June 20th, 2013

MEMORANDUM

TO: Air Docket EPA-HQ-OAR-2013-0178

SUBJECT: Summary of Modeling Inputs and Assumptions for the 

Determination Concerning Renewable Fuels Produced from 

Barley 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 barley. 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. Barley 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 barley was 

straightforward because the lifecycle system for barley 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 barley

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 barley determination

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 barley ethanol. Our analysis considers direct and significant indirect 

emissions related to the production and use of barley 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 barley

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 barley, distillers

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

Table 1

Assumption Value Source

Ethanol Yield 2.16 gal/bu Consultation with USDA experts

Dried Distillers 

Grains Yield

13.25 lbs/bu Yield, nutritional value, displacement rates, and 

inclusion rates based on expert opinion of 

USDA

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. Disaggregation of Spring and Winter Barley

Based on information from industry stakeholders, data from the USDA National 

Agricultural Statistics Service,1as well as in consultation with USDA, the FASOM 

model assumes that barley produced in Delaware, Maryland, North Carolina, 

Pennsylvania, and Virginia is “winter” barley (i.e., barley planted in late fall and 

harvested in early spring), while barley grown in all other regions is assumed to be 

“spring” barley (i.e., barley planted in the spring and harvested in the fall).

FASOM has historically not had the ability to model winter barley production. We have 

added this cropping pattern into FASOM, given the fact winter barley could be a 

potentially significant contributor to total barley ethanol production if this rulemaking is 

finalized. Therefore, we believe, it is important for the modeling framework to consider 

the full range of barley production methods available to the maximum extent possible. 

Conversely, because of differences in model architecture, it was not possible to 

differentiate between spring and winter barley in the FAPRI-CARD model. However, we 

believe not modeling double cropping for barley in the Southeast and Mid-Atlantic region 

of the US in the FAPRI-CARD model results in a conservative estimate of lifecycle GHG 

emissions, as it may slightly overstate the land use change and commodity market 

impacts of an increase in demand for barley ethanol. 

2. Double-Cropping of Winter Barley

Historically, winter barley is “double-cropped” with soybeans. Farmers that utilize this 

double-cropping method plant their soybean crop in the mid or late spring and harvest it 

in the early fall followed soon after with a barley crop that is planted in the fall and 

harvested in the early spring. Importantly, soybean acres in the Southeast and MidAtlantic regions of the U.S. that are not double-cropped with barley are generally left 

fallow during the winter months.

2

Based on information from industry stakeholders, as well as in consultation with USDA,3

the FASOM model assumes that all winter barley is double-cropped with soybeans. This 

means that a grower is assumed to plant soybeans in the spring, harvesting them in the 

fall, then plant barley in the winter, harvesting it in early spring. It is also assumed that 

these acres would be fallow in the winter if they were not double-cropped. Because it 

was not possible to differentiate spring and winter barley in the FAPRI-CARD model, no 

double-cropping assumption was made. However, for reasons stated above, this is not 

expected to have an influence on the international agriculture impacts estimated in the 

FAPRI-CARD model.

C. Volume Scenarios

 

1 USDA National Agricultural Statistics Service (www.nass.usda.gov)

2

Personal communication with USDA

3

Personal communication with USDA
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 a control case and other cases for a number of biofuels 

analyzed for the March, 2010 RFS rule. The control case included a projection of 

renewable fuel volumes that might be used to comply with the RFS renewable fuel 

volume mandates in full. The other cases are designed such that the only difference 

between a given case and the control case is the volume of an individual biofuel, all other 

volumes remaining the same. In the March 2010 RFS 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. Rather than focus on 

the GHG emissions impacts associated with a specific gallon of fuel and tracking inputs 

and outputs across different lifecycle stages, we determined the overall aggregate impacts 

across sectors of the economy in response to a given volume change in the amount of 

biofuel produced. 

For this analysis we compared impacts in the control case to the impacts in a new “barley 

ethanol” case. Some assumptions related to barley production and ethanol use were 

adjusted based on consultation with USDA, academic experts, and industry stakeholders. 

However, the volume of biofuels produced in this version of the control case is the same 

as what was analyzed for the March 2010 RFS rule. 

For the “barley ethanol” case, our modeling analyzed a shock of 140 million gallons of 

barley ethanol in 2022. In FASOM, this volume was divided into 80 million gallons of 

“spring barley” ethanol and 60 million gallons of “winter barley” ethanol. EPA chose 

this modeled volume (for both “spring barley” and “winter barley” ethanol) based upon 

consultations with industry stakeholders regarding their anticipated production capacity, 

and USDA regarding how much barley could practically be dedicated to ethanol 

production 2022 given historical and anticipated barley production levels and various 

demands (e.g., food, animal feed, exports) for barley in the marketplace. As stated 

above, input from industry stakeholders has suggested that there is interest in utilizing 

both spring and winter barley as ethanol feedstock. Further, stakeholders have indicated 

that there is likely to be somewhat more production of ethanol from spring barley than 

from winter barley if this pathway is approved. Therefore, we believe it is important to 

consider the shifting of domestic agriculture in the context of concurrent ethanol 

production from both sources of barley. In the FAPRI-CARD model, as stated above, no 

distinction is made between winter and spring barley. For this reason, the volume in the 

FAPRI-CARD model is simply represented as 140 million gallons of barley ethanol.

The FASOM and FAPRI-CARD models, described above, project how much barley 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 barley case.

D. Barley Ethanol Processing
Based on information submitted by petitioners, we expect dry milling will be the most 

common process for producing ethanol from barley. Therefore this section focuses on a 

lifecycle GHG emissions analysis of several variations of the dry mill process. In the dry 

milling process, the barley is ground and fermented to produce ethanol. The remaining 

components (distillers grains) 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 barley 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 barley ethanol yields of 2.16 gallons (pure 

ethanol) per bushel for dry mill plants (yields represent pure ethanol). 

As per the analysis done in the March 2010 RFS rule, the GHG emission calculation from 

ethanol production needs to account for not only the renewable fuel produced, but also 

any co-products. For barley ethanol production, this analysis accounts for the DG coproduct use directly in the FASOM and FAPRI-CARD agricultural sector modeling 

described above. DGs are considered a replacement animal feed and thus reduce the 

need to make up for the barley 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. 

The barley ethanol process also produces barley hulls. The barley hulls can either be 

processed along with the kernel and end up in the DG, or can be removed and used for 

other purposes. Communications with USDA indicated that general practice is to remove 

barley hulls before the DG enter the feed market. Therefore, our modeling assumed the 

hulls were removed and not used in the DG. We considered cases where the hulls were 

used beneficially as an energy source replacing some of the energy used on-site. Results 

of that analysis are shown below. 

Overall process energy and electricity use for barley ethanol production was based on the 

energy use information for corn ethanol production from the March 2010 RFS rule 

analysis. For the March 2010 RFS 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 March 2010 RFS 

rule RIA Chapter 1. 

The work done on ethanol production for the March 2010 RFS rule was based on 

converting corn to ethanol. Converting barley to ethanol will result in slightly different 

energy use based on differences in the grains and how they are processed. For example, a 

barley plant requires more energy than a corn plant per gallon of ethanol produced since 

the starch / fiber ratio in corn is different than it is in barley. The same ASPEN USDA 

models used for corn ethanol in the final rule were also developed for barley ethanol. 

Based on the numbers from USDA, a barley ethanol plant uses 1.2 times the thermal 
process energy of a corn ethanol plant and 1.3 times the electrical energy per gallon of 

ethanol produced. 

The GHG emissions from production of ethanol from barley were calculated in the same 

way as other fuels analyzed as part of the March 2010 RFS rule. The GHG emissions 

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

barley ethanol plant by emissions factors for combustion of those fuel sources. The 

emission factors for the different fuel types are the same as those used in the March 2010 

RFS 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 March 

2010 RFS rule, which were taken from GREET and represent average U.S. grid 

electricity production emissions. 

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 Barley 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