May 23, 2012

MEMORANDUM

TO: Air Docket EPA-HQ-OAR-2011-0542

SUBJECT: Summary of Modeling Inputs and Assumptions for the Notice 

of Data Availability (NODA) Concerning Renewable Fuels 

Produced from Grain Sorghum Under the Renewable Fuel 

Standard Program

This memorandum provides information on the key inputs and assumptions used for 

modeling the lifecycle greenhouse gas (GHG) emissions associated with renewable fuel 

produced from grain sorghum. Assumptions include energy use, energy sources, 

fertilizer use, co-product production, and other important factors used in the lifecycle 

analysis.

Outline of this Document

I. System Boundaries

II. Data and Assumptions

A. Model Modifications

B. Agriculture Model Assumptions

C. Volume Scenarios

D. Grain Sorghum Ethanol Processing

III. References
I. System Boundaries

The general system boundaries for lifecycle GHG analysis of biofuels under the RFS 

program were determined as part of the March 26, 2010 final rule (EPA 2010). Applying 

these system boundaries to our analysis of ethanol produced from grain sorghum was 

straightforward because the lifecycle system for grain sorghum ethanol are similar to 

those of other biofuels that were analyzed in EPA (2010). 

This document focuses on our assumptions related to the various stages in the grain 

sorghum ethanol lifecycle, including fuel and feedstock production and distribution. To 

analyze the indirect agricultural and land use change impacts, we used the same 

agricultural economic models that were used for the final RFS2 rule. The Forest and 

Agricultural Sector Optimization Model (FASOM), developed by Professor Bruce 

McCarl of Texas A&M University and others, provides detailed information on domestic 

agricultural and greenhouse gas impacts of renewable fuels. The Food and Agricultural 

Policy Research Institute international models, as maintained by the Center for 

Agricultural and Rural Development at Iowa State University (FAPRI-CARD), consist of 

a number of econometric models that are capable of providing detailed information on 

impacts on international agricultural markets from the wider use of renewable fuels in the 

U.S. For more discussion on our use of the FAPRI-CARD model refer to the grain 

sorghum NODA preamble (EPA 2012).

II. Data and Assumptions

This section includes a summary of key assumptions and data inputs used in our lifecycle 

GHG assessment of grain sorghum ethanol. Our analysis considers direct and significant 

indirect emissions related to the production and use of grain sorghum ethanol. As such, 

we also considered GHG emissions impacts related to the production and use of other 

agricultural commodities (e.g., corn, soybeans) that are indirectly impacted by an 

increase in grain sorghum ethanol production and use. For information on the data inputs 

and assumptions used to evaluate these other aspects of our analysis refer to the 

Regulatory Impact Analysis for the RFS2 final rule (EPA 2010). 

A. Model Modifications

Since the analysis for the RFS2 final rulemaking was completed, there was an update to 

the land categories defined in the FASOM model with the addition of a new ‘pasture’ 

category. All other land use category definitions remain unchanged from the final RFS2 

rulemaking. Updated land use definitions are as follows:

• Cropland is actively managed cropland, used for both traditional crops (e.g., corn 

and soybeans) and dedicated energy crops (e.g., switchgrass).

• Cropland pasture is managed pasture land used for livestock production, but which 

can also be converted to cropland production without additional improvement.
• Pasture is land used only for pasture or grazing that cannot be converted into 

cropland.

• Forestland contains a number of sub-categories, tracking the number of acres of 

private forestland existing at the starting point of the model that remain in standing 

forests (i.e., have not yet been harvested), the number of acres harvested, the number 

of harvested acres that are reforested, and the area converted from other land uses 

(afforested). Public forestland area is not explicitly tracked because it is assumed to 

remain constant over time, although exogenous estimates of forest products 

production from these lands are included in the model

• Rangeland is unmanaged land that can be used for livestock grazing production. 

While the amount of rangeland idled or used for production may vary, it is assumed 

that rangeland may not be used for any other purpose than for animal grazing due to 

its low productivity. In addition, much of the rangeland in the U.S. is publicly

owned. 

• Developed (urban) land is assumed to have an inherently higher value than land 

used for any other use. Thus, the rate of urbanization is assumed to be exogenous 

based on projections of population and income growth and does not change between 

the cases analyzed.

• Conservation Reserve Program (CRP) refers to land that is voluntarily taken out 

of crop production and placed in the USDA CRP. Land in the CRP is generally 

marginal cropland retired from production and converted to vegetative cover, such as 

grass, trees, or woody vegetation to conserve soil, improve water quality, enhance 

wildlife habitat, or produce other environmental benefits.

B. Agriculture Model Assumptions

Major assumptions consistently implemented in the FASOM and FAPRI-CARD models 

include ethanol conversion yields, and byproduct yields. In the case of grain sorghum, 

distiller grains (DG) are the only byproduct from the ethanol conversion.

Table 1

Assumption Value Source

Ethanol Yield 2.71 gal/bu Same value used in RFS2 final rulemaking 

analysis as corn ethanol

Dried Distillers 

Grains Yield

17 lbs/bu Same yield, nutritional value, displacement 

rates, and inclusion rates as used in the RFS2 

final rulemaking analysis as corn ethanol.

All other assumptions, such as fertilizer application rates and energy use, in the FASOM 

and FAPRI-CARD models are documented in the Regulatory Impact Analysis for the 

RFS2 final rule (EPA 2010), as well as technical reports for the FASOM (RTI 2010) and 

FAPRI-CARD (FAPRI-CARD Staff 2010) models in the RFS2 final rule docket.
1. Perfect Substitution between Grain Sorghum and Corn in the U.S. Animal Feed Market

Based on information from industry stakeholders, as well as in consultation with USDA, 

both the FASOM and FAPRI-CARD models assume perfect substitution in the use of 

grain sorghum and corn in the animal feed market in the U.S. Therefore, when more 

grain sorghum is used for ethanol production, grain sorghum used in feed decreases. 

Either additional corn or sorghum will be used in the feed market to make up for this 

decrease, depending upon the relative cost of additional production. This assumption is 

based on conversations with industry and the USDA, reflecting the primary use of 

sorghum in the U.S. as animal feed, just like corn.

2. Grain Sorghum Production, Trade and Consumption in India and Nigeria

The United States is one of the largest producers and exporters of grain sorghum. 

However, two large producers of grain sorghum, India and Nigeria, do not actively 

participate in the global trade market for sorghum. Rather, all grain sorghum in those 

two countries is produced for domestic consumption. Therefore, as the U.S. diverts some 

of its exports of grain sorghum for the purposes of ethanol production, we would expect 

close to no reaction in the production levels of grain sorghum in India and Nigeria. 

Historical data on prices, production, and exports from USDA, FAOSTAT, and FAPRI 

support this assumption.

C. Volume Scenarios

To assess the impacts of an increase in renewable fuel volume from business-as-usual 

(what is likely to have occurred without the RFS biofuel mandates) to levels required by 

the statute, we established reference and control cases for a number of biofuels analyzed 

for the RFS2 final rulemaking. The reference case includes a projection of renewable 

fuel volumes without the RFS renewable fuel volume mandates. The control cases are 

projections of the volumes of renewable fuel that might be used in the future to comply 

with the volume mandates. The final rule reference case volumes were based on the 

Energy Information Administration’s (EIA) Annual Energy Outlook (AEO) 2007 

reference case projections. In the RFS2 rule, for each individual biofuel, we analyzed the 

incremental GHG emission impacts of increasing the volume of that fuel to the total mix 

of biofuels needed to meet the EISA requirements. 

For the analysis of grain sorghum ethanol, a new control case was developed to account 

for the current production of grain sorghum ethanol which is approximately 200 million 

gallons per year (see Chapter 1 of the RFS2 RIA). All other volumes for each individual 

biofuel in this new control case remain identical to the control case used in the RFS2 rule. 

For the “grain sorghum” case, our modeling assumes approximately 300 million gallons 

of sorghum ethanol would be consumed in the United States in 2022. The modeled 

scenario includes 2.06 billion lbs of grain sorghum to be used to produce the additional 

100 million gallons of ethanol in 2022.
Our volume scenario of approximately 200 million gallons of grain sorghum ethanol in 

the new control case, and 300 million gallons in the grain sorghum case in 2022, is based 

on several factors including historical volumes of grain sorghum ethanol production, 

potential feedstock availability and other competitive uses (e.g., animal feed or exports). 

Based in part on consultation with experts at the United States Department of Agriculture 

(USDA) and industry representatives, we believe that these volumes are reasonable for 

the purposes of evaluating the impacts of producing additional volumes of ethanol from 

grain sorghum. 

The FASOM and FAPRI-CARD models, described above, project how much grain 

sorghum will be supplied to ethanol production from a combination of increased

production, decreases in others uses (e.g., animal feed), and decreases in exports, in going 

from the control case to the grain sorghum case.

D. Grain Sorghum Ethanol Processing

We expect the dry milling process will be the basic production method for producing 

ethanol from grain sorghum and therefore this is the ethanol production process 

considered here. In the dry milling process, the grain sorghum is ground and fermented 

to produce ethanol. The remaining DG are then either left wet if used in the near-term or 

dried for longer term use as animal feed. 

For this analysis the amount of grain sorghum used for ethanol production as modeled by

the FASOM and FAPRI-CARD models was based on yield assumptions built into those 

two models. Specifically, the models assume sorghum ethanol yields of 2.71 gallons per 

bushel for dry mill plants (yields represents pure ethanol). 

As per the analysis done in the RFS2 final rule, the energy consumed and emissions 

generated by a renewable fuel plant must be allocated not only to the renewable fuel 

produced, but also to each of the by-products. For grain sorghum ethanol production, this 

analysis accounts for the DG co-product use directly in the FASOM and FAPRI-CARD 

agricultural sector modeling described above. DG are considered a replacement animal 

feed and thus reduce the need to make up for the grain sorghum production that went into 

ethanol production. Since FASOM takes the production and use of DG into account, no 

further allocation was needed at the ethanol plant and all plant emissions are accounted 

for there. 

In terms of the energy used at grain sorghum ethanol facilities, significant variation exists 

among plants with respect to the production process and type of fuel used to provide 

process energy (e.g., coal versus natural gas). Variation also exists between the same 

type of plants using the same fuel source based on the design of the production process 

such as the technology used to separate the ethanol from the water, the extent to which 

the DG are dried and whether other co-products are produced. Such different pathways 

were considered for ethanol made from corn. Since for the most part these same 

production processes are available for ethanol produced from sorghum, our analyses 

considered a similar set of different production pathways for grain sorghum ethanol 
production. Our focus was to differentiate among facilities based on key differences, 

namely the type of plant and the type of process energy fuel used. 

Ethanol production is a relatively resource-intensive process that requires the use of 

water, electricity, and steam. In most cases, water and electricity are purchased from the 

municipality and steam is produced on-site using boilers fired by natural gas, coal, or in 

some cases, alternative fuels (described in more detail below).1 

Purchased process fuel and electricity use for grain sorghum ethanol production was 

based on the energy use information for corn ethanol production from the RFS2 final rule 

analysis. For the RFS2 final rule, EPA modeled future plant energy use to represent 

plants that would be built to meet requirements of increased ethanol production, as 

opposed to current or historic data on energy used in ethanol production. The energy use 

at dry mill ethanol plants was based on ASPEN models developed by USDA and updated 

to reflect changes in technology out to 2022 as described in the RFS 2 final rule RIA 

Chapter 1. 

The work done on grain ethanol production for the RFS2 final rule was based on 

converting corn to ethanol. Converting grain sorghum to ethanol will result in slightly

different energy use based on difference in the grains and how they are processed. For 

example, grain sorghum has less oil content than corn and therefore requires less 

processing and mass transfer of the oil which results in a decrease in energy use 

compared to processing corn to ethanol. The same ASPEN USDA models used for corn 

ethanol in the final rule were also developed for grain sorghum ethanol. Based on the 

numbers from USDA, a sorghum ethanol plant uses 96.3% of the thermal process energy

of a corn ethanol plant (3.7% less), and 99.3% of the electrical energy (0.7% less). 

The GHG emissions from production of ethanol from grain sorghum were calculated in 

the same way as other fuels analyzed as part of the RFS2 final rule. The GHG emissions 

were calculated by multiplying the BTUs of the different types of energy inputs at the 

grain sorghum ethanol plant by emissions factors for combustion of those fuel sources. 

The BTU of energy input was determined based on analysis of the industry and work 

done as part of the RFS2 final rule as well as considering the impact of different 

technology options on plant energy needs. The emission factors for the different fuel 

types are the same as those used in the RFS2 final rule and were based on assumed 

carbon contents of the different process fuels. The emissions from producing electricity 

in the U.S. were also the same as used in the RFS2 final rule, which were taken from the 

Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation Model 

(GREET) and represent average U.S. grid electricity production emissions. 

One of the energy drivers of ethanol production is drying of the DG. Plants that are colocated with feedlots have the ability to provide the co-product without drying. This 

energy use has a large enough impact on overall results in previous analyses that we 

defined a specific category for wet versus dry co-product as part of the RFS2 final rule. 

For grain sorghum ethanol production we also consider wet versus dry DG. For corn 

 

1

Some plants pull steam directly from a nearby utility.
ethanol production, as discussed in the RFS2 final rule, the industry average for wet DG 

is approximately 37%. Industry provided data that approximately 92% of grain sorghum 

DG is wet. However, in the case of grain sorghum ethanol production, the current data 

shows that energy used for DG drying does not change whether a facility meets the 20% 

GHG emission threshold (conventional renewable fuel) or the 50% GHG emission 

threshold (advanced renewable fuel). The amount of btu per gallon of ethanol produced 

for processes where DG are dried, and where they are not, can be found in Table 2 below. 

For this NODA, we analyzed several combinations of different advanced process 

technologies and fuels to determine their impacts on lifecycle GHG emissions from grain 

sorghum ethanol. As noted above, many of the same technologies that were considered 

as part of the RFS2 final rule for corn ethanol can also be applied to grain sorghum 

ethanol production. Based on discussion with industry, we understand there is interest in 

building grain sorghum ethanol plants which incorporate such advanced technologies. 

Therefore, as was the case with corn ethanol in the RFS2 final rule, our intent is to 

provide different processing technology options that producers could use to meet the 

lifecycle threshold requirements required by EISA. This section describes the different 

GHG impacts associated with alternative processing technology and fuel options and 

outlines specific process pathways that would be needed to meet different GHG threshold 

requirements. If finalized, these pathways would allow producers to use the updated 

Table 1 in Section 80.1426 to determine whether their combination of technologies and 

process fuels would allow them to qualify as an advanced grain sorghum ethanol 

pathway. 

Several technologies and fuel choices affect emissions from process energy use. Fuel 

choice has a significant impact on process energy emissions; switching from natural gas 

to biogas2, for example, will reduce lifecycle GHG emissions by approximately 20 

percentage points. Another factor that influences GHG impacts from process energy use 

is the percentage of DG that is dried. If a plant is able to reduce the amount of DG it 

dries, process energy use, and therefore GHG emissions, decrease. The impact of going 

from 100% dry DG to 100% wet DG is larger for natural gas plants (approximately a 

10% reduction in overall GHG emissions relative to the petroleum baseline) compared to 

biogas plants because biogas plants already have low emissions from process energy. 

Production facilities that utilize combined heat and power (CHP) systems can also reduce 

GHG emissions relative to less efficient system configurations. CHP, also known as 

cogeneration, is a mechanism for improving overall plant efficiency by using a single fuel 

to generate both power and thermal energy. The most common configuration in ethanol 

plants involves using the boiler to power a turbine generator unit that produces electricity, 

and using waste heat to produce process steam. While the thermal energy demand for an 

ethanol plant using CHP technology is slightly higher than that of a conventional plant, 

the additional energy used is far less than what would be required to produce the same 

amount of electricity in an offsite (central) power plant. The increased efficiency is due 

 

2 Biogas in the context of use as a fuel source at ethanol plants refers to biogas from landfills, waste 

treatment plants, and waste digesters. 
to the ability of the ethanol plant to effectively utilize the waste heat from the electricity 

generation process. 

In addition to CHP (or sometimes in combination), a growing number of ethanol 

producers are turning to alternative fuel sources to replace traditional boiler fuels (i.e., 

natural gas and coal), to improve their carbon footprint and/or become more selfsustainable. Alternative boiler fuels currently used or being pursued by the ethanol 

industry include biomass, co-products from the ethanol production process (bran, thin 

stillage or syrup), manure biogas (methane from nearby animal feedlots), and landfill gas 

(generated from the digestion of municipal solid waste). The CO2 emissions from 

biomass combustion as a process fuel source are not specifically shown in the lifecycle 

GHG inventory of the biofuel production plant; rather, CO2 emissions from biomass use 

are accounted for as part of the land use change calculations for each feedstock. 

Since CHP technologies on natural gas plants reduce purchased electricity but increase 

process energy use emissions (because of increased natural gas use on-site), the net result 

is a small reduction in overall emissions. CHP at biogas facilities result in greater 

reductions since the increased biogas use for electricity production does not result in 

significant increases in on-site emissions. 

Although not exhaustive, Table 2 shows the amount of process fuel and purchased 

electricity used at a grain sorghum ethanol facility for the different technology and fuel 

options in terms of Btu/gal of ethanol produced.

Table 2. Process Fuel and Electricity Options at Grain Sorghum Ethanol Facilities 

(Btu / Gallon of Ethanol Produced)
Fuel Type and Technology Natural Gas 

Use

Biogas 

Use

Coal 

Use

Purchased 

Electricity

Sorghum Ethanol –

Dry Mill Natural Gas

No CHP, 100% Wet DG 16,449 2,235

Yes CHP, 100% Wet DG 18,605 508

No CHP, 92% Wet DG 17,341 2,235

Yes CHP, 92% Wet DG 19,497 508

No CHP, 0% Wet DG 27,599 2,235

Yes CHP, 0% Wet DG 29,755 508

Sorghum Ethanol –

Dry Mill Biogas

No CHP, 100% Wet DG 16,449 2,235

Yes CHP, 100% Wet DG 18,605 508

No CHP, 92% Wet DG 17,341 2,235

Yes CHP, 92% Wet DG 19,497 508

No CHP, 0% Wet DG 27,599 2,235

Yes CHP, 0% Wet DG 29,755 508

Sorghum Ethanol –

Dry Mill Coal

No CHP, 100% Wet DG 20,561 2,675

Yes CHP, 100% Wet DG 24,011 203

No CHP, 92% Wet DG 21,676 2,675

Yes CHP, 92% Wet DG 25,126 203

No CHP, 0% Wet DG 34,499 2,675

Yes CHP, 0% Wet DG 37,949 203

III. References
Food and Agricultural Policy and Research Institute international models as maintained 

by the Center for Agricultural and Rural Development at Iowa State University (FAPRCARD) Staff. 2010. Technical Report: An Analysis of EPA Renewable Fuel Scenarios 

with the FAPRI–CARD International Models. January, 2010. Docket No. EPA-HQOAR-2005-0161-3177.

RTI International. 2010. U.S. Agricultural and Forestry Impacts of the Energy

Independence and Security Act: FASOM Results and Model Description. January 2010. 

Docket No. EPA-HQ-OAR-2005-0161-3178.

U.S. Environmental Protection Agency (EPA). 2012. Notice of Data Availability

Concerning Renewable Fuels Produced from Grain Sorghum Under the RFS Program.

U.S. Environmental Protection Agency (EPA). 2010. Renewable Fuel Standard Program 

(RFS2) Regulatory Impact Analysis. EPA-420-R-10-006. 

http://www.epa.gov/oms/renewablefuels/420r10006.pdf