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Article Dans Une Revue Journal of Cleaner Production Année : 2022

On the possibilities of multilevel analysis to cover data gaps in consequential S-LCA: Case of multistory residential building

Résumé

Building is affiliated with much of the social impact and benefits. However, for long term assessments that can capture indirect consequences, the current common attributional approach is lacking. The challenge become more obvious with large data amounts required to perform social life cycle assessment (S-LCA), and often less representative non site-specific data must be used to fill data gaps. To address above-mentioned problem, this paper presents a multilevel analysis in consequential S-LCA to further demonstrate the added value of such evaluation on addressing the existing data gaps by integrating the four level of analysis: unit process, company, sector and country. The methodology used is multilevel assessment on these four levels performed to five stakeholder of worker, local community, user, society and supplier. The case study used to demonstrate this is a multistorey building that has long supply chain from local, regional and abroad. The results show that using multilevel could help to fill the data gaps. For example, with multilevel analysis, material company or activities could fill at least 14 of the 24 social indicators through company's assessment. If it was only performed on one level, the indicators that can be assessed is lesser. Even though more data is not necessarily better but it can broaden the view to understand the potential hotspot of social impact/benefit and the sphere of its influence to the stakeholders. From consequential point of view, it also shows that for a long term, a decision of constructing more hybrid multistory building will be closely related to some social impacts and benefits in different level, different product life cycle and in different geographical area that cannot be captured with single level of analysis.
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Dates et versions

hal-03942408 , version 1 (17-01-2023)

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Citer

Rizal Taufiq Fauzi, Patrick Lavoie, Audrey Tanguy, Ben Amor. On the possibilities of multilevel analysis to cover data gaps in consequential S-LCA: Case of multistory residential building. Journal of Cleaner Production, 2022, 355, pp.131666. ⟨10.1016/j.jclepro.2022.131666⟩. ⟨hal-03942408⟩
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