Abstract
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.
| Original language | English |
|---|---|
| Article number | 120968 |
| Pages (from-to) | 1-8 |
| Number of pages | 8 |
| Journal | Journal of Cleaner Production |
| Volume | 259 |
| Early online date | 7 Mar 2020 |
| DOIs | |
| Publication status | Published - 20 Jun 2020 |
Funding
This work was supported by the European Union’s Horizon 2020 Research and Innovation Programme within the project SiTaSol [grant number 727497 ].
| Funders | Funder number |
|---|---|
| Horizon 2020 Framework Programme | 727497 |
| Horizon 2020 Framework Programme |
Keywords
- Emerging technologies
- Global sensitivity analysis
- LCA
- Life cycle assessment
- Sustainability assessment
- Uncertainty