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Synergies and challenges of bottom-up and top-down approaches for assessing social impacts in mining operation

  • SOCIETAL LCA
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Abstract

Purpose

The mining industry plays a critical role in the global economy by providing raw materials and metals for various sectors, but it is also associated with environmental and social impacts. This paper presents a comparison of the findings from social life cycle assessment (S-LCA) with those obtained from a stakeholders’ risk perception analysis. The goal is to provide a multifaceted view on the challenges faced by the mining industry in achieving sustainable practices.

Methods

This research reports the results of S-LCA and stakeholders’ risk perception analysis used to evaluate the social dimension of sustainability in two different European Horizon 2020 projects: (i) recovery of secondary metals and minerals from mining residues through bioleaching and chemical precipitation (project NEMO with a demonstration site in Finland), and (ii) recycling of wastewater and valorization of tailings from mining activities to create geopolymers through chemical activation (project ITERAMS with a demonstration site in Portugal).

Results

The S-LCA conducted in NEMO reveals that fair salary is the social category presenting the highest risk (22% of the total). This risk is unequally shared between foreground activities (4%) and background activities (18%), and it occurs mostly in Finland. The S-LCA in ITERAMS shows that the low percentage of employees organized in trade unions accounts for the highest social risk (14%), occurring mostly with the background activities (8.5% out of the 14%). The risk perception analysis conducted among involved stakeholders for both projects highlighted that the analysis performed using only S-LCA databases overestimated some social issues (e.g., access to biomass, trade unionism) that were not relevant for local stakeholders while underestimating, or even ignoring, other social issues that are considered important by the same stakeholders (e.g., health and safety, housing prices).

Conclusions

The two case studies show the critical need to integrate locally gathered data from stakeholders directly involved in the projects with the broader insights offered by sector-level S-LCA. Local analysis can capture site-specific dynamics and social risk perceptions, while S-LCA can extend the analysis to the entire supply chain. Both analyses highlighted that one of the main limitations of the current S-LCA framework is the omission of the positive environmental, social and economic effects resulting from the proposed projects. Ultimately, these case studies provided valuable insights for the stakeholders involved in both projects, facilitating information sharing concerning the primary social risks associated with the development and implementation of the technologies proposed by the projects. This empowers decision-makers with the information required to formulate strategies that can enhance the sustainability of the bioleaching and geopolymer technologies used to valorize mining residues.

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Data availability

All data generated or analyzed during this study are included in this published article and its supplementary information files.

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Acknowledgements

The authors would like to thank Thaís Veiga Barreiros, for the precious contribution to data collection and interviews conducted for the Neves Corvo case, and Cristina Vilabrille Paz for her contribution to research about mining acceptance drivers.

Funding

The ITERAMS Project has received funding from the European Union H2020 programme under grant agreement no. 730480. The NEMO project received funding from the European Union’s EU Framework Programme for Research and Innovation Horizon 2020 under grant agreement no. 776846.

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Correspondence to Andrea Di Maria.

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The authors declare no competing interests.

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Communicated by Sara Russo Garrido.

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Di Maria, A., Di Noi, C., Román Escobar, Y. et al. Synergies and challenges of bottom-up and top-down approaches for assessing social impacts in mining operation. Int J Life Cycle Assess (2024). https://doi.org/10.1007/s11367-024-02283-0

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  • DOI: https://doi.org/10.1007/s11367-024-02283-0

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