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A novel uncertainty assessment protocol for integrated ecosystem services-life cycle assessments: A comparative case of nature-based solutions

Alshehri, Khaled, Chen, I-Chun, Rugani, Benedetto, Sapsford, Devin ORCID:, Harbottle, Michael ORCID: and Cleall, Peter ORCID: 2024. A novel uncertainty assessment protocol for integrated ecosystem services-life cycle assessments: A comparative case of nature-based solutions. Sustainable Production and Consumption 47 , pp. 499-515. 10.1016/j.spc.2024.04.026

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Integrating ecosystem services and life cycle assessment is gaining increasing attention for the analysis of environmental costs and benefits associated with human activities covering multiple geographical scales and life cycle stages. Such integration is particularly relevant for evaluating the sustainability of nature-based solutions. However, merging these methods introduces additional uncertainties. This paper introduces a novel protocol to assess uncertainties in combined ecosystem services-life cycle assessment, focusing on ecosystem services accounting, life cycle inventory of foreground systems, and life cycle impact assessment characterisation factors. Applied to a nature-based solution case study compared to no-action and energy-intensive scenarios, the uncertainties were analysed using multi-method global sensitivity analysis. The robustness of the analysis results was assessed through convergence plots and statistical tests. Findings reveal significant uncertainties, especially in life cycle impact assessment characterisation factors, with the extent varying by impact category. Uncertainties in foreground life cycle inventory, particularly in land use of nature-based solutions scenario, are also notable. Compared to these, uncertainties associated with indicators of impact on ecosystem services (uncertainty arising from input variability in ecosystem services accounting) are relatively lower. This study underscores the critical role of uncertainty assessment in enhancing the reliability of integrated assessments for nature-based solutions, providing a framework to identify and quantify key uncertainties, thereby supporting more informed decision-making.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Engineering
Publisher: Elsevier
ISSN: 2352-5509
Date of First Compliant Deposit: 10 May 2024
Date of Acceptance: 22 April 2024
Last Modified: 10 May 2024 14:15

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