A Review of Integrated Carbon Capture and Hydrogen Storage: AI-Driven Optimization for Efficiency and Scalability

Yasin Khalili, Sara Yasemi, Mahdi Abdi, Masoud Ghasemi Ertian, Maryam Mohammadi and Mohammadreza Bagheri ()
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Yasin Khalili: Faculty of Petroleum Engineering, Amirkabir University of Technology, Tehran 15916-34311, Iran
Sara Yasemi: Faculty of Petroleum and Natural Gas Engineering, Sahand University of Technology, Sahand New Town, Tabriz 51335/1996, Iran
Mahdi Abdi: Faculty of Petroleum and Petrochemical Engineering, Hakim Sabzevari University, Sabzevar 9617976487, Iran
Masoud Ghasemi Ertian: Faculty of Petroleum and Petrochemical Engineering, Hakim Sabzevari University, Sabzevar 9617976487, Iran
Maryam Mohammadi: Faculty of Petroleum and Petrochemical Engineering, Hakim Sabzevari University, Sabzevar 9617976487, Iran
Mohammadreza Bagheri: Faculty of Petroleum and Petrochemical Engineering, Hakim Sabzevari University, Sabzevar 9617976487, Iran

Sustainability, 2025, vol. 17, issue 13, 1-40

Abstract: Achieving global net-zero emissions by 2050 demands integrated and scalable strategies that unite decarbonization technologies across sectors. This review provides a forward-looking synthesis of carbon capture and storage and hydrogen systems, emphasizing their integration through artificial intelligence to enhance operational efficiency, reduce system costs, and accelerate large-scale deployment. While CCS can mitigate up to 95% of industrial CO 2 emissions, and hydrogen, particularly blue hydrogen, offers a versatile low-carbon energy carrier, their co-deployment unlocks synergies in infrastructure, storage, and operational management. Artificial intelligence plays a transformative role in this integration, enabling predictive modeling, anomaly detection, and intelligent control across capture, transport, and storage networks. Drawing on global case studies (e.g., Petra Nova, Northern Lights, Fukushima FH2R, and H21 North of England) and emerging policy frameworks, this study identifies key benefits, technical and regulatory challenges, and innovation trends. A novel contribution of this review lies in its AI-focused roadmap for integrating CCS and hydrogen systems, supported by a detailed analysis of implementation barriers and policy-enabling strategies. By reimagining energy systems through digital optimization and infrastructure synergy, this review outlines a resilient blueprint for the transition to a sustainable, low-carbon future.

Keywords: carbon capture and storage; hydrogen storage; artificial intelligence; system optimization; energy efficiency; scalability; net-zero transition (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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