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ARS Home » Plains Area » Lincoln, Nebraska » Agroecosystem Management Research » Research » Publications at this Location » Publication #337095

Title: Field-to-farm gate greenhouse gas emissions from corn stover production in the midwestern US

Author
item LOCKER, REBECCA - Exxonmobil
item LAURENZI, IAN - Exxonmobil
item TORKAMANI, SARAH - Exxonmobil
item Jin, Virginia
item Schmer, Marty
item Karlen, Douglas

Submitted to: Journal of Cleaner Production
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/13/2019
Publication Date: 3/28/2019
Citation: Locker, R.C., Laurenzi, I.J., Torkamani, S., Jin, V.L., Schmer, M.R., Karlen, D.L. 2019. Field-to-farm gate greenhouse gas emissions from corn stover production in the midwestern US. Journal of Cleaner Production. 226:1116-1127. https://doi.org/10.1016/j.jclepro.2019.03.154.
DOI: https://doi.org/10.1016/j.jclepro.2019.03.154

Interpretive Summary: Corn stover is the plant material remaining after grain harvest. Because of its abundance, particularly in the U.S. Corn Belt, stover has been identified as a primary candidate for biofuel production. U.S. federal regulations under the Renewable Fuel Standards require that biofuels based on non-grain plant biomass meet a 60% reduction in system greenhouse gas (GHG) emissions compared to a petroleum-based system in order to qualify for Renewable Indentification Numbers as a Cellulosic Biofuel under RFS. System GHG emissions are usually estimated with models instead of measured under real-world production conditions. This study is the first to include a comprehensive dataset that uses a multi-year yield and GHG data to calculate system GHG emissions in corn production systems where grain-only or grain+stover is harvested. Data were provided by the USDA-REAP (Resilient Economic Agricultural Practices) program and collected from 9 field sites from 5 states across the U.S. Corn Belt. Mean GHG emissions from the corn stover production sites were comparable to literature values based on models, but the REAP data enabled an assessment of the spatial and temporal variability in emissions. Moderate rates of stover removal (~33%) under reduced or no-till management resulted in the lowest system GHG emissions, and is consistent with current stover removal rates recommended by USDA.

Technical Abstract: This assessment utilizes publicly available data from the USDA-ARS Resilient Economic Agricultural Practices (REAP) research program to compute greenhouse gas (GHG) emissions for corn grain and corn stover production in the Midwestern U.S. Measured yields, fertilization rates and direct soil emissions were averaged across nine locations where three stover harvest rates (none – no removal, medium – 3.1 Mg ha-1, high – 7.2 Mg ha-1) and two tillage practices (conventional and reduced/no-till) were implemented. Net carbon uptake by the corn plant was computed from measured biomass carbon content, and carbon balance was met by assuming no accumulation of soil organic carbon. Farm-to-gate GHG emissions were computed from Monte Carlo simulations for each farm management scenario (2 tillage x 3 harvest rates) and two different methods to account for the corn grain and stover co-products-- mass allocation and system expansion. A moderate removal rate with reduced/no till, consistent with current stover harvesting practices being implemented by three U.S. commercial-scale biorefineries, results in farm-to-gate GHG emissions of -1.51 ± 0.59 kg CO2 eq/kg stover harvested using the system expansion method. Emissions were most sensitive to the co-product accounting method, with system expansion emissions about 15% lower than mass allocation. In all cases studied, soil GHG emissions and net CO2 uptake during growth dominated the magnitude of GHG emissions. Sensitivity analyses revealed that farm input variables associated with computation of these stages contributed most significantly to the variability in the emissions, highlighting the importance of explicitly including soil emissions and biogenic carbon in life-cycle assessments (LCA) of corn stover biofuels in order to accurately assess variability.