A spatial modeling framework to evaluate domestic biofuel-induced potential land use changes and emissions.
We present a novel bottom-up approach to estimate biofuel-induced land-use change (LUC) and resulting CO2 emissions in the U.S. from 2010 to 2022, based on a consistent methodology across four essential components: land availability, land suitability, LUC decision-making, and induced CO2 emissions. Using high-resolution geospatial data and modeling, we construct probabilistic assessments of county-, state-, and national-level LUC and emissions for macroeconomic scenarios. We use the Cropland Data Layer and the Protected Areas Database to characterize availability of land for biofuel crop cultivation, and the CERES-Maize and BioCro biophysical crop growth models to estimate the suitability (yield potential) of available lands for biofuel crops. For LUC decision-making, we use a county-level stochastic partial-equilibrium modeling framework and consider five scenarios involving annual ethanol production scaling to 15, 22, and 29 BG, respectively, in 2022, with corn providing feedstock for the first 15 BG and the remainder coming from one of two dedicated energy crops. Finally, we derive high-resolution above-ground carbon factors from the National Biomass and Carbon Data set to estimate emissions from each LUC pathway. Based on these inputs, we obtain estimates for average total LUC emissions of 6.1, 2.2, 1.0, 2.2, and 2.4 gCO2e/MJ for Corn-15 Billion gallons (BG), Miscanthus × giganteus (MxG)-7 BG, Switchgrass (SG)-7 BG, MxG-14 BG, and SG-14 BG scenarios, respectively.
University of Chicago and Argonne National Laboratory Computation Institute , Chicago, Illinois 60637, United States.
Joshua
J
Elliott
Bhavna
B
Sharma
Neil
N
Best
Michael
M
Glotter
Jennifer B
JB
Dunn
Ian
I
Foster
Fernando
F
Miguez
Steffen
S
Mueller
Michael
M
Wang
D000393:Air Pollutants / Q000032:analysis*; D056804:Biofuels / Q000032:analysis*; D018533:Biomass; D003247:Conservation of Natural Resources; D018556:Crops, Agricultural / Q000737:chemistry; D005843:Geography; D008962:Models, Theoretical; D006109:Poaceae / Q000737:chemistry; D013269:Stochastic Processes; D014481:United States
D000393:Air Pollutants; D056804:Biofuels