Document ID: EPA-HQ-OAR-2011-0542-0408
Agency: epa
Document Type: Supporting & Related Material
Title: 
Posted Date: 2012-06-12T04:00Z

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).  

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 co-located 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 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 biogas, 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 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 self-sustainable.  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 (FAPR-CARD) Staff. 2010. Technical Report: An Analysis of EPA Renewable Fuel Scenarios with the FAPRI - CARD International Models. January, 2010. Docket No. EPA-HQ-OAR-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