Bioethanol, a promising biofuel gasoline additive, was recently produced by a new technology using acetic acid derived from organic waste. This study develops a multiobjective mathematical model with two competing minimization objectives: economy and environmental impact. The formulation is based on a mixed integer linear programming approach. The configuration of the organic-waste (OW)-based bioethanol supply chain network is optimized in terms of the number and locations of bioethanol refineries. The flows of acetic acid and bioethanol between the geographical nodes must meet the bioethanol regional demand. The model is validated in three real-scenario case studies with different OW utilization rates (30%, 50%, and 70%) in South Korea in the near future (2030). The multiobjective problem is solved using the ε-constraint method and the selected Pareto solutions balance the trade-off between the economic and environmental objectives. At the "best-choice" solution points, increasing the OW utilization rate from 30% to 70% decreased the total annual cost from 904.2 to 707.3 million $/yr and the total greenhouse emissions from 1087.2 to -15.7 CO equiv./yr.
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