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Title Multi-period optimization for CO2 sequestration potential of enhanced weathering using non-hazardous industrial wastes
ID_Doc 22424
Authors Zhang, YM; Li, ZW; Aviso, KB; Tan, RR; Wang, F; Jia, XP
Title Multi-period optimization for CO2 sequestration potential of enhanced weathering using non-hazardous industrial wastes
Year 2023
Published
Abstract Negative emission technologies (NETs) can contribute to mitigating climate change. Enhanced weathering (EW) is a NET with considerable carbon sequestration potential. It is based on accelerated chemical reactions between alkaline minerals and water and carbon dioxide to generate bicarbonates in runoff that flows into the ocean to achieve long-term carbon sequestration. EW also presents a potential valorisation pathway for the use of in-dustrial residues. Therefore, we selected non-hazardous industrial wastes (NHIWs) as the alkaline mineral of EW. The processes for implementing EW (crushing, transporting, and spreading NHIWs) will produce additional CO2 emissions and require energy input, and these values may vary in the life cycle of the specific facilities. To address this gap, we developed a multi-period mixed integer nonlinear programming (MINLP) model to optimize NHIWs flows between sources and sinks over the planning horizon, while considering the annual CO2 seques-tration target for achieving regional carbon drawdown. Our results show that the unit net CO2 sequestration cost for removing 1% and 1.5% annual carbon emissions of Shandong province is $273 and $378 /t CO2, respectively. It is estimated that from 2020 to 2030, the maximum CO2 sequestration of NHIWs produced by Shandong province will be 305.78 Mt CO2. The developed model can also be applied to other regions and countries as guidance for EW deployment and support for waste utilization towards circular economy.
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ID Score Article
11006 Aviso, KB; Lee, JY; Ubando, AT; Tan, RR Fuzzy optimization model for enhanced weathering networks using industrial waste(2022)Clean Technologies And Environmental Policy, 24, 1
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