1

Chapter 6: Impacts on Water 

6.1 Feedstock Production and Water Quality 

As the production and price of corn and other biofuel feedstocks increase, there may be 

substantial impacts to both water quality and water quantity. To analyze these impacts, EPA 

focused on corn production for several reasons. Corn acres have increased dramatically, 20% in 

2007 from 2006, an increase of over 15 million additional corn acres for a total of 93.6 million 

acres. Over two-thirds of the new corn acres came from soybean production. 

Most of the 

remaining acres came from the conversion to corn from cotton. Although corn acres declined to 

87 million acres in 2009 due to strong prices for other commodities including soybeans, total 

corn acres remained the second highest since 1946.1

 There are three major pathways for contaminants to reach water from agricultural lands: 

runoff from the land’s surface, subsurface tile drains, or leaching to ground water. A variety of 

management factors influence the potential for contaminants such as fertilizers, sediment, and 

pesticides to reach water from agricultural lands. These factors include nutrient and pesticide 

application rates and application methods, use of conservation practices and crop rotations by 

farmers, and acreage and intensity of tile drained lands. Additional factors outside an agricultural 

producers control include soil characteristics, climate, and proximity to waterbodies. 

6.1.1 Corn Production and Water Quality 

 The rapid growth in corn acres may have major implications for water quality. Unlike 

soybeans and other legumes, corn needs large amounts of fertilizer, especially nitrogen fertilizer, 

to produce economic yields. Of all current and potential feedstocks for biofuels, corn has the 

greatest application rates of both fertilizer and pesticides per acre and accounts for the largest 

share of nitrogen use among all crops.2

 If fertilizers are applied at rates or times when the corn 

cannot use them, they are available to runoff or leach to water. Corn generally utilizes only 40 to 

60% of applied nitrogen. The remaining nitrogen is available to leave the field and runoff to 

surface waters, leach into ground water, or volatilize to the air where it can return to water 

through depositional processes. Farmers were expected to apply an additional one million tons of 

nitrogen fertilizer to the 2007 corn crop.3

 

 Historically, corn has been grown in rotation with other crops such as wheat, hay, oats, 

and especially soybeans. As corn prices increase relative to prices for other crops, farmers chose 

to grow corn every year (continuous corn). Much of the recent growth in corn acres has come 

from reductions in a corn-soybean rotation to continuous corn. Although the amount of losses of 

nitrogen fertilizers to ground and surface water vary, continuous corn loses significantly more 

nitrogen annually than a corn-soybean rotation.4

 

In 2005, the latest year for which data was 

analyzed, the U.S. average nitrogen fertilization rate for corn was 138 pounds per acre. For 

soybeans the average rate was 16 pounds per acre.5

 

Soybeans fix nitrogen, so they do not require 

as much fertilizer for adequate growth. 
 2

 Continuous corn may have additional impacts on the rates of fertilizer and pesticide use. 

Continuous corn has lower yields per acre than corn grown in rotation. In response, farmers may 

add higher rates of nitrogen fertilizer to try to match yields of corn grown in rotation. 

Alternatively, if farmers maintain fertilization rates with these reduced yields, the amount of 

unused nutrients will increase and eventually be lost to the environment. Growing continuous 

corn also increases population densities of pests such as corn rootworm. Farmers may increase 

use of pesticides to control these pests. Total corn herbicide use may also increase due to the 

additional corn acres, especially for atrazine, the most commonly used herbicide on corn. 

 There are potential toxicity concerns with volatilization of pesticide active ingredients6 in 

addition to concerns with contamination of foods and drinking water. Furthermore, raising 

acreage under corn production will increase the quantity of pesticide products in use. Further 

assessment is necessary to determine whether there is the potential for adverse human health 

effects from any increase in pesticide use associated with increased domestic corn production. 

 The most commonly used types of pesticides associated with corn production and storage 

largely belong to two broad use categories, herbicides and insecticides. The majority of the more 

common corn herbicide products presently on the market contain an organochlorine-type (OC) 

active ingredient (AI). For the most part, OC herbicides inhibit cell division and growth while a 

subgroup of these products, the atrazine-containing OC herbicides, inhibit plant photosynthesis. 

Another type of common corn herbicide, the phosphonoglycene or glyphosate–containing 

organophosphate (OP) herbicides, inhibit protein synthesis in plants. Several of the common corn 

herbicide compounds, such as acetochlor, carbaryl and alachlor, are classified by EPA as known 

or likely human carcinogens and oral exposure to some of these AI compounds at high enough 

levels has resulted in adverse health effects, on organs such as the liver or kidney in animals.7, 8, 9

 

 The majority of common corn insecticides are split fairly evenly between OP- and 

carbamate-type AI compounds, with the top selling corn insecticide products, by sales of AI by 

weight, generally contain methomyl. Methomyl is an N-methyl-carbamide compound which 

inhibits the acetylcholinesterase enzyme, causing neurotoxicity in both insects and humans.10 

Methomyl is classified by EPA as an E/unlikely human carcinogen11 and its use is regulated as a 

compound highly toxic to most aquatic and land animals. 

 High corn prices may encourage farmers to grow corn on land where row crops are not 

currently grown. If land is not in row crop production, it generally is an indication that the land is 

marginal for row crop production though the land may still be used for agriculture, such as 

pasture land. Typically, agricultural producers apply far less fertilizer and pesticide on pasture 

land than land in row crops. Corn yield on these marginal lands will be lower, limiting nutrient 

uptake and causing a higher percentage of nutrients under standard fertilization rates to be 

underutilized and ultimately lost to the environment. However since nitrogen fertilizer prices are 

tied to natural gas prices, fertilizer costs have increased significantly. According to U. S. 

Department of Agriculture (USDA) Economic Research Service (ERS), fertilizer prices have 

been rising steadily since 2002. Through 2008, the annual average prices paid for fertilizers rose 

264%. The annual average prices paid for fertilizers were up 82% in 2008 alone. In 2009, ERS 

predicts that the annual average prices paid for fertilizers will fall 26.5%. In October 2009 
 3

fertilizer prices returned to the December 2007 level, when the run-up in prices started.12 

It is 

unclear how agricultural producers responded to these changes in both corn and fertilizer prices. 

 EPA has no data indicating US farmers will increase their corn fertilization rates in 

response to higher corn prices. However, as demand for corn expands, additional acres panted to 

corn will likely results in increased amounts of fertilizer applied. The USDA National 

Agricultural Statistics Service has announced that it will discontinue its national Agriculture 

Chemical Use reports, collected since 1990, the only survey of its kind. Therefore, it will be very 

difficult to obtain future information on fertilizer and pesticide application rates. 

 Artificial drainage is another important factor in determining the losses of nutrients from 

cropland. Artificial drainage consists either of subsurface tiles/pipes or man-made ditches that 

move water from wet soils to surface waters so crops can be planted. In a few areas, drains 

move water to wells and then groundwater instead of to surface water. Artificial drainage has 

transformed large expanses of historic wetland soils into productive agriculture lands. However, 

the artificial drains or ditches also move nutrients and pesticides more quickly to surface waters 

without any of the attenuation that would occur if these contaminants moved through soils or 

wetlands. The highest proportion of tile drainage occurs in the Upper Mississippi and the OhioTennessee River basins in areas of intensive corn production.13 Manmade ditches predominate 

in areas like the Eastern Shore of the Chesapeake Bay. 

6.1.2 Impact on Farm Bill Conservation Programs 

 The increase in corn production and prices may also have significant impacts on 

conservation programs funded by the USDA. USDA funds a variety of voluntary programs to 

help agricultural producers implement conservation practices on their operations. These 

programs fall into two basic categories: land retirement and working lands. 

 USDA’s largest land retirement program and its largest conservation program is the 

Conservation Reserve Program (CRP). Under CRP farmers receive annual rental payments under 

10- to 15- year contracts to take land out of agricultural production and plant grasses or trees on 

those acres. Generally farmers put land into CRP because it is not as productive and has other 

characteristics that make the cropland more environmentally sensitive, such as high erosion rates. 

The 2008 Farm Bill (Food, Conservation and Energy Act of 2008) lowered the cap on CRP acres 

from 39.2 million acres to 32 million acres. Prior to the passage of the new farm bill, farmers had 

already not renewed their contracts on over two million acres of CRP in response to higher crop 

prices. USDA expects another 4.6 million acres to come out of CRP between 2007 and 2010, 1.4 

million acres in major corn producing states.14 

 CRP acres provide valuable environmental benefits both for water quality and for wildlife 

habitat. CRP is an important component of rare grassland habitats in the Midwest and Great 

Plains.15 CRP payments are based on the average agricultural land rental rates in the area. As 

land values increase due to increase in crop prices, CRP payments are not keeping up with the 

higher land rental rates. Farmland in Iowa increased an average of 18% in 2007 from 2006 

prices.16 Midwestern states, where much of the nation’s corn is grown, tend to have reenrollment 
 4

rates lower than the national average. We note that based on input from USDA, EPA has 

modeled assuming the 32 million acres of eligible CRP land will remain protected. 

 The largest USDA conservation program on working lands is the Environmental Quality 

Incentives Program (EQIP). About $1 billion is given to farmers annually to implement 

conservation practices on their farms. Farmers are paid a percentage of the cost of installing the 

practices, generally ranging from 50 to 90%. Conservation practices encompass a wide range 

that can have a significant impact on pollutants reaching ground or surface water from crop 

production. EQIP cost-shares with farmers for important practices such as nutrient management, 

cover crops, livestock manure storage, and riparian buffers. Like CRP, high corn prices may 

have an impact on the willingness of agricultural producers to participate in EQIP. Producers 

may require higher payments to offset potential loss of profits through implementation of 

conservation practices. 

 The effectiveness of agricultural conservation practices in controlling runoff and/or 

leaching of nutrients, sediment, and pesticides at the field level has been established by 

numerous scientific studies across many geographic areas. However, the usefulness of these 

practices in achieving water quality goals is dependent on their placement within watersheds. To 

most effectively protect water quality, conservation practices should be targeted to the most 

vulnerable areas of watersheds. Conservation practices designed to meet wildlife goals will need 

different targeting mechanisms to ensure adequate habitat. USDA through the Conservation 

Effects Assessment Project (CEAP) is trying to evaluate the effectiveness of controlling 

pollution from agricultural lands at the watershed level.1

 

In order to ensure that Farm Bill 

conservation programs meet their environmental quality goals, the EPA’s Science Advisory 

Board report to the Gulf of Mexico Task Force (SAB) also recommends implementing the 

practices through competitive bidding to ensure that the highest environmental benefit is 

achieved at the least cost.17 It also warns that voluntary programs without economic incentives 

are unlikely to be effective to control nitrogen and phosphorus, except for a few practices. 

 The most cost-effective practices on working lands include: riparian buffers; crop 

rotation; appropriate rate, timing, and method of nutrient application; cover crops; and, on tiledrained lands, treatment wetlands and controlled drainage. These practices have significant water 

pollution reduction benefits that vary based on the site-specific conditions and on the 

implementation and operation and maintenance of the practice. For example, controlled drainage 

can reduce nitrogen loads by 30%; treatment wetlands by 40% to 90%; vegetative buffers by 

12% to 90%. 

6.1.3 Other Agricultural Biofuel Feedstocks 

 While corn is the most common feedstock for biofuel production by far, under this 

proposal, in later years other agricultural feedstocks will become increasingly important. These 

feedstocks will have dramatically different impacts on water quality. Biodiesel feedstocks, 

primarily soybeans, as well as cellulosic feedstock such as switchgrass or popular trees are not 

expected to have significant water quality impacts. As noted previously, soybeans require little to 

no additional nitrogen fertilizer. However, soybeans have less residue remaining after harvest 

 

1 See http://www.nrcs.usda.gov/technical/nri/ceap/index.html 
 5

compared to corn, so sediment runoff could be more of a concern, depending on how each crop 

is managed. Switchgrass may be a more favorable biofuels crop for reducing water impacts. It is 

a native plant which does not require high inputs of fertilizers or pesticides and since it is a 

perennial crop, there is limited sediment runoff compared to annual crops. There is very minimal 

acreage of switchgrass grown commercially at the present time, so it is difficult to predict what 

inputs farmers will use to cultivate it. Some concern has been expressed about the potential in the 

future for farmers to increase switchgrass fertilizer application rates and irrigation rates to 

dramatically increase yields. 

 Corn stover, at the present time, appears to be one of the more viable feedstocks for 

cellulosic ethanol, especially in the Corn Belt states. Corn stover is the above ground stalks, 

husks, and corn cobs that remain once the corn grain is harvested. Farmers keep the corn stover 

on their cropland to maintain the productivity of the soil. Corn stover maintains the soil organic 

carbon which has many benefits as a source of nutrients, preventing erosion by wind and water, 

and increasing soil aeration and water infiltration. Wilhelm, et al.18 

evaluated the amount of corn 

stover that could be harvested for biofuel production and still maintain soil carbon. In all the 

soils they evaluated more stover was needed to maintain the soil carbon than for controlling 

erosion. For a more general discussion of cellulosic ethanol production, see Chapter 5, Section 

V.B.2. More research is needed to identify the amount of stover that can be removed and retain 

these important productivity and environmental benefits. 

 Different conservation systems and conservation practice standards will need to be 

developed and adopted for cellulosic feedstocks, such as corn stover, switchgrass, and trees for 

biofuels production. USDA will need to continue to adjust current standards and develop 

additional standards, where needed, to permit cellulosic feedstocks to be produced and utilized in 

a sustainable manner. 

6.2 Ecological Impacts 

6.2.1 Nutrients 

 Nitrogen and phosphorus enrichment due to human activities is one of the leading 

problems facing our nation’s lakes, reservoirs, and estuaries. Nutrient enrichment is also a 

contributing factor to stream degradation. It has negative impacts on aquatic life in streams; 

adverse health effects on humans and domestic animals; aesthetic and recreational use 

impairment; and excessive nutrient input into downstream waterbodies, such as lakes. Excess 

nutrients in streams can lead to excessive growth of phytoplankton (free-floating algae) in slowmoving rivers, periphyton (algae attached to a surface) in shallow streams, and macrophytes 

(aquatic plants large enough to be visible to the naked eye) in all waters. Unsightly filamentous 

algae can impair the aesthetic enjoyment of streams. In more extreme situations, excessive 

growth of aquatic plants can slow water flow in flat streams and canals, interfere with 

swimming, and clog the screens on water intakes of water treatment plants and industries. 

 Nutrient enrichment in streams has also been demonstrated to affect animal communities 

in these waterbodies. For example, declines in invertebrate community structure have been 
 6

correlated directly with increases in phosphorus concentration. High concentrations of nitrogen 

in the form of ammonia are known to be toxic to aquatic animals. Excessive levels of algae have 

also been shown to be damaging to invertebrates. Finally, fish and invertebrates will experience 

growth problems and can even die if either oxygen is depleted or pH increases are severe; both 

of these conditions are symptomatic of eutrophication. As a biologic system becomes more 

enriched by nutrients, different species of algae may spread and species composition can shift; 

however, unless such species shifts cause clearly demonstrable symptoms of poor water 

quality—such as fish kills, toxic algae, or very long streamers of filamentous algae—the general 

public is unlikely to be aware of this potential ecological concern. 

 Nutrient pollution is widespread. The most widely known examples of significant 

nutrient impacts include the Gulf of Mexico and the Chesapeake Bay. For these two areas alone, 

there are 35 states that contribute the nutrient loadings. There are also known impacts in over 80 

estuaries/bays, and thousands of rivers, streams, and lakes. The significance of these impacts has 

led EPA, States, and the public to come together to place an unprecedented priority on public 

partnerships, collaboration, better science, and improved tools to reduce nutrient pollution. 

 Virtually every state and territory is impacted by nutrient-related degradation of our 

waterways. All but one state and two territories have waterbodies that are polluted by nutrients. 

States have listed over 10,000 waterbodies that have nutrient and nutrient-related impairments. 

Fifteen states have more than 200 nutrient-impaired waterbodies each. Reducing nutrient 

pollution is a priority for EPA. 

 EPA’s Wadeable Streams Assessment provided the first statistically defensible summary 

of the condition of the nation’s streams and small rivers.19 To perform the assessment, EPA, 

states, and tribes collected chemical, physical, and biological data at 1,392 perennial stream 

locations to determine the biological condition of these waters and the primary stressors affecting 

their quality. Research teams collected samples at sites chosen using a statistical design to ensure 

representative results. The results of the analysis provide a clear assessment of the biological 

quality of wadeable, perennial streams and rivers across the country. 

 The Wadeable Streams Assessment found that excess total nitrogen is the most pervasive 

biological stressor for the nation. Approximately 32% of the nation’s stream length shows high 

concentrations of nitrogen compared to reference conditions. Phosphorus exhibits comparable 

patterns to nitrogen and is the second most-pervasive stressor for the nation’s stream length. 

Streams with relatively high concentrations of nutrients or excess streambed sediments are two 

to four times more likely to exhibit poor biological conditions. 

 The National Water Quality Inventory: Report to Congress, prepared under section 

305(b) of the Clean Water Act, summarizes water quality reports submitted by the states and 

territories to EPA. Historically, the National Water Quality Inventories have repeatedly shown 

that nutrients are a major cause of ambient water quality use impairments. In the most recent 

report summarizing the 2002 reports from state, nutrients are identified as the leading cause of 

water pollution in assessed lakes and the second leading cause of pollution in assessed estuaries 

and bays.20 

Sediment is the leading cause of pollution in assessed rivers and streams. Agriculture 
 7

is the largest known source of water quality impairment to both assessed rivers and streams and 

lakes and reservoirs. 

6.2.2 Air Deposition of Nitrogen to Water 

 Nitrogen oxide (NOx) emissions from fossil fuel combustion from both stationary 

sources and vehicles can add to the load of nitrogen to waterbodies around the country. 

Depending on climate and other variables, the atmospheric NOx falls back to the ground as rain, 

snow, fog, or dry deposition. NOx is deposited directly on waterbodies or falls on the land and 

can run off to waterbodies. NOx from both stationary sources and vehicles results in significant 

loadings of nitrogen from air deposition to waterbodies around the country21, including the 

Chesapeake Bay22, Long Island Sound23, and Lake Tahoe.24 The majority of the new biofuel 

production facilities are expected to be located in the Corn Belt in the Mississippi River Basin, 

therefore the NOx emissions will add to the nutrient loads to local water bodies and the Gulf of 

Mexico. Much of the nitrogen deposition from vehicles falls on impervious surfaces, such as 

roads and parking lots where it runs off into streams. Road drainage systems generally channel 

runoff quickly and accelerate the nitrogen loadings downstream. In the Chesapeake region, 

vehicle exhaust remains the single largest source of fossil-fuel derived nitrogen pollution.25 Air 

deposition of nitrogen accounts for more than half of all nitrogen loadings to Lake Tahoe.26

6.3 Gulf of Mexico 

 Production of corn for ethanol may exacerbate existing serious water quality problems in 

the Gulf of Mexico. Nitrogen fertilizer applications to corn are already the major source of total 

nitrogen loadings to the Mississippi River.27 A large area of low oxygen, or hypoxia, forms in the 

Gulf of Mexico every year, often called the “dead zone”. Hypoxia threatens commercial and 

recreational fisheries in the Gulf because fish and other aquatic species cannot live in the low 

oxygen waters. The primary cause of the hypoxia is excess nutrients (nitrogen and phosphorus) 

from the Upper Midwest flowing into the Mississippi River to the Gulf. These nutrients trigger 

excessive algal growth (or eutrophication) resulting in reduced sunlight, loss of aquatic habitat, 

and a decrease in oxygen dissolved in the water. 

 The 2008 hypoxic zone was measured at 8,000 square miles, the second largest since 

measurements began in 1985 and an area the size of Massachusetts.28 In 2009 models predicted 

an even larger hypoxic zone, but it was measured at only 3,000 square miles. A combination of 

below average high flows on the Mississippi River and winds that mixed Gulf waters are the 

likely causes of the reduced size of the 2009 zone. The average size of the hypoxic zone over the 

past five years has been 6,600 square miles. 

 The Mississippi River/Gulf of Mexico Watershed Nutrient Task Force’s “Gulf Hypoxia 

Action Plan 2008” lays out two major goals for reducing water quality problems in the 

Mississippi River/Atchafalaya River Basin: 1) reduce the five-year running average areal extent 

of the Gulf of Mexico hypoxic zone to 2,000 square miles by 2015 and 2) implement nutrient 

and sediment reductions to protect public health and aquatic life and reduce negative impacts of 

water pollution. The Gulf of Mexico Action Plan calls for an acceleration of actions to reduce the 
 8

hypoxia in the Gulf. In order to meet these goals, the Action Plan calls for a 45% reduction in 

both nitrogen and phosphorus reaching the Gulf.29 EPA’s Science Advisory Board (SAB) report 

to the Task Force said that an additional reduction in nitrogen and phosphorus reduction will be 

necessary as a result of increased corn production for ethanol and climate change impacts.30 The 

SAB also found that the Gulf of Mexico ecosystem appeared to have undergone a shift so that 

now the system is more sensitive to nutrient inputs than in the past, inducing a larger response in 

hypoxia. 

 Under the Gulf Hypoxia Action Plan, “USDA will encourage the increased use of its 

nutrient management standard to minimize nutrient loss from fields to help alleviate the impact 

of increased biofuels production on nutrient loads to the Gulf”.31 The nutrient management 

standard requires farmers to account for all plant-available nutrient sources immediately 

available or rendered available throughout the crop production cycle. 

6.3.1 Nutrient Loads to the Gulf of Mexico 

 The U.S. Geological Survey (USGS) has estimated that the spring delivery of nutrients to 

the Gulf of Mexico in 2008 was among the highest since the early 1980s. Spring nutrient 

delivery is one of the main factors that control the size of the hypoxic zone. In relation to the 

long-term spring average, total nitrogen was about 35 to 40% higher (817,000 tons) and total 

phosphorus was a record 60 to 85% higher (83,000 tons). The large nutrient contributions are 

primarily due to near record-breaking streamflows in spring 2008 in the Mississippi River Basin. 

Streamflows were about 50% higher this year compared to the long-term spring average flows 

since about 1980. Nutrient contributions for a given spring vary depending on the amount of 

flow in the Mississippi-Atchafalaya River Basin, as well as average stream water nutrient 

concentrations. 

 Alexander, et al. modeled the sources of nutrient loadings to the Gulf of Mexico using the 

USGS SPARROW (spatially referenced regression on watershed attributes) model.32 

They 

estimated that agricultural sources contribute more than 70% of the delivered nitrogen and 

phosphorus. Corn and soybean production alone accounted for 52% of the total nitrogen delivery 

to the Gulf. Atmospheric deposition was the second largest nitrogen source at 16%. Animal 

manure on pasture and rangeland are the main sources of phosphorus loadings, contributing 

37%. Corn and soybean contributed 25% of the phosphorus; other crops 18%, and urban areas, 

12%. 

6.3.2 Recent Analyses of Impact of Corn Ethanol Production on Nutrient Loadings to the 

Gulf 

 Since over 80% of corn grown in the U.S. is produced in the Gulf of Mexico watershed, 

concern has been expressed about the impact on Gulf hypoxia of increasing corn production for 

ethanol. Several recent scientific reports have estimated the water quality impact of that increase 

in corn production. Donner and Kucharik modeled increases in nitrogen export to the Gulf as a 

result of corn ethanol volumes increasing from 2007 production levels to 15 billion gallons in 

2022.33 

They concluded that the expansion of corn-based ethanol production could make it 

almost impossible to meet the Gulf of Mexico nitrogen reduction goals without “radical shift” in 
 9

feed production, livestock diet, and management of agricultural lands. The study estimated a 

mean dissolved inorganic nitrogen load increase of 10 to18% from 2007 to 2022 to meet the 15 

billion gallon corn ethanol goal, depending on the rate of corn yield increases and potential 

efficiency increases in the conversion of corn to ethanol. 

 EPA’s Science Advisory Board (SAB) report to the Mississippi River/Gulf of Mexico 

Watershed Task Force estimated the additional annual nitrogen loadings to the Gulf due to the 

increase in corn acres from 78.3 million acres in 2006 to 93.7 million acres in 2013.34 

The SAB 

estimated that this scenario will result in an additional national annual loading of almost 300 

million pounds of nitrogen. An estimated 80% of that nitrogen loading or 238 million pounds 

will occur in the Mississippi-Atchafalaya River basin and contribute nitrogen to the “dead zone” 

in the Gulf of Mexico. 

 

6.4 Upper Mississippi River Basin Analysis 

 To provide a quantitative estimate of the impact of this regulation and production of corn 

ethanol generally on water quality, EPA conducted an analysis that focused on agricultural 

production in the Upper Mississippi River Basin (UMRB). The UMRB drains approximately 

189,000 square miles, including large parts of the states of Illinois, Iowa, Minnesota, Missouri, 

and Wisconsin. Small portions of Indiana, Michigan, and South Dakota are also within the basin. 

EPA selected the UMRB because it is representative of the many potential issues associated with 

ethanol production, including its connection to major water quality concerns such as Gulf of 

Mexico hypoxia, large corn production, and numerous ethanol production plants. 

 In 2007, there were approximately 23.7 million acres of corn in the UMRB. About 75% 

of ethanol production is expected to be in the states in the Corn Belt region, of which the UMRB 

is a part.35 Additional discussion about corn production can be found in Section 1.5.1. On 

average the UMRB contributes about 39% of the total nitrogen loads and 26% of the phosphorus 

loads to the Gulf of Mexico.36 The Ohio/Tennessee River Basin is the highest contributor of 

nitrogen loads to the Gulf at 41%. The high percentage of nitrogen from these two basins is 

primarily due to the large inputs of fertilizer for agriculture and the extensive systems of tile 

drains. According to USGS, nitrogen loads to the Gulf ranged from 810,000 metric tons to 2.2 

million metric tons between 1985 and 2005. Phosphorus loads to the Gulf ranged from 80,700 

metric tons to 180,000 metric tons during that same 20-year period.37 Although nitrogen inputs to 

the UMRB in recent years is fairly level, there is a 21% decline in loads to the Gulf. The Science 

Advisory Board report attributes this decline to higher amount of nitrogen removed during 

harvest, due to higher crop yields.38 However, most of the reduction in the spring was from 

nitrogen forms other than nitrate. Nitrate is an important nitrogen form fueling the algal growth 

which leads to hypoxia.39 

For the same period phosphorus inputs increased 12%. 

 In 2007, the U.S. produced approximately seven billion gallons of ethanol, mostly from 

corn kernels. Corn-based ethanol production is expected to reach at least 15 billion gallons in 

order for industry to comply with the RFS2 standards. Of the potential crops for biofuels 

production, corn has the highest rates of fertilizer and pesticide application, leading to the 
 10

concern that higher corn production will result in increased loading of nutrients, pesticides, and 

sediment to water bodies, including major rivers and estuaries. 

6.4.1 SWAT Model 

 EPA selected the SWAT (Soil and Water Assessment Tool) model to assess nutrient 

loads from changes in agricultural production in the UMRB. Models are the primary tool that can 

be used to predict future impacts based on alternative scenarios. SWAT is a physical process 

model developed to quantify the impact of land management practices in large, complex 

watersheds. SWAT, primarily developed by USDA’s Agricultural Research Service and the 

Texas A&M University Blackland Research and Extension Center, is a public domain model. 

 EPA determined that SWAT was the most appropriate model to use for this analysis 

because it has been widely used and validated in watersheds both nationally and 

internationally.40 

SWAT has been applied extensively to support water quality and Total 

Maximum Daily Load (TMDL) planning throughout the United States. SWAT is a basin-scale 

continuous simulation model that operates on a daily time step and is designed to predict the 

nonpoint source loadings and resulting water quality impacts of water, sediment, and agricultural 

chemicals (nutrients and pesticides) from a watershed. The model can assess a wide variety of 

impacts of alternative management practices and land use changes. The model is physically 

based, computationally efficient, and capable of continuous simulations over long periods of 

time, ranging from days to years to decades. Major model components include weather, 

hydrology, erosion/sedimentation, soil temperature, plant growth, nutrients, pesticides, bacteria, 

agricultural management, stream routing and pond/reservoir routing. 

 SWAT has several very important strengths that enabled EPA to develop a robust 

representation of the hydrology and water quality of the UMRB: 

1) Watersheds can be modeled to evaluate the relative impact of changes in management 

practices, climate, and vegetation on water quality or other variables of interest; 

2) SWAT uses readily available inputs commonly available from various government 

agencies; 

3) It can simulate crop and plant communities and provide crop yield and plant biomass, 

essential to estimate past trends and project accurately into the future; 

4) Simulation of very large basins or a variety of management strategies can be 

performed expeditiously; 

5) Long-term impacts spanning several decades can be studied. Time- and climatevariable pollutant contributions can be simulated along with the impact on downstream 

water bodies spanning several decades; and 

6) The model code has been validated on hundreds of basins throughout the United States 

and abroad. 
 11

 In addition, prior applications of SWAT for hydrology and nutrient simulation in the 

UMRB had been completed and were available as a starting foundation for the modeling efforts 

and focus of this study.41 42 

Further technical information regarding SWAT can be found at: 

http://www.brc.tamus.edu/swat. 

6.4.1.1 Base Case 

In order to assess alternative potential future conditions within the UMRB, such as 

alternative levels of increased corn production as feedstock for ethanol, we had to establish 

baseline conditions for SWAT. EPA developed a SWAT model of a base case to which the 

results of the RFS1 mandate reference case, AEO2007 reference case, and RFS2 control cases 

could be compared. As in the NPRM, we selected 2005 as the mid-point of the target period for 

baseline conditions in the watershed. However, for the analysis for this final rule, we used the 

2007 corn yield value to correspond with the agricultural analysis described in Chapter 5. We 

assumed that 33% of corn produced in the UMRB was converted to corn ethanol, based on 

estimates from USDA.43 This baseline does not include corn ethanol produced as predicted by 

AEO2007 through 2022 nor the increment over that as a result of this rulemaking. 

 

 Like most water quality modeling, we had to use a range of data sets for the base case 

scenario inputs. In developing this scenario, it was necessary to select a target year, or window of 

years, that represent the conditions on the watershed. For this study the year 2005 was selected as 

the target period for baseline conditions. As with most models of this scale, it was not possible to 

have all of the data sources come from the exact same time period. It is a common modeling 

practice to combine the best available data sources for model development in an attempt to 

characterize the baseline condition within a short time window or period. The majority of the 

data sources were from the years 2000 through 2006. In addition, selected assumptions about the 

baseline were made using 2007 as the reference year. In particular, the baseline value for average 

corn yield (144.2 bushels per acre) was based on the year 2007. In reality, the base case 

represents watershed conditions within a two to three year period. 

 Since one of the driving forces in the SWAT model is the water balance, climate data is 

key to accurately predicting the movement of nutrients and sediment. SWAT was applied (i.e. 

calibrated) to the UMRB using weather data from the NRCS climatic data center for a 40-year 

period from 1960 to 2001 and flow and water quality data from 13 USGS gauges on the 

mainstem of the Mississippi River, spatially distributed from the upper reaches in Minnesota and 

Wisconsin to the UMRB outlet below Grafton, Illinois. In addition, the weather data has been 

spatially interpolated to assign one weather station per subwatershed. 

 To establish the land use for the baseline scenario, SWAT was setup on 131 

subwatersheds [8-digit Hydrologic Unit Code (HUC)] for the entire UMRB using the 2001 

National Land Cover Data (NLCD)44 

and Cropland Data Layer (CDL).45 The CDL contains 

crop specific digital data layers, suitable for us in geographic information system applications. 

The CDL program focuses on classifying corn/soybean/rice/cotton agricultural regions in many 

of the Midwestern and Mississippi delta states using remote-sensing imagery and on-the-ground 

monitoring. The USDA-NRCS STATSGO provided the soils data for the entire analyses. The 

primary input data is the USDA 1997 National Resource Inventory (NRI), which provided land 
 12

use, soil, and data on management practices on the land.46 1997 is the most current year for 

which this data is available. 

 In addition, information from the Conservation Tillage Information Center and USDANASS Census of Agriculture 2002/1997 were used to identify the cropping rotation and 

management practices for the agricultural land areas by these same 131 subwatersheds. Based on 

the management information at this level, each sub-watershed was assigned appropriate 

management and tillage practices. 

 Drainage tiles are one of the critical man-made hydrology structures that changes the 

natural hydrological cycle significantly at both surface and subsurface (lateral flow) levels. There 

are no clear records of where the tiles are within the UMRB, other than a few research articles 

that attempted to estimate the location and extent of the tile drainage coverage. In this study, 

similar literature values were used to estimate and identify the areas that have the tile system to 

drain the excess water and nutrients in a timely manner. First, the STATSGO database was used 

to identify the very poorly drained soils, somewhat poorly drained soils, and poorly drained soils. 

Then, slope and land use maps were overlaid on these poorly drained soils to identify the 

potential tile drainage system. Only slopes <1% and agricultural land uses were identified as 

areas that may potentially be served with tile drainage system. 

 The tillage practice information in the UMRB was obtained at the county level from 

Conservation Technology Information Center.47 There are five major tillage types. Three of 

them (no-tillage, ridge-tillage, and mulch-tillage) belong to conservation tillage, and the other 

two types of tillage (reduced-tillage and intensive-tillage) are non-conservation tillage. The 

county acreages of this tillage information were overlaid on 8-digit HUCs to estimate the percent 

of each tillage practices by crop within each HUC. 

 To estimate nutrient applications on cropland, we started by estimating the livestock and 

the amount of manure produced. The livestock numbers came from the agricultural statistics for 

each county based on the 2002 Census of Agriculture for each 8-digit HUC. (Only cattle and 

hogs numbers were used since they are the dominant livestock types in the UMRB.) Then, the 

manure production of each 8-digit HUC was obtained through multiplying the number of cattle 

and hogs and the manure production rates as outlined in ASABE, 2005.48 

If the total amount of 

the manure production exceeded 20% of the estimated total fertilizer application in one HUC, 

manure application and chemical fertilizer application were used as SWAT model inputs to 

simulate nutrient applications in that HUC. The manure was applied to only those areas that are 

agricultural land use, even during rotation. For example, only hay, corn, and row crops get 

manure application, not legume crops such as alfalfa or soybean. So, if an area had a corn and 

soybean rotation, manure was only applied during the corn growing period. Even when manure 

was applied, chemical fertilizer was used to supplement the manure application where and when 

needed. In areas where the manure was not applied, chemical fertilizer was applied to grow the 

agricultural crops. Chemical nitrogen fertilizer at applied at 1.3 times the amount of nitrogen 

taken off at harvest. 

 For the UMRB analysis we used the auto-fertilization feature in SWAT. Any time actual 

plant growth fell below the specified nitrogen stress threshold, the model automatically applied 
 13

fertilizer. The user specifies the type of fertilizer, the fraction of total fertilizer applied to the soil 

surface, the maximum amount of fertilizer that can be applied during the year, the maximum 

amount of fertilizer that can be applied in any one application, and the application efficiency. 

Fertilizer is applied to match the difference between soil available nitrogen and the crop yield 

nitrogen that is removed during harvest. The auto-fertilization used in the UMRB study was set 

up using default parameter values for fertilizer application rate (200 kg N /ha), maximum per 

year fertilization rate (300 kg N /ha), application efficiency (1.3, ratio, unitless), and fraction of 

fertilizer applied to soil surface (0.2). The nitrogen stress factor was set to 0.75 (ratio, unitless). 

 The 42-year SWAT model runs were performed and the results analyzed to establish 

runoff, sediment, nitrogen, and phosphorous loadings from each of the 131 8-digit HUC 

subwatersheds and the larger 4-digit subbasins, along with the total outflow from the UMRB and 

at the various USGS gage sites distributed along the Mississippi River mainstem. These results 

provided the Reference Case model values to which the RFS1 and RFS2 future alternatives are 

compared. 

 The current national average for corn yield of 150 bushels per acre (bu/ac) was used to 

establish baseline yield levels. The baseline average yield for the UMRB was established at 

144.2 bushels per acre. This baseline yield is due to the significant amount of crop area in 

northern states where yield values are lower than the national average. National average corn 

yields have been increasing primarily due to favorable weather conditions and improvement in 

practices to reduce stress on the corn plants from excess water, drought, and pests. 

6.4.1.2 Reference Cases and RFS2 Control Case 

To assess the impacts of the increased use of corn ethanol, we modeled an RFS2 control 

case and compared it to both the AEO2007 reference case and the RFS1 mandate reference case. 

For the AEO200749 reference case we modeled: 10.49 billion gallons a year (BGY) in 2010, 

11.1 BGY in 2015, 11.83 BGY in 2020, and 12.29 BGY in 2022. For the RFS1 mandate 

reference case we modeled a constant national ethanol goal of 7.05 billion gallons a year (BGY) 

starting in 2012. For this analysis, the reference cases assumed that no cellulosic ethanol was 

produced from corn stover. For the RFS2 control case we modeled a steadily increasing volume 

of corn ethanol in keeping with the EISA standards; 11.24 BGY in 2010, 14.79 BGY in 2015, 

and 15 BGY in 2016 and beyond. We were not able to model the impacts of corn stover removal 

at this time, so the analysis only reflects the impacts of increased use of corn grain for renewable 

fuel use. 

 For SWAT analyses of these three scenarios, national corn ethanol volumes were 

adjusted for the UMRB based on a 42.3% ratio of ethanol production capacity within the UMRB 

compared to national capacity. This fraction was determined by overlaying coverage of 

nationwide ethanol plants with a coverage of the UMRB. Production from ethanol plants within 

the study area were totaled and then divided by the nationwide production. Both current 

production and planned expansion were included in the totals. Ethanol location and production 

information were taken from the Renewable Fuels Association table of ethanol refinery locations 

in April 2008.50 

We assumed an average of 2.7 gallons of ethanol per bushed of corn and a 

moisture content of 20% when converting corn grain mass to bushels. The resulting UMRB 
 14

ethanol production goals were converted into the corresponding required corn production 

acreage, i.e. the extent of corn acreage needed to meet those ethanol production goals. 

 The SWAT model was run with the available input climate record, 1960-2001, with the 

model run under conditions of the increased corn production and yields noted above. Separate 

model runs were performed for each of the three projection years, and the model results were 

analyzed to provide loadings for comparison with the baseline loadings. 

6.4.1.2.1 Corn 

Increases in corn yield were built into the future scenarios, with an annual increase of 

1.23%. This produced yield increases to 149.6 bushels per acre (bu/ac) (3.7% in 2010), 159 bu/ac 

(10.3% in 2015), 169 bu/ac (17.2% in 2020), and 173.2 bu/ac (20.1% in 2022). Table 6.4-1 

shows the corn acreage in the Upper Mississippi River Basin for each scenario. Corn acres 

increased 9% in 2022 between the AEO 2007 scenario and the RFS2 (no stover) scenario. 

Table 6.4-1. 

Corn Acres in the Upper Mississippi River Basin for each Scenario in millions of acres 

AE0 2007 RFS1 RFS2 (no stover) 

2010 26.83 23.65 27.61 

2015 26.78 22.78 30.40 

2020 26.80 22.35 29.73 

2022 26.96 22.20 29.40 

6.4.1.2.2 RFS2 (No Stover) Control Case Pollutant Loadings 

Tables 6.4-2 through 6.4-4 compare the model outputs for nitrogen, phosphorus, and 

sediment between the Reference Case and the RFS2 (no stover) Case scenarios for the years 

2010, 2015, 2020, and 2022. Land load is the total amount of nitrogen or phosphorus that 

reaches a stream within the UMRB. The total outflow is the remaining amount measured at the 

outlet of the UMRB at Grafton, Illinois after accounting for in-stream loses due to uptake or 

assimilation. 

These results only estimate loadings from the Upper Mississippi River basin, not the 

entire Mississippi River watershed. As noted earlier, the UMRB contributes about 39% of the 

total nitrogen loads and 26% of total phosphorus loads to the Gulf of Mexico. The decreasing 

nutrient load over time is likely attributable to the increased average corn yield per acre, resulting 

in greater plant uptake of nitrogen and fewer corn acres planted for ethanol production goals in 

this rule. 
 15

Table 6.4-2. 

Average annual nitrogen loads: Comparison of 2007 AEO Reference Case 

to the 2022 RFS2 (No Stover) Case (% difference in parentheses) 

2007 AEO Reference Case RFS2 (No Stover) Case 

Model 

Run 

Total Land Load, 

million lbs 

Total Outflow, 

million lbs 

Total Land Load, 

million lbs 

Total Outflow, 

million lbs 

2010 1948 1470 1944 (-0.21) 1467 (-0.20) 

2015 1911 1441 1946 (1.83) 1469 (1.94) 

2020 1887 1421 1912 (1.32) 1442 (1.48) 

2022 1877 1413 1897 (1.07) 1430 (1.20) 

 Approximately 24 to 25% of nitrogen leaving agricultural fields was either taken up by 

aquatic plants or volatilized before reaching the outlet of the UMRB at Grafton, Illinois. Even 

though much of the nitrogen that is volatilized from streams and rivers and near-coastal waters is 

removed from the total loading to water, it is not necessarily eliminated as an environmental 

concern. Conversion of the nitrate to nitrogen gas through denitrification is generally an 

incomplete chemical process. 5% or more of the nitrogen can be converted to nitrous gas, a 

powerful greenhouse gas that is 300 times the climate-warming potential of carbon dioxide, the 

major greenhouse gas of environmental concern. Thus, a water pollutant becomes an air 

pollutant until it is either captured through biological sequestration or converted fully to 

elemental nitrogen. 

 The scenarios showed an increase in phosphorous loads at a slightly lower percentage 

than nitrogen. 

Table 6.4-3. 

Average annual phosphorus loads: Comparison of 2007 AEO Reference Case 

to the 2022 RFS2 (No Stover) Case (% difference in parentheses)

2007 AEO Reference Case RFS2 (No Stover) Case 

Model 

Run 

Total Land Load, 

million lbs 

Total Outflow, 

million lbs 

Total Land Load, 

million lbs 

Total Outflow, 

million lbs 

2010 180.0 133.8 179.9 (-0.06) 133.7 (-0.07) 

2015 178.2 132.3 179.6 (0.79) 133.6 (0.98) 

2020 177.0 131.3 178.2 (0.68) 132.4 (0.84) 

2022 176.5 130.9 177.6 (0.62) 131.8 (0.69) 

Total sediment outflow showed very little change over all scenarios. This result is 

primarily due to corn stover remaining on the field following harvest and therefore reducing 

sediment transport to water. 
 16

Table 6.4-4. 

Average annual sediment loads: Comparison of 2007 AEO Reference Case 

to the 2022 RFS2 (No Stover) Case (% difference in parentheses) 

 2007 AEO 

Reference Case 

RFS2 (No 

Stover) Case 

Model 

Run 

Total Outflow, 

million tons 

Total Outflow, 

million tons 

2010 6.231 6.232 (0.02) 

2015 6.221 6.233 (0.19) 

2020 6.214 6.224 (0.16) 

2022 6.211 6.220 (0.14) 

6.4.1.2.3 RFS1 Pollutant Loadings 

Tables 6.4-5 through 6.4-7 compare the models outputs for nitrogen, phosphorus, and 

sediment between the RFS1 reference case and the RFS2 (No Stover) Case scenarios for the 

years 2010, 2015, 2020, and 2022. Land load is the total amount of nitrogen or phosphorus that 

reaches a stream within the UMRB. The total outflow is the remaining amount measured at the 

outlet of the UMRB at Grafton, Illinois after accounting for in-stream loses due to uptake or 

assimilation. 

Table 6.4-5. 

Average annual nitrogen loads: Comparison of RFS1 Reference Case 

to the RFS2 (No Stover) Case (% difference in parentheses) 

RFS1 Reference Case RFS2 (No Stover) Case 

Model 

Run 

Total Land Load, 

million lbs 

Total Outflow, 

million lbs 

Total Land Load, 

million lbs 

Total Outflow, 

million lbs 

2010 1878 1414 1944 (3.5) 1467 (3.7) 

2015 1838 1382 1946 (5.8) 1469 (6.3) 

2020 1806 1357 1912 (5.9) 1442 (6.3) 

2022 1794 1347 1897 (5.7) 1430 (6.2) 

Table 6.4-6. 

Average annual phosphorus loads: Comparison of RFS1 Reference Case 

to the RFS2 (No Stover) Case (% difference in parentheses) 

RFS1 Reference Case RFS2 (No Stover) Case 

Model 

Run 

Total Land Load, 

million lbs 

Total Outflow, 

million lbs 

Total Land Load, 

million lbs 

Total Outflow, 

million lbs 

2010 175.6 130.1 179.9 (2.4) 133.7 (2.8) 

2015 173.5 128.4 179.6 (3.5) 133.6 (4.0) 

2020 171.6 126.9 178.2 (3.8) 132.4 (4.3) 

2022 170.8 126.3 177.6 (4.0) 131.8 (4.4) 
 17

Table 6.4-7. 

Average annual sediment loads: Comparison of RFS1 Reference Case 

to the 2022 RFS2 (No Stover) Case (% difference in parentheses) 

 RFS1 Reference 

Case 

RFS2 (No 

Stover) Case 

Model 

Run 

Total Outflow, 

million tons 

Total Outflow, 

million tons 

2010 6.190 6.232 (.07) 

2015 6.187 6.233 (.07) 

2020 6.178 6.224 (.07) 

2022 6.174 6.220 (.07) 

 

6.4.1.2.4 Case Study 

 To evaluate local water quality impacts that are impossible to ascertain at the scale of the 

UMRB, we also modeled the Raccoon River watershed in central Iowa. The criteria for 

choosing this watershed included: percentage of corn area representative of the UMRB, stream 

segments included in EPA’s 303(d) list of impaired waters due to high nutrient levels, 

biorefinery plants, drinking water intakes, and observed streamflow and water quality data. 

Nearly 88% of the watershed is in agriculture. 75% of the watershed produces corn and 

soybeans, mostly in rotation. Hay and other row crops are produced on the remaining agriculture 

land. The city of Des Moines makes up about 8% of the watershed. The state of Iowa has listed 

numerous stream segments of the Raccoon River as impaired. In particular, the two stream 

segments from the confluence of the North and South branches of the Raccoon River to the 

watershed’s outlet were listed in 2006 for having more than 25% of the collected water samples 

exceed the drinking water standard for nitrate. 

 As part of the UMRB and by itself, the Raccoon River has been the focus of numerous 

modeling studies. As a result, there is a substantial amount of observed data throughout the 

watershed, primarily from the U.S. Geological Survey gaging stations. 

 The case study used the same assumptions and scenarios as those used for the UMRB 

analysis. SWAT-simulated streamflow and water quality (total nitrogen and phosphorus, and 

sediment loadings) were calibrated against observed data at both monthly and yearly time steps. 

 As in the UMRB study, nitrogen loads to water increased for the future scenarios, though 

at a greater rate. Future phosphorus loads decreased in the Raccoon River model, where they 

had shown minor increases in the UMRB model. For the Raccoon River, there was a greater 

decrease in sediment load, which is the likely cause for the decrease in phosphorus loadings. As 

with the UMRB model, there was minimal change in streamflow. 
 18

6.4.1.5 Sensitivity Analysis 

Using the existing UMRB SWAT model, a sensitivity analysis was conducted on a 

number of important meteorological and management related factors. The goal was to further 

understand the model characteristics and sensitivities to parameters and input forcing functions 

that control the model response for the key environmental indicators of concern. Scenarios were 

constructed using four factors: fertilization application threshold, corn residue removal, daily air 

temperature, and daily precipitation. The results of the analysis showed that rainfall and 

temperature are the most influential factors for all model outputs: water yield, total nitrogen and 

phosphorus loadings, and sediment loadings. These results underscored the importance of 

representing these two driving factors accurately in hydrologic modeling. Corn residue removal 

noticeably reduced nutrient loading into streams while increasing sediment loads. However, 

since corn residue is the main source of organic nitrogen and phosphorus, the removal of the 

residue leads to the need for higher nutrient inputs in the growing season. The fertilization 

application threshold scenario did not tangibly impact water yield and sediment loading. The 

findings from this study indicated that future climate change could greatly influence water 

availability and pollution from corn cropland. 

6.5 Climate Change Impacts 

 Although climate change is expected to be an important factor in future crop production 

in the Upper Mississippi River Basin, EPA has not modeled the impact of climate change on 

corn yields for a variety of reasons. Climate change requires a long period of observation. Over 

the short time frame reflected in this proposal, precipitation and temperature increases will be 

small and indistinguishable from the natural variability of the climate. 

 Crop yield changes resulting from climate change depend on the atmospheric carbon 

dioxide level, the crop, and the base temperature. Yield also depends on the characteristics of the 

crop relative to the timing of precipitation and of extreme temperature events. All of these 

variables make an estimation of actual climate-induced yield loss very difficult to develop. 

Farmer adaptation may mitigate the effects of climate change on agriculture to some degree. 

Adaptations are influenced by many unpredictable factors, including government policy, prices, 

research and development, and technical assistance. Climate model simulations generally 

indicate that most locations in the upper Midwest will warm more than the global average and 

will receive more precipitation than current – though estimates vary considerably depending on 

the model used and initial conditions. 

6.6 Chesapeake Bay Watershed 

The Chesapeake Bay Commission and others have expressed concerns about the water 

quality impact of increased corn production for ethanol may have on the Chesapeake Bay.51, 52 

The Chesapeake Bay watershed stretches across more than 64,000 square miles, encompassing 

parts of six states--Delaware, Maryland, New York, Pennsylvania, Virginia and West Virginia—

and the entire District of Columbia. The Chesapeake's land-to-water ratio (14:1) is the largest of 
 19

any coastal water body in the world. This is why land use and land management have such 

significant influences on the health of the Bay. In its annual State of the Bay report in 2007, the 

Chesapeake Bay Foundation gave the Bay a score of 28 on a scale where 70 means the Bay is 

“saved” and 100 is pristine. The Foundation said that “the health of the Chesapeake Bay is 

dangerously out of balance”.53 

In 2000, Chesapeake Bay Program partners (states, federal agencies, universities, 

nongovernmental agencies) agreed to reduce nitrogen pollution from an estimated 285 million 

pounds per year to no more than 175 million pounds by 2010. Similarly they pledged to reduce 

phosphorus from about 19 million pounds per year to less than 13 million pounds. While there 

have been steady declines in nitrogen and phosphorus, they have not been adequate to meet the 

established goals. The watershed must essentially quadruple the pace of the Bay cleanup to meet 

the 2010 commitment. To restore water quality in the Bay, all of the basin’s more than 87,000 

farms will need to implement best management practices (BMPs) at levels never before seen in 

this country. The states have committed to implement close to 30 different agricultural BMPs as 

part of their restoration strategies. 

 In May 2009, President Obama issued Executive Order 13508 on Chesapeake Bay 

Restoration and Protection. The order established a Federal Leadership Committee, chaired by 

EPA, and with senior representatives from the departments of Agriculture, Commerce, Defense, 

Homeland Security, Interior, and Transportation. In November 2009, these federal agencies 

released a draft strategy which contains a range of approaches for accelerating cleanup of the 

nation’s largest estuary and its vast watershed.54 The draft strategy calls for increased 

accountability and performance from pollution control, habitat protection and land conservation 

programs at all levels of government, including an expanded use of regulatory authorities to 

address pollution control and additional voluntary and market-based solutions – particularly 

when it comes to habitat protection and land conservation programs. The proposed actions are in 

response to overwhelming scientific evidence that the health of the Chesapeake Bay remains 

exceptionally poor, despite the concerted restoration efforts of the past 25 years. 

Agricultural lands account for nearly a quarter of the watershed, and contribute more 

nutrients to the Bay than any other land use. Agricultural operations produce about 41% of the 

nitrogen and 47% of the phosphorus loads going to the Bay. Agriculture also contributes about 

63% of the Bay’s sediment. Municipal and industrial wastewater treatment plants throughout the 

watershed are responsible for 21% of the total nitrogen pollution and 22% of the total 

phosphorus pollution delivered to the Bay. 

At least 25% and possibly a third of the nitrogen entering the Bay comes from air 

deposition. The principal sources of emissions are power plants, cars and trucks, agriculture, and 

off-road sources such as construction equipment, lawn mowers and aircraft. While population 

increased about 8% during the last decade, vehicle miles traveled rose 26%. More discussion 

about nitrogen oxides emission impacts can be found in Chapter 3.2. 

The Bay watershed receives significant levels of nitrogen oxides and other airborne 

pollutants from its large airshed (which is about six and a half times the size of the watershed), as 
 20

far west as Ohio and Indiana. Air deposition of nitrogen on the land adds to the burden that must 

be dealt with by farmers, local governments and other landowners. 

6.6.1 Agricultural Production Effects 

 Due to the significant acreage within the Chesapeake Bay watershed that is devoted to 

agricultural production (approximately 22%), increases in corn acreage can potentially contribute 

to changes in nutrient loads to the Bay. High demand for corn reflected in record corn prices 

have played a substantial role in encouraging producers to alter their typical crop production 

rotations and crop acreage, contributing to noteworthy changes in crop acreages across the 

watershed. A technical review committee convened by the Chesapeake Bay Commission 

estimated that 300,000 new acres of corn could be added in the Bay watershed in the coming 

years.55 

This new corn acreage could potentially contribute an additional five million pounds of 

nitrogen to the Bay. The Bay Program partners are trying to reach a 90 million pound reduction 

in nitrogen from all sources. However, it is estimated that 17 million pounds of nitrogen could be 

offset if all agriculture acres used cover crops as a conservation practice after harvest. 

 Strong market forces also encourage agricultural operators to increase grain production 

possibly by increasing the conversion of non-row crop acreage (hay, pasture and fallow or idle 

lands) to row crop production. Grain row crops can add more nutrients per acre to the Bay than 

hay and pasture due to production intensity, management systems, and nutrient efficiency of the 

crop. 

6.6.1.1 Base Analysis Assumptions 

 The Chesapeake Bay Program Watershed Model Phase 4.3 (CBWM) and Vortex were 

utilized in the analysis of potential shifts in nutrient loading to the Bay based on reported 

changes to agricultural crop production from 2005 to 2008. These agricultural production 

changes are partially the result of the rapid expansion of biofuel production within the United 

States, supported by market-driven commodity price increases, government policies, or a 

combination of both. The CBWM is a dynamic watershed model used to characterize nutrient 

and sediment loads, and changes in these loads, due to management actions for decision 

support.2

.

 

In developing the agricultural production trend analysis within the Chesapeake Bay 

watershed, the USDA’s National Agricultural Statistics Service’s (NASS) 2007 and 2008 

Projected Plantings report on reported crop acreages was modified to target only the Bay 

watershed. 

6.6.1.2 Corn Production Analysis 

 Analyzing corn production acreage figures for the period from 2005 to 2008 from the 

NASS 2007 and 2008 Projected Planting reports, a measurable upward trend was evident for 

corn acreage plantings across the Bay watershed over the analysis period. This upward trend 

 

2

 For more information on the CBWM see http://www.chesapeakebay.net/model.htm
 21

increased sharply between 2006 and 2007 and decreased for the 2007 and 2008 period. Despite 

the recent downward trend, total corn acreage increased over the analysis period by almost 

66,000 acres. 

6.6.1.3 Corn Nutrient Load Analysis 

Employing a modeled analysis of the USDA-NASS Prospective Plantings report using 

the Chesapeake Bay Watershed Model Version 4.3 and Vortex, considerable increases of 

potential nitrogen loads to the Bay are associated with increased corn acreage. The decrease of 

corn acreage in the 2007 to 2008 period does not offset the total increase in acreage and nitrogen 

yields between 2005 and 2008. Total nitrogen loads increased by almost 2.4 million pounds. 

6.6.1.4 Land Use Conversion Analysis 

 The agricultural production trends between 2005 and the present not only indicate an 

overall increase in the number of acres under corn production, but also an increase in the total 

acres of land under row crop production by over 355,000 acres. Since agricultural land uses 

within the Chesapeake Bay watershed are continuously decreasing due to urban development, 

the increase in row crop acreage may come at the expense of other cropping systems, or 

agricultural land uses such as hay, pasture or idle lands. 

6.6.1.5 Land Use Conversion Nitrogen Load Analysis 

 The USDA-NASS Prospective Plantings reports and the Chesapeake Bay Program 

Watershed Model indicate a continuous total conversion of non-row crop agricultural lands over 

the period from 2005 to 2008 to more intensive row crop production. The non-row crop land 

uses typically produce less nitrogen yields to the Bay, thus additional acres converted to grain 

production can also increase nitrogen loads significantly. This analysis estimates that nitrogen 

loads increase by 8.8 million pounds. 

 If time and resources allow, the Chesapeake Bay Program proposes to analyze the 

potential impacts within the Chesapeake Bay watershed of the implementation of the RFS2 for 

the FRM using available systems and models at our disposal. The models that would potentially 

be used in the analysis would include Phase 5.2 of the Chesapeake Bay Watershed Model 

(CBWM), the Nutrient and Sediment Scenario Builder (NSSB), the Chesapeake Bay Estuarine 

Water Quality Sediment Transport Model (CBEWQSTM) and the Chesapeake Bay Land Change 

Model (CBLCM). The CBWM is a dynamic watershed model used to characterize nutrient and 

sediment loads, and changes in these loads, due to management actions for decision support. The 

NSSB is being developed to determine nutrient and sediment loads under multiple land uses and 

crop types with variable organic and inorganic nutrient inputs. The CBEWQSTM determines the 

effects of nutrient and sediment load changes to the attainment of water quality standards. The 

CBLCM simulates changes in land use as a result of locally projected increases in population out 

to the year 2030. 
 22

 The scope of the analysis is proposed to include incremental and delivered nitrogen, 

phosphorus and sediment to the Chesapeake Bay, and the effect of management changes to the 

attainment of water quality standards. 

6.7 Ethanol Production and Distribution 

 Under the Clean Water Act, all point sources of pollution, including ethanol plants, must 

have a permit to discharge to water bodies or to municipal wastewater treatment plants for both 

industrial process water and stormwater. The permit regulates the amount of pollutants that can 

be discharged. There are three principle sources of discharges to water from ethanol plants: reject 

water from water purification, cooling water blowdown, and off-batch ethanol. 

6.7.1 Water Discharges 

 Water is required at ethanol facilities for processing and for the production of steam that 

is typically used in biomass pretreatment and ethanol distillation processes. An ethanol plant’s 

wastewater is typically comprised of cooling tower blowdown, boiler blowdown, and water 

softener discharge. The majority of the process water is lost as steam in the distillation process. 

In addition, stormwater runoff from the facility may be contaminated from precipitation (rain or 

snow) coming in contact with plant operations (industrial plant yards, material and waste 

handling, storage areas, shipping and receiving areas, residuals sites) and requires adequate 

control and management.56

 While some ethanol facilities get their process water from municipal water supplies, most 

use on-site wells to produce the process water for the ethanol process. Most groundwater sources 

are not suitable for process water because of their mineral content. Therefore, the water must be 

treated for use in ethanol production. The most common method of groundwater treatment is 

reverse osmosis. Reverse osmosis uses specialized filtration and pressure to produce pure water 

while concentrating the groundwater minerals into reject water. The minerals in the reject water 

are site-specific, but they can include: calcium carbonate, magnesium carbonate, sulfate, iron, 

and sodium. For every two gallons of pure water produced, about a gallon of brine is discharged 

as reject water. Most estimates of water consumption in ethanol production are based on the use 

of clean process water and neglect the water discharged as reject water. 

 The largest source of wastewater discharge is reverse osmosis reject water from process 

water purification. The reverse osmosis process concentrates groundwater minerals to levels 

where they can have water quality impacts. The concentrated minerals can show toxicity due to 

osmotic concentration and the presence of some ions such as sulfate or copper. There is really no 

means of “treating” these ions to reduce toxicity, other than further concentration and disposal, 

or use of in-stream dilution. Some facilities have had to construct long pipelines to get access to 

dilution so they can meet water quality standards. 

 Ethanol plants also discharge cooling water blowdown, where some cooling water is 

discharged to avoid the buildup of minerals in the cooling system. These brines are similar to the 

reject water described above. In addition, if off-batch ethanol product or process water is 
 23

discharged, the waste stream can have high Biochemical Oxygen Demand (BOD) levels. BOD 

directly affects the amount of dissolved oxygen in rivers and streams. The greater the BOD, the 

more rapidly oxygen is depleted in the stream. This means less oxygen is available to higher 

forms of aquatic life. The consequences of high BOD are the same as those for low dissolved 

oxygen: aquatic organisms become stressed, suffocate, and die. 

. 

 Ethanol production facilities are important transportation hubs. For instance, a facility in 

Iowa produces about 130 million gallons of ethanol in a year. On an average workday, 175 

tractor-trailers bring in corn, ethanol goes out in 12 rail tankers, and 8 rail cars are filled with 

dried distillers grain to be used as animal feed. This intensity of vehicle travel can have local 

water impacts from stormwater runoff, spills, etc. similar to any other rail and trucking terminal. 

6.7.2 Water Use 

 Older generation production facilities used 4-6 gallons of process water to produce a 

gallon of ethanol, but newer facilities use less than 3 gallons of water in the production process. 

Most of this water savings is gained through improved recycling of water and heat in the process: 

the conservation of heat energy and water go hand-in-hand. This energy savings is a key 

economic advantage for newer plants. A gallon of ethanol contains about 70,000 Kcal of energy. 

Older plants used 35-40,000 Kcal of energy to produce a gallon of ethanol, but newer facilities 

use only 25-28,000 Kcal per gallon. 

 The abundance or lack of water supply is a local issue, and there have been concerns with 

water consumption as new plants go online. Some facilities are tapping into deeper aquifers as a 

source of water. These deeper water resources tend to contain higher levels of minerals and this 

can further increase the concentration of minerals in reverse osmosis reject water. 

6.7.3 Distillers Grain with Solubles 

 One important co-product of ethanol production is distillers grain with solubles (DGS). 

Due to the increase in ethanol production and the price of corn, DGS has become an increasing 

important feed component for confined livestock. About one-third of the corn processed into 

ethanol is converted into DGS. Therefore approximately 45 million tons of DGS will be 

produced for the 15 billion gallons of corn ethanol produced by 2015. Concerns have been raised 

about the relatively higher phosphorus content of DGS compared to traditional feeds. 

 Livestock producers may partially replace corn or other feeds with DGS for both 

economic and production reasons. Different livestock species can tolerate varying amounts of 

DGS in their diets. The majority of DGS are fed to beef and dairy cows. Current 

recommendations allow beef and dairy cows diets to include from 15 to 40% DGS. 

Recommendations for poultry and swine diets are generally less than 15% DGS. Although 

specific analysis of DGS can vary between ethanol plants, compared to corn, DGS are higher in 

crude protein (nitrogen) and three to four times higher in phosphorus.57 

 The increase in nitrogen and phosphorus from DGS in livestock feed has potential 

implications for water quality. When nitrogen and phosphorus are fed in excess of the animal’s 
 24

needs, these nutrients are excreted in the manure. Most livestock manure is applied to crops, 

especially corn, as a source of nutrients. When manure is applied at rates above the nutrient 

needs of the crop or at times the crop can not use the nutrients, the nitrogen and phosphorus can 

runoff to surface waters or leach or ground waters. Excess nutrients from manure nutrients have 

the same impact on water quality as excess nutrients from other sources. 

 

 Livestock producers can limit the potential pollution from manure applications to crops 

through a variety of techniques. USDA’s Natural Resources Conservation Service (NRCS) has 

developed a standard for a comprehensive nutrient management plan (CNMP) to address the 

issue of proper use of livestock manure.58 Agricultural producers who use manure should test the 

nitrogen and phosphorus content before application of the manure. Due to the substantially 

higher phosphorus content of manure from livestock fed DGS, producers will potentially need 

significantly more acres to apply the manure so that phosphorus will not be applied at rates 

above the needs of the crops. This is a particularly important concern in areas where 

concentrated livestock production already produces more phosphorus in the manure than can be 

taken up by crops or pasture land in the vicinity. 

6.7.4 Water Quality Impact from Ethanol Leaks and Spills 

 The potential for exposure to fuel components and/or additives can occur when 

underground fuel storage tanks leak fuel into ground water that is used for drinking water 

supplies or when spills occur from above ground tanks or distribution systems that contaminate 

surface drinking water supplies or surface waters. Additionally, in surface waters, rapid 

biodegradation of ethanol can result in depletion of dissolved oxygen with potential mortality to 

aquatic life. 

Regarding leaks or spills and drinking water impacts, ethanol biodegrades quickly and is 

not necessarily the pollutant of greatest concern in these situations. Instead, ethanol’s high 

biodegradability shifts the subsurface geochemistry, which can cause reduced biodegradation of 

benzene, toluene, and xylene (up to 50% for toluene and 95% for benzene).59 The plume of 

BTEX (benzene, toluene, ethylbenzene and xylenes) compounds in gasoline from a fuel spill can 

extend as much as 70% farther in groundwater and can persist longer, thereby increasing 

potential human exposures to these compounds.60 

 Particularly large plumes of benzene can be 

expected when: there is a large area of the aquifer that is contaminated with liquid phase 

gasoline; the background concentration of sulfate-reducing bacteria (which biodegrade ethanol 

and benzene) in the ground water is low; the rate of ethanol biodegradation is low; and the flow 

velocity of the ground water is high. More detail on ethanol biodegradation and a summary of 

laboratory and field studies of ethanol spills will be forthcoming in the EPAct 2005 Report to 

Congress on Fuel Additive Replacements for MTBE in 2010. 

Ethanol leak and spills from the approximately 600,000 gas stations in the U.S, could 

have a significant impact on water quality and drinking water supplies. Urban areas, that rely on 

ground water for drinking water would be affected most, especially where are existing water 

shortages 
 25

 With the increasing use of ethanol in the fuel supply nationwide, it is important to 

understand the impact of ethanol on the existing tank infrastructure. Federal regulations require 

that underground storage tank (UST) systems be compatible with the fuel stored. Because much 

of the current underground storage tank equipment was designed and tested for use with 

petroleum fuels, there may be many UST systems currently in use that contain materials that are 

incompatible with ethanol blends greater than 10%. Combined with the fact that ethanol is more 

corrosive than petroleum, there is concern regarding the increased potential for leaks from 

existing distribution systems, terminals and gas stations and subsequent impacts on water 

supplies. Given the practical challenges of determining the age and materials of underground 

storage equipment at approximately 233,000 federally regulated facilities, it may be difficult or 

impossible to confirm the compatibility of current underground storage tanks and other tankrelated hardware with ethanol blends. Further discussion of challenges in retail distribution are 

discussed in Section 1.6 of the RIA. 

In 2007, there were 7,500 reported releases from underground storage tanks. Since 

approximately 50% of the gasoline used in the U.S. contains ethanol, approximately 3,750 of 

those releases likely contained some amount of ethanol. Therefore, EPA is undertaking analyses 

designed to assess the potential impacts of ethanol blends on tank infrastructure and leak 

detection systems and determine the resulting water quality impacts. 

 An additional hazard from spills from fuels containing ethanol is risk of potential 

explosions. Laboratory and field studies have found biodegradation of ethanol can produce 

concentrations of methane in excess of the water solubility of methane (i.e., more methane was 

produced than could be dissolved by the available water). This methane could bubble out of the 

ground water and enter the soil gas at explosive concentrations, although it is not possible to 

quantify the risk at this time. EPA is beginning development of modeling software for the 

assessment of fuels of varying composition on ground water, with simulation of methane 

production being one component of this work. 

6.8 Water Use and Wastewater from Biodiesel Plants 

 Biodiesel plants use much less water than ethanol plants in production of biofuel. Water 

is not used in conversion of oil to biodiesel, but is used for washing impurities from the finished 

product. Water use is variable, but is usually less than one gallon of water for each gallon of 

biodiesel produced. Larger well-designed plants use water more sparingly, while smaller 

producers and hobbyists use more water. Some facilities recycle washwater, which reduces water 

consumption. 

 The strength of process wastewater from biodiesel plants is highly variable. Most 

production processes produce washwater that has very high BOD levels. Essentially the strength 

of the wastewater is based on glycerin and methanol content. Larger facilities are segregating 

glycerin as a side product and have efficient methanol recovery, while smaller plants are more 

likely to dispose of glycerin, excess methanol, and washwater as a single waste stream. Crude 

glycerin is an important side product from the biodiesel process and has many uses. It is about 

10% of the final product. Although there is a commercial market for glycerin, the rapid 
 26

development of the biodiesel industry has caused a glut of glycerin production and many 

facilities dispose of glycerin. 

 The high strength of these wastes can overload and disrupt the biological processes in 

municipal treatment plants. The normal wastewater going into a municipal sewage treatment 

plant has a BOD 200mg/l. Washwater from the biodiesel process with efficient recovery of 

methanol, containing small amounts of glycerin, can have a BOD of 10,000 – 15,000 mg/L. Pure 

glycerin has a BOD of nearly 1,000,000 mg/L. There have been several cases of wastewater 

treatment plant upsets due to these shock loadings from releases of glycerin from biodiesel 

production facilities. Unfortunately, these have been due to slug loadings to small wastewater 

treatment plants. Other states such as Illinois and Alabama have also had problems with 

discharges from small biodiesel plants. In addition, there have been incidences of outright 

dumping of glycerin. One such event resulted in a large fish kill in Missouri. 

 Producers that choose to dispose of glycerin can be regulated under several EPA 

programs, depending on the practice. EPA strongly supports the beneficial use of glycerin as a 

product. While the market for refined glycerin is glutted with an excess supply, there are many 

known uses for glycerin feedstock. As prices for glycerin go down, many of these known 

products will show a better profit margin and demand for glycerin will increase. Most larger 

facilities are segregating crude glycerin for refining into usable feedstock for other products. 

Refining can range from minimal processing up to creation of a food grade product. Nationally, 

there is a lot of research on the creation of new value added products (ethanol, propylene glycol, 

etc.) using glycerin as a feedstock. Most of these projects are in university labs, but a few are up 

to pilot scale. These new technologies will go online at full scale within the next few years, and 

are an important part of the profit stream for the industry. 

6.9 Potential Impacts to Drinking Water and Public Health 

 Under the Safe Drinking Water Act (SDWA), EPA establishes enforceable safety 

standards for drinking water provided by public water systems (PWS). For chemicals, the 

standard is typically called a maximum contaminant level (MCL). A PWS is “a system for the 

provision to the public of water for human consumption through pipes or other constructed 

conveyances, if such system has at least fifteen service connections or regularly serves at least 

twenty-five individuals.” If the source water for a PWS does not meet the MCL, the PWS must 

take measures to reduce the contamination to safe levels and that may entail installing expensive 

drinking water treatment technology e.g., ion exchange (IE), granulated activated carbon (GAC) 

or reverse osmosis (RO). 

 EPA anticipates that increased corn production for ethanol will increase the occurrence of 

nitrate, nitrite, and atrazine in sources of drinking water. New corn acreage may result in increase 

in the application of fertilizers and herbicides, especially on marginal lands that are not as 

productive. The ethanol production process may generate new or increased discharges, injection 

or infiltration of process waste water that could adversely affect the nation’s surface water and 

ground water used for drinking water. 
 27

 In addition to potential additional contamination of sources of drinking water, surface and 

ground water supplies may be strained by increased production of irrigated corn for ethanol and 

the ethanol production process itself in local and regional areas. Increased pumping from 

agricultural aquifers to support ethanol production may accelerate the long running depletion of 

aquifers which has been documented by the USGS. According to U. S. Geological Survey 

(USGS) data, more than 72 billion gallons a day are already being pumped from the “thirty 

regional principle aquifers with the greatest amount of ground water use”, with irrigation 

accounting for slightly more than 75% of those withdrawals.61 

The water table of the Ogallala 

aquifer has declined by over 150 feet in some areas since the 1950s due to increasingly large 

withdrawals.62 

Aquifers provide water for domestic and other uses, and contribute to the base 

flow of many streams and lakes that support aquatic habitats and other ecosystem services such 

as fishing and swimming. Lower stream levels combined with the increased pollutant loadings 

may concentrate pollutants. Higher pollutant concentrations may require increased drinking 

water treatment. The accelerated depletion of agricultural aquifers and surface water supplies 

may be exacerbated by an increase in the incidence of droughts that are predicted under many 

climate change scenarios. 

6.9.1 Nitrogen 

 The nitrogen fertilizers that are applied to corn and other agricultural crops can end up in 

drinking water sources where they can impact human health. The two nitrogen compounds of 

concern are nitrate and nitrite. Nitrate is the most stable form of nitrogen in water. 

 EPA has established the MCL for nitrate-nitrogen at 10 parts per million (ppm) and for 

nitrite at 1 ppm. Infants below six months who drink water containing nitrate and/or nitrite in 

excess of the MCL could become seriously ill and, if untreated, may die.63 

Symptoms include 

shortness of breath and blue baby syndrome. This health effects language is not intended to 

catalog all possible health effects for nitrate. Rather, it is intended to inform people of the most 

significant and probable health effects, associated with nitrate and nitrite in drinking water. 

 Most nitrogen in water is converted to nitrates. Since nitrates are very soluble and do not 

bind to soils, they have a high potential to migrate to ground water. Because they do not 

evaporate, nitrates and nitrites are likely to remain in water until consumed by plants or other 

organisms. Primary sources of nitrate which may contaminate drinking water are human sewage, 

livestock manure, and fertilizers. 

 In 2007, there were 562 public water systems, serving 257, 558 people, reporting 

violations of the nitrate MCL.64 

If a utility’s routine compliance monitoring indicates that nitrate 

or nitrite concentrations are above the MCL, the water system must implement measures such as 

treatment or blending to reduce the concentration so that it is below the MCL (e.g., find a new 

source of water, adjust existing treatment or install new treatment). Also, utilities must monitor 

the finished water every quarter and provide notification to consumers of the MCL exceedance. 

 Since there is no nationally consistent sampling of ambient water used by public water 

systems, the relative contribution of nitrate detections from the various sources is generally 

unknown. 
 28

6.9.2 Pesticides 

The U.S. Geological Survey evaluated the fate and transport of herbicides in surface 

water, ground water, and in precipitation in the Midwest during the 1990s. Results of these 

studies showed the occurrence and temporal distribution of herbicides and their associated 

degradation products in reservoir outflows.65

 Atrazine is estimated to be the most widely used herbicide in the United States for control 

of weeds. Atrazine was the second most frequently detected pesticide in EPA's National Survey 

of Pesticides in Drinking Water Wells. EPA's Pesticides in Ground Water Database indicates 

numerous detections of atrazine at concentrations above the MCL in ground water in several 

states, including Delaware, Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, 

Nebraska, and New York.66 In 1993, EPA and the atrazine registrants initiated a monitoring 

program to focus on the most significant exposures associated with agricultural and residential 

uses -- exposures through drinking water. To this point, levels found in PWS have been low. 

Through the PWS monitoring program, EPA is ensuring that exposures to atrazine in drinking 

water do not reach levels that pose a risk to public health. 

 The MCL for atrazine is three parts per billion (ppb). MCL violations are not triggered by 

single measurement above the MCL but by the running annual average concentration from four 

quarterly samples in which at least one measurement during that period exceeds 3 ppb. Some 

people who drink water containing atrazine well in excess of the MCL over a period of many 

years could experience problems with their cardiovascular system or reproductive difficulties. 

This health effects language is not intended to catalog all possible health effects for atrazine. 

Rather, it is intended to inform people of the most significant and probable health effects, 

associated with atrazine in drinking water. 

 Atrazine may be released to the environment in wastewater from herbicide manufacturing 

facilities and through its use as an herbicide. Microbial activity and other chemicals may 

breakdown atrazine in soil and water, particularly in alkaline conditions. Sunlight and 

evaporation do not reduce its presence. It may bind to some soils, but generally tends to leach to 

ground water. Atrazine is not likely to be taken up in the tissues of plants or animals.67

 In A Review of Contaminant Occurrence in Public Water Systems, published in 1999, 

EPA found atrazine in the finished water of 21% of the surface water systems.68 Atrazine was 

found at concentrations exceeding the MCL in 10.7% of the surface water systems and, in 83% 

of those systems, atrazine was found at concentrations that would have been in violation of the 

MCL. As noted above, MCL violations are not triggered by single excursions above the MCL 

but by the running annual average concentration from four quarterly samples in which the 

measurement of at least one of those samples exceeds three ppb. However in one of the states 

where atrazine is widely used e.g., for corn production, the percentage of single samples 

exceeding the MCL was as high as 77.8% for surface water systems serving less than 500 

people; see Table 6.1. 
 29

Table 6.9-1. 

Percentage of Surface Water Systems with Detections of Atrazine 

for a High Occurrence State, 1999 

POPULATION <500 500 – 3,300 3,301 – 

10,000 

10,001 – 

50,000 > 50,000 

> MRLa 100% 100% 96.2% 96.3% 55.6% 

> MCLb 77.8% 71.1% 57.7% 18.5% 22.2% a The MRL, or minimum reporting level, is the lowest concentration at which the contaminant can be 

consistently and reliably detected. U.S. Environmental Protection Agency, A Review of Contaminant 

Occurrence in Public Water Systems, EPA 816-R-99-006, 1999, Table V.A.2, page D-2. b 

U.S. Environmental Protection Agency, ibid, p. D-3. 

 In 2003, EPA estimated that single atrazine measurements greater than the MCL would 

be observed in 26 to 57 public water systems serving a range of 24,400 – 260,300 people.69 

 Because atrazine is used mostly as a pre-emergent herbicide on corn, the surface water 

concentrations typically spike during growing season then taper off for the rest of the year. Even 

though many surface water systems encounter concentrations above the MCL during the growing 

season, very few experience MCL violations based on the average concentration over four 

consecutive quarters. In 2007, only one water system serving 740 people officially reported a 

MCL violation.70 

 From 1992 through 2001, the USGS observed atrazine in 90% of the samples it took from 

83 stream sites in agricultural areas as part of its National Water Quality Assessment (NAWQA). 

Although it does not target exclusively drinking water intakes or wells, the NAWQA program 

“provides an understanding of water-quality conditions and how those conditions may vary 

locally, regionally, and nationally...”.71 Atrazine was observed in 71% of the samples from 30 

urban stream sites during the same period. For ground water, USGS observed atrazine in 42% of 

the samples it took from wells in agricultural areas and in 31% of the samples from urban wells. 

The detection limits for this study were very low and 95% of the sampling results from streams 

in agricultural areas, where the highest concentrations of atrazine were found, were below 2.4 

ppb which is 80% of the MCL of 3 ppb. 

6.9.3 Future availability of more recent occurrence data 

 EPA anticipates releasing the chemical occurrence data covering the years 1999 – 2006 

from states for publication in 2009 as part of the six year review of drinking water standards. 

Once those data sets are publicly available, they will be useful in updating the occurrence data 

published here for nitrate and atrazine. 
 30

6.10 Water Quantity Concerns 

 Biofuel production based on current and projected approaches and processes, future 

alternative fuel development and production could markedly increase the demand for various 

fresh water resources. Two potential needs could increase water demand: quantities of water to 

produce biomass as a feedstock, and the additional water demand for refining of bio-ethanol and 

biodiesel fuels (by up to a factor of three relative to traditional refining). From a regional 

perspective, water demand for crop production would be relatively much larger than biorefinery 

demand; crop production needs would be approximately 200 times the water needed to refine 

biofuels.72 

 With growth of ethanol production, water supply reliability related to crop demand for 

biomass feedstock will remain an issue. The amount of water needed to grow feedstocks for 

biofuels can be considerable – for example, the ratio of water consumed to produce the corn 

itself for ethanol is nearly one thousand gallons per gallon of corn ethanol. Large scale 

production of perennial energy crops involving tens of millions of acres, even when rain-fed, can 

have water resource impacts and unintended local consequences due to alterations of hydrologic 

flows. The timing of the water demand may also be critical; water is often plentiful in one season 

but scarce in another. 

 Growing crops for biofuel production is likely to have significant regional and local 

impacts, including the potential to change irrigation water use, and thus local water availability. 

The feasibility and sustainability of water diversions for biomass irrigation will vary depending 

on the region. Moreover, some ethanol plants are being sited where water resources are already 

under duress, for example on the High Plains aquifer. 

 Biofuel refineries create additional local scale demand for water withdrawals and 

consumption. It is difficult to generalize about the impact on local water supplies, however, some 

community supplies have been stressed by the water requirements of ethanol facilities. 

However, from a national and regional perspective, relative to the water incorporated in the 

feedstock, water use in biorefineries is quite small. A typical corn ethanol plant consumes 

slightly more than four gallons water per gallon of ethanol produced; biodiesel refining even 

less, about one gallon of water per gallon of biodiesel, which on an energy-equivalent basis is 

even less in comparison to ethanol. (Petroleum refining consumes about 1.5 gallons of water per 

gallon fuel produced.) Biodiesel refining consumes about one gallon water per gallon, but may 

be up to three gallons per gallon. However, biofuel crops may be irrigated with wastewater that 

is biologically and chemically unsuitable for use with food crops. On the other hand, cellulosic 

materials require a different process, and are thought to use 9.5 gallons water per gallon fuel 

produced--but this would be expected to decline as efficiency increases (currently projected to be 

lowered to two to six gallons per gallon). 

 Geographic impacts of biofuel refining vary. Currently, the Midwest and Southeast have 

most of the production. In Iowa, water consumption alone from ethanol refining already accounts 

for about 7% of all industrial water use, and is projected to be 14% by 2012--or about 50 million 

gallons per day. A typical ethanol plant now producing 50 million gallons per year means a 

minimum of 175 million gallons (nearly 480,000 per day) used in a year. In the Great Lakes-St. 
 31

Lawrence region, newer facilities under construction will have capacities of 100 million gallons 

per year.73 

For a 100 million gallon per year corn ethanol plant, water consumption is one 

million gallons of water/day (equates to daily water consumption of a town of 20,000). 

 Research is needed to establish water use requirements across the entire biofuel 

production chain. Information needs related to biomass feedstock production include the 

assessment and quantification of impacts of increased irrigation of energy crops and resulting 

biofuel cost/benefit tradeoffs for both starch/sugar/oil biofuel crops, and the lignocellulosic 

biofuel crops. An assessment is also needed of the impacts on hydrologic flows of regional 

expansion of perennial energy crop production. These include the impacts and risks tradeoffs, 

e.g., altered flows due to deep extensive root systems and dense canopies, as well as a need for 

management practices/metrics, e.g. relatively large absolute water consumption, and additional 

irrigation necessary. Changing climate adds an additional element of uncertainty in making 

assessments of water use. 

 Many uncertainties exist regarding estimating water needs for irrigating cellulosic 

feedstocks in particular. Reasons include: water data is less available for proposed cellulosic 

feedstock than for common crops, evapotranspiration rates of marginal lands used for these crops 

are unknown, and water demand by heretofore unirrigated native grasses is unknown. 

Some practices can mitigate the increased demand for water by biofuels. Both the 

impacts and regulatory opportunities for mitigation of water impacts are likely to be at the state 

and local levels. For example, rainfall harvesting, efficient irrigation water transport and use of 

reclaimed water can lead to more efficient agricultural water use for both corn and cellulosic 

ethanol crops. Also, biorefineries are increasingly incorporating water recycling. 

The economics of the energy-water distribution linkage are important in biofuels 

production. At a macroscale, the high prices of energy driving the increased production of 

biofuels will likely affect water availability and use, e.g., conveyance costs related to irrigation 

waters will also increase with energy costs, possibly leading to water conservation that may 

counter the expanded water use for crops. Also, the value of crops relative to their water demand 

matters: water rights can often be bought and sold if the value of the crop is sufficiently high. 

 Finally, there is the potential for a low water use alternative biomass feedstock to 

develop: oil-producing macro-algae. These algae can be grown without land, using 

nontraditional waters, and CO2 waste streams as a nutrient source. Such fuels can have 

significantly higher energy density and are potentially more fungible within existing 

transportation fuel infrastructure than ethanol. 
 32

Chapter 7: Final Regulatory Flexibility Analysis

 This chapter discusses our Final Regulatory Flexibility Analysis (FRFA) which evaluates 

the potential impacts of the standards on small entities. The Regulatory Flexibility Act, as 

amended by the Small Business Regulatory Enforcement Fairness Act of 1996 (SBREFA), 

generally requires an agency to prepare a regulatory flexibility analysis of any rule subject to 

notice and comment rulemaking requirements under the Administrative Procedure Act or any 

other statute unless the agency certifies that the rule will not have a significant economic impact 

on a substantial number of small entities. Prior to issuing a proposal for this rulemaking, we 

analyzed the potential impacts of these regulations on small entities. As a part of this analysis, 

we convened a Small Business Advocacy Review Panel (SBAR Panel, or ‘the Panel’). During 

the Panel process, we gathered information and recommendations from Small Entity 

Representatives (SERs) on how to reduce the impact of the rule on small entities, and those 

comments are detailed in the Final Panel Report which is located in the public record for this 

rulemaking (Docket EPA-HQ-OAR-2005-0161). 

7.1 Overview of the Regulatory Flexibility Act 

 In accordance with section 609(b) of the Regulatory Flexibility Act, we convened an 

SBAR Panel before conducting the FRFA. A summary of the Panel’s recommendations can be 

found in the preamble to the proposed rule. Further, the Final Panel Report contains a detailed 

discussion of the Panel’s advice and recommendations (as well as comments from the Small 

Entity Representatives (SERs)). The regulatory alternatives that are being adopted in this final 

rule are described below. 

 Section 609(b) of the Regulatory Flexibility Act further directs the Panel to report on the 

comments of small entity representatives and make findings on issues related to identified 

elements of the Regulatory Flexibility Analysis under section 603 of the Regulatory Flexibility 

Act. Key elements of a Regulatory Flexibility Analysis are: 

- a description of and, where feasible, an estimate of the number of small entities to which 

the rule will apply; 

- projected reporting, record keeping, and other compliance requirements of the rule, 

including an estimate of the classes of small entities which will be subject to the 

requirements and the type of professional skills necessary for preparation of the report or 

record; 

- an identification, to the extent practicable, of all other relevant Federal rules which may 

duplicate, overlap, or conflict with the rule; 

- any significant alternatives to the rule which accomplish the stated objectives of 

applicable statutes and which minimize any significant economic impact of the rule on 

small entities. 

The Regulatory Flexibility Act was amended by SBREFA to ensure that concerns 

regarding small entities are adequately considered during the development of new regulations 

that affect those entities. Although we are not required by the Clean Air Act to provide special 

treatment to small businesses, the Regulatory Flexibility Act requires us to carefully consider the 

economic impacts that our rules may have on small entities. The recommendations made by the 
33 

Panel may serve to help lessen these economic impacts on small entities when consistent with 

Clean Air Act requirements. 

7.2 Need for the Rulemaking and Rulemaking Objectives 

A detailed discussion on the need for and objectives of this rule are located in the 

preamble to the final rule. As previously stated, section 1501 of the Energy Policy Act of 2005 

(EPAct) amended section 211 of the Clean Air Act (CAA) by adding section 211(o) which 

required the Environmental Protection Agency (EPA) to promulgate regulations implementing a 

renewable fuel program. The final Renewable Fuels Standard (RFS1) program, which began on 

September 1, 2007, created a specific annual level for minimum renewable fuel use that 

increases over time — resulting in a requirement that 7.5 billion gallons of renewable fuel be 

blended into gasoline by 2012. 

The Energy Independence and Security Act of 2007 (EISA) amended section 211(o), and 

the RFS program, by requiring higher volumes of renewable fuels, to result in 36 billion gallons 

of renewable fuel by 2022. EISA also expanded the purview of the RFS1 program by requiring 

that these renewable fuels be blended into diesel fuel (both highway and nonroad) in addition to 

gasoline. This expanded the volume obligation of parties that were already regulated under 

RFS1. It also expanded the pool of regulated entities, so the obligated parties under the RFS2 

rule will now include certain refiners, importers, and blenders of these fuels that were not 

previously covered by the RFS1 program. In addition to the total renewable fuel standard 

required by EPAct, EISA added standards for three additional types of renewable fuels to the 

program (advanced biofuel, cellulosic biofuel, and biomass-based diesel) and requires 

compliance with all four standards. 

7.3 Definition and Description of Small Entities 

 Small entities include small businesses, small organizations, and small governmental 

jurisdictions. For the purposes of assessing the impacts of the rule on small entities, a small 

entity is defined as: (1) a small business that meets the definition for business based on the Small 

Business Administration’s (SBA) size standards; (2) a small governmental jurisdiction that is a 

government of a city, county, town, school district or special district with a population of less 

than 50,000; and (3) a small organization that is any not-for-profit enterprise which is 

independently owned and operated and is not dominant in its field. 

Small businesses (as well as large businesses) would be regulated by this rulemaking, but 

not small governmental jurisdictions or small organizations as described above. As set by SBA, 

the categories of small entities that will potentially be affected by this rulemaking are defined in 

Table 7.3-1 provides an overview of the primary SBA small business categories potentially 

affected by this regulation. 
34 

Table 7.3-1. Small Business Definitions 

Industry 

Defined as small entity 

by SBA if less than or 

equal to: 

NAICSa codes 

Gasoline and diesel fuel refiners 1,500 employeesb 324110 

a

 North American Industrial Classification System 

b

 EPA has included in past fuels rulemakings a provision that, in order to qualify for the small refiner 

flexibilities, a refiner must also produce no greater than 155,000 bpcd crude capacity

EPA used a variety of sources to identify which entities are appropriately considered 

“small.” EPA used the criteria for small entities developed by the Small Business 

Administration under the North American Industry Classification System (NAICS) as a guide. 

Information about the characteristics of refiners comes from sources including the Energy 

Information Administration (EIA) within the U.S. Department of Energy, oil industry literature, 

and previous rulemakings that have affected the refining industry. EPA then found employment 

information for these companies using the business information database Hoover’s Online (a 

subsidiary of Dun and Bradstreet). These refiners fall under the Petroleum Refineries category, 

324110, as defined by NAICS. 

Small entities that will be subject to the renewable fuel standard include: domestic 

refiners that produce gasoline and/or diesel, and importers of gasoline and/or diesel into the U.S. 

Based on 2007 data, EPA believes that there are about 95 refiners of gasoline and diesel fuel. Of 

these, EPA believes that there are currently 17 refiners owning 20 refineries producing gasoline 

and/or diesel fuel that meet the SBA small entity definition of having 1,500 employees or less. 

Further, we believe that three of these refiners own refineries that do not meet the definition of a 

“small refinery” that Congress specified under section 211(o). It should be noted that because of 

the dynamics in the refining industry (i.e., mergers and acquisitions), the actual number of 

refiners that ultimately qualify for small refiner status under the RFS2 program could be different 

from this initial estimate. 

7.4 Steps to Minimize Impacts on Small Entities 

 As a part of the SBREFA process, we conducted outreach to small refiners of gasoline 

and/or diesel fuels and convened a Panel to gain feedback and advice from these entities. Prior 

to convening the Panel, we held outreach meetings with the SERs to learn the needs of small 

entities and potential challenges that these entities may face. The outreach meetings also helped 

to provide the SERs an opportunity to gain a better understanding of the new requirements under 

EISA and how it would change the RFS program (including those small refiners who only 

produce diesel and were not regulated entities ). The feedback that we received from SERs as a 

result of these meetings was used during the Panel process to develop regulatory alternatives to 

mitigate the impacts of the rulemaking on small businesses. General concerns raised by SERs 

during the SBREFA process were potential costs and access to RINs for compliance with the 

program. 
35 

The Panel consisted of members from EPA, the Office of Management and Budget 

(OMB), and the Small Business Administration’s Office of Advocacy. Following the Panel 

convening, a Final Panel Report detailing all of the alternatives that were recommended by the 

Final Regulatory Support Document Panel (as well as individual Panel members) was issued. 

We either proposed or requested comment on the various recommendations put forth by the 

Panel. Below we discuss those flexibility options recommended in the Panel Report, our 

proposed regulatory alternatives, and those provisions which are being finalized. 

7.4.1 Panel Recommendations 

The purpose of the Panel process is to solicit information as well as suggested flexibility 

options from the SERs, and the Panel recommended that EPA continue to do so during the 

development of the RFS2 rule. Recognizing the concerns about EPA’s authority to provide 

extensions to a subset of small refineries (i.e., those that are owned by small refiners) different 

from that provided to small refineries in section 211(o)(9), the Panel recommended that EPA 

continue to evaluate this issue, and that EPA request comment on its authority and the 

appropriateness of providing extensions beyond those authorized by section 211(o)(9) for small 

refineries operated by a small refiner. The Panel also recommended that EPA propose to provide 

the same extension provision of 211(o)(9) to small refiners who do not own small refineries as is 

provided for small refiners who do own small refineries. 

7.4.2 Extensions of the Temporary Exemption Based on a Study of Small Refinery 

Impacts 

 Panel Recommendations

The Panel recommended that EPA propose in the RFS2 program the provision at 40 CFR 

80.1141(e) extending the RFS1 temporary exemption for at least two years for any small refinery 

that DOE determines would be subject to disproportionate economic hardship if required to 

comply with the RFS2 requirements. 

Section 211(o)(9)(A)(ii) requires DOE to perform a study of the economic impacts of the 

RFS requirements on small refineries. The study, which was required to be completed by 

December 31, 2008, must assess and determine whether the RFS requirements would impose a 

disproportionate economic hardship on small refineries. Small refineries that are found to be in a 

disproportionate economic hardship situation will receive an extension of the temporary 

exemption for at least two years. 

The Panel also recommended that EPA work with DOE in the development of the small 

refinery study, specifically to communicate the comments that SERs raised during the Panel 

process. 

 What We Proposed and Public Comments Received on the NPRM

We did not propose this hardship provision given the outcome of the DOE small refinery 

study. In the small refinery study, “EPACT 2005 Section 1501 Small Refineries Exemption 
36 

Study”, DOE’s finding was that there is no reason to believe that any small refinery would be 

disproportionately harmed by inclusion in the proposed RFS2 program. This finding was based 

on the fact that there appeared to be no shortage of RINs available under RFS1, and EISA has 

provided flexibility through waiver authority (per section 211(o)(7)). Further, in the case of the 

cellulosic biofuel standard, cellulosic biofuel allowances can be provided from EPA at prices 

established in EISA (see regulation section 80.1455). DOE thus determined that no small 

refinery would be subject to disproportionate economic hardship under the proposed RFS2 

program, and that the small refinery exemption should not be extended beyond December 31, 

2010. DOE noted in the study that, if circumstances were to change and/or the RIN market were 

to become non-competitive or illiquid, individual small refineries have the ability to petition 

EPA for an extension of their small refinery exemption (as stated in regulation section 80.1441). 

In their written comments, as well as in discussions we had with them on the proposed 

rule, small refiners indicated that they did not believe that EPA should rely on the results of the 

DOE small refinery study to inform any decisions on small refiner provisions. Small refiners 

generally commented that they believe that the study was flawed and that the conclusions of the 

study were reached without adequate analysis of, or outreach with, small refineries (as the 

majority of the small refiners own refineries that meet the Congressional small refinery 

definition). One commenter stated that such a limited investigation into the impact on small 

refineries could not have resulted in any in-depth analysis on the economic impacts of the 

program on these entities. Another commenter stated that it believes that DOE should be 

directed to reopen and reassess the small refinery study be June 30, 2010, as suggested by the 

Senate Appropriations Committee. 

 What We’re Finalizing

As discussed more in section III.E of the preamble to the final rule, since the only small 

refinery study available for us to use as a basis for whether or not to grant small refineries an 

automatic two-year extension of the exemption is the study that was performed in 2008, we had 

to use this study to develop this final rule. EPAct directs EPA to consider the DOE small 

refinery study in assessing the impacts to small refineries, and we interpret this to mean that any 

extension past December 31, 2010 has to be tied to the DOE Study. Further, since that study 

found that there was no disproportionate economic impact on small refineries, we cannot grant 

an automatic additional extension for small refineries or small refiners (except on a case-by-case 

hardship basis). However, this does not preclude small refiners from applying for case-by-case 

extensions of the small refiner temporary exemption. 

We are aware that there have been expressions of concern from Congress regarding the 

DOE Study. Specifically, in Senate Report 111-45, the Senate Appropriations Committee 

“directed [DOE] to reopen and reassess the Small Refineries Exemption Study by June 30, 

2010,” noting a number of factors that the Committee intended that DOE consider in the revised 

study. The Final Conference Report 111-278 to the Energy & Water Development 

Appropriations Act (H.R. 3183), referenced the language in the Senate Report, noting that the 

conferees “support the study requested by the Senate on RFS and expect the Department to 

undertake the requested economic review.” The DOE study has not been revised at this time; 

however, if DOE prepares a revised study and the revised study finds that there is a 
37 

disproportionate economic impact, we will revisit the exemption extension at that point in 

accordance with section 211(o)(9)(A)(ii). 

7.4.3 Delay in Standards for Small Refiners 

 Panel Recommendations

 The RFS1 program regulations provide small refiners who operate small refineries as 

well as small refiners who do not operate small refineries with a temporary exemption from the 

standard through December 31, 2010. Small refiner SERs suggested that an additional 

temporary exemption for the RFS2 program would be beneficial to them in meeting the RFS2 

standards. EPA evaluated a temporary exemption for at least some of the four required RFS2 

standards for small refiners. The Panel recommended that EPA propose a delay in the effective 

date of the standards until 2014 for small entities, to the maximum extent allowed by the statute. 

However, the Panel recognized that EPA has serious concerns about its authority to provide an 

extension of the temporary exemption for small refineries that is different from that provided in 

CAA section 211(o)(9), since Congress specifically addressed an extension for small refineries 

in that provision. 

The Panel did recommend that EPA propose other avenues through which small 

refineries and small refiners could receive extensions of the temporary exemption. These 

avenues were a possible extension of the temporary exemption for an additional two years 

following a study of small refineries by the Department of Energy (DOE) (as discussed above) 

and provisions for case-by-case economic hardship relief. 

 What We Proposed and Public Comments Received on the NPRM

We proposed and took comment on the recommendations of the Panel and SERs. We 

proposed to continue the temporary exemption finalized in RFS1, through December 31, 2010, 

for small refiners (and small refineries), extending it to include an exemption for diesel volume 

and diesel refiners, importers, and blenders, as required by EISA. 

Commenters that oppose an extension of the temporary exemption generally stated that 

they believe an extension is not warranted, and some of these commenters expressed concerns 

about allowing provisions for small refiners. One commenter also stated that the small refinery 

exemption should not be extended and that the small refiner exemption should be eliminated 

completely. A couple commenters supported the continuation of the exemption through 

December 31, 2010 only; one of those commenters stated that it does not support an extension as 

it believes that all parties have been well aware of the passage of EISA and small refineries and 

small refiners should have been striving to achieve compliance by the end of 2010. Two 

commenters also expressed views that the exemption should not have been offered to small 

refiners in RFS1 as this was not provided by EPAct, and that an extension of the exemption 

should not be finalized for small refineries at all. The commenters further commented that an 

economic hardship provision was included in EPAct, and any exemption extension should be 

limited to such cases, and only to the specific small refinery (not small refiner) that has 

petitioned for such an extension. 
38 

Commenters supporting an extension of the exemption commented that they believe that 

the statutes (EPAct and EISA) do not prohibit EPA from providing relief to regulated small 

entities on which the rule will have a significant economic impact, and that such a delay could 

lessen the burden on these entities. One commenter stated that it believes EPA denied or ignored 

much of the relief recommended by the Panel in the proposal. Another commenter stated that it 

believes EPA’s concerns regarding the legal authority are unsustainable considering EPA’s past 

exercises of discretion under the RFS1 program, and with the discretion afforded to EPA under 

section 211(o) of the CAA. Some commenters requested a delay until 2014 for small refiners. 

One additional commenter expressed support for an extension of the small refinery exemption 

only, and stated that these small refineries should be granted a permanent exemption. 

What We’re Finalizing

The RFS1 program regulations exempt gasoline produced by small refineries from the 

renewable fuels standard through December 31, 2010 (at 40 CFR 80.1141), per EPAct. As EISA 

did not alter the small refinery exemption in any way, we are retaining this small refinery 

temporary exemption in the RFS2 program, extending the relief to diesel fuel volumes produced 

or imported in addition to gasoline, and extending the relief to those small refineries of diesel 

fuel that were not covered under RFS1. Likewise, as we extended under RFS1 the small refinery 

temporary exemption to the few remaining small refiners that met the Small Business 

Administration’s (SBA) definition of a small business (1,500 employees or less company-wide), 

we are also finalizing a continuation of the small refiner temporary exemption through December 

31, 2010 for all gasoline and diesel small refiners. 

As described in the Final Panel Report, EPA early-on identified limitations on its 

authority to issue additional flexibility and exemptions to small refineries. In section 211(o)(9) 

Congress specifically addressed the issue of an extension of time for compliance for small 

refineries, temporarily exempting them from renewable fuel obligations through December 31, 

2010. As discussed above, the statute also includes two specific provisions describing the basis 

and manner in which further extensions of this exemption can be provided. In the RFS1 

rulemaking, EPA considered whether it should provide additional relief to the limited number of 

small refiners who were not covered by the small refinery provision, by providing them a 

temporary exemption consistent with that provided by Congress for small refineries. EPA 

exercised its discretion under section 211(o)(3) and provided such relief. Thus, in RFS1, EPA 

did not modify the relief provided by Congress for small refineries, but did exercise its discretion 

to provide the same relief specified by statute to a few additional parties. 

In RFS2 we are faced with a different issue—the extent to which EPA should provide 

additional relief to small refineries beyond the relief specified by statute, and whether it should 

provide such further relief to small refiners as well. There is considerable overlap between 

entities that are small refineries and those that are small refiners. Providing additional relief just 

to small refiners would, therefore, also extend additional relief to at least a number of small 

refineries. Congress spoke directly to the relief that EPA may provide for small refineries, 

including those small refineries operated by small refiners, and limited that relief to a blanket 

exemption through December 31, 2010, with additional extensions if the criteria specified by 
39 

Congress are met. EPA believes that an additional or different extension, relying on a more 

general provision in section 211(o)(3) would be inconsistent with Congressional intent. Further, 

we do not believe that the statute allows us the discretion to give relief to small refiners only—as 

this would result in a subset of small refineries (those that also qualify as small refiners) 

receiving relief that is greater than the relief already given to all small refineries under EISA. 

EPA also notes that the criteria specified by statute for providing a further compliance 

extension to small refineries is a demonstration of “disproportionate economic hardship.” The 

statute provides that such hardship can be identified through the DOE study, or in individual 

petitions submitted to the Agency. However, the DOE study has concluded that no 

disproportionate economic hardship exists, at least under current conditions and for the 

foreseeable future under RFS2. Therefore, absent further information that may be provided 

through the petition process, there does not currently appear to be a basis under the statute for 

granting further compliance extensions to small refineries. If DOE revises its study and comes to 

a different conclusion, EPA can revisit this issue. 

During the development of this final rule, we again evaluated the various options 

recommended by the Panel, the legality of offering an extension of the exemption to small 

refiners only, and also comments on the proposed rule. Specifically in the case of an extension 

of the exemption for small refiners, we also consulted the small refinery study prepared by DOE, 

as the statute directs us to use this as a basis for providing an additional two year exemption. As 

discussed in Section III.E of the preamble to the final rule, we do not believe that we can provide 

an extension of the exemption considering the outcome of the DOE small refinery study, which 

did not find that there was a disproportionate economic hardship. Further, we do not believe that 

the statute allows us the discretion to give relief to a subset of small refineries (those that also 

qualify as small refiners) that is greater than the relief already given to all small refineries under 

EPAct. However, it is important to recognize that the 211(o)(9) small refinery provision does 

allow for extensions beyond December 31, 2010, as discussed in preamble Section III.E.2. Thus, 

refiners may apply for individual hardship relief. 

7.4.4 Phase-in 

 Panel Recommendations

Small refiner SERs suggested that a phase-in of the obligations applicable to small 

refiners would be beneficial for compliance, such that small refiners would comply by gradually 

meeting the standards on an incremental basis over a period of time, after which point they 

would comply fully with the RFS2 standards, EPA has serious concerns about its authority to 

allow for such a phase-in of the standards. CAA section 211(o)(3)(B) states that the renewable 

fuel obligation shall “consist of a single applicable percentage that applies to all categories of 

persons specified” as obligated parties. This kind of phase-in approach would result in different 

applicable percentages being applied to different obligated parties. Further, such a phase-in 

approach would provide more relief to small refineries operated by small refiners than that 

provided under the small refinery provision. Thus the Panel recommended that EPA should 

invite comment on a phase-in, but not propose such a provision. 
40 

What We Proposed and Public Comments Received on the NPRM

While we did not propose it, we did request comment on the concept of a phase-in for 

small refiners only. Specifically, we requested comments on a phase-in for some or all of the 

applicable standards for small refiners. 

With respect to our request for comments on the concept of a phase-in of the RFS 

standards for small refiners, some commenters stated that they believe that EPA has the ability to 

consider a phase-in of the standards for small refiners. One commenter suggested that a 

temporary phase-in could help lessen the burden of regulation on small entities and promote 

compliance. Another commenter stated that it believes EPA’s legal concerns regarding a phasein are unsustainable considering EPA’s past exercises of discretion under the RFS1 program and 

with the discretion afforded to EPA under section 211(o) of the CAA. 

What We’re Finalizing

After considering the comments on this issue, EPA continues to believe that allowing a 

phase-in of regulatory requirements for small refineries and/or small refiners would be 

inconsistent with the statute, for the reasons mentioned above. Any individual entities that are 

experiencing hardship that could justify a phase-in of the standards have the ability to petition 

EPA for individualized relief. Therefore we are not including a phase-in of standards for small 

refiners in the final rule. 

7.4.5 RIN-related Flexibilities 

 Panel Recommendations

The small refiner SERs requested that the proposed rule contain provisions for small 

refiners related to the RIN system, such as flexibilities in the RIN rollover cap percentage and 

allowing all small refiners to use RINs interchangeably. In the RFS1 program, EPA allows for 

20% of a previous year’s RINs to be “rolled over” and used for compliance in the following year. 

We noted during the Panel process that a provision to allow for flexibilities in the rollover cap 

could include a higher RIN rollover cap for small refiners for some period of time or for at least 

some of the four standards. Further, we noted our belief that since the concept of a rollover cap 

was not mandated by section 211(o), EPA believes that there may be an opportunity to provide 

appropriate flexibility in this area to small refiners under the RFS2 program but only if it is 

determined in the DOE small refinery study that there is a disproportionate effect warranting 

relief. The Panel recommended that EPA request comment on increasing the RIN rollover cap 

percentage for small refiners, and further that EPA should request comment on an appropriate 

level of that percentage. The Panel also recommended that EPA invite comment on allowing 

RINs to be used interchangeably for small refiners, but not propose this concept because under 

this approach small refiners would arguably be subject to a different applicable percentage than 

other obligated parties. 
41 

 What We Proposed and Public Comments Received on the NPRM

We proposed a change to the RIN rollover cap for small refiners only, and we requested 

comment on appropriate level to set the rollover cap for these entities. We also took comment on 

the concept of allowing RINs to be used interchangeably for small refiners only. 

We also requested comment on the concept of RIN-related flexibilities for small refiners. 

In their comments on the proposed rule, one small refiner commented that, in regards to small 

refiners’ concerns about RIN pricing and availability, there is no mechanism in the rule to 

address the possibility that the RIN market will not be viable. The commenter further suggested 

that more “durable” RINs are needed for small refiners that can be carried over from year to 

year, to alleviate some of the potentially market volatility for renewable fuels. Another 

commenter suggested that RINs should be interchangeable for small refiners, or alternatively, 

some mechanism should be implemented to ensure that RIN prices are affordable for small 

refiners. Further, with regard to interchangeable RINs, one commenter stated that small refiners 

do not have the staff or systems to manage and account for four different categories of RINs and 

rural small refiners will suffer economic hardship and disadvantage because of the unavailability 

of biofuels. The commenter also requested an increase in the rollover cap to 50% for small 

refiners. 

What We’re Finalizing

We are not finalizing RIN-related provisions in today’s action. As highlighted in the 

NPRM, we continue to believe that the concept of interchangeable RINs for small refiners only 

fails to require the four different standards mandated by Congress (e.g., conventional biofuel 

could not be used instead of cellulosic biofuel or biomass-based diesel). Further, given the 

findings from the DOE study, if small refineries and small refiners do not face disproportionate 

economic hardship, then we do not believe that we have the basis for granting such additional 

relief beyond what Congress already provided. Thus, small refiners will be held to the same RIN 

rollover cap as other obligated parties. 

7.4.6 Program Review 

 Panel Recommendations

During the SBREFA process, SERs raised concerns over uncertainty with acquiring 

RINs, and the potential pricing of RINs. They commented that an annual program review would 

be beneficial to small refiners as it could provide information about the RIN system. EPA raised 

the concern that this could lead to some redundancy since EPA is required to publish a notice of 

the applicable RFS standards in the Federal Register annually, and that this annual process will 

inevitably include an evaluation of the projected availability of renewable fuels. Nevertheless, 

the SBA and OMB Panel members stated that they believe that a program review could be 

helpful to small entities in providing them some insight to the RFS program’s progress and 

alleviate some uncertainty regarding the RIN system. As EPA will be publishing a Federal 

Register notice annually, the Panel recommended that EPA include an update of RIN system 

progress (e.g., RIN trading, RIN availability, etc.) in this notice and that the results of this 
42 

evaluation be considered in any request for case-by-case hardship relief. 

What We Proposed and Public Comments Received on the NPRM

In the NPRM, we proposed that we would include information to help inform industry 

about the RIN system in the annual notice of the RFS standards that EPA must publish in the 

Federal Register. We also proposed that information from the annual Production Outlook 

Reports that producers and importers must submit to EPA, as well as information required in 

EMTS reports, could be used in the annual Federal Register notice to update RIN system 

progress. 

A group of commenters stated that they support the concept of an annual review. They 

commented that EPA should include a review of the RIN system in annual review procedures, 

and further suggested that EPA invite small refiner participation in the development of the 

review process. (For more information on the comments received on Production Outlook 

Reports specifically, please see Chapter 3 of the Summary and Analysis of Comments.) 

What We’re Finalizing

Based on comments received on the proposed rule, we believe that such information 

could be helpful to industry, especially to small businesses to help aid the proper functioning of 

the RIN market, especially in the first years of the program. However, during the development 

of the final rule, it became evident that there could be instances where we would want to report 

out RIN system information on a more frequent basis than just once a year. Thus, we are 

finalizing that we will report out elements of RIN system progress; but such information will be 

reported via other means (e.g., the RFS website (www.epa.gov/otaq/renewablefuels/index.htm), 

EMTS homepage, etc.). Additionally, we will also publish annual summaries of the Production 

Outlook Reports. 

7.4.7 Extensions of the Temporary Exemption Based on Disproportionate Economic 

Hardship 

 Panel Recommendations

While SERs did not specifically comment on the concept of hardship provisions for the 

upcoming proposal, the Panel noted that under CAA section 211(o)(9)(B) small refineries may 

petition EPA for case-by-case extensions of the small refinery temporary exemption on the basis 

of disproportionate economic hardship. Refiners may petition EPA for this case-by-case 

hardship relief at any time. 

The Panel recommended that EPA propose in the RFS2 program a case-by-case hardship 

provision for small refineries similar to that provided at 40 CFR 80.1141(e)(1). The Panel also 

recommended that EPA propose a case-by-case hardship provision for small refiners that do not 

operate small refineries that is comparable to that provided for small refineries under section 

211(o)(9)(B), using its discretion under CAA section 211(o)(3)(B). This would apply if EPA 

does not adopt an automatic extension for small refiners, and would allow those small refiners 
43 

that do not operate small refineries to apply for the same kind of extension as a small refinery. 

The Panel recommended that EPA take into consideration the results of the annual update of RIN 

system progress and the DOE small refinery study in assessing such hardship applications. 

What We Proposed and Public Comments Received on the NPRM

We did propose hardship provisions for small refineries and small refiners in the RFS2 

proposal program similar to those provided at 40 CFR 80.1141 and 80.1142. We propose to 

extend the temporary exemption for at least two years for any small refinery that DOE’s small 

refinery study determines would face disproportionate economic hardship in meeting the 

requirements of the RFS2 program (per CAA section 211(o)(9)(A)(ii)(I)), and that any small 

refinery could apply for a case-by-case hardship at any time on the basis of disproportionate 

economic hardship per section 211(o)(9)(B). For those small refiners that do not operate small 

refineries, we also proposed the same case-by-case hardship provision using our discretion under 

CAA section 211(o)(3)(B). 

While the findings from DOE’s small refinery study indicate that no small refineries 

would be subject to disproportionate economic hardship under the proposed RFS2 program and 

that the small refinery exemption should not be extended beyond December 31, 2010, DOE 

noted in the study that if circumstances were to change and/or the RIN market became noncompetitive or illiquid, individual small refineries have the ability to petition EPA for an 

extension of their small refinery exemption. 

Two commenters noted that an economic hardship provision was included in EPAct, and 

commented that any extension of the exemption past 2010 should be limited to such cases, and 

only to the specific small refinery (not small refiner) that has petitioned for such an extension. A 

group of commenters also stated that they believe that small refiners that may be subject to 

disproportionate hardship should be granted a two-year extension of the existing RFS1 

temporary exemption. The commenters further suggested that EPA tailor the case-by-case 

hardship provisions to include a general hardship exemption of up to five years for any and all 

small refiners meeting certain specified hardship criteria. The commenters stated that such 

criteria should be developed with small refiner participation. 

What We’re Finalizing

We believe that these avenues of relief can and should be fully explored by small refiners 

who are covered by the small refinery provision. In addition, we believe that it is appropriate to 

allow petitions to EPA for an extension of the temporary exemption based on disproportionate 

economic hardship for those small refiners who are not covered by the small refinery provision 

(again, per our discretion under section 211(o)(3)(B)); this would ensure that all small refiners 

have the same relief available to them as small refineries do. Thus, we are finalizing a hardship 

provision for small refineries in the RFS2 program, that any small refinery may apply for a caseby-case hardship at any time on the basis of disproportionate economic hardship per CAA 

section 211(o)(9)(B). We are also finalizing a case-by-case hardship provision for those small 

refiners that do not operate small refineries (section 80.1442(h)) using our discretion under CAA 

section 211(o)(3)(B). This provision will allow those small refiners that do not operate small 
44 

refineries to apply for the same kind of extension as a small refinery. In evaluating applications 

for this hardship provision EPA will take into consideration information gathered from annual 

reports and RIN system progress updates, as recommended by the SBAR Panel. 

7.5 Reporting, Recordkeeping, and Other Compliance Requirements

Registration, reporting, and recordkeeping are necessary to track compliance with the 

RFS standards and transactions involving RINs. As discussed in Sections II.J and III.A of the 

preamble to the final rule, the compliance requirements under the RFS2 rule are in many ways 

similar to those required under the RFS1 rule, with some modifications (e.g., those to account for 

the new requirements of EISA). New provisions being finalized in today’s action include the 

new EPA Moderated Transaction System (EMTS) to aid industry in their reporting and ensure 

validity of RINs in the marketplace. EMTS allows for “real-time” reporting of RIN generation 

transactions, and the ability for small blenders to “delegate” their RIN-separation responsibilities 

to the party directly upstream. Please see Sections II and III of the final preamble for more 

detailed information on these and other registration, recordkeeping, reporting, and compliance 

requirements of the final rule. 

7.6 Related Federal Rules 

 We are aware of a few other current or proposed Federal rules that are related to this rule. 

The primary related federal rules are: the first Renewable Fuel Standard (RFS1) rule (72 FR 

23900, May 1, 2007), the RFS1 Technical Amendment Direct Final Rulemaking (73 FR 57248, 

October 2, 2008), and Control of Emissions from New Marine Compression-Ignition Engines at 

or Above 30 Liters per Cylinder (proposed rule: 74 FR 44442, August 28, 2009; final rule: signed 

December 22, 2009). 

7.7 Conclusions 

 Based on our outreach, fact-finding, and analysis of the potential impacts of our 

regulations on small businesses, we were able to estimate annual costs, and thus use this 

information to complete a preliminary screening analysis. To perform this analysis, we used a 

cost-to-sales ratio test (a ratio of the estimated annualized compliance costs to the value of sales 

per company). Costs were analyzed using average gasoline + diesel costs for the RFS2 program 

referenced to the AEO 2007 reference case for 2022, and also for 2010 and 2012. 

For 2022, the cost-to-sales test indicated that all 17 small refiners would be affected at 

less than 1 percent of their sales (i.e., the estimated costs of compliance with the rule would be 

less than 1 percent, of their sales), and that these costs would actually be negative (or, a cost 

savings)—ranging from -3.15% to -0.94%. The gasoline and diesel costs for the 2022 scenario 

were estimated to be -2.35 and -12.07 cents per gallon, respectively. 
45 

Under the 2010 and 2012 scenarios, all small refiners were still affected at less than 1 

percent, however the costs were no longer negative. For 2010, costs ranged from 0.24 to 0.84 

percent of small refiners’ sales, with estimated gasoline and diesel costs of 0.29 and 1.29 cents 

per gallon, respectively. For 2012, the costs were relatively similar for all small refiners—at 

0.24-0.25 percent of their sales. The gasoline and diesel costs for 2012 were estimated to be 0.51 

and 0.58 cents per gallon, respectively (the similarity in small refiners’ costs-to-sales was due to 

this similarity in the estimated gasoline and diesel costs). Thus, costs for small refiners are 

generally anticipated to be less than one percent of their sales, and are expected to decrease over 

time, ultimately resulting in a cost savings by 2022. Note that while we did analyze a 2010 

scenario, small refiners would not be participating in the program during this time, as the small 

refiner temporary exemption runs through December 31, 2010. 

The cost estimates for all 3 scenarios do include the current available subsidies for the 

blending of ethanol of 45 cents per gallon for ethanol and $1.00 per gallon for 

biodiesel/renewable diesel, and the $1.01 per gallon producer credit for cellulosic biofuel, which 

depress the true cost of these renewable fuels in the marketplace. 

 For a complete discussion of the costs of the RFS2 rulemaking please see Chapter 4 of 

this Regulatory Impact Analysis.
 46

Appendix A: Biodiesel Effects on Heavy-Duty Highway Engines and 

Vehicles 

Executive Summary 

 Due to the continuing interest in the use of biodiesel fuels, the Environmental Protection 

Agency (EPA) has conducted a comprehensive analysis of the emission impacts of biodiesel 

using publicly-available heavy-duty, in-use diesel chassis and engine exhaust emissions data. 

 We investigated the emission impacts on NOx, PM, HC, and CO of 20 volume percent 

biodiesel fuels produced from various animal- and plant-based feedstock materials tested under 

several cycles in this analysis. Average NOx emissions were found to increase 2.2%, while PM, 

HC, and CO were found to decrease 15.6%, 14.1%, and 13.8% respectively, for all test cycles 

run on 20 vol% soybean-based biodiesel fuel at a significance level of P < 0.05 (See Table ESA). 

Table ES-A. 

Emission impacts for all cycles tested on 20 vol% soybean-based 

biodiesel fuel relative to an average base fuel 

Emissions Percent Change in 

Emissions 

NOx 

PM 

HC 

CO 

+2.2% 

-15.6% 

-14.1% 

-13.8% 

 These results are consistent with the exhaust emission impacts for heavy-duty, in-use 

diesel engines found in our 2002 Draft Technical Report, entitled "A Comprehensive Analysis of 

Biodiesel Impacts on Exhaust Emissions." 

 The current analysis also found that heavy-duty engine dynamometer data was 

statistically indistinguishable from heavy-duty chassis dynamometer data for NOx and HC at a 

significance level of p < 0.05. Likewise, results for Detroit Diesel Corporation (DDC) engines, 

used in many test programs, were found to be statistically similar to results for other engines for 

NOx, CO, and HC at a significance level of p < 0.05. 

 The results of the current analysis also point to a load-dependence of NOx emissions for 

heavy-duty highway engines and chasses. The difference in NOx emissions between our results 

here and those of other researchers appears to be attributable to an artifact of the selected test 

cycle profile. Analyzing the NOx emissions data as a function of load, as we do here -- as 

opposed to a particular test cycle profile -- reconciles the difference and supports the NOx 

emission-load-dependence hypothesis for heavy-duty highway engines and chasses posited by 

Sze et al. and corroborated by Eckerle et al. 
47

A1. Introduction 

 We investigated the emission impacts on NOx, PM, CO, and HC of 20 volume percent 

(vol%) biodiesel fuels produced from various feedstock materials tested under several vehicle 

and engine test cycles. The data used in this analysis is comprised of data used in EPA's 2002 

Draft Technical Report, entitled "A Comprehensive Analysis of Biodiesel Impacts on Exhaust 

Emissions Draft Technical Report", hereafter referred to as the 2002 Draft Technical Report. 

Data from that report was supplemented with pertinent data sources published in the scientific 

and automotive literature between 2002 and 2007. The supplemental data was comprised of late 

model year engines, vehicles, and technology groups. A list of all data sources used in this 

analysis appears in the appendix to this document as does the 2002 Draft Technical Report. 

 The focus of the analysis proceeded from general to specific terms, through seven fuelcycle combinations, summarized below. In Case 1, the most-general fuel-cycle combination, we 

examined all heavy-duty engine and chassis cycles run on plant- and animal-based biodiesel 

fuels; in Case 5a, 5b, and 5c, the most-specific fuel-cycle combinations, we examined heavyduty engine and chassis data for light-, medium-, and heavy-duty cycles using soybean-based 

biodiesel. The latter analysis was designed to examine load-dependence of NOx emissions for 

heavy-duty highway engines and chasses first posited by EPA in 2007 (see Sze et al.). This 

research was further elucidated by Eckerle et al. While feedstock materials varied for the seven 

fuel-cycle combinations presented here, all analyses were conducted using 20 vol% biodiesel 

fuels. 

 A summary of fuel-cycle combinations used in the analysis appears below. 

• Case 1: All cycles tested on plant-based (soybean, rapeseed/canola, and coconut) and 

animal-based (tallow, lard, and grease) biodiesel fuels, 

• Case 2: All cycles tested on soybean-based biodiesel fuel, 

• Case 3: FTP and UDDS cycles tested on soybean-based biodiesel fuel, 

 

• Case 4: Detroit Diesel Corporation (DDC) and non-DDC engines tested on 

 soybean-based biodiesel fuel, 

• Case 5a: Engines and chasses tested on soybean-based biodiesel fuel run on light-duty 

cycles, 

• Case 5b: Engines and chasses tested on soybean-based biodiesel fuel run on 

 medium-duty cycles, and 

• Case 5c: Engines and chasses tested on soybean-based biodiesel fuel run on heavy-duty 

cycles. 

 The results of the analysis of the seven fuel-cycle combinations appear in Section A3.2. 

The results of the analysis of the NOx emissions load-dependence appear in Section A3.3 and a 
 48

discussion of the observed load-dependence impacts in the context of relevant literature and the 

2002 Draft Technical Report appear in Section A3.4. 

 In the 2002 Draft Technical Report, we focused our analysis on data from heavy-duty 

highway engines, since this data was the most abundant in our database and since it was unclear 

to what extent testing on a chassis dynamometer might differ from testing on an engine 

dynamometer. However, some researchers criticized the conclusions of the report for its 

disproportionate reliance on engine data. These researchers argued that these engines may not 

behave in a manner indicative of the actual, in-use fleet or that chassis-generated data may be 

better-suited for NOx emissions testing. 

 Some researchers also criticized the conclusions of our 2002 Draft Technical Report, 

citing its disproportionate reliance on DDC engine data. These researchers argued that these 

engines may not behave in a manner indicative of the actual, in-use fleet as a whole. To help 

address these concerns, we supplemented the database for the 2002 Draft Technical Report with 

non-DDC engine data. In the current analysis, non-DDC engines represent 59.0% of all engines 

present in the supplemented database. 

 To investigate these concerns, we carried out an analysis to determine the compatibility 

of heavy-duty highway engine data with heavy-duty highway chassis data. Establishing 

compatibility between heavy-duty highway engine data and heavy-duty highway chassis data 

would allow us to make more-complete use of all emissions data in the database. In turn, this 

would allow us to perform more robust statistical analyses. The results of this engine and chassis 

data compatibility analysis are presented in Section A3.1. Section A2 contains a discussion of 

the data screening criteria and methodology used in this analysis. 

A2. Data Screening and Methodology 

 The data used in this analysis is comprised of data initially used in our 2002 Draft 

Technical Report, supplemented by pertinent data published between 2002 and 2007. The 

supplemental data included late model year engines, vehicles, and technology groups. A list of 

data sources used in this analysis appears in the appendix to this document. 

 A criticism raised by the 2002 Draft Technical report was that its analysis relied too 

heavily upon data from early model year engines and that these engines may not behave in a 

manner indicative of the actual, in-use fleet as a whole. To help address this concern, we 

supplemented the existing database of over 800 observations with approximately 560 additional 

observations comprised of late model year engines, vehicle, and technology groups. 

 Candidate data were first screened to verify that they met EPA data QC/QA requirements 

as well as criteria consistent with the goals of the analysis before inclusion into the database (See 

Section II of the 2002 Draft Technical Report for a discussion of EPA data QC/QA 

considerations). New data meeting these criteria were entered into the database developed for 

the 2002 Draft Technical Report. These criteria are described in Section A2.1. 
49

A2.1 Criteria for Selecting Data 

 Candidate data were screened to verify that they met criteria consistent with the goals of 

the analysis before inclusion into the database. For instance, the analysis was limited to No. 1 

and No. 2 diesel fuel and related blends that can be used in typical heavy-duty diesel engines 

without engine modifications. As a result, all emulsions and non-biodiesel oxygenated blends 

with more than 20 vol% oxygenate were excluded from the final database used in the analysis. 

Also, synthetic fuels, such as those produced using the Fischer-Tropsch process, rather than 

refinery streams, were excluded from the final database. 

 We also limited this study to vehicles and engines that had already been sold 

commercially or had a high probability of being sold in the future. Vehicles and engines with 

experimental technologies that had no immediate plans for commercialization, such as those with 

innovative combustion chamber geometries, were excluded from the database. Likewise, singlecylinder research engines were excluded from consideration, even though the associated full-size 

parent engine might have been appropriately included in the database, had it been tested. Singlecylinder engines do not appear in heavy-duty applications. By definition, such engines have 

lower total horsepower and displacement, both of which may influence the way in which 

biodiesel impacts emissions. 

 The pairing of diesel and biodiesel fuels used in a particular study also played a role in 

determining if data from that study would be included in our analysis. For example, we excluded 

data from all studies that did not test at least two different biodiesel concentrations on the same 

engine, one of which could be 0 vol% biodiesel. 

 There were a number of instances in which data from one study was repeated in other 

studies. This might occur if the authors published the same dataset in multiple scientific journals 

to maximize exposure, or if the authors presented a previously-published set of data in a new 

publication for the purposes of comparing the two datasets. Such duplicative data was also 

excluded from our database. 

 Also, each prospective data source was screened to verify that it contained raw, not 

aggregated, data. In cases where raw data was not published in a study, attempts were made to 

obtain it from the study author(s). Raw data obtained from author(s) were included in our 

database after successful screening. 

A2.2 Criteria for Selecting Test Cycles 

 We selected cycles which were representative of actual, in-use operating conditions. 

While the Federal Test Procedure (FTP) transient cycle most-closely reflects actual, in-use 

operating conditions, we included data from a number of other studies that used atypical test 

cycles which were adequately comprehensive in their number, selection of modes, and/or in their 

transient speed-load traces, so that the resulting emission measurements may still be informative. 
 50

 Data collected under test cycles that were unique, contained only a single steady-state 

mode, or used two- or three-nonstandard modes for testing, were typically excluded from the 

database. Non-FTP/UDDS test cycles represented about 24 percent of all data in the database. 

 A total of eight different cycles, with two variants, representing a variety of load levels 

were included in our database. A description of the test cycles included in our analysis appears 

below. 

• AVL 8-Mode Test – An eight-mode steady-state engine test procedure, designed to 

correlate with FTP cycle exhaust emission results. Only NOx emissions data generated 

by the AVL 8-Mode test was included in our database. 

• Combined International Local Cycle and Commuter (CILCC) – A transient cycle 

developed by NREL for testing Class 4 to Class 6 vehicles. It is intended to simulate 

urban delivery driving conditions for heavy-duty vehicles. 

• City-Suburban Heavy-Vehicle Cycle (CSHVC) – A transient cycle developed by West 

Virginia University. It is intended to simulate low-speed urban/ suburban driving 

conditions of heavy-duty vehicles and is punctuated with frequent stops. 

• Freeway Cycle – A transient cycle intended to simulate four-lane highway driving 

conditions of heavy-duty vehicles, including entrance and exit ramps. 

• Federal Test Procedure (FTP) – The heavy-duty transient cycle currently used by EPA 

for emission, certification, and other testing of heavy-duty on-road engines; the cycle 

most-closely reflects actual, in-use operating conditions and was developed to simulate a 

variety of heavy-duty truck and bus driving conditions in cities and on expressways. 

• Highway Cycle (HWY) – A high-speed highway cruise cycle based on the Heavy 

Heavy-Duty Diesel Truck chassis cycle developed by the California Air Resources Board 

and previously used in the Coordinating Research Council E-55 program. 

• Rowan University Composite School Bus Cycle (RUCSBC) – A school bus cycle 

developed by Rowan University. 

• Urban Dynamometer Driving Schedule (UDDS) – A heavy-duty chassis dynamometer 

test. Our database includes data from the UDDS cycle and two variants simulating light 

(6,000 lbs) and heavy (28,000 lbs) test weight conditions. 

The summary of the test cycles included in our analysis appears in Table A2-A. 
51

Table A2-A. Test cycles included in this analysis 

Test Cycle Description Duration

AVL 8 Eight-mode steadystate cycle n/a 

CILCC Heavy-duty urban 

delivery cycle 

53 min 

12 sec 

CSHVC 

Heavy-duty citysuburb low-speed 

cycle 

28 min 

20 sec 

Freeway Heavy-duty highway 

cycle 

27 min 

20 sec 

FTP Heavy-duty engine 

certification cycle 20 min 

HWY High-speed cruise 

cycle from CRC E-55 

12 min 

40 sec 

RUCSBC School bus cycle 21 min 

50 sec 

UDDS Heavy-duty chassis 

cycle 

17 min 

40 sec 

UDDS 6k UDDS variant based 

on EPA data 

17 min 

40 sec 

UDDS 28k UDDS variant based 

on CRC E-55 data 

17 min 

40 sec 

A2.3 Criteria for Selecting Feedstock Materials 

 Biodiesel fuel can be produced from a wide variety of feedstock materials. While the 

studies that comprise our database included only a portion of the many feedstock materials 

possible, they do represent the most-common feedstock materials. The biodiesel feedstock 

materials found in our database and their percentages are listed in Table A2-B. 
 52

Table A2-B. 

Biodiesel feedstock material observations in the database 

Feedstock 

Materials 

Number of 

Observations 

Percentage of 

Observations 

Soybean 556 77.1% 

Rapeseed/Canola 95 13.2% 

Grease* 42 5.8% 

Tallow 19 2.6% 

Coconut 6 0.8% 

Lard 3 0.4% 

 * Includes high free fatty acid (HFFA) and low free fatty acid (LFFA) 

 Given the limited data available for some feedstock materials, we aggregated all biodiesel 

feedstock materials into three general categories: plant-based biodiesel, soybean-based biodiesel 

(a subset of plant-based biodiesel), and animal-based biodiesel (See Table A2-C for a listing of

biodiesel feedstock materials aggregated into the categories used in our database). 

Table A2-C. 

Biodiesel feedstock materials aggregated 

into categories used in the database 

Aggregated Feedstock 

Material Category 

Number of Observations 

in Category 

Plant-based 657 

Soybean-based 556 

Animal-based 64 

A2.4 Overview of methodology 

 This section summarizes the statistical approach used in this analysis, which employed 

the SAS/STAT software procedure PROC MIXED. This procedure can treat some variables as 

fixed-effects and others as random-effects. 

 For instance, the NOx fixed-effect was expressed as a function of percent biodiesel (0 or 

20 vol%), vehicle class (Class 1-2a or Class 2b-8), the interaction of percent biodiesel and 
53

vehicle class, test cell type (chassis test cell or engine test cell), and the interaction between test 

cell type and percent biodiesel. Each fixed-effect term is tested and removed if found not 

significant. Additional fixed-effect terms were added to the model when examining DDC and 

non-DDC engines. The random-effects examined were the test cell type and its interaction with 

percent biodiesel, test cycle, and the biodiesel source. 

 After creating the initial model, the distribution of mixed-model residuals are examined; 

residuals with absolute values greater than four standard deviations from a mean of 0 are 

considered outliers and removed from further consideration. 

 The final model evaluates the statistical significance of the difference between fuels 

containing 20 vol% biodiesel and the base fuel, containing no biodiesel. A significance criterion 

of p < 0.05 was used for all analysis. See Section II of the 2002 Draft Technical Report for 

additional discussion and derivations. 

A3. Results 

 This section contains the results of the biodiesel emissions impact analysis described in 

Section A2. The results of the analysis of the compatibility of heavy-duty highway chassis and 

engine data appear in Section A3.1. The results of the analysis of the seven fuel-cycle 

combinations appear in Section A3.2, including the analysis of DDC engines versus non-DDC 

engines. The results of the analysis of the NOx emissions load-dependence appear in Section 

A3.3 and a discussion of the observed load-dependence impacts placed in the context of relevant 

literature and the 2002 Draft Technical Report appear in Section A3.4. 

A3.1 Compatibility of Heavy-duty Highway Chassis and Engine Data 

 

 The primary objective of the analysis was to quantify the impacts of biodiesel fuels. One 

aspect of the analysis was to determine if heavy-duty highway emissions engine data in our 

database was comparable to heavy-duty highway chassis data for purposes of our statistical 

analysis. Much of the database (66%) consisted of heavy-duty highway engine data, with the 

balance of the data comprising heavy-duty highway chassis data. Establishing compatibility 

between engine and chassis data would allow us to make more complete use of all emissions data 

in the database, which, in turn, would allow us to perform more robust statistical analyses. 

 Moreover, some researchers criticized the conclusions of our 2002 Draft Technical 

Report, citing its disproportionate reliance on engine data. These researchers argued that these 

engines may not behave in a manner indicative of the actual, in-use fleet as a whole or that 

chassis-generated data might be better-suited for purposes of biodiesel emissions testing. To 

investigate these claims, we undertook an analysis to determine the compatibility of heavy-duty 

highway engine data with heavy-duty highway vehicle data. 

 Using a significance level of p < 0.05 for all statistical analysis, engine data was found to 

be statistically comparable to chassis data for NOx and CO emissions. This finding is supported 

by the research of NREL, whose examination of published data suggests that there exists no 

discrepancy between engine and vehicle testing data (See NREL Milestone 10.4). See Table A3-
 54

A for a summary of fuel-cycle combinations for which heavy-duty highway engine data was 

statistically comparable to heavy-duty highway chassis data for regulated pollutants. 

Table A3-A. 

Fuel-cycle combinations for which heavy-duty highway 

engine data was statistically comparable to heavy-duty 

highway chassis data for regulated pollutants 

Regulated Pollutants 

NOx PM CO HC 

Case 1 x x 

Case 2 x x 

Case 3 x x 

Case 4 x x 

Case 5a x x 

Case 5b x x 

Fuel-Cycles 

Case 5c x x 

 x Denotes heavy-duty highway engine data that is statistically comparable 

 to heavy-duty highway chassis data. 

 

 Emissions of PM and CO for heavy-duty highway engines and chasses were not found to 

be statistically comparable to each other for any of the seven fuel-cycle combinations. Based 

upon our experience with chassis test cells, it is difficult to accurately quantify PM exhaust 

emissions, as chassis-based testing is often deficient and non-standardized vis-à-vis 40CFR86-

2007 and 40CFR1065 for test specification and test equipment, respectively. Deficiencies 

associated with non-standardized chassis test cells may produce high test-to-test variability. 

Likewise, CO emissions are difficult to accurately quantify on both heavy-duty engine and 

chassis test cells and may also produce high test-to-test variability. 

 High test-to-test variability curtails the ability to accurately capture and discern small 

differences in exhaust emissions, particularly PM and CO exhaust emissions. This variability 

may help to explain why engine and chassis data are not comparable in our analysis for CO and 

PM emissions. 

 In cases where heavy-duty highway engine data is statistically comparable to heavy-duty 

highway chassis data, engine and chassis data are pooled to produce the appropriate statistic. In 

other cases, we believe that the use of engine data alone results in a more-representative statistic, 

which we report here. The results for the following analysis reflect this approach. 

A3.2 Fuel-cycle Results 

 Seven fuel-cycle combinations were identified for our statistical analysis, ranging from a 

general case, combining testing of all test cycles and all cycles and on all biodiesel fuel feedstock 
55

materials to cycles aggregated into light-, medium-, and heavy-duty test cycle categories, which 

were run exclusively on 20 vol% soybean-based biodiesel fuel. Heavy-duty highway engine and 

chassis emissions data were statistically comparable for NOx and HC and were subsequently 

pooled for our analysis. Heavy-duty highway engine and chassis emissions data were not 

statistically comparable for PM and CO, so only engine results are presented here. The results 

for each of the seven fuel-cycle combinations appear below. All results presented are 

statistically significant at a significance level of p < 0.05. 

 Case 1: All cycles tested on all biodiesel fuels

 Our first fuel-cycle combination examined data collected on all cycles included in the 

database and from all vehicles and engines tested on both plant-based (soybean, rapeseed/canola 

and coconut) and animal-based (tallow, lard, and grease) biodiesel fuels (See Table A2-A for a 

listing of all cycles used in the Case 1, Case 2, and Case 4 analyses). 

For plant-based and animal-based biodiesel fuels, NOx emissions were found to increase 

a statistically-significant 2.0% relative to the base fuel, whereas, PM, CO, and HC emissions 

were found to decrease by 13.6%, 13.5%, and 18.7%, respectively, relative to the base fuel. 

 Case 2: All cycles tested on soybean-based biodiesel fuels

 Our second fuel-cycle combination examined all cycles specified in Case 1, but only 

involved vehicles and engines tested on soybean-based biodiesel fuels. 

 For soybean-based biodiesel, NOx emissions were found to increase by 2.2%, whereas 

PM, CO, and HC emissions were found to decrease by 15.6%, 13.8%, and 14.1%%, respectively, 

relative to the base fuel. Case 1 and Case 2 differ in their fuel composition. The biodiesel tested 

in Case 1 is composed of 20 vol% animal- and plant-based biodiesel, whereas in Case 2, the fuel 

is composed of 20 vol% soybean-based biodiesel only. The results suggest that the removal of 

animal-based and/or rapeseed/canola/coconut-based biodiesel fuel feedstock materials may have 

a slight impact on some exhaust emissions. Increases in emissions of 0.2 %, 2.0%, and 0.3% are 

observed for NOx, PM, and CO, respectively, relative to a soybean-based biodiesel discussed in 

Case 2. HC emissions decrease by 4.6% relative to a soybean-based biodiesel. 

 Several hypotheses have been advanced by researchers in an attempt to help explain the 

differences in exhaust emissions between plant-based and animal-based biodiesel feedstock 

materials (See Graboski et al. and Goetz); these are, however, outside the scope of the current 

analysis and are not discussed here. 

 Case 3: FTP and UDDS cycles tested on soybean-based biodiesel fuels

 Our third fuel-cycle combination examined only engines and vehicles tested on soybeanbased biodiesel fuel over only the FTP and UDDS cycles. Together, FTP and UDDS cycles 

comprise 76% of the database observations. 

 For soybean-based biodiesel, NOx emissions were found to increase by 3.2%, whereas 

PM, CO, and HC emissions were found to decrease by 15.6%, 15.9%, and 13.7%, respectively, 

relative to the base fuel. 
 56

 The results of this analysis suggest that the emission impacts associated with heavy-duty 

highway engines and chasses tested on 20 vol% soybean-based biodiesel and run on FTP/UDDS 

cycles produce an increase in exhaust emissions of 1.0% for NOx and 2.1% for CO, relative to 

all engine and chassis cycles run on the same fuels. HC emissions decrease by 0.4% relative to 

all engine and chassis cycles and PM emissions appear to be relatively unaffected. These results 

were statistically significant at a significance level of p < 0.05. 

As the FTP and UDDS cycles may more-closely represent actual, in-use operating 

conditions encountered by heavy-duty highway engines and vehicles, it is possible that the Case 

3 results may be a better indicator of actual, in-use biodiesel emissions impacts.

 Case 4: DDC vs. non-DDC engines tested on soybean-based biodiesel fuels

 Our fourth fuel-cycle combination separately examined DDC and non-DDC engines 

tested on the cycles specified in Case 1 and Case 2 using soybean-based biodiesel fuel. 

 Our analysis found that DDC heavy-duty engine data was statistically comparable to nonDDC heavy-duty engine data for NOx, CO, and HC emissions at a significance level of p < 0.05. 

DDC heavy-duty engines and non-DDC heavy-duty engines did not behave in a statistically 

similar manner for PM emissions, however. In this regard, the results of our analysis suggest 

that DDC heavy-duty engines behave in the same manner in which non-DDC heavy-duty 

engines behave in our database for NOx, CO, and HC emissions. As such, this finding should 

help alleviate earlier concerns that the disproportionate representation of DDC engines may 

produce results which are not indicative of the database as a whole or the in-use fleet. 

 Case 5a: Light-duty cycles tested on soybean-based biodiesel fuels

 Our fifth fuel-cycle combination examined heavy-duty engine and chassis data for lightduty cycles specified in Table A3-B and tested on soybean-based biodiesel fuel. 

 For soybean-based biodiesel tested on light-duty cycles, NOx, PM, CO, and HC 

emissions were found to decrease by 1.0%, 19.0%, 9.9%, and 14.2% respectively, relative to the 

base fuel. 
57

Table A3-B. Cycle composition by case 

 Case 5b: Medium-duty cycles tested on soybean-based biodiesel fuels

 Our sixth fuel-cycle combination examined heavy-duty engine and chassis data for 

medium-duty cycles specified in Table A3-B and tested on soybean-based biodiesel fuel. 

 For soybean-based biodiesel tested on medium-duty cycles, NOx emissions were found 

to increase by 2.5%, relative to the base fuel, whereas PM, CO, and HC emissions were found to 

decrease by 19.0%, 14.0%, and 14.2%, and respectively, relative to the base fuel. 

 Case 5c: Heavy-duty cycles tested on soybean-based biodiesel fuels

 Our seventh fuel-cycle combination examined heavy-duty engine and chassis data for 

heavy-duty cycles specified in Table A3-B and tested on soybean-based biodiesel fuel. 

 For soybean-based biodiesel tested on heavy-duty cycles, NOx emissions were found to 

increase by 5.1%, relative to the base fuel, whereas PM, CO, and HC emissions were found to 

decrease by 32.6%, 22.0%, and 14.2%, respectively, relative to the base fuel. Unlike Case 5a 

and 5b, the PM emissions results were significant and greater than those of the light-duty and 

medium-duty cases. A summary of these results appears in Table A3-C. 

Case Number Case Description Individual 

Cycles

Case 5a Light-duty cycles 

CILCC 

CSHVC 

UDDS6k

Case 5b Medium-duty 

cycles 

AVL8 (NOx) 

Freeway 

FTP 

RUCSBC 

UDDS 

UDDS28k 

Case 5c Heavy-duty cycles HWY55 
 58

Table A3-C. 

Summary of emissions results for seven fuel-cycle combinations 

for heavy-duty highway engines and chasses 

Regulated Pollutants 

NOx PM* CO* HC 

Case 1 +2.0% -13.6% -13.5%+ -18.7% 

Case 2 +2.2% -15.6% -13.8% -14.1% 

Case 3 +3.2% -15.6% -15.9% -13.7% 

Case 4 +2.4% -16.9% -13.9% -14.3% 

Case 5a -1.0% -9.9% 

Case 5b +2.5% 

-19.0% 

-14.0% 

Fuel-Cycles 

Case 5c +5.1% -32.6% -22.0% 

-14.2%

 * Only engine data. 

 + Not significant.

A3.3 Load-dependent Emissions Impacts 

 We initially identified the load-dependence of NOx emissions in heavy-duty highway 

engines in 2007 (See Sze et al.) and these results were later corroborated by Eckerle et al. The 

results of Sze et al. and Eckerle et al. were based largely upon new engine and chassis studies (as 

well as modeling efforts), which were aimed specifically at examining the load-dependent NOx 

emissions phenomenon. 

 In the current research, however, our work is retrospective insofar as we examined data 

from a broad array of pre-existing studies, none of which were designed to examine the loaddependent NOx emissions impacts. As such, this analysis occasionally suffers from the 

experimental design limitations associated with the pre-existing studies. One such limitation is 

the use of test cycles which do not realistically reflect actual, in-use operating conditions. Such 

data can skew results and obscure evidence of the load-dependence of NOx emissions. Such a 

situation is discussed in Case 5a. 

Case 5a, 5b, and 5c: Load-dependent emissions impact on NOx

 The load-dependence of NOx emissions observed in this analysis is apparent when 

comparing Case 5a (light-load cycles) to Case 5b (medium-load cycles) to Case 5c (heavy-load 

cycles). However, results for the light-load conditions in Case 5a may not be representative of 

in-use vehicle operation. 

 Case 5a: Confounding effects of lightly-loaded conditions

 The load-dependence of NOx emissions evident in the research of Sze et al. and Eckerle 

et al. was based upon medium- and heavy-duty cycles, not lightly-loaded cycles as in Case 5a. 
59

 We believe that our current findings for NOx emissions under lightly-loaded conditions 

may not be representative of the operating conditions typically encountered in actual, in-use fleet 

operations. As in-use heavy-duty highway engines and vehicles do not typically operate under 

the lightly-loaded conditions encountered in the cycles which comprise our light-duty category, 

the practical significance of the NOx emissions results for Case 5a is questionable. 

 Further, the NOx emissions results for Case 5a are also suspect when compared to Cases 

1-4 and 5b-5c, all of which indicate that there is a statistically-significant increase in NOx 

emissions of between 2.0% and 5.1%. 

 As such, we place greater significance on the results obtained under medium- (Case 5b) 

and heavy-load (Case 5c) conditions, since they more-accurately mirror typical, in-use fleet 

operations and, as a result, provide a more realistic representation of operating conditions 

encountered in-use. 

 Case 5b vs. Case 5c: Load-dependent NOx emission impacts

 Since the medium-loading conditions associated with these cycles are typical of actual, 

in-use fleet operations, these cycles provide a more realistic representation of operating 

conditions encountered by actual fleet usage. As such, we place greater significance on these 

results. 

 The difference in NOx emissions between our results here and those of other researchers 

appears to be attributable to an artifact of the selected test cycle profile. Analyzing the NOx 

emissions data as a function of load, as we do here -- as opposed to a particular test cycle profile 

-- reconciles the difference and supports the NOx emission-load-dependence hypothesis for 

heavy-duty highway engine and chasses posited by Sze et al. and corroborated by Eckerle et al. 

The discussion of load-dependent NOx emission impacts in the context of our research appears 

in Section A3.4. 

A3.4 Relevant Studies 

 

We initially identified the load-dependence of NOx emissions in heavy-duty highway 

engines in 2007 (See Sze et al.) and these results were later corroborated by Eckerle et al. The 

results of Sze et al. and Eckerle et al. were based largely upon new engine and chassis studies (as 

well as modeling efforts), which were aimed specifically at examining the load-dependent NOx 

emissions phenomenon. 

 In the current research, however, our work is retrospective insofar as we examined data 

from a broad array of pre-existing studies, none of which were designed to examine the loaddependent NOx emissions impacts. As such, this analysis occasionally suffers from the 

experimental design limitations associated with the pre-existing studies. One such limitation is 

the use of test cycles which do not realistically reflect actual, in-use operating conditions. Such 

data can skew results and obscure evidence of the load-dependence of NOx emissions. Such a 

situation is discussed in Case 5a. 
 60

2002 Draft Technical Report 

 

 In 2002, the EPA conducted a comprehensive analysis of the emission impacts of 

biodiesel using publicly available data. Entitled "A Comprehensive Analysis of Biodiesel 

Emissions Impacts on Exhaust Emissions," the 2002 Draft Technical Report made use of 

statistical regression analysis to correlate the concentration of biodiesel in conventional diesel 

fuel with changes in regulated and unregulated pollutants for heavy-duty highway engines. 

 Figure A3-A presents basic emission correlations for NOx, PM, CO, and HC developed 

in the 2002 Draft Technical Report as a function of soybean-based biodiesel concentration. 

Table A3-D presents results specifically for 20 vol% soybean-based biodiesel. 
61

Figure A3-A. 

Emission impacts from the 2002 Draft Technical Report by percent biodiesel 

content for soybean-based biodiesel added to an average base fuel 

0 20 40 60 80 100

Percent biodiesel

-80%

-70%

-60%

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

P

ercent chang

e in e

missions

NOx

HC

CO

PM

Table A3-D. 

Emission impacts from the 2002 Draft Technical Report for 

20 vol% soybean-based biodiesel added to an average base fuel 

Emissions Percent Change in 

Emissions 

NOx 

PM 

HC 

CO 

+2.0% 

-10.1% 

-21.1% 

-11.0% 

 We found that the results of the current analysis, which examined heavy-duty highway 

engine and chassis data, are consistent with the findings of our 2002 Draft Technical Report, 

which examined heavy-duty highway engine data only. Compared to the 2002 Draft Technical 

Report, NOx emissions were found to increase 2.2% while PM, HC, and CO emissions were 

found to decrease by 15.6%, 14.1%, and 13.8%, respectively, in the current study. These are 

shown in Figure A3-B as points overlaid on the results of the 2002 Draft Technical Report.
 62

Figure A3-B. 

Emission impacts from the 2002 Draft Technical Report by percent biodiesel content for 

soybean-based biodiesel added to an average base fuel with new results overlaid 

SAE paper by Sze et al. 

 

 Sze et al. conducted a series of paired fuel tests comparing certification-grade highway 

diesel fuels with 5 to 50 vol% soybean-based biodiesel blends. Each fuel pair was tested for up 

to seven transient cycles representing various load conditions, using a 2006 model year Cummins 

ISB compression ignition engine. 

 

 The authors concluded that biodiesel NOx impact on the test engine is directly 

proportional to average cycle power or fuel consumption and biodiesel content (See Figure A3-

C). 

0 20 40 60 80 100

Percent biodiesel

-80%

-70%

-60%

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

P

ercent chang

e in e

missions

NOx

HC

CO

PM
63

Figure A3-C. 

NOx emissions for 20 vol% and 50 vol% soybean-based biodiesel fuel versus average 

cycle power for various heavy-duty highway engine and chassis cycles 

 Except for the most lightly-loaded cycle, the results show statistically significant 

differences in NOx emissions for all fuel pairs. The average NOx emissions due to biodiesel 

were found to increase over each cycle, ranging from 0.9 to 6.6% for 20 vol% and 2.2 to 17.2% 

for 50 vol% biodiesel fuels. The load-dependence of NOx emissions observed by Sze et al. is 

consistent with the findings presented in this report for Cases 5a, 5b, and 5c as well as those of 

Eckerle et al. 

 To further elucidate the load-dependent nature of NOx emissions, Sze et al. reanalyzed 

chassis-generated NOx emissions data from NREL as a function of fuel consumption (a 

surrogate for average cycle power) and found it to be in close agreement with EPA engine test 

data. This is depicted in Figure A3-D. Data from NREL using the same engines tested instead 

on a chassis dynamometer are also shown in the figure and follow the same trend, with an R2 = 

0.99 with and without the inclusion of the NREL dataset. 

R2 = 0.99

R2

 = 0.99

0

5

10

15

20

25

30

35

40

45

0 20 40 60 80 100 120 140 160

Average Cycle Power (hp)

NOx (Biodiesel Blend) - NOx (B0), (g/hr)

B20 HWY

B20 FTP

B20 WHTC

B20 UDDS 28k

B20 UDDS 6k

B20 HWY 172

B20 NRTC

B50 HWY

B50 FTP

B50 UDDS 28k

B50 UDDS 6k
 64

Figure A3-D. 

NOx emissions for 20 vol% soybean-based biodiesel fuel versus average cycle power for 

various heavy-duty highway engine and chassis cycles, including NREL chassis testing data 

SAE paper by Eckerle et al. 

 The load-dependence of NOx emissions was also examined by Eckerle et al., who 

generated engine data using 20 vol% soybean-based biodiesel to calibrate chemical kinetic 

models. These models were used to examine NOx production during the combustion process. 

The authors concluded that the NOx effect associated with burning biodiesel blends over a duty 

cycle depends, in part, on the duty cycle average power and that higher duty cycle average power 

corresponded to larger increases in NOx emissions. 

R2 = 0.99

R2

 = 0.996

0

5

10

15

20

25

30

35

40

45

0 5 10 15 20 25 30

Fuel Consumption (kg/hr)

NOx (Biodiesel Blend) - NOx (B0), (g/hr)

B20 NREL chassis data

B20 HWY

B20 FTP

B20 WHTC

B20 UDDS 28k

B20 UDDS 6k

B20 HWY 172

B20 NRTC

B50 HWY

B50 FTP

B50 UDDS 28k

B50 UDDS 6k

With NREL chassis data

Without NREL chassis data

R2 = 0.99 
65

References 

Studies included in database 

Aako P. et al., "Emission Performance of Selected Biodiesel Fuels - VTT's Contribution" 

Research Report ENE/33/2000, October 2000 

Alam M. et al., "Combustion and Emissions Performance of Low Sulfur, Ultra Low Sulfur and 

Biodiesel Blends in a DI Diesel Engine," SAE paper no. 2004-01-3024 

Bouché, T., M. Hinz, R. Pitterman, "Optimising Tractor CI Engines for Biodiesel Operation," 

SAE paper no. 2000-01-1969 

Callahan, T.J., C.A. Sharp, "Evaluation of Methyl Soyate/Diesel Fuel Blends as a Fuel for Diesel 

Engines," Southwest Research Institute Final Report to the American Biofuels Association, 

December 1993 

Clark, N.N., C.M. Atkinson, G.J. Thompson, R.D. Nine, "Transient Emissions Comparisons of 

Alternative Compression Ignition Fuels," SAE paper no. 1999-01-1117 

Clark N. N. et al., "Class 8 Truck Emission Testing: Effects of Test Cycles and Data on 

Biodiesel Operation," ASAE, 1999, 42(5), 1211-1219 

Durbin, T.D., J.R. Collins, J.M. Norbeck, M.R. Smith, "Evaluation of the Effects of Alternative 

Diesel Fuel Formulations on Exhaust Emissions Rates and Reactivity," Final Report from the 

Center for Environmental Research and Technology, University of California, April 1999 

Durbin, T.D., et al., Final Report: "Evaluation of the Effects of Biodiesel and Biodiesel Blends 

on Exhaust Emission Rates and Reactivity - 2", Center for Environmental Research and 

Technology; College of Engineering; University of California, Riverside, August 2001 

Durbin, T.D., J.M. Norbeck, “Effects of Biodiesel Blends and Arco EC-Diesel on Emissions 

from Light Heavy-Duty Diesel Vehicles,” Environ. Sci. Technol., 2002, 36, 1686-1691 

Durbin T. D. et al., "Effects of Biodiesel, Biodiesel Blends, and a Synthetic Diesel on Emissions 

from Light Heavy-Duty Diesel Vehicles," Environ. Sci. Technol., 2000, 34, 349-355 

Environment Canada, "Emissions Characterization of a Caterpillar 3126E Equipped with a 

Prototype SCRT System with Ultra Low Sulfur Diesel and a Biodiesel Blend," ERMD Report 

#2005-32, 2005 

Eckerle, W., Lyford-Pike, E., Stanton, D., LaPointe, L., Whitacre, S., Wall, J., “Effects of 

Methyl Ester Biodiesel Blends on NOx Emissions,” SAE paper no. 2008-01-0078. 

Fosseen, D., "DDC 6V-71N Emission Testing on Diesel and Biodiesel Blend," Fosseen 

Manufacturing and Development, Ltd., report no. NSDB4F15, July 14, 1994 
 66

Fosseen, D., "DDC 6V-92TA MU1 Coach Upgrade Emission Optimization on 20%/80% 

Soy/Diesel Blend," Fosseen Manufacturing & Development, Ltd., report no. 260-2 and 24 1-1, 

September 30, 1994 

Frank B.P. et al., "A Study of the Effects of Fuel Type and Emission Control Systems on 

Regulated Gaseous Emissions from Heavy-Duty Diesel Engines," SAE paper no. 2004-01-1085 

Goetz, W., "Evaluation of Methyl Soyate/Diesel Blend in a DDC 6V-92TA Engine: 

Optimization of NOx Emissions," Ortech International, Report No. 93-E14-36, July 20, 1993 

Goetz, W., "Evaluation of a Tallow/Diesel Blend in a DDC 6V-92TA Engine," Ortech 

International report no. 93-E14-37, July 21, 1993 

Graboski, M.S., J.D. Ross, R.L. McCormick, "Transient Emissions from No. 2 Diesel and 

Biodiesel Blends in a DDC Series 60 Engine," SAE paper no. 961166 

Graboski, M.S., R.L. McCormick, T.L. Alleman, A.M. Herring, "The Effect of Biodiesel 

Composition on Engine Emissions from a DDC Series 60 Diesel Engine," Colorado School of 

Mines, Final Report to National Renewable Energy Laboratory, June 8, 2000 

Hansen, K.F., M.G. Jensen, "Chemical and Biological Characteristics of Exhaust Emissions from 

a DI Diesel Engine Fuelled with Rapeseed Oil Methyl Ester (RME)," SAE paper no. 971689 

Holden, Bruce et al., Final Report: "Effect of Biodiesel on Diesel Engine Nitrogen Oxide and 

Other Regulated Emissions," Naval Facilities Engineering Command (NAVFAC) Technical 

Report TR-2275-ENV, May 2006 

Howes, P., G. Rideout, "Evaluation of Biodiesel in an Urban Transit Bus Powered by a 1988 

DDECII6V92 TA Engine," National Biodiesel Board, MSED Report # 96-26743-1, June 1995 

Howes, P., G. Rideout, "Evaluation of Biodiesel in an Urban Transit Bus Powered by a 1981 

DDCC8V71 Engine," National Biodiesel Board, MSED Report # 95-26743-2 

Liotta, F.J., D.M. Montalvo, "The Effect of Oxygenated Fuels on Emissions from a Modern 

Heavy-Duty Diesel Engine," SAE paper no. 932734 

Lyons D. W., "Biodiesel Fuel Comparison Final Data Report for Washington Metropolitan Area 

Transit Authority," West Virginia University, August 2002 

Manicom, B., C. Green, W. Goetz, "Methyl Soyate Evaluation of Various Diesel Blends in a 

DDC 6V-92 TA Engine," Ortech International, April 21, 1993 

Marshall, W., L.G. Schumacher, S. Howell, "Engine Exhaust Emissions Evaluation of a 

Cummins L10E When Fueled With a Biodiesel Blend," University of Missouri 
67

McCormick, R.L., J.D. Ross, M.S. Graboski, "Effect of Several Oxygenates on Regulated 

Emissions from Heavy-Duty Diesel Engines," Environ. Sci. Technol., 1997, 31, 1144-1150 

McCormick, R.L., J.R. Alvarez, M.S. Graboski, "NOx Solutions for Biodiesel," Colorado School 

of Mines, August 31, 2001 

McCormick R.L. et al., "Fuel Additive and Blending Approaches to Reducing NOx Emissions 

from Biodiesel," SAE paper no. 2002-01-1658 

McCormick R.L. et al., "Regulated Emissions from Biodiesel Tested in Heavy-Duty Engines 

Meeting 2004 Emission Standards," SAE paper no. 2005-01-2200 

McCormick, R.L. et al., "Effects of Biodiesel Blends on Vehicle Emissions, FY 2006 Annual 

Operating Plan Milestone 10.4," October 2006 

McDonald, J.F., D.L. Purcell, B.T. McClure, D.B. Kittelson, "Emissions Characteristics of Soy 

Methyl Ester Fuels in an IDI Compression Ignition Engine," SAE paper no. 950400 

McGill, R., Storey, J., Wagner, R., Irick, D., Aakko, P., Westerholm, M., Nylund, N., Lappi, M., 

“Emission Performance of Selected Biodiesel Fuels,” SAE paper no. 2003-01-1866 

National Resources Canada, "National Resources Canada/Fiba Canning - Biodiesel 

Freightliners," National Resources Canada draft report, October 24, 2006 

National Institute for Petroleum and Energy Research, "Effects of Methyl Esters of Tallow and 

Grease on Exhaust Emissions and Performance of a Cummins L10 Engine," September 16, 1993 

ORYXE Energy International, Inc., Biodiesel Emissions Test Summary, ORYXE presentation, 

2006 

Peterson, C., D. Reece, J. Thompson, S. Beck, C. Chase, "Development of Biodiesel for Use in 

High Speed Diesel Engines," University of Idaho, presentation at Sixth National Bioenergy 

Conference, Oct. 2-6, 1994 

Peterson, C.L., D.L. Reece, "Emissions Tests with an On-Road Vehicle Fueled with Methyl and 

Ethyl Esters of Rapeseed Oil," ASAE paper no. 946532 

Peterson C. L., et al., "The Effect of Biodiesel Feedstock on Regulated Emissions in Chassis 

Dynamometer Tests of a Pickup Truck," ASAE, 2000, 43 (6), 1371-1381 

Peterson, C.L., D.L. Reece, "Emissions Testing with Blends of Esters of Rapeseed Oil Fuel With 

and Without a Catalytic Converter," SAE paper no. 961114 

Peterson, C.L., "Truck-In-The-Park Biodiesel Demonstration with Yellowstone National Park," 

University of Idaho, August 1999 
 68

Rantanen, L., S. Mikkonen, L. Nylund, P. Kociba, M. Lappi, N. Nylund, "Effect of Fuel on the 

Regulated, Unregulated and Mutagenic Emissions of DI Diesel Engines," SAE paper no. 932686 

Schumacher, L.G., S.C. Borgelt, W.G. Hires, D. Fosseen, W. Goetz, "Fueling Diesel Engines 

with Blends of Methyl Ester Soybean Oil and Diesel Fuel," University of Missouri. See 

http://web.missouri.edu/~pavt0689/ASAED94.htm. 

Schumacher, L., S.C. Borgelt, W.G. Hires, W. Wetherell, A. Nevils, "100,000 Miles of Fueling 

5.9L Cummins Engines with 100% biodiesel," SAE paper no. 962233 

Schumacher, L., N.N. Clark, D.W. Lyons, W. Marshall, “Diesel Engine Exhaust Emissions 

Evaluation of Biodiesel Blends Using a Cummins L10E Engine,” ASAE, 44(6), 1461-1464 

Sharp, C.A., "Transient Emissions Testing of Biodiesel in a DDC 6V-92TA DDEC Engine," 

Southwest Research Institute, Final Report to the National Biodiesel Board, October 1994 

Sharp, C.A., "Transient Emissions Testing of Biodiesel and Other Additives in a DDC Series 60 

Engine," Southwest Research Institute, Final Report to the National Biodiesel Board, December 

1994 

Sharp, C.A., "Emissions and Lubricity Evaluation of Rapeseed Derived Biodiesel Fuels," 

Southwest Research Institute, Final Report for Montana Department of Environmental Quality, 

November 1996 

Sharp, C.A., "Characterization of Biodiesel Exhaust Emissions for EPA 211(b)," Southwest 

Research Institute report no. 08-1039A, January 1998 

Sharp, C.A., S.A. Howell, J. Jobe, "The Effect of Biodiesel Fuels on transient Emissions from 

Modern Diesel Engines, Part I Regulated Emissions and Performance," SAE paper no. 2000-01-

1967 

Sirman, M.B., E.C. Owens, K.A. Whitney, "Emissions Comparison of Alternative Fuels in an 

Advanced Automotive Diesel Engine," Southwest Research Institute, AD A353968/PAA, 

November 1998 

Smith, J.A., D.L. Endicott, R.R. Graze, "Biodiesel Engine Performance and Emissions Testing," 

Caterpillar Technical Center, May 1998 

Souligny M. et al., "Heavy-Duty Engine Performance and Comparative Emission Measurements 

for Different Biodiesel Blends Used in the Montreal Project," SAE paper no. 2004-01-1861 

Spataru, A., C. Romig, "Emissions and Engine Performance from Blends of Soya and Canola 

Methyl Ester with ARB #2 Diesel in a DDC 6V92TA MUI Engine," SAE paper no. 952388 

Starr, M.E., "Influence on Transient Emissions at Various Injection Timings, Using Cetane 

Improvers, Bio-Diesel, and Low Aromatic Fuels," SAE paper no. 972904 
69

Stotler, R.W., D.M. Human, "Transient Emission Evaluation of Biodiesel Fuel Blend in a 1987 

Cummins L10 and DDC 6V-92-TA," Engineering Test Services, report no. ETS-95-128, Nov. 

30, 1995. 

Sze, C., Whinihan, J, Olson, B., Schenk, C., Sobotowski, R., “Impact of Test Cycle and 

Biodiesel Concentration on Emissions,” SAE paper no. 2007-01-4040. 

Ullman, T.L., C.T. Hare, T.M. Baines, "Heavy-Duty Diesel Emissions as a Function of Alternate 

Fuels," SAE paper no. 830377. 

Wang W. G., "Emissions from Nine Heavy-Duty Trucks Fueled by Diesel and Biodiesel Blend 

Without Engine Modification," Environ. Sci. Technol., 2000, 34, 933-939. 

Studies not included because data collected on single cylinder/experimental engine 

Murayama, T., Y. Oh, A. Kido, T. Chikahisa, N. Miyamoto, K. Itow, "Effects of Super Heating 

of Heavy Fuels on Combustion and Performance in DI Diesel Engines," SAE paper no. 860306 

Murayama, T., Y. Oh, N. Miyamoto, T. Chikahisa, N. Takagi, K. Itow, "Low Carbon Flower 

Buildup, Low Smoke, and Efficient Diesel Operation with Vegetable Oils by Conversion to 

Mono-Esters and Blending with Diesel Oil or Alcohols," SAE paper no. 841161 

Shaheed, A., E. Swain, "Performance and Exhaust Emission Evaluation of a Small Diesel Engine 

Fuelled with Coconut Oil Methyl Esters," SAE paper no. 981156 

Suda, K.J., "Vegetable Oil or Diesel Fuel - A Flexible Option," SAE paper no. 840004 

Ziejewski, M., H.J. Goettler, "Comparative Analysis of the Exhaust Emissions for Vegetable Oil 

Based Alternative Fuels," SAE paper no. 920195 

Studies not included because data not readily available 

Alfuso. S., M. Auriemma, G. Police, M.V. Prati, "The Effect of Methyl-Ester of Rapeseed Oil on 

Combustion and Emissions of DI Diesel Engines," SAE paper no. 932801 

Hemmerlain, N., V. Korte, H. Richter, G. Schröder, "Performance, Exhaust Emissions and 

Durability of Modern Diesel Engines Running on Rapeseed Oil," SAE paper no. 910848 

Humke, A.L., N.J. Barsic, "Performance and Emissions Characteristics of a Naturally Aspirated 

Diesel Engine with Vegetable Oil Fuels - (Part 2)," SAE paper no. 810955 

Knothe, G., C.A. Sharp, T.W Ryan, “Exhaust Emissions of Biodiesel, Petrodiesel, Neat Methly 

Esters, and Alkanes in a New Technology Engine,” Energy and Fuels, 2006, 20, 403-408 

Lapuerta, M., Armas, O., Ballesteros, R., Fernandez, J., "Diesel Emissions from Biofuels 

Derived from Spanish Potential Vegetable Oils," Fuel, 2005, 84(6), 773-780 
 70

Last, R.J., M. Krüger, M. Dürnholz, "Emissions and Performance Characteristics of a 4-Stroke, 

Direct Injected Diesel Engine Fueled with Blend of Biodiesel and Low Sulfur Diesel Fuel," SAE 

paper no. 950054 

Ma, W., L.I. Leviticus, F.G. Ullman, "On-Line Measurement of Formaldehyde in Tailpipe 

Emissions by Tunable Diode Laser Spectroscopy," SAE paper no. 941702 

Martin, B., P. Aakko, D. Beckman, N. D. Giacomo, F. Giavazzi, "Influence of Future Fuel 

Formulations on Diesel Engine Emissions - A Joint European Study," SAE paper no. 972966 

McDonald, J.F., "Evaluation of a Yellow Grease Methyl Ester and Petroleum Diesel Fuel 

Blend," University of Minnesota Final Report to the Agricultural Utilization Research Institute, 

August 11, 1997 

Montagne, X., "Introduction of Rapeseed Methyl Ester in Diesel Fuel - The French National 

Program," SAE paper no. 962065 

Reece, D.L., C.L. Peterson, "Biodiesel Testing in Two On-Road Pickups," SAE paper no. 

952757 

Staat, F., P. Gateau, "The Effects of Rapeseed Oil Methyl Ester on Diesel Engine Performance, 

Exhaust Emissions and Long-Term Behavior - A Summary of Three Years of Experimentation," 

SAE paper no. 950053 

Wang, W.G., D.W. Lyons, N.N. Clark, M. Gautam, "Emissions from Nine Heavy Trucks Fueled 

by Diesel and Biodiesel Blend without Engine Modification," Environ. Sci. Technol., 2000, 34, 

933-939 

Studies not included because test cycle nonstandard/unrepresentative 

Adelman, A.J., "Emission Evaluation Test Report for a Comparative Analysis of Emissions 

Among Petroleum Diesel and Biodiesel Blends fired in a Large Diesel Engine," AirNova, Inc., 

January 1998 

Akasaka, Y., T. Suzuki, Y. Sakurai, "Exhaust Emissions of a DI Diesel Engine Fueled with 

Blends of Biodiesel and Low Sulfur Diesel Fuel," SAE paper no. 972998 

Bagley, S.T., L.D. Gratz, J.H. Johnson, J.F. McDonald, "Effects of an Oxidation Catalytic 

Converter and a Biodiesel Fuel on the Chemical, Biological, and Particulate Size Characteristics 

of Emissions from an IDI Diesel Engine," Michigan Technological University, December 1995 

Chang, D.Y.Z., J.H. Van Gerpen, "Fuel Properties and Engine Performance for Biodiesel 

Prepared from Modified Feedstocks," SAE paper no. 971684 
71

Chang, D.Y., J.H. Van Gerpen, "Determination of Particulate and Unburned Hydrocarbon 

Emissions from Diesel Engines Fueled with Biodiesel," SAE paper no. 982527 

Choi, C.Y., G.R. Bower, R.D. Reitz, "Effects of Biodiesel Blended Fuels and Multiple Injections 

on D.I. Diesel Engines," SAE paper no. 970218 

Czerwinski, J., "Performance of HD-DI-Diesel Engine with Addition of Ethanol and Rapeseed 

Oil," SAE paper no. 940545 

Desantes, J.M., J. Arrègle, S. Ruiz, A. Delage, "Characterization of the Injection-Combustion 

Process in a D.I. Diesel Engine Running with Rape Oil Methyl Ester," SAE paper no. 1999-01-

1497 

Fort, E.F., P.N. Blumberg, H.E. Staph, J.J. Staudt, "Evaluation of Cottonseed Oil as Diesel Fuel," 

SAE paper no. 820317 

Jacobus, M.J., S.M. Geyer, S.S. Lestz, W.D. Taylor, T.H. Risby, "Single-Cylinder Diesel Engine 

Study of Four Vegetable Oils," SAE paper no. 831743 

Masjuki, H., M.Z. Abdulmuin, H.S. Sii, "Investigations on Pre-Heated Palm Oil Methyl Esters in 

the Diesel Engine," IMechE 1996, Part A: Journal of Power and Energy 

Needham, J.R., D.M. Doyle, "The Combustion and Ignition Quality of Alternative Fuels in Light 

Duty Diesels," SAE paper no. 852101 

Schmidt, K., J. Van Gerpen, "The Effect of Biodiesel Fuel Composition on Diesel Combustion 

and Emissions," SAE paper no. 961086 

Scholl, K.W., S.C. Sorenson, "Combustion of Soybean Oil Methyl Ester in a Direct Injection 

Diesel Engine," SAE paper no. 930934 

Schramm, J., I. Foldager, N. Olsen, L. Gratz, "Emissions from a Diesel Vehicle Operated on 

Alternative Fuels in Copenhagen," SAE paper no. 1999-01-3603 

Schröder, O., J. Krahl, A. Munack, J. Krahl, J. Bünger, "Environmental and Health Effects 

Caused By the Use of Biodiesel," SAE paper no. 1999-01-3561 

Senatore, A., M. Cardone, V. Rocco, M.V. Prati, "A Comparative Analysis of Combustion 

Process in D.I. Diesel Engine Fueled with Biodiesel and Diesel Fuel," SAE paper no. 2000-01-

0691 

Uchida, M., Y. Akasaka, "A Comparison of Emissions from Clean Diesel Fuels," SAE paper no. 

1999-01-1121 

Zhang, Y., J.H. Van Gerpen, "Combustion Analysis of Esters of Soybean Oil in a Diesel 

Engine," SAE paper no. 960765 
 72

Studies not included because they lack new emissions data for regulated pollutants 

Culshaw, F.A., "The Potential of 'Biodiesel' from Oilseed Rape," IMechE 1993, Part A: Journal 

of Power and Energy 

Durbin, T.D., J.R. Collins, H. Galdamez, J.M. Norbeck, M.R. Smith, R.D. Wilson, T. 

Younglove, "Evaluation of the Effects of Biodiesel Fuel on Emissions from Heavy-Duty NonRoad Engines," University of California Final Report submitted to South Coast Air Quality 

Management District, May 2000 

Peterson, C.L., D.L. Auld, "Technical Overview of Vegetable Oil as a Transportation Fuel," 

University of Idaho, 1991 

Sharp, C.A., S.A. Howell, J. Jobe, "The Effect of Biodiesel Fuels on Transient Emissions from 

Modern Diesel Engines, Part II Unregulated Emissions and Chemical Characterization," SAE 

paper no. 2000-01-1968 

Exclusion of duplicate datasets 

Colorado Institute for Fuels and High Altitude Engine Research, "Emissions from Biodiesel 

Blends and Neat Biodiesel from a 1991 Model Series 60 Engine Operating at High Altitude," 

Final Report to National Renewable Energy Laboratory, September 1994 

Note: CO2 values were not duplicative. 

Peterson, C.L., D.L. Reece, "Emissions Testing with Blends of Esters of Rapeseed Oil Fuel With 

and Without a Catalytic Converter," SAE paper no. 961114 

Note: Only Table 6 data is duplicative. 

Taberski, J.S., C.L. Peterson, "Dynamometer Emissions test Comparisons on a 5.9L Direct 

Injected Diesel Powered Pickup," BioEnergy '98: Expanding BioEnergy Partnerships 

Taberski, J.S., C.L. Peterson, J. Thompson, H. Haines, "Using Biodiesel in Yellowstone National 

Park - Final Report of the Truck in the Park Project," SAE paper no. 1999-01-2798 

McCormick, R.L., M.S. Graboski, T.L. Alleman, A.M. Herring, "Impact of Biodiesel Source 

Material and Chemical Structure on Emissions of Criteria Pollutants from a Heavy-Duty 

Engine," Environ. Sci. Technol., 2001, 35, 1742-1747 

Studies not included for other reasons 

Watts, W.F., M. Spears, J Johnson, "Evaluation of Biodiesel Fuel and Oxidation Catalyst in an 

Underground Metal Mine," University of Minnesota, September 24, 1998 

Reason: Emission measurements were made in the field with portable emission 

 measurement devices 
73

Yoshimoto, Y., M. Onodera, H. Tamaki, "Reduction of NOx, Smoke, and BSFC in a Diesel 

Engine Fueled by Biodiesel Emulsion with Used Frying Oil," SAE paper no. 1999-01-3598 

Reason: Biodiesel blend included water in an emulsion 

Frank B.P. et al., "A Study of the Effects of Fuel Type and Emission Control Systems on 

Regulated Gaseous Emissions from Heavy-Duty Diesel Engines," SAE paper no. 2004-01-1085 

Reason: Effect of oxycat & CRDPF greater than effect of B20. 

 

Durbin T. D. et al., "Evaluation of the Effects of Biodiesel Fuel on Emissions from Heavy-Duty 

Non-Road Vehicles", Final Report for the SCAQMD under contract No. 99132 by the University 

of California, Riverside, May 2000 

Reason: Non-road vehicles not considered here. 

Guerra S. A. et al., "Comparison Study of NOx and CO2 Emissions from an Off-Road Diesel 

Compactor Running on Regular Diesel, Biodiesel and Ultra-Low Sulfur Diesel," University of 

Kansas draft report, March 17, 2006 

Reason: Non-road equipment not considered here. 

 

1 U.S. Department of Agriculture, National Agricultural Statistics Service, ‘‘Crop Production’’, August 12, 2009, available online at: 

http://usda.mannlib.cornell.edu/usda/current/CropProd/CropProd-08-12-2009.pdf

2 Committee on Water Implications of Biofuels Production in the United States, National Research Council, Water Implications of 

Biofuels Production in the United States, The National Academies Press, 2008, page 3. 3

 Huang , Wen-yuan, “Tight Supply and Strong Demand May Raise U.S. Nitrogen Fertilizer Prices”, Amber Waves, November 2007, 

page 7, available online at: http://www.ers.usda.gov/AmberWaves/November07/PDF/TightSupply.pdf. 4 U. S. Environmental Protection Agency, EPA Science Advisory Board, “Hypoxia in the Northern Gulf of Mexico”, EPA-SAB-08-

003, December 2007, available on line at: 

http://yosemite.epa.gov/sab/sabproduct.nsf/C3D2F27094E03F90852573B800601D93/$File/EPA -SAB-08-003complete.unsigned.pdf. 

5

 U. S. Department of Agriculture, Economic Research Service, “U.S. Fertilizer Use and Price”, 

http://www.ers.usda.gov/Data/FertilizerUse, April 2008. 6

 Inhalation health effect concerns for volatilized a.i. compounds are discussed for individual products, e.g., oxydimeton-methyl, 

carbaryl (and carbamates generally), diazinon, at http://www.epa.gov/pesticides/reregistration/status.htm . A.I. vapor pressure and a 

discussion of product volatilization can be found at http://www.epa.gov/ttn/chief/ap42/ch09/final/c9s02-2.pdf 7

 A discussion of acetochlor toxicity can be found in EPA’s Re-registration Eligibility Document (RED) for this product at 

http://www.epa.gov/IRIS/subst/0521.htm. 8

 A discussion of carbaryl toxicity can be found in EPA’s Re-registration Eligibility Document (RED) for this product at 

http://www.epa.gov/IRIS/subst/0019.htm. 9

 A discussion of alachlor toxicity can be found in EPA’s Re-registration Eligibility Document (RED) for this product at 

http://www.epa.gov/IRIS/subst/0129.htm 
 74

 10 See http://www.irac-online.org/ , Insecticide Resistance Action Committee, for toxicity classifications and toxicity mode of action 

definitions used. 

11 See carcinogen weight of evidence (WoE) determination and description of toxicity for methomyl at 

http://www.epa.gov/pesticides/reregistration/REDs/0028red.pdf 

12 U. S. Department of Agriculture, Economic Research Service, “Farm Income and Costs: 2009 Farm Sector Income Forecast”, 

http://www.ers.usda.gov/Briefing/FarmIncome/nationalestimates.htm, updated November 24, 2009. 13 U.S. Environmental Protection Agency, EPA Science Advisory Board, Hypoxia in the northern Gulf of Mexico, EPA–SAB–08–

003, 275 p, available online at: http://yosemite.epa.gov/sab/sabproduct.nsf/C3D2F27094E03F90852573B800601D93/$File/EPA–

SAB–08–003complete.unsigned.pdf

14 Secchi, S., J. Tyndall, L. Schulte, and H. Asbjornsen. “Raising the Stakes”, Journal of Soil and Water Conservation, Volume 63, 

Number. 3, 2008, pages 68A-73A. 

15 McLachlan, M., M. Carter, C. Rustay, Effects of the Conservation Reserve Program on Priority Mixed-grass Prairie Birds: A 

Conservation Effects Assessment Project, 2007, available online at: 

ftp://ftpfc.sc.egov.usda.gov/NHQ/nri/ceap/Final%20BCR19%20CRP%20Report.pdf . 16 Iowa State University Extension, 2007 Iowa Land Value Survey, 2008, available online at: 

http://www.extension.iastate.edu/Publications/FM1825.pdf. 17 U. S. Environmental Protection Agency, EPA Science Advisory Board, op. cit., p. 177. 18 Wilhelm, W. W., J. M. F. Johnson, D. L. Karlen, and D. T. Lightle, “Corn Stover to Sustain Soil Organic Carbon Further 

Constrains Biomass Supply”, Agronomy Journal, Volume 99, 2007, pages 1665–1667. 

19 U.S. Environmental Protection Agency, Office of Water, Wadeable Streams Assessment: A Collaborative Survey of the Nation's 

Streams, EPA 841-B-06-002, 2006, available online at: http://www.epa.gov/owow/streamsurvey. 20 U. S. Environmental Protection Agency, Office of Water, National Water Quality Inventory: Report to Congress 2002 Reporting 

Cycle, U.S. EPA 841-R-07-001, 2007, available online at http://www.epa.gov/305b/2002report/. 21 Paerl, H.W., D. Robin, D. R. Whitall , “Atmospheric Deposition of Nitrogen: Implications for Nutrient Over-Enrichment of Coastal 

Waters”, Estuaries, Volume 25, Number 4B, 2002, pages 677-693. 22 Chesapeake Bay Program, Sources of Nitrogen Loads to the Bay, available online at: 

http://www.chesapeakebay.net/status_nitrogensources.aspx?menuitem=19797 

23 New York State Department of Environmental Conservation and Connecticut Department of Environmental Protection, A Total 

Maximum Daily Load Analysis to Achieve Water Quality Standards for Dissolved Oxygen in Long Island Sound, December 2000, 

available online at: http://www.longislandsoundstudy.net/pubs/reports/tmdl.pdf . 24 Roberts, D. M., and J. E. Reuter, DRAFT Lake Tahoe Total Maximum Daily Load Technical Report: California and Nevada, 

California Regional Water Quality Control Board, Lahontan Region and Nevada Division of Environmental Protection, September 

2007, available online at: 

http://www.waterboards.ca.gov/lahontan/water_issues/programs/tmdl/lake_tahoe/docs/laketahoe _tmdl_techrpt.pdf . 25 Chesapeake Bay Program, Science and Technical Advisory Committee, Workshop on Atmospheric Deposition of Nitrogen: Media 

Brief, May 30, 2007, available online at: http://www.chesapeake.org/stac/Press/AtmoNmediabrief.pdf 26 Roberts, D. M., op.cit., page 4-164. 

27 Committee on Water Implications of Biofuels Production in the United States, National Research Council, op. cit. 

28 Louisiana Universities Marine Consortium, 2009, ‘Gulf of Mexico Dead Zone Surprising Small, but Severe, available online at: 

http://www.gulfhypoxia.net/Research/Shelfwide%20Cruises/2009/Files/Press_Release.pdf

29 Mississippi River/Gulf of Mexico Watershed Nutrient Task Force, “Gulf Hypoxia Action Plan 2008 for Reducing, Mitigating, and 

Controlling Hypoxia in the Northern Gulf of Mexico and Improving Water Quality in the Mississippi River Basin”, 2008, page 22, 

available online at: http://www.epa.gov/msbasin/actionplan.htm. 

30U. S. Environmental Protection Agency, EPA Science Advisory Board, op.cit. 

31 Mississippi River/Gulf of Mexico Watershed Nutrient Task Force, op.cit., page 37. 

32 Alexander, R.B., Smith, R.A., Schwarz, G.E., Boyer, E.W., Nolan, J.V., and Brakebill, J.W., “Differences in Phosphorus and 

Nitrogen Delivery to the Gulf of Mexico from the Mississippi River Basin”, Environmental Science and Technology, Volume 42, 

Number 3, 2008, pages 822– 830, available online at: http://pubs.acs.org/cgi-bin/abstract.cgi/esthag/2008/42/i03/abs/es0716103.html. 33 Donner, S. D. and Kucharik, C. J., 2008, “Corn-based Ethanol Production Compromises Goal of Reducing Nitrogen Export by the 

Mississippi River”, PNAS, Volume 105, Number 11, 2008, pages 4513–4518, available online at: 

http://www.pnas.org/content/105/11/4513.full. 34 U. S. Environmental Protection Agency, EPA Science Advisory Board, op.cit. page 205. 
75

 35 Institute for Agriculture and Trade Policy, Staying home: How ethanol will change U.S. corn exports, 2006, Minneapolis, MN, 26 

pp., available online at: http://www.agobservatory.org/library.cfm?refid=96658 . 36 Mississippi River/Gulf of Mexico Watershed Nutrient Task Force, op.cit., page 15. 

37 Aulenbach, B.T., Buxton, H.T., Battaglin, W.A., and Coupe, R.H., Streamflow and Nutrient Fluxes of the Mississippi-Atchafalaya

River Basin and Subbasins for the Period of Record Through 2005: U.S. Geological Survey Open-File Report 2007-1080, 2007, 

available online at: http://toxics.usgs.gov/pubs/of-2007-1080/index.html. 38 U. S. Environmental Protection Agency, EPA Science Advisory Board, op. cit., p. 89. 

39 Mississippi River/Gulf of Mexico Watershed Nutrient Task Force, op. cit., page 16. 

40 Gassman, P.W., Reyes, M. R., Green, C. H. , Arnold, J. G. , “The Soil and Water Assessment Tool: Historical Development, 

Applications, and Future Research Directions”, Transactions of the American Society of Agricultural and Biological Engineers, 

Volume 50, Number 4, 2007, pages 1211-1240, available online at:. http://www.card.iastate.edu/environment/items/asabe_swat.pdf. 41 Arnold, J. G., R. S. Muttiah, R. Srinivasan, and P. M. Allen, “Regional Estimation of Base Flow and Groundwater Recharge in the 

Upper Mississippi Basin”, Journal of Hydrology, Volume 227, 2000, pages 21-40, available online at: 

http://ssl.tamu.edu/media/2900/regional%20estimation%20of%20base%20flow%20and%20groundwater%20recharge%20in%20the%

20upper%20mississippi%20river%20basin.pdf 

42 Jha, M., P. W. Gassman, S. Secchi, and J. Arnold, “Upper Mississippi River Basin Modeling System Part 2: Baseline Simulation 

Results”, in: Coastal Hydrology and Processes (Eds. V.P. Singh and Y.J. Xu), Water Resources Publications, Highland Ranch, CO, 

2006, pages. 117-126. 

43 U.S. Department of Agriculture, USDA Agricultural Projections to 2018, February 2009, available on-line at: 

http://www.ers.usda.gov/Publications/OCE091/ 44 Homer, C. C. Huang, L. Yang, B. Wylie and M. Coan. “Development of a 2001 National Landcover Database for the United 

States”. Photogrammetric Engineering and Remote Sensing, Volume 70, Number 7, 2004, pages 829-840, available online at 

http://www.mrlc.gov/pdf/July_PERS.pdf . 45 U.S. Department of Agriculture, National Agricultural Statistic Service, http://www.nass.usda.gov/research/Cropland/SARS1a.htm. 46 U.S. Department of Agriculture, Natural Resources Conservation Service, http://www.nrcs.usda.gov/techical/NRI. 47 Conservation Technology Information Center, http://www.ctic.purdue.edu/. 48 American Society of Agricultural and Biological Engineers, Manure Production and Characteristics. ASAE D384.2 MAR2005, 

available online at: http://asae.frymulti.com/abstract.asp?aid=19432&t=1. 49 U. S. Department of Energy, Energy Information Administration, Annual Energy Outlook 2007 With Projections to 2030, February 

2007, available on-line at: http://tonto.eia.doe.gov/ftproot/forecasting/0383(2007).pdf 50 Renewable Fuels Association, “Ethanol Biorefinery Locations,” http://www.ethanolrfa.org/industry/locations, April 2008. 51 Chesapeake Bay Commission, Biofuels and the Bay: Getting It Right to Benefit Farms, Forests and the Chesapeake, Chesapeake 

Bay Commission, Annapolis, Maryland, 2007, 32 pages, available online at: 

http://www.chesbay.state.va.us/Publications/BiofuelsAndTheBay1.pdf 

52 Simpson, T. W., A. N. Sharpley, R.W. Howarth, H.W. Paerl, and K. R. Mankin, “The New Gold Rush: Fueling Ethanol Production 

while Protecting Water Quality”, Journal of Environmental Quality, Volume 37, 2008, pages 318-324. 53 Chesapeake Bay Foundation, 2007 State of the Bay, 2007, available online at: 

http://www.cbf.org/site/DocServer/2007SOTBReport.pdf?docID=10923. 54 Federal Leadership Committee for the Chesapeake Bay, November 9, 2009, Executive Order 13508: Draft Strategy for Protecting 

and Restoring the Chesapeake Bay, available on-line at: http://executiveorder.chesapeakebay.net/ 55 Chesapeake Bay Commission, op. cit., page 11. 

56 U.S. Environmental Protection Agency, Region 7, Environmental Laws Applicable to Construction and Operation of Ethanol 

Plants, EPA-907-B-07-001, November 2007,104 pages, available online at: 

http://www.epa.gov/region07/priorities/agriculture/ethanol_plants_manual.pdf 

57 Regassa, T., Koelsch, R., Erickson, G., Impact of Feeding Distillers Grains on Nutrient Planning for Beef Cattle Systems, 

University of Nebraska-Lincoln Extension—RP190, 2008, 8 pages, available online at: 

http://www.ianrpubs.unl.edu/epublic/live/rp190/build/rp190.pdf 

58 U.S. Department of Agriculture, Natural Resources Conservation Service, “Comprehensive Nutrient Management Planning 

Technical Guidance”, National Planning Procedures Handbook, Part 600.5, available online at: 

http://policy.nrcs.usda.gov/17088.wba. 

59 Mackay, D.M., de Sieyes, N. R.., Einarson, M.D., Feris, K.P., Pappas, A.A., Wood, I.A., Jacobson, L., Justice, L.G., Noske, M.N., 

Scow, K.M., and Wilson, J.T., 2006, Impact of ethanol on the natural attenuation of benzene, toluene, and o-Xylene in a normally 

sulfate-reducing aquifer, Environmental Science & Technology, v. 40, p. 6123-6130. 
 76

 60 Ruiz-Aguilar, G. M. L.; O’Reilly, K.; Alvarez, P. J. J, “Forum: A Comparison of Benzene and Toluene Plume Lengths for Sites 

Contaminated with Regular vs. Ethanol-amended Gasoline”, Ground Water Monitoring and Remediation, Volume 23, 2003, pages 48-

53. 

61 Reilly, T.E., Dennehy, K.F., Alley, W.M., and Cunningham, W.L., Ground-Water Availability in the United States: U.S. Geological 

Survey Circular 1323, 2008, page 33, available online at http://pubs.usgs.gov/circ/1323/ 62 McGuire, V.L, Changes in Water Level and Storage in the High Plains Aquifer, Predevelopment to 2005: U.S. Geological Survey 

Fact Sheet 2007-3029, 2007, available online at http://pubs.usgs.gov/fs/2007/3029/ . 63 U.S. Environmental Protection Agency, Consumer Fact Sheet on Nitrates/Nitrites, available online at: 

http://www.epa.gov/safewater/dwh/c-ioc/nitrates.html

64 U.S. Environmental Protection Agency, Office of Water, FACTOIDS: Drinking Water and Ground Water Statistics for 2007, EPA 

816-K-07-004, 2008, available online at: 

http://www.epa.gov/safewater/data/pdfs/data_factoids_2007.pdf 

65 Scribner, E.A., Thurman, E.M., Goolsby, D.A., Meyer, M.T., Battaglin, W.A., and Kolpin, D.W., 2005, Summary of 

significant results from studies of triazine herbicides and their degradation products in surface water, ground water, and precipitation 

in the Midwestern United States during the 1990s: U.S. Geological Survey Scientific Investigations Report 2005–5094, 27 p. 

66 U.S. Environmental Protection Agency, Consumer Fact Sheet on Atrazine, available online at: 

http://www.epa.gov/safewater/contaminants/dw_contamfs/atrazine.html 

67 See 40 CFR, Part 141, Subpart O, App. A. 

68 U.S. Environmental Protection Agency, A Review of Contaminant Occurrence in Public Water Systems, EPA 816-R-99-006, 1999, 

available online at: http://www.epa.gov/OGWDW/occur/nov99_lo.pdf 69 U.S. Environmental Protection Agency, of Occurrence Estimation Methodology and Occurrence Findings Report for the Six-Year 

Review of Existing National Primary Drinking Water Regulations, Office of Water, EPA-815-R-03-006, 2003, pages 38 and 40, 

available online at http://epa.gov/OGWDW/standard/review/pdfs/support_6yr_occurancemethods_final.pdf. 70 U.S. Environmental Protection Agency, Safe Drinking Water Information System (SDWIS) End of Year data for FY 2007, 2007. 

71 Gilliom, R. J., The Quality of Our Nation's Waters Pesticides in the Nation's Streams and Ground Water, 1992-2001: U.S. 

Geological Survey Circular 129, 2006, Tables 7A-1 to 7A-4, available online at: 

http://water.usgs.gov/nawqa/pnsp/pubs/circ1291/appendix7/7a.html 

72 Committee on Water Implications of Biofuels Production in the United States, op.cit. 

73 Great Lakes Commission, The Potential Impacts of Increased Corn Production for Ethanol in the Great Lakes-St. Lawrence River 

Region, 2007, available online at: http://www.glc.org/tributary/pubs/documents/EthanolPaper121807FINAL.pdf.