Confronting Uncertainty in Life Cycle Assessment Used for Decision Support: Developing and Proposing a Taxonomy for LCA Studies

Ivan Tengbjerg Herrmann, Michael Zwicky Hauschild, Michael D. Sohn, Thomas E. McKone

    Research output: Contribution to journalJournal articleResearchpeer-review


    The aim of this article is to help confront uncertainty in life cycle assessments (LCAs) used for decision support. LCAs offer a quantitative approach to assess environmental effects of products, technologies, and services and are conducted by an LCA practitioner or analyst (AN) to support the decision maker (DM) in making the best possible choice for the environment. At present, some DMs do not trust the LCA to be a reliable decisionsupport tool—often because DMs consider the uncertainty of an LCA to be too large. The standard evaluation of uncertainty in LCAs is an ex-post approach that can be described as a variance simulation based on individual data points used in an LCA.
    This article develops and proposes a taxonomy for LCAs based on extensive research in the LCA, management, and economic literature. This taxonomy can be used ex ante to support planning and communication between an AN and DM regarding which type of LCA study to employ for the decision context at hand. This taxonomy enables the derivation of an LCA classification matrix to clearly identify and communicate the type of a given LCA. By relating the LCA classification matrix to statistical principles, we can also rank the different types of LCA on an expected inherent uncertainty scale that can be used to confront and address potential uncertainty. However, this article does not attempt to offer a quantitative approach for assessing uncertainty in LCAs used for decision support.
    Original languageEnglish
    JournalJournal of Industrial Ecology
    Issue number3
    Pages (from-to)366–379
    Number of pages14
    Publication statusPublished - 2014


    • Data quality
    • Decision support
    • Industrial ecology
    • Life cycle assessment (LCA)
    • Transparency
    • Variability

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