Recent Advances in Integrated Carbon Dioxide Capture: Exploring Carbon Capture Methods and AI Integration

Achieving the Sustainable Development Goals depends on decarbonizing the industrial sector, as it still contributes the most to global greenhouse gas emissions and energy consumption. Reducing emissions from fossil fuel-based energy systems critically depends on carbon capture, especially post-combustion carbon capture (PCC). Absorption-based carbon capture (ACC) is the most developed and extensively applied PCC system. However, ACC systems are quite energy-intensive and require major heating and cooling utilities, which increases the running costs and makes large-scale adoption difficult. This study investigates the current developments in carbon capture technology and emphasizes the integration of artificial intelligence (AI) to address optimization challenges. In particular, it suggests an artificial intelligence-based approach for improving ACC system design, operation, and utility consumption forecasting. AI-driven solutions can promote scalable and reasonably priced carbon capture technologies by allowing accurate and fast assessments of technical and financial viability. This study emphasizes how artificial intelligence might hasten the shift toward more environmentally friendly industrial methods and significantly support global climate action targets (SDG 13).