2025 Spring Meeting and 21st Global Congress on Process Safety

(138c) Supply Chain Optimization and Policy Design for Bio-Jet Capacity Development in Brazil

Authors

Madelynn Watson - Presenter, West Virginia University
Aline Veronese da Silva, University of Sao Paulo
Eduardo Almeida, University of São Paulo
Alexander Dowling, University of Notre Dame
Aviation accounts for ~3% of global CO2 emissions [1]. Furthermore, it cannot rely on common decarbonization technologies (e.g., electrification and hydrogen) in the short- to medium-term (2030-2050) as they require two or three decades of development and capital-intensive investments [2]. Bio-jet fuel has gained increasing interest from the aviation industry to reduce CO2 emissions due to its economic competitiveness and drop-in compat­ibility with existing aircraft and fuel systems [3]; however, several challenges currently hinder commercial-scale bio-jet fuel development. Notable challenges include underdeveloped biomass-to-bioenergy supply chains, high bio-jet fuel production costs, and a lack of monetary incentives to support capacity development [3-5].

Brazil is a global leader in renewable energy and sustainability efforts. Brazil was one of the first countries to use biofuels for transportation and has had multiple biofuel incentive programs the Brazilian government has supported since the 1970s [6]. They are currently the second-largest producer of bioethanol globally and the largest producer of bioethanol from sugarcane [6]. Bioethanol from sugarcane can be upgraded to bio-jet fuel in Brazil via the ASTM-certified pathway alcohol-to-jet (ATJ) [3]. Brazil’s experience in renewable energy development, historical government support of biofuels, and existing biomass infrastructure create a unique opportunity for commercial bio-jet fuel development.

In this work, we design a bio-jet fuel supply chain to optimize bio-jet fuel capacity distribution in Brazil to meet 50% of the country’s international airport jet fuel demand. Specifically, we use mixed-integer linear programming (MILP) to develop a superstructure model to optimize the location of sugarcane mills that invest in bio-jet fuel capacity, assignment of airports to integrated biorefineries, and transportation links that connect sites across the supply chain network. The optimal supply chain network minimizes the cost of bio-jet fuel based on existing biomass infrastructure (sugarcane mill and airport locations), bio-jet fuel policy incentives, and market prices of sugar, ethanol, and jet fuel. We consider over 300 sugarcane mills, 35 major international airports, and various incentive structures to find the optimal supply chain configuration to promote bio-jet fuel capacity development. Furthermore, we discuss how optimization and analysis can guide biofuel infrastructure and policy development.







References

  1. IEA Aviation. 2024; https://www.iea.org/energy-system/transport/aviation.
  2. Dahal, K.; Brynolf, S.; Xisto, C.; Hansson, J.; Grahn, M.; Gr¨onstedt, T.; Lehtveer, M. Techno-economic review of alternative fuels and propulsion systems for the aviation sector. 2021.
  3. Watson, M.; Machado, P.; da Silva, A.; Rivera, Y.; Ribeiro, C.; Nascimento, C.; Dowling, A. Sustainable aviation fuel technologies, costs, emissions, policies, and markets: A critical review. Journal of Cleaner Production 2024, 141472.
  4. Wei, H.; Liu, W.; Chen, X.; Yang, Q.; Li, J.; Chen, H. Renewable bio-jet fuel production for aviation: A review. 2019.
  5. Shahriar, M. F.; Khanal, A. The current techno-economic, environmental, policy status and perspectives of sustainable aviation fuel (SAF). Fuel 2022, 325.
  6. de Oliveira, S. M.; de Oliveira Ribeiro, C.; Cicogna, M. P. V. Uncertainty effects on production mix and on hedging decisions: The case of Brazilian ethanol and sugar. Energy Economics 2018, 70, 516–524.