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Impact of different bioenergy crop yield estimates on the cellulosic ethanol feedstock mix

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Abstract

Although a cellulosic ethanol mandate for 2022 is in place, significant political, economic, and agronomic uncertainty exists surrounding the attainability of the mandate. This paper evaluates the effects of bioenergy crop yield and cost uncertainty on land allocation and the feedstock mix for cellulosic ethanol in the United States. The county-level model focuses on corn, soybeans, and wheat as the field crops and corn stover, wheat straw, switchgrass, and miscanthus as the biomass feedstocks. The economic model allocates land optimally among the alternative crops given a binding cellulosic biofuel mandate. The model is calibrated to 2022 in terms of yield, crop demand, and baseline prices. The bioenergy and commodity prices resulting from a mandate are endogenous to the model. The scenarios simulated differ in terms of bioenergy crop types (switchgrass and miscanthus), bioenergy crop yields, bioenergy production cost, and the cellulosic biofuel mandate ranging from 15 to 60 billion gallons. Our results indicate that the largest proportion of agricultural land dedicated to either switchgrass or miscanthus is found in the Southern Plains and the Southeast. Almost no bioenergy crops are grown in the Midwest across all scenarios. The 15 and 30 billion liter mandates in the high production cost scenarios for switchgrass and in all miscanthus scenarios are covered to 95\% by agricultural residues. Changes in the prices for the three commodities are negligible for low cellulosic ethanol mandates because most of the mandate is met with agricultural residues. The amount of bioenergy crops brought into production at the highest imposed mandate result in price increases ranging from 5% for corn and soybeans to almost 14% for wheat.

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  • Dumortier, Jerome, 2014. "Impact of different bioenergy crop yield estimates on the cellulosic ethanol feedstock mix," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 171168, Agricultural and Applied Economics Association.
  • Handle: RePEc:ags:aaea14:171168
    DOI: 10.22004/ag.econ.171168
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    1. Li, Chao & Hayes, Dermot J. & Jacobs, Keri L., 2018. "Biomass for bioenergy: Optimal collection mechanisms and pricing when feedstock supply does not equal availability," Energy Economics, Elsevier, vol. 76(C), pages 403-410.

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