Integrated multi-sectoral approach for planning of carbon capture and storage projects

Abstract

Carbon capture and storage (CCS) will play an important role in achieving carbon neutrality. In the deployment of CCS, it is important to identify an optimal network to allocate CO₂ between CO₂ sources and sinks. However, research on source-sink matching has been limited mostly to mathematical programming approaches with inherently limited interpretability to plan CCS involving different emission sectors and different storage reservoirs. Alternative techniques that may offer some interpretability advantages have not been explored as thoroughly. To address this research gap, this study introduces an integrated framework that synergistically combines Carbon Storage Composite Curves (CSCC) with Orthogonal Experimental Design (OED). This CSCC-OED framework is designed for the interpretable, multi-sectoral optimization of CCS infrastructure planning. It could coordinate the dynamic matching of CO₂ source-sink over a multi-decade planning horizon, while addressing constraints of storage capacity, operational timelines, and reservoir availability. The CSCC framework quantifies three critical metrics: additional storage requirement, total storage capacity, and excess capacity. Finally, global sensitivity analysis is performed to investigate the effect of parameters on the CCS deployment based on the deployment factors identified by OED method. Results of the case study indicate that the start time of CO₂ reservoir is the most statistically significant factor. 10 Gt of CO₂ could be stored via three reservoirs commencing operation in 2025, which contributes to 81.63% of the sectoral emission reduction target. Furthermore, scenarios involving policy-, technology-, and economy-driven CCS pathways are analyzed. This work establishes a systematic decision-support tool for CCS infrastructure planning, emphasizing the criticality of coordinated multi-sectoral strategies and early reservoir deployment to meet carbon neutrality goals.