Cost effectiveness of carbon capture and storage based on probability estimation of social cost of carbon (Caesary et al., 2025)

This study assesses the cost effectiveness of CCS technology by comparing CO2 avoidance costs with SCC probability ranges derived from an automated generalized IAM-based machine learning approach. This methodology offers a significant advancement by providing a rapid evaluation of SCC probability distribution across various scenarios, thereby capturing uncertainties within the SCC and aiding the assessment of the economic benefits of CCS expansion. The findings indicate that average SCC values decrease by approximately 23.8 % by 2100 with additional CCS expansion.