Abstract
PurposeIdentification of environmentally preferable alternatives in a comparative life cycle assessment (LCA) can be challenging in the presence of multiple incommensurate indicators. To make the problem more manageable, some LCA practitioners apply external normalization to find those indicators that contribute the most to their respective environmental impact categories. However, in some cases, these results can be entirely driven by the normalization reference, rather than the comparative performance of the alternatives. This study evaluates the influence of normalization methods on interpretation of comparative LCA to facilitate the use of LCA in decision-driven applications and inform LCA practitioners of latent systematic biases. An alternative method based on significance of mutual differences is proposed instead.MethodsThis paper performs a systematic evaluation of external normalization and describes an alternative called the overlap area approach for the purpose of identifying relevant issues in a comparative LCA. The overlap area approach utilizes the probability distributions of characterized results to assess significant differences. This study evaluates the effects in three LCIA methods, through application of four comparative studies. For each application, we call attention to the category indicators highlighted by each interpretation approach.Results and discussionExternal normalization in the three LCIA methods suffers from a systematic bias that emphasizes the same impact categories regardless of the application. Consequently, comparative LCA studies that employ external normalization to guide a selection may result in recommendations dominated entirely by the normalization reference and insensitive to data uncertainty. Conversely, evaluation of mutual differences via the overlap area calls attention to the impact categories with the most significant differences between alternatives. The overlap area approach does not show a systematic bias across LCA applications because it does not depend on external references and it is sensitive to changes in uncertainty. Thus, decisions based on the overlap area approach will draw attention to tradeoffs between alternatives, highlight the role of stakeholder weights, and generate assessments that are responsive to uncertainty.ConclusionsThe solution to the issues of external normalization in comparative LCAs proposed in this study call for an entirely different algorithm capable of evaluating mutual differences and integrating uncertainty in the results.
Highlights
IntroductionResearch in life cycle assessment (LCA) methods focus predominantly on building life cycle inventory (LCI) databasesInt J Life Cycle Assess (2017) 22:2018–2029(Frischknecht et al 2004; Suh and Huppes 2005; Miller and Theis 2006; Dones et al 2007; Verbeeck and Hens 2010; Jungbluth et al 2012), calculating new midpoint characterization factors (Koellner and Scholz 2007; Pfister et al 2009; Van Zelm et al 2009; Gallego et al 2010; Saad et al 2011; Hauschild et al 2013), and improving end-point damage modeling (Hayashi et al 2006; Boulay et al 2011; Motoshita et al 2014)
The overlap area approach does not show a systematic bias across life cycle assessment (LCA) applications because it does not depend on external references and it is sensitive to changes in uncertainty
The solution to the issues of external normalization in comparative LCAs proposed in this study call for an entirely different algorithm capable of evaluating mutual differences and integrating uncertainty in the results
Summary
Research in life cycle assessment (LCA) methods focus predominantly on building life cycle inventory (LCI) databasesInt J Life Cycle Assess (2017) 22:2018–2029(Frischknecht et al 2004; Suh and Huppes 2005; Miller and Theis 2006; Dones et al 2007; Verbeeck and Hens 2010; Jungbluth et al 2012), calculating new midpoint characterization factors (Koellner and Scholz 2007; Pfister et al 2009; Van Zelm et al 2009; Gallego et al 2010; Saad et al 2011; Hauschild et al 2013), and improving end-point damage modeling (Hayashi et al 2006; Boulay et al 2011; Motoshita et al 2014). Less emphasis has been placed on normalization and weighting, which are optional practices in life cycle impact assessment (LCIA). In problems of comparative technology assessment, characterized results alone seldom result in a definitive environmental choice, leaving decision-makers to confront complex environmental tradeoffs largely unaided in examples critical to sustainability (Rowley et al 2012). These environmental tradeoffs exist regardless of the completeness of characterization factors or LCI databases.
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