Techno-economic and environmental optimization of structured-packing absorbers for amine-based post-combustion CO2 capture

Post combustion carbon capture and storage (CCS) using amine solvents is a mature and retrofittable technology where CO2 absorber design remains a critical determinant of cost, energy demand, and environmental footprint. Conventional studies typically size absorbers within proprietary simulators or apply simplified surrogates that limit transparency while excluding case specific design and material related impacts. This work develops a physics based, multi-objective optimization framework for structured-packing amine-based CCS absorbers in natural gas combined cycle (NGCC) plants that balances equilibrium driven mass transfer, hydraulics, techno-economic assessment, and cradle-to-gate embodied global warming potential (GWP) considerations. Several commercially available structured packings are evaluated and vendor relevant absorber geometries, which are height, diameter, packing type, and volume are directly linked to costs, reboiler duty, capture efficiency, and embodied emissions. Baseline optimization for a 250 MWe NGCC plant identifies knee-point optimum absorber designs achieving 95–97% capture at 40–52 million USD, 3.2–4.6 MJ/kmolsolvent reboiler duty, and 1300–1900 t CO2e embodied GWP. Sensitivity analyses show that plant scaling fundamentally alters packing selection, preferring high surface area packings (Montz BSH-400) for 100 MWe NGCC case. Meanwhile, at 750 MWe, hydraulically open packings (Montz B1–250) dominate optimum solutions to limit flooding and column parallelization. Steel emissions intensity further alters optimization outcomes with recycled steel reducing embodied emissions by up to 70%. Overall, the study establishes CCS absorber design as a scale-sensitive, multi-objective problem, and shows that design choices have significant implications for material use, embodied emissions, and overall system sustainability. The findings highlight the need to integrate environmental performance alongside cost and capture efficiency in CCS decision-making for large-scale and sustainable deployment.