Novel Method of Sensitivity Analysis Improves the Prioritization of Research in Anticipatory Life Cycle Assessment of Emerging Technologies

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