Advanced LCA – 12-716

Lecture 2

Today’s lecture

• Data sources and issues for EIOLCA

• Data consistency checks

Common research “problems”1. Studying impact where the product/service has

little influence: - Energy use of digital distribution of company

environmental reports– Alternatives to lead-tin solder (small portion of landfill

lead but… relevant for informal recycling, but not LCA problem yet)

2. The “method trap”: studying what has already been understood with more complicated method to improve accuracy

– Is there an important qualitative question which the added accuracy will answer?

3. The “nobody’s done it” trap: maybe there’s a reason why.

Selecting research topics• Tendency to be driven by

methodological/community level questions• Certainly no harm in doing more studies

but:

There are many “double dividend” LCA problems: methodological and significant societal relevance.(Isaac Newton didn’t do any LCAs!)

Materials flows and lifestyles

Source: J. Ausubel, “The environment for future business” (1998)

Energy use in US and Japanese economies (1999)

US JapanTotal energy demand (10^10 MJ) 10,214 1,526industrial 36% 48%commercial 17% 13%residential 20% 14%transport 27% 25%Energy per capita (GJ/ person) 366 121Per GDP (MJ/PPP $) 13 6

Sources: US Annual Energy Outlook, Integrated Energy Statistics, Maddison (for PPP)

US industrial energy use

1. Boyd

Source: ORNL, “Scenarios for a Clean Energy Future” (2000)

Japan industrial energy use

Source: Integrated Energy Statistics (2000)

Breakdown of industry energy use in Japan agriculture, 6%

mining, 0.4%

construction, 2%

foods, 3%

fabrics, 2%

paper/pulp, 6%

chemicals, 29%

ceramics, 7%

iron/steel, 24%

non-ferrous, 2%

metal machinery, 6%

other, 13%

Data typesWhat kind of data are relevant? Depends

on LCA question, but in general:• Technologies in the industry• Material input-output• Technological progress• Geographical distribution of production

Geographical variation

Differences in:1. Technology2. Producer prices3. Energy sectors

International variations in carbon intensity of electricity

• Electricity is a major player in a number of environmental impacts (e.g. CO2, SOx, NOx emissions)

• Different mixes (and to lesser extent efficiencies) of coal, gas, hydro, nuclear and other generation induce huge international variations in emissions:

US Japan France

CO2 (g per kWh) 593 355 70

Data sources for Process LCA

• LCA databases• Engineering literature• Industry associations• Government agencies• Company reports(see review paper for more on some of these)

The Net as search/organizing mechanism

1. google and scholar.google.com2. Sciencedirect.com3. Web of Science4. Proquest (esp. professional literature)

Keywords: remember to try units (e.g. MJ, $) and names of inputs and outputsAlso: getting better daily, but bear in mind that

many resources are still only in print.

Some LCI/LCA process databases

• IDEMAT – developed at U. Delft. Includes impact assessment.

• BUWAL 250 – Swiss, mainly packaging• GaBi – collected by LCA consulting firm • Ecoinvent – Swiss based, supposedly best

documented.• JEMAI (Japanese industry data, only in

Japanese)

Government agencies • US Economic Census – many sectors

(http://www.census.gov/econ/census02/guide/INDSUMM.HTM )

• United States Geological Service – mineral commodities (http://minerals.usgs.gov/minerals/)

• US Residential Energy Consumption Survey (http://www.eia.doe.gov/emeu/recs/)

• Europe Integrated Pollution Prevention Bureau (http://www.epa.ie/Licensing/IPPCLicensing/BREFDocuments/)

• Plus various, but many around the world do not put information on the web yet

Engineering literature

• Encylopedias – e.g. Kirk Othmer, Ullman’s

• Professional magazines – e.g. Semiconductor International

• Topical technology books – e.g. VSLI Manufacturing)

Company environmental reports • WMC – energy, SO2 emissions, water use data from

Australia’s Olympic Dam, copper, uranium, gold, silver co-product mining

http://hsecreport.bhpbilliton.com/wmc/2004/performance/odo/data/index.htm

• HP - Social and Environmental Responsibility Report. (http://www.hp.com/hpinfo/globalcitizenship/csr/csrreport02/hp_csr_full_lo.pdf)

Only firm level data, but consulting firm data on economic value of different products.

In general very hard to find product normalized data.

Industry associations

• International Iron and Steel Institute (www.worldsteel.org)

• Semiconductor Industry Association (www.sia.org)

• Japan Building Association (only in Japanese)

Sectoral Classification Schemes

• ISIC – International Standard Industrial Classification

• NAICS – North Amer. Classification System

• NACE – Statistical Classification of Economic Activities in the EC

• Point: There’s a lot. For bridges between systems and comparisons, see Eurostat’s RAMON system (Google it)

Input-Output Tables• Best to use a common set with standard

Classification (if >1) OECD has one– Uses 41 sector ISIC classification– Available for 20 countries

» W Europe, USA, Canada, Australia, China, Japan, Korea, Brazil

– Notice many countries don’t produce one!• dsti.contact@oecd.org , mention Input-Output

in title and provide:– Name, Email, Institution, Country of Residence

Environmental Data • Lots of other groups doing EIO-type work

– Academic– Country-wide

• Some we know of:– Japan (Nansai and Moriguchi): details of 400 sector

model (1990, 1995, 2000, CO2 plus SOx and NOx(http://www-cger.nies.go.jp/publication/D031/CGER/Web/eng/index-e.htm )

– UK – Detailed Country-wide effort » http://www.statistics.gov.uk/CCI/nscl.asp?ID=6805

– Europe-wide GHG accounting» Available on EuroStat: Europa (Google it)

EIO-LCA Data Example• Hopefully read documentation excerpt• Where does EIO-LCA data come from?• What all needs to be done to make it

useable on the web?

Data Availability—4 Scenarios • Have IO and Enviro data

– Best case scenario• Don’t have IO or Enviro data

– Generally assume = another country (US for developed world, China for developing)

• Have 1 but not the other– Harder to say what to do– Either way you’re assuming!

Data consistency checks

Meta-question: how do we know if the numbers we base our results on are reasonable?

Almost always secondary sources, so never know for sure, but … different consistency checks are available.

Data consistency checks

1. Multiple sources2. Mass balance3. Micro to macro scaling

Multiple sources

Principle: where possible, collect several sources describing same “thing”:

• Process input/output – find from different facility or aggregation

• Economic input output – can try different country (rough check)

• Prices/product bill of materials

Recurring issues

• Often need to try to use different types or year of data for comparison.

• Often difficult to separate variation in data quality with type, year, aggregation, etc.

Materials balancePrinciple:• Mass is conserved (near enough) or

• What comes in must come out (and vice versa) or

• Sum of masses of inputs = sum of masses of outputs

Micro to Macro scaling

Principle: any micro-result (e.g. energy needed to make one widget) must make sense of at the macro-level

Scale up micro-result and check with known macro-data

Recall examples from last class (water, gold in computers)

Conclusions • Data collection skills not only useful in getting

initial results, but in checking the work of yourself and others.

• Many of these checks are labor intensive, often will not have time to do for all data, but….

At least try to do for key data points.

Producer and Purchaser Prices

• Recall EIO-LCA (currently) uses just producer costs – i.e., only reflective of how much it costs to

make, not how much to buy– Buy = purchaser price– What is the difference?– What makes up the difference?– How can we convert between them?

Producer / Purchaser Prices• See spreadsheet linked for today• How would we use it?• So instead of “$20,000 car”…?

Exta Credit Question

Show effects for each of 500 sectors?