Thermodynamic modeling and optimization of an exhaust-heat-driven MEA onboard carbon capture system for marine diesel engines

Maritime transportation contributes over 3% of global CO2 emissions and remains heavily dependent on fossil fuels, posing challenges for near-term decarbonization. Onboard carbon capture and storage (OCCS) systems offer a potential mitigation option for existing fleets. However, their application is constrained by the high regeneration energy demand of monoethanolamine (MEA)-based systems, and many existing optimization studies do not explicitly evaluate net carbon-reduction effectiveness. In this study, a thermodynamic model of an MEA-based post-combustion OCCS is developed in Aspen HYSYS using realistic exhaust gas data from a marine diesel engine. An exhaust-heat-integrated regeneration scheme is implemented, in which engine exhaust sensible heat serves as the primary heat source for solvent desorption, significantly reducing the reliance on additional fuel or external heating input. The model is validated against two published marine MEA capture studies, with deviations below 7% for key performance indicators. To establish an efficient system configuration, the theoretical stage numbers of the absorber and stripper are optimized using the non-dominated sorting genetic algorithm III (NSGA-III). Based on the optimized column configuration, a genetic algorithm (GA) is applied to optimize key operating variables with the metric of carbon capture efficiency degree (MCCED) as the objective function. Under the optimized conditions, the MCCED reaches 65.8%, representing an absolute improvement of 42.8% over the validated baseline value of 23.0%. The results indicate that coordinated configuration and operational optimization can significantly enhance the net carbon-reduction performance of exhaust-heat-driven OCCS under realistic marine operating constraints.