Tradeoff Evaluation Improves Comparative Life Cycle Assessment: A Photovoltaic Case Study

Current life cycle assessment (LCA) interpretation practices typically emphasize hotspot identification and improvement assessment. However, these interpretation practices fail in the context of a decision-driven comparative LCA where the goal is to select the best option from a set of dissimilar alternatives. Interpretation of comparative LCA results requires understanding of the trade-offs between alternatives—instances in which one alternative performs better or worse than another—to identify the environmental implications of a specific decision. In this case, analysis must elucidate relative trade-offs between decision alternatives, rather than absolute description of the alternatives individually. Here, typical practices fail. This article introduces a probability distribution-based approach to assess the significance of performance differences among alternatives that allows LCA practitioners to focus analyses on those aspects most influential to the decision, identify the areas that would benefit the most from data refinement given the level of uncertainty, and complement existing hotspot analyses. In a case study of a comparative LCA of five photovoltaic technologies, findings show that thin-film cadmium telluride and amorphous silicon cell panels are most likely to perform better than other alternatives. Additionally, the impact categories highlighted by the new approach are different than those highlighted by typical external normalization practices, suggesting that a decision-driven approach to interpretation would redirect environmental research efforts.