Design of a supply chain network for chemicals from biomass using green electrochemistry

Increasing concern about the environmental impact of industrial activities has prompted a shift to renewable energy sources and the development of environmentally conscious supply chains. In this regard, electrochemistry has shown promise for converting biomass into specialty chemicals in distributed facilities that exploit renewable energy resources. To examine the impact of electrochemistry technology on optimal supply chain configuration, we formulate a mixed-integer linear programming model to optimize the locations and capacities of distributed facilities for converting biomass to chemicals. The economic objective of the supply chain design model is to minimize the total annual cost of producing chemicals from biomass-derived glucose and delivering them to market. To analyze the trade-off between environmental and economic considerations, we also consider an environmental objective of minimizing greenhouse gas (GHG) emissions. The results of a US case study indicate that, while cost is minimized by constructing one large facility, GHG emissions are lowered by a distributed configuration. Varying the setting of a process design parameter expands the Pareto frontier along which decision-makers can choose a configuration according to their preferences between economic and environmental criteria.