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Reducing the climate impact of residual waste treatment: A German case study on carbon management strategies.

作者信息

Schmidt Sarah, Laner David

机构信息

Center for Resource Management and Solid Waste Engineering, Faculty for Civil and Environmental Engineering, University of Kassel, Kassel, Germany.

Center for Resource Management and Solid Waste Engineering, Faculty for Civil and Environmental Engineering, University of Kassel, Kassel, Germany.

出版信息

Waste Manag. 2025 May 1;198:137-150. doi: 10.1016/j.wasman.2025.02.048. Epub 2025 Mar 5.

Abstract

Climate neutrality goals require adapting the management of fossil carbon in waste management. This study evaluates the effectiveness of two key carbon management strategies addressing greenhouse gas (GHG) emissions from residual waste treatment, namely: pre-sorting residual waste in a material recovery facility to remove recyclable, carbon-rich materials (S_MRF) versus post-treatment of municipal solid waste incineration (MSWI) flue gas through carbon capture and storage (S_MSWI_CCS). Using residual waste management in Kassel, Germany, as a case study, GHG emissions are assessed for current and prospective scenarios, accounting for changes in waste inputs, material and energy systems, substitution choices, and uncertainties in treatment technology data. It is shown that MSWI in Kassel emits 857 kg of CO per t of wet residual waste, with 31 % fossil CO. Carbon management strategies can reduce direct fossil CO emissions by 27 % (S_MRF) or 90 % (S_MSWI_CCS) and increase the net life cycle GHG savings of residual waste management by a factor of 1.6 (S_MRF) or 2.6 (S_MSWI_CCS), respectively. S_MSWI_CCS offers the highest potential to decrease the GHG footprint of residual waste management and is least sensitive to variations in waste composition, energy and material systems, and substitution choices. Discernibly higher net GHG savings of S_MRF compared to S_MSWI_CCS can only be observed if residual waste is rich in recyclables (low separate collection). Overall, this study highlights the utility of refined scenario, uncertainty and discernability analysis in accounting for local conditions and different settings as well as potential future changes to promote environmental decision support on waste management.

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