Rate-based modeling, multi-objective optimization and economic–CO2 emission trade-off analysis of an industrial-scale reactive distillation column for high purity methyl acetate production

Methyl acetate is a widely used commercial compound with applications in cosmetics, pharmaceuticals and paint industries. The demand for the production of this chemical with high purity is increasing. In this study, a non-equilibrium stages model was applied to simulate a reactive distillation column with a capacity of about 30,000 ton/year for the production of high purity methyl acetate (>99.5 wt%). Sensitivity analysis was used to investigate the impact of different variables including total number of column trays, feed tray location, the reactive and separation zones, tray spacing, free area ratio, weir height and downcomer width on Total Annual Cost (TAC) and CO2 emission rate. The results showed that the two objective functions of TAC and CO2 emission rate may conflict with each other by changing some design and operational parameters. Therefore, Non-Dominated Sorting Genetic Algorithm (NSGA-II) as a multi-objective optimization (MOO) method was used for dealing with conflicting objectives. After performing the optimization calculations, the Pareto front (PF) was obtained, followed Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method to select the best solution from the optimal PF. The results showed that although the TAC in the optimized design increased by 39.01% compared to the base design, aiming to achieve high-purity methyl acetate up to 99.5% compared to the 98% in base design, but the CO2 emission rate in the optimized configuration decreased by 29.85%. These results position the contribution of this study at the process-system level, the quantitative identification and mechanistic interpretation of the TAC–CO2 trade-off in an industrial-scale rate-based RD column for high-purity methyl acetate production.