Multi-objective optimization of sustainable aviation fuel production pathways in the U.S. Corn Belt

Ari Akdemir, Ece; Kern, Jordan; Smith, Jack P.; Limb, Braden J.; Quinn, Jason C.; Field, John L.; Pack, Taylor

doi:10.1016/j.biombioe.2025.107590

Title: Multi-objective optimization of sustainable aviation fuel production pathways in the U.S. Corn Belt

Journal Article · 08 January 2025 · Biomass and Bioenergy

DOI: https://doi.org/10.1016/j.biombioe.2025.107590 · OSTI ID:2563569

^[1];

^[2];

^[2]; Quinn, Jason C. ^[2];

^[3]; Pack, Taylor ^[1]

North Carolina State University, Raleigh, NC (United States)
Colorado State University, Fort Collins, CO (United States)
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

As a potential source of low-carbon transportation energy, biofuels offer certain advantages over vehicle electrification (e.g., lower societal vulnerability to grid failures, and improved range of sustainable aviation), but also several challenges, including cost, carbon intensity, and land usage. There are also well-founded concerns that biofuel supply chains could be disrupted if extreme weather events impact feedstock yields. In this paper, we explore the use of multi-objective optimization to identify biofuel production pathways that balance cost, greenhouse gas emissions, and supply vulnerability to extreme weather. We compare the use of three different many-objective evolutionary algorithms and linear programming in optimizing biomass cultivation decisions in the U.S. Corn Belt under weather uncertainty using historical, modeled, and synthetic yield data. We consider four feedstock choices (corn, soy, switchgrass, and algae) with two land types (agricultural and marginal lands) and evaluate decisions using three alternative spatial resolutions (ranging from the USDA agricultural district level to the state level). Results show that feedstock choice is the primary driver of objective performance (i.e., the position and shape of 3D, approximate Pareto frontiers). Spatial diversification is a less effective tool in reducing exposure to weather-caused drops in crop yield.

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Research Organization:: Colorado State University, Fort Collins, CO (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Office of Sustainable Transportation. Bioenergy Technologies Office (BETO)

Grant/Contract Number:: EE0008935; AC05-00OR22725

OSTI ID:: 2563569

Journal Information:: Biomass and Bioenergy, Journal Name: Biomass and Bioenergy Vol. 193; ISSN 0961-9534

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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