Carbon Capture, Utilisation and Storage (CCUS) as a Tool for Climate Change Mitigation: Challenges and Opportunities with Sustainable Fuzzy Model

Abstract

Anthropogenic climate change, primarily driven by rising atmospheric carbon dioxide (CO₂) concentrations, poses a critical global challenge in the twenty-first century. Although renewable energy expansion and energy efficiency measures have progressed substantially, fossil fuels continue to dominate global energy and industrial systems. Emissions from hard-to-abate sectors such as cement, steel, chemicals, and oil refining remain significant due to both combustion processes and intrinsic industrial reactions. In this context, Carbon Capture, Utilisation and Storage (CCUS) has gained prominence as a strategic technological pathway for achieving deep decarbonisation while supporting a gradual transition to a low-carbon economy. CCUS comprises a range of technologies that capture CO₂ from industrial sources or directly from the atmosphere, transport it via pipelines or other means, and either utilise it in value-added applications or store it securely in geological formations. This study presents a comprehensive and critical assessment of CCUS, examining its technological foundations, mitigation potential, economic feasibility, environmental implications, and governance mechanisms. It identifies key barriers to large-scale deployment, including high capital and operational costs, energy penalties, infrastructure limitations, long-term storage concerns, and issues related to social acceptance. At the same time, the paper highlights emerging opportunities driven by innovation, supportive policy frameworks, industrial decarbonisation imperatives, and global net-zero commitments. The study concludes that while CCUS cannot address climate change independently, it is an essential component of an integrated mitigation strategy. Furthermore, a sustainable fuzzy logic model is proposed to evaluate CCUS across environmental, economic, technological, social, and policy dimensions, facilitating informed decision-making under uncertainty.