A critical view on the current application of LCA for new technologies and recommendations for improved practice

Van der Giesen, C.; Cucurachi, S.; Guinee, J.; Kramer, G.J.; Tukker, A.

doi:doi:10.1016/j.jclepro.2020.120904

LCA is a well-known assessment tool that identifies and provides insights on the environmental impacts of products and services over their lifecycle. The guidance provided by the existing manuals typically applies to modelling and assessing environmental impacts ex-post, meaning that information is available from empirical experience after products have been commercially in use for extended periods of time. This information is not available if LCA is applied in an ex-ante manner before a technology is commercially deployed at scale. We identify the major challenges of applying LCA in an ex-ante manner and propose a route forward in dealing with these challenges that combines intuitions from other disciplinary fields. The first challenge is how to model consistent future foreground systems for the incumbent and new technology systems. Learning curves and scenario approaches are the way forward. The second challenge is how to model future background systems. Here a solution is to...Show moreLCA is a well-known assessment tool that identifies and provides insights on the environmental impacts of products and services over their lifecycle. The guidance provided by the existing manuals typically applies to modelling and assessing environmental impacts ex-post, meaning that information is available from empirical experience after products have been commercially in use for extended periods of time. This information is not available if LCA is applied in an ex-ante manner before a technology is commercially deployed at scale. We identify the major challenges of applying LCA in an ex-ante manner and propose a route forward in dealing with these challenges that combines intuitions from other disciplinary fields. The first challenge is how to model consistent future foreground systems for the incumbent and new technology systems. Learning curves and scenario approaches are the way forward. The second challenge is how to model future background systems. Here a solution is to transform existing LCI databases towards future contexts, informed by the Integrated Assessment Models (IAMs) that provide scenarios in line with the Shared Socioeconomic Pathways (SSPs). Finally, uncertainty in exante LCA is of a different nature as in ex-post LCAs. The main difference with conventional LCA studies is the highly uncertain information for the future. To acknowledge this. considerate attention should be attributed to the discussion on these uncertainties, both in the design of the assessment and the data used. Responsive evaluation can play a supportive role here. This will increase the transparency and efficacy of the results because the relevant stakeholders and experts are involved. In this way technology designers and other stakeholders derive insights on the influence of design choices or contextual factors (that are important, but hard to influence) on the potential environmental impacts of their foreseen technology. (C) 2020 The Authors. Published by Elsevier Ltd.Show less

Leiden University Scholarly Publications

View statistics

Documents

In Collections

A critical view on the current application of LCA for new technologies and recommendations for improved practice