Hybrid Life Cycle Assessment

1. Hybrid Life Cycle Assessment Sangwon Suh Centre of Environmental Science (CML) Leiden University, the Netherlands

2. Contents Truncation in LCA Hybrid input-output LCA Case Study Conclusion

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4. Truncation in Process LCA Estimated truncation 66% 9~52% Reference Lave et al., 1995 Lenzen, 2001 Method 1st order upstream 3rd order (energy)

5. 1st 2nd 3rd 4th 5th 6th [Lave et al., 1995] [Lenzen., 2001]

6. Input-output based LCI [Donhomae, 1994] [Lave et al., 1995] [Hendrickson et al, 1998]

7. Activated carbon and charcoal Alkali metals Alumina Aluminum chloride Aluminum compounds Aluminum hydroxide (alumina trihydrate) Aluminum oxide Aluminum sulfate Alums Ammonia alum Ammonium chloride, hydroxide, and molybdate Ammonium compounds, except for fertilizer Ammonium perchlorate Ammonium thiosulfate Barium compounds Bauxite, refined Beryllium oxide Bleach (calcium hypochlorite), industrial Bleach (sodium hypochlorite), industrial Bleaches, industrial Bleaching powder, industrial Borax (sodium tetraborate) Boric acid Boron compounds, not produced at mines Borosilicate Brine Bromine, elemental Calcium carbide, chloride, and hypochlorite Calcium compounds, inorganic Calcium metal Carbide Catalysts, chemical Cerium salts Cesium metal Charcoal, activated SIC 2819- Industrial inorganic chemicals, NEC 182 items

8. Why Hybrid ? Meso/Macro Economic Model Engineering Model Complete Aggregated General Accurate Disaggregated Partial Integrated hybrid LCA

9. Hybrid Life Cycle Assessment [Moriguchi et al., 1993] Utilized Japanese input-output table and process data for life cycle CO2 emission of automobile

10. Tired hybrid model Input-output analysis Process analysis Bullard et al. (1978) Engelenburg et al. (1994) Moriguchi et al (1993)

11. Input-output based hybrid model Joshi (1999) Gibbson et al. (1982) + Use + Disposal

12. Integrated Hybrid LCI modeling Integrating the computational structure of LCI [Heijungs & Suh, 2002] : Physical unit/operation time IOA [Stone, et al., 1963] : Monetary unit/total production Full interaction between process and economy

13. Steel Steam 0.5 MJ 1 kg CO2/kg steel 4 kg CO2/ MJ Steam 0.25 kg 1 kg 0.5 MJ Production of Toaster 2 kg CO2/unit toaster production 1 unit Use of Toaster 0.001 kg CO2/ piece of bread toasted 1 unit Disposal of toaster 0.5 kg CO2/unit toaster disposal Integrated Hybrid LCI modeling

14. Integrated Hybrid LCI modeling

15. LC CO2 Contribution by processes

16. Integrated Hybrid LCI modeling

17. Pretreatment of IO table for integration

18. Hybrid matrix

19. Steam 0.263$ Sub Bitumen Coal mining 0.031$ Ind.Bld Ind. Installat’n

21. Case Study Linoleum (a flooring material by Forbo BV) • - Baseline (Existing LCI) • - Hybrid (Cut-offs and capitals : 38 links) • IO LCI (Miscellaneous floor coverings)

23. Percent change 0% 5% ~ 73% (avg. 18%) -85% ~ 124% (avg. 3%) Baseline Hybrid Max IO LCI

24. Strengths Weakness Model Hybrid LCA Process specific Encompassing system boundary Process specific Encompassing system boundary Process specific Truncation Process LCA Encompassing system boundary Aggregation Input-Output LCA Approaches in Life Cycle Inventory Modelling

25. Uncertainties in LCI

26. Uncertainty analyses Perturbation Analysis (Heijungs and Suh, 2002) Monte Carlo simulation (Hendry, 1984, Huijlbregts, 2001) Changes in results due to change in a parameter Location and dispersion of the results due to simultaneous changes in all parameters

27. Monte Carlo simulation Computation of LCI E: Life Cycle Inventory B: Environmental intervention matrix A: Technology matrix y: Functional unit

28. Monte Carlo simulation Basic concept Randomly distributed noise on Environmental intervention matrix Randomly distributed noise on Technology matrix Statistical property, location and dispersion

29. Model building Steps for Monte Carlo simulation Data gathering Extraction of distribution properties Coding and running a program Analyse the results

30. Monte Carlo simulation Model building Process LCA Input-output LCA Hybrid LCA

31. Process LCA(Gorree et al., 2001) Input-output LCA(Suh and Huppes, 2001) Hybrid LCA (Suh and Huppes, 2001) Monte Carlo simulation Data gathering Linoleum 1996 US. IO data and environmental statistics 640900 Hard surface floor coverings, n.e.c. 38 missing flows linked with IO table

32. Considered uncertainty IO part Aggregation Uncertainty Uncertainty due to data age Source data uncertainty in IO table Source data uncertainty in environmental data Process part Uncertainty due to data age Source data uncertainty in technology matrix Source data uncertainty in environmental data

33. 1 10 95 496 X 496 Monte Carlo simulation Extraction of distribution property Ex) Aggregation Uncertainty in IO LCA

34. Monte Carlo simulation Data preparation Ex) Aggregation Uncertainty in IO LCA

37. Narrow distribution but relatively underscored Wider than process analysis but much narrower than IO results and closer to the target value More provable to contain the ‘true values’ but rather wider distribution

40. Accuracy vs. precision

41. APPLAUSE

42. ‘Which is the better’ arguments between process LCA and IO LCA Two sides of a coin: Accuracy vs. precision Process LCA High precision but less accuracy IO LCA High accuracy but less precision

43. Conclusions Hybrid approach generally solves the problem of system boundary in process-LCA conserving process-specificity as much as possible In engineering terms, pure process-LCA is precise but lacks accuracy, while pure IO-LCA is more likely cover the true value but lacks precision. Hybrid LCA combines the two and improves the accuracy while maintaining the overall precision.

44. Thank You