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• W3200778834 abstract "Cost benefit analysis (CBA) and social impact assessment are well established methodologies to systematically estimate the viability of investments on technologies as well as the benefits for the society. However, there is a limited application of these assessment methods in the wastewater sector especially for resource recovery to deliver circularity objectives within urban water cycle management. In this regard, the Horizon 2020 SMART-Plant Innovation Action aimed to evaluate holistic impacts of wastewater-based resource recovery by applying and adapting cost benefit and social analysis on innovative technologies (SMARTechs). The SMARTechs were implemented and validated in real wastewater treatment plants (WWTPs) across Europe and Mediterranean basin where potential impacts in terms of carbon, material and energy efficiency, recovery and safe reuse were defined. Sixteen bottom-up SMARTech scenarios were analysed for the estimation of technical, economic and social impacts using CBA, social life cycle assessment (S-LCA) and social readiness level (SRL) methods. Overall, the SMARTechs created benefits both from an environmental and social point of view, with a maximum relative total economic value up to +23% compared to baseline scenario (without any SMARTech implementation). In terms of social benefits, the S-LCA highlighted a global positive impact of all the SMARTechs in terms of technical characteristics and social acceptance. Specifically, SMARTech 1 (cellulose recovery) was the most socially accepted solution thanks to its high performance and simplicity. Finally, based on the SRL assessment, most of the SMARTechs were positioned within the SRL range of 6–7, which implies a good societal acceptance and adaptation potential." @default.
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• W3200778834 date "2021-11-01" @default.
• W3200778834 modified "2023-10-16" @default.
• W3200778834 title "Assessing socio-economic value of innovative materials recovery solutions validated in existing wastewater treatment plants" @default.
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• W3200778834 doi "https://doi.org/10.1016/j.jclepro.2021.129048" @default.
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