However, the performance of these sub-systems depends on each other, and thus individual optimal solutions cannot simultaneously co-exist. When optimizing a sub-system before extending to the whole CCU system, we can only expect to obtain a sub-optimal solution. In a recent review paper, Dieterich et al. also pointed out that the studies on the interaction between CCU sub-systems are still scarce. Inspiringly, Roh et al. optimized a whole CCU system, where MEA is taken as the only CO2 capture technology, and the 15 utilization pathways coexist to satisfy market demands. In Roh's work, the competitive interactions among different sub-systems are considered, but the complexity/non-linearity for individual sub-systems is neglected. To manipulate both high-level system variables and sub-system variables, a more robust method is superstructure optimization, 28 but this method leads to complex formulations and difficult-to-solve MINLP problems. An alternative solution is surrogate-based optimization, where sub-systems can be represented by cheap-to-evaluate surrogates. Surrogates are developed by regression to build a direct relationship between process inputs and outputs. Still, most prior works limit the surrogate-based optimization to a CCU subsystem (either capture or utilization ).