Conclusionsĭata quality scores and inherent (i.e. Monte Carlo sampling was the most popular method used for propagating uncertainty results, regardless of LCA type.

However, there are currently no widely applied methods to specifically account for these sources of uncertainty other than sensitivity analysis. allocation in attributional LCA versus the definition of market-mediated substitution scenarios in consequential LCA). There are also sources of uncertainty specific to each kind of LCA-in particular related to the resolution of multi-functionality problems (i.e. Parameter uncertainty is most often reported, although the other types are considered equally important. There are many different sources of uncertainty in LCA, which can be classified as parameter, scenario or model uncertainty. Less than 20% of LCA studies published in the past five years reported any kind of uncertainty analysis. Observed practices were compared to best practice recommendations from methods papers, and additional recommendations were advanced. Common sources and methods for analysis of uncertainty in both attributional and consequential LCA were described, and their frequency of application evaluated. MethodsĪll relevant LCA methods papers as well as case studies (amounting to 2687 journal articles) published from 2014 to 2018 in the top seven journals publishing LCA studies were reviewed. This paper answers these questions based on a review of recent LCA studies and methods papers, and advances recommendations for improved practice. To date, little research has been reported regarding the comparative sources of uncertainty (and their relative importance) and how, or how commonly, they are quantified in attributional and consequential LCA. However, the large amount of uncertainty characteristic of LCA studies reduces confidence in results. Life cycle assessment (LCA) is intended as a quantitative decision support tool.

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