TY - JOUR
T1 - Assessing the sustainability of emerging technologies
T2 - A probabilistic LCA method applied to advanced photovoltaics
AU - Blanco, Carlos F.
AU - Cucurachi, Stefano
AU - Guinée, Jeroen B.
AU - Vijver, Martina G.
AU - Peijnenburg, Willie J.G.M.
AU - Trattnig, Roman
AU - Heijungs, Reinout
PY - 2020/6/20
Y1 - 2020/6/20
N2 - 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.
AB - 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.
KW - Emerging technologies
KW - Global sensitivity analysis
KW - LCA
KW - Life cycle assessment
KW - Sustainability assessment
KW - Uncertainty
UR - http://www.scopus.com/inward/record.url?scp=85081728036&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85081728036&partnerID=8YFLogxK
U2 - 10.1016/j.jclepro.2020.120968
DO - 10.1016/j.jclepro.2020.120968
M3 - Article
AN - SCOPUS:85081728036
SN - 0959-6526
VL - 259
SP - 1
EP - 8
JO - Journal of Cleaner Production
JF - Journal of Cleaner Production
M1 - 120968
ER -