TY - JOUR
T1 - Novel Method of Sensitivity Analysis Improves the Prioritization of Research in Anticipatory Life Cycle Assessment of Emerging Technologies
AU - Ravikumar, Dwarakanath
AU - Seager, Thomas
AU - Cucurachi, Stefano
AU - Prado, Valentina
AU - Mutel, Christopher L.
N1 - Funding Information:
This study is primarily supported by the National Science Foundation (NSF) and the Department of Energy (DOE) under NSF CA No.EEC-1041895 and 1140190, the U.S. Environmental Protection Agency (EPA) under Assistance Agreement No. RD83558001, and the USAID under Cooperative Agreement Number AID-391-A-15-00001. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect those of NSF, DOE, EPA or USAID. We also thank Lise Laurin from EarthShift Global and the anonymous reviewers for the feedback that has improved the quality of this paper.
Publisher Copyright:
© Copyright 2018 American Chemical Society.
PY - 2018/6/5
Y1 - 2018/6/5
N2 - It is now common practice in environmental life cycle assessment (LCA) to conduct sensitivity analyses to identify critical parameters and prioritize further research. Typical approaches include variation of input parameters one at a time to determine the corresponding variation in characterized midpoints or normalized and weighted end points. Generally, those input parameters that cause the greatest variations in output criteria are accepted as the most important subjects of further investigation. However, in comparative LCA of emerging technologies, the typical approach to sensitivity analysis may misdirect research and development (R&D) toward addressing uncertainties that are inconsequential or counterproductive. This paper presents a novel method of sensitivity analysis for a decision-driven, anticipatory LCA of three emerging photovoltaic (PV) technologies: amorphous-Si (a-Si), CdTe and ribbon-Si. Although traditional approaches identify metal depletion as critical, a hypothetical reduction of uncertainty in metal depletion fails to improve confidence in the environmental comparison. By contrast, the novel approach directs attention toward marine eutrophication, where uncertainty reduction significantly improves decision confidence in the choice between a-Si and CdTe. The implication is that the novel method will result in better recommendations on the choice of the environmentally preferable emerging technology alternative for commercialization.
AB - It is now common practice in environmental life cycle assessment (LCA) to conduct sensitivity analyses to identify critical parameters and prioritize further research. Typical approaches include variation of input parameters one at a time to determine the corresponding variation in characterized midpoints or normalized and weighted end points. Generally, those input parameters that cause the greatest variations in output criteria are accepted as the most important subjects of further investigation. However, in comparative LCA of emerging technologies, the typical approach to sensitivity analysis may misdirect research and development (R&D) toward addressing uncertainties that are inconsequential or counterproductive. This paper presents a novel method of sensitivity analysis for a decision-driven, anticipatory LCA of three emerging photovoltaic (PV) technologies: amorphous-Si (a-Si), CdTe and ribbon-Si. Although traditional approaches identify metal depletion as critical, a hypothetical reduction of uncertainty in metal depletion fails to improve confidence in the environmental comparison. By contrast, the novel approach directs attention toward marine eutrophication, where uncertainty reduction significantly improves decision confidence in the choice between a-Si and CdTe. The implication is that the novel method will result in better recommendations on the choice of the environmentally preferable emerging technology alternative for commercialization.
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U2 - 10.1021/acs.est.7b04517
DO - 10.1021/acs.est.7b04517
M3 - Article
C2 - 29734807
AN - SCOPUS:85046707708
SN - 0013-936X
VL - 52
SP - 6534
EP - 6543
JO - Environmental Science and Technology
JF - Environmental Science and Technology
IS - 11
ER -