Assessing the sustainability of emerging technologies: A probabilistic LCA method applied to advanced photovoltaics

JOURNAL OF CLEANER PRODUCTION

卷:259

Article

Blanco, Carlos F.¹  Cucurachi, Stefano¹  Guinee, Jeroen B.¹  Vijver, Martina G.¹  Peijnenburg, Willie J. G. M.^1,2  Trattnig, Roman^3,4  Heijungs, Reinout^1,5 

[1] Leiden Univ, Inst Environm Sci CML, Leiden, Netherlands

[2] Natl Inst Publ Hlth & Environm RIVM, Ctr Safety Subst & Prod, Bilthoven, Netherlands

[3] Joanneum Res Forsch Gesell mbH MATERIALS, Inst Surface Technol, Weiz, Austria

[4] Joanneum Res Forsch Gesell mbH MATERIALS, Photon Ctr, Weiz, Austria

[5] Vrije Univ Amsterdam, Dept Econometr & Operat Res, Amsterdam, Netherlands

关键词: Life cycle assessment;    Uncertainty;    Global sensitivity analysis;    Emerging technologies;    LCA;    Sustainability assessment;   

DOI  :  10.1016/j.jclepro.2020.120968

来源: Elsevier

【 摘 要 】

A key source of uncertainty in the environmental assessment of emerging technologies is the unpredictable manufacturing, use, and end-of-life pathways a technology can take as it progresses from lab to industrial scale. This uncertainty has sometimes been addressed in life cycle assessment (LCA) by performing scenario analysis. However, the scenario-based approach can be misleading if the probabilities of occurrence of each scenario are not incorporated. It also brings about a practical problem; considering all possible pathways, the number of scenarios can quickly become unmanageable. We present a modelling approach in which all possible pathways are modelled as a single product system with uncertain processes. These processes may or may not be selected once the technology reaches industrial scale according to given probabilities. An uncertainty analysis of such a system provides a single probability distribution for each impact score. This distribution accounts for uncertainty about the product system's final configuration along with other sources of uncertainty. Furthermore, a global sensitivity analysis can identify whether the future selection of certain pathways over others will be of importance for the variance of the impact score. We illustrate the method with a case study of an emerging technology for front-side metallization of photovoltaic cells. (C) 2020 Elsevier Ltd. All rights reserved.

【 授权许可】

Free