Madelynn Watson is a dedicated Ph.D. candidate in chemical engineering at the University of Notre Dame. Advised by Prof. Alexander Dowling, her research is part of an international interdisciplinary collaboration with colleagues at the University of São Paulo in Brazil. Her research focuses on utilizing optimization and analysis to guide technology and policy design for sustainable aviation fuel production in Brazil. She enjoys optimization and simulation-based research and will be seeking full-time employment starting in the spring of 2026.
Abstract:
In response to global sustainability efforts, the aviation industry is turning to sustainable aviation fuel (SAF) as a promising option for reducing greenhouse gas (GHG) emissions. Brazil’s experience in renewable energy development, historical government support of biofuels, and existing biomass infrastructure create a unique opportunity for SAF development from the sugarcane industry’s bioethanol.
Brazil has the third-largest civilian aviation system in the world, with aviation accounting for 18% of the country's transportation [1]. In 2024, Brazil consumed more than 4 million m³ of jet fuel, contributing approximately 12 million tonnes of CO₂ [2]. Bioethanol from sugarcane can be upgraded to SAF via the alcohol-to-jet (ATJ) technology [3]; however, integration of SAF production in the Brazilian sugarcane industry presents complex, interdependent, multiscale optimization problems: 1) High SAF production costs and volatile market conditions create a strong dependence on sustainable energy policy and individual government decisions, 2) Undeveloped SAF supply chains create open questions regarding where ATJ investments should be located within the existing infrastructure in Brazil, and 3) Varying perspectives between supply chain managers and individual mill owners present conflicting objectives (minimize cost vs. maximize profits). My work addresses these three critical challenges by developing a multiscale optimization framework to guide SAF capacity development at the producer and supply chain levels, considering the application of SAF development in Brazil.
In previous work, we developed a new optimization model to inform risk-conscious investment decisions on integrated SAF production in sugarcane mills using historical time-series commodity price data to de-risk decisions [4]. We find that currently available ATJ technologies require SAF premiums between 0.4 $ L−1 and 2 $ L−1. Similarly, with emerging ATJ technologies, premiums between 0.1 $ L−1 and 1.25 $ L−1 are required. Furthermore, we use sensitivity analysis to quantify the impact of ATJ conversion, operating costs, and incentives on the fraction of weeks when SAF production is favorable, guiding ATJ technology and policy development in Brazil.
In this work, we strategically design a supply chain network to optimize SAF capacity distribution in Brazil, aiming to meet up to 50% of the country’s jet fuel demand with SAF derived from sugarcane. Specifically, we proposed a mixed-integer linear program (MILP) to optimize the location of SAF investments and transportation links that connect sites across the supply chain network, considering 335 sugarcane mills, nine refineries, and 29 international airports. We show that varying objectives between supply chain managers and individual mill owners (minimizing system cost vs. maximizing mill profits) significantly impact the optimal supply chain design and total supply chain product flows. Furthermore, we quantify the additional cost required of the supply chain to meet a given SAF demand and recommend incentives for each objective considered.
References: