Advanced LCA – 12-716

1. Advanced LCA – 12-716 Lecture 2

2. Today’s lecture • Data sources and issues for EIOLCA • Data consistency checks

3. Common research “problems” • 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.

4. 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!)

5. Materials flows and lifestyles Source: J. Ausubel, “The environment for future business” (1998)

6. Energy use in US and Japanese economies (1999) Sources: US Annual Energy Outlook, Integrated Energy Statistics, Maddison (for PPP)

7. US industrial energy use • Boyd Source: ORNL, “Scenarios for a Clean Energy Future” (2000)

8. Japan industrial energy use Source: Integrated Energy Statistics (2000)

9. Data types What 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

10. Geographical variation Differences in: • Technology • Producer prices • Energy sectors

11. 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:

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

13. The Net as search/organizing mechanism • google and scholar.google.com • Sciencedirect.com • Web of Science • Proquest (esp. professional literature) Keywords: remember to try units (e.g. MJ, $) and names of inputs and outputs Also: getting better daily, but bear in mind that many resources are still only in print.

14. 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)

15. 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

16. Engineering literature • Encylopedias – e.g. Kirk Othmer, Ullman’s • Professional magazines – e.g. Semiconductor International • Topical technology books – e.g. VSLI Manufacturing)

17. 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.

18. Industry associations • International Iron and Steel Institute (www.worldsteel.org) • Semiconductor Industry Association (www.sia.org) • Japan Building Association (only in Japanese)

19. 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)

20. 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

21. 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)

22. 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?

23. 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!

24. 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.

25. Data consistency checks • Multiple sources • Mass balance • Micro to macro scaling

26. 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

27. 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.

28. Materials balance Principle: • 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

29. 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)

30. 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.

31. 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?

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

33. Exta Credit Question Show effects for each of 500 sectors?