Abstract
CO2-to-methanol process is an attractive option to simultaneously reducing the anthropogenic CO2 while producing value-added chemicals. In this work, two distinct CO2-to-methanol process routes specifically, single step and dual step are evaluated based on their economic and environmental performance. First, a multiobjective optimization (MOO) framework is formulated to develop the optimal process configurations. Three conflicting objectives including methanol production rate, total annual cost (TAC) and carbon intensity of methanol are considered. For this MOO, the elitist non-dominated sorting genetic algorithm (NSGA-II) is employed to get the Pareto front. From the Pareto front, a balanced compromise solution is identified by the technique for order of preference by similarity to ideal solution (TOPSIS) with entropy information as weighting criteria. Then, the comparative performance analysis is conducted across the Pareto front. At the TOPSIS-selected configuration, the single step process offers economic advantages (1.97% lower levelised cost of methanol (LCoM)), but performs poorly on environmental perspective (3.03% higher carbon intensity of methanol). In contrast, at the cost-optimal point the dual step process is marginally favourable in both aspects (0.55% less LCoM and 1.26% reduction in carbon intensity of methanol). Overall, both processes exhibit comparable economic and environmental outcomes, with the dual step showing better environmental performance and reduced variability across the Pareto space.