Uncertainty in LCA case study due to allocation approaches and life cycle impact assessment methods

Abstract

Uncertainty is present in many forms in life cycle assessment (LCA). However, little attention has been paid to analyze the variability that methodological choices have on LCA outcomes. To address this variability, common practice is to conduct a sensitivity analysis, which is sometimes treated only at a qualitative level. Hence, the purpose of this paper was to evaluate the uncertainty and the sensitivity in the LCA of swine production due to two methodological choices: the allocation approach and the life cycle impact assessment (LCIA) method. We used a comparative case study of swine production to address uncertainty due to methodological choices. First, scenario variation through a sensitivity analysis of the approaches used to address the multi-functionality problem was conducted for the main processes of the system product, followed by an impact assessment using five LCIA methods at the midpoint level. The results from the sensitivity analysis were used to generate 10,000 independent simulations using the Monte Carlo method and then compared using comparison indicators in histogram graphics. Regardless of the differences between the absolute values of the LCA obtained due to the allocation approach and LCIA methods used, the overall ranking of scenarios did not change. The use of the substitution method to address the multi-functional processes in swine production showed the highest values for almost all of the impact categories, except for freshwater ecotoxicity; therefore, this method introduced the greater variations into our analysis. Regarding the variation of the LCIA method, for acidification, eutrophication, and freshwater ecotoxicity, the results were very sensitive. The uncertainty analysis with the Monte Carlo simulations showed a wide range of results and an almost equal probability of all the scenarios be the preferable option to decrease the impacts on acidification, eutrophication, and freshwater ecotoxicity. Considering the aggregate result variation across allocation approaches and LCIA methods, the uncertainty is too high to identify a statistically significant alternative. The uncertainty analysis showed that performing only a sensitivity analysis could mislead the decision-maker with respect to LCA results; our analysis with the Monte Carlo simulation indicates no significant difference between the alternatives compared. Although the uncertainty in the LCA outcomes could not be decreased due to the wide range of possible results, to some extent, the uncertainty analysis can lead to a less uncertain decision-making by demonstrating the uncertainties between the compared alternatives.