Life cycle assessment of emerging technologies: Evaluation techniques at different stages of market and technical maturity
Joule A. Bergerson,
Adam Brandt,
Joe Cresko,
Michael Carbajales‐Dale,
Heather L. MacLean,
H. Scott Matthews,
Sean McCoy,
Marcelle McManus,
Shelie A. Miller,
William R. Morrow,
I. Daniel Posen,
Thomas Seager,
Timothy Skone and
Sylvia Sleep
Journal of Industrial Ecology, 2020, vol. 24, issue 1, 11-25
Abstract:
Life cycle assessment (LCA) analysts are increasingly being asked to conduct life cycle‐based systems level analysis at the earliest stages of technology development. While early assessments provide the greatest opportunity to influence design and ultimately environmental performance, it is the stage with the least available data, greatest uncertainty, and a paucity of analytic tools for addressing these challenges. While the fundamental approach to conducting an LCA of emerging technologies is akin to that of LCA of existing technologies, emerging technologies pose additional challenges. In this paper, we present a broad set of market and technology characteristics that typically influence an LCA of emerging technologies and identify questions that researchers must address to account for the most important aspects of the systems they are studying. The paper presents: (a) guidance to identify the specific technology characteristics and dynamic market context that are most relevant and unique to a particular study, (b) an overview of the challenges faced by early stage assessments that are unique because of these conditions, (c) questions that researchers should ask themselves for such a study to be conducted, and (d) illustrative examples from the transportation sector to demonstrate the factors to consider when conducting LCAs of emerging technologies. The paper is intended to be used as an organizing platform to synthesize existing methods, procedures and insights and guide researchers, analysts and technology developer to better recognize key study design elements and to manage expectations of study outcomes.
Date: 2020
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https://doi.org/10.1111/jiec.12954
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