Document 202144
HOW TO DO REGIONALIZED LCA Chris Mutel, Stephan Pfister, Stefanie Hellweg ETH Zurich, InsDtute for Environmental Engineering, Ecological Systems Design Group Email contact: [email protected] Regionaliza*on -‐ easy, but hard 2 www.ifu.ethz.ch/ESD Regionaliza*on -‐ easy, but hard 3 www.ifu.ethz.ch/ESD Regionaliza*on -‐ easy, but hard 4 www.ifu.ethz.ch/ESD Regionaliza*on -‐ easy, but hard 5 www.ifu.ethz.ch/ESD 3 difficul*es 6 www.ifu.ethz.ch/ESD 3 difficul*es • Uncertainty in inventory spa/al data 6 www.ifu.ethz.ch/ESD 3 difficul*es • Uncertainty in inventory spa/al data • Choosing impact assessment spa/al scale 6 www.ifu.ethz.ch/ESD 3 difficul*es • Uncertainty in inventory spa/al data • Choosing impact assessment spa/al scale • Matching inventory and impact assessment spa/al supports 6 www.ifu.ethz.ch/ESD Case study example 5002 power plants 35 fuel types impacts of freshwater consumpDon www.ifu.ethz.ch/ESD 7 7 Inventory spa*al uncertainty 8 www.ifu.ethz.ch/ESD Inventory uncertainty Probability 9 www.ifu.ethz.ch/ESD Inventory uncertainty Probability 10 www.ifu.ethz.ch/ESD Spa*al Autocorrela*on 0.8 0.73 0.67 0.75 0.78 0.8 0.32 0.2 0.43 0.95 0.88 0.9 0.88 0.85 0.72 0.82 0.16 0.78 0.32 0.32 0.92 0.91 0.87 0.90 0.88 0.6 0.18 0.3 0.26 0.41 0.97 0.93 0.84 0.91 0.95 0.55 0.28 0.16 0.33 0.7 0.98 1.0 0.86 0.83 0.81 0.25 0.69 0.22 0.7 0.56 0.54 0.03 www.ifu.ethz.ch/ESD 11 Regionalized IA Disaggregated Highly aggregated www.ifu.ethz.ch/ESD 12 Regionalized IA Disaggregated Highly aggregated www.ifu.ethz.ch/ESD 12 Regionalized IA Disaggregated Highly aggregated www.ifu.ethz.ch/ESD 12 Regionalized IA Disaggregated Highly aggregated www.ifu.ethz.ch/ESD 12 Global autocorrela*on 13 www.ifu.ethz.ch/ESD Comparing spa*al scales 14 AutocorrelaDon-‐opDmized www.ifu.ethz.ch/ESD Watershed-‐based spaDal scale 13 spaDal scale Change of support problem 15 www.ifu.ethz.ch/ESD Change of support problem 1 A= 4 16 www.ifu.ethz.ch/ESD Change of support problem Probability 17 www.ifu.ethz.ch/ESD Change of support problem 18 www.ifu.ethz.ch/ESD Change of support problem 3e-‐4 -‐> 2e-‐4 3e-‐4 -‐> 2e-‐5 5e-‐4 -‐> 3e-‐5 3e-‐4 -‐> 3e-‐5 0.42 -‐> 0.49 0.48 -‐> 0.50 3e-‐4 -‐> 3e-‐4 5e-‐4 -‐> 5e-‐4 0.09 -‐> 0.002 3e-‐4 -‐> 1.7e-‐3 2e-‐4 -‐> 4e-‐4 4e-‐4 -‐> 5e-‐5 2e-‐4 -‐> 4e-‐4 18 www.ifu.ethz.ch/ESD Case study results 19 www.ifu.ethz.ch/ESD Conclusions 20 www.ifu.ethz.ch/ESD Conclusions • Lack of data and so<ware prevented LCA ✓Regionalized impact assessment methods ✓Regionalized inventory databases 20 www.ifu.ethz.ch/ESD Conclusions • Lack of data and so<ware prevented LCA ✓Regionalized impact assessment methods ✓Regionalized inventory databases • Inventory datasets •Integrated uncertainty (even spa/al) assessment possible 20 www.ifu.ethz.ch/ESD Conclusions • Lack of data and so<ware prevented LCA ✓Regionalized impact assessment methods ✓Regionalized inventory databases • Inventory datasets •Integrated uncertainty (even spa/al) assessment possible • Impact assessment methods •Systema/cally choose spa/al scale •Provide background emissions 20 www.ifu.ethz.ch/ESD Thanks! [email protected] Further reading: Aldstadt, J. & GeDs, A. (2006). Using AMOEBA to Create a Spa4al Weights Matrix and Iden4fy Spa4al Clusters. Geographical Analysis, 38 (4), 327-‐343. Arlinghaus, S., ed. Prac4cal Handbook of Spa4al Sta4s4cs. CRC Press: Boca Raton, FL, 1996. GeDs, A. (2009). Spa4al Weights Matrices. Geographical Analysis, 41 (4), 404-‐410. Gotway, C. A. & Young, L. J. (2002). Combining Incompa4ble Spa4al Data. Journal of the American StaDsDcal AssociaDon, 97 (458), 632-‐648. Pocng, J. & Hauschild, M. (2006). Spa4al Differen4a4on in Life Cycle Impact Assessment: A decade of method development to increase the environmental realism of LCIA. The InternaDonal Journal of Life Cycle Assessment, 11, 11-‐13. AT: Impact of Spa*al Uncertainty • Ignoring uncertainty is not realis/c • > 50% of all plants intersected an impact assessment spa/al unit with a factor of 2 difference in characteriza/on factor www.ifu.ethz.ch/ESD 22 AT: Reservoir water consump*on • Data from NID • Average two methods to es/mate evapora/on • Region-‐specific evapora/on (Pfister et al 2011) • Combine area w/ loca/on-‐specific evapora/on (FAO) • Alloca/on based on priority rank • Smaller percentage for run-‐of-‐river www.ifu.ethz.ch/ESD 23 AT: Fossil fuel evapora*on • Cooling systems from EIA 767 reports (2005, nuclear 2000) • EvaporaDon rates do not vary in space • DifferenDate between: • Once through, freshwater • Once through, salt water • RecirculaDng • Mechanical drae, wet process • Mechanical drae, dry process • Mechanical drae, wet/dry process • Coal/biomass • Nuclear • Natural gas/oil www.ifu.ethz.ch/ESD 24 AT: Aggrega*on methodology www.ifu.ethz.ch/ESD 25 AT: Variance in different supports www.ifu.ethz.ch/ESD 26 AT: Not complete disaggrega*on • Numbers, not informa/on • Regionalized LCIA maps are important outputs • Need to be able to interpret them • Gives no spa/al understanding • Appropriate spa/al scale is different for each method www.ifu.ethz.ch/ESD 27 AT: Need for Background Emissions Area-‐weighted CF Emissions-‐ weighted CF Ecosystem damage (PDF-‐m2/year) 7.69 5.39 Human Health (DALYs) 4.5 ·∙ 107 3.7 ·∙ 108 Resource consumpDons (MJ) 18.4 32.5 www.ifu.ethz.ch/ESD 28 AT: Polygon uncertainty • Difficult because no set rela/onship between area and buffer sizes • Preliminary method relates number of ver/ces to polygon perimeter • Area of further research • Need data set www.ifu.ethz.ch/ESD 29 AT: SoPware • So<ware is open source • Documenta/on and installa/on Jan-‐Mar 2012 • Paper in submission www.ifu.ethz.ch/ESD 30 AT: SoPware www.ifu.ethz.ch/ESD 31
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