalizations to emerge from this work are expected to

improve understanding of water, waste, energy, and material flows and their relations to the

unique physical, historical, political, geographical, and socio-economic milieu of megacities.


7

This study is the first to give comparative review of these flows and relations, and to

synthesize a body of literature that accounts for the interconnections of the urban metabolism

in the world’s biggest cities. In doing so, it brings circumspection to the social and

environmental issues facing megacities today.

From the quantities of flows documented in these mega-systems, we can anticipate their

metabolic responses to a range of human and natural forces, such as change in land use, built

form, wealth accumulation, weather and climate, and environmental and political stability.

These changes may come gradually, as with global warming or urban re-design, or abruptly in

the case of natural disasters or breakouts of war.

This working paper is organized into three main chapters. Chapter 1 provides the

methodological framework to retrieve and review the literature on urban metabolism of

megacities. Chapter 2 provides analytical discussion of the literature, and gives historical and

geographical perspectives on topics related to waste, water, energy, and material flows in the

world’s 27 megacities. Lastly, Chapter 3 provides a global synthesis and overview of the

metabolism literature, and identifies the main themes to emerge from this work.


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Los Angeles

Mexico City

Sao Paulo

Buenos Aires

Tokyo

Osaka

Guangzhou

Paris

London

Tehran

Cairo

Mumbai

Dhaka

Seoul

Moscow

Lagos

Rio de Janeiro

Kolkata

Delhi

Manila

Jakarta

New York City BeijingIstanbul

Shenzen

North America

Middle America

South America

Sub-Saharan Africa

North Africa / Southwest Asia

Europe

Russia

South Asia

East Asia

Southeast Asia

0°

30°N

30°S

0°

30°N

30°S

Karachi Shanghai

1 Methods

The world’s 27 megacities were classified into ‘geographic realms,’ defined by de Blij and

Muller (2003) as the largest spatial units into which the human world can be divided while

preserving their regional identity and distinctiveness. This framework allows regional themes

and patterns to emerge from the metabolic characteristics of the 27 megacities. The majority

of megacities are located at low latitudes and within the four Asian realms (Figure 1).

FIGURE 1 - Global distribution of megacities among the world’s geographic realms

Source: own elaboration

The literature review proceeded through a logical search strategy. Key word searches for

relevant citations were performed in standard indexes and bibliographic databases in the

English language. ‘Ancestry searches’ of reference lists in books, journal articles, conference


9

proceedings, and government documents led to additional citations for review. Subject key

words were targeted to specific areas of urban metabolism, such as “energy use”, “water

consumption”, “solid waste management”, “GHG emissions” and “urban sustainability”. Online

searches returned many hundreds of study titles and article abstracts. Strict eligibility criteria

were therefore necessary to keep the review to a workable size and coherent aim. The review

was restricted primarily to scholarly journal articles, government publications, and consultant

reports whose principal aim is to assess and account for the flows and stocks of urban

metabolism in one (or more) megacity, and to report those results at city scale. This criterion

excludes studies employing other research methodologies to investigate the urban metabolism,

such as computer model simulations and theory-based process analyses. “Fugitive” works such

as conference papers, interim reports, society newsletters, and unpublished manuscripts were

sought only if searches of the aforementioned sources were unsuccessful, or if the fugitive

studies contained reliable data to supplement the metabolism surveys of Working Paper

2/2014. If the search was unable to find a study of urban metabolism that accounted for all or

most of the aggregate flows and stocks of energy, water, materials, and waste in a particular

megacity, then it went further to retrieve works on single flows (or specific elements) of urban

metabolism in that city. Books, theses, dissertations, and other monographic works were

excluded from review, as were foreign-language publications.

In addition to the metabolism literature defined by these criteria is a subset of studies that

examines GHG emissions and energy use across multi-city datasets. These studies are not

cited in the main body of this review but are mentioned here because they implicate the

metabolic flows of energy and water in megacities, and contain valuable information for urban

metabolism studies. Sovacool and Brown (2010) compared the carbon footprints of 12

metropolitan areas including the megacities of Beijing, Jakarta, London, Los Angeles, Manila,

Mexico City, New Delhi, New York, São Paulo, Seoul, and Tokyo. The World Energy Council

published a comprehensive report on urban-related energy challenges that all megacities face

in the coming decades. Case studies were prepared for London, Paris, Mexico City, Delhi,

Shanghai, and Tokyo, and each study includes data on energy consumption and GHG

emissions. Specific aspects of the urban metabolism were quantified in a study of GHG

emissions in the megacities of London, Los Angeles, and New York by Kennedy et al. (2009),

whose inventory approach shows the direct influence of urban metabolism (e.g., heating,

transportation, waste) on GHG emissions, and the variance of such emissions among global

cities. Butler et al. (2008) estimated the local pollutant emission profiles of 32 large cities, 25

of which are featured in this paper. A World Bank study of urban metabolism by Hoornweg et

al. (2012) examined the megacities of Rio de Janeiro, São Paulo, Buenos Aires, Manila, and

Beijing. As part of the World Bank’s urban metabolism program, that study is the first to

develop a standardized, abbreviated framework for metabolism reporting. Surveys in each

megacity include components of inflow (e.g., food, water, construction materials, fossil fuels,

electricity, and solar radiation), storage (construction materials, wastes), and outflow (wastes,

recyclables, atmospheric pollutants).


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2 Review of the urban metabolism literature

2.1 Europe

2.1.1 London

The Chartered Institute of Waste Management conducted a comprehensive urban metabolism

study of London in 2002 (IWM, 2002). It was the first investigation of its kind in London.

Energy and material flows are quantified and cataloged for the year 2000. Estimates of urban

metabolism are then calculated for direct energy (consumption of electricity, gas, liquid fuel,

oil, renewable energy, coal, and emissions of CO2); material flows (minerals, metals, wood,

and other raw materials); discarded waste (by type and sector); food consumption (by type);

water consumption (by sector); transport (rail, car, air, bus, other); and land usage. No

significant gaps in waste flow data are reported, although material reporting is incomplete for

sectors other than construction. Little or no data are reported for material flows of glass,

plastics, or timber, while data for other materials were scaled from regional and national

datasets. No attempt was made to access direct energy consumption data. Despite these

limitations, the IWM study determined that London consumed 49 million tonnes of materials in

the year 2000, 50 percent of which were used for construction. Seven million tonnes of food

and 876 billion litres of water were also consumed.

2.1.2 Paris

The first systematic study of Paris’ urban metabolism was conducted by Stanhill (1977), who

quantified the historical energy and mass flows of a unique agro-ecosystem in a central

aristocratic district called the “Marais” (or marsh). This garden ecosystem supplied a large

share of the city’s fresh food during the 1800s, and helped alleviate problems of waste disposal

by recycling manure from the horse-powered transport system into the Marais soils. Data

sources to quantify the mass and energy flows include primary surveys of the Marais district by

nineteenth century writers who documented the “gardening culture” of Paris. Stanhill

constructed a simple mass and energy balance using inputs of human/animal labour, organic

manure, and the wood and glass materials used to house the gardens. Outputs include crop

yields; surplus soils; miscellaneous items like tools, seeds, and fuel; and the release of CO2,

water, and heat. Stanhill concluded that the Marais was an efficient system to recycle energy

and nutrients from unwanted by-products of nearly 100,000 horses in nineteenth-century

Paris.

Nutrient flows through Paris were analysed in historical context by several studies of food and

nitrogen exchange. Barles (2007a) conducted a case study of these flows for the period 1801

to 1914, during which time Paris’ population increase five-fold and the number of horses used


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for transport increased three-fold. This growth led to greater inflows of foodstuffs (namely

biomass to feed humans and livestock) and flows of materials (meat, bread, forage, and the

dietary nitrogen they contain). In a parallel study, Barles (2007b) used methods of historical

and industrial ecology to quantify flows of waste and water between Paris and the Seine River

during the Industrial Era (1790 to 1970), a period when cities were viewed as “parasites” on

the natural landscape. Billen et al. (2009) extended this analysis back in time, demonstrating

that the demand for nitrogen imports from the countryside increased dramatically from the

Middle Ages to the modern day—a result of population growth and increased need for food in

the city. Paris’ “food print” did not change significantly during the past millennium due to the

offsetting effects of population growth and increased rural productivity. After the 1950s, the

“food print” decreased due to modernization of agricultural systems and greater use of

nitrogen fertilizer in food production.

Barles (2009) later analysed the material flows of three geographic regions of Paris: the

compact commercial core; the commercial core and dense suburbs; and the metropolitan area

and its sprawling industrial and agricultural lands. This spatial model enabled Barles to

examine the influences of location (core vs. periphery), urban form (dense vs. dispersed), and

land use (residential vs. industrial) on material flows through Paris. Barles argued that a multi-

scale approach is needed for megacities like Paris that depend on distant rural and suburban

lands for energy, resources, and materials. Using data from 2003, the study reports that the

consumption of food is greatest in the city centre due to its high population density, whereas in

outlying regions consumption of materials and fuels is greatest due to the resource demands

associated with urban sprawl. These results highlight the large flows of materials between city

and countryside, and the low flows to recycling. Barles concluded that Paris’ metabolism—and

specifically its material flows—varies with urban density and land use distribution, and that this

relation has wide implications for city and regional planning and development. Finally, Kim and

Barles (2012) traced Paris’ historical energy demand from the 1700s to present day by

assessing changes in consumption, population growth, urban energy sources, and energy

supply areas and distances.

2.2 Russia

2.2.1 Moscow

Themes of historical and political change are evident in the urban metabolism literature of

Moscow. Oldfield (1999) gave a narrative account of environmental change in that city during

the transition period from the USSR—a period of widespread environmental degradation—to

the Russian Federation and its market economy. The study is largely qualitative but is

supported by statistical data on material flows and land use change from the early 1980s to

the late 1990s. Oldfield attributed a steady decline in stationary-source air pollution during this

time to shifts in energy sources, new air quality controls, and a drop in industrial production.

This contrasts with a sharp rise in mobile-source pollution resulting from dramatic increases in


12

vehicle ownership, from 0.5 million cars in 1985 to 1.4 million in 1996. Other offsets and

balances in the metabolic characteristics of Moscow during the transition period are discussed,

such as the effects of building construction on land use and green space. Oldfield concluded

that the transition period did not improve environmental conditions in Moscow due to these

offsetting influences.

Myagkov (2004) involved various components of the urban metabolism in a study of the urban

heat budget of Moscow for the period 1998 to 2002. The heat balance of any city is normally

represented by the flows of heat from vehicles, buildings, and human metabolism. The author

added heat released through wastewater (sewerage systems and open flows) to the urban

balance by quantifying the heat supply from all heating and power plants, the mean annual

output of thermal energy, as well as total natural gas consumption, annual electricity

consumption, total consumption of motor fuel, and total wastewater volume. Heat from human

metabolism and garbage incineration was considered insignificant and excluded from the

study.

2.3 North America

2.3.1 New York City

In keeping with the historical themes of the European literature, Swaney et al. (2012)

examined changes in the food and water metabolism of New York City (NYC) from the

seventeenth to late twentieth century. The study gives both quantitative and narrative

accounts of population growth (human and animal), production of food and feed supplies,

improvements to the regional transportation system, and changes in water use, water

supplies, and sewage discharge. The findings indicate that food and water consumption rates

have increased through history, but in recent decades water consumption has decreased due

to improvements in infrastructure. Overall consumption in NYC has increased due to expansion

of the city’s “food shed,” as food is now transported long distances from its production centres.

The authors contrast the metabolism of Paris, an inland city historically supported by local food

production, with NYC, a maritime trade centre whose food supplies have come from distant

sources since early in its history.

Studies of water and solid waste metabolism in NYC were conducted by Protopapas et al.

(2000) and Themelis et al. (2002). The former assessed the effects of weather on daily,

weekly, and monthly water consumption in Metropolitan New York from 1982 to 1991. Water

use varied from 4.5 to 9 billion liters per day depending on mean daily temperature; heavy

rains in summer were associated with a 10 percent drop in water use. Themelis et al. (2002)

examined municipal solid waste (MSW) recycling in the five boroughs of Metropolitan New

York. The solid waste stream was stratified by composition and weight, with the greatest

shares attributed to paper, food, and plastics. Of the 4.1 million metric tons of MSW collected


13

each year in NYC, 17 percent is recycled, 12 percent is combusted in waste-to-energy plants,

and 71 percent goes to landfill.

The City of New York (2012) conducts annual GHG inventories for all activities occurring in its

metropolitan area. The inventories began in 2007 with the aim to identify annual trends in

GHG emissions, and to inform the City’s ongoing sustainability efforts to reduce GHG emissions

by 30 percent before 2030. The 2012 report states that the generation and use of electricity is

the largest source of emissions attributable to human activities in NYC. The City’s transition to

a less carbon-intensive electricity supply is therefore the largest driver of GHG reductions, and

has resulted in a drop of 7 million metric tons of GHG emissions. From 2005 to 2011, NYC

reduced per building energy use, per capita vehicle use, and solid waste generation, and also

introduced a cleaner electricity supply. These trends accompanied a 16 percent drop in GHG

emissions (about 10 million metric tons) despite continued growth in the local economy,

building stock, and population.

2.3.2 Los Angeles

Ngo and Pataki conducted a comprehensive metabolism study of Los Angeles in 2008. Their

study quantifies the inputs and outputs of food, water, energy, and pollutants in LA County.

The authors deemed their study especially relevant to problems of urban sprawl, for which Los

Angeles is well known. Data were obtained primarily from state and federal government

sources for the years 1990 and 2000, although no reliable data were found for non-food

material inputs to LA County. In that 10-year period, population grew by 7 percent (mostly in

outlying areas), food imports increased by 13 percent, water and total energy consumption

remained constant, commercial solid waste disposal dropped by 7 percent (1995 to 1999),

waste discharge increased by 30 percent (authors’ estimate), and GHG emissions increased by

6 percent. Other data are provided for different types, sources, and uses of metabolic flows in

LA County. The study reveals a decline in per capita inputs and outputs (the exception being

food inputs and wastewater outputs) that are partly due to policies to improve energy and

water efficiency and reduce waste.

2.4 Middle America

2.4.1 Mexico City

Although no wide-ranging study of Mexico City’s metabolism exists, several studies examine

single flows of resources and wastes. Tortajada (2006) considered the gap between water

availability and water use in Mexico City Metropolitan Area (MCMA). During the past 65 years,

water supply systems have become increasingly stressed by rapid growth in population and

housing stock (especially illegal settlements). This growth is discussed by Tortajada for its

effects on water supply volumes and the percentage of houses with access to sewerage, water,


14

and electricity. Romero Lankao (2007) conducted a simplified GHG inventory for MCMA in

2000. The study demonstrates how local government is tackling climate change and managing

GHG emissions. The author warned that the results are not transferable across regions of

different socio-economic status because per capita carbon emissions vary with urban form,

regional climate, and GDP. MCMA emitted over 60 million tons of CO2 equivalent in 2000, of

which 35 percent are attributed to transportation, 29 percent to industrial activity, and 14

percent to household heaters and cookers. Transportation is therefore the leading consumer of

energy and the main source of pollution in Mexico City. An earlier study by Schifter et al.

(2005) takes inventory of vehicle emissions (CO, HC, and NOx) in MCMA. Using data on fuel

sales, exhaust characteristics, vehicle type and fuel economy, and fuel-based emissions

factors, the authors concluded that vehicle emissions were 2 to 4 times higher than those of

U.S. cities due to the older car fleet in MCMA. However, in the past decade emissions in Mexico

City have decreased due to fleet renewal and changes in emissions control technology.

2.5 South America

2.5.1 Rio de Janeiro

The CO2 component of transport metabolism in Metropolitan Rio de Janeiro was examined by

Ribeiro and Balassiano (1997). Rapid population growth in this megacity during the past 50

years has not been matched by growth in the public transit system. Results indicate that public

buses carry 5 million passengers per day, emit 4,050 tonnes of CO2, and consume 1.4 million

litres of petrol. In contrast, Rio de Janeiro’s 1.4 million cars emit nearly 8,000 tonnes of CO2

per day and consume 3.3 million litres of petrol. Cars therefore emit 8 times more CO2

emissions per person than bus users. Car and bus emissions together represent 6 percent of

total CO2 emissions in Rio di Janeiro.

In 2007, Dubeux and La Rovere prepared an inclusive accounting of CO2 emissions in Rio de

Janeiro based on a GHG inventory previously conducted by the local government. The authors

provided a basic evaluation and scenario analysis of the current emissions in Rio de Janeiro

using secondary data from the 2003 government report, Inventory of GHG Emissions of the

City of Rio de Janeiro. Annual CO2 and CH4 emissions were quantified for the period 1990 to

1998, including the sectors of energy (fuel consumption and natural gas activities), land use

change and forestry (urban expansion and deforestation), agriculture (livestock and manure

management), and waste (landfills and wastewater treatment). The energy sector accounted

for a 60 percent share of total GHG emissions in Rio de Janeiro, with transport (air, road, light

rail) and power generation being the main sources. Solid waste management was the second

largest emitter at 37 percent share.


15

2.5.2 São Paulo

Explosive growth in human and vehicle populations in São Paulo gives context to a transport

metabolism study by Vasconcellos (2005). From 1970 to 1997, the number of people and cars

in São Paulo increased two and six fold, respectively, causing major deterioration of air quality

and road transportation. Results show that cars consume 78 percent of the total transport

energy, compared to 16 percent for buses.

These findings were analysed across six socioeconomic classes in São Paulo, leading to the

discovery that all aspects of transport metabolism (e.g., pollution emissions, energy and fuel

use, travel times and distances) increase with income level: people with the highest monthly

incomes have the greatest mobility, consume the most energy and fuel, and emit the most

pollutants. The study concludes that affluent households in São Paulo are “driving” the

transport metabolism, effecting 8–15 times more influence on its flows and processes than

low-income groups.

Similar social and economic themes appear in a study by Torres et al. (2007), who explored

the environmental and infrastructural consequences of uneven spatial growth in São Paulo.

Since the 1970s the relatively affluent city centre has experienced population decline, whereas

poor peri-urban areas have spread into surrounding lands and destroyed the natural surface

cover.

The authors claimed that in these peri-urban regions, only 60 percent of households have

access to sewerage collection (versus 100 percent in the city centre). In the 1990s, the

metropolitan area saw construction of 96,000 houses per year, the majority being self-built by

the urban poor. As an outcome of this urban sprawl, 64 km2 of woodland was destroyed.

Although no quantitative data regarding energy and material flows are given in this study, one

can deduce the effects of uneven spatial and economic growth on São Paulo’s urban

metabolism.

2.5.3 Buenos Aires

Bravo et al. (2008) analysed the energy metabolism of the urban poor in Buenos Aires,

describing their use of (and access to) gas and electricity. The authors conducted household

interviews on energy consumption in slum and residential areas said to be suffering from

‘energy poverty,’ where many households are illegally connected to the electricity grid. Almost

25 percent of the basic energy requirement for the urban poor of Buenos Aires is not being

met, with greatest shortfalls for lighting, space cooling, and water heating. Although modern

energy sources (i.e., gas and electricity) are widely used in poor households of Buenos Aires,

the availability and affordability of these sources is a key public policy issue. Many poor

households have no choice but to replace clean and modern energy sources with “dirty,” less

efficient fuels like charcoal and kerosene.


16

2.6 Sub-Saharan Africa

2.6.1 Lagos

Lagos is described by Kofoworola (2007) as one of the world’s most polluted megacities. It

generates 4 million tonnes of solid waste per year, 50 percent of which remains uncollected on

city streets and open grounds. A significant challenge facing this megacity is to control and

collect its waste flows, especially as industry and population grow rapidly. Aiming to assess the

status of municipal waste recovery and recycling in Lagos, Kofoworola investigated the flows

and physical composition of solid waste, and suggested that, despite a lack of material

recovery facilities in the city, the informal sector (e.g., scavengers and refuse collectors) can

potentially remove 5 to 8 percent of recyclable materials from the waste stream.

Aluko (2010) examined the effects of population growth on urban decay. Staggering growth in

Lagos has led to deterioration of housing and living conditions. The built-up area of

Metropolitan Lagos more than doubled—from 400 to 1,000 km2—between 1993 and 2006.

Much of this growth was concentrated at the city periphery and is contributing to the spread of

slums and shantytowns, and to the deterioration of water security and supply. Oyegoke et al.

(2012) studied this same issue, noting that with 70 percent of Lagos’ population residing in

slums, and a population growth rate of 8 percent, the megacity is unable to meet its current

water demand. The production capacity of 1 billion liters per day represents a 40 percent

shortfall.

Anthropogenic GHG emissions over Metropolitan Lagos were estimated by Aderogba (2011),

who gathered data from scholarly journals, government interviews, and local newspapers and

magazines. Aderogba found that heavy duty trawlers, trucks, and aircrafts are the chief

contributors to GHG emissions, at more than 500 metric tons of carbon equivalent per vehicle

per kilometer. However, the fleet of 1.8 million motor vehicles on the roads of Lagos

represents the largest GHG emitter. Standby electricity generators (one per household and/or

business unit) are also considered a major source of GHG emissions and make a significant

contribution to the total 340,000 tonnes of CO2 emitted annually in Lagos.

2.7 North Africa / Southwest Asia

2.7.1 Cairo

Meyer (1987) examined a unique segment of Cairo’s population that effects significant control

over its solid waste metabolism, but which is common to all megacities of low/middle income

status: refuse collectors of the informal sector. In Cairo more than 20,000 people earn a living

by retrieving, sorting, and recycling waste materials from households of the middle and upper


17

classes. These collectors—known as zabbalin—and their waste-recycling system date back to

the nineteenth century when Egyptian migrants received fees from households to remove

waste and sell it to purveyors of public baths, who then consumed the waste for fuel. Based

on surveys and maps of the zabbalin districts, Meyer calculated crude volumes and hourly

flows of refuse into these “garbage settlements”. The movement of a typical work day in the

life of the zabbalin begins as “2,000 donkey carts start their…journey from the refuse

settlements to the middle- and upper-class residential districts of the Egyptian metropolis.”

They return hours later with refuse from 100 to 250 dwellings, which is then sorted for

recyclable materials. Organic waste is sorted and used for pig fodder. Fahmi’s (2005) account

of the zabbalin is more contemporary, claiming that they collect nearly 3,000 tons of garbage

per day, or one-third of the total daily trash produced in Greater Cairo. Eighty-five percent of

that garbage is recycled, a proportion Fahmi contends is far greater than any trash collection

system in the industrialized world.

In a more synoptic study of the urban metabolism, Duquennois and Newman (2009) stressed

the urgency to reduce Cairo’s “metabolic footprint” and strive for a more sustainable megacity.

The soaring rates of metabolism in Cairo are depleting its clean water, open spaces, and fresh

air, and are driven by pressures that all low/middle income megacities face: urban sprawl,

infrastructural deficits, high unemployment rates, phenomenal population growth, a

burgeoning informal sector, lack of macro-administrative structures to control growth, and

heightened demands for water, food, shelter, and sanitation.

The authors discussed possible approaches to reduce Cairo’s metabolic footprint, such as

diversifying the city’s energy sources, encouraging urban forms that preserve outlying

agricultural lands, closing the sustainability gap between water supply and use, developing

modern waste-management systems to complement in situ practices of the informal sector

(e.g., the zabbalin), and establishing more efficient modes of public transportation to reduce

automobile dependency. Throughout their discussion, Duquennois and Newman give

quantitative indicators of metabolic flows and processes in Cairo, and establish an instructive

relation between urban metabolism and urban sustainability.

Historical changes in urban transport — and their effects on energy and environment—in

Greater Cairo were considered by Huzayyin and Salem (2013). Using data from travel-demand

surveys conducted between 1971 and 2000, the investigators quantified the 30-year evolution

of urban development (i.e., population and urbanized area), transport (number of cars and

daily motorized trips), energy use (transport fuel consumption), GHG emissions (CO2

equivalent for transport), and air pollution (CO and NOx from transport). Growth trends across

the 30-year study period reveal that both population and urbanized area have increased by

factors of two, while fuel consumption, number of vehicles, and GHG emissions increased by

factors of twelve to fourteen.


18

2.7.2 Tehran

Tehran shares many of Cairo’s environmental challenges with population growth, urban

expansion, and solid waste management. Abduli (1995) assessed the status of waste

management in Tehran based on detailed surveys of its 20 regional municipalities. The

surveys include data on solid waste generation, storage, collection, and transportation, and the

organizational structure of its waste management system. Waste volumes and material

composition for the period 1980 to 1992 are provided in the study. Damghani et al. (2008)

extended Abduli’s assessment of solid waste management to the period 1990 to 2005,

revealing a notable change in waste metabolism due to material separation and recycling.

Although Abduli confirmed that no official processing and recovery activities existed in the

waste management system of Tehran, Damghani et al. examined three new composting

centres and their capacity to extract 5 percent of recyclable materials from the solid waste

stream. This percentage is likely much higher in reality due to the recycling activities of the

informal sector.

Shifting to the traffic metabolism of Tehran, Kakouei et al. (2012) determined that the fleet of

motorized vehicles in that megacity has reached 3.5 million, and that nearly 50 percent of

households now own private cars. These statistics underpin the authors’ investigation into

traffic-related CO2 emissions (cars, buses, taxis, and motorcycles), for which no previous

reports or estimates exist. Using data on fuel consumption, emissions factors (by fuel type),

number and type of vehicles, and distance travelled, the authors concluded that 88 percent of

all traffic-related CO2 emissions are generated by private cars (26,372 tones CO2 per day). In

a related study, Atash (2001) emphasized that very little English language literature exists on

air pollution and CO2 emissions in Tehran, and thus non-English publications—namely Iranian

daily newspapers—are a valuable source for more complete data on transportation and air

pollution. Both Atash and Kakouei et al. confirmed that Tehran’s current transportation

problems are rooted in a deficiency in public transit and a dependency on private cars.

2.7.3 Istanbul

The flows of waste and water in Istanbul have been investigated separately. Kanat (2010)

assessed Istanbul’s solid waste management system and proposed solutions for its shortage of

landfill sites and excessive solid waste flows. Based on literature reviews of waste production

in Istanbul, Kanat extracted a detailed array of statistics on waste quantity and composition.

The data were stratified by material group (including recyclable materials) and location of

origin. Altinbilek (2006) assessed the water management system of Istanbul. Like

investigations in other megacities, the study was set in the context of explosive population

growth and its demands on local infrastructure, in this case for wastewater collection,

treatment, and disposal. Focusing on the years 1993 to 2004, Altinbilek concluded that water

and wastewater systems in Istanbul greatly improved: the percentage of treated wastewater

increased from 9 to 95 percent, and “unaccounted-for” water (i.e., water lost to theft, leaky

pipes, illegal connections, and ill-functioning meters) in the distribution network dropped from

50 to 34 percent.


19

2.8 South Asia

2.8.1 Dhaka

In the past several decades, Dhaka’s extraordinary growth in population and economic

development has generated unprecedented rates of material consumption and solid waste

flows. Hai and Ali (2005) studied the rates, trends, and characteristics of domestic solid waste

in Dhaka City. Based on secondary data sources, the authors estimated that solid waste

generation in Dhaka increased from 1,000 to 5,000 tons per day in the span of 12 years (1985

to 1997). Nearly 10 percent of Dhaka’s daily waste is recycled by refuse collectors of the

informal sector, 3 percent is recycled at the point of generation, and 51 percent is collected

and dumped by Dhaka City Corporation.

The remaining share of waste is left uncollected in backyards, roadside drains, and open

spaces. Qualifying these statistics, Yousaf and Rahman (2007) suggested that as Dhaka

continues to industrialize, its solid waste stream is becoming less organic and more paper- and

plastic-concentrated. Furthermore, solid waste generation varies by as much as 20 percent

with month and season of year, with highest rates occurring in the wet monsoon and summer

fruit seasons. Yousaf and Rahman also exposed a relation between MSW generation and socio-

economic status, suggesting that high-income groups generate more waste than low-income

groups. The total share of recycled materials in Dhaka’s MSW stream is 15 percent, of which 9

percent (or more than 400 tons per day) is recycled by scavengers, hawkers, and small traders

of the informal sector.

The role of the informal sector in waste recycling was examined more closely by Matter et al.

(2013), who insisted that “local” solutions are essential to overcome problems of waste

collection and disposal in low/middle income regions. Based on statistics of waste metabolism

extracted from government documents (e.g., MoEF, 2010) and consultant reports (e.g., Waste

Concern Group), Matter et al. determined that 120,000 people in the informal sector are

involved in the recycling trade of Dhaka City, and that 15 percent of the total waste generated

(or about 475 tons per day) is recycled. Dhaka’s waste-collection efficiency is only 44 percent,

meaning that most of the nearly 5 million tons of solid waste generated per annum remains

uncollected.

Whilst waste collection and disposal have not kept pace with rapid urban expansion in Dhaka,

neither has water or wastewater management. Haq (2006) reviewed different approaches

toward water management in Dhaka, and gave supporting statistics of its water metabolism:

Dhaka’s sewerage infrastructure services only 30 percent of its population; the proportion of

unaccounted-for water in the municipal system is 50 percent; Dhaka’s groundwater table is

dropping 2 metres per year due to water extraction from underground aquifers; and water

supply is 20 percent short of actual demand.


20

2.8.2 Karachi

Like Dhaka, Karachi faces serious challenges in the management of its solid waste streams.

Based on interviews, field surveys, and reports from the Karachi Metropolitan Corporation,

Khatib et al. (1990) identified trends in Karachi’s waste generation in the 1980s and

characterized the quantity and physical composition of recyclable materials in the waste

stream. The authors estimated that Karachi generates 4,500 tonnes of municipal solid water

per day, with a collection efficiency ratio of 42 percent (1984). Thirty-five percent of MSW in

Karachi is classified as recyclable. Using more recent statistics from the Karachi Metropolitan

Corporation (1992), Ali et al. (1998) investigated different approaches to waste management

in Karachi. They claimed that the megacity produced over 6,000 tonnes of solid waste per day

in 1992, a year when the collection efficiency ratio was 54 percent. The authors conceded that

the waste collection ratio in Karachi varies significantly from 38 to 80 percent depending on

location, with lowest rates found in the poorest areas of the city.

An extensive report on the future development and growth of Karachi and its 18 administrative

towns was published by City District Government Karachi (CDGK) in 2007. The Karachi

Strategic Development Plan 2020 sets forth a growth framework for the years 1997 to 2020.

The report includes details of Karachi’s water supply, sewerage and wastewater disposal, solid

waste management, electric power supply, transport, land usage, and urban growth, which

together convey Karachi’s urban metabolism and its social and biophysical characteristics. The

report states that in 2005 Karachi generated 9,000 tons of solid waste per day (with 10

percent processed by scavengers) and 1,400 million litres per day (MLD) of sewerage (with 23

percent treated at wastewater plants). Karachi’s capacity for water supply was 2,400 MLD in

2005, which represents a 15 percent shortfall of demand. Data for additional benchmark years

were given for comparison with earlier studies.

2.8.3 Delhi

An abundance of literature exists on the flows of energy and waste in Delhi, India’s most

densely populated and rapidly growing city. Such flows are putting extreme pressure on the

city’s infrastructure and its management of energy, water, and waste. Sharma et al.

(2002a,b,c) conducted GHG inventories for the agriculture, waste, transport, and energy

sectors of Delhi and Kolkata. Waste was shown to be the main source of methane emissions—

far greater than agriculture—for the period 1971 to 2001. GHG and pollutant inventories were

also conducted for the transportation sectors of Delhi and Kolkata based on number and type

of vehicles and annual consumption of gasoline and diesel. Emissions totals were reported for

select years between 1980 and 1998. The analysis was extended to the year 2004 by Sharma

and Pundir (2008), and to 2009 by Singh and Sharma (2012). The latter study found that

despite the improved CO2 emission efficiencies of vehicles, an increase in vehicle population

has forced a net increase in CO2 emissions. Sharma et al. (2002c) reported that the major

contributor of CO2 emissions in Delhi (and Kolkata) is electricity consumption, with households

(30–40 percent share) and industries (20–30 percent) being the largest consumers. CO2 and

CH4 emissions related to coal, gasoline, diesel, and fuel wood consumption are given for both


21

cities. In Delhi, CO2 emissions from diesel consumption are greatest among all source

materials. Mitra et al. (2003) performed a comparable analysis of energy-related emissions in

Delhi and Kolkata, and included the megacity of Manila.

Emissions in Delhi for the years 1990 to 2000 were calculated by Gurjar et al. (2004), who

used an emission factor–based approach for the source categories of transport, agriculture,

power plants, waste treatment, industrial processes, and the domestic sector. Results were

compared with the aforementioned GHG inventory studies in Delhi and Kolkata. Chavez et al.

(2012) used an expanded geographic framework for their GHG emissions inventory of Delhi in

2009. The study accounts for emissions from infrastructures existing outside the boundaries of

the city, including those of commuter and airline transport, energy and water supply, and

wastewater treatment. Trans-boundary infrastructures generated 32 percent of Delhi’s total

GHG emissions in 2009, with 5 percent attributed to fuel processing, 3 percent to air travel, 10

percent to cement, 14 percent to food production, and 68 percent to in-boundary sources.

Chavez et al. noted that this type of GHG accounting is data intensive, and that their study of

the national capital was possible only because of high-level government reporting in that city.

Studies of municipal waste flows in Delhi were conducted by Agarwal et al. (2005) and Talyan

et al. (2008), each describing solid waste management as one of the most neglected areas of

India’s urban systems. Waste recycling in Delhi is largely an informal sector activity involving

80–100,000 waste pickers of the poorest stratum, but a sector that recycles 17 percent of the

city’s total solid waste flows. Talyan et al. evaluated the quantity and quality of Delhi’s solid

waste for the past 30 years, as well as patterns of waste collection, storage, transportation,

treatment, and disposal. A collection efficiency ratio of 70–80 percent is reported for Delhi.

Rai (2011) quantified water-demand relations for the National Capital Territory of Delhi based

on data gathered from local stakeholders and government officials. In 2006, water supply was

11,200 MLD, while demand exceeded 16,300 MLD. Although 75 percent of Delhi’s households

met their water requirements through the piped water supply system, 46 percent of the

population had no access to piped water. Water loss in the main supply and distribution lines is

estimated at 40 percent, a consequence of deteriorating infrastructure, poorly functioning

metres, and water theft. Sagane (2000) cited similar rates of unaccounted-for water in Delhi

(as well as Mumbai and Kolkata) in the context of a larger study on water supply problems in

Indian megacities.

2.8.4 Mumbai

Inputs and outputs of energy, water, waste, nutrients, and raw materials were quantified for

Mumbai in a wide-ranging metabolism study by Reddy (2013). Metabolism estimates are

reported for inflows of food, water, energy, and construction materials (other goods and

services are not included due to lack of data), and for outflows of wastewater, air pollutants,

and solid waste. Reddy’s study reveals that in 2010, 26,000 tonnes per day of food materials

were consumed; 15,000 tonnes per day of solid waste were generated; and 17.4 million

tonnes of construction materials were brought into the city, with 85 percent remaining in the


22

city as building stock or land fill. Mahadevia et al. (2005) examined the metabolism of solid

waste in Greater Mumbai and its 24 municipal wards, giving particular attention to the

collection, storage, removal, transportation, and disposal of such waste. The authors

determined the physical composition and local origin of Mumbai’s waste, concluding that the

central city generates five times as much solid waste as the suburbs, despite having just 25

percent of the total metropolitan population.

2.8.5 Kolkata

Several recent case studies on solid waste have been conducted in Kolkata. Harza and Goel

(2009) analysed the strengths and weaknesses of Kolkata’s MSW management system. The

collection efficiency ratio for Kolkata is reported at 60–70 percent for registered residents, and

drops to 20 percent or less in slums. Chattopadhyay et al. (2009) investigated changes in the

physical and chemical composition of solid waste in Kolkata across three reference years:

1970, 1995, and 2005. The investigation shows that flows of solid waste in Kolkata vary with

economic prosperity and time of year: wealthy residents produce more garbage than poor

residents, and monsoon and festival seasons generate more waste than dry and non-festival

seasons. Das et al. (2011) conducted a similar review of waste generation, collection, and

composition in Kolkata Metropolitan Area (KMA). Based on field surveys and interviews with

KMA’s 41 municipal towns, the authors identified spatial patterns of MSW generation across

the metropolitan area.

In a more inclusive study of metabolic flows, Sivaramakrishan (2013) surveyed the

environmental effects of Kolkata’s population growth, which averaged 20 percent from 1971 to

2001. Energy and materials consumed in the metropolitan area were quantified and cataloged

based mainly on secondary sources of data. The following indicators of the urban metabolism

are given for two census years (1991 and 2001): water supply; number of vehicles; length of

surfaced roads; and consumption of food, power, vehicle fuel, and building materials. Results

indicate that rates of urban metabolism in Kolkata increased considerably from 1991 to 2001.

Jana et al. (2010) quantified CO2 emissions from vehicle exhaust in KMA for the period 1981

to 2001. Although the number of vehicles increased threefold during that time, CO2 emissions

declined by 44 percent after 1991 due to emissions controls, upgraded highways and roads,

and improved vehicle technology and fuel quality. Basu and Main (2001) recognized problems

of water supply inefficiency and distribution inequity in Kolkata’s municipal water management

system — problems that have left millions of low-income residents without water from the

municipal network. The authors give data on water supply characteristics and volumes in

Kolkata, 1971 to 2001, to support their discussion of management solutions.

A unique example of “living systems” infrastructure is described by Jana (1998) and Carlisle

(2013), whose case studies of East Calcutta Wetland (ECW) illustrate how megacities can use

their topographic settings to manage particular flows of the urban metabolism. In both studies,

the natural wetlands of Kolkata are featured for their highly engineered flows of waste and

food. The unique urban ecosystem was developed over a century ago to treat waste and


23

produce saleable fish and vegetables for Kolkata. ECW consists of a series of canals that divert

the city’s sewerage into one of the largest and most productive wastewater–fed aquaculture

systems in the world. Covering 3,000 hectares, ECW processes 550,000 m3 of raw sewerage

per day, produces 16 percent of the city’s fish sales, and provides fertilizer to thousands of

hectares of farmland.

2.9 Southeast Asia

2.9.1 Manila

Apart from the abbreviated metabolism study of Metropolitan Manila by Hoornweg et al.

(2012) (Chapter 1), which includes all components of the metabolism except for inflows of

construction materials, nutrients, wastewater, and air pollutants, few other such investigations

are reported in the literature. Ajero (2002) conducted an inventory of emissions across

Metropolitan Manila, including the energy, transportation, solid waste, and agriculture sectors

for 1980, 1990, 1995, and 2000 (see also Mitra et al. [2003] in section 2.8.3). Results show

that transportation and electric energy are the biggest contributors of CO2 in Metropolitan

Manila, and that agricultural emissions are extremely low due to minimal agrarian production

inside the metropolitan region. Growth rates in electricity consumption for the period 1980 to

2000 are greatest in the residential (5.0 percent growth) and commercial (4.5 percent)

sectors, which together account for three-quarters of total electricity consumption in

Metropolitan Manila.

2.9.2 Jakarta

Sugar et al. (2013) published a study of sector-based GHG emissions for the megacity of

Jakarta. The study highlights ways that Jakarta can manage its GHG emissions while

confronting development pressures and climate adaptation measures. Jakarta is challenged by

its extensive slums and informal settlements that are poorly equipped for energy and water

supplies, and that are prone to floods and landslides. The authors conducted inventories of

emissions from stationary energy (electricity, space heating/cooling, manufacturing, and

construction), mobile energy (road, aviation, and marine transportation), and waste.

Emissions from industry are not accounted for due to lack of data, and emissions from

agriculture and forestry are considered negligible. Data were sought in collaboration with city

officials and local consultants who gave access to statistical records and local expertise. The

study finds that electricity consumption and road transportation are the two major contributors

to Jakarta’s annual GHG emissions.


24

2.10 East Asia

2.10.1 Seoul

The quantity and physical composition of solid waste in Seoul’s 25 administrative districts was

analysed by Yi et al. (2011). Outcomes show that per capita waste generation is inversely

proportional to population density, and directly proportional to business concentration in

Seoul’s 25 districts. Yoon and Jo (2002) examined solid waste in Seoul (and Tokyo) from 1960

to 2000. MSW generation has declined (as has population) in both megacities in the past

decade, in part due to increased waste recycling and decreased landfilling. Data for the entire

40-year period indicate that solid waste generation is closely related to growth and decline in

population and economic activity. Lee et al. (2007) focused specifically on Seoul’s food waste

(which accounts for 30 percent of the MSW stream) and its environmental effects from 1997 to

2005.

Seo and Hwang (1999) explored a single component of the urban metabolism that is not often

reported in the literature: storage and outflow of building materials. The amount and

composition of construction/demolition debris in Seoul, 1994 to 2021, was estimated based on

the lifespan, floor area, and “material intensity” of the city’s building stock. In the past 30

years, Seoul experienced rapid growth in its economy and building construction; now, with an

average lifespan of 23 years, many of those buildings are facing demolition or redevelopment.

In 1999, 8.6 million tons of building debris (mostly concrete and brick) was generated in

Seoul. This debris has major implications for waste reuse, recycling, and landfilling.

Praskievicz and Chang (2009) conducted a statistical analysis of the relation between

municipal water use in Seoul and daily weather conditions, 2002 to 2007. Their findings

confirm that air temperature has a significant correlation with water use: a one degree

increase in the daily maximum temperature yields a 2 to 4 litre increase in daily per capita

water consumption.

2.10.2 Tokyo

An early study of the urban metabolism in Tokyo was conducted by Hanya and Ambe (1977),

who developed a generalized framework to assess material flows through cities. The authors

adapted a “geochemical systems” approach to Tokyo to account for its inputs and outputs of

water, wastewater, materials, people, solid wastes, and atmospheric gases, 1969–73. Flows

through Tokyo were compared with those of a natural forest ecosystem, revealing important

differences between city and forest metabolisms.

Subsequent literature on the urban metabolism of Tokyo focuses more specifically on water.

Udagawa (1994) and Maeda et al. (1996) discussed the flows and uses of reclaimed water in

Metropolitan Tokyo, beginning in 1951 with wastewater for paper manufacturing. Water

supplies, demands, shortfalls, and effluent volumes are accounted for in both Udagawa and


25

Maeda et al. Takahasi (2000) and Otaki et al. (2007) extended this accounting back in time

several centuries to include water supply and demand, sewerage treatment, and urban

sanitation. Using statistical data from Tokyo Metropolitan Government (TMG), the authors

constructed historical time series for water supply volumes from the city’s waterworks, as well

as the population served and the service coverage of modern waterworks and sewerage

treatment systems. The effects of major events in Tokyo’s history—the Great Kanto

Earthquake of 1923, World War II, and the post-War population boom—on the city’s water

supply and use are evident in the data. For example, water leakage rates in Tokyo’s

infrastructure dropped from 80 percent in 1945 (end of World War II) to less than 10 percent a

half-century later.

Tokyo’s sewerage management system and its energy use and GHG emissions were

investigated by Hara and Mino (2008) for the period 1995 to 2001. The impetus behind their

study is Tokyo’s severe shortage of sludge disposal sites and TMG’s response to develop

recycling and incineration systems in hopes of reducing sewerage volumes and increasing

recycled materials (brick, aggregate) and derived fuels. Flows and volumes of sludge in Tokyo

are cited for 1995 to 2001 based on data obtained from TMG and Tokyo’s 12 wastewater

treatment plants. Katsumi (1990) discussed problems of solid waste in Tokyo and the

overwhelming amounts of garbage produced in the 1980s. Efforts to incinerate, landfill, and

recycle that waste have not kept pace with Japan’s growing consumer-based economy. Yoon

and Jo (2002) also analysed solid waste in Tokyo and established relations among waste

generation, population growth, and economic development for the period 1960 to 2000 (see

section 2.10.1).

2.10.3 Osaka

A simple energy and material flow analysis for Osaka Prefecture was conducted by Shimoda

and Mizuno (2000). In 1994, total inputs of materials (food, construction, and other) to Osaka

were 149 million tons, 25 percent of which accumulated as storage (i.e., buildings, physical

infrastructure, and goods and facilities), 29 percent were consumed, and the remainder

recycled, discharged as solid wastes, or emitted to the atmosphere. In 1997, total inputs of

energy (gas, oil, electricity, solid fuels, and other) were 870,487 TJ, which includes the

industrial, transportation, commercial, and residential sectors. No data are reported for water

or waste flows in Osaka.

2.10.4 Beijing

Due to its sheer size and growth, Beijing (and other Chinese megacities) has drawn much

interest to its urban metabolism and GHG emissions. Underlying the GHG studies are urban

metabolism data on energy use, waste, and industrial production in the cities. Beijing and

Shanghai have featured in many of the studies because they have provincial status. Dhakal

(2009) examined the energy intensity and energy-related GHG emissions for the four


26

provincial cities (which include Beijing and Shanghai), and provided estimates based on gross

regional product for energy use and emissions in other Chinese cities (including Guangzhou

and Shenzhen). Sugar et al. (2012) constructed GHG inventories for Beijing and Shanghai,

including emissions from waste and the industrial production of cement and steel. In

comparison to ten global cities, Beijing and Shanghai were found to have relatively high per

capita use of heating fuels for buildings and industry; high carbon electricity due to the

prevalent use of coal; and relatively low per capita transportation emissions due to high urban

population densities.

The urban metabolism of Beijing has been the focus of several studies. The inner structural

characteristics of Beijing’s metabolism were researched by Liu et al. (2011b, 2012) in terms of

exergy flows among seven sectors (mining, agriculture, energy conversion, manufacturing,

transportation, construction, and domestic consumption). Further studies of resource and

material flows were conducted for seven similar sectors (with recycling instead of

transportation) by Li et al. (2012) and Zhang et al. (2013); synergist relationships were

identified (Zhang et al., 2014a) and a hierarchy of ecological flows established (Yang et al.,

2014). These physical flows between sectors have been combined with monetary input-output

data to develop a network model of Beijing’s metabolism, with linkages between 31 industrial

sectors and the consumption sector (Zhang et al., 2014b). Further studies in Beijing have

focussed on the urban water metabolism (Zhang et al., 2010), phosphorus flows (Qiao et al.,

2011), the carbon content of residential food (Luo et al, 2008), and the material stock of the

road infrastructure system (Guo et al., 2014). Zhang et al. (2009) also conducted an urban

metabolism study of Beijing, expressing results in terms of eMergy (Odum’s measure of

embodied solar energy), and including comparisons with Shanghai and Guangzhou.

Solid waste management in Beijing was examined by Xiao et al. (2007) and Li et al. (2009).

Both studies give an overview of trends in waste generation and composition. MSW increased

from 1 million tons in 1978 to more than 4 million tons in 2006, and is now considered one of

the most serious environmental problems in Beijing. Results from these studies show a strong

correlation between growth trends of MSW and those of total GDP, per capita income, and

population. Li et al. recognized the value of informal recycling by waste pickers and collectors

in Beijing. It is reported that the city has a floating population of 300,000 people who make a

living from the proceeds of informal waste recycling.

2.10.5 Shanghai

According to Ward and Li (1993), China’s weak policies on landfill design, landfill location, and

solid waste management have had serious environmental and social consequences in

Shanghai. The authors described and analysed MSW disposal in the Shanghai metropolitan

area during the 1980s, a period when residential, industrial, and construction waste amounted

to 6,850 tons per day, surpassing 10,000 tons per day in summer. These totals do not include

human waste (8,000 tons per day in 1988), 50 percent of which is discharged directly into the

Yangtze River and the remaining 50 percent processed for agricultural use. While annual

residential and industrial waste increased steadily from 1978 to 1990, construction waste


27

decreased. The authors attributed this drop in part to the “clean-up” campaign following the

end of the Cultural Revolution in 1976, and to the restoration of government and civil order.

The environmental health of Shanghai in subsequent years was scrutinized by Zhang et al.

(2008). China experienced rapid economic development and growth during the 1990s as the

government promoted Shanghai as a growth pole for international finance and trade.

Shanghai consequently joined other Chinese megacities in their plight with environmental

degradation and brisk economic growth. Zhang et al. quantified the relation between economic

activity and the eco-efficiency of its water and energy metabolism.

Data to conduct the study were obtained from statistical yearbooks for China and Shanghai,

and from various government publications. To evaluate the ecological health of Shanghai’s

metropolitan area, the authors developed 15 indicators that were grouped into broad

categories including population/economy (e.g., total population, total GDP) and urban

metabolism (e.g., energy and water consumption, wastewater discharge, waste gas

emissions). The study shows that GDP increased at a rate of 16 percent during the industrial

transformation of 1990 to 2003, while wastewater discharge, waste gas emissions, and water

and energy consumption decreased by 9 to 15 percent per unit of GDP. The authors concluded

that the urban metabolism of Shanghai has become more ecologically efficient with respect to

economic growth.

Ward and Liang (1995) appraised municipal efforts to improve water quality in Shanghai and

the associated problems with water intake, treatment facilities, and wastewater discharge.

Shanghai produced 5.4 million cubic metres of liquid waste per day in the mid-1990s, of which

4 million was industrial sewage released directly into local rivers and tributaries. Only 4

percent of Shanghai’s total sewerage was treated at wastewater plants. The authors accounted

for an additional source of waste flows that contributes to the urban metabolism (but that is

not often documented): the thousands of ships and small boats that use Shanghai’s port

facilities every day. These vessels contribute 25,000 cubic metres of solid and liquid sewerage

per day to Shanghai’s total waste production.

Carbon dioxide emissions in Shanghai are featured in several recent studies (in addition to

Dhakal [2009] in section 2.10.4). Li et al. (2010) estimated CO2 emissions from 1995 to 2006,

and projected future emissions to grow by a factor of almost 4 between 2005 and 2020 under

business-as-usual scenarios. Such growth could be lessened by energy conservation policies.

Liu et al. (2011a) conducted an inventory analysis of energy-related CO2 emissions in

Shanghai in 2008 (see also Sugar et al. [2012] in section 2.10.4).

Outcomes were stratified according to energy source and sector to show that coal (followed by

fuel oil) is the primary source of CO2 emissions in Shanghai. Energy conversion (thermal

power), industry, and transportation contribute the most emissions, with 40, 30, and 22

percent share, respectively, of the total CO2 emitted in Shanghai in 2008.


28

2.10.6 Guangzhou

Despite the difficulties of procuring complete and comprehensive data on solid waste in China,

Chung and Poon (1998, 2001) analysed waste management practices in Guangzhou (and Hong

Kong) using annual waste generation totals for 1982 and 1990 to 1996. Total MSW generated

in Guangzhou increased from 1,300 tonnes per day in 1982 to 4,200 tonnes in 1996. Chung

and Poon (2001) presented findings of a year-long field study on MSW characteristics in

Guangzhou and its 8 administrative regions. Results show the percentage distribution of

wastes and recyclable components, as well as the effects of the fruit season and China’s two

national festivals (autumn and New Year) on solid waste generation and composition.

Zhao (2010) determined the amount of carbon emissions in Guangzhou due to energy

consumption, 1992 to 2007. Based on data from the Guangzhou statistical yearbook, Zhao

claimed that energy consumption increased 12 percent per year across the study period, and

that population and economic growth (GDP) correspond closely with growth in carbon

emissions. The study also reports that, despite increases in total and per capita carbon

emissions from 1992 to 2007, the “intensity” of those emissions (i.e., cost of converting

energy into GDP) actually decreased. Chong et al. (2012) included Guangzhou, along with

China’s four city provinces, in a study showing that economic growth and energy intensity are

key factors underlying the growth of carbon emissions in Chinese cities (see also Dhakal

[2009] in section 2.10.4.).

2.10.7 Shenzhen

Zhang and Yang (2007) examined the urban metabolism of Shenzhen, 1998 to 2004. Trends in

the annual rates of water, energy, and electricity consumption, as well as waste and

wastewater discharge, were compared to trends in the socio-economic development of

Shenzhen. Comparisons revealed the “eco-efficiency” of the urban metabolism in Shenzhen

(or, in other words, the ecological capacity to support growth in population and GDP). The

findings confirm that energy, water, and waste metabolism increased after 1998 with continual

socio-economic development. Across the study period, GDP increased by a factor of 2.7, while

water and electricity metabolism increased by factors of 1.5 and 3.0, respectively. Similarly,

population increased 1.5 times while residential water and electricity flows increased by 1.7

and 1.8 times, respectively. Lastly, GHG emissions in Shenzhen were estimated by Dhakal in

2009 [see section 2.10.4].


29

3 Global synthesis of the urban metabolism literature

Review of the literature on urban metabolism in megacities allows for global synthesis of

themes, patterns, and trends that are otherwise not obvious in single studies. A common

theme among all works in the review is one of “growth and change”—each study is set in a

similar context of growing populations and/or economies, and changing flows and stocks of

resources and wastes. From this premise, we take a multi-dimensional approach to identify

three aspects of the urban metabolism that are specific to the megacity literature: (1)

historical/temporal trends; (2) spatial/geographical patterns; and (3) social/economic

influences.

First, the metabolism of megacities in all regions of the world has been investigated for its

temporal changes, i.e., trends in the flows and stocks of water, waste, energy, and materials.

This approach emphasizes the dynamic and sensitive nature of the urban metabolism to inputs

and outputs at different time scales (hours, days, seasons, years). Historical annals from past

centuries contain valuable proxy data for metabolism studies, as shown in the megacities of

Paris, New York City, and Tokyo. At shorter time scales, water and energy consumption in all

megacities fluctuates with daily, weekly, and monthly weather changes, as documented in

Seoul and New York City. Solid waste generation changes with time of year (monsoon, festival,

and fruit growing seasons) in the low-latitude megacities of Dhaka, Karachi, Guangzhou, and

Delhi, and GHG emissions change with years and decades, as reported in Cairo, Manila,

Kolkata, and Shanghai. The literature therefore conveys an important characteristic of the

urban metabolism: that it is never static and its continuous flows allow for inquiry at all time

scales.

Further to the temporal theme is the effect—sudden or gradual—of historical disruptions and

upheavals on the metabolism of megacities. This often occurs with wars, revolutions, and

political regime changes. The best documented example is Moscow’s transition from a planned

economy to a free market economy—a social and political transformation that met with great

environmental change in Moscow, and with resultant shifts in the stocks and flows of its urban

metabolism. Such a profound transition in governance can influence the rates at which a

megacity imports and consumes food, materials, and energy, and discharges wastes. Similar

effects were reported for megacities in China during and after the Cultural Revolution, and for

Tokyo during and after World War II. Catastrophic events such as natural disasters can also

disrupt the flows and stocks of the urban metabolism, as in the case of the 1923 Great Kanto

Earthquake in Tokyo. In this sense, the urban metabolism is an important method to detect

and analyse structural changes and transitions in urban systems, as described by Barles

(2007a,b) for the case of Paris.

The metabolism of megacities also responds to spatial context and geographic location. The

literature demonstrates that a megacity and its metabolism are not monolithic entities—they

are comprised of many interacting parts and processes that change through space (and time).

Such sensitivity is manifest at local scales within a single megacity, and at regional scales

among megacities. Rates of urban metabolism therefore vary from city centre to city outskirts,

a pattern that is observed widely and that implicates a relation with urban form, land use,


30

population density, and the socio-economic status of a location. For example, in higher-income

regions of the world, the phenomenon of urban sprawl and its effect on metabolism is reported

for Los Angeles, Paris, and Seoul; in lower-income regions, the uneven distribution of wealth in

the city (rich core vs. poor periphery) and its effect on metabolic flows is reported for nearly all

megacities. Waste-collection efficiency ratios and access to energy and sewerage differ greatly

between the inner and outer city, where the distinction between rich and poor is sharp.

Generation of waste also diverges across a megacity, with high-income areas producing more

solid waste (particularly inorganic) than low-income areas. These effects are especially well

documented for megacities of South Asia and South America.

Spatial patterns in the metabolism of megacities are intrinsically linked to social and economic

factors. The literature suggests that high-income residents of megacities contribute more to

the urban metabolism than low-income residents. For example, affluent populations are

typically more mobile (i.e., access to private cars) and consume more energy than poor

populations (in addition to producing more garbage). Thus, the wealthy demographic of a

megacity contributes more GHG and pollutant emissions per capita to its transport

metabolism. However, one must also consider the inefficient flows of energy, water, and

materials through informal settlements of low-income megacities, which result in a more

polluting behaviour of the inhabitants. The relation between socio-economic status of megacity

populations and their influence on metabolic flows and stocks is widely reported in South

American megacities (e.g., “energy poverty” in Buenos Aires). In wealthy megacities, GDP,

consumerism, and population growth are related to accumulations of building and

infrastructure stock, energy use and waste disposal, and emissions of GHG and air pollutants.

The most salient theme in the literature is the unique cultural and geographical setting of the

world’s low/middle income regions and its influence on the urban metabolism. Megacities of

these regions are characterized by burgeoning populations, industrial expansion, sprawling

slums and shantytowns, overcrowded transportation infrastructure, high unemployment rates,

a growing informal sector, extreme poverty, and severe environmental degradation. These

conditions set metabolic rates in low-income megacities at levels not comparable to those of

high-income regions. Consequently, regional and global disparities exist among the resource

and waste flows of the world’s 27 megacities.

Almost every low/middle income megacity has been the focus of a solid waste study, which

attests to the great environmental concern for waste management in these cities, and their

lack of formal recycling programs. Directly associated with these studies is the informal sector

and its role in the diversion of solid wastes. Waste recycling in low/middle income cities is

largely an informal sector activity: researchers in South and Southeast Asian megacities

report that nearly one-third of the solid waste stream can be sorted and recycled by informal

traders and collectors. A well-established informal sector is therefore critical to improve the

waste-collection efficiency ratios in these regions. This represents a relevant challenge for

megacities, and results in a trade-off between the urgency to eradicate slums and the critical

role of the informal sector in waste collection and recycling. Equally critical is the flow of water

and wastewater: megacities with sprawling slums and informal settlements are faced with

added demands on water supply. Access to water, sewerage, and wastewater treatment has

not matched population growth and urban sprawl—a shortfall that is exacerbated by large


31

amounts of unaccounted-for water in megacities. This further reduces the efficiency of the

urban water metabolism. The literature reports that 30 to 50 percent of the total water supply

in these cities is lost to theft, illegal connections, and/or deteriorating pipelines. Finally,

transportation in low/middle income regions has received much attention in the metabolism

literature. Stress on transportation infrastructure and increased fuel consumption, CO2

emissions, and air pollution in megacities are outcomes of an accelerated transport metabolism

whose most studied cause is the rise in private car ownership.

Energy metabolism is another vital aspect of megacities, especially in low/middle income

regions where urban growth triggers intense competition for land, water, and other natural

resources. This is particularly evident in China (e.g., Shanghai and the megacities of the Pearl

River delta—Guangzhou and Shenzhen), and in Africa, Middle America, and South America

where energy metabolism is affected by electricity theft, access to energy sources, and

inefficient and polluting energy consumption patterns and practices. These relations are very

different from those of high-income regions where the growth of megacities into dispersed

forms mostly influences energy consumption for transportation of goods and people.

To summarize the global synthesis of metabolism literature, we provide a table of the main

research topics investigated in all megacities (Table 1). The aim of the table is to give a

thematic overview of the literature, and to highlight specific aspects of the urban metabolism

that have been investigated in megacities. The studies reviewed in this working paper have

been arranged into thematic categories (materials, solid wastes, water, energy, transportation,

and the informal sector), which show clusters and possible gaps in the metabolism literature,

and that can direct readers to particular cities, regions, or flows of the urban metabolism.


32

TABLE 1 - Thematic overview of urban metabolism studies in megacities

Megacity Materials Wastes Water Energy Transportation Informal

sector

London IMW

(2002) IMW (2002) IMW (2002) IMW, 2002 IMW (2002)

Paris Barles (2009)

Barles (2007b)

Barles (2007b) Kim & Barles

(2012)

Moscow Oldfield (1999)

Myagkov (2004)

Myagkov (2004)

New York City

Swaney et al. (2012)

Themelis et al. (2002)

Swaney et al. (2012)

Protopapas et al. (2000)

NYC (2012)

Los Angeles

Ngo & Pataki (2008)

Ngo & Pataki (2008)

Ngo & Pataki (2008)

Ngo & Pataki (2008)

Mexico City

Tortajada (2006) Romero Lankao

(2007) Schifter et al.

(2005)

Rio de Janeiro

Dubeux & La

Rovere (2007)

Dubeux & La

Rovere (2007)

Ribeiro & Balassiano

(1997)

São Paulo Vasconcellos

(2005)

Buenos Aires

Bravo et al.

(2008)

Lagos Kofoworola

(2007) Oyegoke et al.

(2012) Aderogba (2011)

Aderogba (2011)

Cairo

Meyer (1987) Fahmi (2005)

Huzayyin &

Salem (2013)

Meyer (1987) Fahmi (2005)

Tehran

Damghani et al.

(2008) Abduli (1995)

Kakouei et al.

(2012)

Istanbul Kanat (2010)

Altinbilek (2006)

Dhaka

Hai & Ali (2005)

Yousaf & Rahman (2007)

Matter et al. (2013)

Haq (2006) Matter et al.

(2013)

Karachi CDGK (2007)

CDGK (2007)

Ali et al. (1998)

Khatib et al. (1990)

CDGK (2007) CDGK (2007) CDGK (2007)

Dehli

Agarwal (2005)

Talyon et al. (2008)

Rai (2011) Sagane (2000)

Chavez et al. (2012)

Singh & Sharma (2012)

Sharma & Pundir (2008)

Talyon et al. (2008) Agarwal (2005)

Mumbai Reddy (2013)

Reddy (2013)

Mahadevia et al. (2005)

Reddy (2013) Sagane (2000)

Reddy (2013)

Kolkata Sivaramak

rishan (2013)

Das et al. (2011)

Harza & Goel (2009)

Chattopadhy

Sivaramakrishan (2013)

Sagane (2000) Basu & Main

(2001)

Sivaramakrishan (2013)

Jana et al. (2010)


33

ay et al. (2009)

Jana (1998) Carlisle (2013)

Manila Ajero (2002) Ajero (2002) Ajero (2002)

Jakarta Sugar et al.

(2013)

Seoul Seo & Hwang (1999)

Yi et al. (2011)

Yoon & Jo (2002)

Lee et al. (2007)

Praskievicz and Chang (2009)

Tokyo Hanya & Ambe (1977)

Hanya & Ambe (1977)

Hara & Mino (2008)

Yoon & Jo (2002) Katsumi (1990)

Hanya & Ambe (1977)

Otaki et al. (2007)

Udagawa (1994) Maeda et al.

(1996) Takahasi (2000)

Osaka Shimoda &

Mizuno (2000)

Shimoda &

Mizuno (2000)

Beijing

Zhang et al. (2013) Li et al. (2012)

Guo et al. (2014)

Zhang et al. (2013)

Xiao et al. (2007) Li et al. (2009)

Zhang et al. (2010)

Zhang et al. (2013)

Liu et al. (2011b, 2012) Dhakal (2009)

Li et al. (2009)

Shanghai

Zhang et al. (2008)

Ward & Li (1993)

Zhang et al. (2008)

Ward & Liang (1995)

Zhang et al. (2008)

Liu et al. (2011a)

Li et al. (2010) Dhakal (2009)

Guangzhou

Chung & Poon

(2001, 1998)

Zhao (2010)

Dhakal (2009)

Shenzhen Zhang &

Yang (2007) Zhang & Yang

(2007)

Zhang & Yang (2007)

Dhakal (2009)

Source: own elaboration


34

4 Closing remarks

In closing, we acknowledge that a significant barrier to conducting metabolism studies in cities

is access to sufficient and reliable data at the appropriate scale. While this may be true of most

cities, our review of the literature on megacities has revealed an abundance of research that

tracks single, specific flows of the urban metabolism — e.g., electricity, sewerage, solid waste,

food, construction debris — especially for megacities of low/middle income status. The

literature is also noted for its recency, with much of the work being conducted in the past 10

years. In that result alone we expose the topical nature of the urban metabolism and its

relevance to issues of immediate concern to megacities, such as population growth,

environmental degradation, urban sustainability, and quality of life. A well-synthesized

collection of metabolism studies can help to facilitate research in these areas, and enhance

understanding of the ecological performance of the world’s biggest cities.


35

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