Social Life Cycle Assessments: A Review on Past Development, Advances and Methodological Challenges

Sustainability

Ulrike Grote¹  Hans-Josef Endres²  Louisa Pollok²  Sebastian Spierling² 

[1] Institute for Environmental Economics and World Trade, Leibniz Universität Hannover, Königsworther Platz 1, 30167 Hannover, Germany;Institute of Plastics and Circular Economy, Leibniz Universität Hannover, An der Universität 2, 30823 Garbsen, Germany;

关键词: Social Life Cycle Assessment;    literature review;    social sustainability;    Sustainable Development Goals;    automotive industry;   

DOI  :  10.3390/su131810286

来源: DOAJ

【 摘 要 】

Society’s interest in social impacts of products, services and organizational behaviors is rapidly growing. While life cycle assessments to evaluate environmental stressors have generally been well established in many industries, approaches to evaluate social impacts such as Social Life Cycle Assessment (S-LCA) lack methodological consistency and standardization. The aim of this paper is to identify past developments and methodological barriers of S-LCA and to summarize how the automotive industry contributed to the advancement or application of this method. Therefore, a qualitative content analysis of 111 studies published between 2015 and 2020 is used to gather information on past scientific and political milestones, methodological barriers impeding S-LCA and the participation of the automotive sector. The review shows that a broad range of sectors such as the automotive industry contributed to the testing and advancement of S-LCA in the past but that S-LCA remains a young and immature method. Large-scale application is impeded by major barriers such as the variety of impact categories and sub-categories, the lacking integration of the Sustainable Development Goals (SDGs), issues of linking LCA structures to social phenomena or the difficult tracking of social impact pathways. Further research on standardization possibilities, the connection to political social targets and the testing of methods is necessary to overcome current barriers and increase the applicability and interpretability results.

【 授权许可】

Unknown