Quantified Uncertainties in Comparative Life Cycle Assessment: What Can Be Concluded?

Angelica Mendoza Beltran*, Valentina Prado, David Font Vivanco, Patrik J.G. Henriksson, Jeroen B. Guinée, Reinout Heijungs

*Corresponding author for this work

    Research output: Contribution to JournalArticleAcademicpeer-review

    Abstract

    Interpretation of comparative Life Cycle Assessment (LCA) results can be challenging in the presence of uncertainty. To aid in interpreting such results under the goal of any comparative LCA, we aim to provide guidance to practitioners by gaining insights into uncertainty-statistics methods (USMs). We review five USMs - discernibility analysis, impact category relevance, overlap area of probability distributions, null hypothesis significance testing (NHST), and modified NHST-and provide a common notation, terminology, and calculation platform. We further cross-compare all USMs by applying them to a case study on electric cars. USMs belong to a confirmatory or an exploratory statistics' branch, each serving different purposes to practitioners. Results highlight that common uncertainties and the magnitude of differences per impact are key in offering reliable insights. Common uncertainties are particularly important as disregarding them can lead to incorrect recommendations. On the basis of these considerations, we recommend the modified NHST as a confirmatory USM. We also recommend discernibility analysis as an exploratory USM along with recommendations for its improvement, as it disregards the magnitude of the differences. While further research is necessary to support our conclusions, the results and supporting material provided can help LCA practitioners in delivering a more robust basis for decision-making.

    Original languageEnglish
    Pages (from-to)2152-2161
    Number of pages10
    JournalEnvironmental Science and Technology
    Volume52
    Issue number4
    DOIs
    Publication statusPublished - 20 Feb 2018

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