A social impact quantification framework for the resource extraction industry
The objective of this study was to develop a social impact quantification framework for the resource extraction industry. The framework was developed to incorporate two approaches—scale-based and quantitative approaches. It aimed to be used for assessing upstream social impacts for products incorporating mined materials to produce a full social life cycle assessment (S-LCA).
The framework consists of measurable indicators and impact assessment methods. The quantitative approach simulates S-LCA by applying a two-step impact assessment: (1) calculation of impact scores at the social topic level, and (2) normalization and aggregation to the social theme and stakeholder level.
Results and discussion
The framework was demonstrated via a case study to compare one material issue—health and safety—from the material extraction phase of two major photovoltaic (PV) technologies in the USA: poly-Si and CdTe PV under stakeholder workers. A temporal analysis on a key mineral was performed. The results showed large variations in the social impact scores for selected topics on key raw materials associated with the two PVs. While the case study is limited in deriving practical implications due to preset assumptions, the framework itself can be extended and integrated with a whole product S-LCA to enhance the understanding of and promote social sustainability of the resource extraction industry.
A framework to measure both positive and negative social impacts was developed to follow the S-LCA methodology. The framework was illustrated by comparing two dominant PV technologies in the USA for the social theme of health and safety. Our case study demonstrated inspiring patterns for assessing upstream social impacts from the resource extraction industry, especially when incorporating a temporal analysis.
KeywordsHealth and safety Mineral extraction Photovoltaics Social impact Social life cycle assessment
This study is supported by the Sustainable Energy Program of the National Science Foundation (CHE1230246).
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