Abstract

Carbon capture utilization and storage technology has been identified as a key solution for limiting the global temperature increase to 2 °C from preindustrial levels. In this study, we develop a source–sink matching mixed-integer linear programming model to obtain an optimal cost for the Carbon capture utilization and storage supply chain and evaluate the environmental benefits using life cycle assessment. Guangdong Province, China, with annual CO2 emissions of 585 Mt, is chosen as the case study for this paper. The results show that the deployment of the carbon capture utilization and storage supply chain follows a pattern of spreading from coastal to inland regions as the CO2 net reduction rate increases. Moreover, the unit cost of CO2 reduction increases with the CO2 reduction rate, specifically, from 237.81 Yuan per ton to 253.51 Yuan per ton as the CO2 reduction rate increases from 10% to 60%. The CO2-derived methanol is not economically viable, while having low implied carbon emissions, it has approximately 2.5 times the unit cost of traditional methanol. We recommend promoting carbon trading due to its effectiveness in reducing the unit abatement cost. Additionally, the carbon price level of 220 Yuan/t can achieve a profitable supply chain at various reduction rates. However, carbon labeling subsidies have little effect on reducing methanol production costs. The 95% confidence intervals for unit abatement costs obtained from Monte Carlo simulations can provide robust support for policymakers.

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