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## 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 drai ns, 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 applicati on methods, use of conservation pr actices 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 proximit y 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 am ounts of fertilizer, especial ly nitrogen fertilizer, to produce economic yields. Of all current and pot ential 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 l each to water. Corn generally utilizes only 40 to 60% of applied nitrogen. The rema ining nitrogen is available to leave the field and runoff to surface waters, leach into ground water, or vola tilize 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 c ontinuous corn. Although the amount of losses of nitrogen fertilizers to ground and surface water va ry, 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 fertilizati on 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 yiel ds of corn grown in rotation. Alternatively, if farmers mainta in fertilization rates with thes e 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 su ch as corn rootworm. Farmers may increase use of pesticides to control th ese 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 ingredients 6 in

addition to concerns with cont amination of foods and drinking water. Furthermore, raising acreage under corn production will increase the qu antity 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 associ ated 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, herbic ides 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 herb icides inhibit cell division and growth while a subgroup of these products, the atrazine-containi ng OC herbicides, inhibit plant photosynthesis. Another type of common corn herbicide, the phosphonoglycene or glyphosate–containing organophosphate (OP) herbicides, i nhibit protein synthesis in plants. Several of the common corn herbicide compounds, such as acetochlor, carbaryl and alachlor, are classi fied 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 he alth 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 co rn insecticide products, by sales of AI by weight, generally contain me thomyl. 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 carcinogen 11 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 producti on, 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 ap ply far less fertilizer a nd 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 nutri ents under standard fer tilization 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 a nnual average prices paid for fertilizers rose 264%. The annual average prices paid for fe rtilizers were up 82% in 2008 alone. In 2009, ERS predicts that the annual average prices pa id for fertilizers will fall 26.5%. In October 20093 fertilizer prices returned to the December 2007 level, when the run-up in prices started. 12 It is unclear how agricultural producers responded to thes e 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 de mand for corn expands, additional acres panted to corn will likely results in increased amount s 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 tile s/pipes or man-ma de 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 produc tive agriculture lands. However,

the artificial drains or ditches al so 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 pr ices may also have significant impacts on conservation programs funded by the USDA. USDA funds a variety of voluntary programs to help agricultural producers implement cons ervation 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 receiv e annual rental payments under 10- to 15- year contracts to ta ke land out of agricultural producti on 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 e nvironmental 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 reenrollment4 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 a nnually 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%. C onservation practices encompass a wide range that can have a significant impact on pollutant s reaching ground or surface water from crop production. EQIP cost-shares with farmers for impor tant practices such as nutrient management, cover crops, livestock manure storage, and ripari an buffers. Like CRP, high corn prices may have an impact on the willingness of agricultura l producers to participate in EQIP. Producers may require higher payments to offset poten tial loss of profits thr ough 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 acro ss many geographic areas. Howe ver, 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 s hould be targeted to the most vulnerable areas of watersheds. Conservation practices designed to meet wildlife goals will need different targeting mechanisms to ensure ad equate 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 environmenta l 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 nitr ogen and phosphorus, except for a few practices.

The most cost-effective practices on working lands include: riparian buffers; crop rotation; appropriate ra te, timing, and method of nutrient application; cover crops; and, on tiledrained lands, treatment wetlands and controlled drainage. Thes e practices have significant water pollution reduction benefits that vary base d on the site-specific conditions and on the implementation and operati on and maintenance of the practice. For example, controlled drainage can reduce nitrogen loads by 30%; treatment we tlands 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 feedst ocks will become increasingly important. These feedstocks will have dramatically different impacts on water quality. Biodiesel feedstocks, primarily soybeans, as well as cellulosic feedst ock 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, soybea ns have less residue remaining after harvest

1 See http://www.nrcs.usda.gov/technical/nri/ceap/index.html5 compared to corn, so sediment runoff could be more of a concern, depending on how each crop is managed. Switchgra ss may be a more favorable biofuels cr op for reducing water impacts. It is a native plant which does not require high inputs of fertilizers or pestic ides and since it is a perennial crop, there is limited sediment runoff co mpared 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 concer n 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 th e productivity of the soil. Corn stover maintains the soil organic carbon which has many benefits as a source of nut rients, preventing erosion by wind and water, and increasing soil aeration and wa ter infiltration. Wilhelm, et al. 18 evaluated the amount of corn stover that could be harvested for biofuel pr oduction 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 di scussion 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 a nd environmental benefits.

Different conservation systems and conservation practice standards will need to be developed and adopted for cellulosi c 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. Nu trient 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 dow nstream 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 th e 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 plan ts 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 been6 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 eutrophi cation. As a biologic system becomes more enriched by nutrients, different species of al gae may spread and species composition can shift; however, unless such species shifts cause cl early 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 mo st widely known examples of significant nutrient impacts include the Gulf of Mexico and th e Chesapeake Bay. For these two areas alone,

there are 35 states that contri bute 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 togeth er to place an unprecedented priority on public partnerships, collaboration, bette r science, and improved tools to reduce nutrient pollution.

Virtually every state and territory is impact ed by nutrient-relate d degradation of our waterways. All but one state and two territories have waterbodies that are polluted by nutrients. States have listed over 10,000 wate rbodies that have nutrient a nd 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 ch emical, 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 ex cess 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 refere nce conditions. Phosphorus exhibits comparable patterns to nitrogen and is the second most-pervasive stressor fo r 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 wate r quality reports submitted by the states and territories to EPA. Historically, the National Wa ter 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, nu trients are identified as the leading cause of water pollution in assesse d 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. Agriculture7 is the largest known source of water quality impai rment to both assessed rivers and streams and

lakes and reservoirs.

6.2.2 Air Deposition of Nitrogen to Water

Nitrogen oxide (NOx) emissions from fo ssil 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 vari ables, the atmospheric NOx falls back to the ground as rain, snow, fog, or dry deposition. NOx is deposited di rectly 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 depos ition to waterbodies around the country 21 , including the Chesapeake Bay 22 , Long Island Sound 23 , 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 ve hicles falls on impervious surfaces, such as roads and parking lots where it runs off into st reams. Road drainage systems generally channel runoff quickly and accelerate the nitrogen lo adings downstream. In the Chesapeake region, vehicle exhaust remains the single largest sour ce of fossil-fuel derived nitrogen pollution. 25 Air deposition of nitrogen accounts for more than ha lf 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 hypox ia 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 eutrophi cation) resulting in reduced sunl ight, loss of a quatic 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 measur ed at only 3,000 square miles. A combination of below average high flows on the Mississippi Rive r 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 be en 6,600 square miles.

The Mississippi River/Gulf of Mexico Wate rshed Nutrient Task Force’s “Gulf Hypoxia Action Plan 2008” lays out two major goals fo r reducing water quality problems in the Mississippi River/Atchafal aya 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 ca lls for an acceleration of actions to reduce the8 hypoxia in the Gulf. In order to meet these go als, 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 redu ction in nitrogen and phosphorus reduction will be necessary as a result of increased corn pr oduction 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 producti on 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 thr oughout 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 hi ghest 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 nutri ent contributions are primarily due to near record-breaking streamfl ows in spring 2008 in the Mississippi River Basin. Streamflows were about 50% higher this year co mpared to the long-term spring average flows since about 1980. Nutrient contributions for a gi ven spring vary depending on the amount of flow in the Mississippi-Atchafalaya River Basi n, as well as average stream water nutrient

concentrations.

Alexander, et al. modeled the sources of nutri ent loadings to the Gulf of Mexico using the USGS SPARROW (spatially referenced regr ession 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 account ed for 52% of the total nitrogen delivery to the Gulf. Atmospheric deposition was the s econd 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 Gu lf hypoxia of increasing corn production for

ethanol. Several recent sc ientific 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 co rn-based ethanol production could make it almost impossible to meet the Gulf of Mexico n itrogen reduction goals wit hout “radical shift” in9 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 conve rsion of corn to ethanol.

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

Watershed Task Force estimated th e additional annual nitrogen load ings 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 nationa l annual loading of almost 300 million pounds of nitrogen. An es timated 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 qualit y, EPA conducted an analysis that focused on agricultural production in the Upper Mississippi River Basi n (UMRB). The UMRB drains approximately 189,000 square miles, including large parts of the st ates of Illinois, Iowa, Minnesota, Missouri, and Wisconsin. Small portions of Indiana, Michig an, and South Dakota are also within the basin. EPA selected the UMRB because it is representativ e of the many potential issues associated with ethanol production, including its connection to majo r water quality concerns such as Gulf of Mexico hypoxia, large corn production, a nd 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 st ates 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 per centage of nitrogen from these two basins is primarily due to the large inputs of fertilizer fo r 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. Phosphor us loads to the Gulf ranged from 80,700 metric tons to 180,000 me tric 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 declin e 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 se ven billion gallons of ethanol, mostly from corn kernels. Corn-based ethanol production is ex pected to reach at least 15 billion gallons in order for industry to comply with the RFS2 st andards. Of the potential crops for biofuels production, corn has the highest rates of fertiliz er and pesticide applic ation, leading to the10 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 th e UMRB. Models are the primary tool that can be used to predict future impact s based on alternative scenarios. SWAT is a physical process model developed to quantify the impact of la nd management practices in large, complex watersheds. SWAT, primarily de veloped by USDA’s Agricultural Research Service and the Texas A&M University Blackland Research and Ex tension 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 valid ated in watersheds both nationally and internationally. 40 SWAT has been applied extensivel y to support water quality and Total Maximum Daily Load (TMDL) planning througho ut the United States. SWAT is a basin-scale

continuous simulation model that operates on a daily time step a nd is designed to predict the nonpoint source loadings and resulting water quality impacts of water, sediment, and agricultural chemicals (nutrients and pesticides) from a wate rshed. The model can assess a wide variety of impacts of alternative management practices an d 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 r outing and pond/reservoir routing.

SWAT has several very im portant strengths that enab led 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 co mmonly 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 s imulated along with the impact on downstream water bodies spanning several decades; and

6) The model code has been validated on hundre ds 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 re garding SWAT can be found at: http://www.brc.tamus.edu/swat.

6.4.1.1 Base Case

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

alternative levels of increase d 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, a nd RFS2 control cases could be compared. As in the NPRM, we select ed 2005 as the mid-point of the target period for

baseline conditions in the watershe d. However, for the analysis for this final rule, we used the 2007 corn yield value to correspond with the agricu ltural analysis described in Chapter 5. We assumed that 33% of corn produced in the UM RB 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 wa s necessary to select a target year, or window of years, that represent the conditions on the waters hed. For this study the year 2005 was selected as the target period for baseline conditions. As with mo st 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 s hort time window or period. The majority of the data sources were from the years 2000 through 20 06. 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 di stributed from the upper reaches in Minnesota and Wisconsin to the UMRB outlet below Grafton, Illi nois. In addition, the weather data has been spatially interpolated to assign one weather station per subwatershed.

To establish the land use for the ba seline 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 th e soils data for the entire analyses. The primary input data is the US DA 1997 National Resource Inventor y (NRI), which provided land12 use, soil, and data on mana gement practices on the land. 46 1997 is the most current year for

which this data is available.

In addition, information from the Conser vation Tillage Informa tion Center and USDANASS Census of Agriculture 2002/1997 were us ed to identify the cropping rotation and management practices for the agricultural land ar eas 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, somewh at 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 UM RB 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 cropla nd, we started by estimating the livestock and the amount of manure produced. The livestock nu mbers came from the agricultural statistics for each county based on the 2002 Census of Agricu lture 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 ra tes as outlined in ASABE, 2005. 48 If the total amount of the manure production exceeded 20% of the estima ted total fertilizer a pplication in one HUC, manure application and chemical fertilizer application were us ed 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 alfa lfa 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 s upplement the manure applic ation 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 applied13 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, a nd 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), applica tion efficiency (1.3, ratio, unitless), and fraction of fertilizer applied to soil surface (0.2). The nitrogen stress fact or was set to 0.75 (ratio, unitless).

The 42-year SWAT model runs were perfor med and the results analyzed to establish runoff, sediment, nitrogen, and phosphorous lo adings 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 site s 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 conditi ons 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 AEO2007 49 reference case we modeled: 1 0.49 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 c onstant national ethanol goal of 7.05 billion gallons a year (BGY) starting in 2012. For this analysis, the referen ce cases assumed that no cellulosic ethanol was produced from corn stover. For the RFS2 cont rol 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 scenar ios, 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 divide d 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 UMRB14 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 availa ble 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 thre e 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 fu ture scenarios, with an annual increase of 1.23%. This produced yield increases to 149.6 bushe ls 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 Upp er 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 mo del 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 out flow is the remaining amount measured at the outlet of the UMRB at Grafton, Illinois after ac counting 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 ear lier, 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 co rn acres planted for ethanol production goals in

this rule.15 Table 6.4-2. Average annual nitrogen loads: Co mparison 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 fro m 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 clim ate-warming potential of carbon dioxide, the major greenhouse gas of environmental concer n. 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 phosphor ous loads at a slightly lower percentage than nitrogen.

Table 6.4-3. Average annual phosphorus loads: Co mparison 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: Co mparison 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 to tal amount of nitrogen or phosphorus that

reaches a stream within the UMRB. The total out flow is the remaining amount measured at the outlet of the UMRB at Grafton, Illinois after ac counting for in-stream loses due to uptake or

assimilation.

Table 6.4-5. Average annual nitrogen loads: Comp arison 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: Co mparison 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 wate rshed 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 imp aired waters due to high nutrient levels, biorefinery plants, drinking water intakes, a nd 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 s ubstantial amount of obser ved data throughout the watershed, primarily from the U.S. Ge ological Survey gaging stations.

The case study used the same assumptions and scenarios as those used for the UMRB analysis. SWAT-simulated streamflow and wa ter 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 d ecreased 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 meteorologi cal and management related fact ors. The goal was to further

understand the model characteristic s and sensitivities to parameters and input forcing functions that control the model response for the key enviro nmental 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 orga nic 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 di d 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 r easons. Climate change requires a long period of observation. Over the short time frame reflected in this proposal, precipitation and temperat ure 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 – t hough estimates vary considerably depending on

the model used and initial conditions.



### 6.6 Chesapeake Bay Watershed

The Chesapeake Bay Commission and others ha ve 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 Yor k, Pennsylvania, Virginia and West Virginia— and the entire District of Columbia. The Chesapeake's land-to-water ratio (14:1) is the largest of19 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 “t he 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 phosphor us, they have not been adequate to meet the established goals. The watershe d 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 prac tices (BMPs) at levels never before seen in this country. The states have committed to impleme nt 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 Transportati on. In November 2009, these federal agencies released a draft strategy which contains a rang e 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 contro l, habitat protection and land conservation programs at all levels of government, including an expanded use of regulatory authorities to address pollution control and a dditional voluntary and market-bas ed solutions – particularly when it comes to habitat protec tion 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 rest oration efforts of the past 25 years.

Agricultural lands account for nearly a quart er 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 industr ial wastewater treatment plants throughout the watershed are responsible for 21% of the to tal 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 equipmen t, lawn mowers and aircraft. While population increased about 8% during the last decade, vehi cle 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 si x and a half times the size of the watershed), as20 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%), increas es 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 encouragin g producers to alter their typical crop production rotations and crop acreage, contributing to not eworthy changes in crop acreages across the

watershed. A technical review committee c onvened 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 co ntribute 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 cr ops as a conservation practice after harvest.

Strong market forces also encourage ag ricultural 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, manage ment 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 ex pansion of biofuel produc tion within the United States, supported by market-driven commodity pr ice increases, government policies, or a combination of both. The CBWM is a dynamic wa tershed model used to characterize nutrient and sediment loads, and changes in these lo ads, due to management actions for decision

support. 2

. In developing the agricultural production tr end analysis within the Chesapeake Bay watershed, the USDA’s National Agricultura l Statistics Service’ s (NASS) 2007 and 2008 Projected Plantings report on reported crop acr eages 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.htm21 increased sharply between 2006 and 2007 and d ecreased 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 US DA-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 offs et 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 co rn production, but also an increase in the total acres of land under row crop production by ove r 355,000 acres. Since agricultural land uses within the Chesapeake Bay watershed are continu ously 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 c onversion of non-row crop agricultural lands over the period from 2005 to 2008 to more intensiv e row crop production. The non-row crop land uses typically produce less nitrogen yields to th e Bay, thus additional acres converted to grain production can also increase nitrogen loads signif icantly. 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 Ph ase 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 (CBE WQSTM) and the Chesapeake Bay Land Change Model (CBLCM). The CBWM is a dynamic waters hed 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 de termine nutrient and sediment lo ads 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 a nd delivered nitrogen, phosphorus and sediment to the Chesapeake Bay, a nd 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 wa ter bodies or to municipal wastew ater treatment plants for both industrial process water and stormwater. The perm it 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 purifica tion, cooling water blowdown, and off-batch ethanol.

6.7.1 Water Discharges

Water is required at ethanol facilities for pr ocessing 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 coo ling 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 ma y 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 f acilities get their process water from municipal water supplies, most use on-site wells to produce the process water fo r 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 specializ ed filtration and pressure to produce pure water while concentrating the groundwater minerals into re ject water. The minerals in the reject water are site-specific, but they can include: calciu m 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 estimate s of water consumption in etha nol 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 wa ter blowdown, where some cooling water is discharged to avoid the buildup of minerals in th e cooling system. These brines are similar to the reject water described above. In addition, if off-batch ethanol product or process water is23 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 conse quences of high BOD are the sa me as those for low dissolved oxygen: aquatic organisms become stressed, suffocate, and die.

. Ethanol production facilities ar e important transportation hubs. For instance, a facility in Iowa produces about 130 million gallons of etha nol 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 a nd trucking terminal.

6.7.2 Water Use

Older generation production f acilities used 4-6 gallons of process water to produce a gallon of ethanol, but newer fac ilities use less than 3 gallons of water in the production process. Most of this water savings is gained through impro ved 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 etha nol, 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 leve ls 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 producti on is distillers grain with solubles (DGS). Due to the increase in ethanol production and th e 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 t ons 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 par tially replace corn or other feeds with DGS for both economic and production reasons. Different livesto ck 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’s24 needs, these nutrients are excreted in the manur e. 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 wate rs. Excess nutrients from manure nutrients have the same impact on water quality as ex cess nutrients from other sources.

Livestock producers can limit the potential po llution from manure applications to crops through a variety of techniques. USDA’s Natu ral Resources Conservation Service (NRCS) has developed a standard for a comprehensive nutri ent 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 applica tion of the manure. Due to the substantially higher phosphorus content of manure from lives tock 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 par ticularly 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 com ponents and/or additives can occur when underground fuel storage tanks leak fuel into gr ound water that is used for drinking water supplies or when spills occur from above ground ta nks or distribution systems that contaminate surface drinking water supplies or surface wa ters. Additionally, in surface waters, rapid biodegradation of ethanol can resu lt 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 concer n 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 xyle nes) 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 sulfat e-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 de tail 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 approximate ly 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 affect ed most, especially wh ere are existing water shortages25 With the increasing use of ethanol in the fuel supply nationwide, it is important to understand the impact of ethanol on the existing ta nk infrastructure. Federal regulations require that underground storage tank (UST) systems be comp atible with the fuel stored. Because much of the current underground storage tank equipm ent 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 federall y regulated facilities, it may be difficult or impossible to confirm the compatibility of cu rrent underground storage tanks and other tankrelated hardware with ethanol blends. Further di scussion 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 th e gasoline used in the U.S. cont ains ethanol, approximately 3,750 of those releases likely contained some amount of ethanol. Therefor e, EPA is undertaking analyses designed to assess the potential impacts of et hanol blends on tank in frastructure 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 availa ble water). This methane could bubble out of the ground water and enter the soil gas at explosive c oncentrations, although it is not possible to quantify the risk at this time. EPA is beginni ng 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 et hanol plants in producti on 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 gall on 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 fa cilities recycle washwater, which reduces water consumption.

The strength of process wastewater from bi odiesel plants is highly variable. Most production processes produce washwa ter that has very high BOD le vels. 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 me thanol 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 bi odiesel process and has ma ny uses. It is about 10% of the final product. Although there is a commercial market fo r glycerin, the rapid26 development of the biodiesel industry has cause d a glut of glycerin production and many facilities dispose of glycerin.

The high strength of these wastes can overl oad 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 biod iesel process with e fficient recovery of methanol, containing small amounts of glycer in, can have a BOD of 10,000 – 15,000 mg/L. Pure glycerin has a BOD of nearly 1,000,000 mg/L. Ther e have been several cases of wastewater treatment plant upsets due to these shock loadin gs from releases of glycerin from biodiesel production facilities. Unfort unately, these have been due to sl ug loadings to small wastewater treatment plants. Other states such as Illi nois and Alabama have also had problems with discharges from small biodiesel plants. In a ddition, 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 glyc erin 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 bette r profit margin and demand for glyc erin 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 ne w value added products (ethanol, propylene glycol, etc.) using glycerin as a feedstock. Most of thes e projects are in university labs, but a few are up to pilot scale. These new technologies will go onlin e 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 Drinki ng Water and Public Health

Under the Safe Drinking Water Act (SDW A), 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 cons umption 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 ex change (IE), granulated activated carbon (GAC) or reverse osmosis (RO).

EPA anticipates that increased corn producti on 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 pr ocess may generate new or in creased discharges, injection or infiltration of process waste water that coul d adversely affect the nation’s surface water and ground water used for drinking water.27 In addition to potential additional contaminati on of sources of drinking water, surface and ground water supplies may be strained by increase d 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 US GS. 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 greates t 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 aqua tic habitats and other ecosystem services such as fishing and swimming. Lower stream levels comb ined with the increased pollutant loadings may concentrate pollutants. Higher pollutant co ncentrations may require increased drinking water treatment. The accelerated depletion of agricultural aquifers and surface water supplies may be exacerbated by an increase in the incide nce 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 dr ink water containing nitr ate 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 ba by syndrome. This health effect s language is not intended to catalog all possible health effects for nitrate. Ra ther, 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 nitr ates. 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 dr inking water are human sewage, livestock manure, and fertilizers.

In 2007, there were 562 public water syst ems, 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 samp ling of ambient water used by public water systems, the relative contribution of nitrate de tections from the various sources is generally

unknown.28 6.9.2 Pesticides

The U.S. Geological Survey evaluated the fa te 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 a nd temporal distribution of herb icides 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 frequent ly detected pesticide in EPA's National Survey of Pesticides in Drinking Water Wells. EPA's Pesticides in Ground Wate r Database indicates

numerous detections of atrazine at concentra tions 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 th is point, levels found in PWS have been low. Through the PWS monitoring program, EPA is ensu ring 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 billi on (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 meas urement 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 possi ble 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 environm ent 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 alka line 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 ta ken up in the tissues of plants or animals. 67

In A Review of Contaminant Occurre nce in Public Water Systems , published in 1999,

EPA found atrazine in the finished wate r 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 concentrat ions 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 concentrati on 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

> MRL a 100% 100% 96.2% 96.3% 55.6%

> MCL b 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 sy stems 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 co ncentrations above the MCL during the growing season, very few experience MCL violations ba sed on the average concentration over four consecutive quarters. In 2007, only one water syst em serving 740 people o fficially reported a

MCL violation. 70

From 1992 through 2001, the USGS observed at razine 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 drinki ng 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 sa me period. For ground water, USGS observed atrazine in 42% of the samples it took from wells in agricultural area s and in 31% of the sa mples 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 concentr ations 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 oc currence 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 updati ng the occurrence data published here for nitrate and atrazine.30 

### 6.10 Water Quantity Concerns

Biofuel production based on cu rrent 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 fact or of three relative to traditional refining). From a regional perspective, water demand for crop production woul d be relatively much larger than biorefinery demand; crop production needs w ould 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, th e ratio of water consumed to produce the corn itself for ethanol is nearly one thousand gall ons 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 uni ntended 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 likel y 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 th e 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 gall on of ethanol produced; bi odiesel 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 re fining 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, biofue l 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 (cu rrently 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 consumpti on 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 construc tion 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 (equa tes 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/s ugar/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. Th ese 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 la rge absolute water cons umption, 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. Reas ons 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 wate r transport and use of reclaimed water can lead to more efficient agricultural water use for both corn and cellulosic ethanol crops. Also, biorefineries are increa singly incorporating water recycling.

The economics of the energy-water distribu tion 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, th e 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. Thes e 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 Busine ss 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 und er the Administrative Procedure Act or any other statute unless the agency certifies that th e rule will not have a si gnificant 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 Advo cacy 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 (Docke t 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 su mmary of the Panel’s recommendations can be found in the preamble to the proposed rule. Furt her, the Final Panel Re port contains a detailed

discussion of the Panel’s advi ce and recommendations (as well as comments from the Small Entity Representatives (SERs)). The regulatory alte rnatives 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 estima te of the number of sm all 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 pr ofessional 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 re quired 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 the33 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 objec tives of this rule are located in the preamble to the final rule. As previously st ated, 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 (E PA) 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 le vel 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 ble nded into diesel fuel (both high way 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 th ree additional types of renewable fuels to the program (advanced biofuel, cellulosic biofue l, and biomass-based diesel) and requires compliance with all four standards.



### 7.3 Definition and Descript ion 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 m eets 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 distri ct 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 jurisdicti ons or small organizations as de scribed 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 overvie w 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: NAICS a codes

Gasoline and diesel fuel refiners 1,500 employees b 324110

a North American Industrial Classification System

b EPA has included in past fuels rulemakings a provisi on that, in order to qua lify for the small refiner flexibilities, a refiner must also produc e 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 refine rs 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 th e refining industry. EPA then found employment information for these companies using the busin ess information databa se Hoover’s Online (a subsidiary of Dun and Bradstreet). These refi ners 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 impor ters 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 en tity 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 secti on 211(o). It should be noted that because of the dynamics in the refining industry (i.e., me rgers 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 c onducted 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 progra m (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 th e various recommendations put forth by the Panel. Below we discuss those flexibility options recommended in the Panel Report, our proposed regulatory alternatives, and t hose provisions which are being finalized.

7.4.1 Panel Recommendations

The purpose of the Panel proce ss is to solicit information as well as suggested flexibility options from the SERs, and the Panel recommend ed that EPA continue to do so during the development of the RFS2 rule. Recognizing th e 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 sec tion 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 exte nsions beyond those authorized by section 211(o)(9) for small refineries operated by a small refiner. The Pa nel 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 Exemptio n 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 fo r at least two years for any small refinery that DOE determines would be subject to disp roportionate economic hard ship if required to comply with the RFS2 requirements.

Section 211(o)(9)(A)(ii) requires DOE to perfo rm a study of the economic impacts of the RFS requirements on small refine ries. The study, which was required to be completed by December 31, 2008, must assess and determine wh ether the RFS requirements would impose a disproportionate economic ha rdship on small refineries. Small re fineries 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 w ith 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 gi ven the outcome of the DOE small refinery study. In the small refinery study, “EPA CT 2005 Section 1501 Small Refineries Exemption36 Study”, DOE’s finding was that there is no reason to believe that any sm all refinery would be disproportionately harmed by inclusion in the pr oposed RFS2 program. This finding was based on the fact that there appeared to be no shorta ge 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 standa rd, 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 disproportiona te economic hardship under the proposed RFS2 program, and that the small refinery exemp tion should not be extended beyond December 31, 2010. DOE noted in the study that, if circumstance s 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 di scussions 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 provisi ons. Small refiners generally commented that they believe that the st udy 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-d epth 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 pr eamble 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 dispropor tionate economic impact on small refineries, we cannot grant

an automatic additional extension for small refine ries 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 re finer temporary exemption.

We are aware that there have been expressions of concern from Congress regarding the DOE Study. Specifically, in Senate Repor t 111-45, the Senate A ppropriations Committee “directed [DOE] to reopen and reassess the Sm all 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), refe renced 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 a nd the revised study finds that there is a37 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 refi ner SERs suggested that an additional temporary exemption for the RFS2 program would be beneficial to them in meeting the RFS2

standards. EPA evaluated a tem porary exemption for at least some of the four required RFS2

standards for small refiners. The Panel recomme nded 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 seri ous concerns about its authority to provide an extension of the temporary exemption for small refi neries that is different from that provided in CAA section 211(o)(9), since Congr ess specifically addressed an extension for small refineries in that provision.

The Panel did recommend that EPA propos e other avenues through which small

refineries and small refiners could receive extensions of th e temporary exemption. These avenues were a possible extension of the tem porary exemption for an additional two years following a study of small refineries by the De partment 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 recomme ndations of the Panel and SERs. We proposed to continue the temporary exempti on finalized in RFS1, through December 31, 2010, for small refiners (and small refineries), extendi ng it to include an exem ption for diesel volume and diesel refiners, importers, and blenders, as required by EISA.

Commenters that oppose an extension of the te mporary exemption generally stated that they believe an extension is not warranted, a nd some of these comment ers 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 comment ers supported the continuation of the exemption through December 31, 2010 only; one of those commenters stat ed that it does not support an extension as it believes that all parties have been well aware of the passage of EISA a nd small refineries and small refiners should have been striving to achieve compliance by the end of 2010. Two commenters also expressed views that the exem ption 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 EP Act, 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 exem ption 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 significan t 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 re quested 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 refineri es should be granted a permanent exemption.

What We’re Finalizing

The RFS1 program regulations exempt gaso line 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, extendi ng the relief to diesel fuel volumes produced or imported in addition to gasolin e, and extending the relief to thos e 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 bus iness (1,500 employees or less company-wide), we are also finalizing a continuation of the sma ll 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 exempti ons 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 re newable fuel obligations through December 31, 2010. As discussed above, the statute also incl udes two specific provisions describing the basis

and manner in which further extensions of th is exemption can be provided. In the RFS1 rulemaking, EPA considered whether it should pr ovide additional relief to the limited number of

small refiners who were not c overed by the small refinery provision, by providing them a temporary exemption consistent with that pr ovided by Congress for small refineries. EPA exercised its discretion under section 211(o)(3) an d 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 re lief 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 additiona l extensions if the criteria specified by39 Congress are met. EPA believes that an additi onal or different extension, relying on a more general provision in section 211(o)(3) would be inc onsistent with Congressi onal intent. Further,

we do not believe that the statute allows us the di scretion to give relief to small refiners only—as

this would result in a subset of small refineri es (those that also qualify as small refiners) receiving relief that is greater than the relief al ready 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 “disproporti onate economic hardship.” The statute provides that such hardship can be iden tified 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, abse nt 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 refi neries. 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 ru le. Specifically in the case of an extension of the exemption for small refiners, we also cons ulted 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 belie ve that we can provide an extension of the exemption considering the out come of the DOE small refinery study, which did not find that there was a disproportionate econo mic hardship. Further, we do not believe that the statute allows us the discretion to give relief to a subset of small refi neries (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 recogniz e that the 211(o)(9) small refinery provision does allow for extensions beyond December 31, 2010, as di scussed in preamble Section III.E.2. Thus, refiners may apply for in dividual hardship relief.

7.4.4 Phase-in

Panel Recommendations

Small refiner SERs suggested that a phase-i n 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, EP A has serious concerns about its authority to allow for such a phase-in of the standards. C AA section 211(o)(3)(B) states that the renewable fuel obligation shall “consist of a single applicab le percentage that applies to all categories of persons specified” as obligated parties. This ki nd of phase-in approach wo uld result in different applicable percentages being applied to different obligated parties. Further, such a phase-in approach would provide more relie f to small refineries operated by small refiners than that provided under the small refinery provision. T hus 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 fo r 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 sma ll 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 ex ercises of discretion unde r the RFS1 program and

with the discretion afforded to EP A 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 requireme nts 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. Th e Panel also recommended that EP A invite comment on allowing RINs to be used interchangeably for small re finers, but not propose this concept because under this approach small refiners would arguably be su bject 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 le vel 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 intercha ngeable 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 acc ount for four different categories of RINs and

rural small refiners will suffer economic hardship and disadvantag e 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 ba sis 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 a bout the RIN system. EPA raised

the concern that this could lead to some redund ancy since EPA is required to publish a notice of the applicable RFS standards in the Federal Regi ster 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 th ey believe that a prog ram 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 Pa nel 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 this42 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 in clude information to help inform industry about the RIN system in the annual notice of th e 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 re finer participation in the development of the review process. (For more informati on 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 ru le, we believe that such information could be helpful to industry, especially to sma ll 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 c ould 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 w ill also publish annual summa ries of the Production Outlook Reports.

7.4.7 Extensions of the Temporary Exemptio n Based on Dispropo rtionate Economic Hardship

Panel Recommendations

While SERs did not specifically comment on th e concept of hardship provisions for the upcoming proposal, the Panel noted that under CA A 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 petiti on EPA for this case-by-case hardship relief at any time.

The Panel recommended that EPA propose in th e 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 hardsh ip provision for small refiners that do not operate small refineries that is comparable to that provided fo r small refineries under section 211(o)(9)(B), using its discretion under CAA sect ion 211(o)(3)(B). This would apply if EPA does not adopt an automatic extension for small refiners, and would allo w those small refiners43 that do not operate small refineries to apply for the same kind of extension as a small refinery.

The Panel recommended that EPA ta ke into consideration the resu lts 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 re fineries and small refiners in the RFS2 proposal program similar to those provide d 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 dispr oportionate economic hardship in meeting the requirements of the RFS2 program (per CAA se ction 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 th at 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 dispropor tionate 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 hard ship provision was included in EPAct, and commented that any extension of the exempti on past 2010 should be limited to such cases, and only to the specific small refinery (not small refi ner) 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 shoul d 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 a nd 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 th e temporary exemption ba sed 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 progra m, 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 th ose small refiners that do not operate small44 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 informati on gathered from annual reports and RIN system pr ogress updates, as recommende d by the SBAR Panel.



### 7.5 Reporting, Recordkeeping, and Other Compliance Requirements

Registration, reporting, and recordkeeping ar e 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 require ments 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 Secti ons II and III of the final preamble for more detailed information on these and other registra tion, 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 fi rst 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 an alysis of the potential impacts of our regulations on small businesses, we were able to estimate annua l 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 w ould 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 sa les), and that these costs would actually be negative (or, a cost savings)—ranging from -3.15% to -0.94%. The ga soline 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 re finers 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’ sale s, with estimated gasoline and di esel 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 a nd 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 gall on 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 an alysis of the emission impacts of biodiesel using publicly-available heavy-duty, in-use diesel chassis and engine ex haust emissions data.

We investigated the emission impacts on NOx, PM, HC, and CO of 20 volume percent biodiesel fuels produced from various animal- an d 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 biodies el 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 Dr aft 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 ch assis 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 st atistically 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 poi nt to a load-dependence of NOx emissions for heavy-duty highway engines and chasses. The di fference 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 -- r econciles 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 fro m 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 pert inent data sources publis hed in the scientific

and automotive literature between 2002 and 2007. Th e supplemental data wa s comprised of late model year engines, vehicles, and technology gro ups. A list of all data sources used in this analysis appears in the appendix to this doc ument as does the 2002 Draft Technical Report.

The focus of the analysis proceeded from ge neral 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 cy cles run on plant- and animal-based biodiesel fuels; in Case 5a, 5b, and 5c, the most-specifi c fuel-cycle combinations, we examined heavyduty engine and chassis data fo r 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 materi als 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, rapese ed/canola, and coconut) and animal-based (tallow, lard, a nd grease) biodiesel fuels,

• Case 2: All cycles tested on soybean-based biodiesel fuel,

• Case 3: FTP and UDDS cycles test ed 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 chasse s tested on soybean-based biodiesel fuel run on light-duty cycles,

• Case 5b: Engines and ch asses tested on soybean-based biodiesel fuel run on medium-duty cycles, and

• Case 5c: Engines and chasse s 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 a48 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 fo cused 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 c onclusions of our 2002 Dr aft Technical Report, citing its disproportionate reliance on DDC engine data. These researchers argued that these engines may not behave in a manner indicative of th e actual, in-use fleet as a whole. To help address these concerns, we supplemented the data base 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 heav y-duty highway chassis data. Establishing compatibility between heavy-duty highway engine data and heavy-duty highway chassis data would allow us to make more-compl ete use of all emissions data in the database. In turn, this would allow us to perform more robust statistical an alyses. The results of this engine and chassis data compatibility analysis ar e 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 compri sed of data initially used in our 2002 Draft Technical Report, supplemented by pertin ent 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 a ppears 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 ob servations with appr oximately 560 additional observations comprised of la te model year engines, ve hicle, and technology groups.

Candidate data were first sc reened 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 Re port for a discussion of EPA data QC/QA considerations). New data meeting these criteri a were entered into the database developed for the 2002 Draft Technical Report. These cr iteria 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 ca n be used in typical heavy-duty diesel engines without engine modifications. As a result, a ll emulsions and non-biodies el oxygenated blends with more than 20 vol% oxygenate were excluded fro m the final database used in the analysis. Also, synthetic fuels, such as those produced us ing 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 pl ans for commercialization, such as those with innovative combustion chamber geom etries, were excluded from the database. Likewise, singlecylinder research engines were excluded from consid eration, even though the associated full-size parent engine might have been appropriately includ ed in the database, had it been tested. Singlecylinder engines do not appear in heavy-duty appl ications. 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 biodi esel fuels used in a particular study also played a role in determining if data from that st udy would be included in our anal ysis. For example, we excluded

data from all studies that did not test at least two different biodiesel c oncentrations 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 presen ted a previously-published set of data in a new publication for the purposes of comparing the tw o 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, a ttempts were made to obtain it from the study author(s). Raw data obtained from author(s) were included in our

database after succ essful screening.

A2.2 Criteria for Selecting Test Cycles

We selected cycles which were representa tive of actual, in-use operating conditions. While the Federal Test Procedure (FTP) transient cycle most-closely reflects actual, in-use operating conditions, we incl uded data from a number of other studies that used atypical test cycles which were adequately comprehensive in th eir 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 cycl es 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 re sults. Only NOx emi ssions data generated by the AVL 8-Mode test wa s included in our database.

• Combined International Local Cycle and Commuter (CILCC) – A transient cycle developed by NREL for testing Class 4 to Cla ss 6 vehicles. It is intended to simulate urban delivery driving conditions for heavy-duty vehicles.

• City-Suburban Heavy-Ve hicle Cycl e (CSHVC) – A transient cycle developed by West Virginia University. It is intended to simulate low-speed urban/ suburban driving conditions of heavy-duty vehicles a nd is punctuated with frequent stops.

• Freeway Cycle – A transient cycle intended to simulate four-lane highway driving conditions of heavy-duty vehicles, in cluding 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 operatin g conditions and was deve loped to simulate a variety of heavy-duty truck and bus drivin g 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 Coordi nating 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 fe edstock materials. Th e biodiesel feedstock

materials found in our databa se and their percentages are listed in Table A2-B.52 Table A2-B.

Biodiesel feedstock material ob servations 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 anima l-based biodiesel (See Ta ble 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 expre ssed as a function of percent biodiesel (0 or 20 vol%), vehicle class (Class 1-2a or Class 2b-8), the interac tion of percent biodiesel and53 vehicle class, test cell type (cha ssis test cell or engine test cell) , and the interaction between test cell type and percent biodiesel. Each fixed-e ffect 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 f our standard deviations from a mean of 0 are

considered outliers and remove d 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 bi odiesel. A significance criterion of p < 0.05 was used for all analysis. See S ection II of the 2002 Draft Technical Report for

additional discussion and derivations.



### A3. Results

This section contains the results of the bi odiesel 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 Secti on 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-depende nce 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 Hig hway 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 h eavy-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%) consiste d 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 w ould allow us to make more comp lete use of all emissions data in the database, which, in tur n, would allow us to perform more robust statistical analyses.

Moreover, some researchers criticized th e conclusions of our 2002 Draft Technical Report, citing its dispropor tionate 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 xFuel-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 tes ting is often deficient and non- standardized vis-à-vis 40CFR86- 2007 and 40CFR1065 for test specification and test equipment, respectivel y. Deficiencies

associated with non-standardized chassis test cel ls 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 feedstock55 materials to cycles aggregated into light-, medi um-, and heavy-duty test cycle categories, which were run exclusively on 20 vol% soybean-based biodi esel fuel. Heavy-duty highway engine and chassis emissions data were statistically comp arable for NOx and HC and were subsequently pooled for our analysis. Heavy-duty highway en gine and chassis emi ssions 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 (ta llow, 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 fu els, 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 decr ease 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 pl ant-based biodiesel, whereas in Case 2, the fuel is composed of 20 vol% soybean-based biodiesel onl y. The results suggest that the removal of animal-based and/or rapeseed/ca nola/coconut-based biodi esel fuel feedstock materials may have a slight impact on some exhaust emissions. Incr eases in emissions of 0.2 %, 2.0%, and 0.3% are observed for NOx, PM, and CO, respectively, relativ e 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 re searchers in an attempt to help explain the differences in exhaust emissions between plan t-based and animal-base d 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 test ed 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 d ecrease 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 a ppear 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 engi nes and vehicles, it is possible that the Case 3 results may be a better indicator of ac tual, in-use biodiesel emissions impacts.

Case 4: DDC vs. non-DDC engines test ed on soybean-based biodiesel fuels Our fourth fuel-cycle combination sepa rately examined DDC and non-DDC engines tested on the cycles specified in Case 1 a nd 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 en gines 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, a nd HC emissions. As such, this finding should help alleviate earlier concerns that the disp roportionate representati on 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 fuelsOur 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 test ed 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 me dium-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 re spectively, relative to the base fuel.

Case 5c: Heavy-duty cycles tested on soybean-based biodiesel fuels Our seventh fuel-cycle combination examin ed 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 heav y-duty cycles, NOx emissions were found to increase by 5.1%, relative to the base fuel, wh ereas 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 th an 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 HWY5558 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 en gine 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 ofwhich 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 discu ssed in Case 5a.

Case 5a, 5b, and 5c: Load-dep endent emissions impact on NOx The load-dependence of NOx emissions obser ved in this analysis is apparent when comparing Case 5a (light-load cy cles) to Case 5b (medium-load cycles) to Case 5c (heavy-load cycles). However, results for the light-load c onditions 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 engi nes 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 r ealistic representation of operating conditions

encountered in-use.

Case 5b vs. Case 5c: Load-d ependent 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 gr eater 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 lo ad, 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 imp acts 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 en gine 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 ofwhich 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 discu ssed 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 Anal ysis 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 corre lations 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 T echnical 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 e r c e n t c h a n g e i n e m i s s i o n s NOx

HC CO PM

Table A3-D. Emission impacts from the 2002 Draft Technical Report for 20 vol% soybean-based biodiesel a dded 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 c onsistent 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 f ound 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 th e results of the 2002 Draft Technical Report.62 Figure A3-B. Emission impacts from the 2002 Draft Technica l Report by percent biodiesel content for soybean-based biodiesel added to an aver age base fuel with new results overlaid

SAE paper by Sze et al.

Sze et al . conducted a series of paired fuel te sts comparing certification-grade highway diesel fuels with 5 to 50 vol% soybean-based biodie sel 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 cons umption 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 e r c e n t c h a n g e i n e m i s s i o n s NOx

HC CO PM63 Figure A3-C. NOx emissions for 20 vol% and 50 vol% soybea n-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, rang ing 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 re port for Cases 5a, 5b, and 5c as well as those of

Eckerle et al

.

To further elucidate the load-depen dent nature of NOx emissions, Sze et al . reanalyzed chassis-generated NOx emissions data from NR EL 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 R 2 = 0.99 with and without the inclus ion of the NREL dataset. R 2 = 0.99 R 2 = 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 6k64 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-ba sed biodiesel to calibra te chemical kinetic

models. These models were used to examin e NOx production during the combustion process.

The authors concluded that the NOx effect associ ated 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. R 2 = 0.99 R 2 = 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

R 2 = 0.9965 

### References

Studies included in database

Aako P. et al ., "Emission Performance of Selected Bi odiesel 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, "Evalua tion of Methyl Soyate/Diesel Fuel Blends as a Fuel for Diesel Engines," Southwest Research In stitute Final Report to the Am erican Biofuels Association,

December 1993

Clark, N.N., C.M. Atkinson, G.J. Thompson, R.D. Nine, "Transient Emissions Comparisons of Alternative Compression Igniti on Fuels," SAE paper no. 1999-01-1117

Clark N. N. et al ., "Class 8 Truck Emission Testing: Ef fects 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 Tec hnology, University of California, April 1999

Durbin, T.D., et al ., Final Report: "Evaluation of the Effect s of Biodiesel and Biodiesel Blends on Exhaust Emission Rates and Reactivity - 2" , Center for Environmental Research and Technology; College of Engineering; Universi ty of California, Riverside, August 2001

Durbin, T.D., J.M. Norbeck, “Effects of Biodies el Blends and Arco EC-Diesel on Emissions from Light Heavy-Duty Diesel Vehicl es,” Environ. Sci. Technol., 2002, 36, 1686-1691

Durbin T. D. et al ., "Effects of Biodiesel, Biodiesel Ble nds, and a Synthetic Diesel on Emissions from Light Heavy-Duty Diesel Vehicl es," Environ. Sci. Technol., 2000, 34, 349-355

Environment Canada, "Emissions Characteriza tion 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., LaPo inte, 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, 199466 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-Du ty 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 Inte rnational, 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. McCormic k, T.L. Alleman, A.M. Herring, "The Effect of Biodiesel Composition on Engine Emissions from a DDC Seri es 60 Diesel Engine," Colorado School of Mines, Final Report to Na tional Renewable Energy Laboratory, June 8, 2000

Hansen, K.F., M.G. Jensen, "Chemical and Biolog ical 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 Biodies el 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 Biodies el in an Urban Transit Bus Powered by a 1981 DDCC8V71 Engine," National Biodies el 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 Soya te 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 Missouri67 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 Standard s," 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 Bi odiesel Fuels,” SAE paper no. 2003-01-1866

National Resources Canada, "National Resource s Canada/Fiba Canning - Biodiesel Freightliners," National Resources Ca nada 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 Si xth 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 Feedstoc k 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 De monstration with Yellows tone National Park," University of Idaho, August 199968 Rantanen, L., S. Mikkonen, L. Nylund, P. Kociba, M. Lappi, N. Nylund, "Effect of Fuel on the Regulated, Unregulated and Muta genic 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. Ma rshall, “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 Evaluatio n of Rapeseed Derived Biodiesel Fuels," Southwest Research Institute, Final Report for Montana Department of Environmental Quality,

November 1996

Sharp, C.A., "Characterization of Biodiesel Ex haust Emissions for EPA 211(b)," Southwest Research Institute repor t 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," S outhwest Research Institute, AD A353968/PAA,

November 1998

Smith, J.A., D.L. Endicott, R.R. Graze, "Biodi esel 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 th e 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. 97290469 Stotler, R.W., D.M. Human, "Transient Emissi on Evaluation of Biodiesel Fuel Blend in a 1987 Cummins L10 and DDC 6V-92-TA," Engineerin g 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 E missions,” 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 Tr ucks 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 Opera tion 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 Fu el - 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-E ster of Rapeseed Oil on Combustion and Emissions of DI Diesel Engines," SAE paper no. 932801

Hemmerlain, N., V. Korte, H. Richter, G. Sc hröder, "Performance, Exhaust Emissions and Durability of Modern Diesel Engines R unning on Rapeseed Oil," SAE paper no. 910848

Humke, A.L., N.J. Barsic, "Performance and E missions 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 Emi ssions 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., Fern andez, J., "Diesel Emissions from Biofuels Derived from Spanish Potential Vege table Oils," Fuel, 2005, 84(6), 773-78070 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 Greas e 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 Tes ting 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. Gaut am, "Emissions from Nine Heavy Trucks Fueled by Diesel and Biodiesel Blend without En gine Modification," Environ. Sci. Technol., 2000, 34,

933-939

Studies not included because test cycle nonstandard/unrepresentative Adelman, A.J., "Emission Evaluati on Test Report for a Comparative Analysis of Emissions Among Petroleum Diesel and Biodiesel Blends fi red in a Large Diesel Engine," AirNova, Inc., January 1998

Akasaka, Y., T. Suzuki, Y. Sakurai, "Exhaust E missions of a DI Diesel Engine Fueled with

Blends of Biodiesel and Low Sulf ur 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," Mi chigan Technological University, December 1995

Chang, D.Y.Z., J.H. Van Gerpen, "Fuel Prope rties and Engine Performance for Biodiesel Prepared from Modified Feedstocks," SAE paper no. 97168471 Chang, D.Y., J.H. Van Gerpen, "Determinati on 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 En gine 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 Este r," 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, "Investiga tions 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 Soyb ean 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 Copenha gen," 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 E missions from Clean Diesel Fuels," SAE paper no.

1999-01-1121

Zhang, Y., J.H. Van Gerpen, "Combustion Analys is of Esters of Soybean Oil in a Diesel Engine," SAE paper no. 96076572 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 Biodi esel 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 Seri es 60 Engine Operating at High Altitude," Final Report to Nationa l Renewable Energy Laboratory, September 1994

Note : CO 2 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," BioEnerg y '98: Expanding BioEnergy Partnerships

Taberski, J.S., C.L. Peterson, J. Thompson, H. Ha ines, "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," Universi ty of Minnesota, September 24, 1998

Reason : Emission measurements were made in the field with portable emission

measurement devices73 Yoshimoto, Y., M. Onodera, H. Tamaki, "Reduc tion 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 Biodies el Fuel on Emissions from Heavy-Duty Non-Road Vehicles", Final Report for the SCAQ MD 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 CO 2 Emissions from an Off-Road Diesel Compactor Running on Regular Diesel, Biodiesel a nd 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 onlin e 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-methy l,
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.htm74 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 Co llaborative 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 Coasta l 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/prog rams/tmdl/lake_tahoe/docs/laketahoe _tmdl_techrpt.pdf

. 25 Chesapeake Bay Program, Science and Technical Advisory Committee, Workshop on Atmospheric Depos ition 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,
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30 U. 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
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39 Mississippi River/Gulf of Mexico Watershed Nutrient Task Force, op. cit., page 16.

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. 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/

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50 Renewable Fuels Association, “Ethanol Biorefinery Locations,” http://www.ethanolrfa.org/industry/locations , April 2008.

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52 Simpson, T. W., A. N. Sharpley, R.W. Howarth, H.W. Paerl, and K. R. Mankin

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53 Chesapeake Bay Foundation, 2007 State of the Bay, 2007, available online at:
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. 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

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62 McGuire, V.L, Changes in Water Level and Storage in the High Plains Aquifer, Predevelopment to 2005: U.S. Geological Survey

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64 U.S. Environmental Protection Agency, Office of Water, FACTOIDS: Drinking Water and Ground Water Statistics for 2007, EPA

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67 See 40 CFR, Part 141, Subpart O, App. A.

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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.
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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

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.