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2017 | OriginalPaper | Chapter

Modeling Bioenergy, Land Use, and GHG Mitigation with FASOMGHG: Implications of Storage Costs and Carbon Policy

Authors : Robert H. Beach, Yuquan W. Zhang, Bruce A. McCarl

Published in: Handbook of Bioenergy Economics and Policy: Volume II

Publisher: Springer New York

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Abstract

Biofuels production has increased rapidly in recent years due to heightened concerns regarding climate change and energy security. Biofuels produced from agricultural feedstocks increase pressure on land resources. Competition for land is expected to continue growing in the future as mandated biofuels volumes increase along with rising demand for food, feed, and fiber, both domestically and internationally. In response to concerns regarding impacts such as indirect land use change and higher food prices, U.S. policy is focusing on second-generation (cellulosic) feedstocks to contribute the majority of the mandated increase in biofuels volume through 2022. However, there has been little work exploring supply logistics, feedstock mix, and net GHG effects of combining renewable fuels mandates with climate policy. Using the recently updated Forest and Agricultural Sector Optimization Model with Greenhouse Gases (FASOMGHG), we explore implications of alternative assumptions regarding feedstock storage costs and carbon price for renewable energy production mix, land use, and net GHG emissions. The model is used to quantify the magnitude and regional distribution of changes in the optimal mix of bioenergy feedstocks when accounting for storage costs. Further, combining a volume mandate with carbon price policy impacts feedstock mix and provides substantially larger net reduction in GHG.

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Footnotes
1
The results reported for each 5-year interval are intended to be representative of the average annual results for that 5-year time step. In previous versions of the model, results were generated at 10-year time steps and represented average annual results for that 10-year period.
 
2
Although timberland is not explicitly modeled because the focus of the model is on private decision-maker responses to changing incentives, FASOMGHG includes an exogenous timber supply from public forestlands.
 
3
Note that FASOMGHG does not include all cropping activities conducted in the United States. For instance, tobacco, vineyards, and most fruits and vegetables are not included within the model.
 
5
Note that the developed land category tracked in the model refers to land that was initially in forest or agricultural use in the initial model period only, not land that was already developed prior to that time.
 
6
As noted by an anonymous reviewer for an earlier version of this chapter, there is considerable uncertainty regarding changes to the CRP that may be introduced in the future. However, in this study, we assume that the U.S. would continue supporting CRP indefinitely at acreage levels consistent with the 2008 Farm Bill. We have explored alternative assumptions for the CRP in previous model runs and found that, as expected, allowing greater conversion of CRP land reduces commodity market impacts.
 
7
The national subsidy included in FASOMGHG is based on the subsidy included in the Emergency Economic Stabilization Act of 2008 (H.R.1424), signed into law in October 2008. The Energy Policy Act of 2005 (H.R.6), which extended the biodiesel credit specified as part of the Volumetric Ethanol Excise Tax Credit (VEETC) under the American Jobs Creation Act of 2004 (H.R. 4520), provided a subsidy equal to $1 per gallon for “agri-biodiesel” (diesel fuel made from virgin oils derived from agricultural commodities and animal fats) and $0.50 per gallon for “biodiesel” (diesel fuel made from agricultural products and animal fats). The Emergency Economic Stabilization Act of 2008 eliminated the distinction between agri-biodiesel and biodiesel such that all biodiesel qualified for the $1-per-gallon subsidy.
 
8
A multiplicative factor of 2 is included in the calculation to represent round-trip costs.
 
9
FASOMGHG assumes a standard plant size of 75 million gallons per year for starch-based ethanol and 100 million gallons per year for cellulosic ethanol, with the exception of sweet sorghum, which is assumed to be used in 40 million gallon-per-year plants. The quantity of feedstock required to produce that amount of ethanol varies based primarily on differences in starch/sugar content or potential to convert cellulose to ethanol that lead to variation in ethanol yield per unit of feedstock.
 
10
No additional storage costs are included for grain crops because they are routinely stored for year-round consumption in other markets using a well-established infrastructure and their storage costs are assumed to be reflected in their market prices.
 
11
The average number of months feedstock is stored is calculated based on an assumption of equal monthly withdrawals from storage over the number of months that feedstock is stored; that is, if residues are stored for up to 10 months, then it was assumed that 10/12 of total plant feedstock requirements are stored for 1 month, 9/12 for 2 months, and so on. In this example, the average number of months that a ton of crop residues would be stored is 4.5833 months.
 
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Metadata
Title
Modeling Bioenergy, Land Use, and GHG Mitigation with FASOMGHG: Implications of Storage Costs and Carbon Policy
Authors
Robert H. Beach
Yuquan W. Zhang
Bruce A. McCarl
Copyright Year
2017
Publisher
Springer New York
DOI
https://doi.org/10.1007/978-1-4939-6906-7_10