Multi-objective optimization for sustainable renewable jet fuel production: A case study of corn stover based supply chain system in Midwestern U.S.

Sustainable development of biomass-based renewable jet fuel (RJF) production mitigates the environmental stress and improves rural economics. We develop a mixed-integer linear programming model to incorporate spatial, agricultural, techno-economical, and environmental data for multi-objective optimization of RJF supply chain systems. The model is applied to the Midwestern U.S. to evaluate the sustainability performance of three pathways including alcohol-to-jet (ATJ), Fischer-Tropsch (FT) and Hydrothermal liquefaction (HTL). The results show that HTL is the most cost-effective with a cost of $4.64/gal while FT is most environmental-friendly with the greenhouse gas (GHG) emissions of 0.10 kg CO₂/gal. The cost-optimal analysis suggests a centralized supply chain configuration with large facilities, while the environmental optimization analysis prefers a distributed system with small biorefinery facilities. For FT approach, cost optimization analysis suggests developing a supply chain with one large biorefinery, whereas environmental optimization prefers a system with 11 small biorefineries. Considering the economic and environmental factors simultaneously, the Pareto curve demonstrates that total production costs of three pathways all increase with the more stringent constraints of GHG emissions. This indicates that RJF production costs are sensitive to the regulation of GHG emissions. Considering the carbon price at $0.22 per kg of CO₂ reduction, FT yields the lowest cost of $2.83/gal among three pathways, but it is still 47% higher than that of fossil jet fuel. FT is not cost competitive with fossil jet fuel until the carbon price increases to $0.30 per kg of CO₂ reduction. FT is suggested a promising sustainable RJF production pathway due to its relatively low capital investment and production costs, centralized supply chain configuration, and low GHG emissions.