ABSTRACT
Carbon Capture and Storage (CCS) is an essential pillar towards achieving net-zero emissions, especially to decarbonise the more than 40% of the global CO₂ emissions associated with industrial and power sectors. Research around CCS technologies is extensive and thorough, but in many cases, they do not bring together a comprehensive quantitative analysis of the full chain of CCS. This review provides a comprehensive and critical synthesis of the state of play regarding technological performance, quantifying capture efficiency, for example, 85-90% for amine scrubbing and 70-90% for direct air capture (DAC) and the costs associated with those technologies ($50-150/tCO2 for point-source capture, over $600/tCO2 for DAC). We also provide insight into geological storage capacity, limits of injectivity, and transport logistics. Importantly, and in addition to a technical assessment, this review assesses future implications of emerging artificial intelligence (AI) and machine learning (ML) capabilities on CCS design, monitoring, and policy. Lastly, we identify critical barriers, including excessive energy penalties (5-10 GJ/tCO₂) and regulatory gaps, and provide a potential research and policy pathway towards improving the viable deployment of CCS as part of climate mitigation goals.
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