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Advancing Social Life Cycle Assessment: A Novel Approach to Uncertainty Analysis
Beatriz Cassuriaga1, Andreia Santos1, Ana Carvalho1
1CEGIST - Centro de Estudos de Gestão do Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, Lisboa 1049-101, Portugal.
Abstract:
Social life cycle assessment is gaining importance, being recognized as a well-established methodology to evaluate potential social risks that might occur in value chains. Several studies have been conducted in applying traditional social databases (e.g., Social Hotspot Database) to assess social risks, but these studies generally do not consider the uncertainty associated with the characterization factors used in the models. This type of uncertainty is intrinsic to social risk modeling, as the underlying indicators and expert-based assessments are inherently variable. Therefore, this paper aims to address this literature gap by proposing an uncertainty analysis methodology that explicitly accounts for the uncertainty associated with the characterization factors. It represents one of the first studies to model such uncertainty directly within the context of the Social Life Cycle Assessment. The methodology will be applied to assess the social performance of two components, a car dashboard and a ship counter bar, manufactured using conventional materials (ABS and reinforced gypsum) and an innovative cellulose-based material. The results show that the methodology is easily employed and applicable to different case studies. The cellulose-based material exhibited significantly lower potential social impacts in the ship counter bar and consistently higher impacts in the car dashboard when compared to conventional materials, and these findings remained consistent even when accounting for uncertainty in the characterization factors. The approach also quantifies the confidence associated with each comparison, reinforcing the robustness of the conclusions. By integrating uncertainty modeling into the Social Life Cycle Assessment, the study enhances the transparency and interpretability of social performance evaluations across different value chains.
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