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Implementation of uncertainty analysis and moment‐independent global sensitivity analysis for full‐scale life cycle assessment models
Cucurachi, S.; Blanco Rocha, C.F.; Steubing, B.R.P.; Heijungs, R. 2021
Implementation of uncertainty analysis and moment‐independent global sensitivity analysis for full‐scale life cycle assessment models
Article / Letter to editor
open access
Life cycle assessment (LCA) models and databases have increased in size, resolution, and complexity, requiring analysts to rely on an ever-increasing number of uncertain model inputs. Such... Show moreLife cycle assessment (LCA) models and databases have increased in size, resolution, and complexity, requiring analysts to rely on an ever-increasing number of uncertain model inputs. Such increased complexity calls for systematic approaches to assessing the uncertainty of the output results of LCA models and the sensitivity of LCA model outputs to the model's uncertain inputs. In this contribution, we provide a theoretical basis and present a practical software implementation that combines uncertainty analysis and moment-independent global sensitivity analysis, which can be readily applied to full-scale LCA models. We implemented our approach in the Activity-Browser open source LCA software and it is made available for use in LCA studies. We demonstrate the approach and software implementation with a case study of crystalline silicon photovoltaics. Show less
Assessing the sustainability of emerging technologies: A probabilistic LCA method applied to advanced photovoltaics
Blanco Rocha, C.F.; Cucurachi, S.; Guinee, J.B.; Vijver, M.G.; Peijnenburg, W.J.G.M.; Trattnig, R.; Heijungs, R. 2020
Assessing the sustainability of emerging technologies: A probabilistic LCA method applied to advanced photovoltaics
Article / Letter to editor
open access
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... Show more

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.

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