Evaluating operating trade-offs in CO2 hydrogenation to methanol: Conversion, energy efficiency, and techno-economic implications

The direct hydrogenation of carbon dioxide (CO2) to methanol presents a promising approach to mitigate atmospheric CO2 levels while producing a valuable chemical feedstock. However, the technical and economic feasibility of renewable methanol is still under evaluation, making it essential to identify optimal operational conditions and develop predictive models to enhance its competitiveness. This study investigates the optimization of the methanol production process via CO2 hydrogenation in a conventional catalytic reactor, combining simulation and statistical analysis to enhance both CO2 conversion and energy conversion efficiency (ηPtF). Aspen Plus simulations were conducted under varying pressures, temperatures, and hydrogen-to-CO2 feed ratios, and response surface methodology (RSM) was applied to identify optimal conditions. The results revealed that the maximum CO2 conversion (91.1 %) occurs at 83 bar, 247°C, and a hydrogen-to-CO2 ratio of 5:1, while the optimal ηPtF (58.4 %) is achieved at 50 bar, 210°C and a ratio of 3:1. A techno-economic assessment shows that the high-conversion scenario demands substantially higher hydrogen recycle and compression, increasing capital and operating costs. In contrast, the ηPtF-optimized condition offers lower energy demand and improved economic performance. CO2 conversion and ηPtF reached values comparable to or exceeding those in state-of-the-art studies, while highlighting the trade-off between maximizing conversion and optimizing energy efficiency. This underscores the need for tailored operating conditions. The generated surrogate models accurately predict the process outcomes, offering valuable insights for future studies, and demonstrating the potential for different economic and energy outcomes depending on the optimization strategy.