Greenhouse Gas Accounting Procedures in Low Carbon Fuel Policies Overlook the Spatial Variability of Miscanthus-derived Sustainable Aviation Fuel

28 April 2025, Version 2
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

Low carbon fuel policies such as the U.S. Renewable Fuel Standard (RFS), Canada Clean Fuel Regulations (CFR), and California Low Carbon Fuel Standard (LCFS) as well as the 45Z tax credit are intended to reduce greenhouse gas (GHG) emissions from transportation. Cellulosic feedstocks, optimized biorefineries, and favorable farming locations can significantly reduce biofuel carbon intensity (CI). Despite the emergence of field-to-fuel GHG monitoring technologies that could verify such benefits, policy-specific requirements for CI accounting procedures may limit fuel producers’ ability to capitalize on these opportunities. This work examines a hypothetical biomass-to-sustainable aviation fuel (SAF) pathway using miscanthus and alcohol-to-jet (i) to demonstrate how GHG accounting requirements drive estimates of biofuel CIs and (ii) to explore potential CI and financial benefits of scenario-specific life cycle assessment (LCA). Results demonstrate that GHG accounting using the CFR and LCFS can reasonably account for distinct levels of net electricity production by a biorefinery, but only the CFR yields similar CI sensitivity to spatially explicit factors (feedstock CI, grid electricity CI) as scenario-specific LCA: most GHG accounting frameworks do not capture CI variation across candidate sites in the United States. Ultimately, this work demonstrates the importance of LCA methodological specifications in low carbon fuel policies and tax credits.

Keywords

sustainable aviation fuel (SAF)
ethanol-to-jet (ETJ)
alcohol-to-jet (ATJ)
life cycle assessment (LCA)
techno-economic analysis (TEA)
cellulosic biofuel
measurement monitoring reporting and verification (MMRV)

Supplementary materials

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Supporting Information
Description
Detailed policy-specific CI calculations, description of input parameter distributions and sensitivity analysis results, description of low carbon fuel program credit prices, expanded TEA and LCA results.
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