1 

## Chapter 4: Impacts on Cost of Renewable Fuels, Gasoline, and Diesel

4.1 Renewable Fuel Production Costs

4.1.1 Ethanol Production Costs

4.1.1.1 Corn Ethanol

Corn ethanol costs for our work were estimated using a model developed by USDA that was documented in a peer-reviewed journal paper on cost modeling of the dry-grind corn ethanol

process. i The USDA model considers a 40 MMgal/yr corn plant producing ethanol with a primary co-product of distillers dr ied grains with solubles (DDGS). The ethanol yield used in the model is 2.76 gallons per bushel with 2.0% gaso line denaturant. The model is based on work done in chemical process simulation software to ge nerate equipment sizes, stream flowrates, and material and energy balances. These results can then be put together with feedstock, energy, and equipment cost information in a spreadsheet format to generate a per-gallon cost estimate.

For our primary case scenario, we us ed corn prices of $3.60/bu in 2022 with corresponding DDGS prices of $124.74/ton (a ll 2007$). These estimates are taken from agricultural economics modeling work done for this proposal using the Forestry and Agricultural Sector Optimization Model. Energy prices also play a significant role in the cost of ethanol production. For this we relied on the AEO 2009 re port for projections of energy costs in 2022 and intermediate years of intere st. According to the AEO 2009 updated report the relevant costs are as follows: $7.75 per MMBTU natural gas, $2.57 per MMBTU coal, $30.32 per MMBTU gasoline (~$3.49 per gallon), and $19.31 per MMBTU el ectricity ($0.066 per kWh). All of these prices are in 2007 dollars.

Using the USDA models and the feedstock and energy prices mentioned above we were able to generate a per gallon cost of ethanol production from a dry mill plant that produces dry DGS, uses natural gas as it’s primary fuel sour ce, and utilized no advanced technologies. We did, however, assume that by 2022 the combinatio n of process improvements and more efficient boilers and motors allow the plant described here to produce ethanol with an energy input of 28,660 BTU natural gas per gallon and 2,251 BTU of electricity per gallon. These energy use values are described in more detail in Section 1.5.1.3. The only modification that was made to the USDA model, other than updating the energy and feedstock costs in line with our 2022 projections, was to change the energy de mand of the plant to match our projections 1 . The projected cost of ethanol production from this modified USDA model was $1.63 per gallon. For this scenario corn feedstock minus DDGS sale cr edit represents about 54% of the final per-gallon cost, while utilities, facility, chemical and enzymes, and labor comprise about 22%, 13%, 7%, and 4%, respectively. Figure 4.1-1 shows the cost breakdown for production of a gallon of ethanol. Note that this production model does not account for the cost to ship the DDGS. Those

1 An Excel spreadsheet showing a summary of the outputs of this model and the modifications that were made has been placed in the docket (EPA-HQ-OAR-2005-0161- 2726).costs are external and are expected to increase the price of DDGS the further an end user is located from the plant. While we do not expect th is to be the average cost of ethanol production in 2022 it serves as a baseline cost to which the co st impacts of different types of fuel used for primary process energy, new technologies, and DGS drying will be applied below.

Figure 4.1-1. Cost Breakdown of Natural Gas Dry Mill Corn Ethanol Production (2007$).

The price of energy can vary greatly depending on the source of the energy. We expect, therefore, that the cost of ethanol producti on would also vary depending on whether the production facility uses natural gas, coal, or biom ass as its primary thermal energy source. In order to determine the impact that different fuel sources had on the cost of ethanol production in 2022 we first had to project how much of the co rn ethanol industry will use each fuel type in 2022. For these projections we relied on our own current industry characterization as well as projections made by Steffen Mue ller of the University of Illinois at Chicago. The resulting mix of primary fuel type used in the corn etha nol industry is shown in Table 4.1-1 below.3 Table 4.1-1. Breakdown of fuel types used in estimating production cost of corn ethanol Fuel Type Total by Plant Type Plant Type Biomass Coal Natural Gas Biogas All Fuels Coal/Biomass Boiler 11% 0% - - 11% Coal/Biomass Boiler + CHP 10% 4% - - 14%

Natural Gas Boiler - - 49% 14% 63% Natural Gas Boiler + CHP - - 12% - 12%

Total by Fuel Type 21% 4% 61% 14% 100%

To determine per-gallon cost impact of coal , biomass, and biogas as a process energy source we relied on the modeling work done by the USDA. The USDA modeled dry mill corn ethanol plants using both natural gas and coal as a primary energy source. Their models take into account the differences in capital costs that result from the differences in materials handling and boiler types necessary to use gaseous and solid fuels. We a ssumed that on average, coal and biomass combustion systems would have the same capital cost due to similarities in feed, ash handling, and emission controls; the same argument can be made for use of biogas combustion relative to natural gas combustion (excluding the digesters or other source). Tables 4.1-2 shows the impact that different primary fuel sources ha s on the overall cost per gallon of corn ethanol production. The overall impact of using different fuel types is very small, less than $0.01 per gallon. Thus, a change in process fuel type has very little impact on the projected future cost of corn ethanol.

Table 4.1-2. Breakdown of cost impacts by fuel type used in estimating production cost of corn ethanol Fuel Type Total by Plant Type Plant Type Biomass a Coal Natural Gas Biogas b All Fuels Coal/Biomass Boiler +$0.009 +$0.009 - - - Coal/Biomass Boiler + CHP -$0.021 -$0.021 - - -

Natural Gas Boiler - - baseline +$0.00 - Natural Gas Boiler + CHP - - -$0.032 - -

Total by Fuel Type - - - - $-0.006

Table 4.1-2 shows that for our cost analysis we made the assumption that biomass firing has the same overall cost impact on ethanol production as coal firing . One reason for this is that our analysis of biomass feedstock costs suggests a range of $72 per ton in future years which is comparable to the cost of coal supplied to non- electric-power industries after transportation is included. ii Wood and stover biomass has on average a pproximately 85% of the energy content of coal on a mass basis, varying by type of bi omass and coal, again suggesting that they are comparable on an energy per mass basis. iii Nevertheless, we still project that biomass will displace some coal in the future. If biomass transportation and storage costs are small it isplausible that some ethanol produ cers near biomass sources (such as the Midwest and Southeast) may have a cost incentive to transition from coal to biomass for process heat. In addition, ethanol plant owners may want to improve their greenhouse gas performance to increase capacity.

Similarly, for our cost analysis we made the assumption that biogas combustion for process heat would have the same cost impact on ethanol production as na tural gas combustion. Use of biogas is somewhat different from bi omass in that it would require some capital investment for on-site anaerobic digesters and re lated feedstock and gas handling equipment. However, we anticipate the digester feedstock its elf would have very low or no cost, thus it is reasonable to assume that the ongoing operating costs besides capital would be considerably less than purchasing natural gas. As with biomass combustion, most plants utilizing biogas would take advantage of situations such as co-location with feedlots or MSW facilities where suitable biomass resources are available.

Another factor that we expect to have a significant impact on the cost of ethanol production in 2022 is the developmen t and adoption of new technolog ies. There are several new technologies currently available or under develo pment that reduce the energy requirements of ethanol production facilities. These include more efficient boilers, motors and turbines, raw starch hydrolysis, corn fractionation, corn oil extraction, and ethanol me mbrane dehydration. These technologies, and their impact on the projected average energy usage of an ethanol plant in 2022, are discussed in section 1.5.1.3. In addition to reducing cost by decreasing an ethanol plant’s energy demand, two of these technologie s, corn fractionation and corn oil extraction, produce new co-product streams that also have an impact on the cost of ethanol production. We have adjusted the USDA cost model to reflect th e impact that reduced energy usage of ethanol plants in 2022 and new co-products have on the average cost of ethanol production 2 . The impact of these technologies is outlined in Tables 4.1-3 and 4.1-4 below.

Table 4.1-3. New Technology Impacts on Corn Ethanol Cost Capital Cost (40MMGY) Capital Charge (per gallon) Operating cost change New coproduct profit Additional Profit More Efficient Boilers, etc. None (included in baseline) N/A N/A N/A $0.00

Raw Starch Hydrolysis $0 $0.00 -$0.066 N/A $0.066

Corn Fractionation $14,000,000 $0.016 -$0.003 $0.106 $0.093

Corn Oil Extraction $5,100,000 $0.019 -$0.037 $0.060 $0.079

Membrane Separation $1,500,000 $0.006 -$0.070 N/A $0.064

2 As an example, the spreadsheet with adjusted values for corn oil extraction has been placed in the docket (EPAHQ-OAR-2005-0161-2727).5 Table 4.1-4. Breakdown of cost impacts by technology for es timating production cost of corn ethanol Technology Percent of Plants Adopting Technology Cost Impact (Change from Baseline) Weighted Cost Impact

More Efficient Boilers/Motors/Turbines 100% Included in Baseline $0.00

Raw Starch Hydrolysis 22% -$0.066 -$0.015

Corn Fractionation 20% -$0.093 -$0.019

Corn Oil Extraction 70% -$0.079 -$0.055 Membrane Separa tion 5% -$0.064 -$0.003

Total N/A N/A -$0.092

Whether or not the distillers grains and solubles (DGS) are dried also has an impact on the cost of ethanol production. Drying the DGS is an energy intensive process and results in a significant increase energy usages as well as cost. The advantages of dry DGS are reduced transportation costs and a product that is less susceptible to spoilage, and can therefore be sold to a much wider market. If the DGS can be sold wet, the cost of ethanol production can be reduced by $0.083 per gallon. A 2007 survey of ethanol producer s indicated that 37% of DGS were being sold wet. We anticipate that this percentage of we t DGS will remain constant in 2022. The net cost impact of selling 37% of the DGS wet is an average cost reduction of $0.031 per gallon.

The effect of plant scaling on production cost can be estimated by applying an engineering scaling factor to all plant equipment. In past rulemakings involving modifications to refineries we have used a material scaling factor of 0.65. This factor is applied as an exponent to the ratio of the new size to the original size, the result of which is then multiplied by the original capital cost. The fact that this figure is less than 1.0 reflects the per-unit or per-gallon savings that is often realized when processes are scaled up. However, there is information suggesting that a general factor may be considerably high er for ethanol plants. A factor of 0.84 was put forth in a recent publication on dry mill ethanol production. iv Using this larger factor, we find that the change in per-gallon production cost due to economies of scale is very small over the range of typical plant sizes, on the order of $0.02 between 40 and 100 MMgal/yr. Thus, in computing production costs for this rulemaking we chose to ignore effects of any changes average plant size.

In order to generate a cost estimate for the production of corn ethanol in the year 2022 the cost impact of each of these factors, primary fu el type, advanced technologies, and DGS drying, were applied to the ba seline cost produced by the USDA m odel. When each of these cost reduction have been applied to th e baseline cost, the result is a projected cost of production for corn ethanol of $1.50 per gallon in 2022. As with the energy and input costs, this production cost is also in 2007 dollars. We believe this num ber is an accurate projection of the cost of ethanol in 2022 based on the best available info rmation. For a summary of the cost analysis, including the baseline cost and all the adjustments, see Table 4.1-5 below.Table 4.1-5 Average Ethanol Cost of Production in 2022 Baseline Cost of Production (Natural Gas, no new technologies, 100% dry DGS) $1.627/gal

Fuel Type Cost Impact -$0.006/gal New Technology Cost Impact -$0.092/gal DGS Drying Cost Impact -$0.031/gal Average Cost of Ethanol Production (2022) $1.499/gal

4.1.1.2 Cellulosic Ethanol

4.1.1.2.1 Feedstock Costs

In order to allow for an accurate estimate of the cost of production for cellulosic biofuels in 2022 we must first determine the cost of the cellulosic feedstocks. We relied on the Forest and Agriculture Sector Optimization Model (FASOM) to project the roadside cost of agricultural residues, energy crops, and wood residues for 202 2. For more details on the FASOM model see Chapter 5 of the RIA. FASOM does not m odel MSW costs. We therefore relied on conversations with companies w ho intend to use MSW as a renewable fuel feedstock, as well as our own analysis of the necessary steps require d to acquire appropriate feedstock streams from MSW to help inform our feedstock cost estimates. In order to validate the reasonableness of the FASOM cost estimates we also conducted an inte rnal assessment of the potential agricultural residue, energy crop, wood residue, and MSW feed stock systems. The description of this analysis is discussed in Section 4.1.1.2.2.

To each of these roadside costs we added the cost of transportation and secondary storage where appropriate based on our ow n modeling of cost of secondar y storage and transportation. The framework of this modeling is discussed in Section 1.3.3 and a more detailed discussion of the assumptions and equations used in this model can be found below. Table 4.1-6 shows a summary of the individual roadside costs for each of the feedstock sources, as well as average costs for storage and transport and grinding of th e materials. A weighted average cost, based on the percentage of the overall feedstock supply each of the categories is expected to represent according to the FASOM model, is also given.7 Table 4.1-6 Summary of Cellulosic Feedstock Costs Ag Residue Switchgrass Forest Residue MSW 36% of Total

Feedstock 49% of total Feedstock 1% of Total Feedstock 15% of Total Feedstock Mowing, Raking, Baling, Hauling, Nutrients and Farmer Payment $34.49/ton Land Rent, Mowing, Raking, Baling, Hauling, Nutrients and Farmer Payment $40.85/ton Harvesting, Hauling to Forest Edge,

$20.79/ton Sorting, Contaminant

Removal, Tipping Fees Avoided $15/ton

Hauling to Secondary Storage, Secondary Storage, Hauling to Plant $21.53/ton (average)

Grinding $11/ton

Total $67.42/ton

Crop Residue Costs

The FASOM agricultural econometric model described in Chapter 5 estimated the roadside price for corn stover, which we used to be representative of all agricultural residues. The FASOM model accounted for harvesting, sh redding, raking, baling and hauling the corn stover to the farm edge, and replenishing the soil w ith nutrients. It predicts a roadside price of $34.49 per dry ton in 2022 for corn residue. In or der to validate FASOM’s cost estimate we also performed an analysis of a possible agricultural residue harvest system. We based our analysis on a Purdue University study of the logistics of corn stover storage and transportation. Our analysis, described in Section 4.1.1.2.2, predicts a roadside cost for corn stover ranging from $44.97 to $46.20 per dry ton, depending on the size of the farms from which the stover is harvested. The FASOM cost is a pproximately $10 per ton lower than the price calculated in our analysis. While this is a significant price difference it is in the same vicinity as the FASOM estimate, and it is not unreasonable to expect th at advances in technology and changes in harvesting practice for corn stover and other agricultural residues will significantly reduce the cost for these feedstocks. For all of the biof uel production cost analysis work, the FASOM price was used as the projected price of agricultural resi due. To this roadside cost was added the cost of transportation and secondary st orage as calculated by the model discussed in Section 1.3. A detailed description of our analysis of a likely agricultural residue harvest system using existing machinery can be found below.

Energy CropsThe FASOM model predicts a roadside cost for switchgrass and similar energy crops of $40.85 per dry ton in 2022. While this costs is high er than the cost of agricultural residues the delivered cost of energy crops is expected to be slightly lower because of the lower transportation and secondary storage costs associ ated with the higher production density of energy crops. The $40.85 per dry ton roadside cost has been used in our cost analysis of biofuel production, with appropriate transportation and storage costs ad ded using the model described in Section 1.3. See Table 4.1-6 for a summary of the expected delivered costs of various feedstocks. Wood Residue

The FASOM model estimates costs for two di fferent types of wood residues, hardwood logging residue ($21.16 per dry ton) and softwood logging residue ($18.37 per dry ton). We decided to use $19.77 per dry ton, an average of th ese two prices, as the roadside cost of wood residue for our analysis of biofuel production co sts. Despite the low roadside cost of wood residues, FASOM predicts that few biofuels produc tion facilities (less than 1%) will use wood residues. We believe that the reason for this is that the high transportation costs for wood residue in the FASOM model cause the delivered cost of wood residue to be re latively high. The FASOM model allowed bi ofuel producers to use only one ty pe of feedstock (wood residue, agricultural residue, energy crops, or MSW). Th erefore, in order for a facility to use wood residues, the entire feedstock supply must come from wood residues. Logging operations are less likely to be concentrated in a small area than other potential feedstock supply systems such as agricultural residues or energy crops. The re sult is that in order to supply a 100 million gallon per year biofuel production plant (the size sp ecified in the FASOM model) with sufficient feedstock from wood residues the residues must be transported long distances. In most cases these high transportation costs outweighed the low roadside costs despite the fact that no secondary storage will be required for wood residue s. If this assumption were relaxed and the FASOM model allowed bi ofuel production facilities to use lo cally available wood residues in combination with other feedstocks such as agri cultural residues, energy crops, or MSW, we believe that much more wood resi dues would be selected for biof uel production. At this point, however, it is not clear whether biofuel production facilities would require uniform feedstock or be able to process a diverse feedstock stream. This uncertainty was one of the factors in our decision to use the FASOM estimates for our cost analysis work.

Municipal Solid Waste

Unlike the other three sources of cellulo sic feedstock, the FASOM model does not predict a roadside cost for MSW. We therefor e relied on our own analysis, together with input from the Office of Solid Waste and conversations with companies who intend to use MSW as a feedstock for producing biofuels. One of the biggest costs associated with using MSW as a biofuel feedstock is the cost to sort the waste material. Some materials, such as metals and contaminated materials, must be removed so that they do not interfere with the biofuel production process. Other materials, such as paper or plastics, may also be separated due to their value as recovered materials or in order to increase the renewability content of the resulting fuel. The Office of Solid Waste has estimated that so rting costs will likely be $20 - $30 per ton. In addition to sorting costs, the biofuel producer wo uld also have to pay for the transportation and disposal of unusable material. These costs may be relatively high due to the nature of this9 contaminated material. Offsetting these costs would be tipping fees received by the biofuel producer, which we estimate would be in the $30 per ton range.

In addition to our own analyses presented in Section 4.1.1.2.2, we also contacted companies that intend to use MSW as a feedstock for biof uel production. In confid ential conversations these companies indicated that they believed that MSW would be available, at least initially, at close to zero net cost, after accounting for the recei pt of tipping fees and the sale of recoverable materials. One company told us that whether the MSW was sorted or unsorted was not expected to make much of a difference from a cost perspective, as they expected that the higher tipping fees received for unsorted MSW and the money received from the sale of the recovered materials would pay for the cost of sorting. We believe that while these costs may be accurate, they are likely only representative of the cheapest and most readily available sources of MSW. It is likely that as more biofuel producers seek to use MSW as a feedstock, the cost of this feedstock source will increase. Competition from waste to energy companies may be another driver for the cost increase of MSW. Taking all this into acc ount, we have conservatively estimated that the average cost of MSW will be $15 per dry ton in 2022. While this is an admittedly conservative estimate, MSW remains the cheapest source of feedstock for the production of biofuels. More details of our cost assessment for MSW can be found below.

4.1.1.2.2 EPA Internal Assessment of Potentia l Roadside Cellulosic Feedstock Costs

While the FASOM model provides an estimate for the roadside costs of agricultural residue, energy crops, and wood residue, we were al so interested in performing our own internal assessment of the potential roadside cost of thes e feedstocks. This assessment served as a second estimate for the costs of these feedstocks, and allowed us to verify the costs generated by FASOM. They also allowed us to have a better understanding of the costs of each of the steps in the harvest process. In each of these cases we found that our ow n assessments matched reasonably well with the roadside costs reported by FASOM. Our internal assessment of the roadside costs of crop residue, energy crops, w ood residue, and MSW is shown in detail in the following sections.

Crop Residue

We could have used any of the crop residues as an example feedstock in the following discussion, since similar logistics a pply to all of them. We chose to use corn stover, e.g., the stalks, leaves, and cobs that remain following grain harvest, since it is likely to represent a significant portion of cellulosic feedstocks in the future. Since there is no equipment specifically designed to harvest corn, the system we descri be below uses combines, mowers, rakes, balers, and bale haulers already in use for harvesting hay or straw. Differences in stalk or stem diameter and density, bale density, moisture content, machine field speeds and efficiencies are a few things that make it relatively more difficult to harvest stover than hay or straw. One of the main concerns is that the density of the large stover bales, whether round or rectangular, can be as little as one-half that of similar dimension hay bales, which usually translates into higher transportation costs. vMost biomass feedstocks must be harveste d, stored, and transported to a processing facility before they can be converted into etha nol. At present, there are no commercial sized cellulosic ethanol plants in the U.S. Li kewise, there are no commercially proven, fullyintegrated feedstock supply systems dedicated to providing any of the crop residues or other feedstocks to ethanol facilities of any size. We emphasize ‘integrated feedstock supply systems’ because logistically the delivery of a feedstock to a processing facility w ill require the planning, executing, and controlling of several different, closely integrated operations, e.g., feedstock harvesting, gathering, storing, and moving by road and rail. Apart from the large numbers and wide variety of equipment, these operations will require professiona l and technical support services and personnel such as office space, st aff, and office equipment such as computers and printers. Also, engineers, light- and heavy- duty equipment operators, vehicle maintenance personnel and repair and storage facilities for tractors, rakes, ba lers, loaders, and trucks and trailers, as well as transportation infra structure planning and management.

Ordinarily, to determine the ope rational sufficiency and efficiency of such a system, we would ‘analyze’ it. We would first break it down into its component parts or essential features and then study them, e.g., how much they cost, and how and/or whether they operate efficiently within the ‘system.’ However, no such system cu rrently exists. Therefore, we ‘synthesized’ a feedstock supply system in order to analyze it. We used a Purdue University, School of Industrial Engineering simulation study of corn stover logistics from sa tellite storage to an ethanol plant, to set up our feedstock harves ting and gathering operation. Purdue’s notional cellulosic ethanol plant was to be constructed next to an actual existing corn grain plant in northern Indiana. They used discrete event simulation software and GIS tools to study the transportation logistics associated with supplyi ng the conversion facilit y directly from satellite storage. They identified 785,200 available ac res out of 848,453 potential acres, on 2,052 actual farms, of 200-, 400-, or 800-acres, in 12 nor thern Indiana counties within 50-miles of the production facility (they disregarded fields or farms of less than 200-acres). We reproduced their original table as Table. 4.1-7.

Table 4.1-7 Feedstock Availability at Various Distances From South Bend, IN

Average Farm Size

200 400 800 Average Distance County Actual Acres Cumulative Acres Acres Available Acres Cumulative Acres bales/ day bales/day /farm set 12 St Joseph 69 69 74 51 35 63 63 4,956 4,956 25 Elkhart 150 219 90 47 23 55 118 4,328 10,257 Marshall 110 52 41 76 194 5,928 30 La Porte 113 332 113 73 70 108 302 8,453 8,453 35 Starke 60 392 34 39 41 55 357 4,328 4,328

40 Kosciusk

o 93 485 108 66 43 82 439 6,461 6,461

45 Lagrange 132 617 53 47 20 45 485 3,560 9,049 Fulton 86 66 43 70 555 5,489 50 Porter 225 842 76 59 34 66 621 5,175 18,224 Noble 115 47 21 59 679 4,595 Pulaski 39 72 64 108 787 8,453

842 998 619 435 787 61,726 61,72811We initially assumed that the stover had been harvested (square bales), gathered, fieldtransported, and stored at seven-satellite storage areas located near the corn fields. vi However, upon further study, we determined the counties that Purdue combined into each of the farm sets, weren’t anywhere near each other. In reality, it would have been far too costly to gather all the bales from the Porter, Noble, and Pulaski counties into one site, because these three counties are actually separated by other counties. Rather than try to construct seven satellite storage sites, we constructed a site at the center of each county. This was done in order to estimate the cost to collect the bales from all the fields in each c ounty. We determined that the distance from the center of each of the Porter, Noble, and Pula ski counties, as well as the other two so-called farm-sets, to the ethanol plant was about equal, so regardless of whether we treat them as single sites, the transport costs for the bales to the ethanol plant will be the same. We ‘synthesized’ the feedstock system to harvest, gather, field tran sport, and store stover bales at the 11-notional satellite storage units rather than the seven farm-set units used in the Purdue transportation model (our study was not done in c onjunction with the Purdue study; rather we used their information/data as the basis from which to synt hesize our notional operation). The format we chose to analyze was to shred, rake, square-bale, gather, field-side, and then load and haul the bales to satellite storage; then, as needed, haul the bales to the processing plant.

Rather than guess at how such a system should look and function, we carefully studied several similar systems that were put forward by various agricultural and biological experts. vii , viii ,

ix , x, xi, xii, xiii, xiv, xv We used the American Society of Agricultural and Biological Engineers (ASABE), 2007 Standards, Engineering Practices , and Data as the primary source for our equipment capital and operating co st estimates. It has a mach inery management section, ASE EP496.3, FEB2006, devoted to providing helpful info rmation in making management decisions involving machine power requirements, capacitie s, cost, selection, and replacement, as well section ASAE D497.5 FEB2006, with data which includes representative values of farm machinery operating parameters, to aid managers, planners, and designers in estimating the performance of field machines. These data are intended for us e with ASAE EP496 (some data are also presented in equation form for easier use with computers, etc.). xvi We used these sections along with other examples by other experts to estimate the machinery capital and operating costs for our analysis. xvii , xviii , xix, xx, xxi We were able to get some machinery purchase prices from vendors whose identities are confidential. We reduced the equipment listed price by 10% to determine the purchase price, a standard industry estimating practice. Otherwise, most of the data used to calculate machinery costs were generated with equations and appropriate data from the ASABE 2007 Standards. We used the e quipment, list and purchase prices, along with their power and size estimates, with the suggested data and equations, me ntioned previously, to calculate the lifetime hours and year s, annual use, field efficiency, salvage value, fuel and oil use and cost (we obtained vendor quotes for oil cost), capital charge, repairs, insurance, housing, taxes, and labor. We compared our data, where appropriate, with the USDA 2006 Price Summary, published July 2007. xxii We also compared our results with those generated by the experts we listed earlier in this paragraph.

The Purdue study was based on supplying a 100-million gallon per year ethanol production facility, which they assumed would convert the stove r-to-ethanol at 72-gallons per ton; they assumed that 2-dry tons corn stover c ould be harvested per acre, as did we. We used National Agricultural Statistical Service (NASS) data to determine the actual corn grain yield in2005 (the data year for the Purdue study) fo r the counties studied in the simulation. We determined how much corn each county produced and from that how much stover was produced, 2,455,000 tons or 3.12 dry tons per acre, with an assu med harvest index (HI) of 1:1 (see Table. 4.1.1.2.2.) xxiii HI is based on the assumption that, for a single corn plant, half of the above ground dry matter is made up of stover a nd the other half is made up of grain. This is a fairly common assumption, although more than one group of resear chers has found that this 1:1 ratio may not be the most accurate under some conditions. When considering above ground dry matter before and after full grain physiological maturation, they found that a stover to grain ratio of 0.8 to 1 may be more realistic especially when grain moisture is between 18 and 31 percent. xxiv

Table 4.1-8 NASS Indiana Data and Purdue Data Comparison

USDA-NASS – Counties in State of Indiana - 2005 Purdue Model Year – 2005

Planted Harvested Grain Yield Grain Production Model Available Acres Prorated Grain Production Wet Tons Stover Dry Tons Stover

County acres x 10 3 acres x 10 3 bu/

acre bu x 10 6 acres x 10 3 acres x 10 3 bu x 10 6 x 10 3 x 10 3

St Joseph 71 70 147 10.2 69 65 9.5 266 225

Elkhart 60 53 142 7.6 150 52 7.4 206 174

Marshall 94 89 150 13.4 0 87 13.1 366 309

La Porte 117 112 137 15.3 113 104 14.2 398 336 Starke 61 60 137 8.2 60 56 7.7 214 181

Kosciusko 102 100 149 14.9 93 93 13.8 386 326 Lagrange 55 51 113 5.8 132 45 5.0 141 119

Fulton 90 89 159 14.1 0 78 12.3 345 291

Porter 68 67 137 9.2 225 61 8.4 234 198 Noble 65 62 142 8.8 0 57 8.0 225 190

Pulaski 103 101 152 15.3 0 92 13.9 390 330

855 842 787 3,172 2,455

However, a professor of agricultural engin eering at the University of Wisconsin found that several researchers, going back to 1973 re ported a grain mass fraction of 45% to 55% of total corn crop DM yield. On average, the vari ations seem to confirm the common rule of thumb of one unit mass of stover for a unit mass of gr ain. However, differences among harvesting methods, stages of maturity, and harvest dates can no doubt lead to much of the variation the researchers found in this estimate. His research indicates that the ratio of grain dry mass to total mass increased from about 38% in late August to about 59% in mid-October, during a recent harvest. Therefore, the stover to total ratio declined from 62% to 41%. During the typical harvest period in the Upper Midwest when grain moisture is between 20% and 30%, the ratio of stover to total dry mass was less than 45% and averaged 43%. These results are similar to those found by others. xxv Mainly, because we have no inform ation upon which to base a reason to use something different, we chose to use the 1:1 ratio for corn stover to corn grain. We also assumed 56-lbs per wet bushel (15.5% mois ture) and 47.3-lbs per dry bushel, for the corn grain, to make our stover yield calculations. xxvi Table 4.1-9 summarizes the genera l operating parameters for our study.13 Table 4.1-9 Operating Parameters EtOH Operating Year 350-days/yr On Stream Factor 0.96 Hours per year 8,400-hr/yr EtOH Production Rate 100,000,000-gal/yr EtOH Yield 72-gal/dry ton Feedstock Required per year 1,389,000-dry tons/yr per day 3,970-dry tons/day Expected Dry Matter Loss 11.8% Feedstock Harvested 1,574,000-dry tons/yr Feedstock Yield 2-dry tons/acre Harvest Period Days, 50-days Hours per Day 16-hr/day Harvest Hours 800-hr Format: Shred/Rake, Bale - Lg. Sq. - 3'x4'x8' Field Side - Self-Propelled Wagon Satellite Storage – Pole Barn on Concrete Transport to EtOH Facility – Truck & Trailer

At 72 gallons per dry ton, the processing plant would require 1,389,000 dry tons of stover per year. However, we believe storage and tran sportation losses can be significant and should be taken into account. If, as stated in the report, they harvested 2-tons per acre, they actually harvested 1,574,000 tons of stover, or 64% of th e 2,455,000 tons of available dry stover. The quantity of stover used versus the quantity harvested represents an 11.8% loss. 3 Thus, we assumed that with an 11% loss, we would need to harvest 4,500- dry tons of stover per day, which by the time it reaches the plant will act ually equal 3,970-dry tons – the amount required per day at the ethanol plant. During a 350-day production year, 1.574-million tons of stover would have be stored in a bout 3.5-million, 900-lb bale s (Purdue study bale weight), at the various satellite storage areas. For this study, we assumed all the loss took place between the satellite storage areas and the ethanol plant, rather than guess what the losses would be at various points within the harvest/transport scheme.

In the following analysis, we did not account for the extra time or equipment that would be necessary for inevitable break-downs. Nor was time and equipment factored in for driving between fields and for weather delays. Stover su ppliers face several, in some cases, difficult problems. At best, the actual harvest period is nearly always too short; winter weather can suddenly set in, which in some cases may comple tely stop a potential stover or straw harvest. Once the grain is harvested and the stalks are mowe d, stover usually must be left in the field for three or four days to dry to below 20% moisture before it’s baled, otherwise spoilage or rot as well as spontaneous combustion are possible. If it rains, additional time is required for drying and muddy roads and fields can be badly damage d and the field-soil compacted by the increased

3 We indicated in a previous section that there may be as little as 25% to 50% stover actually available; however, since we didn’t have the computer software and database Purdue used and therefore couldn’t rerun the simulation, we chose to use the data we had.heavy-weight harvest and transport equipment traffic. One expert commented that, “If there’s a rainy harvest, you might as well forget about it. Also, the longer the wet material is left in the field, there’s more of a chance for microbes to eat away at the hemicellulose.” xxvii Delayed baling also raises the chances of dry matter loss. The stover needs to field-dry, so the stover harvest can’t actually begin for at least a few days after the grain harvest starts. But, once it begins it can continue until either it’s finished or until winter weather stops it.

For reasons that weren’t explained in the repor t, the researchers at Purdue chose 50-days for the harvest period, which at their 16-hr pe r day schedule, provided a total of 800-hrs to complete the harvest and store the stover. In this harvest format (800-hrs), most of the machinery will be stored for the balance of the year. Crop harvest schedules in the Midwest and upper-Midwest are determined by the length of the growing season, the time of year when the crops are mature enough to harvest, and the time when winter weather sets in. Under ordinary conditions, farmers use their harvesting machinery during just a few weeks each year. During the past few years, as machinery costs have risen, many farmers have turned to custom harvesters, that move into an area and harvest several farms. A farmer must always weigh the differences in the custom rates and what it woul d cost him to own the equipment and complete the harvest himself, but then store most of the ha rvesting machinery for the rest of the year. In the South, winters are milder and it’s possible to harv est some crops all year long. In such cases, feedstocks could conceivably be harvested and sh ipped to a conversion facility on an ‘as needed’ basis; storage costs could be sa ved and machinery would be used all year long. However, an important factor, when it comes to harvest machinery, is the usable-life of the equipment. The more hours used each year, the more often the machine will need to be replaced. A machine lasts only so many hours, whether it’s used 800 -hrs per year or 8,000-hours per year. We obviously could have arbitrarily c hosen some longer period, but in order to maintain at least some consistency with the Purdue study, we chose to use the 50-day schedule for our study. This short period means we must harvest and stor e a full year’s inventory within a few weeks.

Mow, Shred, Rake: Modern corn combines strip most of the leaves from a corn stalk, but leave up to about half of the stalk standing when they cut it off just below the bottom ear. In the combine, the corn grain is stripped from the cob, a nd the top part of the stalk, the leaves, and the cobs are subsequently discharged out the spreader at the rear of the machine. According to a group of researchers, at the time of grain harvest, of the total stover dry mass, 16% resides in the cob, 7% in the husk, 16% in the leaves, and 60% in the stalk fractions. Of the stalk dry mass, roughly 45% is found in the bottom one-quarter and 80% in bottom one-half of the stalk. If stover yield is to be maximized, harvesting system s must be developed that allow the bottom half of the stalk to be fully harvested. xxviii We summarized the costs to shred and rake in Table 4.1-1015 Table 4.1-10 Corn Stover Shre dding & Raking Operation

Tractor – 245-hp FlailShredder -30’ Tractor 75-hp MFWD Wheeled V-Rake - 20 ft Equipment Factors Purchase price $ 144,502 28,733 59,383 3,660 Useful life yrs 11.3 3.1 11.3 15 Discounted Salvage value $ 11,736 0.00 7,861 Annual use hr 800 800 800 800 Fixed Costs $/hr Depreciation and interest 25.47 14.51 10.06 1.87 Taxes Insurance Housing (THI) $/hr 3.97 0.79 1.63 0.10 Total Fixed Costs $/hr 29.44 15.30 11.69 1.97 Variable Costs Repairs and maintenance $/hr 19.62 14.05 8.06 1.63 Fuel consumption 4 gal/hr 9.6 8 5.6 Fuel and lubrication $/hr 23.82 19.87 13.81 4.27 Operating Interest 1.70 1.21 0.82 0.21 Labor $/hr 15.91 15.91 15.91 4.00 Total Variable Cost $/hr 61.05 51.04 38.60 10.11 Total Costs Total $/hr 90.49 66.34 50.29 12.08 Equipment capacity MT/hr 32.7 13.27 Total $/ton 4.80 4.70

It will likely be necessary to flail-cut or mow the standing-stalks, and then rake and bale the windrows. We estimated that it cost about $4.80 per ton of stover for shredding and about $4.70 per ton for raking.

Bale: As previously discussed, large square bales will likely be the bale-format for this system, although large round bales could be use d. There are currently more round balers than square balers in use, mainly because large s quare balers are more expensive. However, gathering, stacking, and transporting large, round ba les is much less efficient. It is difficult to stack round bales more than about three high, since they tend to deform rather badly, during even short storage periods; square bale stacks can be stacked up to five or six bales high, which translates into a more efficient use of storage area as well as more stable stacks that are far less prone to deformation over extended storage period s. Although large round bales tend to weather better out in the open, for the reasons just stated as well as those given in the Purdue report, we used large square bales in this analysis. Table 4.1-11 summarizes the cost of the baling operation, which we estima te to be $10.87 per ton. xxix , xxx

4 We have received comment that it may be inappropriate to assign a fuel usage to both the 245-hp tractor and the flail shredder. We were unable to determine whether this was the case. The impact of not including such fuel would be a decrease in the price per ton cost of $0.61.Table 4.1-11 Corn Stover Baling Operation

Tractor - 275-hp Lg. Sq. Baler - 3' x 4' x 8' Equipment Factors Purchase price $ 147,102 110,723 Useful life yrs 11.3 3.8 Discounted Salvage value $ 7,553 32,455 Annual use hr 800 800 Fixed Costs $/hr Depreciation and interest 25.93 36.74 Taxes Insurance Housing (THI) $/hr 4.05 3.04 Total Fixed Costs $/hr 29.98 39.78 Variable Costs Repairs and maintenance $/hr 19.98 45.11 Fuel consumption 5 gal/hr 10 8 Fuel and lubrication $/hr 24.84 19.87 Operating Interest 1.71 2.38 Labor $/hr 15.91 10.66 Total Variable Cost $/hr 62.44 78.02 Total Costs Total $/hr 92.42 117.80 Equipment capacity DMT/hr 19.4 Total $/ton 10.87

Bale Pick-Up & Field Side: It is important to remove the stover bales from off the fields. Few farmers will tolerate bales left for long periods on their fields, especially if there is a chance spring planting will be negatively affected. Nor do we expect farmers will allow random piles of bales left at field edges, for retrieval over the winter and spring months. Aside from the likelihood that trucks and other equipment would get stuck in muddy roads and fields, thus slowing down deliveries and runni ng up operating costs, farmers would have little tolerance for torn-up roads and fields. This may not be a big problem, if the farmer/grower intends to plow a field in the spring. However, it could be highly problematic for a farmer/grower who “no till” farms and would be forced to repair ruts and holes in fields and roads before spring planting. Apart from this, dry matter losses from bales, left out in the open on dirt, can be as high as 10% to 20%. At harvest time, the bales, regardless of format, must be picked up and hauled either to a satellite storage site for intermediate storage or hauled directly to the processing plant.

Several variables must be ta ken into account for bale pi ckup and the field-side haul operation that could easily affect the cost. Be cause the exact location on a field where a bale lands as it falls from a baler varies according to stover yield and harvest efficiency, there is no easy or accurate method for predicting the exact lo cation of each bale on the field, either relative to each other or to the field edges or entry. The distance between bales and the potential variability in the area, shape, and relative dimensions of each field add to the difficulty of estimating bale pickup costs. If it was possible to somehow tag each bale with GPS coordinates as it fell to the ground, theoretically the coordina tes could be used in some type of ‘bale retrieval’ program to optimize th e time and pickup distance traveled. xxxi, xxxii

5 We have received comment that it may be inappropriate to assign a fuel usage to both the 275-hp tractor and the baler. We were unable to determine whether this was the case. The impact of not including such fuel would be a decrease in the price per ton cost of $1.06.17 For this study, we used the theoretical stove r density on the field, the speed and width of the harvester to estimate the distance between bales. We used a spreadsheet with these data to position the bales in a variety of patterns on a notional rectangular 100-acre field. We devised three or four drive-patterns in which the bale s could be retrieved, by using simple visual inspection. We calculated the time to pick up th e bales using each pattern and the average speed of the self-propelled bale-wagon. There were a few variables for which we couldn’t adjust our numbers because we simply had no way of knowing their effect. For exam ple, if the field was furrowed, it seemed that the less time spent driving across the furrows, at, as we assumed a slower speed than could be traveled along the fu rrows, the more efficient would be the pick up. Table 4.1-12 summarizes the informati on we used for our calculations.

Table 4.1-12 Bale Pickup and Field-Side

Ft. Between Each Bale 490 Pickup One 10-Bale Load - Ft/Load 4,901 Bales/Acre 4.4 Bales/Load 10 Tons/Load 4.5 Loader Speed - mph 7.5 Field Size - Acres 200 400 800 Number of Loads per Field Size 89 178 356 Bales/Field Size - Total 889 1,778 3,556 Miles Traveled per Load 1.74 2.05 2.51 Tons/Hour 26 22 18 Cost per Ton – Pickup & Field-Side $2.82 $3.31 $ 4.05

In any case, using our basic assumptions, the time it took to retrieve a 10-bale load didn’t vary significantly for any of our plots



## . Table 4.1-13 presents the operating data for the bale

wagon.Table 4.1-13 Self-P ropelled Bale-Wagon

Bale Wagon Equipment Factors Purchase price $ 153,716 Useful life yrs 18.1 Discounted Salvage value 6,013 Annual use hr 800 Fixed Costs $/hr Depreciation and Interest $/hr 20.70 Taxes Insurance Housing (THI) $/hr 4.23 Total Fixed Costs $/hr 24.93 Variable Costs Repairs and Maintenance $/hr 12.96 Fuel Consumption gal/hr 7 Fuel and Lubrication $/hr 17.39 Operating Interest 1.21 Labor $/hr 15.91 Total Variable Cost $/hr 47.47 Total Costs $/hr 72.40 Total $/hr 72.40 Equipment capacity DMT/hr 23 Total $/ton 3.15

Since the fields were no smaller than 200-acres, we piled the bales at one of the corners, which we assumed as the field-entry. We calcul ated the cost to haul bales for each of the 200-, 400-, and 800-acre fields. We assumed the 20-ft rake made 148-passes across the 200-acre field; 209-passes across the 400-ft field; and 295-passes across the 800-ft field. We used the number of windrows the rake left to determine the num ber of passes the baler would make. The baler dropped a bale every 490-ft; to collect a 10-bale lo ad the loader would need to travel 4,900-ft. We estimated that the average distance every bale would need to travel to the corner of the field, e.g., the field entry, would be the distance from the field center to the corner (field-entry); we assumed the fields were square. The loader would need to travel that distance and then return empty, for the next load. Therefore, each load er would travel 4,900-ft to pickup the load, and then an additional 4,174-ft for the 200-acre field; 5,903-ft for the 400-acre field; and 8,348-ft for the 800-acre field to haul to the field edge (corne r) and return. We chose to pick up 10-bales per load with a self-propelled bale wagon with an average speed of about 10-mph. We assumed the bales would be picked up, trans ported, and dumped at the field-edge at a cost of $2.82-per ton for the 200-acre fields; $3.31-per ton for the 400-ac re fields; and $4.05-per ton for the 800-acre fields

. We weighted the DM hauled for each field size by the total tons recovered from each size, to arrive at 23-weighted dr y tons/hr hauled for $3.15-per ton

Haul to Satellite Storage: Theoretically, we could store all th e bales at the ethanol plant. If so, we would need to move 3,149,000-bales or about 100-loads per hour for 16 hours each day during the 50-day harvest. It would require 50-st acks, each, eight-bales wide by 5-bales high, by 1,577-bales (12,615-ft.) long, with 51 x 20-ft apro ns and isles, between each stack and along two-sides of the entire area, plus a 20-ft apron, across the entire front and rear. The area would total ~33-million square feet or 1.19-square miles.19 We stored the bales at satellite facilities near the center of each county. As previously discussed, the Purdue study established ‘farm-s ets,’ but did not describe how they were configured and how bales were to be hauled to each storage site, nor did the study specify exactly where each storage site was. Rather, they only estimated the distance between each storage area and the ethanol plant. The following table summarizes the cost factors used to estimate the costs to haul the bales to satellite storage.

Table 4.1-14 Haul - Field Side to Satellite Storage High-Speed

Tractor Bale Wagon 2- Telescopic Handlers Equipment Factors Purchase price $ 133,865 23,851 130,106 Useful life yrs 15 15 12.5 Discounted Salvage Value $ 10,782 4,803 6,490 Annual use hr 800 800 800 Fixed Costs $/hr Depreciation and Interest $/hr 19.62 3.34 21.48 Taxes Insurance Housing(THI) $/hr 3.68 0.66 3.58 Total Fixed Costs $/hr 23.30 4.00 25.06 Variable Costs Repairs and Maintenance $/hr 13.63 1.94 15.90 Fuel Consumption gal/hr 6 0 2 Fuel and Lubrication $/hr 14.90 0 9.94 Operating Interest $/hr 1.13 0.09 1.02 Labor $/hr 15.91 7.95 31.82

Total Variable Cost $/hr 45.57 9.98 58.68

Total Costs $/hr 68.87 13.98 83.74 Total $/hr 166.59 Equipment capacity DMT/hr 9.3 Total $/ton 17.91

We assumed that a telescopic loader would lo ad the bales at the field-edges onto 20-bale, 2-axle, 30-ft long wagons, each pulled by a high-speed tractor to the storage area located at the center of each county, where they were unloade d by another telescopic loader and the bales stacked for temporary storage. Several variable s make the cost of this operation difficult to estimate. A cursory inspection of the general outli ne/shape of many of th e counties in the study reveals that they are by no means square. Ho wever, to make our calcu lations manageable, we assumed they were in order to determine the average distance each bale would need to be transported to its respective storage area in each county. We estimated that the average distance any load would travel from any position in the counties, e.g., from the furthest to the nearest, would be equal to one-half the distance from the co rner of the county to its center. We used the published area of each county, from which we de termined the distance from one-corner to the center; that distance equaled the trip to the st orage area and the return. We multiplied each by a 30% winding factor (rather than a straight- line drive, this accounts for turns and other meanderings). xxxiii We estimated the operation would cost about $17.91 per ton.Satellite Storage: We assumed each storage unit would consist of a concrete slab with open sides and pole-supported tin roof. Smooth pa ved surfaces are safer and make work easier. Gravel and dirt do not stick to the bottoms of the bales. If winter (wet, muddy) access is necessary, this cost should be included in the overall costs for storage; particularly from the highway to the stack. Beyond the need to keep the area around the stack accessible and clean, the could be problems with local authorities, if trucks leaving the property carry significant quantities of mud onto a public highway. Ordinarily , in an agricultural area a certain amount of mud is expected to be left on highways during we t weather. However, at the truck and trailer volumes we’re anticipating, the amount being tracked onto highways and possibly through municipalities, would increase rapidly. We used 1% of construction costs for upkeep, and 2% of the construction cost for the storage unit to cover the cost of access. These are incurred costs within the overall maintenance of stored stacks of biomass. These costs are essentially insignificant in the overall storage costs, are s ubject to great fluctuations due to weather and equipment availability, and, therefore, were ro lled up into a percentage of the overall storage costs of stacked bales. The following table summa rizes our storage area construction cost factors and costs.

Table 4.1-15 Satellite Storage Construction & Maintenance Costs – For Each of 11-Areas Land Rent ($/acre/yr) 100 Land Preparation ($/acre) 30,000 Construction ($/sq ft) 3.75 Upkeep – 1% of Construction ($/ton) 0.91 Access – 2% of Construction ($/ton) 1.81 Depreciation Period (yrs) 12

Number of Bales Bale Storage Area (sq ft) Bale Storage Area (acres) Tons Stover per site Supply days Total Storage

Cost St Joseph 280,889 2,943,716 67.6 126,400 28.1 $1,123,463 Elkhart 245,333 2,571,093 59.0 110,400 24.5 $981,252 Marshall 336,000 3,521,280 80.8 151,200 33.6 $1,343,889 La Porte 479,111 5,021,084 115.3 215,600 47.9 $1,916,286 Starke 245,333 2,571,093 59.0 110,400 24.5 $981,252 Kosciusko 366,222 3,838,009 88.1 164,800 36.6 $1,464,768 Lagrange 201,778 2,114,631 48.6 90,800 20.2 $807,044 Fulton 311,111 3,260,444 74.8 140,000 31.1 $1,244,342 Porter 293,333 3,074,133 70.6 132,000 29.3 $1,173,236 Noble 260,444 2,729,458 62.7 117,200 26.1 $1,041,692 Pulaski 479,111 5,021,084 115.3 215,600 47.9 $1,916,286 Total 1,574,400 350 $13,993,510 Total Cost $8.89/ton

With well-paved surfaces, equipment can be maneuvered regardle ss of weather, and surfaces can be sloped to enhance drainage. We also assumed the bales would be stored in multiple stacks, 8-bales wide and 5-bales high, and long enough to accommodate the number of bales we expect; there would 20-ft aprons along the outside of the stacks and 20-ft isles between stacks for stacking, stack management , and for general and fire safety. xxxiv One researcher determined that the economics of scale, in the curr ent situation, did not really apply. The cost for21 secondary storage would therefor e be approximately equal on a pe r ton basis regardless of the size of the biofuel production f acility. Based on the numbers a bove, we estimated that storage would cost about $8.89 per ton. xxxv We used this as the cost per ton for the satellite storage as well as for storage at the plant.

We used 11-telehandlers at the storage areas. (However, once the harvest is complete the telehandlers being used for loading and unloading bale wagons during the field-side to storage area operation could possibly be pressed into tran sport – load, unload service (see Table 4.1-15). If so, the cost to use the telehandlers could be reduced from $3.28 to $3.08 per ton.) Plus 11- telehandlers at the plant to lo ad and unload trucks and trailers that deliver the stover from satellite storage to the plant; extra telehandler time at the plant will be used to move feedstock as needed. The following table summarizes the co st associated with the transportation. The following table summarizes the cost associated with the transportation.

Table 4.1-16 Haul From Satellite Storage to Plant

Class 8 Truck 53-ft Flatbed Trailer 22-Telescopic Handlers Equipment Factors Purchase price $ 103,839 42,173 130,106 Useful life yrs 20 22 13 Discounted Salvage Value $ 4,025 931 6,490 Annual use hr 5,600 5,600 800 Fixed Costs $/hr Depreciation and Interest $/hr 1.91 0.74 236.28 Taxes Insurance Housing(THI) $/hr 0.41 0.71 39.38 Total Fixed Costs $/hr 2.31 1.45 275.66 Variable Costs Repairs and Maintenance $/hr 1.13 3.16 174.90 Fuel Consumption gal/hr 9 0 2 Fuel and Lubrication $/hr 33.95 0 109.34 Operating Interest $/hr 0.37 0.14 11.22 Labor $/hr 17.46 350.02 Total Variable Cost $/hr 52.91 2.31 $645.48 Total Costs $/hr 55.22 3.76 921.14 Total $/hr 58.97 921.14 Equipment capacity DMT/hr 4.5 281 Total, each $/ton 13.10 3.28 Total $/ton 16.38

To transport the bales to the ethanol plant, we calculated the ton-weighted average triptime to be 4.09 hr. We plan to ship 4,497-tons of stover to the plant on each of the 350-operating days. At 17.5-tons per load, we anticipate ther e will be about 256-loads per day. Using the 4.09- ton weighted trip time, we estimate d that it would require 63-trucks and trailers to haul 4 x 17.5- ton per day. The cost of transportation plus loading and unloading is estimated to be $16.38 per dry ton. The following table summarizes all the cost s to harvest, bale, fiel d-side, haul to satellite storage, store, and haul to the plant.Table 4.1-17 Ag Residue Cost Summary Farm-Set Size, acres 200 400 800 Total Tons Tons per Farm-Set, t 756,4 39 476,402 341,559 1,574,400

Farmer/Grower $/t 10.00 10.00 10.00 Nutrient Replace $/t 11.81 11.81 11.81 Shred $/t 4.80 4.80 4.80 Rake $/t 4.70 4.70 4.70 Bale $/t 10.84 10.84 10.84 Haul – Edge $/t 2.82 3.31 4.05 Total Farm Edge Cost $/t 44.97 45.46 46.20 Haul – SS $/t 17.91 17.91 17.91 Storage $/t 8.89 8.89 8.89 Haul to Ethanol Plant $/t 16.38 16.38 16.38 Field to Plant – Total $/t 43.18 43.18 43.18

Per Farm- Set – Total $/t 88.15 88.64 89.38 Avg. Total Cost $/t 88.71

We anticipate that by 2022 the industry will improve the efficiency of feedstock delivery and reduce the cost of feedstocks. The cu rrent harvest-system is usually referred to as a multipass system: the corn grain is first combined, and then the stover is shredded, raked, baled, and the bales hauled to the field side. Each fiel d-pass adds to the final cost and further compacts the soil; soil compaction is especially critical if the soil is prone to compaction or in no-till situations. xxxvi Because the combine-spreader drops the stover on to the ground, not only are fewer cobs collected, but dirt, dirt clods, and other debris, including metal, are inevitably gathered up with the stover by the baler. xxxvii, xxxviii Thus, extra effort and money must be expended to remove the debris before processing can begin, apart from the fact that dry matter is also lost during this operation. In their 2002 study report, NR EL included a wash table to remove dirt and grit and had magnets to remove tramp iron, e.g., wire, etc. from the stover. xxxix

According to a few sources, which for reasons of confidentiality, we can’t quote, there appears to be active interest in restructurin g the system we just described to move the preprocessing (feedstock preparation) forward in the chain, away from the ethanol plant, and closer to the fields. Including the issues highlig hted in the previous paragraphs, a major concern has to do with the use of standard hay and fo rage equipment, for which the overall collection efficiency of stover (ratio of stover collected to the total above-ground stover excluding grain) using flail choppers, rakes, and balers was less than 30%. xl Until now, most research has been based on a multi-pass system similar to the one we synthesized. xli , xlii In addition, the timeliness for collection (weather concerns) and moisture content issues are major problems associated with a multi-pass corn stover harvest. xliii

The restructuring efforts also include exploring other methods to more efficiently gather the stover that avoids the need to pick it up from the ground, e.g., gather or catch it before it hits23 the ground. xliv In one early case, a baler was hitched directly onto a combine, to capture the combine effluent and square-bale it. The problem was that there was a strict need to limit moisture to under 20% if bales are to be stor ed, plus the extra equipment slowed the grain harvest. xlv Ideally, the stover harvest system should be capable of harvesting stover at any level of moisture even while the grain is being harves ted. All the cobs would be collected, the stover wouldn’t touch the ground and a controlled amount of residue would be left to meet any conservation requirements (we be lieve finding a way to leave the correct amount of residue behind will be difficult, and should be a top priority).

A modification of the system we previously described would be to use a mobile tub grinder that could be towed from one satellite storage area to the next. A telehandler would feed the grinder to directly fill trucks for transport to the production facility. The ‘walking floor,’ rear-dump, or belly-dump trailers would unload the ground-up stover into silos or tanks at the facility. These silos or tanks could be sized to provide as much feed surge capacity as the facility required to maintain continuous operation. xlvi

Again, ideally, the corn stover harvest shoul d be reduced to a single-pass operation during which the amount of residue left on the fiel d will be less a function of harvest efficiency and more a function of the farmer/grower and th e harvesting company being able to determine how much residue must be left to maintain soil h ealth. In reality, most of the equipment doesn’t yet exist that could perform some of the operations we will describe. Nevertheless, we believe this reflects some of the forward thinking that is currently taking place. For example, a combine designed specifically for the job must still be constructed. A single-pass harvester would cut the whole stalk a few inches above the soil, leaving some stalk anchored to the ground. It would pull the entire plant, e.g., stalks, leaves, and cobs with grain into the combine, where they are mixed into a single, clean, grain and stover stream. It would then blow the entire stream into tractorpulled grain-carts that run along-side the harvester. It is important to be able to change full carts for empties without stopping the harvester. As a cart is filled, it is pulled from beneath the discharge tube, as an empty cart is pulled under it. The full cart is hauled to the field side, where the harvested material is unloaded directly into bulk ‘walking-floor’ semi trailers, for transport to a co-op or depot type elevator/facility. After the biomass stream is unloaded, equipment at the elevator/depot separates the stover from the grai n, following which the stover is chopped, dried, and sent to tanks or silos for intermediate storage. Currently , there are no simple methods for drying wet corn stover, other than to let it field-dry. However, if the single-pass harvest is to become a reality, the stover will need to be dried or else stored in much the same way silage is stored. xlvii At harvest, corn grain has a moisture content of 25%, while at the same time, the stover ordinarily ranges from 35% to well over 50% moisture. There have been studies to artificially dry corn stover as well as other biomass types; there will likely be changes to the reported results of these and other studies, but, then we expect advancements and certainly changes in several parts of the feedstock supply system. xlviii, xlix, l Given that these changes take place, the stover, would have flowability characte ristics similar to small cereal grains, and could be moved by standard grain loading and unloadi ng systems into large corrugated steel bins (silos) for intermediate storage. In this ha rvest format, the stover is handled by only two machines before it reaches the roadside and ne ver hits the ground. Dry matter losses should be significantly reduced. liHarvesting, storing, and transporting a denser feedstock should offer significant savings. lii Using this and other anticipated improvements, it a ppears possible that in the out years, e.g., by 2022, corn stover and other residues could be commoditized, much as is the case with grain, and then purchased by a processor on an as-needed basis.

However, commoditization offers its own set of issues, among which are both tangible and non-tangible infrastructures. Although tangible infrastructure with regard to ethanol distribution are discussed in greater detail in Section 4.2, we believe th e following comments fit within the context of our preceding informati on. The impact of both feedstock and finished ethanol on rural road, highway and railroad infrastr ucture is likely to be even greater than the current and anticipated impact of corn based ethanol. Raw cellulosic feedstocks have lower levels of concentrated fermentable carbohyd rates and therefore require a greater mass of feedstock to produce an equivale nt level of ethanol. Thus, pub lic and private transportation infrastructure must move a gr eater volume of feedstock per gallon of ethanol produced. The magnitude of the impact will depend on the field density of feedstocks near the plant and whether feedstock densification will make it possi ble to ship more dense carbohydrate product to the cellulosic ethanol plant.

Intangible infrastructure is essentially absent for crop residue type cellulosic feedstocks. Intangible infrastructure includes such things as uniform grade and quality standards, market price discovery mechanisms, collateral warehous e receipts, regulatory structure and other marketing institutions. Grain market institutions have been developed and fine-tuned over the past century that give corn etha nol plants a decided benefit. Da ily price information, as well as a wealth of crop condition, and supply and demand information from a variety of public and private sources is available on corn grain. Well known institutions such Uniform Grade and Quality Standards, FGIS, Grain Warehouse Regu lations, Collateral Warehouse Receipts, Trade Associations, Non-Recourse Government Commodity Loans, and a set of futures markets that efficiently price grain over time and space are all readily available. This infrastructure is already in place, tested and readily accessible to corn grain ethanol producers. Although not highly visible and frequently taken for granted, it plays a cr itical role in efficient feedstock pricing, risk management, trading and financing. The cellulosic marketing infrastructure required for similar efficient commercial transactions will need to be established from top to bottom.

Pricing infrastructure is one of the most pre ssing needs. Large daily volumes of corn and other grains are traded on well established exchan ges with a great deal of confidence on the part of buyers and sellers that the other party will perform. Initially, it could be difficult, at best, to develop these infrastructure benef its for crop residues such as corn stover. Cellulosic feedstocks will be starting from a relativel y small production base with no pricing institutions in place. There are no existing grades and quality standard s to underpin transactions over distance and time. Nor are there any trade rules or established patterns for prompt and efficient settlement of trade disputes between buyers and sellers. The abse nce of these factors does not mean that they won’t develop, but there could be a stressful transition period.

Also, there is no regulatory infrastructu re to protect producers who wish to hold inventory after harvest in a public warehouse or handlers warehouse. This kind of infrastructure serves an important role in underpinning ware house receipts and producer financing by creating25 a higher and more reliable collateral value for i nventory. Nor are there equivalents to the U.S. grain grades and quality standards or Federal Gr ain Inspection Service. While there are other ways these functions can be provided some type of commodity grades and standards will be necessary to permit trading. Another possibility would be to have the production of cellulosic feedstocks and the production of ethanol vertically integrated in some fashion so that the responsibility for quality is internalized. liii

Energy Crops

Energy crops such as switchgrass and miscan thus would be harves ted, baled, stored and transported very similar to crop residues. Becau se energy crops are not currently grown on a commercial scale, and are therefore not harvested, it is difficult to model the costs of harvesting these crops. Given the process for harvesting is likely to resemble the corn stover harvesting system described in our internal analysis of agri cultural residue costs, we believe the costs would also be similar. Despite these similarities, there are several key differences that will cause the price of energy crops to differ from that of corn stover and other agricultural residues.

One of the main advantages of growing en ergy crops is the low nutrient inputs, and therefore low nutrient replacement costs, that are required as compared to traditional crops. Energy crops are also expected to produce high er yields per acre than the harvesting of agricultural residues. This higher density is lik ely to increase the number of tons of feedstock than can be harvested per hour, while at the same time decreasing the transportation distance between the farms where the feedstock is produced and the biofuel production facility. Both of these factors would further decrease the co st of energy crop production, as labor and transportation costs would be lower and less secondary storage facilities would be required.

Not all of the traits of energy crops woul d indicate lower costs of production, however. Energy crops will also incur a land rent cost. In the scenario described in our internal analysis for corn stover no land rent cost was charged to the production of corn stover. This is because the stover is assumed to be a secondary crop, and therefore all the land rent charges are assumed to be included in the cost of grain production. Because energy crops will likely be grown as primary crops there will be some land rent cost associated with their production. How big this cost is will vary greatly, depending on where and on what type of land the energy crops are grown. If energy crops are grown on marginal land that is unsuitable for traditional crops, as has been suggested, this cost may be low. In any case, it will be an increase when compared with agricultural residues, which do not ha ve any associated land rent costs 6

.

Wood Residue

As we did with agricultural residues, we al so examined the costs associated with wood residue harvesting to validate the cost generated with FASOM. Harvest and transport costs for woody biomass in its different forms vary due to tract size, tree species, volumes removed, distance to the wood-using/storage facility, terrain, road condition, and other many other considerations. There is a significant variation in these factors within the United States, so timber harvest and delivery systems must be designed to meet constraints at the local level.

6 Land rent charges are included in the FASOM estimate of the roadside cost of energy crops.Harvesting costs also depend on the type of equipment used, season in which the operation occurs, along with a host of other factors. Much of the forest residue is already being harvested by logging operations, or is available from milling operations. However, the smaller branches and smaller trees proposed to be used for biofue l production are not collected for their lumber so they are normally left behind. Thus, this forest residue would simply have to be collected and transported out of the forest, although it would s till have to be chipped be fore transport to the biofuel plant.

In general, most operators in the near future will chip at roadside in the forest, blowing the chips directly into a chip van. When the van is full it will be hauled to an end user's facility and a new van will be moved into position at the chipper. The process might change in the future as baling systems become economically feas ible or as roll-off containers are proven as a way to handle logging slash. At present, most of the chipping for biomass production is done in connection with fuel-reduction tr eatments. This could change if the price of raw biomass increases to a point where it becomes feasible to recover logging residues associated with normal commercial operations. The majo r problem associated with collecting logging residues and biomass from small trees is handling the material in the forest before it gets to the chipper. Balers and roll-off containers offer some promise to reduce this cost. Whether the material is collected from a fuel-reduction treatment or a commerc ial logging operation, chips from residues will be dirty and will require screening or some type of filtration at the end-user's facility. 7

Results from a study in South Georgia show that under the right conditions, a small chipper can be added to a larger operation to obtain additional chip pr oduction without adversely impacting roundwood production, and chips can be produced from limbs and tops of harvested trees at costs ranging from $11 per ton and up. Harvesting understory (the layer formed by grasses, shrubs, and small trees under the canopy of larger trees and plants) for use in making fuel chips is about $1 per ton more expensive.

Per ton costs decrease as the volume chipped increases per acr e. Some estimates suggest that if no more than 10 loads of roundwood are pr oduced before a load of chips is made, that chipper-modified system could br eak even. Cost projections s uggest that removing only limbs and tops may be marginal in terms of cost sin ce one load of chips is produced for about every 15 loads of roundwood.

The U.S. Forest Service provided us a cost cu rve for different categories of forest residue, including logging residue, other removals (i.e., clearing trees for new building construction), timberland trimmings (forest fire prevention strategy) and mill residues. liv The data was provided to us on a county-by-county basis. The national forest lands are omitted from consideration, and the urban forest residue is not considered here , but in the section discussing MSW. The information was also provided at different price points. The quantities of forest residue are summarized by source type in Tabl es 4.1-18, 4.1-19 and 4.1-20. To avoid presenting a huge amount of data, we aggregated the county data by state, and we are presenting the data at specific price points: $30/dry t on, $45/dry ton and $70/dry ton.

7 Personal Communication, Eini C. Lowell, Research Scientist, USDA Forest Service27 Table 4.1-18. Volume of Wood Residue Availa ble for Producing Biofuel Biomass Available at $30/ton (dry tons) Logging Residue Other Removals Timberland Thinnings Unused Mill Residue Total Quantity Alabama 1,202,541 253,620 433,519 7,117 1,896,798 Arizona 8,849 22,436 33,085 1,351 65,721 Arkansas 851,772 385,492 369,083 12,889 1,619,236 California 334,870 0 871,351 65,088 1,271,309 Colorado 9,203 7 0 2,302 11,511 Connecticut 4,195 15,339 10,465 3,949 33,949 Delaware 15,051 12,109 4,918 0 32,077 Florida 535,215 257,704 240,947 2,202 1,036,067 Georgia 1,556,954 496,631 553,627 45,138 2,652,350 Idaho 126,573 0 41,548 6,006 174,126 Illinois 139,101 117,589 115,431 18,523 390,644 Indiana 281,242 52,087 198,112 10,627 542,068 Iowa 56,049 27,580 48,991 159 132,780 Kansas 7,329 44,202 9,676 8,720 69,928 Kentucky 513,989 332,179 344,948 55,196 1,246,311 Louisiana 1,317,139 440,293 300,924 30,075 2,088,431 Maine 1,206,438 470 80,314 42,483 1,329,705 Maryland 90,722 415 40,994 17,067 149,197 Massachusetts 35,461 31,043 13,801 0 80,305 Michigan 379,463 122,476 327,640 13,763 843,343 Minnesota 348,807 331,492 132,712 26,878 839,889 Mississippi 1,548,534 355,071 425,344 95,138 2,424,088 Missouri 387,434 265,146 342,077 79,787 1,074,443 Montana 131,335 0 66,592 9,136 207,063 Nebraska 10,572 9,386 11,707 4,971 36,637 Nevada 15 53 0 0 67 New Hampshire 157,321 174 47,802 7,019 212,316 New Jersey 2,959 39 2,288 1,437 6,723 New Mexico 11,929 1,279 25,898 4,902 44,008 New York 367,003 54,671 163,336 27,390 612,400 North Carolina 1,013,165 629,632 560,814 12,811 2,216,422 North Dakota 1,453 7,601 3,822 265 13,141 Ohio 185,398 9,053 83,676 22,600 300,726 Oklahoma 173,869 98,794 53,043 495 326,200 Oregon 760,276 31 527,702 16,316 1,304,326 Pennsylvania 543,663 699 224,978 170,972 940,312 Rhode Island 884 22,860 2,800 389 26,934 South Carolina 714,551 348,289 301,850 1,051 1,365,741 South Dakota 6,972 14,436 2,993 2,294 26,695 Tennessee 316,706 244,920 423,906 187,583 1,173,115 Texas 616,777 218,464 185,718 3,021 1,023,979 Utah 2,973 7 9,909 4,437 17,325 Vermont 104,876 18,652 48,395 0 171,923 Virginia 741,673 406,800 436,870 39,366 1,624,709 Washington 641,144 22 925,479 21,446 1,588,091 West Virginia 488,356 24,714 161,653 118,779 793,502 Wisconsin 568,800 491,132 260,293 60,410 1,380,636 Wyoming 11,343 0 14,050 34,014 59,407 Total 18,530,943 6,165,088 9,485,083 1,295,560 35,476,674Table 4.1-19. Tons of Wood Residue Availa ble for Producing Biofuel Biomass Available at $45/ton (dry tons) Logging Residue Other Removals Timberland Thinnings Unused Mill Residue Total Quantity Alabama 1,202,541 253,620 506,045 7,117 1,969,324 Arizona 13,566 21,210 34,967 1,351 71,094 Arkansas 851,772 385,492 429,414 12,889 1,679,567 California 583,478 0 949,468 65,088 1,598,034 Colorado 10,056 11 30,619 2,302 42,988 Connecticut 4,301 16,095 10,465 3,949 34,810 Delaware 17,932 14,145 6,700 0 38,777 Florida 535,215 257,704 266,597 2,202 1,061,718 Georgia 1,556,954 496,631 644,295 45,138 2,743,018 Idaho 216,303 0 52,594 6,006 274,902 Illinois 139,153 117,589 115,431 18,523 390,696 Indiana 281,464 52,087 221,845 10,627 566,023 Iowa 56,050 27,607 49,551 159 133,367 Kansas 7,329 44,202 9,676 8,720 69,928 Kentucky 513,989 332,179 407,371 55,196 1,308,735 Louisiana 1,317,139 440,293 330,512 30,075 2,118,019 Maine 1,280,511 495 102,442 42,483 1,425,931 Maryland 94,579 421 40,994 17,067 153,060 Massachusetts 39,127 33,191 13,801 0 86,119 Michigan 391,732 128,600 410,302 13,763 944,398 Minnesota 358,518 341,894 159,990 26,878 887,280 Mississippi 1,548,534 355,071 467,935 95,138 2,466,679 Missouri 387,434 265,146 466,082 79,787 1,198,448 Montana 215,597 0 70,775 9,136 295,507 Nebraska 10,710 9,434 11,707 4,971 36,822 Nevada 22 71 0 0 93 New Hampshire 165,519 197 57,566 7,019 230,301 New Jersey 3,184 40 2,423 1,437 7,084 New Mexico 17,239 1,287 26,862 4,902 50,291 New York 384,457 56,552 189,696 27,390 658,094 North Carolina 1,013,165 629,632 668,420 12,811 2,324,028 North Dakota 1,454 7,601 3,822 265 13,142 Ohio 186,022 9,069 88,572 22,600 306,263 Oklahoma 173,869 98,794 62,700 495 335,858 Oregon 1,341,835 34 574,948 16,316 1,933,133 Pennsylvania 1,341,835 34 574,948 170,972 2,087,789 Rhode Island 957 25,039 2,800 389 29,185 South Carolina 714,551 348,289 352,018 1,051 1,415,909 South Dakota 11,872 15,581 3,253 2,294 32,999 Tennessee 316,706 244,920 507,698 187,583 1,256,906 Texas 616,777 218,464 219,187 3,021 1,057,448 Utah 3,758 0 10,786 4,437 18,980 Vermont 108,542 19,182 53,836 0 181,560 Virginia 741,673 406,800 524,372 39,366 1,712,212 Washington 1,067,587 23 981,839 21,446 2,070,895 West Virginia 488,356 24,714 241,184 118,779 873,033 Wisconsin 576,938 499,302 327,027 60,410 1,463,677 Wyoming 18,163 0 18,202 34,014 70,380 Total 20,928,463 6,198,742 11,301,737 1,295,560 39,724,50229 Table 4.1-20. Tons of Wood Residue Availabl e for Producing Biofuels Biomass available at $70/ton (dry tons) Logging Residue Other Removals Timberland Thinnings Unused Mill Residue Total Quantity Alabama 1,202,541 253,620 581,654 7,117 2,044,933 Arizona 13,566 24,510 38,678 1,351 78,105 Arkansas 851,772 385,492 492,094 12,889 1,742,247 California 583,478 0 1,000,615 65,088 1,649,181 Colorado 10,056 11 30,619 2,302 42,988 Connecticut 4,301 16,095 10,465 3,949 34,810 Delaware 17,932 14,145 6,700 0 38,777 Florida 535,215 257,704 332,353 2,202 1,127,474 Georgia 1,556,954 496,631 776,911 45,138 2,875,634 Idaho 216,303 0 61,926 6,006 284,235 Illinois 139,153 117,589 115,431 18,523 390,696 Indiana 281,464 52,087 221,845 10,627 566,023 Iowa 56,050 27,607 49,551 159 133,367 Kansas 7,329 44,202 9,676 8,720 69,928 Kentucky 513,989 332,179 463,904 55,196 1,365,268 Louisiana 1,317,139 440,293 375,052 30,075 2,162,559 Maine 1,280,511 495 166,117 42,483 1,489,605 Maryland 94,579 421 40,994 17,067 153,060 Massachusetts 39,127 33,191 13,801 0 86,119 Michigan 391,732 128,600 533,107 13,763 1,067,203 Minnesota 358,518 341,894 200,599 26,878 927,889 Mississippi 1,548,534 355,071 516,598 95,138 2,515,342 Missouri 387,434 265,146 643,929 79,787 1,376,295 Montana 215,597 0 83,023 9,136 307,755 Nebraska 10,710 9,434 11,707 4,971 36,822 Nevada 22 71 0 0 93 New Hampshire 165,519 197 58,098 7,019 230,833 New Jersey 3,184 40 2,423 1,437 7,084 New Mexico 17,239 1,287 32,187 4,902 55,616 New York 384,457 56,552 192,851 27,390 661,249 North Carolina 1,013,165 629,632 800,455 12,811 2,456,063 North Dakota 1,454 7,601 3,822 265 13,142 Ohio 186,022 9,069 88,572 22,600 306,263 Oklahoma 173,869 98,794 81,634 495 354,792 Oregon 1,251,094 34 566,594 16,316 1,834,037 Pennsylvania 546,418 707 340,497 170,972 1,058,594 Rhode Island 957 25,039 2,800 389 29,185 South Carolina 714,551 348,289 395,555 1,051 1,459,446 South Dakota 11,872 15,581 4,129 2,294 33,875 Tennessee 316,706 244,920 516,550 187,583 1,265,759 Texas 616,777 218,464 253,670 3,021 1,091,931 Utah 3,758 7 14,717 4,437 22,918 Vermont 108,542 19,182 71,105 0 198,829 Virginia 741,673 406,800 630,366 39,366 1,818,206 Washington 1,067,587 23 1,029,985 21,446 2,119,041 West Virginia 488,356 24,714 287,639 118,779 919,489 Wisconsin 576,938 499,302 420,775 60,410 1,557,425 Wyoming 18,163 0 21,598 34,014 73,775 Total 20,042,304 6,202,722 12,593,373 1,295,560 40,133,959The relatively flat supply curve indicates that small changes in the demand for wood residues could have a significant impact on the cost of these residues. Th is makes predicting an appropriate cost for these re sidues a difficult task. The FASOM model estimates that 1.67 million dry tons of wood residues will be used in cellulosic biofuel production in 2022. This number is far less than the 35.5 million dry tons of wood residue that the US Forestry service estimates will be available at $30 a ton. This would suggest that the low costs estimated by FASOM ($19.77 per dry ton) are reasonable.

Delivery of woody biomass from the harvesting site to a conversion facility, like delivery of more conventional forest produc ts, accounts for a significant portion of the delivered cost. In fact, transportation of wood fiber (including haul ing within the forest) accounts for about 25 to 50 percent of the total delivered costs and highly depends on fuel prices, ha ul distance, material moisture content, and vehicle capacity and utilization. Also, beyond a certain distance, transportation becomes the limiting factor and the costs become directly proportional to haul distance. We believe Class 8 over-the-road hauling will be used to transport the wood residues from the roadside to the biofuel production facilitie s. The cost for the transportation of wood residues was determined using the transportation and secondary storage model presented in Section 1.3 and in further detail below. Because wood residues can be harvested throughout the year and delivered to the biofuel production plan t on an as needed basis no secondary storage costs were included.

Municipal Solid Waste

Million of tons of municipal solid waste (MSW) continue to be disposed of in landfills across the country, despite recent large gain s in waste reduction and diversion. The biomass fraction of this total stream represents a potentially significant resource for renewable energy (including electricity and biofuels). Because this waste material is already being generated, collected and transported (it would solely need to be transported to a different location), its use is likely to be less expensive than other cellulosic fe edstocks. One important difficulty facing those who plan to use MSW fractions for fuel production is that in many places, even today, MSW is a mixture of all types of wastes, including biomat erials such as animal fats and grease, tin, iron, aluminum, and other metals, painte d woods, plastics, and glass. Ma ny of these materials can’t be used in biochemical and thermochemical etha nol production, and, in fact, would inflate the transportation costs, impede the operations at th e biofuel plant and leave an expensive waste stream for biofuel producers.

Thus, accessing sorted MSW would likely be a requirement for firms planning on using MSW for producing cellulosic biofuels. In a c onfidential conversation, a potential producer who plans to use MSW to produce ethanol indicated th at their plant plans ar e based on the obtaining cellulosic biowaste which has already been sorted at the waste source (e.g., at the curbside, where the refuse hauler picks up waste already sorted by the generating home-owner or business). For example, in a tract of homes, one refuse truck would pick up glass, plastic, and perhaps other types of waste destined for a sp ecific disposal depot, wh ereas a different truck would follow to pick up wood, paper, and other cellu losic materials to be hauled to a depot that supplies an ethanol plant. However, only a sma ll fraction of the MSW generated today is sorted at the curbside.31 Another alternative would be to sort the waste either at a sorting facility, or at the landfill, prior to dumping. There are two prominent options here. The first is that there is no sorting at the waste creation site, the home or business, and thus a single waste stream must be sorted at the facility. This operation would likely be done by hand or by automated equipment at the facility. To do so by hand is very labor intensive and some what slower than using an automated system. In most cases the ‘by-hand’ system produces a sli ghtly cleaner stream, but the high cost of labor usually makes the automated system more cost-effec tive. Perhaps the best approach for low cost and a clean stream is the combination of hand sorting with automated sorting.

The third option is a combination of the two which requires that there is at least some sorting at the home or business which helps to pr event contamination of the waste material, but then the final sorting occurs downstream at a sorting site, or at the landfill.

We have little data and few estimates for the cost to sort MSW. One estimate from our Office of Solid Waste for a combination of mechanically and manually sorting of a single waste stream downstream of where the waste is generate d puts the cost in the $20 to $30 per ton range. There is a risk, though, that the waste stream could still be conta minated and this would increase the cost of both transporting and using this mate rial at the biofuel plant due to the toxic ash produced which would require disposal at a toxic waste facility. If a less contaminated stream is desired it would probably require sorting at the generation site – the home or business - which would likely be more costly since many more peop le in society would then have to be involved and special trucks would need to be used. Al so, widespread participation is difficult when a change in human behavior is required as some may not be so willing to participate. Offering incentives could help to speed the transition to curbside recycling (i.e., charging fee for nonsorted waste, or paying a small amount fo r sorted tree trimmings and construction and demolition waste). Assuming that curbside sortin g is involved, at least in a minor way, total sorting costs might be in the $30 to $40 per ton range.

These sorting costs would be offset by the cost savings for not disposing of the waste material as well as the value of the recovered materials. Most landfills charge tipping fees, the cost to dump a load of waste, a societal cost that would be avoided. In the United States, the national average nominal tipping fee increased fourfold from 1985 to 2000. The real tipping fee almost doubled, up from a national average (in 1997 dollars) of about $12 per ton in 1985 to just over $30 in 2000. Equally important, it is apparent that the tipping fee is much higher in densely populated regions. Statewide aver ages also varied widely, from $8 a ton in New Mexico to $75 in New Jersey. Tipping fees ranged from $21 to 98 per ton in 2006 for MSW and $18/ton to $120/ton for construction and demolition waste. It is likely that the tipping fees are highest for waste contaminated by toxic materials that re quire the disposal at Resource Conservation and Recovery Act (RCRA) certified toxic waste sites as opposed to a composting site. However, this same contaminated material woul d not be desirable to biofuel producers. Presuming that only the noncontaminated cellulosic waste (yard and food wastes, building construction and demolition waste and some paper) is collected as feedstocks for biofuel plants, the handling and tipping fees are likely much lower, in the $30 per ton range. 8

8 A much more thorough analysis of tipping fees by waste type is planned for the final rulemaking analysis.The avoidance of tipping fees, however, is a complex issue since landfills are generally not owned by municipalities anymore. Both large and small municipalities recognized their inability to handle the new and complex solid waste regulations at a reasonable cost. Only 38 out of the 100 largest cities own th eir own landfills. To deal with the solid waste, large private companies built massive amounts of landfill capacity. The economic incentive is for private landfill operators to fill their landfills with garbage as early as possible to pay off their capital investment (landfill site) quickly. Also, the longer the landfill is operating the greater is itsexposure to liability due to leakages and leaching. Furthermore, landfills can more costeffectively manage the waste as the scale of the landfill is enlarged. As a result, there are fewer landfills and landfill owners, and an expansion of market share by large private waste management firms, thus decreasing th e leverage a biofuel producer may have. 9 Hence, MSWbiofuel plants could be opposed by landfill operators. This may also be true in the case of a waste-to-energy (WTE) facility, which burns as mu ch garbage as possible to produce electricity. For sustainable operation, a certain amount of daily waste supply should be guaranteed. A MSW-biofuel plant may therefore be seen as an unwelcome competition to both landfill owners and WTE facilities. This competition may increase the cost of cellulosic biomass to the biofuel producers.

Once the cellulosic biomass has been sorted fro m the rest of MSW, it would have to be transported to the biofuels plant. Transporta tion is different for MSW biomass compared to forest and crop residues. Forest and crop residue s are collected from forests and farms, which are both rural sites, and transported to the biofuel plant which likely is located at a rural site. The trucks which transport the forest and crop re sidues are large over-the-road trucks which can average moderate speeds because of the lowe r amount of traffic that they experience. Conversely, MSW is collected from throughout urban areas and would have to transported through those urban areas to the plant site. If the cellulosic biomass is being collected at curbside, it would likely be collected in more conv entional refuse trucks. If the biofuel plant is nearby, then the refuse trucks could transport the cellulosic biomass directly to the plant. In this case, the refuse trucks would simply be deliver ing the MSW to the biofuel producer instead of a landfill or waste sorting facility, and therefore would not result in any additional cost to the biofuel producer. If, however, the plant is locat ed far away from where the waste is collected, then the refuse trucks would probably to be o ffloaded to more conventi onal over-the-road trucks with sizable trailers to make transport more cost-effective. This would likely be an additional cost charged to the biofuel producer, as the MSW is now being transported farther to be used as a biofuel feedstock instead of disposed of at a local landfill. Because the roadside cost of MSW is significantly lower than the other feedstock s ources it may still be cheaper to import MSW from some distance away rather than use an alternative, locally available feedstock.

Cellulosic biomass sourced from MSW is generated year-round. If a steady enough stream of this material is available, then sec ondary storage would not be necessary, thus avoiding the need to install secondary storage. We a ssumed that no secondary storage costs would be incurred for MSW-sourced cellulosic biomass. If the MSW is sourced from within the same county as the biofuel plant we ha ve assumed that there is no cost to the biofuel producer for the

9 Osamu Sakamoto, The Financial Feasibility Analysis of Municipal Solid Waste to Ethanol Conversion, Michigan State University, Plan B Master Research Paper in partial fulfillment of the requirement for the degree of Master of Science, Department of Agricultural Economics, 200433 transportation of the feedstock. If, however, th e feedstock comes from a county other than the one in which the biofuel plant is located we assu me that the biofuel producer must pay to have the MSW transported in large over-the-road tr ucks. These assumptions are used for the transportation and secondary storage model di scussed in Section 1.3 and in detail in the following section.

4.1.1.2.3 Transportation and Secondary Storage

4.1.1.2.4 Cellulosic Ethanol Production Costs

Two different technologies served as the basis for estimating the costs for converting cellulose into ethanol. One t echnology relies on the biochemical conversion of the cellulose to ethanol. The second technology converts the cellulo se to a syngas and then reacts the syngas to mixed alcohols over a catalyst.

Biochemical Conversion of Cellulose to Ethanol

We contracted with the National Renewable Energy Laboratory (NREL) to estimate the cost to convert corn stover into ethanol for the years 2010, 2015, and 2022. It is of particular importance for the following discussion, to note the following: NREL used the same feedstock mass (772,168 dry tons of corn stover) in all three cases.

For the three cases, NREL assumed the feedstoc k, ‘as-needed,’ was hauled to the plant by trucks and trailers from satellite storage, already shredded to the appropriate size for processing, and free of dirt, iron, and other contaminates; in other words – process ready. The transport vehicles were unloaded into surge tanks, larg e enough to hold feedstock for three days of operation. The pretreatment and hydrolysis reactors are charged from these feed surge tanks.

The following is background information fo r our discussion of bot h operating and capital costs, some of which is also included in our br ief discussion of the pro cess flow description and capital equipment charges. The first step was to develop a set of process flow diagrams that set the arrangement of the equipment. Based on the desired production volume, these diagrams, were used within an ASPEN Plus4 © model to develop complete mass and energy balance. The model consists of 164 unit operati on blocks, 457 streams (247 material and 210 heat or work), 63 components, and 82 control blocks.

The overall model is thermodynamically rigor ous and uses physical properties for the feedstock and process chemical s included in the ASPEN softwa re as well as property data developed at NREL. The individual unit models are also thermodynamically consistent and can be either rigorous (for example, the simulation of the distillation) or simple. The reactors could be modeled with kinetic expressions, but b ecause of the level of development of the experimental data, they were m odeled as experimentally deter mined conversions of specific reactions. This type of model still satisfies the rigorous mass and energy balance. Other unit operations, such as liquid-solid separations, are typically modeled with fixed solids removal andliquid retention (in the solids st ream) data from vendor tests. 10 Using the process flow diagrams and the mass and energy balance information, NREL estimated stream flows and conditions, along with the estimated quantities of raw materials and other process chemicals.

The following table presents NREL’s summary of each of the three year’s total project investment. For each year’s total project i nvestment, NREL provided capital charge, which includes income tax, depreciation, and average retu rn on investment, the cost of raw materials, waste handling charges, and by-product credits.

Table 4.1-23. Summary of NREL’s Capi tal Charges and Operating Costs

Year Technology 2010 2015 2022

Plant Size MMgal/yr 56 69 71

Capital Cost $MM (TPI) 232 220 199

$MM/yr ¢/gal $MM/yr ¢/gal $MM/yr ¢/gal Capital Charge 10% after tax ROI 42 75 39 56 35 50

Fixed Costs 9 16 9 12 8 12

Feedstock Cost 84 46 51 35 50 35

Other Raw Matl. Costs 17 30 4 5 16 16

Enzyme Cost 18 32 7 10 5 8

Enzyme Nutrients 8 14 2 3 2 2

Electricity -6 -10 -7 -9 -12 -16

Waste Disposal 1 2 3 4 1 1

Total Costs 173 205 108 116 105 108

The quantities of all raw material, generated electricity, and produced wastes were determined using the ASPEN mass and energy balance model. These costs include: Feedstock – corn stover, CSL – purchased corn steep liquor (a nutrient); Cellulase – purchased cellulase

enzymes; Other Raw Materials – sulfuric acid, diammonium phosphate, make-up water, boiler

10 A. Aden, M. Ruth, K. Ibsen, J. Jechura, K. Neeves, J. Sheehan, and B. Wallace National Renewable Energy Laboratory (NREL); L. Montague, A. Slayton, and J. Lukas Harris Group, Seattle, Washington, Ethanol Process Design and Economics Utilizing Co-Current Dilute Acid Prehydrolysis and Enzymatic Hydrolysis for Corn Stover ; June 2002; NREL is a U.S. Department of Energy Laboratory Operated by Midwest Research Institute • Battelle • Bechtel; Contract No. DE-AC36-99-GO1033735 feed water chemicals, cooling water chemicals. Waste Disposal – waste water chemicals, waste water polymers, ash dispos al, gypsum disposal. Electricity – marketing and distribution of surplus electricity to the grid for credit.

We note that the percent change in total project investment from year to year is not insignificant and reflects improvements in mechanical process efficiencies among other general improvements in the process technology, including the automatic distributed process control system, all of which are off-set to some extent by increases in the real cost of the technology improvements, as well as those of constructions materials. We discuss capital costs following this discussion of operating costs.

The most notable reductions in NREL’s operatin g costs are in the price per dry ton of the corn stover feedstock and in the cost of cellulase enzyme. NREL anticipates significant improvement in the efficiency of these enzymes, especially those that saccharify glucan to glucose and xylose oligomers 11 generated during hydrolysis. Th ey also expect improvement in the yeasts that ferment xylose. According to the 2007 NREL – State of Technology report, they anticipate that as a first step, the relationship between corn stover hydrolysate conditioning and fermentation will be better de fined and understood. Commercial cellulase preparations will continue to be analyzed for baseline performance (specific activity), and due to increased research efforts, cellulase f unction will be better understood, wh ich should lead to efficiency improvements. Integrated testing of whole sl urry and recycle options will also be conducted resulting in potential improvements in that area. Last, the efficacy of advanced enzyme preparations (including oligomerases and/or hemicellulases) will continue to be tested in conjunction with alternative pret reatment technologies. NREL expects that the cost of pretreatment will deminish, hydrolysis time will decrease, and the sugar (xylose and glucose) yields will increase. 12

As the process costs decline over time, the feedstock costs become a larger fraction of the overall costs. We also note that in the followi ng table that the cost of the feedstock makes up 50% of the total cost in 2010; 67% in 2015; and 68% in 2022. The reduction in feedstock cost, from $60 per dry ton in 2010, to $45.90 per dry ton in both 2015 and 2022 also has a significant effect on operating costs. In addition, NREL di d not include payments to the farmers/growers nor for soil nutrients (fertilizer, etc.) that were removed with the harvested corn stover. The cost of the cellulase enzyme is the next highest c ontributor, with percent reductions contributed to total cost that reduced from ~19% in 2010, to 13% in 2015 and 10% in 2022. It should be obvious that any reductions in these costs have significant effects on the total operating cost. The majority of research going forward will be focused on these two items, although some work will be done to reduce the cost of the others. Table 4.1-24 summarizes NREL’s operating costs for a biochemical cellulo sic ethanol plant.

11 Xylan polymer chains, with considerably fewer residue numbers in the chain than were in the original xylan polymer; they were broken off the polymer as these short chains rather than as single molecule sugars. 12 Andy Aden, National Renewable Energy Laboratory, Golden, Colorado, Biochemical Production of Ethanol from Corn Stover: 2007 State of Technology Model, Technical Report NREL/TP-510-43205, Task No. BB07.2410; May 2008Table 4.1-24. Percent of the total oper ating cost for each actu al operating cost item

2010 2015 2022

¢/gal % of Total ¢/gal % of Total ¢/gal % of Total

Feedstock 84 50 51 67 50 68 Biomass to

Boiler 0.0 0.0 0.0 0.0 0.0 0.0

CSL a 14 8 3 4 2 3 Cellulase 32 19 9 13 8 10 Other Raw Matl. Costs 31 18 5 7 16 22

Waste Disposal 2 1 4 5 2 2 Electricity -10 -6 -9 -12 -16 -22 Fixed Costs 16 10 12 16 12 16

168 76 72

a Corn steep liquor – provides nutrients for the enzymes.

The following table includes our adjustments to NREL’s variable or operating cost data for the three years studied. We note that the two main differences between NREL’s and our estimates are in the feedstock costs and in the way we calculate capital charges. We adjusted NREL’s capital charges which were calculated using a 10% after tax return on investment, to reflect a 7 percent before tax rate of return, whic h is the capital cost basis for our cost analyses. We also adjusted the NREL feedstock costs to those that we estimated in Table 4.1-21, which was $67.4 per dry ton. This significant difference between their and our fe edstock cost estimates is due to our including payments to farmers/grow ers plus covering the cost to replace nutrients (fertilizer, etc.) removed at the time the stover was harvested. According to a personal communication, NREL used unpublished data from th e Idaho National Laboratory that indicate feedstock costs will be significan tly reduced between 2010 and 2015.37 Table 4.1-25. Adjusted Capital Charge s and Operating Costs

Year Technology 2010 2015 2022

Plant Size MMgal/yr 56 69 71

Capital Cost $MM 232 220 199

$MM/yr ¢/gal $MM/yr ¢/gal $MM/yr ¢/gal Capital Cost 7% ROI before taxes 25 46 24 35 22 31

Fixed Costs 9 16 9 12 8 12

Feedstock Cost 52 94 55 75 52 73

Other Raw Matl. Costs 17 30 4 5 16 16

Enzyme Cost 18 32 7 10 5 8

Enzyme Nutrients 8 14 2 3 2 2

Electricity -6 -10 -7 -9 -12 -16

Waste Disposal 1 2 3 4 1 1

Total Costs 124 224 94 135 90 127

The changes in the minimum ethanol selling prices for the three years studied are partially due to the changes in necessary capital investments. In order to determine capital costs, NREL developed specifications for pieces of e quipment that fall within different areas of a biochemical plant. A biochemi cal plant is divided up into 8 different areas (Area 200 through Area 900)._ For each equipment specification, th ey developed individua l purchased equipment and installation costs. Vendor s supplied installation costs wh ere possible; in other cases installation factors were used. Equipment co sts were obtained from vendor quotations when possible, especially for uncommon equipment such as pretreatment reactors. These costs reflect the base case for which the equipment was desi gned. If process changes were made and the equipment size changed, the equipment is not genera lly re-costed, in detail. Rather, the cost was adjusted by scaling using the following exponen tial scaling expression, [New Cost = Original Cost x (New Size/Original Size)^exp]. They also scaled the size of equipment that was known to change linearly with a change in inlet flow. The scaling exponents (exp) were obtained from vendor quotes, or from a standard reference, such as Garrett. 13

13 Garrett, D.E., Chemical Engineering Economics, Van Nostrand Reinhold, New York, 1989Installation costs were taken primarily from Delta-T, a process consultant’s experience. Once the scaled, installed equipment costs (total installed capital costs) were determined, they applied overhead and contingency f actors to determine a total plant investment cost. That cost, along with the plant operating expenses (general ly developed from the ASPEN model) was used in a discounted cash flow analysis to deter mine the cost of ethanol production, using a set discount rate. NREL use a discount rate of 10%, whereas we used 7%, a factor generally used in our financial calculations. For this analysis, the minimum ethanol selling price was the primary value used to compare cases.

The total project investment was briefly disc ussed previously in our summary discussion of operating costs; we used NREL’s total project investment for our estimates. The following summarizes the capital expenditures that account for that capital investment.

Area 200: Pretreatment and Hydrolysis . The equipment in this area consists of an assortment of pipe, pumps, tanks, tank-agitators, tank-mixers, coolers, 3-pneumapress filters, as well as three separate process trains, each of which includes a presteamer, a blow tank, and a reactor. The presteamer uses low-pressure steam to heat the feedstock to about 212 o F. It discharges the hot, saturated mix into a blow tank that serves as a seal between the presteamer and the hydrolysis reactor. The mix is charged to the reactor and dilute sulfuric acid is added; the reactor operates at 191 psia and 547 o F. Most of the hemicellulo se, e.g., primarily xylose, mannose, arabinose, and galactose are converted into sugars. Glu can in the hemicellulose and a small portion of the glucan in the cellulose are converted to glucose. These conditions also solubilize some of the lignin in the feedstoc k and ‘expose’ the cellulose for subsequent enzymatic hydrolysis, in a downstream section. In addition, acetic acid is liberated from the hemicellulose hydrolysis. Degrada tion products of pentose sugars (p rimarily furfural) and hexose sugars (primarily hydroxymethyl furfural (HMF)) are also formed.

Following the pretreatment reactor, the hydrolyzate liquid and solids are flash cooled, which vaporizes a large amount of water, a porti on of the acetic acid, and much of the furfural and HMF, which can be toxic to downstream fermentation microorganisms.

In addition to the flash removal of aldehydes, the solids are washed and filter-pressed to remove the liquid portion of the hydrolyzate, whic h contains sulfuric acid. The liquid is then neutralized to pH 10 with ammonia and held un til the gypsum precipitates and is filtered out. The hydrolyzate, which contains the hydrolyzed xylose sugars and some glucose sugars, is mixed back with dilution water and the filter cake, which contains the unhydrolyzed cellulose and is sent to saccharificati on and co-fermentation (Area 300)

An important issue on an industrial scale is ac curate pH control. By pH 11, as much as 30% of the glucose may be lost to HMF and other side reactions. Several factors increase the probability of overshooting pH e ndpoints during neutralization. Th e natural buffering capacity of hydrolyzates causes neutralization reactions to be slow. Plus, measurements using pH membrane probes are affected by temperature and the presence of dissolved organic compounds (sugars and lignin).39 Since we are handling the same mass of feed stock in each of the modeled years, we don’t expect the cost of the equipment for pretreatment and hydrolysis will change much over the 2010-2022 time period. The equipment costs for Area 200 – Pretreatment & Hydrolysis are 2010: $23-million; 2015: $22.7-million; and 2022: $18.9-million. Neutralization and Conditioning costs were separated out from the Pr etreatment & Hydrolysis costs, even though the NREL’s design report includes both cost centers in Area 200. Neutralization and Conditioning costs are as follows: 2010: $8.4-million; 2015: $9.4-million; and 2022: $7.7- million. The combined cost for Area 200 is as follows: 2010: $31.4-million; 2015: $32.1- million; and 2022: $26.6-million. In total, this area contributed about 23.5% to the total installed capital cost of the project in 2010; about 25.3% in 2015; an 23.2% in 2022

Area 300: Saccharification and Co-Fermentation . The equipment in this area consists of pumps, tanks, tank-agitators, coolers, and heaters. Two different operations take place in this process area — the saccharification of the cellulose to glucose using cellulase enzymes, and the fermentation to ethanol of that glucose plus the xylose and glucose sugars from the dilute acid pretreatment of hemicellulose from Area 200.

Glucan from the cellulose undergoes hydrol ysis or saccharification, at about 149 o F, prior to fermentation. This slightly higher temperat ure increases enzyme activity and reduces the time and amount of enzyme required for saccharifica tion. Saccharification or cellulase enzymes, purchased from an enzyme manufacturer, and the diluted, detoxified hydrolyzate are continuously added to a train of five 1-million ga llon saccharification vessels; residence time is estimated to be 36-hours.

Cellulase enzyme is actually a ‘cocktail’ of enzymes, comp rised of: (1) endoglucanases, which attack randomly along the cellulose fi ber to reduce polymer size rapidly; (2) exoglucanases, which attack the ends of cellulo se fibers, allowing it to hydrolyze highly crystalline cellulose; and (3) β -glucosidase, which hydrolyzes cellobiose to glucose. Several bacteria and fungi naturally produce these enzyme s, including bacteria in ruminant and termite guts and white rot fungus. The most common orga nism used to produce cellulase industrially is Trichoderma reesei . Genencor International and Novozymes Biotech are developing more cost effective cellulase enzymes. DOE is funding this important work, which should improve the economic viability of biomass conversion.

The recombinant Z. mobilis bacterium is used as the biocatalyst to ferment glucoses and xyloses to ethanol. Several research institutions are genetically engineering strains, such as Z. mobilis , to treat additional sugars and identifying other naturally occurring organisms that metabolize hemicellulosic sugars.

The Z. mobilis must be ‘grown’ in increasingly higher volume stages. Initially, a small amount of saccharified slurry and nutrients are combined in a very small vessel with a seed inoculum, that’s been grown in the laboratory. This initial seed batch is used as the inoculum for the next larger size seed batch, and so on. This series of batch scale-ups continues until the last batch is large enough to support the actual production fermentation.Finally, the seed inoculum, nutrients (c orn steep liquor) & (diammonium phosphate – a source of nitrogen for the yeast), and sa ccharified slurry are cooled to about 106 o F and added to a train of five 1-million gallon continuous fermen tors. At this point, the process actually becomes a simultaneous saccharification and co-fermentation (SSCF) process. Even though the temperature in the fermentation tanks has b een reduced to account for the ethanologen’s intolerance to heat, the enzymes do continue to hydrolyze cellulose, albeit at a slightly reduced rate. The main byproduct, produced during fermentation is carbon dioxide (CO 2 ), which is removed in a later process stage. The ethanol br oth called ‘beer’ is collected in a storage tank, called a beer well, before it’s pumped to distillation.

NREL anticipates significant capital savings for saccharification and co-fermentation between 2010 and 2015, with fewer between 2015 a nd 2022. We note that this area contributed 15.4% to the total installed capital cost in 2010, but only 8.8% in 2015 and 8.8% in 2022. The equipment costs for Area 300 – Saccharifi cation and Fermentation are 2010: $20.5-million; 2015: $11.2-million; and 2022: $10.1-million.

Area 400 – In earlier studies, NREL included plans to produce enzymes in Area 400. For the current studies, Area 400 has been removed and enzymes will be purchased and grown on site under licensing agreements with enzyme suppliers.

Area 500 – Product, Solids, and Water Recovery (Distillation, Dehydra tion, Evaporation, and Solid-Liquid Separation). The equipment in this area includes distillation and rectification columns, pumps, condensers and coolers, pum ps, pipe, filter-presses, and evaporators.

Beer, from the beer well in Area 300, is preheat ed and fed to a distillation column. The column overhead containing all the CO 2 and about 0.2% of the etha nol and a small quantity of water is sent to a scrubber, whic h recovers and recycles about 99% of the vented ethanol. In the tower bottoms, about 90% of the water has been removed and it contains approximately 0.7% of the total volume of ethanol fed to the tower. Over 99% of the total ethanol fed to the tower is removed as a 39.4% w/w mixture with water vapor through a side draw and fed directly to a rectification column for further ethanol enrichment. We discuss the distillation column bottoms in the evaporation and solid-liquid separation section of this area.

The rectification tower oper ating conditions are set to produce an overhead 92.5% w/w ethanol/water saturated vapor mixture. The tower bottoms are a 0.05% w/w ethanol/water mixture. In fact, only 0.1% of the total ethanol from the fermentation area is lost to the bottoms.

The rectification column overhead is supe rheated and fed to one of two adsorption columns in a molecular sieve adsorption unit. The two columns operate alternately; while one bed is operated to remove water from the ethanol , the other is regenerated by passing a very small slipstream of pure ethanol vapor back throug h the loaded bed that strips the water off the adsorbent, while the column is under a vacuum. The mixture is condensed and returned to the rectification column feed stream. The adsorption column removes 95% of the water and a small quantity of ethanol. The 99.5% pure ethanol vapor is condensed, cooled, and pumped to storage.41 Evaporation, and Solid -Liquid Separation : The beer column bottoms, with about 5.8% insoluble solids, are fed to the first effect evaporator, where 24% of the water in the feed is evaporated. The evaporator bottom slurry, cooled from ~243 o F to ~189 o F, is sent to a filterpress, from which the filtrate is returned to the second evaporator effect; the filter cake is not washed. In the second effect evaporator, 44% of the feed water is evaporated. The third effect evaporates 76% of the remaining water. The fi nal vapor is condensed and fed to a condensate drum. Of the total feed to the evaporation/ separation system, 10.5% remains as syrup, 11.5% is removed as a wet cake in the pressure filter, 17% is recycled back to the process as recycle water, and 61% is evaporated. The syrup from the third evaporator bottoms is 60% water, e.g., the maximum dissolved solids level that can be ach ieved without rapid foul ing of the evaporator; the flow of very low-pressure steam to the evaporat or is set to achieve this level. This syrup is mixed with the cake from the filter-press and sent to the combustor for disposal. Air from the filter-press is used for combustion air.

The equipment costs for Area 500 – Product, Solids, and Water Recovery (Distillation, Dehydration, Evaporation, and Solid-Liquid Separation) are for 2010: $23.4-million; 2015: $26.1-million; and 2022: $23.3-million. This area’s c ontribution to the total installed capital cost in 2010 is 17.5%; in 2015, 20.6%; and in 2022, 20.3%. We believe that some of the increase from 2010 to 2015 has to do with the increased liquid flow due to the conversion improvements; larger pipe, pumps, tanks, etc may be necessary to handle the increased flow. The changes from 2015 to 2022 are not that significan t, as reflected by the percent contribution of the area to total installed equipment cost.

Area 600 – Wastewater Treatment : The equipment in Area 600 consists mainly of aerobic and anaerobic digesters, digester agitators, tanks (basins), a biogas emergency flare, coolers, and pumps. The main purpose of the wast ewater treatment section is to reduce the plant makeup water requirement by re covering, treating and recycling as much process water as possible. The feed to the wastewater treatment se ction consists of: conde nsed pretreatment flash vapor, condensate from the hydrolyzate filte r-press vent, boiler blowdown, cooling tower blowdown, clean-in-place waste, and the non-recycl ed evaporator condensate. Rain and snow run-off, equipment washing, and other non-pro cess wastewater are assumed to flow to the municipal wastewater treatment sy stem. The stream is screened to remove large waste particles that are sent to a landfill; any remaining organic matter is anaerobically and aerobically digested. Anaerobic digestion produces a me thane rich (75%-methane, 25%-c arbon dioxide) biogas that’s fed to the combustor. Aerobic digestion produces relatively clean water that’s recycled back to the process and sludge that’s burned in the combustor.

NREL didn’t expect much change over the 2010 to 2022 time period. In 2010 the installed capital cost for this area was $3.4-million; in 2015, $3.7-million; and in 2022 it was 3.1- million. As important as this area is to the entir e operation its contribution to the total project installed capital cost is relatively minor. In 2010 the contribution was 2.5%; in 2015, 2.9%; and in 2022 it was 2.7%.

Area 700: Bulk Storage of Chemicals. This section of the plant stors chemicals in bulk for the process and for finished, fuel-grade ethanol. The feedstock feed surge tanks we discussed just prior to the discussion of Area 200 are not incl uded in this area. Process chemicals stored inthis area include: corn steep liquor (a nutrient), su lfuric acid, cellulase en zyme, gasoline (used as a denaturant finish the fuel grade etha nol), and water for fire suppression.

There is approximately five-days of SS316-stainless steel 14 tank sulfuric acid storage. Corn steep liquor (CSL), a nutri ent for fermentation seed growth and ethanol production, also has about five-days of SS304-stainless steel 15 storage; NREL expects the plant will require about three-25,000 gallon rail cars of CSL every three-da ys. There are seven-days of storage for diammonium phosphate (DAP), deliv ered as pellets via rail car. Appropriate qua ntities of CSL and DAP are mixed in a day-tank and used in Area 300 for fermentation seed production and ethanol production. A producer that supplies cellula se enzymes is expected to set up an enzyme production operation either on site or on a nearby location. Liquid enzyme storage is set for four-days in SS304 stainless steel tanks. The carbon steel fire-fighting water storage tanks provide about four-hours of ope rating time; the firewater pump delivers 2,500 gpm. Other pumps are sized per process requirements

There is seven-days of ethanol product st orage in two 600,000 gallon carbon steel tanks. Five percent gasoline (v/v), a denaturant, is adde d to the ethanol as it’s loaded for shipment to customers. The pumps in this section are gene rally sized to load a 10,000 gallon truck and trailer in about 15 min. to 20 min. maximum filling time. They can also be used to fill process day tanks.

The installed capital costs for bulk storage are, for 2010, $3.8-million; for 2015, $2.4- million; and for 2022, $2.4-million. The contribution to total project installed capital costs are, for 2010, 2.8%; for 2015, 1.9%; and for 2022, 2.1%.

Area 800: Combustor, Boiler, and Turbogenerator . The purpose of the combustor, boiler, and turbogenerator is to burn various by -product or waste streams to produce steam and to generate electricity. All of the feedstock lignin and some of the cellulose and hemicellulose are not hydrolyzed in Area 300.

As previously discussed, a high soluble, solids syrup is generated in Area 600 and anaerobic and aerobic digestion of the remain ing wastewater produced biogas and a small quantity of biomass sludge which are burned to generate steam and produce electricity. This contributes to over-all plant ener gy self-sufficiency, reduces so lid waste disposal costs, and generates additional revenue throug h sales of excess electricity. Be cause of heightened interest in using biomass, pulping wastes, and sewage sl udge in place of fossil fuels, new methods are being developed to handle higher moisture feeds. Traditional methods in clude blending the wet feed with dry material or adding auxiliary fuel to maintain the combustion temperature. When the dry solids from the filter-press cake are combined with the high soluble, solids syrup, it helps

14 SS316 is an improved version of SS304, with the addition of molybdenum and a slightly higher nickel content. The resultant composition of 316 gives it much increased corrosion resistance in many aggressive environments. The molybdenum makes the steel more resistant to pitting and crevice corrosion in chloride-contaminated media, sea water and acid vapors. 15 SS304-stainless steel is the most versatile and the most widely used of all stainless steels. Its chemical composition, mechanical properties, weldability and corrosion/oxidation resistance provide the best all-round performance stainless steel at relatively low cost.43 ensure a stable combustion bed temperature and improved boiler efficiency. In these studies NREL used a circulating fluidized bed combusto r that is suitable for varying feeds and feed characteristics; however, this flexibility makes the unit more expensive than a grate or pile combustor. A Lower Heating Value (LHV) of 2,000-2,500 BTU/lb is considered the minimum for maintaining combustion. 16 The combined feed to the combustor has a LHV of 4,179 Btu/lb. Thus, the total higher-heating value energy of th e combined feed streams to the combustor is 706 MMBtu/hr. The solids contribute 59% of this energy and the syrup contributes 37%. A baghouse removes particulates from the combus tion flue gas after it preheats the incoming combustion air and before it’s discharged through the stack.

The boiler feed water (BFW) system incl udes a softener for makeup and condensate water, a deaerator to remove air and other non-condensables, surge tanks and pumps. The amount of water pretreatment necessary depends on the incoming water quality, metallurgy of the boiler, and the ratio of make up to condensate in the feed water. Pretreatment chemicals for pH control, scale removal, and oxygen remova l are added. Treated well water used for makeup and condensate are softened, deaerated, preheated and mixed to provide BFW that’s converted to steam that’s superheated to 950 o F at 1,265 psia at the rate of 407,420 lb/hr. Support equipment includes BFW pumps, deaerator, automatic water pretreatment chemical injection, and condensate gathered from the various heat exchangers in the process. Boiler efficiency, the percentage of the feed heat converted to steam heat, is estimated to be 68%. Boiler blowdown is 3% of steam production. The turbine efficiency was estimated to be 85%.

The turbogenerator consisting of a multistage turbine with extraction ports, a generator, and condenser is used to generate electricity. After high pressure steam drives the multistage turbines, it is extracted at three different conditions for injection into the pretreatment reactor and heat exchange in distillation and evaporation. Tw enty-eight percent of the steam is extracted from the turbine at 191 psia and 514°F, 60% at 65 psia and 327°F, and 3% at 25 psia and 239°F for process needs, as described. The remaining st eam (9%) is condensed at 1.5 psia with cooling water and returned to the BFW system. For th is design, a total of 30.4 megawatts (MW) of power is generated from the system. The process uses 11.7 MW, leaving 18.7 MW that is sold to the grid.

The installed capital cost for Area 800 are, for 2010, $45.5-million; for 2015, $46- million; and for 2022, $43.3-million. This area’s contribu tion to the total installed capital cost is, for 2010, 34.1%; for 2015, 36.2%; and for 2022, 37.7%.

Area 900: Utilities . All utilities, except steam and electricity, necessary for the production of ethanol are accounted for in this ar ea. The utilities provided include cooling water, chilled water, plant and instrument air, process water, and the clean-in-place (CIP) system. No chilled water is used in the plant; the required process temperatures can be achieved by cooling water year-round.

16 Steam and Electricity Generation Options For the Biomass-To-Ethanol Process, NREL Subcontract ACO-8- 18019-01, Reaction Engineering International, Salt Lake City, UT, March 16, 1998. http://www.ott.doe.gov/biofuels/process_engineering.htmlThe plant and instrument air systems provide compressed air for air-driven equipment, instrument operation, for clean up, and the filter-pre ss units in the post-distillation dewatering. The process water system mixes fre sh well water with treated wast ewater and provides water at a constant pressure to the facility. Water is pr ovided to seed production, boiler feed water, cooling tower make-up, the CIP system, and the scrubber. It is also mixed with recycle water for dilution before saccharification. Process wa ter is also used throughout the facility for cleaning on an asneeded basis. The CIP system provides a soluti on that can be heated and includes cleaning and sterilization chemicals to saccharification and co -fermentation, seed vesse ls, and the distillation system.

The installed capital costs for the utilities area are, for 2010, $5.6-million; for 2015, $5.5- million; and for 2022, $6.1-million. This area’s cont ribution to the total project installed equipment costs are, for 2010, 4.2%; for 2015, 4.3%; and for 2022, 5.3%.

Table 4.1-26 summarizes the total projected ca pital costs for a biochemical cellulosic ethanol plant for the years 2010, 2015 and 2022.45 Table 4.1-26. Projected Capital Costs for a Biochemical Cellulosic Ethanol Plant ($million/yr) 2010 2015 2022 Total Capital Investment 133.5 127 114.8

Added Costs* 98.2 93.1 83.8 Total Project Investment 231.7 220.1 198.6

* Added costs include the following:

Warehouse: This is estimated to be 1.5% of total installed cost Site Development: This includes fencing, curbing, parking, lot, roads, well drainage, rail system, soil borings, and general paving. This factor allows for minimum site development assuming a clear site, with no unusual problems such as ri ght-of-way, difficult land clearing, or unusual environmental problems, usually calculated as 9% of the installed cost of process equipment.

Prorateable Costs: This includes fringe benefits, burden s, and insurance of the construction contractor, usually calculated as 10% of total installed cost. Field Expenses: This includes consumables, small tool equip. rental, field services, temporary construction facilities, and field construction supervision, usuall y calculated as 10% of total installed cost.

Home Office and Const.: This includes engineering plus incidentals, purchasing, and construction, usually calculated as 25% of total installed cost. Project Contingency: These costs are small because of th e detail included in the process design usually calculated as 3% of total installed cost.

Other Costs: This includes start-up and commissioni ng costs; land, rights-of-way, permits, surveys, and fees; piling, soil compaction/dewate ring, unusual foundations; sales, use, and other taxes; freight, insurance in transit and import du ties on equipment, piping, steel, instrumentation, etc.; overtime pay during construction; field insurance; project team; transportation equipment, bulk shipping containers, plant vehicles, etc.; escalation or inflation of costs over time; interest on construction loan. These other costs are usually calculated as 10% of total capital investment.

The costs for cellulosic ethanol produced bioc hemically could be lower if not all the water would have to be removed from the ethanol . Separating the water from ethanol is costly because water forms an azeotrope with ethanol. Removing the last of the water above the azeotrope requires additional capita l and operating costs. Some research conducted with hydrous ethanol as well as practical experience in Brazil suggests that by not removing the last few percent of water from ethanol, the ethanol pr oduction costs would be lower and the water contained in ethanol might not cause driveability, not cause corrosion problems and not lower the fuel economy. A lot more research needs to be conducted before hy drous ethanol would be proven as a viable and safe motor vehi cle fuel in existing U.S. vehicles.Thermochemical Conversion of Cellulose to Ethanol

Thermochemical conversion is another reac tion pathway which exists for converting cellulose to ethanol. Thermochemical technol ogy is based on the heat and pressure-based gasification or pyrolysis of nearly any biomass feedstock, including those we’ve highlighted as likely biochemical feedstocks. The syngas coul d then be converted into mixed alcohols, hydrocarbon fuels, chemicals, and power. To produce ethanol, the syngas is passed over a catalyst which converts the syngas to mixed alc ohols – mainly methanol. The methanol can be reacted further to ethanol.

NREL has authored a thermochemical report which already provided a cost estimate. lv However, this report only hypothesized how a thermochemical ethanol plant could achieve production costs at a very low cost of $1 per ga llon. However, to obtain a more detailed cost assessment that may be achievable within the timeframe of our program, EPA contracted NREL to assess the costs for a thermochemical tec hnology which produces mixed alcohols for years 2010, 2015 and 2022. lvi Table 4.1-27 summarizes the cost information provided by NREL.

Table 4.1-27 Summary of Mixed Cellulosic Alcohol Production Costs by NREL (2007 dollars, 10% after tax ROI)

2010 2015 2022 Annual Ethanol Production 48.8 56.7 61.9 Annual Total Alcohol Production 57.5 66.6 72.7 Ethanol Yield 63.2 73.4 80.1 Total Alcohol Yield 74.5 86.2 94.1

Capital Costs Feed Handling and Drying 25.2 25.2 25.2 Gasification 14.0 14.0 14.0 Tar Reforming and Quench 53.4 38.6 41.6 Acid Gas and Sulfur Removal 20.4 14.6 15.8 Alcohol Synthesis Compression 35.4 18.5 17.3 Other Synthesis Costs 6.1 4.7 5.1 Alcohol Separation and Purification 6.8 7.5 7.8 Steam System and Power Generation 19.2 19.7 18.2 Cooling Water and other Utilities 4.2 4.3 3.9 Total Installed Equipment Cost 184.7 147.1 148.9 Added Cost Factors 72.1 57.5 58.1 Total Project Investment 256.8 204.6 207.0

Operating and Amortized Capital Costs $MM/yr $/gal Ethanol $MM/yr $/gal Ethanol $MM/yr $/gal Ethanol Feedstock 46.4 0.95 35.4 0.63 35.6 0.58 Catalysts 7.6 0.16 0.2 0.003 0.2 0.003 Olivine 0.5 0.01 0.5 0.01 0.5 0.01 Other Raw Materials 0.4 0.02 0.4 0.02 0.3 0.02 Waste Disposal 0.3 0.01 0.3 0.01 0.3 0.01 Electricity -1.8 -0.04 0.0 0.00 0.0 0.00 Fixed Costs 14.8 0.30 12.7 0.23 12.8 0.21 Co-Product Credits -10.4 -0.21 -11.8 -0.21 -12.9 -0.21 Capital Depreciation, Income Tax and Return on Investment 46.3 0.95 37.1 0.66 37.5 0.61

Total 104.1 2.15 74.8 1.33 74.3 1.2147 In its mixed cellulosic alcohol report, NREL did not assess the technology’s costs on the same basis that EPA is using. NREL used a fe edstock cost of $46.1/dry ton which is lower than our estimate of $67.4/dry ton. Also, NREL amor tized the capital costs based on a 10 percent after tax return on investment (ROI) compared to our 7% before tax ROI. Thus, we adjusted the NREL cellulosic mixed alcohol costs to reflect our feedstock costs and capital cost amortization assumptions. Table 4.1-28 contains a summary of the mixed cellulosic alcohol costs based on our feedstock and capital am ortization cost assumptions.

Table 4.1-28 Summary of Adjusted Mixed Cellulosic Alcohol Production Costs by NREL (2007 dollars, 7% before tax ROI)

2010 2015 2022 Operating and Amortized Capital Costs $MM/yr $/gal Ethanol $MM/yr $/gal Ethanol $MM/yr $/gal Ethanol Feedstock 67.8 1.39 51.8 0.92 52.1 0.85 Catalysts 7.6 0.16 0.2 0.003 0.2 0.003 Olivine 0.5 0.01 0.5 0.01 0.5 0.01 Other Raw Materials 0.4 0.02 0.4 0.02 0.3 0.02 Waste Disposal 0.3 0.01 0.3 0.01 0.3 0.01 Electricity -1.8 -0.04 0.0 0.00 0.0 0.00 Fixed Costs 14.8 0.30 12.7 0.23 12.8 0.21 Co-Product Credits -10.4 -0.21 -11.8 -0.21 -12.9 -0.21 Capital Depreciation, Income Tax and Return on Investment 28.3 0.58 22.8 0.40 22.8 0.37

Total 107.5 2.22 76.8 1.38 76.0 1.26

4.1.1.3 Imported Sugarcane Ethanol Costs

Our analysis of imported ethanol costs began with a literature search of recent estimates for production costs for sugar cane ethanol in Brazil. Since the liberalization of ethanol prices in Brazil, few cost estimation studies have been made and most of the cost analyses refer to the same study. lvii This study was carried out by the Br azilian Ministry of Science and Technology (MC&T), based on 1990 data, and referred to a production cost of $0.87/gallon. Table 4.1-29 gives a breakdown of cost s based on this data.Table 4.1-29. Sugarcane Ethanol Produc tion Costs in Brazil, circa 1990 Average cost (US$ per gallon) Operating costs Labor Maintenance Chemicals Energy Other Interest payments on working capital Feedstock (cane) $0.64 $0.02 $0.02 $0.01 $0.01 $0.02 $0.08 $0.48 Fixed costs Capital at 12% depreciation rate Other $0.23 $0.19 $0.04 Total $0.87

Since then, there have been significant varia tions in exchange rates, costs of sugarcane and oil products, etc. For example, earlier es timates may undere stimate crude and natural gas costs which influence the cost of feedstock as well as energy costs at the plant. Another possible difference in production cost estimates is whether or not the estimates are referring to hydrous or anhydrous ethanol. Costs for anhydrous ethanol (for blending with gasoline) are typically several cents per gallon higher th an hydrous ethanol (for use in dedicated ethanol vehicles in Brazil). lviii It is not entirely clear from the majority of studies whether reported costs are for hydrous or anhydrous ethanol. Yet another differe nce could be the slate of products the plant is producing, for example, future plants may be de dicated ethanol facilities while others involve the production of both sugar and ethanol in the same facility. Due to economies of scale, production costs are also typically smaller per gallon for larger facilities. Tabl e 4.1-30 summarizes the various estimates reported by ot hers. Production costs range from as low as $0.57 per gallon of ethanol to as high as $1.48 per gallon of ethanol.49 Table 4.1-30. Other Sugarcane Ethano l Production Cost Estimates Reference Cost (US$ per gallon) AgraFNP. 2007. Sugar and Ethanol in Brazil: A Study of the Brazilian Sugar Cane, Sugar and Ethanol Industries. $0.80-$1.07 per gallon (in 2006 $’s depending on region in Brazil), avg. is $0.78 per gallon for cane production cost and $0.13 per gallon for industrial

costs IEA. 2004. Biofuels for Transport: An International Perspective. $0.87 per gallon (in 1990 $’s) references MC&T study; also reports recent production cost estimates for hydrous ethanol as low as $0.57 per gallon (at the prevailing exchange rate in Jan. 2004) USDA. 2006. The Economic Feasibility of Ethanol Production from Sugar in the United States. Avg. is $0.81 per gallon

Von Lampe, Martin. OECD. 2006. Working Party on Agricultural Policies and Markets: Agricultural Market Impacts of Future Growth in the Production of Biofuels. $0.83 per gallon

Brazil Institute. April 2007. The Global Dynamics of Biofuels: Potential Supply and Demand for Ethanol. Issue No. 3. $0.83 per gallon.

ESMAP. October 2005. Po tential for Biofuels for Transport in Developing Countries. $.87-$1.10 per gallon

OECD, March 2008. ITF Round Tables No. 138. Biofuels: Linking Support to Performance. Avg. is $1.40 per gallon

Bain, R. December 2007. World Biofuels Assessment Worldwide Biomass Potential: Technology Characterizations. NREL/MP-510- 42467. $1.04-$1.48 per gallon depending on size of plant, i.e. 100 MGY-4.6 MGY; Sugarcane feedstock costs $0.68 per gallon, Variable operating costs $0.27 per gallon, Fixed costs $0.02-0.13 per gallon, and Capital costs $0.07-0.40 per gallon Macedo, I.C. and L.A.H. Nogueira. 2005. “Biocombusíveis”. Cadernos NAE, No. 2. Núcleo de Assuntos Estratégicos da Presidência da República, Brasilia; As sited in OECD, op. sit. $0.79 per gallon in the Center-South Brazil

Kojima, M. and T. Johnson. 2006. “Potential for Biofuels for Transport in Developing Countries”. ESMAP Knowledge Exchange Series, No. 4.; As sited in OECD, op sit. $0.87-$1.09 per gallon

Smeets, E. 2008. The Sustainability of Brazilian Ethanol-An Assessment of the Possibilities of Certified Production. Bi omass and Bioenergy $1.18 assuming exchange rate of $1.20= 1 Euro

Van den Wall Bake, J.D., et. al. 2009. Explaining the experience curve: Cost reductions of Brazilian ethanol from sugarcane $1.29 per gallon presently; Estimates for 2020 range from $0.76-$0.98 per gallon, Sugarcane costs $0.35-$0.46 per gallon, rest from industrial costs 17

17 Costs were given in $/TC and $/m 3 , conversions were used to translate to per gallon numbers.The study by OECD (2008) entitled “Biofuels: Linking Support to Performance”, appears to provide the most recent and detailed set of assumptions and production costs. As such, our estimate of sugarcane production co sts primarily relies on the assu mptions made for the study, which are shown in Table 4.1-31. The estimate a ssumes an ethanol-dedicated mill and is based off an internal rate of return of 12%, a debt/equi ty ratio of 50% with an 8% interest rate and a selling of surplus power at $57 per MWh.

Table 4.1-31. Cost of Production in a Standard Ethanol Project in Brazil Sugarcane Productivity 71.5 t/ha Sugarcane Consumption 2 million tons/year Harvesting days 167 Ethanol productivity 85 liters/ton (22.5 gal/ton) Ethanol Production 170 million liters/year (45 MGY) Surplus power produced 40 kWh/ton sugarcane Investment cost in mill USD 97 million Investment cost for sugarcane production USD 36 million O & M (Operating & Maintenance) costs $0.26/gal Variable sugarcane production costs $0.64/gal Capital costs $0.49/gal Total production costs $1.40/gal

The estimate above is based on the costs of producing ethanol in Brazil on average, today. However, we are interested in how the costs of producing ethanol will change by the year 2022. Although various cost estimates exist, analysis of the cost trends over time shows that the cost of producing ethanol in Brazil has been stead ily declining due to efficiency improvements in cane production and ethanol conve rsion processes. Between 1980 and 1998 (total span of 19 years) ethanol cost declin ed by approximately 30.8%. lix This change in the cost of production over time in Brazil is known as the ethanol cost “Learning Curve”. See Figure 4.1-2.

Figure 4.1-2. Ethanol Co st “Learning Curve”

The change in ethanol costs will depend on the likely productivity gains and technological innovations that can be made in the fu ture. As the majority of learning has already occurred, it is likely that the decline in ethanol costs will be less drastic in the future as the51 production process and cane practi ces have matured. Industrial efficiency gains are already at about 85% and are expected to increase to 90% in 2015. lx Most of the productivity growth is expected to come from sugarcane production, where yields are expected to grow from the current 70 tons/ha, to 96 tons/ha in 2025. lxi Sugarcane quality is also expected to improve, with sucrose content growing from 14.5% to 17.3% in 2025. lxii All productivity gains together could allow the increase in the production of ethanol from 6,000 liters/ha (at 85 liters/ton sugarcane) to 10,400 liters/ha (at 109 liters/ton sugarcane) in 2025. lxiii

Assuming that ethanol productivity increase s to 100 liters/ton by 2015 and 109 liters/ton by 2025, variable sugarcane ethanol production costs are be expected to decrease to approximately $0.51/gal from $0.64/ga l since less feedstock is needed to produce the same volume of ethanol using the estimates from Table 4.1-31, above. Table 4.1-32 shows the calculated decrease for the years 2005-2025. We assumed a linear decrease between data points for 2005, 2015, and 2025. Adding operating ($0.26/ga l) and capital costs ($0.49/gal) from Table 4.1-27, to a sugarcane cost of $0.51/gal, total production costs are $1.26/gal in 2022.

Table 4.1-32. Estimated Decrease in Sugarca ne Production Cost by 2022 Due to Increases in Ethanol Productivity

Sugarcane Production Cost $/gal liters/ton gal/ton

2005 0.64 85 22.46

2006 0.63 86.5 22.85 2007 0.62 88 23.25 2008 0.61 89.5 23.65 2009 0.60 91 24.04 2010 0.59 92.5 24.44 2011 0.58 94 24.83 2012 0.57 95.5 25.23 2013 0.56 97 25.63 2014 0.55 98.5 26.02

2015 0.54 100 26.42

2016 0.54 100.9 26.66 2017 0.53 101.8 26.90 2018 0.53 102.7 27.13 2019 0.53 103.6 27.37 2020 0.52 104.5 27.61 2021 0.52 105.4 27.85 2022 0.51 106.3 28.08 2023 0.51 107.2 28.32 2024 0.50 108.1 28.56

2025 0.50 109 28.80

Brazil sugarcane producers are also ex pected to move from burned cane manual harvesting to mechanical harvesting. See Figure 4.1-3. lxiv As a result, large amounts of straw are expected to be available. Costs of mechanical harvesting are lower compared to manuallyharvesting, therefore, we would expect costs for sugarcane to decline as greater sugarcane producers move to mechanical harvesting. However, diesel use increases with mechanical harvesting and with diesel fuel prices expected to increase in the future, costs may be higher than expected. Therefore, we have not assumed any changes to harvesting costs due to the switchover from manual harvesting to mechanical harvesting.

Figure 4.1-3. Phase-out Schedule for Trash Burning Practices

As more straw is expected to be collected at future sugarcane ethanol facilities, there is greater potential for production of excess electric ity. The production cost estimates in the OECD study assumes an excess of 40 kWh per ton suga rcane, however, future sugarcane plants are expected to produce 135 kWh per ton sugarcan e assuming the use of higher efficiency condensing-extraction steam turbine (CEST) sy stems and use of 40% of available straw. lxv Assuming excess electricity is sold for $57 pe r MWh, the production of an additional 95 kWh per ton would be equivalent to a credit of $0.22 per gallon ethanol produced. We have included this potential additional credit from greater use of bagasse and straw in our estimates at this time, calculated as a decrease in operating cost s from $0.26 per gallon to $0.04 per gallon.

It is also important to note that ethanol production costs can increase if the costs of compliance with various sustainability criteria are taken into account. For instance, using organic or green cane production, adopting higher wages, etc. could increase production costs for sugarcane ethanol. lxvi Such sustainability criteria could also be applicable to other feedstocks, for example, those used in corn- or soy-based biof uel production. If these measures are adopted in the future, production costs will be higher than we have projected.53 In addition to production costs, there are also logistical and port costs. We used the report from AgraFNP to estimate such costs since it was the only resource that included both logistical and port costs. The total average lo gistical and port cost for sugarcane ethanol is $0.20/gal and $0.09/gal, respectively, as shown in Table 4.1-33.

Table 4.1-33. Imported Ethanol Cost at Port in Brazil (2007 $’s)

Logistical Costs Port Cost Region US ($/gal) US ($/gal)

NE Sao Paulo 0.150 0.097 W Sao Paulo 0.210 0.097 SE Sao Paulo 0.103 0.097 S Sao Paulo 0.175 0.097 N Parana 0.238 0.097 S Goias 0.337 0.097 E Mato Grosso do sul 0.331 0.097 Triangulo mineiro 0.207 0.097 NE Cost 0.027 0.060 Sao Francisco Valley 0.193 0.060 Average 0.197 0.089

Total fuel costs must also include the cost to ship ethanol from Brazil to the U.S. The average cost from 2006-2008 was estimated to be approximately $0.17 pe r gallon of ethanol. lxvii Costs were estimated as the difference between the unit value cost of insurance and freight (CIF) and the unit value customs price. The average cost to ship ethanol from Caribbean countries (e.g. El Salvador, Jamaica, etc.) to the U. S. from 2006-2008 was approximately $0.13 per gallon of ethanol. Although this may seem to be an advantage for Caribbean countries, it should be noted that there would be some additional cost for shipping ethanol from Brazil to the Caribbean country. Therefore, we assume all costs for sh ipping ethanol to be $0.17 per gallon regardless of the country importing ethanol to the U.S.

The total imported ethanol fuel costs (at U.S. ports) over the time period of 2010 to 2022 are shown in Table 4.1-34. In 2022, the total sugar cane ethanol cost estimate prior to tariffs and taxes is $1.50/gallon. Direct Brazilian imports ar e also subject to an additional $0.54 per gallon tariff, whereas those imports arriving in the U.S. from Caribbean Basin Initiative (CBI) countries are exempt from the tariff. In addition, all im ports are given an ad valorem tax of 2.5% for undenatured ethanol and a 1.9% tax for denatured ethanol. We a ssumed an ad valorem tax of 2.5% for all ethanol. Thus, including tariffs and ad valorem taxes, the average cost of imported ethanol is shown in Table 4.1-35 in the “Brazil Direct w/ Tax & Tariff” and “CBI w/ Tax” columns for the years 2010-2022.Table 4.1-34. Average Imported Ethanol Costs Prior to Tariff and Taxes

Sugarcane Production Cost ($/gal) Operating Cost ($/gal) Capital Cost ($/gal) Logistical Cost ($/gal) Port Cost ($/gal) Transport Cost from Port to US ($/gal) Total Cost ($/gal)

2010 0.59 0.04 0.49 0.20 0.09 0.17 1.58 2011 0.58 0.04 0.49 0.20 0.09 0.17 1.57 2012 0.57 0.04 0.49 0.20 0.09 0.17 1.56 2013 0.56 0.04 0.49 0.20 0.09 0.17 1.55 2014 0.55 0.04 0.49 0.20 0.09 0.17 1.54 2015 0.54 0.04 0.49 0.20 0.09 0.17 1.53 2016 0.54 0.04 0.49 0.20 0.09 0.17 1.53 2017 0.53 0.04 0.49 0.20 0.09 0.17 1.52 2018 0.53 0.04 0.49 0.20 0.09 0.17 1.52 2019 0.53 0.04 0.49 0.20 0.09 0.17 1.52 2020 0.52 0.04 0.49 0.20 0.09 0.17 1.51 2021 0.52 0.04 0.49 0.20 0.09 0.17 1.51 2022 0.51 0.04 0.49 0.20 0.09 0.17 1.50

Table 4.1-35. Average Imported Ethanol Costs

Brazil Direct ($/gal) Brazil Direct w/ Tax & Tariff ($/gal) CBI ($/gal) CBI w/ Tax ($/gal)

2010 1.58 2.16 1.58 1.62 2011 1.57 2.15 1.57 1.61 2012 1.56 2.14 1.56 1.60 2013 1.55 2.13 1.55 1.59 2014 1.54 2.12 1.54 1.58 2015 1.53 2.11 1.53 1.57 2016 1.53 2.11 1.53 1.57 2017 1.52 2.10 1.52 1.56 2018 1.52 2.10 1.52 1.56 2019 1.52 2.10 1.52 1.56 2020 1.51 2.09 1.51 1.55 2021 1.51 2.09 1.51 1.55 2022 1.50 2.08 1.50 1.5455 4.1.2 Biodiesel Production Costs

Virgin vegetable oils, fats, waste oils and greases costs

The feedstocks that we project to make up the largest share of biodiesel are virgin vegetable oil (primarily soy o il) and non-food-grade corn oil ge nerated as a co-product of dry mill ethanol production. These feedstock streams we re included in the agricultural commodity modeling done for this rulemaking using the FASOM model. This work is described in detail in Section 2.5 of this RIA. Table 4.1-36 summarize s the volumes and costs of these feedstocks.

Rendered fats and other waste greases are expected to make up a smaller, but still important, source of biodiesel feedstock. These were not explicitly modeled by FASOM;

18 therefore their value was estimated to be 70% that of soy oil, based on historical trends.

Table 4.1-36. Summary of biodie sel feedstock use and cost for primary control case in 2022 (2007$). Fuel / Feedstock Feedstock Price ($/lb) Projected use in 2022 (MMgal) Soy oil 0.33 a 660 Corn oil from dry mill ethanol production 0.17 a 680 Yellow grease or other rendered fats 0.23 b 230 Algae oil or other advanced feedstock 0.58 c 100

Algae-derived oils costs

Algae oil cost projections are based on As pen modeling completed by NREL and are reported in 2007 dollars. Detailed cost information is provide d in their report submitted to the docket. lxviii The results are summarized below in Figure 4.1-4. Two production pathways were assumed, open pond (OP) and photobioreactor (PBR ) systems. For each production pathway a base case, aggressive case, and maximum development case were evaluated based on assumptions on key variables e.g., yield, lipid cont ent on algae, etc. The oil production cost for the open pond case ranged from $11.25/gal in the base case to $3.99/gal for the max case. The oil production cost for the PBR case ranged from $19.49/gal in the base case to $6.62/gal in the

max case.

18 Data available from various sources suggests that tallow and yellow grease prices have been closer to half the value of crude soy oil, but we have chosen to assume 70% as this is what USDA/ARS had assumed during some initial cost modeling they had done for us. Also, given that rendered fat volumes will be more limited than vegetable feedstocks, we might expect their prices to rise against the alternative (and still more expensive) vegetable feedstocks in a climate of higher biofuel production.Figure 4.1-4. Cost to Produce 10 MMgal/yr oil at growth rate scenarios developed by NREL for open pond (op) and photobioreactor (PBR) production. TAG = triacylglyceride

Since algal biofuel technology is still in a relatively early stage of development, there is a higher degree of uncertainty associated with potential performance and cost relative to more established technologies. It is important to note that the “max ” case merely means the maximum algae growth and oil content applied to the sp ecific configuration and associated assumptions analyzed and does not imply that these are the absolute lowest costs that can ever be achieved as technology develops. For the algal technology syst ems analyzed, the report indicated that the areas with the highest economic impact include the optimum amount of nutrients required, the CO 2 delivery cost, the flocculant requirement for harvesting, and the material costs for the PBR production system. The economic modeling assumptions and results from NREL for microalgae-derived oil correspond we ll with other studies which report the cost of production for algae oil from $1 to >$40/gal. lxix

NREL also investigated the uncertainty in key assumptions and the associated potential cost impact of such assumptions in a sensitivity analysis. Figure 4.1-5 shows that for open ponds, the amount of nutrients required has th e highest impact on production cost of the variables evaluated. Figure 4.1-6 shows that the sing le largest cost item in the PBR system is the cost of the tubes themselves.57 Figure 4.1-5. Open Pond Sensitivity Analysis

Figure 4.1-6: PBR Sensitivity Analysis

For this rulemaking, we made the simplifying assumption of using the production cost of the open pond aggressive case of $5.11/gal or $0.68/lb for this feedstock to estimate costs of algae-derived fuel. Given the uncertainties in esti mating costs for algae as well as the need for a single-value estimate for algal oil for cost anal yses purposes, we chose the open pond aggressive case which appears to represent a somewhat middle value as well as a more reasonably competitive feedstock with alternatives, such as soy oil.

Biodiesel production costsBiodiesel production costs for this rule were estimated using two variations of a model generated by USDA for a 10 million gallon-per-year transesterification biodiesel plant. One version uses degummed soy oil as feedstock, a nd a second version includes acid pre-treatment steps required to utilize feedstocks such as rendered fat and yellow grease, which have higher free fatty acid content. USDA used the SuperPro Designer chemical process simulation software to build up a process model with estimates of heat and material flowrates and equipment sizing. Outputs from this model were then combined in a spreadsheet with capital, energy, labor, and feedstock costs to generate a final estimate of production cost. Additional details on the model are given in a 2006 technical publication in the peer-reviewed scientific journal Bioresource Technology. lxx At 10 million gallons per year, the modeled plant size is between the mean and median plant sizes (16 million and 6 million gal/ yr, respectively) as given in our industry characterization. Therefore, the model cost estim ate is believed to be sufficiently accurate for our analyses and no further work was done to de termine the effect of scale on production cost.

This model is periodically updated by USDA to reflect technology upgrades, changes to cost of capital, etc. Such an update was made to the model just before its outputs were used in the analyses presented here. We also made modifi cations to the capital cost to be consistent with typical cost amortization schemes used for regulatory programs. The capital charge estimate was derived as shown in Table 4.1-37. Installed capital cost was $11.9 million; adding 3% annual maintenance charge, we arrive at a final capital charge of 14% annuall y. Energy prices were taken from AEO 2009: natural gas at $7.75/MMBtu and electricity at $0.066/kWh for 2022 in 2007 dollars.59 Table 4.1-37. Economic Factors Used in Deriving th e Capital Cost Amortization Factor

Amortization Scheme Depreciation Life Economic and Project Life Federal and State Tax Rate Return on Investment (ROI) Annual Maintenance Charge Resulting Capital Amortization Factor

Societal Cost 10 Years 15 Years 0% 7% 3% 0.14

The value of the glycerin co-product has been depressed and volatile in recent years due to a large increase in production in biodiesel facilities. This has been balanced at times by new uses coming online as feedstocks for traditiona lly petrochemical-based products as well as increased demand in personal care and other c onsumer products as the standard of living increases in many parts of the world. Some facilities are even experimenting with using it as a supplemental fuel along with biomass or other ma terials. We can exp ect that new uses for glycerin will continue to be found as long as it is plentiful and cheap. For a simple and conservative projection of its value in the future , we have assumed an energy-equivalent value based on residual heating oil. Using a heating value of 7,979 Btu/lb and a heating oil value of $18.90/MMBtu in 2022, we arrive at $0.15/lb as a co-product value. Table 4.1-38 shows the overall process mate rial balance output by the model.

Table 4.1-38. Material Balance and Values for Biodiesel Production Model in 2022 Stream By weight Estimated value (2007$) Soy oil input 100 $0.33/lb Methanol input 11 $0.16/lb Biodiesel output (main product) 100 -

Glycerin output (co-product) 12 $0.15/lb

Table 4.1-39 shows the production cost allocati on for the soy oil-to-biodiesel facility as modeled in the 2022 primary control case. Production cost for biodies el is primarily a function of feedstock price, with other process inputs, fac ility, labor, and energy comprising much smaller fractions.

Table 4.1-39. Production cost allocation for soy biodiesel derived from this analysis for the primary control case in 2022 Cost Category Share of Per-Gallon Cost Soy Oil 85% Other Materials a 6% Capital & Facility 6% Labor 2% Utilities 2%

a Includes acids, bases, methanol, catalyst4.1.3 Renewable Diesel Production Costs

The renewable diesel process converts rendered fats (or plant oils) into diesel fuel using thermal depolymerization, which is similar to refinery hydrotreating used to remove sulfur. The process uses hydrogen and catalyst to remove oxygen from the triglyceride molecules in the feedstocks oils via a decarboxylation and hy dro-oxygenation reaction, yielding some light petroleum products and water as by products. The reactions also saturate the olefin bonds in the feedstock oils, converting them to paraffins, and may also isomerize some paraffins. Depending on process operating conditions, the yield to dies el-range material is typically between 90-99% volume, with the rest being naphtha and li ght fuel gases (primarily propane).

As described in the industry characterizati on discussion (see RIA Section 1.5.4), we have chosen to focus on stand-alone renewable dies el production, as we believe this will be the primary pathway given tax incentives and the de finition of the biomass-based diesel fuel category. We assume a total project cost of $150MM for a standalone facility based on materials made publically available by Syntroleum Co rp. related to their Geismar, LA, project. lxxi

Our operating cost and yield estimates were derived from material presented by UOP and Eni at a 2007 industry conference, which describe s producing renewable diesel in a grass roots standalone production pro cess inside a refinery. lxxii In addition to feedstock and facility costs, another significant cost input is hydrogen. For hydrogen operating costs, we used the UOP analysis and guidance from Conoco Philips to de rive our estimate to ma ke renewable diesel. lxxiii The UOP paper presents a range of 1000 to 2000 standard cubic feed (scf) per barrel for converting the various feedstock to renewable di esel. Based on characteristics of rendered fats, we estimated a hydrogen demand of 1,590 SCF/bbl of feedstock processed.

Accounting for this quantity of hydrogen, al ong with a value taken from our refinery modeling work, we derived a figure of 6.9 cents/ gallon of diesel product to cover utilities, labor, and other costs. Finally, total cost per ga llon was estimated at $2.42 fo r the 2022 primary control case (2007 dollars). Table 4.1-40 gives more detail s for the process assumed in this analysis. Co-product values were also taken from refinery modeling work done for this rulemaking. Table 4.1-41 shows the cost allocation we arrive d at for renewable diesel production.

Table 4.1-40. Parameters used in renewable diesel production cost estimates. Stream By volume Estimated value (2007$) Fat input 100 gal $0.23/lb Hydrogen input 505 scf $0.0044/scf Renewable diesel output (main product) 93.5 gal - Naphtha output (co-product) 5 gal $0.55/lb Light fuel gas output (co-product) 9 gal $0.13/lb61 Table 4.1-41. Production Cost Allocation for Renewabl e Diesel for Primary Control Case in 2022 Cost Category Contribution to Cost Feedstock 78% Capital & Facility 11% Hydrogen 7% Other variable costs 3%

4.1.4. Biodiesel and Renewable Diesel Cost Summary

Table 4.1-42 summarizes the feedstock prices and fuel production cost for biodiesel. Table 4.1-43 gives the same information for renewa ble diesel. Combined with information from Table 4.1-36, a weighted average production cost could be estimated ( our overall economic impacts take into account this information).

Table 4.1-42 Summary of Costs for Biodiesel for the Primary Control Case in 2022 Fuel / Feedstock Feedstock Price ($/lb) Fuel Production Cost ($/gal) Biodiesel / soy oil 0.33 a 2.73 Biodiesel / corn oil extraction at ethanol plants 0.17 a 1.90

Biodiesel / yellow grease or other rendered fats 0.23 b 2.43

Biodiesel / algae or other advanced virgin oil feedstock 0.58 c 4.52 d

a Taken from outputs of FASOM model.

b Derived from outputs of FASOM model, assuming 70% value of soy oil.

c Derived from figures in a Technical Memo by Ryan Davis of NREL entitled “Techno-economic analysis of microalgae-derived biofuel production” (available in docket).

d This production cost assumes this advanced feedstock has very low free fatty acid content.

Table 4.1-43 Summary of Cost for Renewable Diesel for the Primary Control Case in 2022 Fuel / Feedstock Feedstock Price ($/lb) Fuel Production Cost ($/gal) Renewable diesel / yellow grease or other rendered fats 0.23 a 2.42

a Derived from outputs of FASOM model, assuming 70% value of soy oil.4.1.5 BTL Diesel Production Costs

Biofuels-to-Liquids (BTL) processes, which are also thermochemical processes, convert biomass to liquid fuels via a syngas route. If cellulose is converted to syngas, rather than converting the syngas to mixed alcohols, a Fische r Tropsch reactor can be added to convert the syngas to diesel fuel and naphtha. The primary pr oduct produced by this process is diesel fuel. This technology is commonly termed biomass-to- liquids (BTL) because of its similarity to gasto-liquids and coal-to-liquids t echnology. Diesel fuel’s higher energy density per gallon than ethanol and even biodiesel provide s it an inherent advantage over these other fuels. In addition, BTL diesel fuel can be more easily distributed from production to retail outlets and used by motor vehicles. The diesel fuel produced by th e Fischer Tropsch process tends to be comprised of paraffins which provide a much higher cetan e number than petroleum diesel fuel, with a downside of poorer cloud point which reduces its widespread use in cold temperatures.

There are many steps involved in a BTL pr ocess which makes this a capital-intensive process. The first step, like all the cellulosic pro cesses, requires that the feedstocks be processed to be dried and ground to a fine size. Th e second step is the syngas step, which thermochemically reacts the biomass to carbon monoxide and hydrogen. Since carbon monoxide production exceeds the stoichiometric ideal fraction of the mixture, a water shift reaction must be carried out to increase the relative balance of hydrogen. The syngas products must then be cleaned to facilitate the following Fischer-Trops ch (FT) reaction. The Fischer-Tropsch reaction reacts the syngas to a range of hydrocarbon com pounds – a type of synthetic crude oil. This hydrocarbon mixture is then hydrocracked to max imize the production of high cetane diesel fuel, although some low octane naphtha and small amounts of wax are al so produced. The many steps of the BTL process contribute to its high capital cost.

Although there were several studies availa ble which provided costs estimates for BTL diesel fuel, they did not provide sufficient de tail to understand all the cost elements of BTL diesel fuel and naphtha. EPA therefore contracted with NREL to estimate the production costs for BTL diesel fuel and naphtha. Like the other technologies, we asked for cost estimates for the same years assessed above for cellulosic et hanol which was for 2010, 2015 and 2022, however, NREL did not believe that the costs would change that much over this time span. So NREL only provided the costs for 2022, advising us that th e costs would only be slightly less for earlier years, and most of that difference would becaus e of the poorer economies of scale if the initial plants are sized smaller. Table 4.1-44 summari zes the cost information provide by NREL to EPA for a year 2022 cellulosic BTL plant.63 Table 4.1-44 Year 2022 Production Costs for Thermochemcal (BTL) Cellulosic Fischer Tropsch Diesel Fuel Provided by NREL (2007 dollars and 10% after tax rate of return) Plant Size MMgal/yr 33.2 Diesel Fuel 49.4 All Liquid Capital Cost $MM 346 Capital Cost 10% ROI after taxes ($MM/yr) 61.7 Fixed Costs ($MM/yr) 18.3 Feedstock Cost ($MM/yr) 39.1 Coproduct Credit ($MM/yr) a -53.5 Other raw material Costs ($MM/yr) 0.9 Waste Disposal and Catalyst Costs ($MM/yr) 1.1 Total Costs ($MM/yr) 79 Total Costs (cents/gallon of diesel fuel) 206 a Based on a naphtha coproduct value of 327 cents per gallon.

NREL estimated that diesel fuel made by a 33 million gallon per year FT plant in 2022 could be produced at $2.06 per ga llon estimated (in year 2007 dollars). lxxiv Three adjustments however are needed to make the NREL production co st compatible with the rest of our analysis: 1) increase the feedstock costs, 2) reduce the ca pital charge costs and 3) adjust the co-product prices for naphtha and wax.

For capital charges, the NREL costs were based on amortizing capital assuming a 10 percent rate of return after taxe s, using an annual capital charge factor of 0.178. The report’s estimate for capital costs was $346 million for the pl ant, resulting in annual capital cost of $61.6 million or $1.85 per gallon of diesel fuel produced. We adjusted the capital cost by amortizing the capital cost assuming a 7 percent rate of return before taxes, using an annual capital charge factor of 0.11 which resulted in yearly cost of $38 million or $1.14 per gallon of diesel fuel produced.

In the NREL study, the total operating cost due to feedstock is $1.17 per gallon, using wood at $50.7 per dry ton. We adjusted the feed stock cost to $67.4 per dry ton, see subsection 4.1.1.2.1 , which increased the feedstock cost s to $1.56 per gallon of diesel fuel.

In the NREL analysis, the co-products produced have a credit value of $1.60 per gallon of diesel fuel, assuming a price for naphtha of $3.27 per gallon and wax at $0.49 per pound. The price of naphtha was set by NREL at 40 cents pe r gallon below the price of gasoline to account for its low octane value. The naphtha produced by the BTL process is also largely comprised of paraffins, however, as a gasoline blendstock it is poor because its octane could potentially be as low as 50. This material could be processed by refinery isomeriza tion units raising its octane to perhaps 70 octane, but it cannot be processed by refinery reformers since it does not contain the napthenic compounds that are necessary for octane improvement by those units. Because of the large amount of octane rich ethanol which is ex pected to be made available from both corn and cellulose, it could be that BTL na phtha could be blended along with the ethanol into the gasoline pool. Rather than prejudge how this naphtha may be utilized in the future, for our cost analysiswe simply assigned it a coproduct credit. So we set the BTL naphtha cost to be 83% as much of the cost of BTL diesel fuel based on its relative ener gy density. This results in a naphtha price of $1.98 per gallon. We adjusted the price of wax, by ratio-ing the NREL price by the change in price for naphtha. The price adjustment for napht ha and wax, results in a co-product value of $0.97 per gallon of FT diesel produced. The resu lt is a diesel fuel production cost of $2.37 per gallon from the FT process.

Table 4.1-45 summarizes NREL’s estimated and projected production costs for a thermochemical Fischer Tropsch biochemical cellulosic ethanol plant technology for their projected year 2022 technology in 2007 dollars reflec ting a 7 percent before tax rate of return on investment. The costs are based on a cellu losic feedstock cost of $67.4 per dry ton.

Table 4.1-45 Year 2022 Production Costs for Thermochemcal (BTL) Cellulosic Fischer Tropsch Diesel Fuel Provided by NREL (2007 dollars and 7% before tax rate of return) Plant Size MMgal/yr 33.2 Diesel Fuel 49.4 All Liquid Capital Cost $MM 346 Capital Cost 7% ROI be fore taxes ($MM/yr) 38 Fixed Costs ($MM/yr) 18 Feedstock Cost ($MM/yr) 52 Coproduct Credit ($MM/yr) a -32 Other raw matl. Costs ($MM/yr) 1.5 Waste Disposal and Catalyst Costs ($MM/yr) 1.5 Total Costs ($MM/yr) 79 Total Costs (cents/gallon of diesel fuel) 237 a Based on a naphtha coproduct value of 198 cents per gallon.

Initially, the estimated cost of $2.37 per gallon seems high relative to the projected cost for a year 2022 biochemical cellulo sic ethanol plant, which is 126 cents per gallon of ethanol (see subsection 4.1.1.2.4)

. However, ethanol provides about half the energy content on a per gallon basis as Fischer Tropsch diesel fuel. S o, if we double the biochemical cellulosic ethanol costs to $2.52 to be consistent with the energy per diesel fuel-equivalent gallon, the estimated costs are very consistent between the two. The cellulosic biofuel tax subsidy currently favors the biochemical ethanol plant, though, because it is a per-gallon subsidy regardless of the energy content, and it therefore offsets twice as much cost as the BTL plant producing diesel fuel. However, the cellulosic diesel fuel may still be more valuable in the marketplace than cellulosic ethanol. In 2008 and for much of 2009 diesel fuel was priced higher than gasoline, and if this trend continues in the future, it may provide a better market for selling the BTL diesel fuel than for selling biochemical ethanol into the E85 market.

It was necessary to estimate cellulosic diesel fuel costs for previous years for the year-byyear cost analysis (see Section 4.4). However, NREL did not provide costs for previous years, although NREL did say that the primary differen ce in costs for the previous years would be65 economies of scale impacts for the capital costs due to smaller sized plants. Thus, to derive a cost for 2010, we estimated that the cellulosic diesel fuel plants that would be installed in 2010 would be half the size of the plant estimated for 2022. While the total capital costs decrease, the capital costs increase relative to the volume of cel lulosic diesel fuel produced. We increased the naphtha credit from 198 cents per gallon to 216 cen ts per gallon to maintain an 83% cost percentage relative to the cellulosic diesel fuel. For this smaller plant size, we estimate the cost for cellulosic diesel fuel to be 258 cents per gallon.

Other Cellulosic Diesel Fuel Costs

For our volumes analysis, we assumed early on for our final rule analysis that there would likely be one or more other cellulosic diesel fuel technologies, other than BTL, producing cellulosic diesel fuel. However, we were either not able to obtain cost information from them, or we were uncertain enough about their future that we felt that we should not base the cost of the program on them. For example, Cello Energy has already built a cellulosic diesel fuel facility in Alabama here in the US with pr ojected costs of about one dolla r per gallon of diesel fuel. However, the facility has had difficulty operating as designed. As a result, perhaps very conservatively, we assumed that the other cellulosi c diesel fuel costs would be the same as the BTL diesel fuel costs, and used the 237 cents pe r gallon cost for BTL diesel fuel for the entire cost for cellulosic diesel fuel.



### 4.2 Renewable Fuel Distribution Costs

Our analysis of the costs associated with distributing the volumes of biofuels that we project will be used under RFS2 focuses on: 1) the capital cost of making the necessary upgrades to the fuel distribution in frastructure system directly related to handling these fuels, and 2) the ongoing additional freight costs associated with shipping renewable fuels to the point where they are blended with petroleum-based fuel s. Our analysis considers distribution costs within the U.S. only. The costs associated w ith bringing ethanol imports to the U.S. are considered in the context of the cost of the imports themselves. We chose to evaluate the distribution costs for cellulosic distillate and renewable diesel together because the same considerations apply to their handling in the fu el distribution system a nd because the projected volume of renewable diesel fuel is relatively small. The following sections outline our estimates of the distribution costs for the additional volumes of ethanol, cellulosic distillate fuel/renewable diesel fuel, and biodiesel that we project will be used to meet the RFS2 standards. There will be ancillary costs associated with upgrading the basic rail, marine, and road transportation nets to handle the increase in freight volume due to the RFS2. We have not sought to quantify these ancillary costs because 1) the growth in freight traffic that is attributable to RFS2 represents a minimal fraction of the total anticipated increas e in freight tonnage (approximately 0.4% by 2022, see Section 1.6.3 of this RIA), and 2) we do not believe there is an adequate way to estimate such non-direct costs.

The biofuels used in response to the RFS2 standards will displace petroleum-based fuels that would otherwise be used. T hus, it would be appropria te to subtract the distribution costs for the displaced petroleum-based fuels from the distribution costs attributed to the biofuels thatreplace these petroleum-based fuels. However, we chose not to do so as it is difficult to project exactly what changes would result in cost saving s. As a result, our analysis should provide a conservatively high estimate of biofuel distribution costs given the uncertainties in our analysis.

A discussion of the changes that will be needed in the biofuels distribution system to accommodate the increased volumes of biofuels that we project will be used to meet the RFS2 standards is contained in Section 1.6 of this RIA. In this Secti on, we further detail the nature of these projected changes and estimate the associated costs. Distribution capital costs associated with the additional volume of ethanol, cellulosic distillate fuel/renewable diesel, and biodiesel that we project will be used by 2022 to meet the RFS2 standards under the primary mid-ethanol scenario relative to the AEO 2007 reference case to tals $8.4 billion, of which 68% is attributed to ethanol, 17% to cellulosic distillate/renewable diesel fuel, and 14% to biodiesel.

4.2.1 Ethanol Distribution Costs

As discussed in the following sections, we estimate that the total capital costs in the U.S to support distribution of the additional volume of ethanol that will be used to meet the RFS2 standards under the primary mid-e thanol scenario will be $5.5 billion by 2022 relative to the AEO 2007 reference case. When amortized, this tr anslates to 7 cents per gallon of additional ethanol used to meet the RFS2 standards. Amortization of capital costs was done over 15 years at a 7% annual cost of capital except in the cas e of the cost of tank trucks where a 10 year amortization schedule was used. These costs we re calculated relative to the AEO 2007 baseline which projects that 13.2 BGY of ethanol would be used in 2022 absent the RFS2 standards. Under the mid-ethanol primary scenario, we proj ect that 22.2 BGY of ethanol will be used by 2022. Ethanol freight costs are estimated to be 13 cents per gallon on a national average basis. Thus, we estimate that total ethanol distribution costs will be 20 cents per gallon of ethanol that we project will be used to meet the RFS2 standards. 19

The ethanol distribution capital and freight costs for all the control scenarios relative to the 2 reference cases that we evaluated in this FRM is summarized in Table 4.2-1. The itemized ethanol capital costs are presented in Table 4.2-2 relative to the AEO 2007 reference case, and in Table 4.2-3 relative to the RFS1 reference case. These costs do not include the potential costs to supply butane to terminals for E85 blending, wh ich are presented in Table 4.2-4. The way in which we estimated these costs is detailed in the following sections.

19 As noted previously, we chose not to subtract the distribution costs for the petroleum-based fuels that would be displaced by the use of biofuels from our estimated biofuel distribution costs. We believe that the freight costs to ship petroleum-based fuels to the terminal are approximately 4 cents per gallon. If we were to subtract these costs from the estimated ethanol distribution costs under the mid-ethanol scenario relative to the AEO 2007 reference case, the result would be 16 cents per gallon.67 Table 4.2-1. Summary of Estimated Ethanol Distribution Capital and Freight Costs for the RFS2 Control Scenarios Relative to the Reference Cases

Low-Ethanol Scenario Mid-Ethanol Scenario High-Ethanol Scenario RFS1 Reference AEO Reference RFS1 Reference AEO Reference RFS1 Reference AEO Reference Billion $

Capital 5.5 3.0 7.9 5.5 11.9 9.9

Capital Costs (cpg) 6 8 6 7 5 6

Freight

Costs (cpg) 13 13 13 13 12 12

Total Distribution Costs (cpg) 19 21 19 20 17 18

Table 4.2-2. Summary of Estimated Ethanol Distribution Capital Costs for the RFS2 Control Scenarios Relative to the AEO 2007 Reference Case

Capital Cost (Million $) Low-Ethanol Scenario Mid-Ethanol Scenario High-Ethanol Scenario Rail Cars 365 760 1,699 Barges 22 45 102 Tank Trucks 42 87 194 Storage Tanks at Petroleum Terminals 355 739 1,568 Blending and other Miscellaneous Equipment at Petroleum Terminals 345 411 503

Unit Train Receipt Facilities 238 434 748 Manifest Rail Receipt Facilities 7 12 21 Marine Receipt Facilities for Inta-U.S. Transport 76 100 144

Import Receipt Facilities 49 53 63 E85 Retail Facilities 1,526 2,863 4,893 Total (Million $) 3,025 5,505 9,935 Total (cpg) 8 7 6Table 4.2-3. Summary of Estimated Ethanol Distribution Capital Costs for the RFS2 Control Scenarios Relative to the RFS1 Reference Case

Capital Cost (Million $) Low-Ethanol Scenario Mid-Ethanol Scenario High-Ethanol Scenario Rail Cars 884 1,279 2,218 Barges 53 77 133 Tank Trucks 107 154 268 Storage Tanks at Petroleum Terminals 859 1,243 2,073 Blending and other Miscellaneous Equipment at Petroleum Terminals 1,006 1,064 1,144

Unit Train Receipt Facilities 444 586 838 Manifest Rail Receipt Facilities 15 20 28 Marine Receipt Facilities for Inta-U.S. Transport 98 130 186

Import Receipt Facilities 49 53 63 E85 Retail Facilities 1,957 3,293 4,973 Total (Million $) 5,471 7,898 11,922 Total (cpg) 6 6 5

Table 4.2-4. Potential Costs to Provide Butane to Terminals for E85 Blending for the RFS2 Control Scenarios

Capital Cost (Million $) Low-Ethanol Scenario Mid-Ethanol Scenario High-Ethanol Scenario Butane Blending, Storage, Receipt and Other Miscellaneous Terminal Costs 235 536 1,249

Tank Trucks 325 830 837 Rail Cars 32 81 89 Total Capital Costs 592 942 2,175 Freight Cost (Annual cost in 2022) 16 24 40 Total Butane Distribution Costs Relative to the RFS1 Reference Case (cpg ethanol) 1 1 1

Total Butane Distribution Costs Relative to the AEO Reference Case (cpg ethanol) 2 2 269 4.2.1.1 Capital Costs to Upgrade the Ethanol Distribution System

4.2.1.1.1 Petroleum Terminal Ethanol Distribution Capital Costs

The terminal facility modifications needed to support the use of the volume of ethanol that we project will be used to meet the RF S2 standards are discussed in Section 1.6.7. A summary of the costs associated with these m odifications is detailed in Tables 4.2-5 and 4.2-6.

Table 4.2-5. Ethanol Associated Petroleum Terminal Costs for the RFS2 Control Scenarios Relative to the AEO Reference Case

Capital Cost (Million $) Low-Ethanol Scenario Mid-Ethanol Scenario High-Ethanol Scenario Total Costs 858 1,150 1,913 Total Storage Tank Costs 355 739 1,568 New Storage Tank Construction Costs 291 606 1,287 Cost to Retrofit Existing Storage Tanks 64 133 282 Costs to Prepare Terminals to Handle Ethanol for the First Time 167 167 167

Tank Truck Unloading Facilities 277 186 123 Ethanol Blending and Miscellaneous Ethanol Handling Costs 59 57 55

Table 4.2-6. Ethanol Associated Petroleum Terminal Costs for the RFS2 Control Scenarios Relative to the RFS1 Reference Case

Capital Cost (Million $) Low-Ethanol Scenario Mid-Ethanol Scenario High-Ethanol Scenario Total Costs 2,003 2,307 3,078 Total Storage Tank Costs 859 1,243 2,073 New Storage Tank Construction Costs 705 1,020 1,701 Cost to Retrofit Existing Storage Tanks 154 223 372 Costs to Prepare Terminals to Handle Ethanol for the First Time 594 594 594

Tank Truck Unloading Facilities 366 286 231 Ethanol Blending and Ancillary Ethanol Handling Costs 184 183 180

The above cost estimates are bases on the fo llowing. Input from terminal operators indicates that the primary modifi cations needed to prepare a terminal to handle ethanol for thefirst time are associated with the modification of vapor recovery equipment to handle ethanolcontaining gasoline at a cost of $1,000,000 per te rminal. We added another $20,000 to account for related ancillary costs. Input from terminal operators indicates that the cost of ethanol blending equipment is $300 thousand for E 10-capable equipment, $310 thousand for E85- capable equipment, and $10,000 to upgrade E10-ca pable equipment to handle E85. Input from companies that are familiar with the installation of ethanol truck unloading equipment at terminals indicates that the cost averages $500 thousand per facility. Input from terminal operators indicates that the cost of new ethanol storage tank c onstruction is $40 per barrel of capacity, and that the cost of retrofitting existing gasoline storage tanks for ethanol service is $5 per barrel of capacity for the size of tanks that are likely to be used.

4.2.1.1.2 Capital Cost of Unit Train Receipt Facilities for Ethanol

Our estimation of the number of unit train re ceipt facilities that w ill be need to support the transport of the volumes of ethanol and cellulosic distillate fuel that we project will be used to meet the RFS2 standards is discussed in Section 1.6.4 of this RIA. Input from industry indicates that the cost of un it train receipt facility capable of handling 229 million gallons of biofuels per year is $10 million and the cost of a facility capable of handling 613 million gallons is $25 million. We interpolated between these two estimates to derive a cost estimate for each unit train receipt facility that we projected w ill be constructed based on its anticipated annual throughput volume. The total cost of unit train receipt facilities was divi ded between ethanol and cellulosic distillate fuel/renewable diesel fuel in proportion to the fraction of the total ethanol + cellulosic distillate fuel/renewable diesel fu el volume under the respective control scenario.

Our projections of the total cost of unit train receipt facilities and the portion that we attributed to the volume of ethanol that we project will be used to meet the RFS2 standards is presented in Tables 4.2.7 and 4.2.8.

Table 4.2-7. Cost of Unit Train Facilities to Fa cilitate the Transport of Ethanol for the RFS2 Control Scenarios Relative to the AEO Reference Case

Capital Cost (Million $) Low-Ethanol Scenario Mid-Ethanol Scenario High-Ethanol Scenario Total Cost of Unit Train Facilities Needed for the Transport of Ethanol and Cellulosic Distillate Fuel/Renewable Diesel Fuel 748 748 748

Cost of Unit Train Facilities Attributed to Ethanol Transport 238 434 73871 Table 4.2-8. Cost of Unit Train Facilities to Facilitate the Transport of Ethanol for the RFS2 Control Scenarios Relative to the RFS1 Reference Case

Capital Cost (Million $) Low-Ethanol Scenario Mid-Ethanol Scenario High-Ethanol Scenario Total Cost of Unit Train Facilities Needed for the Transport of Ethanol and Cellulosic Distillate Fuel/Renewable Diesel Fuel 838 838 838

Cost of Unit Train Facilities Attributed to Ethanol Transport 444 586 838

4.2.1.1.3 Capital Cost of Manifest Ra il Receipt Facilities for Ethanol

Our estimation of the number of manifest rail receipt facilities that will be needed to support the transport of the volumes of ethanol an d cellulosic distillate fuel that we project will be used to meet the RFS2 standards is discussed in Section 1.6.4 of this RIA. The cost of these facilities was divided between ethanol and cellulosic distillate fuel/renewable diesel fuel in proportion to the fraction of the total ethanol + ce llulosic distillate fuel/r enewable diesel fuel volume. Based on input from companies familiar w ith the installation of manifest rail receipt facilities, we estimate that the total cost per facility will be $500 thousand.

Our projections of the total cost of the mani fest rail receipt facilities and the portion that we attributed to the volume of ethanol that we project will be used to meet the RFS2 standards is presented in Tables 4.2.9 and 4.2.10.

Table 4.2-9. Cost of Manifest Rail Receipt Facilities for the RFS2 Control Scenarios Relative to the AEO Reference Case

Capital Cost (Million $) Low-Ethanol Scenario Mid-Ethanol Scenario High-Ethanol Scenario Total Cost of Manifest Rail Receipt Facilities Needed for the Transport of Ethanol and Cellulosic Distillate Fuel/Renewable Diesel Fuel 21 21 21

Cost of Unit Train Facilities Attributed to Ethanol Transport 14 9 21Table 4.2-10. Cost of Manifest Rail Receipt Facilities for the RFS2 Control Scenarios Relative to the RFS1 Reference Case

Capital Cost (Million $) Low-Ethanol Scenario Mid-Ethanol Scenario High-Ethanol Scenario Total Cost of Manifest Rail Receipt Facilities Needed for the Transport of Ethanol and Cellulosic Distillate Fuel/Renewable Diesel Fuel 28 28 28

Cost of Unit Train Facilities Attributed to Ethanol Transport 13 8 28

4.2.1.1.4 Ethanol Import Fac ility Capital Costs

Our estimation of the number of marine fa cilities that will be needed to support the receipt of the volume of importe d ethanol that we project will be used to meet the RFS2 standards is discussed in Secti on 1.6.5 of this RIA. We estimate that a total of 30 port facilities will receive imported ethanol by 2022. Of these ports, 14 will need to accommodate ethanol receipts for the first time under the low-ethanol scenario, 15 under the mid-ethanol scenario, and 18 under the high ethanol scenario.

We believe that all such port facilities also serve as petroleum terminals. Thus, the cost of additional ethanol storage, ethanol blending equipment, a nd other miscellaneous equipment related to handling ethanol from the standpoint of terminal ope rations at such facilities is accounted for in the context of the costs at petroleum terminals (s ee Section 4.2.1.1.1 of this RIA). However, there will be additional costs at the port facilities which had not received ethanol in the past. Input from industry indica tes that offloading la rge marine transport containers of ethanol requires significantly upgraded vapory recovery equipment. Based on this input, we estimated the cost of making the need ed upgrades to vapor recovery equipment at 2.5 million dollars per facility. We further estimated miscellaneous costs associated with delivery of ethanol into storage tanks from marine vessels at 1 million dollars per facility. This is meant to include new piping, pumps, various other fittings, and a contingency cost. The actual cost could be significantly lower. Thus, we estimate that the total cost to prepare for delivery of ethanol at a port that had not received ethanol befo re at 3.5 million dollars per facility.

Based on the above, we estimate that the etha nol import port costs due to the importation of the additional volume of ethanol used to meet the RFS2 standards will be $49 million under the low-ethanol scenario, $52 million under the mi d-ethanol scenario, and $63 million under the high-ethanol scenario. We assumed the same co sts relative to both the RFS1 and AEO reference cases because we believe that the use of the incr emental volume of ethanol imports attributed to meeting the RFS2 standards will take place afte r the RFS1 and AEO ethanol use volumes are

met.

4.2.1.1.5 Capital Costs of Barge Receipt Fac ilities for Intra-U.S Ethanol Transport73 Our estimation of the number of barge receipt facilities for intra-U. S. biofuel shipment that will be need to support the transport of the volumes of ethanol and ce llulosic distillate fuel that we project will be used to meet the RFS2 st andards is discussed in Section 1.6.5 of this RIA. We estimate that 41 additional barge receipt f acilities will receive ship ments of ethanol and cellulosic distillate fuel/renewable diesel fuel relative to the AEO reference case and 53 relative to the RFS1 reference case. We used the same $3.5 million per facility cost that we estimated for the ethanol import facilities (see Section 4.2.1.1.4). The cost of these facilities was divided between ethanol and cellulosic distillate fuel/renewable diesel fuel in proportion to the fraction of the total ethanol + cellulosic distillate fuel/renewable diesel fuel volume.

Our projections of the total cost of the ba rge receipt facilities and the portion that we attributed to the volume of ethanol that we project will be used to meet the RFS2 standards is presented in Tables 4.2.11 and 4.2.12.

Table 4.2-11. Cost of Barge Receipt Facilities for the RFS2 Control Scenarios Relative to the AEO Reference Case

Capital Cost (Million $) Low-Ethanol Scenario Mid-Ethanol Scenario High-Ethanol Scenario Total Cost of Barge Receipt Facilities Needed for the Transport of Ethanol and Cellulosic Distillate Fuel/Renewable Diesel Fuel 143 143 143

Cost of Barge Receipt Facilities Attributed to Ethanol Transport 76 100 143

Table 4.2-12. Cost of Barge Receipt Facilities for the RFS2 Control Scenarios Relative to the RFS1 Reference Case

Capital Cost (Million $) Low-Ethanol Scenario Mid-Ethanol Scenario High-Ethanol Scenario Total Cost of Barge Receipt Facilities Needed for the Transport of Ethanol and Cellulosic Distillate Fuel/Renewable Diesel Fuel 185 185 185

Cost of Barge Receipt Facilities Attributed to Ethanol Transport 98 129 1854.2.1.1.6 Ethanol Rail Ca r Capital Costs

Our estimation of the number of rail cars needed to transport the additional volume of ethanol that we project will be used to meet th e RFS2 standards is discussed in Section 1.6.4 of this RIA. Based on input from rail car manufact ures, we estimate that the cost of a new 30,000 gallon rail car suitable for ethanol service is $90 thousand. The cost of the additional ethanol rail cars needed under the 3 control scenarios relative to the 2 reference cases is presented in Tables 4.2-13 and 4.2-14.

Table 4.2-13. Cost of Additional Ethanol Rail Cars for the RFS2 Control Scenarios Relative to the AEO Reference Case

Low-Ethanol Scenario Mid-Ethanol Scenario High-Ethanol Scenario Number of Additional Rail Cars 4,050 8,450 18,870 Rail Car Cost ($Million) $365 $760 $1,699

Table 4.2-14. Cost of Additional Ethanol Rail Cars for the RFS2 Control Scenarios Relative to the RFS1 Reference Case

Low-Ethanol Scenario Mid-Ethanol Scenario High-Ethanol Scenario Number of Additional Rail Cars 9,820 14,210 24,639 Rail Car Cost ($Million) $884 $1,279 $2,218

4.2.1.1.7 Ethanol Barge Capital Costs

Our estimation of the number of barges needed for intra-U.S. transport of the additional volume of ethanol that we project will be used to meet the RFS2 standards is discussed in Section 1.6.5 of this RIA. Based on input from fuel barge manufactures, we estimate that the cost of a new 10,000 barrel barge suitable for ethanol service is $1.4 million. The cost of the additional ethanol barges needed under the 3 control scenarios relative to the 2 reference cases is presented in Tables 4.2-15 and 4.2-16.75 Table 4.2-15. Cost of Additional Ethanol Barges for the RFS2 Control Scenarios Relative to the AEO Reference Case

Low-Ethanol Scenario Mid-Ethanol Scenario High-Ethanol Scenario Number of Additional Barges 16 32 73 Cost of Barges ($Million) $22 $45 $101

Table 4.2-16. Cost of Additional Ethanol Barges for the RFS2 Control Scenarios Relative to the RFS1 Reference Case

Low-Ethanol Scenario Mid-Ethanol Scenario High-Ethanol Scenario Number of Additional Barges 38 55 95 Cost of Barges ($Million) $53 $76 $133

4.2.1.1.8 Ethanol Tank Truc k Capital Costs

Our estimation of the number of tank trucks needed to transport the additional volume of ethanol that we project will be used to meet th e RFS2 standards is discussed in Section 1.6.6 of this RIA. Based on input from ethanol tank truc k manufactures, we estimate that the cost of a new 8,000 gallon tank truck suitable for ethanol service is $180 thousand. The cost of the additional ethanol tank trucks needed under the 3 control scenarios relative to the 2 reference cases is presented in Tables 4.2-17 and 4.2-18.

Table 4.2-17. Cost of Additional Et hanol Tank Trucks for the RFS2 Control Scenarios Relative to the AEO Reference Case

Low-Ethanol Scenario Mid-Ethanol Scenario High-Ethanol Scenario Number of Additional Tank Trucks 230 480 1,080 Cost of Tank Trucks ($Million) $42 $87 $194

Table 4.2-18. Cost of Additional Et hanol Tank Trucks for the RFS2 Control Scenarios Relative to the RFS1 Reference Case

Low-Ethanol Scenario Mid-Ethanol Scenario High-Ethanol Scenario Number of Additional Tank Trucks 590 860 1,490 Cost of Tank Trucks ($Million) $107 $154 $2684.2.1.1.9 E85 Retail Facility Costs

Our estimates of the number of additional E85 retail facilities and the number of E85 refueling positions needed at such facilities to enable the use of the volumes of E85 that we project will be used to meet the RFS2 standards under the 3 control scenarios is contained in Section 1.6.9 of this RIA. Our estimates of the additional E85 refueling infrastructure that will be needed relative to the 2 reference ca ses are presented in Table 4.2-19 and 4.2-20.

Table 4.2.19. Additional E85 Retail Facilitie s Needed by 2022 to Support th e Projected Incr ease in E85 use under the RFS2 Control Scenarios Relative to the RFS1 Reference Case

Low-Ethanol Scenario Mid-Ethanol Scenario High-Ethanol Scenario New E85 Installation with 1 Dispenser 14,967 10,923 0 New E85 Installation with 2 Dispensers 0 12,133 0 New E85 Installation with 3 Dispensers 0 0 27,099 Addition of 2 Dispensers to Retail Facility that had 1 Dispenser 0 0 1,210

Table 4.2.20. Additional E85 Retail Facilities Needed by 2022 to Support the Projected Increase in E85 use under the RFS2 Control Scenarios Relative to the AEO Reference Case

Low-Ethanol Scenario Mid-Ethanol Scenario High-Ethanol Scenario New E85 Installation with 1 Dispenser 11,677 7,633 0 New E85 Installation with 2 Dispensers 0 12,133 0 New E85 Installation with 3 Dispensers 0 0 23,809 Addition of 2 Dispensers to Retail Facility that had 1 Dispenser 0 0 4,500

The following estimates regarding the cost of E85 compatible retail equipment are based on input from gasoline retailers and other parties with experience in the requirements and costs associated with installing E85 retail equipment. The total cost of installing a two nozzle E85 dispenser is estimated at $23,000. This is com posed of $17,000 for the dispenser itself, $750 for hanging hardware, $950 for refueling isla nd hardware, $3,000 for installation, and a $1,300 contingency cost. Hanging hardware costs are composed of $310 for 2 nozzles, $135 for 2 breakaway connections, $135 for 2 swivel connec tions, and $170 for 2 hoses. Refueling island hardware costs are composed of $450 for the dispenser island, $250 for an island sump pump, and $250 for bumper posts. Installation costs ar e composed of $1,500 for concrete removal and replacement, and $1,500 for wiring and piping.

The cost of automatic tank level gauging equipment is estimated at $6,500. It is estimated that 65% of retailers will install automatic tank gauging (ATG) equipment and the remainder will rely on manual m eans of determining the amount of fuel remaining in their77 underground storage tank. Thus, the average cost per facility will be $4,225 for ATG equipment. We estimate the cost of installing a canopy addition to provide cover for an additional dispenser at $15,000. We estimated that only 10% of facilit ies will need to inst all additional canopy coverage in order to accommodate the new E85 re tail dispenser. Thus, the average canopy cost per facility is estimated at $1,500. The cost of installing a new 15,000 underground E85 storage tank is estimated at $102,000. The cost of connectin g the tank to the dispenser(s) is included in this cost along with other miscellaneous storage tank related costs. In the NPRM, we estimated that an 8,000 gallon storage tank would be used at E85 retail facilities. We increased the size to 15,000 based on industry comments that the added st orage volume will be needed to keep pace with fuel throughput without necessitating an overl y-frequent fuel delivery schedule. The use of a 15,000 gallon storage tank will also allow the delivery of a full 8,000 gallon tank truck at a single retail facility. Input fro m fuel retailers indicates that there typically is at least 15,000 gallons of gasoline storage at current retail facilities.

Our E85 retail facility cost estimates are pr esented in Table 4.2-21 are based on the above E85 equipment cost estimates a nd the estimated facility requireme nts detailed in Tables 4.2-19 and 4.2-20.

Table 4.2-21. Cost of the Additional E85 Re tail Facilities Needed by 2022 to Support the Projected Increase in E85 use under the RFS2 Control Scenarios

E85 Capital Costs ($Billion) Low-Ethanol Scenario Mid-Ethanol Scenario High-Ethanol Scenario Relative to the AEO 2007 Reference Case 1.526 2.863 4.893

Relative to the RFS1 Reference Case 1.956 3.293 4.973

4.2.1.1.10 Potential Costs of Supplying Special Blendstocks at Petroleum Terminals for E85

As discussed in Section 1.6.8 of this RIA, spec ial blendstocks may need to be supplied to terminals to facilitate the manufacture of E85 which meets ASTM International minimum volatility specifications. To evaluate the potential impacts to the fuel distribution system if this is the case, we assumed that butane would be used as the special blendstock and that it would be blended into gasoline before being blended with denatu red ethanol to produce E85. As such, we estimated the potential costs associated with automated inline butane blending systems, butane storage tanks, tank trucks, railcars, transloading facilities, and other facility changes needed for butane blending into E85. These costs are based upon discussions with industry representatives.

We assume that butane would be transported by tank truck and/or ra ilcar from petroleum refineries to E85-producing petr oleum terminals and stored until blended into a final product. Of the 1,063 terminals identified in our analysis, two-th irds (709) are assumed to blend E85. All of these terminals are assumed to require butane blending equipment. Our cost estimates assumed that twenty-five percent (177) of these termin als will receive butane via 31,500 gallon railcar andthe remaining seventy-five perc ent (532) will receive butane vi a 8,200 gallon tank truck. Of the 177 terminals that receive butane vi a railcar, fifty-percent are assume d to directly off-load butane to tank storage for eventual blending into E85. The other fifty-percent of the terminals which received butane via railcar are assumed to transload the butane from railcars to tank trucks for final delivery to terminals which store but ane for eventual blending into E85.

The blending of butane into E85 requires pe troleum terminals to have on-site butane blending equipment. In developing our cost es timates, we assume that each terminal which blends E85 uses an automated, in-line butan e blending system and two 60,000 gallon butane storage tanks. The cost of an in-line butane blending systems is assumed to be $1.5 million per unit. The cost each 60,000 gallon butane storag e tank is assumed to be $150,000. Transloading equipment is assumed to cost $500,000 per unit.

Transport cost estimates we re based upon the ORNL transport analysis discussed in Section 1.6.3. In that analysis, the cost of frei ght rail transport was assumed to average $0.12 per ton-mile. The cost of truck transport was assumed to average $0.14 per ton-mile. Average round trip distance is assumed to be 1,200 mile s for railcars and 300 mile s for tank trucks. Travel speed estimates are truck 35 mph a nd railcar 10 mph with roundtrip times being approximately 8 hours for trucks a nd 5 days for railcars. Each tank truck is assumed to cost $150,000 and each railcar is assumed to cost $135,000.

Estimates of the number of tank trucks and railcars required to deliver butane appears by low, medium, and high volume cases in Table 4.2-22 and a summary of cost estimates for the three volume cases appears in Table 4.2-23.

Table 4.2-22. Estimated Number of Tank Trucks and Rail Cars Needed for Shipment of Butane under the RFS2 Control Scenarios

Number of Tank Trucks and Rail Cars Needed to Transport Butane Low-Ethanol Scenario Mid-Ethanol Scenario High-Ethanol Scenario Tank Truck (8,200 gallons) 2,165 3,280 5,530 Railcar (31,500 gallons) 236 358 602

Table 4.2-23. Summary of Potential Costs to Provide Butane for E85 Blending under the RFS2 Control Scenarios

Freight Costs Capital Costs Low-Ethanol Scenario $16 million $357 million Mid-Ethanol Scenario $24 million $911 million High-Ethanol Scenario $40 million $927 million79 4.2.1.2 Ethanol Freight Costs

Our estimates of ethanol freight costs ar e based on a study conducted by Oakridge National Laboratories (ORNL). lxxv The ORNL analysis contains detailed projec tions of which transportation modes and combina tion of modes (e.g. unit train to barge) are best suited for delivery of ethanol to specific markets consid ering ethanol source and end use locations, the current configuration and projected evolution of the distribution sy stem, and cost considerations for the different transportation modes. The NP RM analysis assumed that all biofuel volumes other than biodiesel would be ethanol. For this FRM, we analyzed three scenarios under which varying volumes of cellulosic dis tillate fuel take the place of etha nol production volumes to meet the RFS2 standards. However, due to the timing of the various analyses for the FRM, the NPRM projections of the location of ethanol production facilities and e nd use areas contained in the NPRM had to be used as the inputs into the ORNL analysis. 20 Therefore, our use of the ORNL analysis to evaluate the freight costs for the fi nal rule assumes that ce llulosic distillate production plants will take the place of some of the ethanol production plants projected in the NPRM. It further assumes that cellulosic distillate fuel use will coincide with the ethanol end-use areas projected in the NPRM and that both fuels will be transported by the same means.

We estimated the freight costs under the FRM co ntrol scenarios by totaling the cellulosic distillate/renewable diesel fuel and ethanol volume under each scenario and interpolating between the freight costs projected by ORNL for 2 NPRM ethanol volum e scenarios. This approach provides for the economy of scale in bi ofuel freight costs with increased volume. Based on this approach, we estimate that ethanol freight costs will be 12 cents per gallon (cpg) under the high-ethanol scenario and 13 cpg under the low-ethanol and mid-ethanol scenarios. Our use of the ORNL freight cost estimates to derive the freight FRM freight cost estimates is illustrated in Table 4.2-24.

20 The ORNL final report contains maps of projected ethanol production locations and end use areas.Table 4.2-24. Interpolation of FRM Ethanol and Cellulosic Distillate Fuel/Renewable Diesel Fuel Freight Costs from ORNL Freight Cost Estimates for NPRM Ethanol Volume Scenarios

Volume of Ethanol, Cellulosic Distillate Fuel, and Renewable Diesel Fuel (BGal/yr in 2022) Freight Cost (cpg)

NPRM Control Scenario 34.14 12.2 (ORNL estimate) FRM High-Ethanol Scenario 33.24 12 (Interpolation) FRM Mid-Ethanol Scenario 28.68 13 (Interpolation) FRM Low Ethanol Scenario 26.75 13 (Interpolation) AEO 2007 Reference Case 13.18 15.3 (ORNL estimate)

4.2.2 Cellulosic Distillate Fu el Distribution Costs

As discussed in the following sections, we estimate that the total capital costs in the U.S to support distribution of the additional volume of cellulosic distillate fuel/renewable diesel fuel that will be used in to meet the RFS2 standards under the primary mid-ethanol scenario will be 1,392 billion dollars by 2022 relative to the AEO 2007 reference case. When amortized, this translates to 2 cents per gallon of additional cellulosic distillate fuel/renewable fuel attributed to the RFS2 standards. Amortization of capital cost s was done over 15 years at a 7% annual cost of capital except in the case of the cost of tank tr ucks where a 10 year amortization schedule was used. Under the mid-ethanol primary scenario, we project that 6.7 BGY of cellulosic distillate fuel/renewable diesel fuel will be used by 2022. Cellulosic distillate fuel/renewable diesel fuel freight costs are estimated to be 13 cents per gallon on a national average basis. Thus, we estimate that total cellulosic distillate fuel/renewable diesel fuel distribution costs will be 15 cents per gallon of cellulosic distillate fuel/renewable diesel fuel that we project will be used to meet the RFS2 standards. 21

The cellulosic distillate fuel/renewable diesel fuel distribution capital and freight costs for all the control scenarios relative to the 2 reference cases that we evaluated in this FRM is summarized in Table 4.2-25. The itemized cellulosic distillate fuel/renewable diesel fuel capital costs are presented in Table 4.2-26 relative to the AEO 2007 reference case, and in Table 4.2-27 relative to the RFS1 reference case. The way in which we estimated these costs is detailed in the following sections. As discussed in the followi ng sections, some biofue l infrastructure assets

21 As noted previously, we chose not to subtract the distribution costs for the petroleum-based fuels that will be displaced by the use of biofuels from our estimated biofuel distribution costs. We believe that the freight costs to ship petroleum-based fuels to the terminal are approximately 4 cents per gallon. If we were to subtract these costs from the estimated cellulosic distillate fuel/renewable diesel fuel distribution costs under the mid-ethanol scenario relative to the AEO 2007 reference case, the result would be 11 cents per gallon.81 such as unit train receipt facilities are used to distribute both cellulosic distillate fuel/renewable diesel fuel and ethanol. We attributed a fraction of the capital costs for such facilities to either cellulosic distillate fuel/renewable diesel fuel or ethanol in proportion to the fraction of the total additional volume of these fuels th at we project will be used to meet the RFS2 standards relative to the reference case. This approach results in a slight difference in the capital costs under the 2 reference case despite the fact that the incremental volume of cellulosic distillate/renewable diesel fuel used to meet the RFS2 standa rds is the same under both reference cases.

Table 4.2-25. Summary of Estimated Cellulosic Distillate Fuel/Renewable Diesel Fuel Distribution Capital and Freight Costs under the RFS2 Control Scenarios Relative to the Reference Cases

Low-Ethanol Scenario Mid-Ethanol Scenario High-Ethanol Scenario

RFS1 Reference AEO Reference RFS1 Reference AEO Reference RFS1 Reference AEO Reference Billion $

Capital 1,999 2,036 1,375 1,392 NA NA

Capital Costs (cpg) 2 2 2 2 NA NA

Freight

Costs (cpg) 13 13 13 13 NA NA

Total Distribution Costs (cpg) 16 16 15 15 NA NATable 4.2-26. Summary of Estimated Cellulosic Distillate Fuel/Renewable Diesel Fuel Distribution Capital Costs under the RFS2 Control Scenarios Relative to the AEO 2007 Reference Case

Capital Cost (Million $) Low-Ethanol Scenario Mid-Ethanol Scenario High-Ethanol Scenario Rail Cars 784 552 NA Barges 47 33 NA Tank Trucks 90 63 NA Storage Tanks at Petroleum Terminals 218 154 NA Blending and other Miscellaneous Equipment at Petroleum Terminals 304 223 NA

Unit Train Receipt Facilities 511 315 NA Manifest Rail Receipt Facilities 15 9 NA Marine Receipt Facilities for Inta-U.S. Transport 67 43 NA

Total (Million $) 2,036 1,392 NA Total (cpg) 2 2 NA

Table 4.2-27. Summary of Estimated Cellulosic Distillate Fuel/Renewable Diesel Fuel Distribution Capital Costs under the RFS1 Reference Case

Capital Cost (Million $) Low-Ethanol Scenario Mid-Ethanol Scenario High-Ethanol Scenario Rail Cars 784 552 NA Barges 47 33 NA Tank Trucks 95 67 NA Storage Tanks at Petroleum Terminals 218 154 NA Blending and other Miscellaneous Equipment at Petroleum Terminals 361 252 NA

Unit Train Receipt Facilities 394 253 NA Manifest Rail Receipt Facilities 13 8 NA Marine Receipt Facilities for Inta-U.S. Transport 87 56 NA

Total (Million $) 1,999 1,375 NA Total (cpg) 2 2 NA

4.2.2.1 Cellulosic Distillate Fuel Distribution Capital Costs

4.2.2.1.2 Petroleum Terminal Cellulosic Distilla te Fuel/Renewable Diesel Fuel Distribution Capital Costs83 The terminal facility modifications needed to support the use of the volume of cellulosic diesel fuel/renewable diesel fuel that we project will be used to meet the RFS2 standards are discussed in Section 1.6.7. A summary of the co sts associated with these modifications is detailed in Tables 4.2-28 and 4.2-29. The estimated costs vary depending on the reference case considered because of the way we attributed the cost of tank truck unloading facilities (which are used to handle both ethanol and cellulosic distillate fuel/renewable diesel fuel) to either ethanol or cellulosic distillate fuel/renewable diesel fuel. The cost of such facilities was divided between ethanol and cellulosic distillate fuel/renewable diesel fuel in proportion to the fraction of the to tal ethanol + cellulosic di stillate fuel/renewable diesel fuel volume.

Table 4.2-28. Cellulosic Distillate Fuel/Renewable Diesel Fuel Associated Petroleum Terminal Costs under the RFS2 Control Scenarios Relative to the AEO Reference Case

Capital Cost (Million $) Low-Ethanol Scenario Mid-Ethanol Scenario High-Ethanol Scenario Total Costs 522 377 NA New Storage Tank Construction Costs 218 154 NA Tank Truck Unloading Facilities 65 55 NA Blending and Miscellaneous Fuel Handling Costs 239 168 NA

Table 4.2-29. Cellulosic Distillate Fuel/Renewable Diesel Fuel Associated Petroleum Terminal Costs under the RFS2 Control Scenarios Relative to the RFS1 Reference Case

Capital Cost (Million $) Low-Ethanol Scenario Mid-Ethanol Scenario High-Ethanol Scenario Total Costs 579 406 NA New Storage Tank Construction Costs 218 154 NA Tank Truck Unloading Facilities 122 84 NA Blending and Miscellaneous Fuel Handling Costs 239 168 NA

The above cost estimates are based on the fo llowing. Input from terminal operators indicates that the cost of ethanol blending equipment is $310 thousand for E85-capable equipment. Input from companies that are fa miliar with the installa tion of ethanol truck unloading equipment at terminal s indicates that the cost averages $500 thousand per facility. Input from terminal operators indicates that the cost of new diesel fuel storage tank construction is $35 per barrel for the size of tanks that are likely to be used. We used the above estimatesregarding the costs of installing similar equipment for cellulosic distillate fuel/renewable diesel fuels.

4.2.2.1.3 Capital Cost of Unit Train Receipt Facilities for Cellulosic Distillate Fuel/Renewable Diesel fuel

Our estimation of the number of unit train recei pt facilities that will be needed to support the transport of the volumes of ethanol and cellulosic distillate fuel/renewable diesel fuel that we project will be used to meet the RFS2 standards is discussed in Section 1.6.4 of this RIA. The cost of these facilities was divided between ethanol and cellulosic distillate fuel/renewable diesel fuel in proportion to the fraction of the total et hanol plus cellulosic distillate fuel/renewable diesel fuel volume. See S ection 4.2.1.1.2 for additional discussi on regarding the derivation of the total cost of unit train receipt facilities.

Our projections of the total cost of unit train receipt facilities and the portion that we attributed to the volume of cellulosic distillate fuel/renewable diesel fuel that we project will be used to meet the RFS2 standards is presented in Tables 4.2-30 and 4.2-31.

Table 4.2-30. Cost of Unit Train Facilities to Facilitat e the Transport of Cellulosic Distillate Fuel/Renewable Diesel Fuel under the RFS2 Control Scenarios Relative to the AEO Reference Case

Capital Cost (Million $) Low-Ethanol Scenario Mid-Ethanol Scenario High-Ethanol Scenario Total Cost of Unit Train Facilities Needed for the Transport of Ethanol and Cellulosic Distillate Fuel/Renewable Diesel Fuel 748 748 748

Cost of Unit Train Facilities Attributed to Cellulosic Distillate Fuel/Renewable Diesel Fuel Transport 394 253 NA85 Table 4.2-31. Cost of Unit Train Facilities to Facilitat e the Transport of Cellulosic Distillate Fuel/Renewable Diesel Fuel under the RFS2 Control Scenarios Relative to the RFS1 Reference Case

Capital Cost (Million $) Low-Ethanol Scenario Mid-Ethanol Scenario High-Ethanol Scenario Total Cost of Unit Train Facilities Needed for the Transport of Ethanol and Cellulosic Distillate Fuel/Renewable Diesel Fuel 838 838 838

Cost of Unit Train Facilities Attributed to Cellulosic Distillate Fuel/Renewable Diesel Fuel Transport 511 315 NA

4.2.2.1.4 Capital Cost of Manife st Rail Receipt Facilities fo r Cellulosic Distillate Fuel/Renewable Diesel Fuel

Our estimation of the number of manifest rail receipt facilities that will be needed to support the transport of the volumes of ethanol an d cellulosic distillate fuel that we project will be used to meet the RFS2 standards is discussed in Section 1.6.4 of this RIA. The cost of these facilities was divided between ethanol and cellulosic distillate fuel/renewable diesel fuel in proportion to the fraction of the total ethanol plus cellulosic distillate fuel/renewable diesel fuel volume. See Section 4.2.1.1.2 for add itional discussion regarding the derivation of the total cost of manifest rail receipt facilities.

Our projections of the total cost of the mani fest rail receipt facilities and the portion that we attributed to the volume of cellulosic distillate fuel/renewable diesel fuel that we project will be used to meet the RFS2 standards is presented in Tables 4.2-32 and 4.2-33.Table 4.2-32. Cost of Manifest Rail Receipt Facilit ies under the RFS2 Control Scenarios Relative to the AEO Reference Case

Capital Cost (Million $) Low-Ethanol Scenario Mid-Ethanol Scenario High-Ethanol Scenario Total Cost of Manifest Rail Receipt Facilities Needed for the Transport of Ethanol and Cellulosic Distillate Fuel/Renewable Diesel Fuel 21 21 21

Cost of Unit Train Facilities Attributed to Cellulosic Distillate Fuel/Renewable Diesel Fuel Transport 14 9 NA

Table 4.2-33. Cost of Manifest Rail Receipt Facilit ies under the RFS2 Control Scenarios Relative to the RFS1 Reference Case

Capital Cost (Million $) Low-Ethanol Scenario Mid-Ethanol Scenario High-Ethanol Scenario Total Cost of Manifest Rail Receipt Facilities Needed for the Transport of Ethanol and Cellulosic Distillate Fuel/Renewable Diesel Fuel 28 28 28

Cost of Unit Train Facilities Attributed to Cellulosic Distillate Fuel/Renewable Diesel Fuel Transport 13 8 NA

4.2.2.1.5 Barge Receipt Facility Costs for Ce llulosic Distillate Fuel/Renewable Diesel Fuel

Our estimation of the number of barge receipt facilities for intra-U. S. biofuel shipments that will be needed to support the transport of the volumes of ethanol and cellulosic distillate fuel/renewable diesel fuel that we project will be used to meet the RFS2 standards is discussed in Section 1.6.5 of this RIA. The cost of these f acilities was divided betwee n ethanol and cellulosic distillate fuel/renewable diesel fuel in propor tion to the fraction of the total ethanol plus cellulosic distillate fuel/renewable diesel fuel volume. Our projections of the total cost of the ba rge receipt facilities and the portion that we attributed to the volume of cellulosic distillate fuel/renewable diesel fuel that we project will be used to meet the RFS2 standards is presen ted in Tables 4.2-34 and 4.2-35. See Section 4.2.1.1.5 of this RIA for additional discussion of the derivation of these estimates.87 Table 4.2-34. Cost of Barge Receipt Facilities under the RFS2 Control Scenarios Relative to the AEO Reference Case

Capital Cost (Million $) Low-Ethanol Scenario Mid-Ethanol Scenario High-Ethanol Scenario Total Cost of Barge Receipt Facilities Needed for the Transport of Ethanol and Cellulosic Distillate Fuel/Renewable Diesel Fuel 143 143 143

Cost of Barge Receipt Facilities Attributed to Cellulosic Distillate Fuel/Renewable Diesel Fuel Transport 87 56 NATable 4.2-35. Cost of Barge Receipt Facilities under the RFS2 Control Scenarios Relative to the RFS1 Reference Case

Capital Cost (Million $) Low-Ethanol Scenario Mid-Ethanol Scenario High-Ethanol Scenario Total Cost of Barge Receipt Facilities Needed for the Transport of Ethanol and Cellulosic Distillate Fuel/Renewable Diesel Fuel 185 185 185

Cost of Barge Receipt Facilities Attributed to Cellulosic Distillate Fuel/Renewable Diesel Fuel Transport 67 46 NA

4.2.2.1.6 Cellulosic Distillate Fue l/Renewable Diesel Fuel Rail Car Capital Costs

Our estimation of the number of rail cars needed to transport the additional volume of cellulosic distillate fuel/renewable diesel fuel that we project will be used to meet the RFS2 standards is discussed in Sec tion 1.6.4 of this RIA. Based on input from rail car manufactures, we estimate that the cost of a new 30,000 gall on rail car suitable for ethanol service is $90 thousand. We used this estimate as the cost of a rail car suitable for cellulosic distillate fuel/renewable diesel fuel service. This may tend to overstate the cost of such rail cars given that ethanol rail cars need to be cons tructed of ethanol tole rant materials. The cost of the additional cellulosic distillate fuel/renewable diesel fuel rail cars needed under the 3 control scenarios is presented in Table 4.2-36. Our estimate of the additional number of cellulosic distillate fuel/renewable diesel fuel rail cars needed to support meeting the RFS2 standards is the same relative to both reference cases.

Table 4.2-36. Cost of Additional Cellulosic Distillate Fuel/Renewable Diesel Fuel Rail Cars under the RFS2 Control Scenarios

Low-Ethanol Scenario Mid-Ethanol Scenario High-Ethanol Scenario Number of Additional Rail Cars 8,710 6,130 NA Rail Car Cost ($Million) $784 $552 NA89 4.2.2.1.7 Cellulosic Distillate Fuel/Renewable Diesel Fuel Barge Capital Costs

Our estimation of the number of barges needed for intra-U.S. transport of the additional volume of cellulosic distillate fuel/renewable diesel fuel that we project will be used to meet the RFS2 standards is discussed in Section 1.6.5 of this RIA. Based on input from fuel barge manufactures, we estimate that the cost of a ne w 10,000 barrel barge suitable for ethanol service is $1.4 million. We used this estimate as the cost of a barge suitable for cellulosic distillate fuel/renewable diesel fuel service. This may tend to overstate the cost of such barges given that ethanol barges need to be constr ucted of ethanol tolera nt materials. The cost of the additional cellulosic distillate fuel/renewable diesel fuel barges needed under the 3 control scenarios is presented in Table 4.2-37. Our estimate of the additional number of cellulosic distillate fuel/renewable diesel fuel barges needed to support meeting the RFS2 standards is the same relative to both reference cases.

Table 4.2-37. Cost of Additional Cellulosic Distillate Fuel/Renewable Diesel Fuel Barges under the RFS2 Control Scenarios

Low-Ethanol Scenario Mid-Ethanol Scenario High-Ethanol Scenario Number of Additional Barges 33 24 NA Cost of Barges ($Million) $47 $33 NA

4.2.2.1.8 Cellulosic Distillate Fuel/Renewable Diesel Fuel Tank Truck Capital Costs

Our estimation of the number of tank trucks needed to transport the additional volume of cellulosic distillate fuel/renewable diesel fuel that we project will be used to meet the RFS2 standards is discussed in Sec tion 1.6.6 of this RIA. Based on input from ethanol tank truck manufactures, we estimate that the cost of a new 8,000 gallon tank truck suitable for ethanol service is $180 thousand. We used this estimate as the cost of a tank truck suitable for cellulosic distillate fuel/renewable diesel fuel service. This may tend to overstate the cost of such tank trucks given that ethanol tank trucks need to be constructed of ethanol tolerant materials. The cost of the additional cellulosic distillate fuel/renewable diesel fuel tank trucks needed under the 3 control scenarios is presented in Table 4.2- 38. Our estimate of th e additional number of cellulosic distillate fuel/renewable diesel fuel tank trucks needed to support meeting the RFS2 standards is the same relative to both reference cases.Table 4.2-38. Cost of Additional Cellulosic Distillate Fuel/Renewable Diesel Fuel Tank Trucks under the RFS2 Control Scenarios

Low-Ethanol Scenario Mid-Ethanol Scenario High-Ethanol Scenario Number of Additional Tank Trucks 500 350 NA Cost of Tank Trucks ($Million) $90 $63 NA

4.2.2.2 Cellulosic Distillate Fuel Freight Costs

We used a study conducted by Oakridge National Laboratories (ORNL) to estimate ethanol and cellulosic distillate fu el/renewable diesel fuel freigh t costs. Refer to Section 4.2.1.2 of this RIA for a discussion of how these costs were derived. We estimate that cellulosic distillate fuel/renewable diesel fuel freight costs will be 13 cents per gallon under both the lowethanol and mid-ethanol scenarios.

4.2.3 Biodiesel Dist ribution Costs

As discussed in the following sections, we estimate that the total capital costs in the U.S to support distribution of the additional volume of bi odiesel that we project will be used to meet the RFS2 standards will be 1,141 billion dollars relative to the AEO 2007 reference case and 1,212 billion dollars relative to the RFS1 reference case. 22 When amortized, this translates to 10 cents per gallon of additional biodiesel volume that we project will be used to meet the RFS2 standards relative to both reference cases. Am ortization of capital costs was done over 15 years at a 7% annual cost of capital except in the cas e of the cost of tank trucks where a 10 year amortization schedule was used. We project that 1.67 BGY of biodiesel will be used by 2022 to meet the RFS2 standard volumes. Under the AE O reference case 380 BG/yr of biodiesel will be used by 2022. Under the RFS1 reference case, 300 BG/yr of biodiesel will be used by 2022. Thus, the additional amount of biodiesel that w ill be used by 2022 to meet the RFS2 standard volumes is 1,290 BG/yr relative to the AEO reference case and 1,370 BG/yr relative to the RFS1 reference case. Biodiesel freight costs are estimated to be 10 cents per gallon on a national average basis. Thus, we estimate that biodiesel distribution costs will be 20 cents per gallon of biodiesel that we project will be used to meet the RFS2 standards. 23

The biodiesel distribution capital and freight costs relative to the 2 reference cases that we evaluated in this FRM are summarized in Ta ble 4.2-39. The itemized biodiesel capital costs are presented in Table 4.2-40. The way in wh ich we estimated these costs is detailed in the following sections.

22 Biodiesel distribution costs do not vary under the th ree control scenarios evaluated in this final rule.

23 As noted previously, we chose not to subtract the distribution costs for the petroleum-based fuels that will be displaced by the use of biofuels from our estimated biofuel distribution costs. We believe that the freight costs to ship petroleum-based fuels to the terminal are approximately 4 cents per gallon. If we were to subtract these costs from the estimated biodiesel distribution, the result would be 16 cents per gallon.91 Table 4.2-39. Summary of Estimated Biodiesel Capital and Freight Costs for the RFS2 Control Scenario Relative to the Reference Cases

RFS1 Reference AEO Reference Billion $ Capital 1,212 1,141

Capital Costs (cpg) 10 10

Freight Costs (cpg) 10 10

Total Distribution Costs (cpg) 20 20

Table 4.2-40. Summary of Estimated Biodiesel Distribution Capital Costs for the RFS2 Control Scenario Relative to the Reference Cases

Capital Costs (Million$) RFS1 Reference AEO Reference Rail Cars 111 105 Barges 53 50 Tank Trucks 25 24 Storage Tanks at Petroleum Terminals 411 387 Blending and other Miscellaneous Equipment at Petroleum Terminals 612 576

Total (Million $) 1,212 1,141 Total (cpg) 10 104.2.3.1 Capital Costs to Upgrade the Biodiesel Distri bution System

4.2.3.1.1 Petroleum Terminal Biodiese l Distribution Capital Costs

The terminal facility modifications needed to support the use of the volume of biodiesel that we project will be used to meet the RFS2 standards are discussed in Section 1.6.7. Total capital costs at terminals by 2022 are estimate d at $963 million relative to the AEO reference case and $1,023 million relative to the RFS1 reference case.

We estimate that a total of 5.5 million barrels of new biodiesel storage will be needed at petroleum terminals to facilitate meeting the projected RFS2 biodiesel volume relative to the AEO reference case, and 5.9 million barrels relative to the RFS1 reference case. We assumed that all of the additional biodiesel storage w ill be satisfied by new construction. Based on information from industry, we estimate that the co st of constructing new biodiesel storage tanks would be 70 dollars per barrel of capacity. This is considerably higher than the 40 per barrel cost we estimated for construction of new ethanol tanks for two reasons. Biodiesel tanks need to be heated/insulated in colder climes and they tend to be of considerably smaller size compared to ethanol tanks. Both of these factors contribute si gnificantly to the cost pe r barrel of constructing a new storage tank. We estimate that the total cost at petroleum ter minals of new biodiesel storage tanks would be $387 million dollars rela tive to the AEO reference case and $411 million relative to the RFS1 reference case.

We projected that 600 additional petroleum terminals will need to install biodiesel blending equipment by 2022 to facilitate meeting the RFS2 biodi esel volume relative to the AEO reference case and 637 relative to the RFS1 refe rence case. Based on input from industry, we estimated that the cost of biodiesel blendi ng equipment will be 400 thousand dollars per terminal. The cost of additional piping is estimated at 60,000 per termin al. Ancillary costs associated with receiving/blending/storing bi odiesel are estimated at 500 thousand dollars per terminal. 24 Based on the above, the cost of additiona l biodiesel blending and other miscellaneous biodiesel handling equipment at terminals is estimated at $576 million relative to the AEO reference case, and $612 million relative to the RFS1 reference case. Estimated equipment costs for handling biodiesel are higher than those for similar equipment designed to handle ethanol due to the need for insulated/heated equipment in colder climes.

4.2.3.1.2 Biodiesel Rail Car Capital Costs

As discussed in Section 1.64 of this RIA, we estimate that an additional 1,060 rail cars will be needed by 2022 to facilitate transport of the volume of biodi esel that we project will be used to meet the RFS2 standards relative to the AEO reference case, and 1,120 relative to the RFS1 reference case. Based on input from industry, we estimate that the cost of a new biodiesel tank car of 25,600 gallon capacity is $99,000. The estima ted cost for a biodiesel rail car is 10% higher than that of an ethanol rail car to accommodate the need for insulated/heated tanks in colder climes. Thus, we estimate that the cost of the biodiesel rail tanks cars needed by 2022 to facilitate transport of the volume of biodiesel that we project will be used to meet the RFS2

24 This includes the installation of biodiesel truck receipt facilities, quality control testing equipment, and other ancillary equipment at terminals.93 standards would be $105 million relative to the AE O reference case, and $111 million relative to the RFS1 reference case.

4.2.3.1.3 Biodiesel Barge Capital Costs

As discussed in Section 1.65 of this RIA, we estimate that an add itional 32 barges will be needed by 2022 to facilitate transport of the volume of biodiesel that we project will be used to meet the RFS2 standards relative to the AEO reference case, and 34 relative to the RFS1 reference case. Based on input from industry, we estimate that the cost of a new biodiesel barge of 10,000 bbl capacity is $1.54 million. The estimated cost for a biodiesel barge is 10% higher than that of an ethanol rail car to accomm odate the need for insulated/heated storage compartments in colder climes. Thus, we estimate that the cost of the biodiesel barges needed by 2022 to facilitate transport of the volume of biodiesel that we proj ect will be used to meet the RFS2 standards would be $49 million relative to the AEO reference case, and $52 million relative to the RFS1 reference case.

4.2.3.1.4 Biodiesel Tank Truck Capital Costs

As discussed in Section 1.66 of this RIA, we estimate that an add itional 120 tank trucks will be needed by 2022 to facilitate transport of the volume of biodi esel that we project will be used to meet the RFS2 standards relative to the AEO reference case, and 130 relative to the RFS1 reference case. Based on input from industry, we estimate that the cost of a new biodiesel tank truck of 8,000 gallon capacity is $198,000. This is based on an 110,000 dollar cost for the tractor and an 88,000 thousand dollar cost for the tank trailer. This estimate is 25% higher than the cost of a tank trailer designed to transport et hanol due to the need for an insulated/heated tank in colder climes. Based on the above, we estimate that the cost of the biodiesel tank trucks needed by 2022 to facilitate transport of the volume of biodiesel that we project will be used to meet the RFS2 standards would be $23 million relative to the AEO reference case, and $25 million relative to the RFS1 reference case.

4.2.3.2 Biodiesel Freight Costs

Our analysis of biodiesel fre ight costs for this FRM draws upon the analysis conducted for the NPRM. The NPRM analysis was base d on a total biodiesel production volume of 810 million gallons by 2022 and was conducted relative to the AEO reference case under which 380 million gallons of biodiesel would be used. For the FRM, we are assuming that 1,670 million gallons of biodiesel would be used by 2022. Th e biodiesel capital cost analysis was conducted relative both the AEO and RFS1 reference case s. Under the RFS1 reference case 300 million gallons of biodiesel would be used by 2022 compared to the 380 million gallons under the AEO reference case. We believe that the difference be tween to the two reference cases is sufficiently small (80 million gallons per year by 2022) so that a single analysis of biodiesel freight costs conducted relative to the AEO reference case pr ovides a reasonable estimate relative to both reference case. Hence, we used the results of our biodiesel freight cost analysis under the AEO reference case for the RFS1 reference case as well.Our estimation of biodiesel freight costs for the NPRM was based on our evaluation of where biodiesel would be produced and the potential biodiesel de mand centers. Our projections of where biodiesel would be produced and used un der the NPRM analysis is contained in Section 1.8.2 of this RIA. Our projections of where bi odiesel will be produced under the final rule (FRM) analysis are contained in Section 1.5.4 of this RIA. The NPRM estimate of where biodiesel would be used was used in our final rule analysis. Due to time constraints, we used a modified NPRM biodiesel freight cost analysis (which a ssumes the same pr oduction and demand centers used in the NPRM) to estimate biodiesel freight costs for this final rule. This analysis is described below. Our comparison of project ed biodiesel production centers under the NPRM and FRM analyses relative to the projected demand centers indicates that the biodiesel transportation modes and distances are substantially similar. As a result, the freight cost estimates should be similar.

The distribution of biodiesel from producti on plants to petroleum terminals where it would be blended with diesel fu el is discussed in Section 1.6.2 of this RIA. Tank truck was the assumed method of shipment for distances of less than 300 miles. Where distances are longer than 300 miles, shipment by manife st rail was assumed to be the preferred option other than in cases on the East coast where there were appa rent barge routes from production to demand centers. Biodiesel that could not be consumed in the state where it was produced to meet State level biodiesel mandates, demand for biodiesel use in heating o il, or other project ed biodiesel use in diesel fuel was assumed to be shipped to market by manifest rail. 25 A 1,000 mile shipping distance was selected to ensure that all biodiesel not used to satisfy a state mandate, otherwise used in state, or used for bio-heat could find a market.

Our estimates of the freight costs for shipping biodiesel by tank truck are based on the ethanol tank truck freight costs that we developed for the RFS1 final rule. These ethanol transport costs were increased by 10% to acc ount for the increased co st associated with preventing fuel gelling during cold conditions. The cost of shipping biodiesel by truck when the trip (or multiple trips) could be completed in a day was estimated to range from 7 to 8 cents per gallon. Some long truck trans ports were assumed to be neces sary (up to 300 miles), where a round trip could not be completed in a single day. In such cases, the need for an overnight layover was assumed to add 120 dollars to shippi ng costs, resulting in an estimated 9.5 cents per gallon freight cost.

Our estimate of the cost of shipping biodiesel by manifest rail cars is based on publicly available biodiesel freight tariff information from BNSF railway from February 2008. lxxvi Specific tariff information was not available for source/destinations needed for our analysis. A minimum cost of 9 cents per gallon was assume d to accommodate loading, unloading, and rail car lease costs. Based on the BNSF tariff information, we estimated that every 100 miles of additional shipment by manifest rail car beyond 600 miles adds 1.4 cents per gallon to shipping cost. Thus, for the assumed 1,000 mile shippi ng distance for biodies el used to meet miscellaneous demand (i.e. not used to meet state mandates or for bioheat) the cost to ship by manifest rail car was estimated at 15 cents per gall on. Barge shipping costs were assumed to be comparable to the cost of shipping by manifest rail. This will tend to overstate barge shipping

25 Biodiesel is projected to be blended into most heating oil used in the Northeast by 2022. The blended product is commonly referred to as bioheat.95 costs, since we understand that barge freight cost s tend to be significantly less than rail freight costs. However, given the small fraction of biodi esel is projected to me moved by barge, this will have only a minimal effect on our overall estimation of biodiesel freight costs. Shipping distances were estimated based on a review of biodiesel production plant locations, demand centers, and the rail/barge transportation net. 26

Considering the location of biodiesel plan ts and biodiesel demand centers, 86% of biodiesel was projected to be shipped by truck, 13% was estimated to be shipped by manifest rail car, and 1% was estimated to be shipped by barge. We project that approximately 44% of the biodiesel production volume in 2022 would be used in the state where it was produced to meet state mandates, satisfy the demand for bioheat, or to meet other in-sta te miscellaneous demand. The average cost of shipping this volume by tank truck is estimated to average 8 cents per gallon. Approximately 3% of biodiesel production volume is estimated to be sh ipped out-of-state by manifest rail car to meet miscella neous biodiesel demand at an av erage freight cost of 16 cents per gallon. Approximately 54% of biodiesel production is projected to be shipped out of state to satisfy state mandates or bioheat demand which could not be satis fied with in-state production. We assigned portions of the production volumes from states that had already satisfied this demand to meet this demand in other states ba sed on minimizing overall shipping distances (and costs).

A freight cost estimate was derived based on the fraction of the volumes that would be shipped by each mode and the freight cost for each mode used given the shipping distance. On average the cost of shipping biodi esel from out-of-state to satisfy state biodiesel mandates or the demand for bioheat is estimated at 10 cents per ga llon. By weighting the biodiesel volumes used to satisfy the three demand categories by the respective freight cost to ship that volume we arrived at a national average bi odiesel freight cost estimate of 10 cents per gallon. Biodiesel freight costs are summarized in Table 4.2-41.

Table 4.2-41. Estimated Biodiesel Freight Costs for the RFS2 Control Case

Biodiesel Demand Category Fraction of Biodiesel Production Freight Cost (cpg) Shipped In-State to Satis fy In-State Demand 43% 8 Shipped Out-of-State to Satisfy State Mandates and Demand for Bioheat 54% 11

Shipped Out-of-State to Satisfy Miscellaneous Demand 3% 16

Total (National Average) 100% 10

26 See Section 1.8.2 of this RIA.4.2.4 Potential Fuel Retail Costs to Fac ilitate the Use of Mid-Level Ethanol Blends

As discussed in Section 1.6.10 of this RIA, our preliminary projections regarding the potential costs to the fuel distribution system are based on the premise that the facility changes needed would be limited to retail facilities. There may be additional costs upstream of retail facilities if separate gasoline blendstocks are needed to blend E10 and E15.

Testing is still underway regarding what chan ges might be needed to retail fuel storage and dispensing equipment originally designed to handle E10 to ensure its compatibility for an E15 blend. Thus there is considerable uncertain ty regarding the potential costs. Ideally, E15 could be dispensed and stored in existing reta il equipment with no physical modifications. However, it seems most prudent to assume that the potential changes might range from the replacement of hanging hardware (hoses attached to the dispenser and the nozzles), to the replacement of dispensers with E85 compatible equipment, and/or to the modification to underground piping which connects the dispenser to the underground storage tanks. There may also be the need to replace the underground storag e tanks themselves at some facilities. Some newer facilities might need to make fewer changes, while older facilities may require more extensive modifications.

We evaluated 3 cost scenarios regarding the potential modifications needed to ensure the compatibility of current retail fuel storage and di spensing facilities to handle E15. Under the first scenario, each retail facility would need to replace only the hanging hardware on the pumps which dispense gasoline. The National Associ ation of Convenience St ores (NACS) estimates that there are 3.9 gasoline refueling di spensers on average at retail facilities. lxxvii The National Petroleum News (NPN) estimate s that there were 161,768 retail facilities in the U.S. in 2008. lxxviii Thus, we estimate that there are appr oximately 631,000 gasoline dispensers at retail facilities. Information from fuel retailers indicates that the cost of hanging hardware that is compatible with E85 is $750 for the 2 hoses and nozzles needed for a single dispenser. We choose to use the cost for E85-compatible hard ware because there is no information on whether there may be lower costs for E15-compatible equipment. 27 We assumed a $25 installation cost per dispenser. Assuming that the hanging hard ware on all gasoline dispensers would need to replaced, the resulting cost would be $127 million. However, a significant fraction of this cost might be deferred to the extent that hanging hardware could be replaced on a timetable that is consistent with the normal ma intenance schedule as the numbe r of E15 facilities ramps up. Information from fuel retailers indicates that hanging hardware is typically replaced every 3 to 5

years.

Under the second scenario, the wetted component s inside fuel dispensers would need to be replaced in addition to the hanging hardware. 28 Information from fuel dispenser manufactures indicates that the cost of th e wetted fuel dispenser components is approximately $10,000. We assumed a $1,000 installation cost pe r dispenser. Fuel dispenser equipment installers indicated

27 Underwriters Laboratories has separate certification for E10, E25, and E85 retail dispensing equipment. No equipment has currently been certified for E25 or E85 use. However, there is considerable experience regarding the equipment suitable for E85 service.

28 The wetted components refers to the components inside the fuel dispenser which come into contact with the fuel.97 that the replacement of the wetted components in a fuel dispenser is not standard practice, and there may be logistical and administrative difficulties that would need to be overcome. The cost would be $6.940 billion, if assume th at the wetted components in all fuel dispensers would need to replaced. Adding the cost of replacing th e wetted dispenser components to the cost of replacing the hanging hardware, results in a total cost estimate of $7.067 billion.

Under the third scenario, a fraction of retail facilities would need to break concrete to modify underground components such as the piping between dispensers and storage tanks and the joints between piping and other underground components. This is the most speculative scenario given that the costs of modify ing underground components could vary greatly depending on the extent of the m odifications that might be needed. We assumed an average cost of $25,000 per facility to make the changes needed to underground facilities. We believe that this is a low-end estimate given that the cost of modifications to underground retail fuel storage facilities can escalate quickly. We assumed that 50% of all retail facilities would need to make such changes for a total cost of $2.022 billion. Adding in the cost of replacing the wetted dispenser components and cost of replacing the ha nging hardware, results in a total cost estimate of $9.089 billion.

These cost estimates could be altered significantly as a result of the findings of the test programs currently underway regarding the compa tibility of existing fuel retail equipment with E15. As discussed in Section 1.6.10 of this RIA, there may be difficulties in identifying what changes are needed at some retail facilities due to a lack of records on the type of equipment currently installed. This may limit the ability to make such retail facilities E15 compatible.



### 4.3 Reduced U.S. Refining Demand

As renewable and alternative fuel use incr eases, the volume of petroleum-based products, such has gasoline and diesel fuel produced by U.S. refineries, would decrease. This reduction in finished refinery petroleum products results in reduced refinery industry costs. The reduced costs would essentially be the volume of fuel displaced multiplied by the cost for producing the fuel. There is also a reduction in capital costs as investment in new refinery capacity is displaced by investments in renewable and alternative fuels capacity.

Although we conducted refine ry modeling for estimating the cost of blending ethanol (see Section 4.4), we did not rely on the refine ry model results for estimating the volume of displaced petroleum as other ec onomic factors also come into play. Instead we conducted an energy balance around the increased use of rene wable fuels, estimating the energy-equivalent volume of gasoline or diesel fuel displaced. This allowed us to more easily apply our best estimates for how much of the petroleum would displace imports of finished products versus crude oil for our energy security analysis whic h is discussed in Section 5.2 of the RIA.

As part of this petroleum displacement analysis, we accounted for the change in petroleum demanded by upstream processes related to additiona l production of the renewable fuels as well as reduced production of petroleum fuels. For example, growing corn used for ethanol production requires the use of diesel fuel in tractors, which reduces the volume ofpetroleum displaced by the ethanol. Similarly, the refining of crude oil uses by-product hydrocarbons for heating within the refinery, ther efore the overall effect of reduced gasoline and diesel fuel consumption is actua lly greater because of the additional upstream effect. We used the lifecycle petroleum demand estimates provided for in the GREET model to account for the upstream consumption of petroleum for each of th e renewable and alternative fuels, as well as for gasoline and diesel fuel. Although there ma y be some renewable fuel used for upstream energy, we assumed that this entire volume is petroleum because the volume of renewable and alternative fuels is fixed by the RFS2 standard.

We assumed that a portion of the gasolin e displaced by ethanol would have been produced from domestic refineries causing reduced demand from US refineries, while the rest of the additional ethanol displaces imported gasoline or gasoline blendstocks which does not affect domestic refining sector costs. To estimate the portion of new etha nol which displaces US refinery production we relied on so me Markal refinery modeling conducted for us by DOE. The Markal refinery model models all the refinery sectors of the world and thus can do a fair job estimating how renewable fuels would impact imports of finished gasoline and gasoline blendstocks. The Markal refinery model estimated that 2/3rds of a reduction in petroleum gasoline demand would be met by a reduction in imported gasoline or gasoline blendstocks, while the other 1/3 rd would be met by reduced refining production by the US refining sector. In the case of biodiesel and renewable diesel, all of it is presumed to offset domestic diesel fuel production. For ethanol, biodiesel and renewable diesel, the amount of petroleum fuel displaced is estimated based on the relative energy contents of the renewable fuels to the fuels which they are displacing. The savings due to lower importe d gasoline and diesel fuel is accounted for in the energy security analys is contained in Section 5.2.

For estimating the U.S. refinery industry cost reductions, we multiplied the estimated volume of domestic gasoline and dies el fuel displaced by the projected wholesale price for each of these fuels in 2022, which are $3.42 per gallon for gasoline, and $3.83 per gallon for diesel fuel (see Section 4.4). For the volume of petrol eum displaced upstream, we valued it using the wholesale diesel fuel price. Table 4.3-1 shows the net volum etric impact on the petroleum portion of gasoline and diesel fuel demand, as we ll as the reduced refining industry costs for 2022.99 Table 4.3-1 Changes in U.S. Refinery Industry Volume s and Costs for the RFS2 Program in 2022 Relative to the AEO 2007 Reference Case (2007 dollars) Low Ethanol Case Primary Case (mid-ethanol case) High Ethanol Case

Bil Gals Bil $ Bil Gals Bil $ Bil Gals Bil $

Upstream Petroleum 0.34 1.3 0.34 1.3 0.33 1.3 Gasoline -0.9 -3.1 -2.0 -6.8 -4.4 -15.0 End Use Diesel Fuel -10.1 -38.7 -7.5 -28.7 -1.3 -5.0

Total -10.7 -40.5 -9.2 -34.2 -5.4 -18.7

For the primary control case, this analysis estimates that the RFS2 program would reduce the gasoline and diesel fuel production volume of US refineries by 9.2 billion gallons in 2022, which would reduce their production costs by $34 billion dollars. Accounting for all the petroleum displaced (domestic and foreign), th e RFS2 program is estimated to reduce gasoline and diesel fuel demand by 13.6 billion gallons.



### 4.4 Overall Costs to Gaso line and Diesel Fuel

The previous sections of this chapter have presented estimates of the cost of producing and distributing ethanol, biodiesel and renewable and cellulosic diesel fuel. In this section, we summarize the overall cost of the RFS 2 program by assessing the costs of using more renewable fuels in the transportation fuel supply. The an alysis was conducted in two steps. One step involved running a refinery model for estimating th e costs of blending and using more ethanol. 79

We used the Haverly Linear Programming (LP) model to conduct the refinery analysis. This model is widely used by the refining industry, consultants, engineering firms and government agencies to analyze refinery economics, refinery operations, fuel quality changes, refinery capital investments, environmental chan ges and demand changes. This Haverly model uses Jacobs’s Refining Process Technology Database to represent refining operations.

While the change in volumetric demand for petroleum-based diesel fuel was modeled with the Haverly refinery model, the modeling of the cost of blending and using cellulosic and renewable diesel fuel an d biodiesel on the overall cost of di esel fuel was estimated as a secondstep post-refinery modelling. Assessing the costs of blending of renewable diesel fuels postrefinery modeling inherently assumes that the renewable diesel fuels will be drop in replacements for petroleum-based di esel fuel. However, if the higher cetane values for cellulosic and renewable diesel fuel and bi odiesel can be taken advantage of by refiners in blending up diesel fuel, then our cost estimates are likely to be conservative. We provide a more detailed description about how we estimate d the costs of using cellulosic and renewable diesel fuel and biodiesel at the end of subsection 4.4.1.

4.4.1 Description of Cases Modeled and Methodology100 The fuels cost analysis was set up to analyze the volumes required by the RFS 2 as described in Section 1.2. Because of the uncer tainty in how cellulosic biofuel industry will develop over time, we assessed three different renewable fuels scenarios each of which totaled 36 billion gallons based on the energy equivalency of ethanol. The three cases represent a high quantity of cellulosic ethanol and a low amount of cellulosic diesel fuel, a low amount of cellulosic ethanol and a high amount of cellulosi c diesel, and a midpoint between these two cases which served as our primary control case. We also considered a small amount of biodiesel and renewable diesel as required under EISA.

The refinery modeling analysis analyzed the extent to which ethanol will be used in conventional gasoline and reformulated gasoline by region and the resulting effects on gasoline composition. The refining industry was modeled based on five aggregate complex refining regions, representing Petroleum Administration for Defense Districts (PADD) 1, 2, 3, 4 & 5 together minus California, and California se parately. All of the PADDS were modeled simultaneously together in the LP model which allowed the refinery model to most efficiently rebalance the regional gasoline production volumes in response to the addition of the renewable fuels. We conducted the refinery modeling analys is assuming that crude oil would be priced at about $51 per barrel and product prices were set based on this crude oil price. We adjusted the costs to reflect a crude oil price of $116 per ba rrel which is the reference crude oil price estimated by the Energy Information Administration (EIA) for its 2009 Annual Energy Outlook (AEO). 80

The fuels cost analysis was conducted in thr ee distinct steps which involved a base case, two reference cases and the three control cases.

4.4.1.1 Base Case

The first step involved the establishmen t of a 2004 base case which calibrated the refinery model against 2004 volumes, gasoline qua lity, and refinery capital in place. We chose 2004 because the following year, 2005, as well as the beginning of 2006, were affected by hurricanes and would not be representative of a typical year, and 2007 and 2008 were years of extreme crude oil price volatility which skews the price relationships between crude oil and gasoline and diesel fuel. Refinery unit capacities from the Oil and Gas Journal and Energy Information Administration (EIA), as well as refinery feedstock and product volumes from EIA data were entered into the refinery model. The refinery model was then run and the resulting gasoline quality compared and calibrated to actual gasoline quality data information from EPA’s Reformulated Gasoline data base.

4.4.1.2 Reference Cases

The reference cases are benchmark cases that serve as references to the control cases. Thus, the only difference between the control cases and the reference cases is that the control cases model the RFS 2 volumes of renewable fuels ve rsus lesser volumes in the reference cases. We established two reference cases. One repres ented the volumes of renewable fuels assumed for the RFS1 program. The second reference case represented the growth of renewable fuels by101 EIA’s 2007 Annual Energy Outlook (AEO). The volumes for both these cases are summarized in Section 1.2 above. Because the RFS2 fuel standard becomes fully implemented in 2022, we established our reference cases using the projecte d volumes of finished products in 2022. These projected volumes were based on the energy dema nd for gasoline and diesel fuel from the EIA’s AEO 2009. The projected volumes were used for establishing total fi nished product production which then led to refinery production levels for each PADD.

The refinery modeling was conducted using a projection of crude o il and product prices in 2022 that Jacobs made for the proposed rule making. The average price of crude oil was projected to be about $51 per barrel, although cr ude oil prices varied by PADD. Jacobs based the prices for refined products based on the histor ical price spreads of fuels between the PADDs, using information from EIA’s 2004 price inform ation tables, Platts, and AEO 2006. For the reference case as well as for the control cases, we assumed the same crude oil and product prices when conducting the refinery modeling work. The crude oil prices and summertime and wintertime prices for gasoline, diesel fuel and jet fuel used in the refinery modeling are summarized in Table 4.4-1.

Table 4.4-1. Crude Oil and Finished Produc t Prices used in Refinery Modeling PADD 1 PADD 2 PADD 3 PADD 4/5 CA excl. California

Crude Oil ($/bbl) Year-round Average 53.6 53.0 50.6 51.8 50.2

Summer 175.2 173.5 170.8 - 186.7 Reformulated Gasoline (c/gal) Winter 161.4 158.7 155.3 - 173.7

Summer 167.6 165.1 161.4 173.6 - Conventional Gasoline (c/gal) Winter 154.0 151.8 148.5 160.4 -

Summer 156.6 157.6 154.6 166.6 164.6 Diesel Fuel (c/gal) Winter 162.6 163.6 160.6 172.6 170.6 Summer 158.6 158.6 156.6 164.6 164.6 Jet Fuel (c/gal) Winter 156.6 156.6 154.6 162.6 162.6

However, AEO 2009 projected crude oil prices to be $116 bbl in 2022, which is much higher than those that Jacobs had estimated. After completing the refinery modeling, we adjusted the costs of using the renewable fu els post-refinery modeling using a methodology described below in Subsection 4.4.1.6.

We also modeled the implementation of several environmental programs that will have required changes in fuel quality by 2022, including the 30 ppm average gasoline sulfur standard, the 15 ppm cap standards on highway and nonroad di esel fuel and the Mobi le Source Air Toxics (MSAT) benzene standard. Although there may st ill be a small amount high sulfur diesel fuel, we assumed that all distillate fuel would be ultra low sulfur in compliance with the 15 ppm cap standard required by the highway and nonroad dies el fuel sulfur standards. We modeled the implementation of the 2005 Energy bill, which by rescinding the RFG oxygenate standard,102 resulted in the discontinued use of MTBE, and a la rge increase in the amount of ethanol blended into reformulated gasoline. 81 By using the AEO 2009 energy demand we also included the EISA Corporate Average Fuel Economy (CAFE) standard s that were mandated in EISA and modeled in AEO 2009. . 82 The assumed EISA vehicle CAFE standard as projected by EIA in AEO phases-in less aggressively than the EPA and NHTSA proposed greenhouse gas and CAFE standards. However, because both programs woul d be fully phased in by 2022, their net effects in 2022 would not be that different. So basing our refinery modeling analysis on the EISA CAFE standard versus the EPA/NHTSA proposed standard would not make a significant difference in our costs.

4.4.1.3 Control Cases

The third step in the refinery modeling analysis was to model the control cases. As stated above, we modeled three different control cases to capture the impacts of a range of different levels of cellulosic ethanol versus cellulosic diesel fuel. All three cases model increased volumes of corn ethanol, biodies el and renewable diesel fuel. Tables 1.2-1 through 1.2-3 in Section 1.2 of the RIA summarize the volumes mode led for the control cases. For the additional ethanol blended into the gasoline pool, a subs tantial portion of the additional ethanol was blended as E85. The cost and other implications of the control cases are compared to the reference cases to assess the costs of the prog ram. We ran these multiple cases to understand how costs change based on different levels of ce llulosic ethanol versus cellulosic diesel fuel.

The gasoline and diesel fuel product energy output for each control case modeled was maintained the same as that for the reference cases which modeled the energy demand of the AEO 2009. Thus, as the volumes of lower energy dense renewable fuels increased, the total volume of combined renewable and conventional fu els was increased to ma intain the same level of energy demand. Maintaining constant energy output assumes that vehicle miles traveled would remain the same between the various cases despite any change in gasoline and diesel fuel prices caused by the use of renewable fuels. In reality the increased use of renewable fuels may result in changes to fuel prices to consumers, either directly as estimated in this section, or indirectly by affecting world oil prices as disc ussed in Chapter 5, and changes in fuel prices would be expected to affect demand. However, our analysis was conducted in parallel without the ability to input the results of the other analys is. Furthermore, it is difficult to predict the impacts on fuel prices to consumers, especially in light of the federal tax subsidies which we attempted to account for in our analysis, and the many and diverse state tax subsidies which we did not attempt to account for. Maintaining c onstant fuel product energy output captures the capital cost differences between the cases. Table 4.4-3 below summarizes the volumes of gasoline and diesel fuel used for the two reference cases, the primary control case and the two other control cases. The gasoline volumes incl ude the volumes of renewable fuels, while the diesel fuel volumes do not since diesel fuel costs were estimated post refinery modelling.103 Table 4.4-2. Volumes of Gasoline and Diesel Fuel Used in Refinery Modeling (Billion Gallons/yr) RFS 1 Reference Case AEO 2007 Reference Case Low Ethanol Control

Case Mid-Ethanol Control

Case Primary

Case High Ethanol Control Case

Gasoline Volume (Gasoline and Ethanol) 136.3 138.2 139.6 141.1 144.7

Diesel Fuel

Volume (Diesel Only) 70.7 70.6 60.7 63.3 69.4

All the other fuel standards and ASTM fuel quality constraints modeled in the reference case described above are assumed to apply to the control case as well. The reference and control cases where modeled assuming that ethanol conventional gasoline blends are entitled to the current 1.0 psi RVP waiver during the summer (i .e., for all 9.0 RVP and many low RVP control programs) so as to correctly assess the use of butanes in summertime conventional gasoline. Reformulated gasoline (RFG), however, must meet the same volatility stan dard with or without ethanol, so the addition of ethanol into RFG forced the refinery model to remove the last of the butane and some pentanes to rebalance RVP. Wintertime conventi onal and reformulated gasoline are normally blended up to either the RVP or vapor/liquid ASTM limits so the addition of ethanol into the wintertime gasoline pools re sulted in the removal of light hydrocarbon compounds – normally butane. The crude oil and product prices for the control cases were the same as the reference cases. The capital investments made for the reference cases are not assumed to be sunk when the refinery model is assessing the economics for capital investments for the various control cases. Thus, the refinery model is free to optimize the capital investments made for each control case incremental to the base case. The control cases are run with capital costs evaluated at a 15 percent rate of return on investment (ROI) after taxes, but are then adjusted post-modeling to a 7 percent ROI before taxes.

4.4.1.4 Ethanol Blending and Prices

A special procedure was set up in the refine ry model to capture the costs of blending ethanol. Because ethanol is primarily produced in the Midwest, but distributed to the final terminals where it is blended with the gasoline (or gasoline blendstock for blending with ethanol), hypothetical terminals were set up in each PADD with in the refinery model which would receive the shipped ethanol as well as the gasoline blendstock for blending with ethanol (also referred to as conventional blendstock for oxygenate blending (CBOB) for conventional gasoline and reformulated blendstock for ox ygenate blending (RBOB) for RFG and for California RFG (CARBOB). The gasoline blendstock either comes from the same PADD where the terminal is located, or transferred from a di fferent PADD. This refinery modeling technique helps to more correctly estimate the distribution costs for both the ethanol and the gasoline. The104 refinery model assessed ethanol’s use in each PADD based on its price relative to CG and RFG, which is based on its production co st and distribution costs, and its blending economics. For the base case we assumed that etha nol would be splash blended into gasoline. But for both the reference and control cases modeled in the year 2022 we expect that most, if not all, of the ethanol will be octa ne match-blended for blending up E10.

The price of ethanol used in the referenc e case and the primary control cases were based on the 2004 yearly average price spread between re gular conventional gasoline sold into the spot market in Houston and ethanol sold on the spot market on Chicago Board of Trade (CBOT). This price spread was 12.3 cents per gallon lowe r than gasoline in the summer, and 7.7 cents per gallon lower than gasoline in the winter. This worked out to an average ethanol price of 146.8 c/gal in the summer, and 139.4 in the summer. To derive ethanol prices for all the PADDs, the Midwest ethanol production price was then adjusted for transportation costs to deliver ethanol from the Midwest to end use terminals (see Section 4.2 for additiona l details about the distribution costs). This assumes that the Midwest ethanol market will continue to set the price for ethanol – a reasonable assumption consider ing the significant amount of corn and other biomass available in the Midwest. The sales prices assigned to ethanol are summarized in Table 4.4-4.

Table 4.4-3. Ethanol Prices used in Refinery Modeling (c/gal) PADD 1 PADD 2 PADD 3 PADD 4/5 CA excl. California

Summer 166.2 158.9 164.3 170.4 170.2 Winter 158.8 151.5 156.9 163.0 162.8

After the refinery modeling was completed, th e ethanol prices and the costs for each case were adjusted to reflect the et hanol production and distribution cost s described above in Sections 4.1 and 4.2. The ethanol production cost is the volume-weighted averag e for ethanol sourced from corn, cellulose and imports. The ethanol pr oduction and distribution cost and cellulosic and renewable diesel and bi odiesel costs for 2022 are shown in Table 4.4-4105 Table 4.4-4. Average 2022 Production a nd Distribution Costs for Ethanol, Biodiesel and Cellulosic and Renewable Diesel Fuels Production Cost (c/gal) Low Ethanol Case Primary Case Mid Ethanol Case High Ethanol Case

Distribution Cost Total Cost Distribution Cost Total Cost Distribution Cost Total Cost Corn Ethanol 150 23.2 173.2 21.6 171.6 18.8 168.8 Cellulosic Ethanol 127 23.2 150.2 21.6 148.6 18.8 145.8

Imported Ethanol 150 23.2 173.2 21.6 171.6 18.8 168.8

Biodiesel from virgin oils 273 20.0 293 20.0 293 20.0 293

Biodiesel from waste oil 243 20.0 263 20.0 263 20.0 263

Biodiesel from corn oil 190 20.0 210 20.0 210 20.0 210

Biodiesel from algae oil 452 20.0 472 20.0 472 20.0 472

Renewable Diesel Fuel from waste oil 242 15.7 257.7 15.4 257.4 14 256

Cellulosic diesel from BTL 237 15.7 252.7 15.4 252.4 14 251

The ethanol production and distribution costs summarized in Table 4.4-4 are different in value compared to the ethanol prices used in the refinery modeling summarized above in Table 4.4-3. To capture the costs of the RFS 2 program renewable fuel volumes, we adjusted the initial costs of the refinery modeling cost analysis us ing the ethanol production an d distribution costs. This cost adjustment was made by multiplying the difference in ethanol cost or price between Tables 4.4-4 and 4.4-3 by the difference in et hanol volume modeled betw een the control case and the reference case.

We also estimated the costs of the RFS 2 program renewable fuel volumes taking into account the consumption subsidies for corn ethano l, cellulosic ethanol, bi odiesel and renewable diesel fuel. While these subsidies conceal large portions of the costs of renewable fuels, their economic effects deserve to be understood.

4.4.1.5 E85 Blending and Prices

Today E85 is blended at 85 percent by volume in the summer and at 70 percent by volume in the winter. Ethanol mu st be blended at less than 85 pe rcent in the winter because of ethanol’s low blending Reid Va por Pressure (RVP). Unlike wh en ethanol is blended at 10 percent and causes a large vapor pressure increa se, when ethanol is blended at 85 percent it blends much closer to its very low neat ble nding RVP of 2.2. The denaturant provides a small106 RVP increase to the neat ethanol, however, the am ount of denaturant whic h may be blended into neat ethanol was recently limited to 2 percent. The lower denaturant volume limits the RVP increase that the denaturant will have on neat ethanol.

When ethanol is blended with gasoline at the terminal to make E85, the available gasoline blendstock must be used. Today this bl endstock is either a conventional blendstock for oxygenate blending (CBOB) or reformulated blendstock for ox ygenate blending (RBOB) used for blending E10 to the local gasoline specifica tions. For example, refo rmulated gasoline (RFG) must comply with the hydrocarbon standard of the RFG program and therefore RFG tends to have an RVP of 6.8, and the RBOB that is blende d with ethanol has an RVP of about 5.8. When this 5.8 RVP RBOB is blended with ethanol to make E85, its final RVP is estimated to be 4.72. However, the RVP minimum specified in the E85 ASTM standard shows the summertime lower limit of E85 is 5.5, thus, blending RBOB with 85 percent ethanol would not comply with the ASTM lower RVP standard. Ta ble 4.4-7 summarizes ethanol’s blending RVP, gasoline’s RVP and the final blend RVP for summertime RFG and CG gasoline, and compares the blends RVP values to that of the E85 ASTM RVP standards. 83

Table 4.4-5. Comparison of E85 RVP levels to the ASTM RVP Standard Summer E85 Winter E70 Gasoline RVP a CG 10.0 RFG & low RVP 6.8 ASTM Std CG/RFG 14 ASTM Std

Gasoline Blendstock RVP 9.0 5.8 13

Ethanol Blending RVP 4.37 4.37 - 6.1

Blend RVP 5.20 4.72 5.5 minimum 5.85 9.5 minimum

a Summertime CG is allowed a 1 psi waiver for blending with ethanol, however, RFG and some low RVP areas and wintertime CG/RFG do not normally receive 1 psi waivers.

Table 4.4-7 shows that summertime RFG a nd CG and wintertime gasoline cannot meet the ASTM RVP minimum standards based on ble nding ethanol with the locally available gasoline blendstock for blending up E10. For th is reason, we ran the refinery model assuming that E85 will be blended differently in the future than it is today if it is to be used in large volumes. We assumed in the refinery modeling that all E85 will be blended at 85 percent ethanol year-round by being blended with some butan es or pentanes (whichever is available from the nearest refineries) to bring E85 up to the maximum ASTM RVP standard for E85, in addition to the CBOB or RBOB being supplied to the local area. The maximum ASTM E85 RVP standard is 8.5 in the summertime and 12.0 in the wintertime.

E85 is expected to be priced much lower in the marketplace than E10 and even less relative to gasoline (E0) because of E85’s lo wer energy density. E85 contains about 77,900 BTUs per gallon compared to E10 which contains about 111,300 BTUs per gallon. Thus, when consumers consider refueling their vehicle using E85, they will bypass using it unless it is priced107 at parity with gasoline on an energy basis. Parity pricing means that E85 would have to be priced about 25 percent lower than E10. Assuming that E85 is priced 25 percent lower than E10 at retail to account for the energy content diff erences, the pricing disparity between ethanol and gasoline is even greater at the terminal. Tabl e 4.4-6 summarizes the prici ng of E85 at retail and at the terminal where ethanol is usually blende d with gasoline blendstock to create the E85. Retail markup averages about 10 cents per gallon. 84 Federal and state taxes average 46 cents per gallon (although this varies significantly by stat e), and transportation from the terminal to retail averages 3 cents per gallon. 85 Thus, if E10 gasoline is priced at 163 cents per gallon at the terminal, CC it would be priced at 222 cents per gallon at retail when the costs for transporting the fuel to the retail market and taxes and retail markup are adde d on. Based on E85’s 25 percent lower energy density, E85 would have to be pri ced at 167 cents per gallon at retail to reflect its lower energy density. Using the same terminal to retail costs/taxes, E85 would be priced at 108 cents per gallon at the terminal. All this is shown in Table 4.4-6. The bottom row of the table shows what ethanol (E100 plus denaturant) would ha ve to be priced at for terminals to breakeven using ethanol in E85 (this assumes that E85’s gaso line blendstock is priced the same as E10 at the terminal). Thus, unlike with E10 where th e lower energy content of ethanl is largely transparent to the consumer, based on ethanol’s en ergy content alone, ethanol used in E85 would have to be discounted significantly compared to ga soline for refiners to find it cost-effective to

use.

Table 4.4-6. E85 Pricing at Retail a nd at Terminals (cents per gallon) Price at Retail Retail Markup Average Federal and State Taxes Transportation terminal to retail Terminal Price

Gasoline E10 222 10 46 3 163 E85 167 10 46 3 108 Ethanol Breakeven Price - - - - 97

In addition to this effect of energy equi valency, Section 1.7 above outlines the difficulty of using all this E85 because of the relatively lo w number of fuel flexible vehicles (FFVs) that will be available to consume the fuel. The relatively low number of FFVs means that the refueling rate of these vehicles will have to be very high. In the year 2022, we estimate that FFVs will have to refuel 74 percent of the time to use the volume of ethanol required by the RFS2 standard. DD This means that E85 may have to be priced significantly lower than gasoline for FFV owners to choose to fuel on it instead of gasoline. In addition, it is unlikely that every service station would make the capital investments to make E85 available for sale. In Section 4.2, we estimate that one out of ve ry four service stations will carry E85. Thus, E85 may have to be priced even lower than its fuel economy-adjust ed price to entice FFV owners to refuel at a station carrying E85. To estimate the marginal lo wer price at which FFV owners would refuel at this high rate, we referenced an analysis based on a willingness to pay survey conducted by

CC The terminal price of 163 c/gal is the wholesale gasoline priced used in the refinery modeling analysis.

DD The FFV refueling percentage was estimated at 74% for the proposed rulemaking. Because the refinery modeling analysis was started before the FFV refueling percentage was reasessed for the final rulemaking, we continued to base our analysis on the 74% refueling figure.108 David Greene of the Oak Ridge National Laboratory. 86 The summary of this analysis is depicted in the Figure 4.4-1.

Figure 4.4-1



### Alternative Fuel Market Share as a Function of Fuel Availability and Price Advantage (David L. Greene, 1997, Figure 6)Refueling frequency given“reasonable access”

Percent of stations offering E85 in areas of the country with “reasonable access”, i.e., 25% $0.21/gal Price Advantage (1997$) X 

### Alternative Fuel Market Share as a Function of Fuel Availability and Price Advantage (David L. Greene, 1997, Figure 6)Refueling frequency given“reasonable access”

Percent of stations offering E85 in areas of the country with “reasonable access”, i.e., 25% $0.21/gal Price Advantage (1997$) X

Based on our estimates that E85 would have to be purchased 74 percent of the time and that one out of every four servi ce stations would carry E85, then Figure 4.4-1 estimates that E85 would have to be priced 21 cents per gallon lower than gasoline to match this availability and refueling scenario in addition to the adjustment for energy content. This cost estimate is based in 1997 dollars. Adjusting this cost estimate to 2006 do llars increases this estimate to 26 cents per gallon in addition to the adjustment for energy content.

There is one more factor which we believe could affect the price of E85. FFV owners who refuel on E85 will drive fewer miles before having to refuel compared to operating their vehicle on gasoline. The FFV drivers will therefore spend more time refueling their vehicle. As described above, FFV owners will drive 25 percent fewer miles per gallon and thus, will have to spend 25 percent more time refueling. We estim ate that each refueling event requires 6 minutes of time, and that a person’s time is worth an average of 30 dollars per hour. 87,88,89,90 Finally we assumed that a typical refueling volume for a refueling event is 15 gallons. Using these assumptions, the increased refueling frequency is costing the average FFV owner 5 cents per gallon more to use E85. To account for this additional cost, E85 would have to be priced 5 cents per gallon lower to make refueling FFVs a breakeven proposition. For our refinery modeling work, we reduced the refiner purchase price of E85 used in our refinery modeling analysis by this additional 5 cents per gallon.109 Table 4.4-7 summarizes the E85 refinery purchase prices at terminals by PADD used in our refinery modeling work. These prices repres ent the total of the energy content, the price adjustment for reduced fuel availability and the cost for increased refueling events. The E85 prices should be compared to regular grade ga soline because the FFVs generally only require regular grade gasoline when operated on gasoline.

Table 4.4-7. Wholesale E85 Prices used within the Refinery Model

E85 used in Conventional Gasoline Areas (c/gal) E85 used in Reformulated Gasoline Areas (c/gal) PADD 1 Summer 76 81 Winter 67 72 PADD 2 Summer 75 80 Winter 66 71 PADD 3 Summer 74 79 Winter 65 70 PADDs 4/5 Summer 84 80 Winter 75 81 CA Summer - 86 Winter - 77

While we used these E85 prices within the refinery model, they don’t necessarily represent the societal costs for using E85. The pricing to reflect reduced fuel availability, in particular, contains a significan t amount of transfer payments from the refining industry to consumers and other entities, and these transfer pa yments do not represent the true cost for using E85. EE

For estimating the program costs for using E85 (shown in Tables 4.4-12 and 4.4-13 and other similar tables), we adjust ed E85 price back up to 5 cents per gallon less than the gasoline price for each case (the additional time spent refuelin g is a true cost). We then used the relative energy density of the E85 to that of gasoline as reported by the refinery model (see energy content values in Table 4.4-19 a nd other similar tables) to account for the energy density costs for using E85. We preferred the energy content price cost made by the refinery model to our preliminary E85 energy content price adjustment s because the refinery model accounts for other changes in gasoline energy content made when accommodating the blending of ethanol . We are not assuming that the price adjustment that we made account for lower E85 availability accounts for any additional social cost. If the FFV driverwould have to drive out of his way from time-totime to find the E85, then there would be some extra cost associated with the lower availability. But most of the time FFV drivers would likely learn where to find E85 along the routes that they normally frequent, thus, no additi onal effort and cost would be incurred for refueling on E85. Thus, we assume that the lower E85 price to account for reduced E85 availability is purely a transfer payment from the refiner to the FFV owner. Despite assessing the costs on a different basis, estimating E85 prices for the refinery modeling is important so that the refinery model can

EE The possibility for this potentially large transfer payment associated with using ethanol in E85 would encourage obligated partners to pursue the development of nonethanol renewable fuels.110 correctly choose which gasoline type and which part of the country to blend the ethanol in the refinery model.

The assumption used here and throughout this proposed rulemaking is that ethanol’s fuel economy is directly proportional to its energy dens ity and its concentration in the fuel. Since the volumetric energy content of ethanol is approximately 33 pe rcent less than conventional gasoline, we assumed this loss in fuel economy proportional to its concen tration in the fuel. Some studies have suggested, however, that ethano l’s decrease in fuel economy may be less than its relative decrease in volumetric energy content of the fuel. In other words, there is less of a fuel consumption decrease than what the lower energy density of ethanol would suggest. However, the results may more be a function of how the testng was conducted than the true effect of ethanol on fuel economy. We therefore intend to investigate this issue more as more data becomes available.

As discussed above, we needed to adjust the estimated program costs from costs based on $51/barrel crude oil, the crude oil price at whic h the refinery model was run, to $116/bbl which is the crude oil costs that served as the basis for our cost analysis. To make these adjustments we estimated the wholesale gasoline and diesel fuel prices (which are the surrogate for the gasoline and diesel fuel production costs) at the adjusted crude oil price and compared these adjusted wholesale gasoline and diesel fuel adjusted pri ces to the baseline wholesale gasoline and diesel fuel prices. The baseline wholes ale gasoline and diesel fuel pr ices, based on an average $51/bbl crude oil price, are summarized in Table 4.4-1. To adjust these wholesale prices, we estimated how the price of crude oil will affect them. We conducted a regression between the annual average spot price of price of Western Texas In termediate crude oil and the annual average retail gasoline and diesel fuel prices for the years 2002 through 2008. 91,92 This regression is reflected in Table 4.4-8 as Gasoline Retail Price = Crude Oil Price multiplied times 2.65 plus 79.0, or Gasoline Retail Price = Crude Oil Price x “X” + “Y.” The slope “X” and intercept “Y” for this equation are summarized in Table 4.4-8. The X and Y factors for diesel fuel are also summarized in Table 4.4-8 as well. However, we needed to estimate the wholesale prices instead of the retail prices, so we adjusted the equations to estimate the wholesale price using the Jacob’s wholesale prices as the calibrating values. The regression, including the adjustment values to derive the wholesale prices equations are summarized in Table 4.4-8.

Table 4.4-8. Equations Used for Estimating Wholesale Average Gasoline and Diesel Fuel Prices* Equation for Retail Prices E quation for Wholesale Prices X Y X Adjusted Y Gasoline 2.65 79.0 2.65 +27.0 Diesel Fuel 3.38 44.8 3.38 -11.7 * The equation is used by multiplying the crude oil price ($/bbl) times the X and then adding Y to that product resulting in a gasoline or diesel fuel cost expressed in cents per gallon.

The equations were used to estimate the average wholesale gasoline and diesel fuel prices. These average wholesale gasoline and dies el fuel prices are summa rized in Table 4.4-9.111 Table 4.4-9 Average Gasoline and Diesel Fuel Wholesale Prices by Crude Oil Price Crude Oil Price Gasoline Diesel Fuel $/bbl c/gal c/gal

51 163 160 116 342 383

Table 4.4-9 shows the nationwide average cost s, but our cost analysis was conducted on a PADD basis, thus, it was necessary to estimate revised gasoline and diesel fuel wholesale prices in each PADD. This was accomplished by generating a ratio of the average wholesale gasoline and diesel fuel prices at the higher crude oil price relative to the average gasoline and diesel fuel wholesale prices at the lower crude oil price, and applying this ratio to the gasoline price in each PADD. It is important to point out one aspect of the gasoline and diesel fuel pricing changes captured by our crude oil/gasoline and diesel fuel price relationship price model. Prior to 2005, diesel fuel was priced about the same as gasoline (+/- 5 cents per gallon on a yearly average). In 2005 and 2006, when crude oil was priced higher, diesel fuel was priced 13 cents per gallon higher than gasoline. In 2007 gasoline and diesel fuel were priced about the same, but then in 2008, diesel fuel was priced much higher than gasoline. Thus, the equation picks up this relatively higher diesel fuel price at the higher crude oil prices in 2005, 2006 and 2008 and projects a greater relative higher price for diesel fuel at our high crude oil price of $116/bbl. A higher relative diesel fuel price at higher crude oil prices in the future may be appropriate for a couple reasons. The first reason is that from January to mid-October 2008, when crude oil prices were very high, diesel fuel averaged 51 cents pe r gallon higher than gasoline. While we cannot say for certain that this associa tion would always hold true at high er crude oil prices, we do have a possible explanation for a possible relationship here. Higher cr ude oil prices are likely to affect gasoline demand more than diesel fuel as more of the trips made by gasoline powered light-duty vehicles are discretionary. For example, people may readily change their vacations plans at higher crude oil prices, while diesel fuel used to power trucks that bring food to markets would be expected to continue. Thus, as crude oil pr ices increase, gasoline consumption is likely more elastic resulting in greater reductions in gasoline demand compared to diesel fuel. We therefore believe that higher crude oil prices will tend towards relatively higher diesel fuel prices compared to gasoline.

For other reasons, diesel fuel prices may tr end higher in the future relative to gasoline prices. Because EISA required that corporat e average fuel economy (CAFE) standards be increased for light duty motor vehicles, over time light duty vehicles, which are almost exclusively gasoline powered, will become more fuel efficient. This will cause gasoline demand to decrease, while diesel demand is projected to continue to increase with GDP to transport goods and services. A second r eason why refinery gasoline production will decrease is that most of the renewable fuel volume being produced to comply with the RFS will displace gasoline. This will contribute to the over supply of gasoline and the relative undersupply of diesel fuel, thus causing gasoline prices to be soft relative to diesel fuel prices.112 Another adjustment we made to the costs directly estimated by the LP refinery cost model was to add additional cost for distributing gasoline from the refinery to the terminal. The refinery cost model assigned a low distribution costs to gasoline for moving the gasoline from the refinery to the terminal. We estimate that this distribution cost s hould be about 4 cents per gallon, but the refinery model only assigned 2. 5 cents per gallon for this. Thus, we credited ethanol 1.5 cents per gallon for each gasoline-e quivalent gallon of etha nol blended into each PADD’s gasoline, since this roughly corresponded to the volume of gasoline displaced by the ethanol.

The diesel fuel costs are estimated based on two calcula tions conducted post-refinery modeling. The first calculation estimates costs based on the difference in the renewable fuels production costs compared to the production costs for petroleum-based diesel fuel multiplied times the increased volume of renewable fuels in the control case compared to the reference case. For example, producing and distributing cellulosic diesel fuel for the primary control case is estimated to cost 252 cents per ga llon (see Table 4.4-4). The cost of producing diesel fuel is estimated to be 383 cents per gallon when crude oil is priced at $116 per barr el (see Table 4.4-9), which is 131 cents per gallon higher than the cellulo sic diesel fuel costs. From the volume tables in Section 1.2, the incremental volume of cellulosic diesel fuel is 6.52 billion gallons for the primary reference relative to the AEO 2007 refere nce case. Therefore, the net production cost for cellulosic diesel fuel is -131 cents per gallon times 6.52 billion gallons for a cost of -8540 million dollars in 2022.

The second calculation for estimating the cellulo sic diesel fuel cost s is an estimate of the fuel economy cost. This is calculated by multiplying the percent loss in fuel economy for cellulosic diesel fuel compared to petroleum-based diesel fuel times the production cost for petroleum-based diesel fuel. Continuing with the cellulosic diesel fuel example, we assume that cellulosic diesel fuel is from the biomass-to -liquids (BTL) process and contains 123,000 BTUs per gallon versus petroleum diesel fuel which is estimated to contain 130,000 BTUs per gallon. Thus, cellulosic diesel fuel cont ains about 95% of the energy c ontent of petroleum-based dieselfuel. The 5% shortfall in energy content is multiplied times the production cost of petroleumbased diesel fuel, which is 383 cents per gallon, and multiplied times 6.52 billion gallons - the volume of cellulosic diesel fuel. This results in a cost of 1250 million dollars in 2022.

The total cost for cellulosic diesel fuel is the sum of the production cost and the fuel economy cost which is -7290 million dollars in 2022. The total annual cost is converted to a per-gallon cost by dividing the total annual co st by the total volume of petroleum-based and renewable diesel fuel.

4.4.1.6 Other Adjustments to the Costs

The assumed volumes of E85 in our control cases will require increased numbers of flexible fuel vehicles (FFVs) be available to use the fuel. In Section 1.7 above, we estimate the number of FFVs that would be produced to enable the consumption of the volume of E85 that we project would have to be consumed for each c ontrol case. As the number of FFVs increases it results in higher costs due to the production of FFVs. In the following tables, we resummarize113 the number of FFVs that we projected would be available for the AEO 2007 reference case and each control case that we described above in Secti on 1.7. However, to estimate the cost impacts, we attribute a cost for every FFV produced. For the low ethanol case, we assume that each FFV would cost $100 per vehicle, which is an estimat e for producing an FFV today. For the higher ethanol cases, as FFV production vol umes increase, because of ec onomies of scale, we expect that the per-vehicle costs would decrease. Furthermore, overhead costs associated with producing FFVs would be amortized over a larger number of vehicles further lowering the pervehicle costs. For the primary cas e we project that FFV costs would decrease to $75 per vehicle. For the high ethanol case we assume that FFV co sts would decrease to $50 per vehicle. Tables 4.4-10 and 4.4-11 provide estimates of the FFV co sts above the business-as-usual FFV costs in the AEO 2007 and RFS 1 reference cases.

Table 4.4-10 Numbers of FFVs and Total FFV Costs for the Control Cases Relative to the AEO 2007 Reference Case

AEO 2007 Reference Case

Number of FFVs (millions) Number of FFVs (millions) Incremental FFV Cost (millon dollars)

($100/FFV) Number of FFVs (millions) Incremental FFV Cost (millon dollars)

($75/FFV) Number of FFVs (millions) Incremental FFV Cost (millon dollars)

($50/FFV)

2010 1.67 1.25 -$41.7 1.85 $13.4 3.62 $97.4 2011 1.75 1.60 -$14.8 2.66 $68.6 5.44 $184.6 2012 1.77 1.90 $13.6 3.52 $131.6 7.39 $281.2 2013 1.80 2.25 $45.6 3.74 $145.9 9.42 $381.1 2014 1.83 2.52 $69.7 3.88 $154.1 11.40 $478.8 2015 1.82 2.69 $87.6 3.96 $160.5 13.29 $573.4 2016 1.82 2.76 $94.4 3.97 $161.3 13.32 $575.3 2017 1.83 2.80 $97.8 4.00 $163.3 13.44 $580.8 2018 1.83 2.93 $109.4 4.04 $165.6 13.57 $586.9 2019 1.86 2.83 $97.0 4.08 $167.2 13.71 $592.8 2020 1.90 2.77 $87.1 4.12 $166.3 13.82 $596.2 2021 1.91 2.67 $75.6 4.10 $163.9 13.76 $592.4 2022 1.91 2.61 $69.4 4.10 $163.7 13.75 $591.9 Totals 23.7 31.6 $791 48.0 $1,826 145.9 $6,113 High Ethanol Control Case Low Ethanol Control Case Primary Control Case (mid ethanol case)

Year

Table 4.4-10 summarizes our estimated cost s for the increased numbers of FFVs that would be produced to use the projected increased volume of E85. For the primary control case we estimate that increased FFV production would cost $1.8 billion. For the low and high ethanol control cases we estimate that increased FFV production would cost $0.8 and $6.1 billion, respectively.114 Table 4.4-11 Numbers of FFVs and Total FFV Costs for the Control Cases Relative to the RFS 1 Reference Case

RFS 1 Reference Case

Number of FFVs (millions) Number of FFVs (millions) Incremental FFV Cost (millon dollars)

($100/FFV) Number of FFVs (millions) Incremental FFV Cost (millon dollars) ($75/FFV) Number of FFVs (millions) Incremental FFV Cost (millon dollars) ($50/FFV)

2010 0.98 1.25 $27.0 1.85 $64.9 3.62 $131.7 2011 1.08 1.60 $51.5 2.66 $118.3 5.44 $217.8 2012 1.16 1.90 $74.1 3.52 $177.1 7.39 $311.5 2013 1.23 2.25 $101.7 3.74 $188.0 9.42 $409.2 2014 1.28 2.52 $124.2 3.88 $195.1 11.40 $506.1 2015 1.31 2.69 $138.7 3.96 $198.9 13.29 $599.0 2016 1.31 2.76 $145.2 3.97 $199.4 13.32 $600.7 2017 1.32 2.80 $148.3 4.00 $201.2 13.44 $606.0 2018 1.33 2.93 $159.5 4.04 $203.2 13.57 $612.0 2019 1.35 2.83 $147.8 4.08 $205.2 13.71 $618.2 2020 1.36 2.77 $141.2 4.12 $206.9 13.82 $623.2 2021 1.35 2.67 $131.7 4.10 $206.0 13.76 $620.5 2022 1.35 2.61 $125.6 4.10 $205.8 13.75 $620.0 Totals 16.4 31.6 $1,516 48.0 $2,370 145.9 $6,476 High Ethanol Control Case Low Ethanol Control Case Primary Control Case (mid ethanol case)

Year

Table 4.4-11 summarizes our estimated costs for the increased numbers of FFVs that would be produced to use the projected increased volume of E85. For the primary control case we estimate that increased FFV production would cost $2.4 billion. For the low and high ethanol control cases, we estimate that increased FFV production would cost $1.5 and $6.5 billion, respectively.

4.4.2 Refinery Modeling Results

In this subsection, we summarize the results of the three control cases that we modeled and compare them to the two different reference cases.

Table 4.4-12 summarizes the costs for the pr imary control case relative to the AEO 2007 reference case excluding federa l ethanol, biodiesel and renewabl e diesel tax subsidies. By excluding the federal ethanol, bi odiesel and renewable diesel fuel consumption subsidies, we avoid the transfer payments caused by these subsid ies that would hide a po rtion of the program’s costs. The costs are reported by different cost components and adjustments described above, as well as aggregated to show the total annual and per-gallon costs. The costs are reported separately for gasoline and diesel fuel. The estimate of gasoline costs are based on the refinery model and reflect the changes in gasoline that are estimated to occur by the refinery model accommodating the expanded use of ethanol. The refinery model variable operating costs include the labor, utility and other operating costs and are a direct output from the refinery model. These costs reflect ethanol’s and E85’s prices used in the refinery model and reflect115 crude oil priced at about $51 per barrel. The redu ced refinery capital costs are shown in the table amortized annually and over the gasoline pool (t he nonamortized refinery and biofuel capital costs are summarized in Table 4.4-18). The fixed costs shown in the table include the maintenance and insurance costs and are calculated to be 3 percent of the reduced capital costs. Next in the table we show the adjustment to remove the costs associated with low E85 prices, except for the 5 cent per gallon refueling cost, and then we show the costs for using lower energy density E10 gasoline and E85. The energy density costs changes rely on the fractional change in energy density shown in Table 4.4-19, multiplied by the wholesale price of gasoline. The cost adjustment is shown for basing the gasoline co sts on $116 per barrel crude oil price versus the $51 per barrel price that was the basis for the refi nery model runs. At $11 6 per barrel crude oil costs, ethanol’s production and di stribution costs are lower than the wholesale cost of gasoline which results in the cost savings. Finally for the gasoline costs, the table summarizes our estimated costs for producing an appropriate number of fuel flexib le vehicles (FFVs) for using E85. With respect to the cellulosic and renewa ble diesel fuel and biodi esel costs, the production costs and for the fuel economy effects ar e both presented in Table 4.4-12.

Table 4.4-12. Primary Control Case Costs without Tax Subsidies Relative to the AEO 2007 Reference Case (2007 dollars, 7% ROI before taxes) Gasoline Diesel Fuel Refinery Model Variable Operating Cost $MM/yr 11,077 - Amortized Refinery Capital Costs $MM/yr -997 - Fixed Operating Costs $MM/yr -275 - A dded Gasoline Transportation Cost $MM/yr -88 - E85 Pricing Effect $MM/yr -8,338 - Crude Oil Cost $51 to $116/bbl $MM/yr -15,302 - Lower Energy Density $MM/yr 8,745 1,722 A djustment from Ethanol Price to Cost $MM/yr 83 - FFV Costs $MM/yr 1,826 Renewable Diesel Cost vs Pe troleum Diesel $MM/yr - -10,268 Total Costs $MM/yr -3,349 -8,546 Refinery Model Variable Operating Cost c/gal 7.85 - A mortized Refinery Capital Costs c/gal -0.71 - Fixed Operating Costs c/gal -0.19 - A dded Gasoline Transportation Cost c/gal -0.06 - E85 Pricing Effect c/gal -5.91 - Crude Oil Cost $51 to $116/bbl c/gal -10.84 - Lower Energy Density c/gal 6.20 2.42 A djustment from Ethanol Price to Cost c/gal 0.06 - FFV Costs c/gal 1.29 Renewable Diesel Cost vs Pe troleum Diesel c/gal - -14.41 Total Costs c/gal -2.37 -11.99116 Our analysis shows that when considering all the costs associated with the expanded use of ethanol for the primary control case relative to the AEO 2007 reference case that the cost of gasoline will decrease by $3.3 billion in the year 2022. Expressed as per-gallon costs, these fuel changes will save the U.S. 2.4 cents per gallon of gasoline. The addition of biodiesel, renewable and cellulosic diesel fuel is estimated to reduce the cost of diesel fuel by $8.5 billion in the year 2022, or save 12.0 cents per gallon.

Table 4.4-13 expresses the tota l and per-gallon gasoline costs for the primary control case with the federal ethanol, biodies el and renewable diesel subsid ies included. The federal tax subsidy is 45 cents per gallon for each gallon of ethanol blended into gasoline and 101 cents per gallon for each gallon of cellulosic biofuel. Im ported ethanol is also assumed to receive the 45 cents per gallon ethanol subsidy, although we a ssume that a greater volume of imported ethanol would be used than that which can flow through the Caribbean Basin, tariff free. Thus the 51 cents per gallon tariff would apply to that in cremental volume of impor ted ethanol above the allowable Caribbean Basin initiative volume. We estimate that imported ethanol would earn 23 cents per gallon net subsidy. The biodiesel s ubsidy is 100 cents per gallon, and the renewable diesel fuel subsidy is 50 cents per gallon. The cost adjustment is estimated by multiplying the subsidy times the volume of new ethanol, biodiesel and renewable diesel estimated to be used.

Table 4.4-13. Primary Control Case Costs Reflecting Tax Subsidies Relative to the AEO 2007 Reference Case (2007 dollars, 7% ROI before taxes) Gasoline Diesel Fuel Total Costs $MM/yr -3,349 -8,546 Federal Subsidies $MM/yr -6,313 -7,944 Revised Total Cost $MM/yr -9663 -16,490 Total Costs c/gal -2.37 -11.99 Federal Subsidies c/gal -4.47 -11.15 Total Costs c/gal -6.85 -23.14

The cost including subsidies would represent gasoline and diesel fuel ’s apparent cost as reflected to the fuel industry as a whole because the federal tax subsidie s tends to transfer a portion of the actual costs to consumers through non-fuel taxes. Our analysis estimates that relative to the AEO 2007 reference case, the pr imary control case would cause a 6.9 cent per gallon decrease in the apparent cost of produc ing gasoline, and a 23.1 cent decrease in the apparent cost of producing diesel fuel. These costs would also represent the apparent cost to consumers “at the pump” if the full tax credit were passed along to the consumers. However, it is possible that only a portion of the tax subsidy will be passed along to the consumer (historically, this has been the case). Thus, the price impact at the pump may be somewhere between the values in Tables 4.4-12 and 4.4-13. However, consumers would also pay the full tax subsidy through higher taxes in addition to the values in Tables 4.4-13.

Table 4.4-14 summarizes the volumetric inputs to refineries in each PADD for the primary control case and provides the incremen tal difference relative to the AEO 2007 reference case. Because of the increased use of biofuels, petroleum inputs would be expected to decrease, and this is confirmed.117 Table 4.4-14. Summary of the Total and Incremental Vo lumetric Refinery Inputs by PADD for the Primary Control Case Relative to the AEO 2007 Reference Case (barrels/day)

Control Difference Control Difference Control Difference Control Difference Control Difference Case from Ref Case Case from Ref Case Case from Ref Case Case from Ref Case Case from Ref Case PADD Crude 1,246,981 -281,399 3,117,973 -340,516 7,056,501 -194,917 1,460,255 -73,349 1,865,224 -24,171 GTL Naphtha 0 0 0 0 0 0 0 0 0 0 GTL Diesel 0 0 0 0 0 0 0 0 0 0 VGO HS 0 0 0 0 0 -43,785 0 0 0 0 VGO LS 0 0 38,063 0 0 0 0 0 0 0 HS AR (A960) 0 0 0 0 0 0 0 0 0 0 LS AR (Alg) 290,427 60,773 0 0 732,497 26,283 0 0 0 0 Normal Butane 26,527 4,042 65,106 13,451 111,678 25,512 40,206 490 39,573 0 Isobutane 9,412 8,868 17,236 -6,556 25 25 19,001 12,735 0 0 Other 0 0 0 0 0 0 0 0 0 0 MTBE 0 0 0 0 0 0 0 0 0 0 Ethanol - E10 300,677 27,590 188,968 -8,932 155,813 -19,904 69,817 -573 145,656 2,998 Ethanol - E20 0 0 0 0 0 0 0 0 0 0 Ethanol - E85 243,490 243,490 111,243 111,243 212,446 212,446 17,420 17,420 0 0 Reformer Feed 0 0 0 0 0 0 0 0 0 0 Methanol 0 0 0 0 0 0 0 0 0 0 Natural Gas (FOE) 68,419 -12,688 135,263 -9,379 490,908 -13,379 87,228 -6,669 154,101 -1,567 Hydrogen (MSCF) 0 0 0 0 0 0 0 0 0 0 Pentanes Plus 0 0 32,124 0 52,055 0 18,580 0 0 0 Import CBOB 10% 148,371 142,085 0 0 0 0 0 0 0 0 Import CBOB 20% 0 0 0 0 0 0 0 0 0 0 Import RBOB 10% 65,943 -79,650 0 0 0 0 0 0 0 0 Import RBOB 20% 0 0 0 0 0 0 0 0 0 0 Import Alkylate 19,134 16,901 0 0 0 0 0 0 0 0 Import Raffinate 38,375 -15,151 0 0 0 0 0 0 45,808 0 Import Reformate 7,080 -1,749 0 0 0 0 0 0 0 0 Import FCC Naphtha 0 0 0 0 17,503 17,503 0 0 0 0 Import Lt Naphtha 0 0 0 0 0 0 0 0 584 0 Import Hvy Naph 0 0 0 0 41,644 0 0 0 0 0 Transfer Lt Naphtha 23,342 19,010 0 0 0 0 0 0 23,053 4,669 Transfer Reformate 17,226 569 0 0 0 0 0 0 0 0 Transfer Alkylate 59,431 -569 9,795 9,795 0 0 0 0 60,000 0 Transfer FCC Naphtha 0 0 20,822 0 0 0 0 0 0 0 Transfer Raffinate 0 0 784 -10,853 0 0 0 0 60,000 12,556 Transfer RBOB 10% 242,605 0 37,596 37,596 0 0 0 0 0 0 Transfer RBOB 20% 0 0 0 0 0 0 0 0 0 0 Transfer CBOB 10% 1,355,660 219,387 81,092 27,037 0 0 9,099 2,747 0 0 Transfer CBOB 20% 0 0 0 0 0 0 0 0 0 0 Isooctane 3,278 3,178 100 0 100 0 100 0 13,287 -1,975 Isooctene 17,071 16,971 100 0 100 0 100 0 2,461 1,861 PADD 4/5 ex CA CA PADD 1 PADD 2 PADD 3

Table 4.4-14 shows that inputs of crude oil de creases substantially in most of the PADDs. In all the PADDs the input of crude oil to refineries decreases, which is expected since renewable fuels will supplant the need for petroleum feedstocks. Imports of gasoline blendstocks into PADD 1 also decreases. Butane inputs increase due to its blending into E85.

Table 4.4-15 below summarizes the refinery output volumes and changes in refinery output volumes relative to the reference case by PADD.118 Table 4.4-15. Summary of Total and Incremental Refinery Outputs by PADD for the Primary Control Case Relative to the AEO 2007 Reference Case (barrels/day)

Control Difference Control Difference Control Difference Control Difference Control Difference Case from Ref Case Case from Ref Case Case from Ref Case Case from Ref Case Case from Ref Case Propane 30,305 -1,816 50,863 -6,424 100,460 -17,092 21,022 -1,481 52,834 1,242 Propylene 18,685 0 42,525 0 245,407 0 2,041 0 11,774 0 Normal Butane 0 -4,967 1,698 733 23,031 -10,632 0 0 0 0 Isobutane 0 0 0 0 0 -411 0 0 39,318 -2,172 PC Naphtha 15,830 0 40,290 0 432,937 0 0 0 0 0 PC Gasoil 0 0 502,059 -58,642 157,500 0 0 0 0 0 CG Reg 0 0 0 0 0 0 0 0 0 0 CG Prem 0 0 0 0 0 -182,001 0 0 0 0 CG E10 Reg 1,654,618 397,669 1,277,077 -100,639 850,572 -224,891 577,355 -8,008 96,902 1,992 CG E10 Prem 214,377 144,044 267,934 5,512 209,149 4,299 113,837 2,340 18,457 379 RFG E10 Reg 885,097 -271,021 273,652 5,624 405,579 19,731 0 0 1,114,370 22,903 RFG E10 Prem 222,613 2,400 52,124 1,071 77,253 3,758 0 0 212,261 4,363 CG E20 Reg 0 0 0 0 0 0 0 0 0 0 RFG E20 Reg 0 0 0 0 0 0 0 0 0 0 E85 to CG 0 0 129,577 129,577 247,459 247,459 20,291 20,291 0 0 E85 to RFG 283,619 283,619 0 0 0 0 0 0 0 0 Transfer RBOB 10% 0 0 0 0 280,201 37,596 0 0 0 0 Transfer RBOB 20% 0 0 0 0 0 0 0 0 0 0 Transfer CBOB 10% 0 0 0 0 1,445,851 249,171 0 0 0 0 Transfer CBOB 20% 0 0 0 0 0 0 0 0 0 0 Jet/Kero A (450ppm) 70,000 0 143,275 3,194 936,227 0 274,537 0 229,653 0 X-Fer Diesel Rundown 0 0 0 0 0 0 0 0 0 0 HSD Gr 76 (0.2%) 0 0 0 0 0 0 0 0 0 0 LSD Gr 74 (.05%) 0 0 0 0 0 0 0 0 0 0 ULSD (15 ppm) 505,645 -128,972 562,879 -109,292 2,011,680 -124,623 470,858 -62,441 0 0 CARB Diesel 0 0 0 0 0 0 0 0 326,650 -37,699 X-Fer C5's to Storage 0 0 0 0 0 0 0 0 0 0 1% Residual Fuel 0 0 0 0 0 0 0 0 0 0 Residual Fuel 50,000 -41,643 57,026 -7,562 262,834 0 126,642 4,352 49,880 0 Slurry 31,083 3,675 76,076 -10,192 108,692 -5,256 18,513 5,031 28,829 -178 A sphalt & Wax 91,682 0 198,329 -9,357 157,500 0 5,250 0 41,774 0 Gasoil 0 0 4,895 0 0 0 0 0 9,814 0 Lubes 18,706 0 17,313 0 157,500 0 0 0 20,149 0 Benzene 11,003 0 11,003 0 51,347 0 0 0 0 0 Toluene 0 0 0 0 34,910 0 0 0 0 0 Xylenes 0 0 0 0 7,777 0 0 0 0 0 Cumene 0 0 0 0 0 0 0 0 0 0 Other 0 0 0 0 0 0 0 0 0 0 Cyclohexane 0 0 0 0 0 0 0 0 0 0 Transfer Raffinate 0 0 0 0 60,784 1,703 0 0 0 0 Transfer Alkylate 0 0 0 0 129,226 9,226 0 0 0 0 Transfer Reformate 0 0 0 0 17,226 569 0 0 0 0 Transfer FCC naphtha 0 0 0 0 20,822 0 0 0 0 0 Transfer Lt Naphtha 0 0 0 0 23,342 19,010 0 0 23,053 4,669 Transfer Blendstock 0 0 0 0 0 0 0 0 0 0 Sulfur (STons) 1,008 -146 3,676 -438 11,971 -427 1,925 -162 3,504 -42 Coke (STon) 2,913 -1,037 10,524 -2,203 47,524 -2,276 7,111 -1,368 17,012 -282 PADD 1 PADD 2 PADD 3 PADD 4/5 ex CA CA

What stands out in Table 4.4-15 is that E 85 volumes increase while 10 percent ethanol gasoline blends decrease in response to the in creased ethanol blended into the gasoline pool. Similarly, ultra low sulfur diesel fuel output decreases in response to the new volume of cellulosic and renewable diesel fuel and biodiesel.

Table 4.4-16 summarizes the change in refinery unit capacities by PADD comparing the primary control case to the AEO 2007 reference case.119 Table 4.4-16. Change in Refinery Unit Capacities by PADD for the Primary Control Case Relative to the AEO 2007 Reference Case (thousand barrels/day)

PADD 1 PADD 2 PADD 3 PADD 4/5 ex C A California US Total Crude Tower 0 -414 0 0 0 -414 Vacuum Tower 0 -185 0 0 0 -185 Sats Gas Plant -12 0 -2 0 8 -6 Unsats Gas Plant 0 0 0 0 0 0 FCC DeC5 Tower 0 0 0 0 0 0 FCC 0 0 0 0 0 0 FCC Splitter 4 -6 0 0 0 -2 Hydrocracker -16 0 0 -21 0 -37 H-Oil Unit 0 0 0 0 0 0 Delayed Coker 0 0 0 -24 0 -24 Visbreaker 0 0 0 0 0 0 Thermal Naphtha Splitter -1 -6 0 -1 0 -8 CRU Reformer 0 0 0 0 0 0 SRU Reformer 0 0 0 0 -5 -5 BTX Reformer 0 0 -10 0 0 -10 C4 Isomerization 0 0 0 0 1 1 C5/C6 Isomerization 21 0 0 0 0 21 HF Alkylation 0 0 0 0 0 0 H2SO4 Alkylation -14 0 0 13 0 -2 Dimersol 0 0 0 0 0 0 Cat Poly 6 0 0 0 0 6 Isooctane 0 0 0 0 0 0 DHT - Total -132 0 -75 -49 0 -256 DHT 2nd RCT - Total -117 -116 -146 -51 -4 -435 DHT Arom Saturation 0 0 0 0 0 0 NHT - Total Fd 0 0 0 0 0 0 CGH - Generic -16 -23 -6 -2 0 -48 CGH - Olefin Sat'n 0 0 0 0 0 0 FCCU Fd HDT 55 0 0 0 0 55 LSR Splitter 0 0 0 0 0 0 LSR Bz Saturator 0 0 0 0 0 0 Reformate Saturator -14 -4 1 0 0 -16 Reformate Splitter -41 -12 4 0 0 -49 SDA 0 0 0 0 0 0 MTBE 0 0 0 0 0 0 TAME 0 0 0 0 0 0 Hydrogen Plant - Total MSC F -88 -72 -84 -71 0 -316 Lube Unit 0 0 0 0 0 0 Sulfur Plant -95 0 0 -204 -69 -368 Merox Jet 0 0 0 0 0 0 Merox Diesel 0 0 0 0 0 0 BTX Reformer - Tower feed 0 0 0 0 0 0 BTX Reformer - Extract feed 0 0 0 0 0 0

Most of the capacity throughput changes are negative, reflecting the decreased processing of crude oil and vacuum gas oil and decreased do wnstream refining units as projected by the refinery model. Another important decrease in refinery unit throughput is the distillate120 hydrotreater and hydrocracker units which refl ect the displacement of petroleum distillate by cellulosic and renewable diesel and biodiesel.

These changes in refinery unit throughputs are associated with changes in capital investments. Table 4.4-17 summa rizes the projected change in capital investments between the primary control case and the AEO 2007 reference case.121 Table 4.4-17. Change in Refinery Unit Investments by PADD for the Primary Control Case Relative to the AEO 2007 Reference Case (million dollars/year)

PADD 1 PADD 2 PADD 3 PADD 4/5 ex C A California US Total Crude Tower 0 -960 0 0 0 -960 Vacuum Tower 0 -572 0 0 0 -572 Sats Gas Plant -67 0 -4 0 53 -18 Unsats Gas Plant -2 0 0 0 0 -2 FCC DeC5 Tower 0 0 0 0 0 0 FCC 0 0 0 0 0 0 FCC Splitter 2 -7 0 0 0 -5 Hydrocracker -584 0 0 -641 0 -1,225 H-Oil Unit 0 0 0 0 0 0 Delayed Coker 0 0 0 -534 0 -534 Visbreaker 0 0 0 0 0 0 Thermal Naphtha Splitter -3 -7 0 -2 0 -12 CRU Reformer 0 0 0 0 0 0 SRU Reformer 0 0 0 0 -30 -30 BTX Reformer 0 0 -63 0 0 -63 C4 Isomerization 0 0 0 0 6 6 C5/C6 Isomerization 187 0 0 0 0 187 HF Alkylation 0 0 0 0 0 0 H2SO4 Alkylation -246 0 0 246 0 1 Dimersol 0 0 0 0 0 0 Cat Poly 48 0 0 0 0 48 Isooctane 0 0 0 0 0 0 DHT - Total -1,364 0 -496 -531 0 -2,391 DHT 2nd RCT - Total -905 -771 -694 -308 -21 -2,699 DHT Arom Saturation 0 0 0 0 0 0 NHT - Total Fd 0 0 0 0 0 0 CGH - Generic -75 -131 -60 -7 0 -274 CGH - Olefin Sat'n 0 0 0 0 0 0 FCCU Fd HDT 695 0 0 0 0 695 LSR Splitter 0 0 0 0 0 0 LSR Bz Saturator 0 0 0 0 0 0 Reformate Saturator -92 -19 5 0 0 -105 Reformate Splitter -53 -16 2 0 0 -68 SD A 000 000 MTBE 0 0 0 0 0 0 TAME 0 0 0 0 0 0 Hydrogen Plant - Total MSC F -352 -221 -227 -237 0 -1,038 Lube Unit 0 0 0 0 0 0 Sulfur Plant -3 0 0 -2 -2 -6 Merox Jet 0 0 0 0 0 0 Merox Diesel 0 0 0 0 0 0 BTX Reformer - Tower feed 0 0 -1 0 0 -1 BTX Reformer - Extract feed 0 0 0 0 0 0 Total -2,814 -2,704 -1,539 -2,016 6 -9,067

Table 4.4-17 shows that incremental to the AEO 2007 reference case, refiners are expected to reduce their capital investments by $9.1 billion under the primary control case. The reduction in capital investments occurs in PADDs 1 through 4 and PADD 5 outside of California. Table 4.4-17 essentially expresses the change in refinery capacity input shown in122 Table 4.4-16, but expresses the changes in terms of dollars instead of thousands of barrels per day.

The capital cost decrease in refineries is count ered by the capital costs incurred to build new renewable fuels plants and to put into pla ce the distribution system that the new renewable fuels require. The increased use of renewabl e and alternative fuels would require capital investments in corn and cellulosic ethanol plants, and rene wable diesel fuel plants. In addition to producing the fuels, storage and distribution facilities along the whole distribution chain, including at retail, will have to be constructed for these new fuels. In Table 4.4-18, we list the total incremental capital investments that we project would be made for the primary control case incremental to the AEO 2007 reference case. A ll these capital costs are represented in the summary of costs in Table 4.4-12 either in th e per-gallon biofuel production costs, or the pergallon distribution costs.

Table 4.4-18. Projected Total U.S. Capital Investme nts for the Primary Control Case Relative to the AEO 2007 Reference Case (billion dollars) Cost Type Plant Type Capital Investments Corn Ethanol 3.9 Cellulosic Ethanol 14.3 Cellulosic Diesel a 68.0 Production Costs

Renewable Diesel and Algae 1.1

All Ethanol 8.2 Cellulosic and Renewable Diesel Fuel 1.4 Distribution Costs

Biodiesel 1.2 FFV Costs 1.8 Refining -9.4 Total Capital Investments 90.5a The cellulosic diesel fuel capital costs are based on the biomass-toliquids (BTL) technology which is a very capital intensive technology. If other cellulosic bi ofuel technologies are used which are less capital intensive than BTL technologies, these capital costs would be lower.

Table 4.4-18 shows that the total U.S. incremental capital investments to achieve the RFS 2 volumes under the primary control case in 2022 is $90.5 billion. One contributing reason why the capital investments made for re newable fuels technologies is so much more than the decrease in refining industry capital invest ments is that a part of the decrease in petroleum gasoline supply was from reduced imports. In addition, renewabl e fuels technologies are more capital intensive per gallon of fuel produced than incremental incr eases in gasoline and diesel fuel production at refineries.123 Table 4.4-19 summarizes the gasoline volume and qualities by different gasoline types for the primary control case, and also, for comp arison, lists the same for the AEO 2007 reference

case.

Table 4.4-19. Ethanol and Gasoline Volume, Quality and Energy Density by Gasoline Type at the PADD Terminal for the Primary Control Case Relative to the AEO 2007 Reference Case

Ref Case Control Ref Case Control Ref Case Control Ref Case Control Ref Case Control Ref Case Control RFG

Total ('000 BPD) 1,376,331 1,107,710 319,080 325,776 459,343 482,832 0 0 1,299,365 1,326,631 3,454,120 3,242,949 Ethanol ('000 BPD) 139,023 111,890 32,230 32,907 46,397 48,771 0 0 131,244 134,003 348,895 327,571 RVP (psi) 10.8 10.8 10.6 10.6 9.7 9.8 0.0 0.0 9.5 9.5 10.1 10.1 Sulfur (ppm) 24.4 24.6 20.0 20.5 23.2 23.4 0.0 0.0 8.8 8.5 18.0 17.4 Density 258.9 258.9 258.2 258.3 259.5 259.4 0.0 0.0 258.5 258.7 258.8 258.8 Octane (R+M/2) 88.1 88.3 88.0 88.0 88.0 88.0 0.0 0.0 87.6 87.6 87.9 87.9 Aromatics (vol%) 19.9 19.9 19.9 19.9 19.6 19.7 0.0 0.0 22.2 22.1 20.7 20.8 Benzene (vol%) 0.57 0.57 0.57 0.57 0.56 0.56 0.00 0.00 0.53 0.54 0.55 0.56 Olefins (vol%) 13.6 14.7 9.4 9.3 11.5 11.1 0.0 0.0 5.7 5.7 10.0 9.9 Oxygen (wt%) 3.7 3.7 3.7 3.7 3.7 3.7 0.0 0.0 3.7 3.7 3.7 3.7 E200 (vol%) 55.6 55.1 58.3 57.4 53.3 52.7 0.0 0.0 58.2 58.2 56.5 56.2 E300 (vol%) 93.9 95.3 93.9 93.8 93.9 93.4 0.0 0.0 86.2 86.2 91.0 91.2 Energy (MMBtu/Bbl 4.947 4.961 4.924 4.935 4.981 4.990 0.000 0.000 4.994 5.002 4.967 4.979 CG

Total ('000 BPD) 1,830,582 1,868,996 1,640,138 1,545,011 1,280,314 1,059,721 696,861 691,193 112,988 115,359 5,560,884 5,280,279 Ethanol ('000 BPD) 134,064 188,787 165,671 156,062 129,320 107,043 70,390 69,817 11,413 11,652 510,857 533,362 RVP (psi) 11.4 11.8 11.6 11.5 10.7 10.4 11.4 11.4 10.6 10.6 11.3 11.3 Sulfur (ppm) 22.9 24.5 23.6 23.3 23.1 23.1 28.0 28.0 26.6 26.3 23.9 24.4 Density 258.9 259.5 259.1 259.1 260.5 260.1 258.1 257.9 262.7 264.1 259.3 259.4 Octane (R+M/2) 87.8 87.8 88.0 88.0 88.0 88.2 86.9 86.9 89.3 89.5 87.8 87.9 Aromatics (vol%) 23.1 22.4 22.5 22.5 22.4 21.8 15.9 15.6 26.5 28.3 21.9 21.6 Benzene (vol%) 0.53 0.53 0.53 0.52 0.51 0.51 1.05 1.01 0.59 0.61 0.59 0.59 Olefins (vol%) 13.2 14.0 11.0 11.0 13.1 12.3 8.5 7.6 17.8 18.4 12.0 12.0 Oxygen (wt%) 2.7 3.7 3.7 3.7 3.7 3.7 3.7 3.7 3.7 3.7 3.4 3.7 E200 (vol%) 52.5 53.1 58.8 58.0 53.0 52.5 63.0 62.7 58.0 56.4 55.9 55.8 E300 (vol%) 93.9 95.3 93.9 83.8 93.9 79.5 93.9 90.6 86.2 86.2 93.7 88.0 Energy (MMBtu/Bbl 4.995 4.980 4.925 4.937 4.988 5.005 0.000 4.912 4.942 4.964 4.961 4.963 E85

Total ('000 BPD) 0 283,619 0 129,577 0 247,459 0 20,291 0 0 0 680,947 Ethanol ('000 BPD) 0 243,490 0 111,243 0 212,446 0 17,420 0 0 0 584,599 RVP (psi) 0.0 11.1 0.0 12.2 0.0 12.1 0.0 11.9 0.0 0.0 0.0 11.7 Sulfur (ppm) 0.0 9.5 0.0 8.8 0.0 8.8 0.0 8.8 0.0 0.0 0.0 9.1 Density 0.0 267.7 0.0 266.3 0.0 266.2 0.0 266.1 0.0 0.0 0.0 266.8 Octane (R+M/2) 0.0 107.9 0.0 108.0 0.0 108.0 0.0 107.9 0.0 0.0 0.0 107.9 Aromatics (vol%) 0.0 0.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.3 Benzene (vol%) 0.00 0.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 Olefins (vol%) 0.0 2.4 0.0 3.0 0.0 1.8 0.0 0.0 0.0 0.0 0.0 2.2 Oxygen (wt%) 0.0 30.6 0.0 30.8 0.0 30.8 0.0 30.8 0.0 0.0 0.0 30.7 E200 (vol%) 0.0 128.1 0.0 130.1 0.0 129.8 0.0 129.3 0.0 0.0 0.0 129.1 E300 (vol%) 0.0 96.1 0.0 96.6 0.0 96.6 0.0 96.6 0.0 0.0 0.0 96.4 Energy (MMBtu/Bbl 0.000 3.628 0.000 3.599 0.000 3.597 0.000 3.594 0.000 0.000 0.000 3.610 All Mogas

Total BPD 3,206,913 3,260,324 1,959,219 2,000,364 1,739,657 1,790,012 696,861 711,484 1,412,353 1,441,990 9,015,003 9,204,175 Ethanol BPD 273086.9 544,167 197900.9 300,212 175717.0 368,259 70390.0 87,238 142657.3 145,656 859752.1 1,445,532 RVP 11.1 11.4 11.4 11.4 10.4 10.5 11.4 11.4 9.6 9.6 10.8 10.9 Sulfur ppm 24 23 23 22 23 21 28 27 10 10 22 21 Density 258.9 260 259.0 259 260.2 261 258.1 258 258.9 259 259.1 260 R+M/2 87.9 89.7 88.0 89.3 88.0 90.9 86.9 87.5 87.8 87.8 87.8 89.4 Aromatics 21.7 19.7 22.1 20.6 21.7 18.2 15.9 15.2 22.5 22.6 21.5 19.7 Benzene 0.55 0.50 0.53 0.50 0.53 0.45 1.05 0.98 0.54 0.55 0.58 0.53 Olefins 13.4 13.2 10.7 10.2 12.7 10.6 8.5 7.4 6.7 6.7 11.2 10.6 Oxygen (wt%) 3.1 6.1 3.7 5.5 3.7 7.5 3.7 4.5 3.7 3.7 3.5 5.8 E200 53.8 60.3 58.7 62.6 53.1 63.2 63.0 64.6 58.2 58.1 56.1 61.4 E300 93.9 95.4 93.9 86.3 93.9 85.6 93.9 90.8 86.2 86.2 92.7 89.7 Energy (MMBtu/Bbl 4.974 4.856 4.925 4.850 4.986 4.806 4.913 4.874 4.990 4.999 4.963 4.869 PADD 3 PADD 4/5 ex CA CA US PADD 1 PADD 2

Several very important differences are evident when comparing the U.S. gasoline (mogas) qualities of the primary control case to the AEO 2007 reference case in Table 4.4-19.124 First, the energy content of the control case gasoline is lower than that of the reference case. Other obvious changes include decreases in aroma tics, benzene, olefins and sulfur. Another important change is the increase in the gasoline pool octane. Since the reference case gasoline pool was compliant in octane, the increased octa ne of the control case represents octane giveaway. After further review, it is evident that virtually all these changes are caused by the blending of E85 which significantly dilutes these properties in the gasoline blendstock in E85.

Year-by-Year Costs

To understand entire costs of the increase in renewable fuel use mandated by EISA, theirimpacts on the U.S. economy, and to compare those costs to the benefits, we estimated the yearby-year costs from 2010, the first year of the RFS 2 program, to 2030. We first estimated renewable fuels volumes for each renewable fuel s type based on the RFS2 volume standards and based on our projections of which renewable fuels would be used to comply with the standard (see Section 1.2). These volumes represent the increment between the AEO 2007 reference case and the primary control case. Based on AEO 200 9, we also estimated the overall gasoline and diesel fuel volumes. Table 4.4-20 below summarizes the projected year-by-year incremental renewable fuel, and total gaso line and diesel fuel volumes.

Table 4.4-20. Summary of Year-by-Year Volumes for the Primary Control Case Relative to the AEO 2007 Reference Case (Billion Gallons/year)

Year Diesel Fuel Volume Cellulosic Diesel

Fuel Renewable Diesel Fuel Biodiesel (all types) Gasoline Volume Corn Ethanol Imported Ethanol Cellulosic Ethanol

2010 62.93 0.04 0.04 0.51 158.65 0.75 0.00 -0.09 2011 63.98 0.10 0.08 0.56 162.54 1.38 0.00 -0.11 2012 65.47 0.20 0.08 0.71 162.15 2.01 0.00 -0.10 2013 66.42 0.41 0.08 0.87 161.03 2.49 0.00 0.06 2014 66.50 0.71 0.15 1.01 159.48 3.08 0.00 0.29 2015 66.65 1.22 0.15 1.13 157.14 3.69 0.00 0.67 2016 67.21 1.73 0.15 1.06 154.50 3.84 0.12 1.06 2017 67.85 2.24 0.15 1.09 152.44 3.70 0.54 1.44 2018 68.57 2.85 0.15 1.13 149.84 3.51 0.97 1.90 2019 69.23 3.46 0.15 1.16 148.08 3.31 1.38 2.36 2020 69.98 4.28 0.15 1.20 145.78 3.17 1.29 2.98 2021 70.59 5.50 0.15 1.24 144.14 2.93 1.19 3.90 2022 71.25 6.52 0.15 1.28 141.10 2.71 1.60 4.67 2023 72.16 6.52 0.15 1.28 141.18 2.71 1.60 4.67 2024 73.17 6.52 0.15 1.28 141.80 2.71 1.60 4.67 2025 74.21 6.52 0.15 1.28 141.66 2.71 1.60 4.67 2026 75.16 6.52 0.15 1.28 141.70 2.71 1.60 4.67 2027 76.07 6.52 0.15 1.28 139.74 2.71 1.60 4.67 2028 76.99 6.52 0.15 1.28 139.65 2.71 1.60 4.67 2029 77.87 6.52 0.15 1.28 138.14 2.71 1.60 4.67 2030 78.97 6.52 0.15 1.28 138.59 2.71 1.60 4.67125 Also for our year-by-year cost analysis, we needed year-by-year estimates of the production and distribution cost for each renewable fuel type. The feedstock costs were available for the years 2012, 2017 and 2022 from FASOM for corn ethanol and soy oil, used for producing biodiesel, with crude oil priced at $116 per barrel. We entered those feedstock costs into the respective cost models and interpolat ed and extrapolated the production costs for the years provided to develop production costs for the in-between years. For cellulosic ethanol, we assumed the same feedstock cost s for all years, but we adjust ed the production costs based on our adjusted NREL production cost s, interpolating between the years for which we have specific cost data. Imported ethanol costs by year are from Section 4.1 above. Tables 4.4-21 summarize the renewable fuels production costs by year al ong with the projected crude oil, gasoline and diesel fuel wholesale costs.

Table 4.4-21. Renewable Fuel Production Costs Used in the Year-by- Year Analysis for the Primary Control Case Relative to the AEO 2007 Reference Case

Year Crude Oil Price ($/bbl) Wholesale Diesel Fuel Cost (c/gal) Cellulosic Diesel Fuel Cost

(c/gal) Renewable Diesel Fuel Cost (c/gal) Biodiesel Fuel Cost

(c/gal) Wholesale Gasoline

Cost (c/gal) Corn Ethanol

Cost (c/gal) Imported Ethanol

Cost (c/gal) Cellulosic Ethanol

Cost (c/gal)

2010 49.0 154 258 236 261 157 160 158 220 2011 62.0 198 256 236 264 191 160 157 203 2012 72.1 232 255 236 227 218 160 156 186 2013 81.0 262 253 238 227 241 159 155 168 2014 88.6 288 251 240 225 262 158 154 151 2015 96.8 315 249 243 226 283 158 153 134 2016 101.9 333 248 245 228 297 157 153 133 2017 106.2 347 246 247 232 308 156 152 132 2018 110.5 362 244 246 234 320 155 152 131 2019 112.8 369 242 245 235 326 154 152 130 2020 114.5 375 241 244 238 330 152 151 129 2021 115.8 380 239 243 241 334 151 151 128 2022 116.5 383 237 242 244 335 150 150 127 2023 117.7 386 237 242 244 339 150 150 127 2024 118.3 388 237 242 244 340 150 149 127 2025 116.1 380 237 242 244 334 150 149 127 2026 117.5 385 237 242 244 338 150 149 127 2027 119.2 391 237 242 244 343 150 149 127 2028 121.2 398 237 242 244 348 150 149 127 2029 121.9 400 237 242 244 350 150 149 127 2030 124.4 409 237 242 244 356 150 149 127

Based on the volumes and renewable fuel s production and distribution costs, we estimated the net cost for the in creased volumes of renewable fu els in years other than 2022 and summarized them in Table 4.4-22. We started wi th the year 2022 costs as our basis. We then adjusted those costs using the volume and pri ce relationship between et hanol and gasoline to estimate the costs in other years. We also calculated the total dollar amount of the subsidies based on the volumes of renewable fuels and the s ubsidy that applies to each renewable fuel, and what the subsidized cost would be when the subsidies are applied.126 Table 4.4-22. Year-by-Year Annual Average and Per-Gallon Costs for Gasoline for the Primary Control Case Relative to the AEO 20007 Reference Case

Total Annual

Cost ($MM/yr) PerGallon

Cost (c/gal) Subsidy ($MM/yr) Subsidized Per-Gallon Cost (c/gal) Total Annual

Cost ($MM/yr) PerGallon

Cost (c/gal) Subsidy ($MM/yr) Subsidized Per-Gallon Cost (c/gal)

2010 456 0.3 242 0.1 815 1.3 602 0.3 2011 703 0.4 511 0.1 719 1.1 693 0.0 2012 835 0.5 808 0.0 377 0.6 940 -0.9 2013 831 0.5 1181 -0.2 152 0.2 1312 -1.7 2014 758 0.5 1678 -0.6 -251 -0.4 1771 -3.0 2015 198 0.1 2339 -1.4 -963 -1.4 2405 -5.1 2016 -229 -0.1 2839 -2.0 -1601 -2.4 2797 -6.5 2017 -1110 -0.7 3275 -2.9 -2351 -3.5 3343 -8.4 2018 -2076 -1.4 3726 -3.9 -3400 -5.0 3992 -10.8 2019 -2825 -1.9 4150 -4.7 -4333 -6.3 4640 -13.0 2020 -2922 -2.0 4721 -5.2 -5479 -7.8 5504 -15.7 2021 -2936 -2.0 5554 -5.9 -7099 -10.1 6779 -19.7 2022 -3349 -2.4 6308 -6.8 -8546 -12.0 7849 -23.0 2023 -3545 -2.5 6308 -7.0 -8787 -12.2 7849 -23.1 2024 -3640 -2.6 6308 -7.0 -8933 -12.2 7849 -22.9 2025 -3285 -2.3 6308 -6.8 -8369 -11.3 7849 -21.9 2026 -3512 -2.5 6308 -6.9 -8728 -11.6 7849 -22.1 2027 -3769 -2.7 6308 -7.2 -9157 -12.0 7849 -22.4 2028 -4097 -2.9 6308 -7.5 -9679 -12.6 7849 -22.8 2029 -4199 -3.0 6308 -7.6 -9857 -12.7 7849 -22.7 2030 -4589 -3.3 6308 -7.9 -10473 -13.3 7849 -23.2 Gasoline Costs Diesel Fuel Costs

Year

The projected costs in Table 4.4-22 show that in the initial years of 2010 to 2013 for diesel fuel and 2010 to 2015 for gasoline, the per-gallon costs are positive reflecting the generally higher projected production costs for re newable fuels and the lower crude oil prices. After those initial years, the program would accrue a cost savings assuming that the crude oil prices projected by EIA hold true.

4.4.2.1.2 Primary (Mid-Ethanol) Control Case Incremental to the RFS 1 Reference Case

We also assessed the gasoline and diesel fu el costs and other impacts of the primary control case relative to the RFS1 reference case. The costs contained in Table 4.4-23 are reported by different cost components as well as aggregated total and per-gallon costs.127 Table 4.4-23. Primary Control Case Costs without Tax Subsidies Relative to the RFS 1 Reference Case (2007 dollars, 7% ROI before taxes) Gasoline Diesel Fuel Refinery Model Variable Operating Cost $MM/yr 11,252 - Amortized Refinery Capital Costs $MM/yr -1,031 - Fixed Operating Costs $MM/yr -284 - A dded Gasoline Transportation Cost $MM/yr -148 - E85 Pricing Effect $MM/yr -8,338 - Crude Oil Cost $51 to $116/bbl $MM/yr -25,884 - Lower Energy Density $MM/yr 15,928 1,750 A djustment from Ethanol Price to Cost $MM/yr 507 - FFV Costs $MM/yr 2,370 Renewable Diesel Cost vs Pe troleum Diesel $MM/yr - -10,382 Total Costs $MM/yr -5,628 -8,632 Refinery Model Variable Operating Cost c/gal 7.97 - A mortized Refinery Capital Costs c/gal -0.73 - Fixed Operating Costs c/gal -0.20 - A dded Gasoline Transportation Cost c/gal -0.10 - E85 Pricing Effect c/gal -5.91 - Crude Oil Cost $51 to $116/bbl c/gal -18.34 - Lower Energy Density c/gal 11.29 2.45 A djustment from Ethanol Price to Cost c/gal 0.36 - FFV Costs c/gal 1.68 Renewable Diesel Cost vs Pe troleum Diesel c/gal - -14.56 Total Costs c/gal -3.99 -12.10

Our analysis shows that when considering all the costs associated with the expanded use of ethanol for the primary control case relative to the RFS 1 reference case that the cost of gasoline will decrease by $5.6 billion in the year 2022. Expressed as per-gallon costs, these fuel changes will reduce the cost of producing gasoline in the U.S. by 4.0 cents per gallon. The addition of biodiesel, renewable and cellulosic diesel fuel is estimated to reduce the cost of diesel fuel by $8.6 billion in the year 2022, or save 12.1 cents per gallon.

Table 4.4-24. Primary Control Case Costs Reflecting Tax Subsidies Relative to the RFS 1 Reference Case (2007 dollars, 7% ROI before taxes) Gasoline Diesel Fuel Total Costs $MM/yr -5,628 -8,632 Federal Subsidies $MM/yr -9,075 -8,026 Revised Total Cost $MM/yr -14,703 -16,659 Total Costs c/gal -3.99 -12.10 Federal Subsidies c/gal -6.43 -11.25 Total Costs c/gal -10.42 -23.35

Our analysis of the primary control case costs relative to the RFS 1 reference case128 reflecting the federal tax subsidies would cause a 10.4 cent per gallon decrease in the apparent cost of producing gasoline, and a 23.4 cent decrease in the apparent cost of producing diesel fuel. While this could represent the cost of the renewable fuel use to consumers at retail, it is possible that only a portion of the tax subsidy will be passed along to the consumer. Thus, the price impact at the pump may be somewhere between the values in Tables 4.4-23 and 4.4-24. However, consumers would also pay the full ta x subsidy through higher taxes which would offset the cost savings caused by the subsidies.

Table 4.4-25 summarizes the volumetric inputs to refineries in each PADD for this control case and shows the relative changes of the primary control case compared to the RFS 1 reference case. Because of the increased use of biofuels, petroleum inputs would be expected to decrease, and this is confirmed.

Table 4.4-25. Summary of the Total and Incremental Volu metric Refinery Inputs by PADD for the Primary Control Case Relative to the RFS 1 Reference Case (barrels/day)

Control Difference Control Difference Control Difference Control Difference Control Difference Case from Ref Case Case from Ref Case Case from Ref Case Case from Ref Case Case from Ref Case PADD Crude 1,347,342 -151,714 3,058,241 -475,740 7,117,305 -241,263 1,534,859 -4,119 1,886,357 -1,136 GTL Naphtha 0 0 0 0 0 0 0 0 0 0 GTL Diesel 0 0 0 0 0 0 0 0 0 0 VGO HS 0 0 0 0 0 -33,772 0 0 0 0 VGO LS 0 0 7,920 -23,914 0 0 0 0 0 0 HS AR (A960) 0 0 0 0 0 0 0 0 0 0 LS AR (Alg) 279,819 39,889 0 0 738,057 21,829 0 0 0 0 Normal Butane 30,814 8,329 78,293 19,185 69,363 -14,040 25,526 -13,917 39,573 0 Isobutane 12,582 12,582 16,476 -8,390 8,234 8,234 1,178 -22,245 0 0 Other 0 0 0 0 0 0 0 0 0 0 MTBE 0 0 0 0 0 0 0 0 0 0 Ethanol - E10 270,313 130,437 168,062 63,684 142,590 88,811 66,626 40,273 143,845 8,610 Ethanol - E20 0 0 0 0 0 0 0 0 0 0 Ethanol - E85 575,048 575,048 332,715 332,715 361,999 361,999 60,129 60,129 46,969 46,969 Reformer Feed 0 0 0 0 0 0 0 0 0 0 Methanol 0 0 0 0 0 0 0 0 0 0 Natural Gas (FOE) 74,115 -6,201 136,509 -5,559 493,553 6,876 86,015 -3,625 154,032 -2,444 Hydrogen (MSCF) 0 0 0 0 0 0 0 0 0 0 Pentanes Plus 0 0 58 -32,066 52,055 0 0 -17,467 0 0 Import CBOB 10% 0 0 0 0 0 0 0 0 0 0 Import CBOB 20% 0 0 0 0 0 0 0 0 0 0 Import RBOB 10% 0 -200,000 0 0 0 0 0 0 0 0 Import RBOB 20% 0 0 0 0 0 0 0 0 0 0 Import Alkylate 45,167 45,167 0 0 0 0 0 0 0 0 Import Raffinate 3,442 -61,147 0 0 0 0 0 0 45,808 0 Import Reformate 0 0 0 0 0 0 0 0 0 0 Import FCC Naphtha 15,980 15,980 0 0 11,943 11,943 18,580 18,580 0 0 Import Lt Naphtha 0 0 17,575 17,575 0 0 0 0 584 0 Import Hvy Naph 0 0 0 0 41,644 0 0 0 0 0 Transfer Lt Naphtha 0 -23,342 0 -20,822 0 0 0 0 11,387 -9,842 Transfer Reformate 16,658 0 0 -14,074 0 0 0 0 0 0 Transfer Alkylate 60,000 17,381 0 0 0 0 0 0 60,000 16,933 Transfer FCC Naphtha 0 0 20,822 20,822 0 0 0 0 0 0 Transfer Raffinate 0 0 11,353 -5,888 0 0 0 0 60,000 11,077 Transfer RBOB 10% 242,605 0 0 0 0 0 0 0 0 0 Transfer RBOB 20% 0 0 8,720 8,720 0 0 0 0 0 0 Transfer CBOB 10% 1,398,409 1,381,833 80,262 77,306 0 0 6,493 -19,539 0 0 Transfer CBOB 20% 0 0 0 0 0 0 0 0 0 0 Isooctane 100 0 100 0 100 0 100 0 16,462 2,029 Isooctene 100 0 100 0 100 0 100 0 600 0 PADD 3 PADD 4/5 ex CA C A PADD 1 PADD 2

The changes in 4.4-25 are similar to thos e in 4.4-14 except because the new volume of ethanol is larger, some of the differences are larger.

Table 4.4-26 below summarizes the refinery output volumes and changes in refinery output volumes for the primary control case relative to the RFS 1 reference case by PADD.129 Table 4.4-26. Summary of Total and Incremental Refinery Outputs by PADD for the Primary Control Case Relative to the RFS 1 Reference Case (barrels/day)

Control Difference Control Difference Control Difference Control Difference Control Difference Case from Ref Case Case from Ref Case Case from Ref Case Case from Ref Case Case from Ref Case Propane 34,143 1,539 50,843 -12,263 103,144 -32,064 23,369 -1,541 52,782 1,461 Propylene 18,685 0 42,525 0 245,407 0 2,041 0 11,774 0 Normal Butane 0 -7,832 0 -2,370 0 -45,506 0 0 0 0 Isobutane 0 0 0 0 0 -345 0 0 40,012 5,009 PC Naphtha 15,830 0 40,290 0 432,937 0 0 0 0 0 PC Gasoil 0 0 455,618 -108,658 157,500 0 0 0 0 0 CG Reg 0 -118,066 0 -852,131 0 -2,020,447 0 -374,129 0 -53,481 CG Prem 0 0 0 0 0 -416,926 0 -51,984 0 0 CG E10 Reg 1,535,198 1,516,962 1,172,450 704,964 872,274 872,274 542,856 325,693 99,374 59,284 CG E10 Prem 306,669 306,669 274,765 23,409 214,485 134,887 116,742 72,990 18,928 1,105 RFG E10 Reg 605,554 -542,443 163,150 -101,096 246,042 -134,362 0 0 1,088,091 12,026 RFG E10 Prem 228,678 10,012 53,454 3,122 78,844 6,386 0 0 217,676 12,712 CG E20 Reg 0 0 0 0 0 0 0 0 0 0 RFG E20 Reg 0 0 0 0 0 0 0 0 0 0 E85 to CG 74,814 74,814 270,064 270,064 253,773 253,773 70,039 70,039 0 0 E85 to RFG 595,006 595,006 117,484 117,484 167,888 167,888 0 0 54,710 54,710 Transfer RBOB 10% 0 0 0 0 251,325 8,720 0 0 0 0 Transfer RBOB 20% 0 0 0 0 0 0 0 0 0 0 Transfer CBOB 10% 0 0 0 0 1,485,164 1,439,600 0 0 0 0 Transfer CBOB 20% 0 0 0 0 0 0 0 0 0 0 Jet/Kero A (450ppm) 70,000 0 138,523 -3,108 936,227 0 274,537 0 229,653 0 X-Fer Diesel Rundown t 0 0 0 00 0 0 0 0 0 HSD Gr 76 (0.2%) 0 0 0 0 0 0 0 0 0 0 LSD Gr 74 (.05%) 0 0 0 0 0 0 0 0 0 0 ULSD (15 ppm) 587,042 -39,165 643,331 -30,227 2,150,901 2,423 523,035 -11,120 0 0 CARB Diesel 0 0 0 0 0 0 0 0 358,152 -6,714 X-Fer C5's to Storage 0 0 0 0 0 0 0 0 0 0 1% Residual Fuel 0 0 0 0 0 0 0 0 0 0 Residual Fuel 68,283 -21,481 67,826 8 262,834 0 138,312 22,862 45,680 -4,199 Slurry 30,026 3,876 67,363 -19,645 112,554 -4,041 12,295 -4,210 29,893 1,191 Asphalt & Wax 86,013 -5,669 198,329 -11,671 157,500 0 5,250 0 41,774 0 Gasoil 0 0 4,895 0 0 0 0 0 9,814 0 Lubes 18,706 0 17,313 0 157,500 0 0 0 20,149 0 Benzene 11,003 0 11,003 0 51,347 0 0 0 0 0 Toluene 0 0 0 0 34,910 0 0 0 0 0 Xylenes 0 0 0 0 7,777 0 0 0 0 0 Cumene 0 0 0 0 0 0 0 0 0 0 Othe r 0 0 0 00 0 0 0 0 0 Cyclohexane 0 0 0 0 0 0 0 0 0 0 Transfer Raffinate 0 0 0 0 71,353 5,190 0 0 0 0 Transfer Alkylate 0 0 0 0 120,000 34,314 0 0 0 0 Transfer Reformate 0 0 0 0 16,658 16,658 0 0 0 0 Transfer FCC naphtha 0 0 0 0 20,822 20,822 0 0 0 0 Transfer Lt Naphtha 0 0 0 0 0 -23,342 0 0 11,387 -9,842 Transfer Blendstock 0 0 0 0 0 0 0 0 0 0 Sulfur (STons) 1,076 -74 3,571 -630 12,042 -533 2,038 -59 3,559 -10 Coke (STon) 3,495 -227 10,154 -3,068 48,646 -2,278 7,899 -790 17,358 86 PADD 1 PADD 2 PADD 3 PADD 4/5 ex CA CA

Table 4.4-27 summarizes the change in refinery unit capacities by PADD comparing the primary control case to the RFS 1 reference case.130 Table 4.4-27. Change in Refinery Unit Capacities by PADD for the Primary Control Case Relative to the RFS 1 Reference Case (thousand barrels/day) PADD 1 PADD 2 PADD 3 PADD 4/5 ex CA California US Total Crude Tower 0 -439 0 0 0 -439 Vacuum Tower 0 -196 0 -2 0 -198 Sats Gas Plant 3 0 -30 0 9 -18 Unsats Gas Plant -2 0 0 0 0 -2 FCC DeC5 Tower 0 0 0 0 0 0 FCC 0 0 0 -8 0 -8 FCC Splitter 2 -6 0 0 0 -5 Hydrocracker -18 0 0 -14 0 -33 H-Oil Unit 0 0 0 0 0 0 Delayed Coker 0 0 0 -28 0 -28 Visbreaker 0 0 0 0 0 0 Thermal Naphtha Splitter -1 -6 0 -1 0 -8 CRU Reformer 0 0 0 0 0 0 SRU Reformer 0 0 0 0 -1 -1 BTX Reformer 0 -10 -18 0 0 -27 C4 Isomerization 0 0 0 0 1 1 C5/C6 Isomerization 26 0 0 0 0 26 HF Alkylation 0 0 0 0 0 0 H2SO4 Alkylation 1 0 0 -5 0 -4 Dimersol 0 0 0 0 0 0 Cat Pol y 000 0 00 Isooctane 0 0 0 0 0 0 DHT - Total -132 0 -103 -50 -4 -290 DHT 2nd RCT - Total -117 -153 -174 -52 -4 -501 DHT Arom Saturation 0 0 0 0 0 0 NHT - Total Fd 0 0 0 -4 0 -4 CGH - Generic -12 -19 -19 -6 0 -57 CGH - Olefin Sat'n 0 0 0 0 0 0 FCCU Fd HDT 37 0 0 0 0 37 LSR Splitter 0 41 38 0 0 80 LSR Bz Saturator 0 0 0 0 0 0 Reformate Saturator -4 -4 1 0 0 -7 Reformate Splitter -12 -12 3 0 0 -21 SDA 0 0 0 0 0 0 MTBE 0 0 0 0 0 0 TAME 0 0 0 0 0 0 Hydrogen Plant - Total MSC -72 11 109 -47 0 1 Lube Unit 0 0 0 0 0 0 Sulfur Plant -128 0 0 -204 -71 -402 Merox Jet 0 0 0 0 0 0 Merox Diesel 0 0 0 0 0 0 BTX Reformer - Tower feed 0 -1 -1 0 0 -2 BTX Reformer - Extract fee d -1 0 0 0 0 -1

These changes in refinery unit throughputs are associated with changes in capital investments. Table 4.4-28 summa rizes the projected change in capital investments between the primary control case and the RFS 1 reference case.131 Table 4.4-28. Change in Refinery Unit Investments by PADD for the Primary Control Case Relative to the RFS 1 Reference Case (million dollars/year) PADD 1 PADD 2 PADD 3 PADD 4/5 ex CA California US Total Crude Tower 0 -997 0 0 0 -997 Vacuum Tower 0 -591 0 0 0 -591 Sats Gas Plant 12 0 -101 0 55 -34 Unsats Gas Plant -10 0 0 0 0 -10 FCC DeC5 Tower 0 0 0 0 0 0 FCC 0 0 0 -193 0 -193 FCC Splitter 1 -7 0 0 0 -6 Hydrocracker -631 0 0 -505 0 -1,137 H-Oil Unit 0 0 0 0 0 0 Delayed Coker 0 0 0 -592 0 -592 Visbreaker 0 0 0 0 0 0 Thermal Naphtha Splitter -3 -7 0 -3 0 -13 CRU Reformer 0 0 0 0 0 0 SRU Reformer 0 0 0 0 -4 -4 BTX Reformer 0 -93 -231 0 0 -324 C4 Isomerization 0 0 0 0 8 8 C5/C6 Isomerization 227 0 0 0 0 227 HF Alkylation 0 0 0 0 0 0 H2SO4 Alkylation 16 0 0 -70 0 -54 Dimersol 0 0 0 0 0 0 Cat Pol y -1 0 0 0 0 -1 Isooctane 0 0 0 0 0 0 DHT - Total -1,367 0 -702 -539 -96 -2,703 DHT 2nd RCT - Total -904 -998 -840 -312 -21 -3,076 DHT Arom Saturation 0 0 0 0 0 0 NHT - Total Fd 0 0 0 -46 0 -46 CGH - Generic -58 -63 -92 -25 0 -238 CGH - Olefin Sat'n 0 0 0 0 0 0 FCCU Fd HDT 555 0 0 0 0 555 LSR Splitter 0 29 18 0 0 47 LSR Bz Saturator 0 0 0 0 0 0 Reformate Saturator -46 -19 4 0 0 -60 Reformate Splitter -20 -16 2 0 0 -34 SDA 0 0 0 0 0 0 MTBE 0 0 0 0 0 0 TAME 0 0 0 0 0 0 Hydrogen Plant - Total MSC -255 69 274 -171 0 -84 Lube Unit 0 0 0 0 0 0 Sulfur Plant -3 0 0 -2 -2 -7 Merox Jet 0 0 0 0 0 0 Merox Diesel 0 0 0 0 0 0 BTX Reformer - Tower feed 0 -2 -1 0 0 -3 BTX Reformer - Extract fee d -3 0 0 0 0 -3 Total -2,491 -2,694 -1,669 -2,459 -59 -9,373

Table 4.4-28 shows that incremental to th e RFS 1 reference case, refiners under the primary control case are expected to reduce their capital investments by $9.4 billion compared to132 business as usual. The reduction in capital investments occurs in PADDs 1 through 4 and PADD 5 outside of California. Table 4. 4-17 essentially expresses the chan ge in refinery capacity input shown in Table 4.4-16, but expresses the changes in terms of dollars instead of thousands of barrels per day.

Table 4.4-29 summarizes the gasoline volume and qualities by different gasoline types for the primary control case, and also, for comp arison, lists the same for the RFS 1 reference

case.133 Table 4.4-29. Ethanol and Gasoline Volume, Quality and Energy Density by Gasoline Type at the PADD Terminal for the Primary Control Case Relative to the RFS 1 Reference Case

Ref Case Control Ref Case Control Ref Case Control Ref Case Control Ref Case Control Ref Case Control RFG

Total ('000 BPD) 1,366,663 1,107,710 314,578 325,776 452,862 482,832 0 0 1,281,031 1,326,631 3,415,134 3,242,949 Ethanol ('000 BPD) 138,034 111,890 31,773 32,907 45,739 48,771 0 0 129,386 134,003 344,932 327,571 RVP (psi) 10.7 10.8 10.3 10.6 9.6 9.8 0.0 0.0 9.5 9.5 10.1 10.1 Sulfur (ppm) 23.8 24.6 20.1 20.5 23.5 23.4 0.0 0.0 8.7 8.5 17.8 17.4 Density 258.5 258.9 256.2 258.3 259.1 259.4 0.0 0.0 258.5 258.7 258.4 258.8 Octane (R+M/2) 88.1 88.3 88.0 88.0 88.0 88.0 0.0 0.0 87.6 87.6 87.9 87.9 Aromatics (vol%) 19.9 19.9 18.2 19.9 19.5 19.7 0.0 0.0 22.2 22.1 20.5 20.8 Benzene (vol%) 0.57 0.57 0.57 0.57 0.57 0.56 0.00 0.00 0.54 0.54 0.56 0.56 Olefins (vol%) 13.1 14.7 8.0 9.3 9.3 11.1 0.0 0.0 5.7 5.7 9.3 9.9 Oxygen (wt%) 3.7 3.7 3.8 3.7 3.7 3.7 0.0 0.0 3.7 3.7 3.7 3.7 E200 (vol%) 55.7 55.1 62.5 57.4 54.5 52.7 0.0 0.0 58.5 58.2 57.2 56.2 E300 (vol%) 93.9 95.3 91.5 93.8 93.9 93.4 0.0 0.0 86.2 86.2 90.8 91.2 Energy (MMBtu/Bbl ) 4.963 4.961 4.864 4.935 5.027 4.990 0.000 0.000 4.988 5.002 4.971 4.979 CG

Total ('000 BPD) 1,841,024 1,868,996 1,570,973 1,545,011 1,262,249 1,059,721 687,028 691,193 111,394 115,359 5,472,668 5,280,279 Ethanol ('000 BPD) 1,842 188,787 72,606 156,062 8,040 107,043 26,352 69,817 5,849 11,652 114,689 533,362 RVP (psi) 10.5 11.8 11.8 11.5 10.7 10.4 11.3 11.4 10.8 10.6 11.0 11.3 Sulfur (ppm) 27.8 24.5 25.3 23.3 27.3 23.1 24.6 28.0 26.4 26.3 26.6 24.4 Density 259.3 259.5 258.8 259.1 259.4 260.1 256.8 257.9 260.8 264.1 258.9 259.4 Octane (R+M/2) 88.0 87.8 88.0 88.0 88.0 88.2 86.8 86.9 88.0 89.5 87.8 87.9 Aromatics (vol%) 28.7 22.4 26.3 22.5 28.4 21.8 19.3 15.6 26.8 28.3 26.7 21.6 Benzene (vol%) 0.65 0.53 0.64 0.52 0.65 0.51 0.80 1.01 0.62 0.61 0.67 0.59 Olefins (vol%) 15.2 14.0 11.2 11.0 16.0 12.3 8.0 7.6 18.6 18.4 13.4 12.0 Oxygen (wt%) 0.0 3.7 1.7 3.7 0.2 3.7 1.4 3.7 1.9 3.7 0.8 3.7 E200 (vol%) 45.2 53.1 52.9 58.0 45.9 52.5 58.9 62.7 54.5 56.4 49.5 55.8 E300 (vol%) 93.9 95.3 91.5 83.8 93.9 79.5 93.9 90.6 86.2 86.2 93.0 88.0 Energy (MMBtu/Bbl ) 5.133 4.980 5.007 4.937 5.127 5.005 5.004 4.912 4.998 4.964 5.077 4.963 E85

Total ('000 BPD) 0 283,619 0 129,577 0 247,459 0 20,29 1 0 0 0 680,947 Ethanol ('000 BPD) 0 243,490 0 111,243 0 212,446 0 17,42 0 0 0 0 584,599 RVP (psi) 0.0 11.1 0.0 12.2 0.0 12.1 0.0 11.9 0.0 0.0 0.0 11.7 Sulfur (ppm) 0.0 9.5 0.0 8.8 0.0 8.8 0.0 8.8 0.0 0.0 0.0 9.1 Density 0.0 267.7 0.0 266.3 0.0 266.2 0.0 266.1 0.0 0.0 0.0 266.8 Octane (R+M/2) 0.0 107.9 0.0 108.0 0.0 108.0 0.0 107.9 0.0 0.0 0.0 107.9 Aromatics (vol%) 0.0 0.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.3 Benzene (vol%) 0.00 0.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 Olefins (vol%) 0.0 2.4 0.0 3.0 0.0 1.8 0.0 0.0 0.0 0.0 0.0 2.2 Oxygen (wt%) 0.0 30.6 0.0 30.8 0.0 30.8 0.0 30.8 0.0 0.0 0.0 30.7 E200 (vol%) 0.0 128.1 0.0 130.1 0.0 129.8 0.0 129.3 0.0 0.0 0.0 129.1 E300 (vol%) 0.0 96.1 0.0 96.6 0.0 96.6 0.0 96.6 0.0 0.0 0.0 96.4 Energy (MMBtu/Bbl ) 0.000 3.628 0.000 3.599 0.000 3.597 0.000 3.594 0.000 0.000 0.000 3.610 All Mogas

Total BPD 3,207,687 3,260,324 1,885,551 2,000,364 1,715,111 1,790,012 687,028 711,484 1,392,425 1,441,990 8,887,802 9,204,175 Ethanol BPD 139875.7 544,167 104378.5 300,212 53779.6 368,259 26352.4 87,238 135235.5 145,656 459621.7 1,445,532 RVP 10.6 11.4 11.5 11.4 10.4 10.5 11.3 11.4 9.6 9.6 10.6 10.9 Sulfur ppm 26.1 23.2 24.5 21.9 26.3 21.2 24.6 27.4 10.1 9.9 23.2 20.8 Density 258.9 260.0 258.4 259.5 259.3 260.8 256.8 258.1 258.7 259.2 258.7 259.8 R+M/2 88.0 89.7 88.0 89.3 88.0 90.9 86.8 87.5 87.7 87.8 87.8 89.4 Aromatics 24.9 19.7 24.9 20.6 26.0 18.2 19.3 15.2 22.6 22.6 24.3 19.7 Benzene 0.62 0.50 0.63 0.50 0.63 0.45 0.80 0.98 0.55 0.55 0.63 0.53 Olefins 14.3 13.2 10.7 10.2 14.2 10.6 8.0 7.4 6.7 6.7 11.8 10.6 Oxygen (wt%) 1.6 6.1 2.0 5.5 1.2 7.5 1.4 4.5 3.6 3.7 1.9 5.8 E200 49.7 60.3 54.5 62.6 48.1 63.2 58.9 64.6 58.1 58.1 52.5 61.4 E300 93.9 95.4 91.5 86.3 93.9 85.6 93.9 90.8 86.2 86.2 92.2 89.7 Energy (MMBtu/Bbl ) 5.061 4.856 4.983 4.850 5.101 4.806 5.004 4.874 4.988 4.999 5.036 4.869 CA US PADD 1 PADD 2 PADD 3 PADD 4/5 ex CA

4.4.2.2 Low Ethanol Control Case

This section contains the tables which summa rizes the costs and other impacts of the low ethanol control case relative to the AE O 2007 and RFS 1 reference cases.

4.4.2.2.1 Low Ethanol Control Case In cremental to the AEO 2007 Reference Case134 This subsection summarizes the costs and othe r impacts of the low ethanol control case relative to the AEO 2007 reference case.

Table 4.4-30 Low Ethanol Control Case Costs without Tax Subsidies Relative to the AEO 2007 Reference Case (2007 dollars, 7% ROI before taxes) Gasoline Diesel Fuel Refinery Model Variable Operating Cost $MM/yr 6,113 - Amortized Refinery Capital Costs $MM/yr -1,138 - Fixed Operating Costs $MM/yr -314 - A dded Gasoline Transportation Cost $MM/yr -42 - E85 Pricing Effect $MM/yr -3,549 - Crude Oil Cost $51 to $116/bbl $MM/yr -7,232 - Lower Energy Density $MM/yr 4,098 2,254 A djustment from Ethanol Price to Cost $MM/yr 648 - FFV Costs $MM/yr 791 Renewable Diesel Cost vs Pe troleum Diesel $MM/yr - -13,962 Total Costs $MM/yr -672 -11,707 Refinery Model Variable Operating Cost c/gal 4.38 - A mortized Refinery Capital Costs c/gal -0.82 - Fixed Operating Costs c/gal -0.22 - A dded Gasoline Transportation Cost c/gal -0.03 - E85 Pricing Effect c/gal -2.54 - Crude Oil Cost $51 to $116/bbl c/gal -5.18 - Lower Energy Density c/gal 2.94 3.16 A djustment from Ethanol Price to Cost c/gal 0.46 - FFV Costs c/gal 0.57 Renewable Diesel Cost vs Pe troleum Diesel c/gal - -19.56 Total Costs c/gal -0.48 -16.40

Table 4.4-31. Low Ethanol Control Case Costs Reflecting Tax Subsidies Relative to the AEO 2007 Reference Case (2007 dollars, 7% ROI before taxes) Gasoline Diesel Fuel Total Costs $MM/yr -672 -11,707 Federal Subsidies $MM/yr -1,597 -10,712 Revised Total Cost $MM/yr -2,269 -22,419 Total Costs c/gal -0.48 -16.40 Federal Subsidies c/gal -1.14 -15.00 Total Costs c/gal -1.63 -31.40135 Table 4.4-32. Summary of the Total and Incremental Volumetric Refinery Inputs by PADD

for the Low Ethanol Control Case Relative to the AEO 2007 Reference Case (barrels/day)

Control Difference Control Difference Control Difference Control Difference Control Difference Case from Ref Case Case from Ref Case Case from Ref Case Case from Ref Case Case from Ref Case PADD Crude 1,279,888 -248,492 3,227,551 -230,937 6,947,777 -303,641 1,418,700 -114,904 1,842,788 -46,607 GTL Naphtha 0 0 0 0 0 0 0 0 0 0 GTL Diesel 0 0 0 0 0 0 0 0 0 0 VGO HS 0 0 0 0 11,581 -32,204 0 0 0 0 VGO LS 0 0 38,063 0 0 0 0 0 0 0 HS AR (A960) 0 0 0 0 0 0 0 0 0 0 LS AR (Alg) 296,982 67,329 0 0 738,419 32,205 0 0 0 0 Normal Butane 22,485 0 55,234 3,579 111,678 25,512 39,858 142 39,573 0 Isobutane 9,412 8,868 15,826 -7,966 617 617 20,399 14,133 0 0 Other 0 0 0 0 0 0 0 0 0 0 MTBE 0 0 0 0 0 0 0 0 0 0 Ethanol - E10 319,378 46,291 200,104 2,203 157,892 -17,825 68,870 -1,520 144,107 1,450 Ethanol - E20 0 0 0 0 0 0 0 0 0 0 Ethanol - E85 25,821 25,821 27,311 27,311 178,439 178,439 18,976 18,976 0 0 Reformer Feed 0 0 0 0 0 0 0 0 0 0 Methanol 0 0 0 0 0 0 0 0 0 0 Natural Gas (FOE) 71,943 -9,163 135,126 -9,516 486,804 -17,483 84,312 -9,585 150,902 -4,765 Hydrogen (MSCF) 0 0 0 0 0 0 0 0 0 0 Pentanes Plus 0 0 32,124 0 52,055 0 18,580 0 0 0 Import CBOB 10% 241,570 235,283 0 0 0 0 0 0 0 0 Import CBOB 20% 0 0 0 0 0 0 0 0 0 0 Import RBOB 10% 107,364 -38,229 0 0 0 0 0 0 0 0 Import RBOB 20% 0 0 0 0 0 0 0 0 0 0 Import Alkylate 19,290 17,057 0 0 0 0 0 0 0 0 Import Raffinate 45,299 -8,228 0 0 0 0 0 0 45,808 0 Import Reformate 0 -8,829 0 0 0 0 0 0 0 0 Import FCC Naphtha 0 0 0 0 0 0 0 0 0 0 Import Lt Naphtha 0 0 0 0 0 0 0 0 584 0 Import Hvy Naph 7,291 7,291 0 0 41,644 0 0 0 0 0 Transfer Lt Naphtha 39,298 34,965 0 0 0 0 0 0 22,233 3,849 Transfer Reformate 9,504 -7,154 0 0 0 0 0 0 0 0 Transfer Alkylate 48,790 -11,210 1,609 1,609 0 0 0 0 60,000 0 Transfer FCC Naphtha 2,408 2,408 20,822 0 0 0 0 0 0 0 Transfer Raffinate 0 0 1,066 -10,571 0 0 0 0 59,963 12,519 Transfer RBOB 10% 242,605 0 37,596 37,596 0 0 0 0 0 0 Transfer RBOB 20% 0 0 0 0 0 0 0 0 0 0 Transfer CBOB 10% 1,289,975 153,702 114,969 60,914 0 0 9,099 2,747 0 0 Transfer CBOB 20% 0 0 0 0 0 0 0 0 0 0 Isooctane 6,030 5,930 100 0 100 0 100 0 13,445 -1,817 Isooctene 24,113 24,013 100 0 100 0 100 0 804 204 CA PADD 1 PADD 2 PADD 3 PADD 4/5 ex CA136 Table 4.4-33. Summary of Total and Incremental Refinery Outputs by PADD for the Low Ethanol Control Case Relative to the AEO 2007 Control Case (barrels/day)

Control Difference Control Difference Control Difference Control Difference Control Difference Case from Ref Case Case from Ref Case Case from Ref Case Case from Ref Case Case from Ref Case Propane 30,661 -1,460 54,531 -2,756 101,580 -15,973 20,156 -2,347 52,426 834 Propylene 18,685 0 42,525 0 245,407 0 2,041 0 11,774 0 Normal Butane 6,350 1,383 2,614 1,650 22,377 -11,285 0 0 0 0 Isobutane 0 0 0 0 0 -411 0 0 41,656 167 PC Naphtha 15,830 0 40,290 0 432,937 0 0 0 0 0 PC Gasoil 0 0 535,896 -24,805 157,500 0 0 0 0 0 CG Reg 0 0 0 0 0 0 0 0 0 0 CG Prem 0 0 0 0 0 -182,001 0 0 0 0 CG E10 Reg 1,684,887 427,937 1,388,234 10,518 878,511 -196,953 569,190 -16,174 95,872 961 CG E10 Prem 168,009 97,675 270,485 8,063 206,925 2,075 112,627 1,129 18,261 183 RFG E10 Reg 1,094,702 -61,416 270,743 2,715 401,267 15,419 0 0 1,102,523 11,057 RFG E10 Prem 214,244 -5,969 51,570 517 76,432 2,937 0 0 210,004 2,106 CG E20 Reg 0 0 0 0 0 0 0 0 0 0 RFG E20 Reg 0 0 0 0 0 0 0 0 0 0 E85 to CG 0 0 31,813 31,813 207,848 207,848 22,103 22,103 0 0 E85 to RFG 30,077 30,077 0 0 0 0 0 0 0 0 Transfer RBOB 10% 0 0 0 0 280,201 37,596 0 0 0 0 Transfer RBOB 20% 0 0 0 0 0 0 0 0 0 0 Transfer CBOB 10% 0 0 0 0 1,414,043 217,363 0 0 0 0 Transfer CBOB 20% 0 0 0 0 0 0 0 0 0 0 Jet/Kero A (450ppm) 70,000 0 143,275 3,194 936,227 0 274,537 0 229,653 0 X-Fer Diesel Rundown to Storage 0 0 0 0 0 0 0 0 0 0 HSD Gr 76 (0.2%) 0 0 0 0 0 0 0 0 0 0 LSD Gr 74 (.05%) 0 0 0 0 0 0 0 0 0 0 ULSD (15 ppm) 487,798 -146,819 552,466 -119,705 1,937,875 -198,428 448,555 -84,744 0 0 CARB Diesel 0 0 0 0 0 0 0 0 313,223 -51,127 X-Fer C5's to Storage 0 0 0 0 0 0 0 0 0 0 1% Residual Fuel 0 0 0 0 0 0 0 0 0 0 Residual Fuel 50,000 -41,643 56,903 -7,686 262,834 0 115,134 -7,157 49,880 0 Slurry 32,981 5,572 76,116 -10,151 106,272 -7,675 20,000 6,518 28,956 -51 Asphalt & Wax 91,682 0 210,000 2,314 157,500 0 5,250 0 41,774 0 Gasoil 0 0 4,895 0 0 0 0 0 9,814 0 Lubes 18,706 0 17,313 0 157,500 0 0 0 20,149 0 Benzene 11,003 0 11,003 0 51,347 0 0 0 0 0 Toluene 0 0 0 0 34,910 0 0 0 0 0 Xylenes 0 0 0 0 7,777 0 0 0 0 0 Cumene 0 0 0 0 0 0 0 0 0 0 Other 0 0 0 0 0 0 0 0 0 0 Cyclohexane 0 0 0 0 0 0 0 0 0 0 Transfer Raffinate 0 0 0 0 61,029 1,948 0 0 0 0 Transfer Alkylate 0 0 0 0 110,399 -9,601 0 0 0 0 Transfer Reformate 0 0 0 0 9,504 -7,154 0 0 0 0 Transfer FCC naphtha 0 0 0 0 34,440 13,618 0 0 0 0 Transfer Lt Naphtha 0 0 0 0 28,088 23,755 0 0 22,233 3,849 Transfer Blendstock 0 0 0 0 0 0 0 0 0 0 Sulfur (STons) 1,034 -120 3,768 -345 11,741 -657 1,880 -207 3,459 -86 Coke (STon) 3,201 -749 10,908 -1,818 46,210 -3,591 7,111 -1,368 16,750 -544 PADD 1 PADD 2 PADD 3 PADD 4/5 ex CA CA137 Table 4.4-34. Change in Refinery Unit Capacities by PADD for the Low Ethanol Control Case Relative to the AEO 2007 Control Case (thousand barrels/day) PADD 1 PADD 2 PADD 3 PADD 4/5 ex CA California US Total Crude Tower 0 -175 0 0 0 -175 Vacuum Tower 0 -78 0 0 0 -78 Sats Gas Plant -12 0 -13 0 6 -18 Unsats Gas Plant 1 0 0 0 0 1 FCC DeC5 Tower 0 0 0 0 0 0 FCC 0 0 0 0 0 0 FCC Splitter 4 -6 0 0 0 -2 Hydrocracker -16 0 0 -33 0 -49 H-Oil Unit 0 0 0 0 0 0 Delayed Coker 0 0 0 -24 0 -24 Visbreaker 0 0 0 0 0 0 Thermal Naphtha Splitter -1 -4 0 -1 0 -6 CRU Reformer 0 0 0 0 0 0 SRU Reformer 0 0 0 0 -9 -9 BTX Reformer 0 7 -6 0 0 1 C4 Isomerization 0 0 0 0 1 1 C5/C6 Isomerization 21 0 0 0 0 21 HF Alkylation 0 0 0 0 0 0 H2SO4 Alkylation -14 0 0 15 0 0 Dimersol 0 0 0 0 0 0 Cat Pol y 600 006 Isooctane 0 0 0 0 0 0 DHT - Total -136 0 -213 -61 0 -410 DHT 2nd RCT - Total -127 -150 -220 -63 -10 -571 DHT Arom Saturation 0 0 0 0 0 0 NHT - Total Fd 0 0 0 0 0 0 CGH - Generic 24 -10 -17 -3 0 -6 CGH - Olefin Sat'n 0 0 0 0 0 0 FCCU Fd HDT 57 0 0 0 0 57 LSR Splitter 0 0 0 0 0 0 LSR Bz Saturator 0 0 0 0 0 0 Reformate Saturator -14 -9 1 0 0 -22 Reformate Splitter -43 -27 3 0 0 -66 SDA 0 0 0 0 0 0 MTBE 0 0 0 0 0 0 TAME 0 0 0 0 0 0 Hydrogen Plant - Total MSC -79 -52 -149 -101 0 -381 Lube Unit 0 0 0 0 0 0 Sulfur Plant -95 0 0 -264 -73 -432 Merox Jet 0 0 0 0 0 0 Merox Diesel 0 0 0 0 0 0 BTX Reformer - Tower feed 0 0 0 0 0 0 BTX Reformer - Extract fee d 000 000138 Table 4.4-35. Change in Refinery Unit Investments by PADD for the Low Ethanol Control Case Relative to the AEO 2007 Control Case (million dollars/year) PADD 1 PADD 2 PADD 3 PADD 4/5 ex CA California US Total Crude Tower 0 -372 0 0 0 -372 Vacuum Tower 0 -297 0 0 0 -297 Sats Gas Plant -65 0 -24 0 48 -41 Unsats Gas Plant 6 0 0 0 0 6 FCC DeC5 Tower 0 0 0 0 0 0 FCC 0 0 0 0 0 0 FCC Splitter 2 -7 0 0 0 -5 Hydrocracker -584 0 0 -891 0 -1,475 H-Oil Unit 0 0 0 0 0 0 Delayed Coker 0 0 0 -534 0 -534 Visbreaker 0 0 0 0 0 0 Thermal Naphtha Splitter -3 -3 0 -2 0 -9 CRU Reformer 0 0 0 0 0 0 SRU Reformer 0 0 0 0 -66 -66 BTX Reformer 0 70 -38 0 0 32 C4 Isomerization 0 0 0 0 5 5 C5/C6 Isomerization 184 0 0 0 0 184 HF Alkylation 0 0 0 0 0 0 H2SO4 Alkylation -245 0 0 274 0 29 Dimersol 0 0 0 0 0 0 Cat Pol y 48 0 0 0 0 48 Isooctane 0 0 0 0 0 0 DHT - Total -1,394 0 -1,511 -606 0 -3,510 DHT 2nd RCT - Total -949 -985 -1,103 -443 -57 -3,536 DHT Arom Saturation 0 0 0 0 0 0 NHT - Total Fd 0 0 0 0 0 0 CGH - Generic 157 -88 -87 -12 0 -29 CGH - Olefin Sat'n 0 0 0 0 0 0 FCCU Fd HDT 709 0 0 0 0 709 LSR Splitter 0 0 0 0 0 0 LSR Bz Saturator 0 0 0 0 0 0 Reformate Saturator -94 -60 5 0 0 -149 Reformate Splitter -55 -36 2 0 0 -88 SDA 0 0 0 0 0 0 MTBE 0 0 0 0 0 0 TAME 0 0 0 0 0 0 Hydrogen Plant - Total MSC -324 -172 -385 -363 0 -1,244 Lube Unit 0 0 0 0 0 0 Sulfur Plant -3 0 0 -2 -2 -7 Merox Jet 0 0 0 0 0 0 Merox Diesel 0 0 0 0 0 0 BTX Reformer - Tower feed 0 1 0 0 0 1 BTX Reformer - Extract fee d 000 000 Total -2,609 -1,948 -3,141 -2,578 -72 -10,349139 Table 4.4-36. Projected Total U.S. Capital Investments for the Low Ethanol Control Case Relative to the AEO 2007 Reference Case (billion dollars) Cost Type Plant Type Capital Investments Corn Ethanol 3.9 Cellulosic Ethanol 0 Cellulosic Diesel a 96.5 Production Costs

Renewable Diesel and Algae 1.1

All Ethanol 5.6 Cellulosic and Renewable Diesel Fuel 2.0 Distribution Costs

Biodiesel 1.2 FFV Costs 0.8 Refining -10.3 Total Capital Investments 110.0140 Table 4.4-37. Ethanol and Gasoline Volume, Quality and Energy Density by Gasoline Type at the PADD Terminal for the Low Ethanol Control Case Relative to the AEO 2007 Control Case

Ref Case Control Ref Case Control Ref Case Control R ef Case Control Ref Case Control Ref Case Control RFG

Total ('000 BPD) 1,376,331 1,308,946 319,080 322,313 459,343 477,699 0 0 1,299,365 1,312,528 3,454,120 3,421,486 Ethanol ('000 BPD) 139,023 132,217 32,230 32,557 46,397 48,252 0 0 131,244 132,579 348,895 345,605 RVP (psi) 10.8 10.7 10.6 10.6 9.7 9.7 0.0 0.0 9.5 9.5 10.1 10.1 Sulfur (ppm) 24.4 24.5 20.0 20.7 23.2 24.1 0.0 0.0 8.8 8.8 18.0 18.0 Density 258.9 258.6 258.2 258.2 259.5 258.5 0.0 0.0 258.5 258.7 258.8 258.6 Octane (R+M/2) 88.1 88.1 88.0 88.0 88.0 88.0 0.0 0.0 87.6 87.6 87.9 87.9 Aromatics (vol%) 19.9 19.8 19.9 19.9 19.6 18.5 0.0 0.0 22.2 22.1 20.7 20.5 Benzene (vol%) 0.57 0.56 0.57 0.57 0.56 0.56 0.00 0.00 0.53 0.54 0.55 0.55 Olefins (vol%) 13.6 14.8 9.4 9.1 11.5 11.2 0.0 0.0 5.7 5.7 10.0 10.2 Oxygen (wt%) 3.7 3.7 3.7 3.7 3.7 3.7 0.0 0.0 3.7 3.7 3.7 3.7 E200 (vol%) 55.6 54.8 58.3 57.6 53.3 53.7 0.0 0.0 58.2 58.3 56.5 56.3 E300 (vol%) 93.9 82.3 93.9 91.1 93.9 93.9 0.0 0.0 86.2 86.2 91.0 86.2 Energy (MMBtu/Bbl) 4.947 4.953 4.924 4.939 4.981 4.973 0.000 0.000 4.994 5.000 4.967 4.972 CG

Total ('000 BPD) 1,830,582 1,852,896 1,640,138 1,658,720 1,280,314 1,085,436 696,861 681,817 112,988 114,133 5,560,884 5,393,001 Ethanol ('000 BPD) 134,064 187,161 165,671 167,547 129,320 109,640 70,390 68,870 11,413 11,529 510,857 544,748 RVP (psi) 11.4 11.8 11.6 11.5 10.7 10.5 11.4 11.4 10.6 10.6 11.3 11.4 Sulfur (ppm) 22.9 24.2 23.6 23.6 23.1 23.0 28.0 28.0 26.6 26.0 23.9 24.3 Density 258.9 258.9 259.1 258.9 260.5 259.6 258.1 257.6 262.7 263.4 259.3 259.0 Octane (R+M/2) 87.8 87.7 88.0 88.0 88.0 88.1 86.9 86.9 89.3 89.4 87.8 87.8 Aromatics (vol%) 23.1 22.4 22.5 22.5 22.4 21.8 15.9 15.2 26.5 27.6 21.9 21.5 Benzene (vol%) 0.53 0.52 0.53 0.53 0.51 0.51 1.05 1.03 0.59 0.63 0.59 0.59 Olefins (vol%) 13.2 13.9 11.0 10.8 13.1 11.9 8.5 7.6 17.8 17.5 12.0 11.8 Oxygen (wt%) 2.7 3.7 3.7 3.7 3.7 3.7 3.7 3.7 3.7 3.7 3.4 3.7 E200 (vol%) 52.5 52.9 58.8 58.5 53.0 52.5 63.0 63.1 58.0 57.2 55.9 55.9 E300 (vol%) 93.9 79.3 93.9 84.0 93.9 79.3 93.9 91.0 86.2 86.2 93.7 82.4 Energy (MMBtu/Bbl) 4.995 4.966 4.925 4.939 4.988 4.990 4.907 4.942 4.946 4.961 4.955 E85

Total ('000 BPD) 0 30,077 0 31,813 0 207,848 0 22,103 0 0 0 291,840 Ethanol ('000 BPD) 0 25,821 0 27,311 0 178,439 0 18,976 0 0 0 250,548 RVP (psi) 0.0 12.9 0.0 12.2 0.0 12.1 0.0 11.9 0.0 0.0 0.0 12.1 Sulfur (ppm) 0.0 8.9 0.0 8.8 0.0 8.8 0.0 8.8 0.0 0.0 0.0 8.8 Density 0.0 266.0 0.0 266.3 0.0 266.2 0.0 266.1 0.0 0.0 0.0 266.2 Octane (R+M/2) 0.0 108.1 0.0 108.0 0.0 107.9 0.0 107.9 0.0 0.0 0.0 108.0 Aromatics (vol%) 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Benzene (vol%) 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Olefins (vol%) 0.0 3.0 0.0 3.0 0.0 1.3 0.0 0.0 0.0 0.0 0.0 1.5 Oxygen (wt%) 0.0 30.8 0.0 30.8 0.0 30.8 0.0 30.8 0.0 0.0 0.0 30.8 E200 (vol%) 0.0 130.1 0.0 130.1 0.0 129.7 0.0 129.3 0.0 0.0 0.0 129.7 E300 (vol%) 0.0 96.6 0.0 96.6 0.0 96.6 0.0 96.6 0.0 0.0 0.0 96.6 Energy (MMBtu/Bbl) 0.000 3.591 0.000 3.599 0.000 3.596 0.000 3.594 0.000 0.000 0.000 3.596 All Mogas

Total BPD 3,206,913 3,191,919 1,959,219 2,012,845 1,739,657 1,770,983 696,861 703,921 1,412,353 1,426,660 9,015,003 9,106,327 Ethanol BPD 273,087 345,199 197,901 227,416 175,717 336,332 70,390 87,846 142,657 144,107 859,752 1,140,900 RVP 11.1 11.4 11.4 11.4 10.4 10.5 11.4 11.4 9.6 9.6 10.8 10.9 Sulfur ppm 24 24 23 23 23 22 28 27 10 10 22 21 Density 259 259 259 259 260 260 258 258 259 259 259 259 R+M/2 87.9 88.0 88.0 88.3 88.0 90.4 86.9 87.6 87.8 87.8 87.8 88.5 Aromatics 21.7 21.1 22.1 21.7 21.7 18.3 15.9 14.8 22.5 22.6 21.5 20.4 Benzene 0.55 0.53 0.53 0.52 0.53 0.46 1.05 1.00 0.54 0.55 0.58 0.56 Olefins 13.4 14.1 10.7 10.4 12.7 10.5 8.5 7.4 6.7 6.6 11.2 10.9 Oxygen (wt%) 3.1 4.0 3.7 4.2 3.7 7.0 3.7 4.6 3.7 3.7 3.5 4.6 E200 53.8 54.4 58.7 59.5 53.1 61.9 63.0 65.2 58.2 58.2 56.1 58.4 E300 93.9 80.7 93.9 85.3 93.9 85.3 93.9 91.2 86.2 86.2 92.7 84.3 Energy (MMBtu/Bbl) 4.974 4.948 4.925 4.918 4.986 4.822 4.913 4.866 4.990 4.995 4.963 4.918 CA US PADD 1 PADD 2 PADD 3 PADD 4/5 ex CA

4.4.2.2.2 Low Ethanol Control Case In cremental to the RFS 1 Reference Case

This subsection summarizes the gasoline and diesel fuel co sts and other impacts of the low ethanol control case relative to the RFS1 reference case.141 Table 4.4-38. Low Ethanol Control Case Costs without Tax Subsidies Relative to the RFS 1 Reference Case (2007 dollars, 7% ROI before taxes) Gasoline Diesel Fuel Refinery Model Variable Operating Cost $MM/yr 6,289 - Amortized Refinery Capital Costs $MM/yr -1,172 - Fixed Operating Costs $MM/yr -323 - A dded Gasoline Transportation Cost $MM/yr -102 - E85 Pricing Effect $MM/yr -3,549 - Crude Oil Cost $51 to $116/bbl $MM/yr -17,805 - Lower Energy Density $MM/yr 10,917 2,283 A djustment from Ethanol Price to Cost $MM/yr 1,108 - FFV Costs $MM/yr 1,516 Renewable Diesel Cost vs Pe troleum Diesel $MM/yr - -14,071 Total Costs $MM/yr -3,121 -11,788 Refinery Model Variable Operating Cost c/gal 4.50 - A mortized Refinery Capital Costs c/gal -0.84 - Fixed Operating Costs c/gal -0.23 - A dded Gasoline Transportation Cost c/gal -0.07 - E85 Pricing Effect c/gal -2.54 - Crude Oil Cost $51 to $116/bbl c/gal -12.75 - Lower Energy Density c/gal 7.82 3.19 A djustment from Ethanol Price to Cost c/gal 0.79 - FFV Costs c/gal 1.09 Renewable Diesel Cost vs Pe troleum Diesel c/gal - -19.69 Total Costs c/gal -2.24 -16.49

Table 4.4-39. Low Ethanol Control Case Costs Reflecting Tax Subsidies Relative to the RFS 1 Reference Case (2007 dollars, 7% ROI before taxes) Gasoline Diesel Fuel Total Costs $MM/yr -3,121 -11,788 Federal Subsidies $MM/yr -4,358 -10,794 Revised Total Cost $MM/yr -7479 -22,582 Total Costs c/gal -2.24 -16.49 Federal Subsidies c/gal -3.12 -15.10 Total Costs c/gal -5.36 -31.60142 Table 4.4-40. Summary of the Total and Incremental Volumetric Refinery Inputs by PADD (barrels/day)

Control Difference Control Difference Control Difference Control Difference Control Difference Case from Ref Case Case from Ref Case Case from Ref Case Case from Ref Case Case from Ref Case PADD Crude 1,279,888 -219,169 3,227,551 -306,429 6,947,777 -410,791 1,418,700 -120,278 1,842,788 -44,705 GTL Naphtha 0 0 0 0 0 0 0 0 0 0 GTL Diesel 0 0 0 0 0 0 0 0 0 0 VGO HS 0 0 0 0 11,581 -22,191 0 0 0 0 VGO LS 0 0 38,063 6,229 0 0 0 0 0 0 HS AR (A960) 0 0 0 0 0 0 0 0 0 0 LS AR (Alg) 296,982 57,053 0 0 738,419 22,191 0 0 0 0 Normal Butane 22,485 0 55,234 -3,874 111,678 28,274 39,858 415 39,573 0 Isobutane 9,412 9,412 15,826 -9,041 617 617 20,399 -3,024 0 0 Other 0 0 0 0 0 0 0 0 0 0 MTBE 0 0 0 0 0 0 0 0 0 0 Ethanol - E10 319,378 179,502 200,104 95,726 157,892 104,113 68,870 42,518 144,107 8,872 Ethanol - E20 0 0 0 0 0 0 0 0 0 0 Ethanol - E85 25,821 25,821 27,311 27,311 178,439 178,439 18,976 18,976 0 0 Reformer Feed 0 0 0 0 0 0 0 0 0 0 Methanol 0 0 0 0 0 0 0 0 0 0 Natural Gas (FOE) 71,943 -8,373 135,126 -6,941 486,804 126 84,312 -5,329 150,902 -5,574 Hydrogen (MSCF) 0 0 0 0 0 0 0 0 0 0 Pentanes Plus 0 0 32,124 0 52,055 0 18,580 1,113 0 0 Import CBOB 10% 241,570 241,570 0 0 0 0 0 0 0 0 Import CBOB 20% 0 0 0 0 0 0 0 0 0 0 Import RBOB 10% 107,364 -92,636 0 0 0 0 0 0 0 0 Import RBOB 20% 0 0 0 0 0 0 0 0 0 0 Import Alkylate 19,290 19,290 0 0 0 0 0 0 0 0 Import Raffinate 45,299 -19,291 0 0 0 0 0 0 45,808 0 Import Reformate 0 0 0 0 0 0 0 0 0 0 Import FCC Naphtha 0 0 0 0 0 0 0 0 0 0 Import Lt Naphtha 0 0 0 0 0 0 0 0 584 0 Import Hvy Naph 7,291 7,291 0 0 41,644 0 0 0 0 0 Transfer Lt Naphtha 39,298 15,956 0 -20,822 0 0 0 0 22,233 1,004 Transfer Reformate 9,504 -7,154 0 -14,074 0 0 0 0 0 0 Transfer Alkylate 48,790 6,171 1,609 1,609 0 0 0 0 60,000 16,933 Transfer FCC Naphtha 2,408 2,408 20,822 20,822 0 0 0 0 0 0 Transfer Raffinate 0 0 1,066 -16,175 0 0 0 0 59,963 11,040 Transfer RBOB 10% 242,605 0 37,596 37,596 0 0 0 0 0 0 Transfer RBOB 20% 0 0 0 0 0 0 0 0 0 0 Transfer CBOB 10% 1,289,975 1,273,399 114,969 112,012 0 0 9,099 -16,933 0 0 Transfer CBOB 20% 0 0 0 0 0 0 0 0 0 0 Isooctane 6,030 5,930 100 0 100 0 100 0 13,445 -988 Isooctene 24,113 24,013 100 0 100 0 100 0 804 204 CA PADD 1 PADD 2 PADD 3 PADD 4/5 ex CA143 Table 4.4-41. Summary of Total and Incremental Refinery Outputs by PADD for the Low Ethanol Control Case Relative to the RFS 1 Control Case (barrels/day)

Control Difference Control Difference Control Difference Control Difference Control Difference Case from Ref Case Case from Ref Case Case from Ref Case Case from Ref Case Case from Ref Case Propane 30,661 -1,943 54,531 -8,575 101,580 -33,628 20,156 -4,754 52,426 1,106 Propylene 18,685 0 42,525 0 245,407 0 2,041 0 11,774 0 Normal Butane 6,350 -1,482 2,614 244 22,377 -23,129 0 0 0 0 Isobutane 0 0 0 0 0 -345 0 0 41,656 6,653 PC Naphtha 15,830 0 40,290 0 432,937 0 0 0 0 0 PC Gasoil 0 0 535,896 -28,380 157,500 0 0 0 0 0 CG Reg 0 -118,066 0 -852,131 0 -2,020,447 0 -374,129 0 -53,481 CG Prem 0 0 0 0 0 -416,926 0 -51,984 0 0 CG E10 Reg 1,684,887 1,666,651 1,388,234 920,748 878,511 878,511 569,190 352,027 95,872 55,782 CG E10 Prem 168,009 168,009 270,485 19,129 206,925 127,328 112,627 68,875 18,261 438 RFG E10 Reg 1,094,702 -53,295 270,743 6,497 401,267 20,863 0 0 1,102,523 26,457 RFG E10 Prem 214,244 -4,422 51,570 1,238 76,432 3,974 0 0 210,004 5,040 CG E20 Reg 0 0 0 0 0 0 0 0 0 0 RFG E20 Reg 0 0 0 0 0 0 0 0 0 0 E85 to CG 0 0 31,813 31,813 207,848 207,848 22,103 22,103 0 0 E85 to RFG 30,077 30,077 0 0 0 0 0 0 0 0 Transfer RBOB 10% 0 0 0 0 280,201 37,596 0 0 0 0 Transfer RBOB 20% 0 0 0 0 0 0 0 0 0 0 Transfer CBOB 10% 0 0 0 0 1,414,043 1,368,478 0 0 0 0 Transfer CBOB 20% 0 0 0 0 0 0 0 0 0 0 Jet/Kero A (450ppm) 70,000 0 143,275 1,643 936,227 0 274,537 0 229,653 0 X-Fer Diesel Rundown t 0 00 0 0 0 0 0 0 0 HSD Gr 76 (0.2%) 0 0 0 0 0 0 0 0 0 0 LSD Gr 74 (.05%) 0 0 0 0 0 0 0 0 0 0 ULSD (15 ppm) 487,798 -138,408 552,466 -121,092 1,937,875 -210,603 448,555 -85,599 0 0 CARB Diesel 0 0 0 0 0 0 0 0 313,223 -51,643 X-Fer C5's to Storage 0 0 0 0 0 0 0 0 0 0 1% Residual Fuel 0 0 0 0 0 0 0 0 0 0 Residual Fuel 50,000 -39,764 56,903 -10,915 262,834 0 115,134 -316 49,880 0 Slurr y 32,981 6,831 76,116 -10,892 106,272 -10,322 20,000 3,494 28,956 254 Asphalt & Wax 91,682 0 210,000 0 157,500 0 5,250 0 41,774 0 Gasoil 0 0 4,895 0 0 0 0 0 9,814 0 Lubes 18,706 0 17,313 0 157,500 0 0 0 20,149 0 Benzene 11,003 0 11,003 0 51,347 0 0 0 0 0 Toluene 0 0 0 0 34,910 0 0 0 0 0 Xylenes 0 0 0 0 7,777 0 0 0 0 0 Cumene 0 0 0 0 0 0 0 0 0 0 Other 0 0 0 0 0 0 0 0 0 0 Cyclohexane 0 0 0 0 0 0 0 0 0 0 Transfer Raffinate 0 0 0 0 61,029 -5,135 0 0 0 0 Transfer Alkylate 0 0 0 0 110,399 24,713 0 0 0 0 Transfer Reformate 0 0 0 0 9,504 9,504 0 0 0 0 Transfer FCC naphtha 0 0 0 0 34,440 34,440 0 0 0 0 Transfer Lt Naphtha 0 0 0 0 28,088 4,746 0 0 22,233 1,004 Transfer Blendstock 0 0 0 0 0 0 0 0 0 0 Sulfur (STons) 1,034 -115 3,768 -433 11,741 -834 1,880 -216 3,459 -110 Coke (STon) 3,201 -520 10,908 -2,313 46,210 -4,714 7,111 -1,577 16,750 -523 PADD 1 PADD 2 PADD 3 PADD 4/5 ex CA CA144 Table 4.4-42. Change in Refinery Unit Capacities by PADD for the Low Ethanol Control Case Relative to the RFS 1 Control Case (thousand barrels/day) PADD 1 PADD 2 PADD 3 PADD 4/5 ex CA California US Total Crude Tower 0 -200 0 0 0 -200 Vacuum Tower 0 -89 0 -2 0 -92 Sats Gas Plant 4 0 -40 0 7 -29 Unsats Gas Plant 0 0 0 0 0 0 FCC DeC5 Tower 0 0 0 0 0 0 FCC 0 0 0 -8 0 -8 FCC Splitte r 2 -6 0 0 0 -5 Hydrocracke r -18 0 0 -26 0 -45 H-Oil Unit 0 0 0 0 0 0 Delayed Coker 0 0 0 -28 0 -28 Visbreake r 00 0 0 00 Thermal Naphtha Splitter -1 -4 0 -1 0 -6 CRU Reforme r 00 0 0 00 SRU Reformer 0 0 0 0 -5 -5 BTX Reforme r 0 -3 -14 0 0 -16 C4 Isomerization 0 0 0 0 1 1 C5/C6 Isomerization 25 0 0 0 0 25 HF Alkylation 0 0 0 0 0 0 H2SO4 Alkylation 1 0 0 -3 0 -2 Dimersol 0 0 0 0 0 0 Cat Poly 0 0 0 0 0 0 Isooctane 0 0 0 0 0 0 DHT - Total -137 0 -241 -62 -4 -444 DHT 2nd RCT - Total -126 -187 -248 -64 -10 -637 DHT Arom Saturation 0 0 0 0 0 0 NHT - Total Fd 0 0 0 -4 0 -4 CGH - Generic 28 -6 -30 -7 0 -15 CGH - Olefin Sat'n 0 0 0 0 0 0 FCCU Fd HDT 39 0 0 0 0 39 LSR Splitter 0 41 38 0 0 80 LSR Bz Saturator 0 0 0 0 0 0 Reformate Saturator -4 -9 1 0 0 -13 Reformate Splitte r -13 -27 3 0 0 -38 SDA 0 0 0 0 0 0 MTBE 0 0 0 0 0 0 TAME 0 0 0 0 0 0 Hydrogen Plant - Total MSCF -62 31 44 -77 0 -64 Lube Unit 0 0 0 0 0 0 Sulfur Plant -128 0 0 -264 -75 -467 Merox Jet 0 0 0 0 0 0 Merox Diesel 0 0 0 0 0 0 BTX Reformer - Tower feed 0 -1 0 0 0 -1 BTX Reformer - Extract feed -1 0 0 0 0 -1145 Table 4.4-43. Change in Refinery Unit Investments by PADD for the Low Ethanol Control Case Relative to the RFS 1 Control Case (million dollars/year) PADD 1 PADD 2 PADD 3 PADD 4/5 ex CA California US Total Crude Tower 0 -408 0 0 0 -408 Vacuum Tower 0 -317 0 0 0 -317 Sats Gas Plant 14 0 -120 0 50 -57 Unsats Gas Plant -1 0 0 0 0 -1 FCC DeC5 Tower 0 0 0 0 0 0 FCC 0 0 0 -193 0 -193 FCC Splitte r 1 -7 0 0 0 -6 Hydrocracke r -631 0 0 -755 0 -1,386 H-Oil Unit 0 0 0 0 0 0 Delayed Coker 0 0 0 -592 0 -592 Visbreaker 0 0 0 0 0 0 Thermal Naphtha Splitter -3 -3 0 -3 0 -10 CRU Reforme r 00 0 0 00 SRU Reformer 0 0 0 0 -40 -40 BTX Reforme r 0 -22 -206 0 0 -229 C4 Isomerization 0 0 0 0 7 7 C5/C6 Isomerization 224 0 0 0 0 224 HF Alkylation 0 0 0 0 0 0 H2SO4 Alkylation 17 0 0 -42 0 -25 Dimersol 0 0 0 0 0 0 Cat Poly -1 0 0 0 0 -1 Isooctane 0 0 0 0 0 0 DHT - Total -1,397 0 -1,716 -614 -96 -3,822 DHT 2nd RCT - Total -948 -1,212 -1,249 -447 -57 -3,913 DHT Arom Saturation 0 0 0 0 0 0 NHT - Total Fd 0 0 0 -46 0 -46 CGH - Generic 175 -20 -119 -29 0 7 CGH - Olefin Sat'n 0 0 0 0 0 0 FCCU Fd HDT 569 0 0 0 0 569 LSR Splitter 0 29 18 0 0 47 LSR Bz Saturator 0 0 0 0 0 0 Reformate Saturato r -48 -60 4 0 0 -104 Reformate Splitte r -21 -36 2 0 0 -55 SDA 0 0 0 0 0 0 MTBE 0 0 0 0 0 0 TAME 0 0 0 0 0 0 Hydrogen Plant - Total MSCF -227 118 117 -298 0 -290 Lube Unit 0 0 0 0 0 0 Sulfur Plant -3 0 0 -2 -2 -7 Merox Jet 0 0 0 0 0 0 Merox Diesel 0 0 0 0 0 0 BTX Reformer - Tower feed 0 -1 -1 0 0 -2 BTX Reformer - Extract feed -3 0 0 0 0 -3 Total -2,285 -1,938 -3,272 -3,021 -138 -10,654146 Table 4.4-44. Ethanol and Gasoline Volume, Quality and Energy Density by Gasoline Type at the PADD Terminal for the Low Ethanol Control Case Relative to the RFS 1 Control Case

Ref Case Control Ref Case Control Ref Case Control Ref Case Control Ref Case Control Ref Case Control RFG

Total ('000 BPD) 1,366,663 1,308,946 314,578 322,313 452,862 477,699 0 0 1,281,031 1,312,528 3,415,134 3,421,486 Ethanol ('000 BPD) 138,034 132,217 31,773 32,557 45,739 48,252 0 0 129,386 132,579 344,932 345,605 RVP (psi) 10.7 10.7 10.3 10.6 9.6 9.7 0.0 0.0 9.5 9.5 10.1 10.1 Sulfur (ppm) 23.8 24.5 20.1 20.7 23.5 24.1 0.0 0.0 8.7 8.8 17.8 18.0 Density 258.5 258.6 256.2 258.2 259.1 258.5 0.0 0.0 258.5 258.7 258.4 258.6 Octane (R+M/2) 88.1 88.1 88.0 88.0 88.0 88.0 0.0 0.0 87.6 87.6 87.9 87.9 Aromatics (vol%) 19.9 19.8 18.2 19.9 19.5 18.5 0.0 0.0 22.2 22.1 20.5 20.5 Benzene (vol%) 0.57 0.56 0.57 0.57 0.57 0.56 0.00 0.00 0.54 0.54 0.56 0.55 Olefins (vol%) 13.1 14.8 8.0 9.1 9.3 11.2 0.0 0.0 5.7 5.7 9.3 10.2 Oxygen (wt%) 3.7 3.7 3.8 3.7 3.7 3.7 0.0 0.0 3.7 3.7 3.7 3.7 E200 (vol%) 55.7 54.8 62.5 57.6 54.5 53.7 0.0 0.0 58.5 58.3 57.2 56.3 E300 (vol%) 93.9 82.3 91.5 91.1 93.9 93.9 0.0 0.0 86.2 86.2 90.8 86.2 Energy (MMBtu/Bbl ) 4.963 4.953 4.864 4.939 5.027 4.973 0.000 0.000 4.988 5.000 4.971 4.972 CG

Total ('000 BPD) 1,841,024 1,852,896 1,570,973 1,658,720 1,262,249 1,085,436 687,028 681,817 111,394 114,133 5,472,668 5,393,001 Ethanol ('000 BPD) 1,842 187,161 72,606 167,547 8,040 109,640 26,352 68,870 5,849 11,529 114,689 544,748 RVP (psi) 10.5 11.8 11.8 11.5 10.7 10.5 11.3 11.4 10.8 10.6 11.0 11.4 Sulfur (ppm) 27.8 24.2 25.3 23.6 27.3 23.0 24.6 28.0 26.4 26.0 26.6 24.3 Density 259.3 258.9 258.8 258.9 259.4 259.6 256.8 257.6 260.8 263.4 258.9 259.0 Octane (R+M/2) 88.0 87.7 88.0 88.0 88.0 88.1 86.8 86.9 88.0 89.4 87.8 87.8 Aromatics (vol%) 28.7 22.4 26.3 22.5 28.4 21.8 19.3 15.2 26.8 27.6 26.7 21.5 Benzene (vol%) 0.65 0.52 0.64 0.53 0.65 0.51 0.80 1.03 0.62 0.63 0.67 0.59 Olefins (vol%) 15.2 13.9 11.2 10.8 16.0 11.9 8.0 7.6 18.6 17.5 13.4 11.8 Oxygen (wt%) 0.0 3.7 1.7 3.7 0.2 3.7 1.4 3.7 1.9 3.7 0.8 3.7 E200 (vol%) 45.2 52.9 52.9 58.5 45.9 52.5 58.9 63.1 54.5 57.2 49.5 55.9 E300 (vol%) 93.9 79.3 91.5 84.0 93.9 79.3 93.9 91.0 86.2 86.2 93.0 82.4 Energy (MMBtu/Bbl ) 5.133 4.966 5.007 4.939 5.127 4.990 5.004 4.907 4.998 4.946 5.077 4.955 E85

Total ('000 BPD) 0 30,077 0 31,813 0 207,848 0 22,103 0 0 0 291,840 Ethanol ('000 BPD) 0 25,821 0 27,311 0 178,439 0 18,97 6 0 0 0 250,548 RVP (psi) 0.0 12.9 0.0 12.2 0.0 12.1 0.0 11.9 0.0 0.0 0.0 12.1 Sulfur (ppm) 0.0 8.9 0.0 8.8 0.0 8.8 0.0 8.8 0.0 0.0 0.0 8.8 Density 0.0 266.0 0.0 266.3 0.0 266.2 0.0 266.1 0.0 0.0 0.0 266.2 Octane (R+M/2) 0.0 108.1 0.0 108.0 0.0 107.9 0.0 107.9 0.0 0.0 0.0 108.0 Aromatics (vol%) 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Benzene (vol%) 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Olefins (vol%) 0.0 3.0 0.0 3.0 0.0 1.3 0.0 0.0 0.0 0.0 0.0 1.5 Oxygen (wt%) 0.0 30.8 0.0 30.8 0.0 30.8 0.0 30.8 0.0 0.0 0.0 30.8 E200 (vol%) 0.0 130.1 0.0 130.1 0.0 129.7 0.0 129.3 0.0 0.0 0.0 129.7 E300 (vol%) 0.0 96.6 0.0 96.6 0.0 96.6 0.0 96.6 0.0 0.0 0.0 96.6 Energy (MMBtu/Bbl ) 0.000 3.591 0.000 3.599 0.000 3.596 0.000 3.594 0.000 0.000 0.000 3.596 All Mogas

Total BPD 3,207,687 3,191,919 1,885,551 2,012,845 1,715,111 1,770,983 687,028 703,921 1,392,425 1,426,660 8,887,802 9,106,327 Ethanol BPD 139,876 345,199 104,378 227,416 53,780 336,332 26,352 87,846 135,236 144,107 459,622 1,140,900 RVP 10.6 11.4 11.5 11.4 10.4 10.5 11.3 11.4 9.6 9.6 10.6 10.9 Sulfur ppm 26.1 24.2 24.5 22.9 26.3 21.6 24.6 27.4 10.1 10.2 23.2 21.4 Density 258.9 258.9 258.4 258.9 259.3 260.1 256.8 257.9 258.7 259.1 258.7 259.1 R+M/2 88.0 88.0 88.0 88.3 88.0 90.4 86.8 87.6 87.7 87.8 87.8 88.5 Aromatics 24.9 21.1 24.9 21.7 26.0 18.3 19.3 14.8 22.6 22.6 24.3 20.4 Benzene 0.62 0.53 0.63 0.52 0.63 0.46 0.80 1.00 0.55 0.55 0.63 0.56 Olefins 14.3 14.1 10.7 10.4 14.2 10.5 8.0 7.4 6.7 6.6 11.8 10.9 Oxygen (wt%) 1.6 4.0 2.0 4.2 1.2 7.0 1.4 4.6 3.6 3.7 1.9 4.6 E200 49.7 54.4 54.5 59.5 48.1 61.9 58.9 65.2 58.1 58.2 52.5 58.4 E300 93.9 80.7 91.5 85.3 93.9 85.3 93.9 91.2 86.2 86.2 92.2 84.3 Energy (MMBtu/Bbl ) 5.061 4.948 4.983 4.918 5.101 4.822 5.004 4.866 4.988 4.995 5.036 4.918 CA US PADD 1 PADD 2 PADD 3 PADD 4/5 ex CA

4.4.2.3 High Ethanol Control Case

This section summarizes the costs and other impacts of the high ethanol control case relative to the AEO 2007 and RFS 1 reference cas es. This case assumes that the cellulosic biofuel standard would be me t solely through the production and use of cellulosic ethanol.147 4.4.2.3.1 High Ethanol Control Case Relative to the AEO 2007 Reference Case

This subsection summarizes the gasoline and diesel fuel co sts and other impacts of the high ethanol control case relative to the AEO 2007 reference case.

Table 4.4-45. High Ethanol Control Case Costs without Tax Subsidies Relative to the AEO 2007 Reference Case (2007 dollars, 7% ROI before taxes) Gasoline Diesel Fuel Refinery Model Variable Operating Cost $MM/yr 23,718 - Amortized Refinery Capital Costs $MM/yr -426 - Fixed Operating Costs $MM/yr -117 - A dded Gasoline Transportation Cost $MM/yr -197 - E85 Pricing Effect $MM/yr -19,854 - Crude Oil Cost $51 to $116/bbl $MM/yr -34,958 - Lower Energy Density $MM/yr 21,728 473 A djustment from Ethanol Price to Cost $MM/yr -1,866 - FFV Costs $MM/yr 6,113 - Renewable Diesel Cost vs Pe troleum Diesel $MM/yr - -1,744 Total Costs $MM/yr -5,961 -1,271 Refinery Model Variable Operating Cost c/gal 16.39 - A mortized Refinery Capital Costs c/gal -0.29 - Fixed Operating Costs c/gal -0.08 - A dded Gasoline Transportation Cost c/gal -0.14 - E85 Pricing Effect c/gal -13.72 - Crude Oil Cost $51 to $116/bbl c/gal -24.16 - Lower Energy Density c/gal 15.02 0.67 A djustment from Ethanol Price to Cost c/gal -1.29 - FFV Costs c/gal 4.22 - Renewable Diesel Cost vs Pe troleum Diesel c/gal - -2.46 Total Costs c/gal -4.12 -1.79

Table 4.4-46. High Ethanol Control Case Costs Reflecting Tax Subsidies Relative to the AEO 2007 Reference Case (2007 dollars, 7% ROI before taxes) Gasoline Diesel Fuel Total Costs $MM/yr -5,961 -1,271 Federal Subsidies $MM/yr -17,504 -1,359 Revised Total Cost $MM/yr -23,465 -2,630 Total Costs c/gal -4.12 -1.79 Federal Subsidies c/gal -12.10 -1.92 Total Costs c/gal -16.22 -3.71148 Table 4.4-47. Summary of the Total and Incremental Volume tric Refinery Inputs by PADD for the High Ethanol Control Case Relative to the AEO 2007 Reference Case (barrels/day)

Control Difference Control Difference Control Difference Control Difference Control Difference Case from Ref Case Case from Ref Case Case from Ref Case Case from Ref Case Case from Ref Case PADD Crude 1,347,342 -181,037 3,058,241 -400,248 7,117,305 -134,113 1,534,859 1,256 1,886,357 -3,037 GTL Naphtha 0 0 0 0 0 0 0 0 0 0 GTL Diesel 0 0 0 0 0 0 0 0 0 0 VGO HS 0 0 0 0 0 -43,785 0 0 0 0 VGO LS 0 0 7,920 -30,143 0 0 0 0 0 0 HS AR (A960) 0 0 0 0 0 0 0 0 0 0 LS AR (Alg) 279,819 50,165 0 0 738,057 31,843 0 0 0 0 Normal Butane 30,814 8,329 78,293 26,638 69,363 -16,802 25,526 -14,190 39,573 0 Isobutane 12,582 12,038 16,476 -7,315 8,234 8,234 1,178 -5,088 0 0 Other 0 0 0 0 0 0 0 0 0 0 MTBE 0 0 0 0 0 0 0 0 0 0 Ethanol - E10 270,313 -2,774 168,062 -29,838 142,590 -33,127 66,626 -3,764 143,845 1,188 Ethanol - E20 0 0 0 0 0 0 0 0 0 0 Ethanol - E85 575,048 575,048 332,715 332,715 361,999 361,999 60,129 60,129 46,969 46,969 Reformer Feed 0 0 0 0 0 0 0 0 0 0 Methanol 0 0 0 0 0 0 0 0 0 0 Natural Gas (FOE) 74,115 -6,992 136,509 -8,134 493,553 -10,734 86,015 -7,881 154,032 -1,636 Hydrogen (MSCF) 0 0 0 0 0 0 0 0 0 0 Pentanes Plus 0 0 58 -32,066 52,055 0 0 -18,580 0 0 Import CBOB 10% 0 -6,286 0 0 0 0 0 0 0 0 Import CBOB 20% 0 0 0 0 0 0 0 0 0 0 Import RBOB 10% 0 -145,593 0 0 0 0 0 0 0 0 Import RBOB 20% 0 0 0 0 0 0 0 0 0 0 Import Alkylate 45,167 42,933 0 0 0 0 0 0 0 0 Import Raffinate 3,442 -50,084 0 0 0 0 0 0 45,808 0 Import Reformate 0 -8,829 0 0 0 0 0 0 0 0 Import FCC Naphtha 15,980 15,980 0 0 11,943 11,943 18,580 18,580 0 0 Import Lt Naphtha 0 0 17,575 17,575 0 0 0 0 584 0 Import Hvy Naph 0 0 0 0 41,644 0 0 0 0 0 Transfer Lt Naphtha 0 -4,333 0 0 0 0 0 0 11,387 -6,997 Transfer Reformate 16,658 0 0 0 0 0 0 0 0 0 Transfer Alkylate 60,000 0 0 0 0 0 0 0 60,000 0 Transfer FCC Naphth a 0 0 20,822 0 0 0 0 0 0 0 Transfer Raffinate 0 0 11,353 -284 0 0 0 0 60,000 12,556 Transfer RBOB 10% 242,605 0 0 0 0 0 0 0 0 0 Transfer RBOB 20% 0 0 8,720 8,720 0 0 0 0 0 0 Transfer CBOB 10% 1,398,409 262,136 80,262 26,208 0 0 6,493 142 0 0 Transfer CBOB 20% 0 0 0 0 0 0 0 0 0 0 Isooctane 100 0 100 0 100 0 100 0 16,462 1,200 Isooctene 100 0 100 0 100 0 100 0 600 0 PADD 3 PADD 4/5 ex CA CA PADD 1 PADD 2149 Table 4.4-48. Summary of Total and Incremental Refinery Outputs by PADD for the High Ethanol Control Case Relative to the AEO 2007 Reference Case (barrels/day)

Control Difference Control Difference Control Difference Control Difference Control Difference Case from Ref Case Case from Ref Case Case from Ref Case Case from Ref Case Case from Ref Case Propane 34,143 2,023 50,843 -6,445 103,144 -14,409 23,369 866 52,782 1,190 Propylene 18,685 0 42,525 0 245,407 0 2,041 0 11,774 0 Normal Butane 0 -4,967 0 -965 0 -33,663 0 0 0 0 Isobutane 0 0 0 0 0 -411 0 0 40,012 -1,478 PC Naphtha 15,830 0 40,290 0 432,937 0 0 0 0 0 PC Gasoil 0 0 455,618 -105,083 157,500 0 0 0 0 0 CG Reg 0 0 0 0 0 0 0 0 0 0 CG Prem 0 0 0 0 0 -182,001 0 0 0 0 CG E10 Reg 1,535,198 278,248 1,172,450 -205,266 872,274 -203,190 542,856 -42,507 99,374 4,464 CG E10 Prem 306,669 236,335 274,765 12,343 214,485 9,635 116,742 5,244 18,928 850 RFG E10 Reg 605,554 -550,564 163,150 -104,878 246,042 -139,806 0 0 1,088,091 -3,375 RFG E10 Prem 228,678 8,465 53,454 2,401 78,844 5,349 0 0 217,676 9,778 CG E20 Reg 0 0 0 0 0 0 0 0 0 0 RFG E20 Reg 0 0 0 0 0 0 0 0 0 0 E85 to CG 74,814 74,814 270,064 270,064 253,773 253,773 70,039 70,039 0 0 E85 to RFG 595,006 595,006 117,484 117,484 167,888 167,888 0 0 54,710 54,710 Transfer RBOB 10% 0 0 0 0 251,325 8,720 0 0 0 0 Transfer RBOB 20% 0 0 0 0 0 0 0 0 0 0 Transfer CBOB 10% 0 0 0 0 1,485,164 288,485 0 0 0 0 Transfer CBOB 20% 0 0 0 0 0 0 0 0 0 0 Jet/Kero A (450ppm) 70,000 0 138,523 -1,557 936,227 0 274,537 0 229,653 0 X-Fer Diesel Rundow n 0 00 00 00 00 0 HSD Gr 76 (0.2%) 0 0 0 0 0 0 0 0 0 0 LSD Gr 74 (.05%) 0 0 0 0 0 0 0 0 0 0 ULSD (15 ppm) 587,042 -47,575 643,331 -28,840 2,150,901 14,598 523,035 -10,264 0 0 CARB Diesel 0 0 0 0 0 0 0 0 358,152 -6,197 X-Fer C5's to Storage 0 0 0 0 0 0 0 0 0 0 1% Residual Fuel 0 0 0 0 0 0 0 0 0 0 Residual Fuel 68,283 -23,360 67,826 3,237 262,834 0 138,312 16,021 45,680 -4,199 Slurr y 30,026 2,617 67,363 -18,904 112,554 -1,394 12,295 -1,187 29,893 886 Asphalt & Wax 86,013 -5,669 198,329 -9,357 157,500 0 5,250 0 41,774 0 Gasoil 0 0 4,895 0 0 0 0 0 9,814 0 Lubes 18,706 0 17,313 0 157,500 0 0 0 20,149 0 Benzene 11,003 0 11,003 0 51,347 0 0 0 0 0 Toluene 0 0 0 0 34,910 0 0 0 0 0 Xylenes 0 0 0 0 7,777 0 0 0 0 0 Cumene 0 0 0 0 0 0 0 0 0 0 Other 0 0 0 0 0 0 0 0 0 0 Cyclohexane 0 0 0 0 0 0 0 0 0 0 Transfer Raffinate 0 0 0 0 71,353 12,273 0 0 0 0 Transfer Alkylate 0 0 0 0 120,000 0 0 0 0 0 Transfer Reformate 0 0 0 0 16,658 0 0 0 0 0 Transfer FCC naphth a 0 0 0 0 20,822 0 0 0 0 0 Transfer Lt Naphtha 0 0 0 0 0 -4,333 0 0 11,387 -6,997 Transfer Blendstock 0 0 0 0 0 0 0 0 0 0 Sulfur (STons) 1,076 -78 3,571 -542 12,042 -356 2,038 -49 3,559 14 Coke (STon) 3,495 -455 10,154 -2,572 48,646 -1,154 7,899 -580 17,358 64 CA PADD 1 PADD 2 PADD 3 PADD 4/5 ex CA150 Table 4.4-49. Change in Refinery Unit Capacities by PADD for the High Ethanol Control Case Relative to the AEO 2007 Reference Case (thousand barrels/day) PADD 1 PADD 2 PADD 3 PADD 4/5 ex C A California US Total Crude Towe r 0 -459 0 0 0 -459 Vacuum Towe r 0 -205 0 8 0 -197 Sats Gas Plant -21 0 -45 0 10 -56 Unsats Gas Plant 1 0 0 0 0 1 FCC DeC5 Towe r 000 000 FCC 0 0 0 0 0 0 FCC Splitte r 1 -6 0 0 0 -4 H y drocracke r 14 0 0 -6 0 7 H-Oil Unit 0 0 0 0 0 0 Dela y ed Coke r 0 0 0 -1 0 -1 Visbreaker 0 0 0 0 0 0 Thermal Naphtha Splitte r 0 -6 0 0 0 -6 CRU Reformer 0 0 0 0 0 0 SRU Reforme r 000 099 BTX Reforme r 0 7 -9 0 0 -1 C4 Isomerization 0 0 0 0 3 3 C5/C6 Isomerization 16 0 0 0 0 16 HF Alk y lation 0 0 0 0 0 0 H2SO4 Alk y lation -27 0 0 0 0 -27 Dimersol 0 0 0 0 0 0 Cat Pol y 100 001 Isooctane 0 0 0 0 0 0 DHT - Total -40 0 -19 -10 0 -69 DHT 2nd RCT - Total -38 -52 -20 -10 0 -120 DHT Arom Saturation 0 0 0 0 0 0 NHT - Total Fd 0 0 0 2 0 2 CGH - Generic 13 -30 -6 1 0 -23 CGH - Olefin Sat'n 0 0 0 0 0 0 FCCU Fd HDT 24 0 0 0 0 24 LSR Splitter 0 -25 0 0 0 -25 LSR Bz Saturato r 000 000 Reformate Saturato r -18 0 -2 0 0 -20 Reformate Splitter -54 0 -6 0 0 -59 SDA 0 0 0 0 0 0 MTBE 0 0 0 0 0 0 TAME 0 0 0 0 0 0 H y dro g en Plant - Total MSCF -2 -43 -80 -31 0 -156 Lube Unit 0 0 0 0 0 0 Sulfur Plant -24 0 0 -30 -22 -76 Merox Jet 0 0 0 0 0 0 Merox Diesel 0 0 0 0 0 0 BTX Reformer - Tower feed 0 0 0 0 0 0 BTX Reformer - Extract feed 0 0 0 0 0 0151 Table 4.4-50. Change in Refinery Unit Investments by PADD for the High Ethanol Control Case Relative to the AEO 2007 Reference Case (million dollars/year) PADD 1 PADD 2 PADD 3 PADD 4/5 ex C A California US Total Crude Towe r 0 -1,121 0 0 0 -1,121 Vacuum Towe r 0 -676 0 70 0 -606 Sats Gas Plant -107 0 -129 0 60 -176 Unsats Gas Plant 8 0 0 0 0 8 FCC DeC5 Towe r 000 000 FCC 0 0 0 0 0 0 FCC Splitte r 1 -7 0 0 0 -6 H y drocracke r 305 0 0 -129 0 176 H-Oil Unit 0 0 0 0 0 0 Delayed Coker 0 0 0 -22 0 -22 Visbreaker 0 0 0 0 0 0 Thermal Naphtha Splitte r 0 -7 0 0 0 -7 CRU Reforme r 000 000 SRU Reforme r 0 0 0 0 45 45 BTX Reforme r 0 70 -55 0 0 16 C4 Isomerization 0 0 0 0 20 20 C5/C6 Isomerization 156 0 0 0 0 156 HF Alk y lation 0 0 0 0 0 0 H2SO4 Alk y lation -470 0 0 0 0 -470 Dimersol 0 0 0 0 0 0 Cat Poly 8 0 0 0 0 8 Isooctane 0 0 0 0 0 0 DHT - Total -390 0 -82 -174 0 -646 DHT 2nd RCT - Total -355 -361 -64 -43 0 -822 DHT Arom Saturation 0 0 0 0 0 0 NHT - Total Fd 0 0 0 31 0 31 CGH - Generic 109 -157 -59 4 0 -102 CGH - Olefin Sat'n 0 0 0 0 0 0 FCCU Fd HDT 319 0 0 0 0 319 LSR Splitte r 0 -17 0 0 0 -17 LSR Bz Saturato r 000 000 Reformate Saturator -110 0 -9 0 0 -119 Reformate Splitter -64 0 -4 0 0 -68 SDA 0 0 0 0 0 0 MTBE 0 0 0 0 0 0 TAME 0 0 0 0 0 0 H y dro g en Plant - Total MSCF -7 -148 -186 -129 0 -469 Lube Unit 0 0 0 0 0 0 Sulfur Plant 0 0 0 0 0 -1 Merox Jet 0 0 0 0 0 0 Merox Diesel 0 0 0 0 0 0 BTX Reformer - Tower feed 0 1 0 0 0 1 BTX Reformer - Extract feed 0 0 0 0 0 0 Total -597 -2,422 -587 -391 124 -3,874152 Table 4.4-51. Projected Total U.S. Capital Investments for the High Ethanol Control Case Relative to the AEO 2007 Reference Case (billion dollars) Cost Type Plant Type Capital Investments Corn Ethanol 3.9

Cellulosic Ethanol 48.3 Cellulosic Diesel a 0 Production Costs

Renewable Diesel and Algae 1.1

All Ethanol 11.9 Cellulosic and Renewable Diesel Fuel - Distribution Costs

Biodiesel 1.2 FFV Costs 6.1 Refining -4.1 Total Capital Investments 68.4153 Table 4.4-52. Ethanol and Gasoline Volume, Quality and Energy Density by Gasoline Type at the PADD Terminal for the High Ethanol Control Case Relative to the AEO 2007 Reference Case

Ref Case Control Ref Case Control Ref Case Control R ef Case Control Ref Case Control Ref Case Control RFG

Total ('000 BPD) 1,376,331 834,232 319,080 216,604 459,343 324,886 0 0 1,299,365 1,305,768 3,454,120 2,681,490 Ethanol ('000 BPD) 139,023 84,266 32,230 21,879 46,397 32,817 0 0 131,244 131,896 348,895 270,858 RVP (psi) 10.8 10.3 10.6 12.5 9.7 11.3 0.0 0.0 9.5 9.4 10.1 10.1 Sulfur (ppm) 24.4 23.4 20.0 24.5 23.2 22.4 0.0 0.0 8.8 8.9 18.0 16.3 Density 258.9 259.4 258.2 257.1 259.5 258.7 0.0 0.0 258.5 258.9 258.8 258.9 Octane (R+M/2) 88.1 88.6 88.0 88.5 88.0 88.5 0.0 0.0 87.6 87.7 87.9 88.1 Aromatics (vol%) 19.9 20.0 19.9 20.0 19.6 19.8 0.0 0.0 22.2 22.2 20.7 21.1 Benzene (vol%) 0.57 0.58 0.57 0.57 0.56 0.54 0.00 0.00 0.53 0.55 0.55 0.56 Olefins (vol%) 13.6 14.0 9.4 11.4 11.5 13.7 0.0 0.0 5.7 5.7 10.0 9.7 Oxygen (wt%) 3.7 3.7 3.7 3.8 3.7 3.7 0.0 0.0 3.7 3.7 3.7 3.7 E200 (vol%) 55.6 56.7 58.3 60.7 53.3 54.2 0.0 0.0 58.2 58.2 56.5 57.4 E300 (vol%) 93.9 95.1 93.9 95.1 93.9 95.1 0.0 0.0 86.2 86.2 91.0 90.7 Energy (MMBtu/Bbl) 4.947 4.956 4.924 4.895 4.981 4.951 0.000 0.000 4.994 4.997 4.967 4.970 CG

Total ('000 BPD) 1,830,582 1,841,867 1,640,138 1,447,215 1,280,314 1,086,759 696,861 659,598 112,988 118,302 5,560,884 5,153,740 Ethanol ('000 BPD) 134,064 186,047 165,671 146,183 129,320 109,774 70,390 66,626 11,413 11,950 510,857 520,580 RVP (psi) 11.4 11.7 11.6 11.4 10.7 10.4 11.4 11.2 10.6 10.6 11.3 11.3 Sulfur (ppm) 22.9 24.1 23.6 24.7 23.1 22.6 28.0 28.0 26.6 25.6 23.9 24.5 Density 258.9 260.0 259.1 259.3 260.5 260.8 258.1 259.1 262.7 262.5 259.3 259.9 Octane (R+M/2) 87.8 88.0 88.0 88.1 88.0 88.2 86.9 87.0 89.3 89.2 87.8 88.0 Aromatics (vol%) 23.1 22.5 22.5 22.5 22.4 22.4 15.9 17.7 26.5 26.7 21.9 22.0 Benzene (vol%) 0.53 0.53 0.53 0.53 0.51 0.51 1.05 1.03 0.59 0.57 0.59 0.59 Olefins (vol%) 13.2 13.9 11.0 10.9 13.1 12.6 8.5 9.5 17.8 16.1 12.0 12.3 Oxygen (wt%) 2.7 3.7 3.7 3.7 3.7 3.7 3.7 3.7 3.7 3.7 3.4 3.7 E200 (vol%) 52.5 53.5 58.8 58.9 53.0 51.4 63.0 63.5 58.0 58.5 55.9 56.0 E300 (vol%) 93.9 80.4 93.9 95.0 93.9 79.2 93.9 95.8 86.2 86.2 93.7 86.3 Energy (MMBtu/Bbl) 4.995 4.974 4.925 4.938 4.988 4.998 0.000 4.930 4.942 4.929 4.961 4.962 E85

Total ('000 BPD) 0 669,821 0 387,549 0 421,660 0 70,039 0 54,710 0 1,603,779 Ethanol ('000 BPD) 0 575,048 0 332,715 0 361,999 0 60,129 0 46,969 0 1,376,860 RVP (psi) 0.0 9.9 0.0 10.3 0.0 10.7 0.0 11.9 0.0 12.0 0.0 10.4 Sulfur (ppm) 0.0 10.1 0.0 9.7 0.0 9.6 0.0 9.0 0.0 8.8 0.0 9.8 Density 0.0 268.9 0.0 268.1 0.0 267.8 0.0 266.6 0.0 266.2 0.0 268.2 Octane (R+M/2) 0.0 107.7 0.0 107.7 0.0 107.8 0.0 107.9 0.0 107.9 0.0 107.7 Aromatics (vol%) 0.0 1.2 0.0 0.8 0.0 0.7 0.0 0.1 0.0 0.0 0.0 0.9 Benzene (vol%) 0.00 0.03 0.00 0.02 0.00 0.02 0.00 0.00 0.00 0.00 0.00 0.03 Olefins (vol%) 0.0 2.4 0.0 2.0 0.0 2.1 0.0 2.8 0.0 1.2 0.0 2.2 Oxygen (wt%) 0.0 30.5 0.0 25.7 0.0 30.6 0.0 28.6 0.0 30.8 0.0 29.3 E200 (vol%) 0.0 126.8 0.0 127.7 0.0 128.0 0.0 129.8 0.0 129.6 0.0 127.6 E300 (vol%) 0.0 95.6 0.0 95.9 0.0 96.0 0.0 96.6 0.0 96.6 0.0 95.8 Energy (MMBtu/Bbl) 0.000 3.656 0.000 3.642 0.000 3.633 0.000 3.605 0.000 3.596 0.000 3.642 All Mogas

Total BPD 3,206,913 3,345,919 1,959,219 2,051,367 1,739,657 1,833,305 696,861 729,637 1,412,353 1,478,780 9,015,003 9,439,008 Ethanol BPD 273,087 845,361 197,901 500,777 175,717 504,590 70,390 126,755 142,657 190,815 859,752 2,168,297 RVP 11.1 11.0 11.4 11.3 10.4 10.6 11.4 11.3 9.6 9.6 10.8 10.8 Sulfur ppm 24 21 23 22 23 19 28 26 10 10 22 20 Density 259 262 259 261 260 262 258 260 259 259 259 261 R+M/2 87.9 92.1 88.0 91.9 88.0 92.7 86.9 89.0 87.8 88.5 87.8 91.4 Aromatics 21.7 17.6 22.1 18.1 21.7 16.9 15.9 16.0 22.5 21.8 21.5 18.1 Benzene 0.55 0.44 0.53 0.44 0.53 0.40 1.05 0.93 0.54 0.53 0.58 0.49 Olefins 13.4 11.6 10.7 9.3 12.7 10.3 8.5 8.9 6.7 6.4 11.2 9.8 Oxygen (wt%) 3.1 9.2 3.7 8.0 3.7 10.0 3.7 6.2 3.7 4.7 3.5 8.2 E200 53.8 69.0 58.7 72.1 53.1 69.5 63.0 69.9 58.2 60.9 56.1 68.6 E300 93.9 87.1 93.9 95.1 93.9 85.9 93.9 95.9 86.2 86.6 92.7 89.2 Energy (MMBtu/Bbl) 4.974 4.706 4.925 4.689 4.986 4.676 4.913 4.803 4.990 4.939 4.963 4.740 CA US PADD 1 PADD 2 PADD 3 PADD 4/5 ex CA

4.4.2.3.2 High Ethanol Control Case Relative to the RFS 1 Reference Case

This subsection summarizes the gasoline and diesel fuel co sts and other impacts of the high ethanol control case relative to the RFS1 reference case.154 Table 4.4-53. High Ethanol Control Case Costs without Tax Subsidies Relative to the RFS 1 Reference Case (2007 dollars, 7% ROI before taxes) Gasoline Diesel Fuel Refinery Model Variable Operating Cost $MM/yr 23,894 - Amortized Refinery Capital Costs $MM/yr -460 - Fixed Operating Costs $MM/yr -127 - A dded Gasoline Transportation Cost $MM/yr -257 - E85 Pricing Effect $MM/yr -19,854 - Crude Oil Cost $51 to $116/bbl $MM/yr -45,548 - Lower Energy Density $MM/yr 29,609 502 A djustment from Ethanol Price to Cost $MM/yr -1,524 - FFV Costs $MM/yr 6,476 Renewable Diesel Cost vs Pe troleum Diesel $MM/yr - -1,851 Total Costs $MM/yr -7,790 -1,350 Refinery Model Variable Operating Cost c/gal 16.51 - A mortized Refinery Capital Costs c/gal -0.32 - Fixed Operating Costs c/gal -0.09 - A dded Gasoline Transportation Cost c/gal -0.18 - E85 Pricing Effect c/gal -13.72 - Crude Oil Cost $51 to $116/bbl c/gal -31.48 - Lower Energy Density c/gal 20.46 0.71 A djustment from Ethanol Price to Cost c/gal -1.05 - FFV Costs c/gal 4.48 Renewable Diesel Cost vs Pe troleum Diesel c/gal - -2.61 Total Costs c/gal -5.38 -1.90

Table 4.4-54. High Ethanol Control Case Costs Reflecting Tax Subsidies Relative to the RFS 1 Control Case (2007 dollars, 7% ROI before taxes) Gasoline Diesel Fuel Total Costs $MM/yr -7,790 -1,350 Federal Subsidies $MM/yr -20,266 -1,441 Revised Total Cost $MM/yr -28,055 -2,791 Total Costs c/gal -5.38 -1.90 Federal Subsidies c/gal -14.01 -2.03 Total Costs c/gal -19.39 -3.94155 Table 4.4-55. Summary of the Total and Incremental Vo lumetric Refinery Inputs by PADD for the High Ethanol Control Case Relative to the RFS 1 Reference Case (barrels/day)

Control Difference Control Difference Control Difference Control Difference Control Difference Case from Ref Case Case from Ref Case Case from Ref Case Case from Ref Case Case from Ref Case PADD Crude 1,347,342 -151,714 3,058,241 -475,740 7,117,305 -241,263 1,534,859 -4,119 1,886,357 -1,136 GTL Naphtha 0 0 0 0 0 0 0 0 0 0 GTL Diesel 0 0 0 0 0 0 0 0 0 0 VGO HS 0 0 0 0 0 -33,772 0 0 0 0 VGO LS 0 0 7,920 -23,914 0 0 0 0 0 0 HS AR (A960) 0 0 0 0 0 0 0 0 0 0 LS AR (Alg) 279,819 39,889 0 0 738,057 21,829 0 0 0 0 Normal Butane 30,814 8,329 78,293 19,185 69,363 -14,040 25,526 -13,917 39,573 0 Isobutane 12,582 12,582 16,476 -8,390 8,234 8,234 1,178 -22,245 0 0 Other 0 0 0 0 0 0 0 0 0 0 MTBE 0 0 0 0 0 0 0 0 0 0 Ethanol - E10 270,313 130,437 168,062 63,684 142,590 88,811 66,626 40,273 143,845 8,610 Ethanol - E20 0 0 0 0 0 0 0 0 0 0 Ethanol - E85 575,048 575,048 332,715 332,715 361,999 361,999 60,129 60,129 46,969 46,969 Reformer Feed 0 0 0 0 0 0 0 0 0 0 Methanol 0 0 0 0 0 0 0 0 0 0 Natural Gas (FOE) 74,115 -6,201 136,509 -5,559 493,553 6,876 86,015 -3,625 154,032 -2,444 Hydrogen (MSCF) 0 0 0 0 0 0 0 0 0 0 Pentanes Plus 0 0 58 -32,066 52,055 0 0 -17,467 0 0 Import CBOB 10% 0 0 0 0 0 0 0 0 0 0 Import CBOB 20% 0 0 0 0 0 0 0 0 0 0 Import RBOB 10% 0 -200,000 0 0 0 0 0 0 0 0 Import RBOB 20% 0 0 0 0 0 0 0 0 0 0 Import Alkylate 45,167 45,167 0 0 0 0 0 0 0 0 Import Raffinate 3,442 -61,147 0 0 0 0 0 0 45,808 0 Import Reformate 0 0 0 0 0 0 0 0 0 0 Import FCC Naphtha 15,980 15,980 0 0 11,943 11,943 18,580 18,580 0 0 Import Lt Naphtha 0 0 17,575 17,575 0 0 0 0 584 0 Import Hvy Naph 0 0 0 0 41,644 0 0 0 0 0 Transfer Lt Naphtha 0 -23,342 0 -20,822 0 0 0 0 11,387 -9,842 Transfer Reformate 16,658 0 0 -14,074 0 0 0 0 0 0 Transfer Alkylate 60,000 17,381 0 0 0 0 0 0 60,000 16,933 Transfer FCC Naphtha 0 0 20,822 20,822 0 0 0 0 0 0 Transfer Raffinate 0 0 11,353 -5,888 0 0 0 0 60,000 11,077 Transfer RBOB 10% 242,605 0 0 0 0 0 0 0 0 0 Transfer RBOB 20% 0 0 8,720 8,720 0 0 0 0 0 0 Transfer CBOB 10% 1,398,409 1,381,833 80,262 77,306 0 0 6,493 -19,539 0 0 Transfer CBOB 20% 0 0 0 0 0 0 0 0 0 0 Isooctane 100 0 100 0 100 0 100 0 16,462 2,029 Isooctene 100 0 100 0 100 0 100 0 600 0 PADD 3 PADD 4/5 ex CA C A PADD 1 PADD 2156 Table 4.4-56. Summary of Total and Incremental Refinery Outputs by PADD for the High Ethanol Control Case Relative to the RFS 1 Reference Case (barrels/day)

Control Difference Control Difference Control Difference Control Difference Control Difference Case from Ref Case Case from Ref Case Case from Ref Case Case from Ref Case Case from Ref Case Propane 34,143 1,539 50,843 -12,263 103,144 -32,064 23,369 -1,541 52,782 1,461 Propylene 18,685 0 42,525 0 245,407 0 2,041 0 11,774 0 Normal Butane 0 -7,832 0 -2,370 0 -45,506 0 0 0 0 Isobutane 0 0 0 0 0 -345 0 0 40,012 5,009 PC Naphtha 15,830 0 40,290 0 432,937 0 0 0 0 0 PC Gasoil 0 0 455,618 -108,658 157,500 0 0 0 0 0 CG Reg 0 -118,066 0 -852,131 0 -2,020,447 0 -374,129 0 -53,481 CG Prem 0 0 0 0 0 -416,926 0 -51,984 0 0 CG E10 Reg 1,535,198 1,516,962 1,172,450 704,964 872,274 872,274 542,856 325,693 99,374 59,284 CG E10 Prem 306,669 306,669 274,765 23,409 214,485 134,887 116,742 72,990 18,928 1,105 RFG E10 Reg 605,554 -542,443 163,150 -101,096 246,042 -134,362 0 0 1,088,091 12,026 RFG E10 Prem 228,678 10,012 53,454 3,122 78,844 6,386 0 0 217,676 12,712 CG E20 Reg 0 0 0 0 0 0 0 0 0 0 RFG E20 Reg 0 0 0 0 0 0 0 0 0 0 E85 to CG 74,814 74,814 270,064 270,064 253,773 253,773 70,039 70,039 0 0 E85 to RFG 595,006 595,006 117,484 117,484 167,888 167,888 0 0 54,710 54,710 Transfer RBOB 10% 0 0 0 0 251,325 8,720 0 0 0 0 Transfer RBOB 20% 0 0 0 0 0 0 0 0 0 0 Transfer CBOB 10% 0 0 0 0 1,485,164 1,439,600 0 0 0 0 Transfer CBOB 20% 0 0 0 0 0 0 0 0 0 0 Jet/Kero A (450ppm) 70,000 0 138,523 -3,108 936,227 0 274,537 0 229,653 0 X-Fer Diesel Rundown t 0 0 0 00 0 0 0 0 0 HSD Gr 76 (0.2%) 0 0 0 0 0 0 0 0 0 0 LSD Gr 74 (.05%) 0 0 0 0 0 0 0 0 0 0 ULSD (15 ppm) 587,042 -39,165 643,331 -30,227 2,150,901 2,423 523,035 -11,120 0 0 CARB Diesel 0 0 0 0 0 0 0 0 358,152 -6,714 X-Fer C5's to Storage 0 0 0 0 0 0 0 0 0 0 1% Residual Fuel 0 0 0 0 0 0 0 0 0 0 Residual Fuel 68,283 -21,481 67,826 8 262,834 0 138,312 22,862 45,680 -4,199 Slurry 30,026 3,876 67,363 -19,645 112,554 -4,041 12,295 -4,210 29,893 1,191 Asphalt & Wax 86,013 -5,669 198,329 -11,671 157,500 0 5,250 0 41,774 0 Gasoil 0 0 4,895 0 0 0 0 0 9,814 0 Lubes 18,706 0 17,313 0 157,500 0 0 0 20,149 0 Benzene 11,003 0 11,003 0 51,347 0 0 0 0 0 Toluene 0 0 0 0 34,910 0 0 0 0 0 Xylenes 0 0 0 0 7,777 0 0 0 0 0 Cumene 0 0 0 0 0 0 0 0 0 0 Othe r 0 0 0 00 0 0 0 0 0 Cyclohexane 0 0 0 0 0 0 0 0 0 0 Transfer Raffinate 0 0 0 0 71,353 5,190 0 0 0 0 Transfer Alkylate 0 0 0 0 120,000 34,314 0 0 0 0 Transfer Reformate 0 0 0 0 16,658 16,658 0 0 0 0 Transfer FCC naphtha 0 0 0 0 20,822 20,822 0 0 0 0 Transfer Lt Naphtha 0 0 0 0 0 -23,342 0 0 11,387 -9,842 Transfer Blendstock 0 0 0 0 0 0 0 0 0 0 Sulfur (STons) 1,076 -74 3,571 -630 12,042 -533 2,038 -59 3,559 -10 Coke (STon) 3,495 -227 10,154 -3,068 48,646 -2,278 7,899 -790 17,358 86 PADD 1 PADD 2 PADD 3 PADD 4/5 ex CA CA157 Table 4.4-57. Change in Refinery Unit Capacities by PADD for the High Ethanol Control Case Relative to the RFS 1 Reference Case (thousand barrels/day) PADD 1 PADD 2 PADD 3 PADD 4/5 ex CA California US Total Crude Tower 0 -439 0 0 0 -439 Vacuum Tower 0 -196 0 -2 0 -198 Sats Gas Plant 3 0 -30 0 9 -18 Unsats Gas Plant -2 0 0 0 0 -2 FCC DeC5 Tower 0 0 0 0 0 0 FCC 0 0 0 -8 0 -8 FCC Splitter 2 -6 0 0 0 -5 Hydrocracker -18 0 0 -14 0 -33 H-Oil Unit 0 0 0 0 0 0 Delayed Coker 0 0 0 -28 0 -28 Visbreaker 0 0 0 0 0 0 Thermal Naphtha Splitter -1 -6 0 -1 0 -8 CRU Reformer 0 0 0 0 0 0 SRU Reformer 0 0 0 0 -1 -1 BTX Reformer 0 -10 -18 0 0 -27 C4 Isomerization 0 0 0 0 1 1 C5/C6 Isomerization 26 0 0 0 0 26 HF Alkylation 0 0 0 0 0 0 H2SO4 Alkylation 1 0 0 -5 0 -4 Dimersol 0 0 0 0 0 0 Cat Pol y 000 0 00 Isooctane 0 0 0 0 0 0 DHT - Total -132 0 -103 -50 -4 -290 DHT 2nd RCT - Total -117 -153 -174 -52 -4 -501 DHT Arom Saturation 0 0 0 0 0 0 NHT - Total Fd 0 0 0 -4 0 -4 CGH - Generic -12 -19 -19 -6 0 -57 CGH - Olefin Sat'n 0 0 0 0 0 0 FCCU Fd HDT 37 0 0 0 0 37 LSR Splitter 0 41 38 0 0 80 LSR Bz Saturator 0 0 0 0 0 0 Reformate Saturator -4 -4 1 0 0 -7 Reformate Splitter -12 -12 3 0 0 -21 SDA 0 0 0 0 0 0 MTBE 0 0 0 0 0 0 TAME 0 0 0 0 0 0 Hydrogen Plant - Total MSC -72 11 109 -47 0 1 Lube Unit 0 0 0 0 0 0 Sulfur Plant -128 0 0 -204 -71 -402 Merox Jet 0 0 0 0 0 0 Merox Diesel 0 0 0 0 0 0 BTX Reformer - Tower feed 0 -1 -1 0 0 -2 BTX Reformer - Extract fee d -1 0 0 0 0 -1158 Table 4.4-58. Change in Refinery Unit Investments by PADD for the High Ethanol Control Case Relative to the RFS 1 Reference Case (million dollars/year) PADD 1 PADD 2 PADD 3 PADD 4/5 ex CA California US Total Crude Tower 0 -997 0 0 0 -997 Vacuum Tower 0 -591 0 0 0 -591 Sats Gas Plant 12 0 -101 0 55 -34 Unsats Gas Plant -10 0 0 0 0 -10 FCC DeC5 Tower 0 0 0 0 0 0 FCC 0 0 0 -193 0 -193 FCC Splitter 1 -7 0 0 0 -6 Hydrocracker -631 0 0 -505 0 -1,137 H-Oil Unit 0 0 0 0 0 0 Delayed Coker 0 0 0 -592 0 -592 Visbreaker 0 0 0 0 0 0 Thermal Naphtha Splitter -3 -7 0 -3 0 -13 CRU Reformer 0 0 0 0 0 0 SRU Reformer 0 0 0 0 -4 -4 BTX Reformer 0 -93 -231 0 0 -324 C4 Isomerization 0 0 0 0 8 8 C5/C6 Isomerization 227 0 0 0 0 227 HF Alkylation 0 0 0 0 0 0 H2SO4 Alkylation 16 0 0 -70 0 -54 Dimersol 0 0 0 0 0 0 Cat Pol y -1 0 0 0 0 -1 Isooctane 0 0 0 0 0 0 DHT - Total -1,367 0 -702 -539 -96 -2,703 DHT 2nd RCT - Total -904 -998 -840 -312 -21 -3,076 DHT Arom Saturation 0 0 0 0 0 0 NHT - Total Fd 0 0 0 -46 0 -46 CGH - Generic -58 -63 -92 -25 0 -238 CGH - Olefin Sat'n 0 0 0 0 0 0 FCCU Fd HDT 555 0 0 0 0 555 LSR Splitter 0 29 18 0 0 47 LSR Bz Saturator 0 0 0 0 0 0 Reformate Saturator -46 -19 4 0 0 -60 Reformate Splitter -20 -16 2 0 0 -34 SDA 0 0 0 0 0 0 MTBE 0 0 0 0 0 0 TAME 0 0 0 0 0 0 Hydrogen Plant - Total MSC -255 69 274 -171 0 -84 Lube Unit 0 0 0 0 0 0 Sulfur Plant -3 0 0 -2 -2 -7 Merox Jet 0 0 0 0 0 0 Merox Diesel 0 0 0 0 0 0 BTX Reformer - Tower feed 0 -2 -1 0 0 -3 BTX Reformer - Extract fee d -3 0 0 0 0 -3 Total -2,491 -2,694 -1,669 -2,459 -59 -9,373159 Table 4.4-59. Ethanol and Gasoline Volume, Quality and Energy Density by Gasoline Type at the PADD Terminal for the High Ethanol Control Case Relative to the RFS 1 Reference Case

Ref Case Control Ref Case Control Ref Case Control Ref Case Control Ref Case Control Ref Case Control RFG

Total ('000 BPD) 1,366,663 834,232 314,578 216,604 452,862 324,886 0 0 1,281,031 1,305,768 3,415,134 2,681,490 Ethanol ('000 BPD) 138,034 84,266 31,773 21,879 45,739 32,817 0 0 129,386 131,896 344,932 270,858 RVP (psi) 10.7 10.3 10.3 12.5 9.6 11.3 0.0 0.0 9.5 9.4 10.1 10.1 Sulfur (ppm) 23.8 23.4 20.1 24.5 23.5 22.4 0.0 0.0 8.7 8.9 17.8 16.3 Density 258.5 259.4 256.2 257.1 259.1 258.7 0.0 0.0 258.5 258.9 258.4 258.9 Octane (R+M/2) 88.1 88.6 88.0 88.5 88.0 88.5 0.0 0.0 87.6 87.7 87.9 88.1 Aromatics (vol%) 19.9 20.0 18.2 20.0 19.5 19.8 0.0 0.0 22.2 22.2 20.5 21.1 Benzene (vol%) 0.57 0.58 0.57 0.57 0.57 0.54 0.00 0.00 0.54 0.55 0.56 0.56 Olefins (vol%) 13.1 14.0 8.0 11.4 9.3 13.7 0.0 0.0 5.7 5.7 9.3 9.7 Oxygen (wt%) 3.7 3.7 3.8 3.8 3.7 3.7 0.0 0.0 3.7 3.7 3.7 3.7 E200 (vol%) 55.7 56.7 62.5 60.7 54.5 54.2 0.0 0.0 58.5 58.2 57.2 57.4 E300 (vol%) 93.9 95.1 91.5 95.1 93.9 95.1 0.0 0.0 86.2 86.2 90.8 90.7 Energy (MMBtu/Bbl ) 4.963 4.956 4.864 4.895 5.027 4.951 0.000 0.000 4.988 4.997 4.971 4.970 CG

Total ('000 BPD) 1,841,024 1,841,867 1,570,973 1,447,215 1,262,249 1,086,759 687,028 659,598 111,394 118,302 5,472,668 5,153,740 Ethanol ('000 BPD) 1,842 186,047 72,606 146,183 8,040 109,774 26,352 66,626 5,849 11,950 114,689 520,580 RVP (psi) 10.5 11.7 11.8 11.4 10.7 10.4 11.3 11.2 10.8 10.6 11.0 11.3 Sulfur (ppm) 27.8 24.1 25.3 24.7 27.3 22.6 24.6 28.0 26.4 25.6 26.6 24.5 Density 259.3 260.0 258.8 259.3 259.4 260.8 256.8 259.1 260.8 262.5 258.9 259.9 Octane (R+M/2) 88.0 88.0 88.0 88.1 88.0 88.2 86.8 87.0 88.0 89.2 87.8 88.0 Aromatics (vol%) 28.7 22.5 26.3 22.5 28.4 22.4 19.3 17.7 26.8 26.7 26.7 22.0 Benzene (vol%) 0.65 0.53 0.64 0.53 0.65 0.51 0.80 1.03 0.62 0.57 0.67 0.59 Olefins (vol%) 15.2 13.9 11.2 10.9 16.0 12.6 8.0 9.5 18.6 16.1 13.4 12.3 Oxygen (wt%) 0.0 3.7 1.7 3.7 0.2 3.7 1.4 3.7 1.9 3.7 0.8 3.7 E200 (vol%) 45.2 53.5 52.9 58.9 45.9 51.4 58.9 63.5 54.5 58.5 49.5 56.0 E300 (vol%) 93.9 80.4 91.5 95.0 93.9 79.2 93.9 95.8 86.2 86.2 93.0 86.3 Energy (MMBtu/Bbl ) 5.133 4.974 5.007 4.938 5.127 4.998 5.004 4.930 4.998 4.929 5.077 4.962 E85

Total ('000 BPD) 0 669,821 0 387,549 0 421,660 0 70,039 0 54,710 0 1,603,779 Ethanol ('000 BPD) 0 575,048 0 332,715 0 361,999 0 60,129 0 46,969 0 1,376,860 RVP (psi) 0.0 9.9 0.0 10.3 0.0 10.7 0.0 11.9 0.0 12.0 0.0 10.4 Sulfur (ppm) 0.0 10.1 0.0 9.7 0.0 9.6 0.0 9.0 0.0 8.8 0.0 9.8 Density 0.0 268.9 0.0 268.1 0.0 267.8 0.0 266.6 0.0 266.2 0.0 268.2 Octane (R+M/2) 0.0 107.7 0.0 107.7 0.0 107.8 0.0 107.9 0.0 107.9 0.0 107.7 Aromatics (vol%) 0.0 1.2 0.0 0.8 0.0 0.7 0.0 0.1 0.0 0.0 0.0 0.9 Benzene (vol%) 0.00 0.03 0.00 0.02 0.00 0.02 0.00 0.00 0.00 0.00 0.00 0.03 Olefins (vol%) 0.0 2.4 0.0 2.0 0.0 2.1 0.0 2.8 0.0 1.2 0.0 2.2 Oxygen (wt%) 0.0 30.5 0.0 25.7 0.0 30.6 0.0 28.6 0.0 30.8 0.0 29.3 E200 (vol%) 0.0 126.8 0.0 127.7 0.0 128.0 0.0 129.8 0.0 129.6 0.0 127.6 E300 (vol%) 0.0 95.6 0.0 95.9 0.0 96.0 0.0 96.6 0.0 96.6 0.0 95.8 Energy (MMBtu/Bbl ) 0.000 3.656 0.000 3.642 0.000 3.633 0.000 3.605 0.000 3.596 0.000 3.642 All Mogas

Total BPD 3,207,687 3,345,919 1,885,551 2,051,367 1,715,111 1,833,305 687,028 729,637 1,392,425 1,478,780 8,887,802 9,439,008 Ethanol BPD 139,876 845,361 104,378 500,777 53,780 504,590 26,352 126,755 135,236 190,815 459,622 2,168,297 RVP 10.6 11.0 11.5 11.3 10.4 10.6 11.3 11.3 9.6 9.6 10.6 10.8 Sulfur ppm 26.1 21.0 24.5 21.8 26.3 19.5 24.6 26.1 10.1 10.3 23.2 19.6 Density 258.9 261.7 258.4 260.8 259.3 262.1 256.8 259.8 258.7 259.4 258.7 261.1 R+M/2 88.0 92.1 88.0 91.9 88.0 92.7 86.8 89.0 87.7 88.5 87.8 91.4 Aromatics 24.9 17.6 24.9 18.1 26.0 16.9 19.3 16.0 22.6 21.8 24.3 18.1 Benzene 0.62 0.44 0.63 0.44 0.63 0.40 0.80 0.93 0.55 0.53 0.63 0.49 Olefins 14.3 11.6 10.7 9.3 14.2 10.3 8.0 8.9 6.7 6.4 11.8 9.8 Oxygen (wt%) 1.6 9.2 2.0 8.0 1.2 10.0 1.4 6.2 3.6 4.7 1.9 8.2 E200 49.7 69.0 54.5 72.1 48.1 69.5 58.9 69.9 58.1 60.9 52.5 68.6 E300 93.9 87.1 91.5 95.1 93.9 85.9 93.9 95.9 86.2 86.6 92.2 89.2 Energy (MMBtu/Bbl ) 5.061 4.706 4.983 4.689 5.101 4.676 5.004 4.803 4.988 4.939 5.036 4.740 PADD 3 PADD 4/5 ex CA CA US PADD 1 PADD 2160 i Kwaitkowski, J.R., McAloon, A., Taylor, F., Johnston, D.B., Modeling the process a nd costs of fuel ethanol production by the corn dry-grind process. Industrial Crops and Products 23 (2006) 288-296. A copy of the current USDA model can be obtained by contacting the corresponding author.

ii See Tables 4.1-21 and 4.1-22 of this section for biom ass costs. Coal costs taken from EIA Annual Energy Outlook 2008 Table 15.

iii Bioenergy Feedstock Characteristics from Jonathan Scurlock, Oak Ridge Na tional Laboratories, available at http://bioenergy.ornl.gov/papers/misc/biocha r_factsheet.html (accessed October 1, 2008)

iv Gallagher, P.W., Brubaker, H., and Shapouri, H. “Plant Size: Capital Cost Relationships in the Dry Mill Ethanol Industry,” Biomass and Bioenergy Vol. 28. 2005. Pp. 565-7.

v Corn Stover Collection Project , David A. Glassner, Nati onal Renewable Energy Laboratory, 1617 Cole Blvd., Golden, CO 80401, James R. Hettenhaus , Chief Executive Assistance, 3211 Trefoil Ave, Charlotte, NC 28226, and Thomas M. Schechinger, Iron Horse Custom Farm ing, 816 Iron Horse Rd, Harlan, IA 51537; in BioEnergy ’98: Expanding BioEnergy Partnerships

vi Abhijith Mukunda, Graduate Student School of Industrial Engineering, Purdue University, West Lafayette IN 47907, Klein E Ileleji, Assistant Professor, School of Agri cultural & Biological Engineering, Purdue University, West Lafayette IN 47907, Hong Wan, A ssistant Professor, School of Industria l Engineering, Purdue University, West Lafayette IN47906, Simulation of Corn Stover Logistics from On-farm Storage to an Ethanol Plant, Paper Number: 0661772006, ASABE Annual International Meeting, Portland Convention Center , Portland, Oregon, 9 - 12 July 2006

vii Shahab Sokhansanj, , Anthony Turhollow, Oak Ridg e National Laboratory, North Logan, UT 84341-8804, Janet Cushman, Oak Ridge National Laboratory, Oak Ridge, TN 37831-6422, John Cundiff, Biological Systems Engineering, Virginia Technical University, Blacks burg, VA 24061-0303, Engineering aspects of collecting corn stover for bioenergy, Biomass and Bioenergy 23 (2002) 347 – 355; Received 15 October 2001; received in revised form 15 April 2002; accepted 3 May 2002 ; 2002 Published by Elsevier Science Ltd.

viii David A. Glassner, National Rene wable Energy Laboratory, Golden, CO 80401, James R. Hettenhaus, Chief Executive Assistance, Charlotte, NC 28226, and Thomas M. Schechinger, Iron Horse Custom Farming, Harlan, IA 51537; Corn Stover Collection Project , in BioEnergy ’98: Expanding BioEnergy Partnerships

ix J.E. Atchison, Atchison Consultants, Inc., J. R. Hette nhaus, Chief Executive Assistance, Inc. Charlotte, North Carolina, National Renewable Energy Laboratory Gold en, Colorado, .Innovative Methods for Corn Stover Collecting, Handling, Storing and Transporting, March 2003.

x Daniel R. Petrolia, Depa rtment of Applied Economics , College of Food, Agricultu re, and Natural Resources Sciences, University of Minnesota, The Economics of Harvesting and Transporting Corn Stover for Conversion to Fuel Ethanol: A Case Study for Minnesota, Staff Paper P06-12 August 2006

xi Renee Sayler & Kenneth Von Bargen, Principal Investigators, Feasibility of Corn Residue Collection in Kearney, Nebraska Area, for Western Regional Biomass Energy Program, Report of findings, by University of Nebraska-Lincoln, Industrial Agricultural Products Center, Lincoln, NE 68583, September 1993.

xii John S. Cundiff, Professor, Robert D. Grisso, Prof essor, Biological Systems Engineering Dept(MS 0303), Virginia Tech, Blacksburg, VA 24061, Hosein Shapouri, Senior Agricultural Economis t, U.S.D.A., Office of Energy Policy and New Uses, Washington DC 20250-3815, Economic Analysis of two Receiving Facility Designs for a Bioenergy Plant, Paper Number: 076051,2007 ASABE Annual International Meeting, Sponsored by ASABE, Minneapolis Convention Center , Minneapolis, Minnesota, 17 - 20 June 2007161 xiii Kevin J. Shinners – Professor of Agricultural Engineer ing, Ben N. Binversie – Gra duate Research Assistant, Department of Biological Systems Engineering, Univ ersity of Wisconsin, Madi son, WI, Philippe Savoie – Research Scientist, Agriculture and Agri-Food Canada , Quebec, Canada, Whole-Plant Corn Harvesting for Biomass: Comparison of Single-Pass and Multiple-Pass Harvest Systems, Paper Number: 036089 2003 ASAE Annual International Me eting, Sponsored by ASAE, Riviera Hotel and Convention Center, Las Vegas, Nevada, USA, 27- 30 July 2003.

xiv S. Sokhansanj1, A. Turhollow, and R. Perlack, Oak Ridge National Laboratory, Tennessee, USA 37830, Stochastic Modeling of Costs of Corn Stover Costs Delivered to an Intermediate Storage Facility, Paper Number: 024190, Presented at: 2002 ASAE Annual Inte rnational Meeting / CIGR XVth World Congress, Sponsored by ASAE and CIGR, Hyatt Regency Chicago, Chicago, Illinois, USA, July 28-July 31, 2002

xv D. Montross, Associate Professor, Scott A. Shearer, Professor, Timothy S. Stom baugh, Associate Extension Professor, Stephen F. Higgins, Rese arch Specialist, and Samuel G. McNeill, Associate Extension Professor, Department of Biosystems and Agricu ltural Engineering, University of Kentucky, Lexington, Kentucky; and Shahab Sokhansanj, Professor, Oak Ridge National Labor atory, Environmental Scie nces Division, Oak Ridge, Tennessee, Corn Stover Availability and Collection Efficiency Using Typical Hay Equipment, This article is published with the approval of the Director of the Ke ntucky Agricultural Experime nt Station and designated Paper No. 04-05-066. Transactions of the ASABE, Vol. 50(3): 705

− 711 – 2007 American Society of Agricultural and Biological Engineers, ISSN 0001

− 2351. xvi American Society of Agricultural and Biolog ical Engineers (ASABE), ASABE Standards, 2007, 54 th Edition, Standards, Engineering Practices, Data, 2950 Niles Road, St. Joseph, MI 49085-9659.

xvii William Edwards, extension economist, Machinery Management: Estimating Farm Machinery Costs, PM 710 Paper version, Revise d November 2001; Electronic version Revise d August 2005, University Extension, Iowa State University.

xviii Mark Hanna, Extension Engineer, University Extension, Iowa State University, Ames Iowa, Estimating the Field Capacity of Farm Machines, File A3-24, April 2002.

xix Terry Kastens, Extension Agricultural Economist, Kans as State University Agricu ltural Experiment Station and Cooperative Extension Service, Farm Machinery Operation Cost Calculations, MF-2244 May 1997

xx Machinery Cost Estimates: Forage Field Operations, University of Illinois Farm Business Management Handbook, University of Illinois Extension FBM 0203 Depa rtment of Agricultural and Consumer Economics • College of Agricultural, Consumer a nd Environmental Sciences, University of Illinois at Urbana-Champaign

xxi Tim Cross, Agricultural Economics, Agricu lture Machinery Cost Calculation Methods, E12-2015-00-032-98, Agricultural Extension Service, The University of Tennessee Institute of Agriculture.

xxii Agricultural Prices 2006 Summary, July 2007 United States, Department of Agriculture National Agricultural Statistics Service, Pr 1-3 (07)

xxiii National Agricultural Statis tics Service, Quick Stats (Agricultural Statistics Data Base, State and County Data), USDA, http://www.nass.usda.gov/

xxiv L. O. Pordesimo, W. C. Edens, The University of Tennessee, Dept. of Biosystems Engineering and Environmental Science, Knoxville, TN, U.S.A., S. S okhansanj Oak Ridge National Laboratory, Environmental Sciences Division, Oak Ridge, TN , U.S.A., Distribution of Above Ground Biomass in Corn , Stover, Paper Number: 02-6059; 2002 ASAE Annual Inte rnational Meeting/CIGR XVth World Congress, Hyatt Regency Chicago, Chicago, Illinois, USA,; July 29-31, 2002.

xxv Kevin J. Shinners, Professor of Agricultural Engineer ing, Ben N. Binversie, Graduate Research Assistant, Department of Biological Systems Engineering, Univ ersity of Wisconsin, Madi son, WI, Philippe Savoie, Research Scientist, Agriculture a nd Agri-Food Canada, Quebec, Canada; Harvest and Storage Of Wet and Dry Corn Stover As A Biomass Feedstock, Paper Number: 036088, 2003 ASAE Annual Interna tional Meeting Riviera Hotel and Convention Center, La s Vegas, Nevada, USA, 27- 30 July 2003

xxvi R.L. Graham, R.D. Perlack, and L.L. Wright, Envir on. Sci. Div., Oak Ridge National Lab., Oak Ridge, TN 37831-6407; R. Nelson, Engineering Extension Programs, Kansas State Univ., Manhattan, KS 66506, and J. Sheehan, National Renewable Energy Lab., Golden, CO 80401. Current and Pote ntial U.S. Corn Stover Supplies, Agronomy Journal 99:1–11, American Societ y of Agronomy, Madison, WI 53711 USA; doi:10.2134/agronj2005.0222 prepared 2005; published online 1 January 2007162 xxvii Ron Kotrba, Ethanol Producer Magazine st aff writer, The Great Biomass Inquisition, Ethanol Producer Magazine, January 2007. http://ethanolproducer.com/article .jsp?article_id=2621&q=&page=all

xxviii Kevin J. Shinners, Professor of Agricultural Engineer ing, Ben N. Binversie, Graduate Research Assistant, Department of Biological Systems Engineering, Univ ersity of Wisconsin, Madi son, WI, Philippe Savoie, Research Scientist, Agriculture a nd Agri-Food Canada, Quebec, Canada; Harvest and Storage Of Wet and Dry Corn Stover As A Biomass Feedstock, Paper Number: 036088, 2003 ASAE Annual Interna tional Meeting Riviera Hotel and Convention Center, Las Vegas, Nevada, USA, 27- 30 July 2003.

xxix William Edwards, Extension Economist, Estimating Farm Machinery Costs, PM710, Machinery Management, University Extension, Iowa State University, revised November 2001

xxx Renee Sayler & Kenneth Von Bargen, Principal Investigators, Feasibility of Corn Residue Collection in Kearney, Nebraska Area, for Western Regional Biomass Energy Program, Report of findings, by University of Nebraska-Lincoln, Industrial Agricultural Products Center, Lincoln, NE 68583, September 1993.

xxxi Robert D. Grisso , Professor, Virginia Tech, Depart ment of Biological Systems Engineering, Blacksburg, Virginia; Paul J. Jasa , Extension Engineer, Biolog ical Systems Engineering Department, University of Nebraska, Lincoln, Nebraska; and Dale E. Rolofson , Farm Manager, Agri-Cross Farms, Inc. Greenwood, Nebraska. Corresponding author : Paul J. Jasa, Biologi cal Systems Engineering Dept., University of Nebraska, Lincoln, Analysis of Traffic Patterns and Yield Monitor Data for Field Efficiency Determination, Paper No. 011013, Presented at the 2000 ASAE Annual Meeting, A pplied Engineering in Agriculture Vol. 18(2): 171- 178 ( © 2002 American Society of Agricultural Engineers ). A contribution of the University of Nebraska Agricultural Research Division, Lincoln, Nebraska. J ournal Series No. 13335. Mention of trade and company names are for the reader and do not infer endorsemen t or preferential treatment of the products by the University of Nebraska, Lincoln.

xxxii Robert “Bobby” Grisso, Professor, and John C. Cundi ff, Professor; and David H. Vaughan, Professor, Department of Biological Systems Engineering, Virginia Tech, Blacksburg, VA., Investigating Machinery Management Parameters with Computer Tools, Paper Number: 071030, Presented at 2007 ASABE Annual International Meeting, Minneapolis Convention Center, Minneapolis, Minn esota, 17 - 20 June 2007. Mention of trade and company names are for the reader and do not infer endorsement or pref erential treatment of the products by Virginia Tech.

xxxiii Poorna P. Ravula, Robert D. Gr isso and John S. Cundiff, Biological Systems Engineering Department, Virginia Tech, Blacksburg, VA 24061-0303, Comparison be tween Two Policy Strategies for Scheduling in a Biomass Logistic System, Paper Number: 071095, Presented at the 2007 ASABE Annual Intern ational Meeting, Sponsored by ASABE, Minnea polis Convention Center

xxxiv International Fire Code 2903.4: Ag ricultural Products. Hay, straw or si milar agricultural products shall not be stored adjacent to structures of combustible material s. Storage shall be limited to stacks of 100 tons (91 metric tons) each. Stacks shall be separated by a mini mum of 20 feet (6096 mm) of clear space. Quantities of hay, straw and other agricultural products shall not be limited where stored in or near farm structures located outside closely built areas. A permit shall not be required for agricultural storage.

xxxv Daniel R. Petrolia, Depa rtment of Applied Economics , College of Food, Agriculture, and Natural Resources Sciences, University of Minnesota, The Economics of Harvesting and Transporting Corn Stover for Conversion to Fuel Ethanol: A Case Study for Minnesota, Staff Paper P06-12 August 2006

xxxvi Ron Kotrba, staff writer, The Great Biomass Inquisition, Ethanol Producer Magazi ne. January 2007 Issue. Reach him at rkotrba@bbibiofuels.com, © 2007 BBI International http://ethanolproducer.com/article .jsp?article_id=2621&q=&page=all

xxxvii Ron Kotrba, staff writer, The Great Biomass Inquisition, Ethanol Producer Magazi ne. January 2007 Issue. Reach him at rkotrba@bbibiofuels.com, © 2007 BBI International http://ethanolproducer.com/article .jsp?article_id=2621&q=&page=all163 xxxviii Graeme R Quick, Single-pass Corn and Stove r Harvesters: Development and Performance. Proceedings of the International Conference on Crop Harvesting and Pr ocessing, 9-11 February 2003, Louisville, Kentucky USA, ASABE, St. Joseph, Mich.; ASAE Publication Number 701P1103e

xxxix A. Aden, M. Ruth, K. Ibsen, J. Jechura, K. Neeves, J. Sheehan, and B. Wallace National Renewable Energy Laboratory (NREL); L. Montague, A. Slayton, and J. Lukas Harris Group, Seattle, Washington, Ethanol Process Design and Economics Utilizing Co-Current Dilute Acid Prehydrolysis and Enzymatic Hydrolysis for Corn Stover ; June 2002;NREL is a U.S. Departme nt of Energy Laboratory Operated by Midwest Research Institute • Battelle • Bechtel; Contract No. DE-AC36-99-GO10337

xl Robert M. Prewitt, Graduate Research Assistant, Michael D. Montross, Associate Professor, Scott A. Shearer, Professor, Timothy S. Stombaugh, A ssociate Extension Professor, Stephen F. Higgins, Research Specialist, Samuel G. McNeill, Associate Extension Professor, Department of Biosystems and Agricultural Engineering, University of Kentucky, Lexington, KY; Shahab S okhansanj, Professor, Oak Ridge National Laboratory, Environmental Sciences Division, Oak Ridge, TN, Corn Stover Availability and Collection Efficiency Using Typical Hay Equipment, Transactions of the American Society of Agricultural and Biological Engineers (ASABE), Vol. 50(3): 705

− 711, 2007, ISSN 0001

− 2351; Publication of this article approved by the Director of the Kentucky Agricultural Experiment St ation and designated Paper No. 04-05-066.

xli Graeme R Quick, Single-pass Corn and St over Harvesters: Development and Performance. Proceedings of the International Conference on Crop Harvesting and Pr ocessing, 9-11 February 2003, Louisville, Kentucky USA, ASABE, St. Joseph, Mich.; ASAE Publication Number 701P1103e

xlii Kevin J. Shinners, Professor of Ag ricultural Engineering, Graham S. Adsit, Graduate Research Assistant, Benjamin N. Binversie, Graduate Research Assistant, Matthew F. Digman, Graduate Research Assistant, Department of Biological Systems Engineering, Universi ty of Wisconsin, Richard E. Muck, Research Scientist, Paul. J. Weimer, Research Scientist, US Dairy Fo rage Research Center – USDA-ARS, Madison, WI, Characteristic Performance and Yields using a Single-Pass, Split- Stream Maize Grain and Stover Harvester, Paper Number: 056051, presented at the 2004 ASAE/CSA E Annual International and the 2005 ASAE Annual International Meeting, Sponsored by ASAE, Tampa Convention Center, Tampa, Florida 17 - 20 July 2005

xliii Shahab Sokhansanj, , Anthony Turhollow, Oak Ridg e National Laboratory, North Logan, UT 84341-8804, Janet Cushman, Oak Ridge National Laboratory, Oak Ridge, TN 37831-6422, John Cundiff, Biological Systems Engineering, Virginia Technical University, Blacks burg, VA 24061-0303, Engineering aspects of collecting corn stover for bioenergy, Biomass and Bioenergy 23 (2002) 347 – 355; Received 15 October 2001; received in revised form 15 April 2002; accepted 3 May 2002 ; 2002 Published by Elsevier Science Ltd.

xliv Kevin J. Shinners, Professor of Agricultural Engineering, Garrit C. Boettcher, Graduate Research Assistant, Jesse T. Munk, Graduate Rese arch Assistant, Matthew F. Digman, Grad uate Research Assistant, Department of Biological Systems Engineering, University of Wisc onsin; Richard E. Muck, Research Engineer, Paul. J.Weimer, Research Scientist, US Dairy Forage Research Center, USDA-ARS, Madison, WI, Single-Pass, SplitStream of Corn Grain and Stover: Characteristic Performance of Three Harvester Configurations, Presented at: ASABE Annual International Meeting, 2006; Oregon Conve ntion Center, Portland, Oregon, 9 – 12 July 2006.

xlv W. C. Edens, L. O. Pordesimo, The University of Tennessee, Dept. of Biosystems Engineering and Environmental Science, Knoxville, TN, S. Sokhansan j, Oak Ridge National Laboratory, Environmental Sciences Division, Oak Ridge, TN, Field Drying Ch aracteristics and Mass Rela tionships of Corn Stover Fractions, Presented at the ASAE Annual International M eeting/ CIGR XVth World Congress, 2002, Hyatt Regency Chicago, Chicago, Illinois, USA, July 28-31, 2002.

xlvi Richard Hess, Idaho National Laboratory, Unifor m Format Feedstock Supply System Design for Lignocellulosic Biomass, Western Region Biomass Workshop August 27, 2007 http://sungrant.oregonstate.edu/work shop/HESS_Western_RP_workshop.pdf

xlvii Kevin J. Shinners, Professor of Agricultural Engineer ing, Ben N. Binversie, Graduate Research Assistant, Department of Biological Systems Engineering, Univ ersity of Wisconsin, Madi son, WI, Philippe Savoie, Research Scientist, Agriculture a nd Agri-Food Canada, Quebec, Canada; Harvest and Storage Of Wet and Dry Corn Stover As A Biomass Feedstock, Paper Number: 036088, 2003 ASAE Annual Interna tional Meeting Riviera Hotel and Convention Center, Las Vegas, Nevada, USA, 27- 30 July 2003.

xlviii Shahab Sokhansanj and Janet Cushman, Bioenergy Feedstock Development Program164 Oak Ridge National Laboratory (ORNL), Feedstock Engineering, Presentation, Lincoln, NB, December 12, 2001 ORNL, Energy Efficiency and Renewable Energy, US DOE, USA

xlix Sudhagar Mani, Ph.D. Candida te, Shahab Sokhansanj, Adjunct Professo r, Xiaotao Bi, Associate Professor, Department of Chemical & Biological Engineering, University of British Columbia, Vancouver, BC CANADA V6T 1Z4, Modeling of Forage Drying in Single and Triple Pass Rotary Drum Dryers, Paper Number: 056082, 2005 ASAE Annual International Mee ting, Tampa Convention Center, Tampa, Florida, 17 - 20 July 2005

l Xianzhe Zheng, Professor, Yiyuan Jiang, Professor, College of Engineering, North East Agricultural University, Harbin, China; Yubin Lan, Associate Profe ssor, Agricultural Engineering Technology, Fort Valley State University, University Systems of Georgia, Fort Valley, GA 31030, Determinati on of Parameters for an Alfalfa Rotary Dryer, Paper Number: 056186, 2005 ASAE Annual In ternational Meeting, Tampa Convention Center, Tampa, Florida, 17 - 20 July 2005

li This information came in a conf idential, personal communication.

lii Christopher T. Wright , Peter A. Pryfogle , Nathan A. Stevens , J. Richard Hess , Corey W. Radtke , Idaho National Laboratory , Idaho Falls , ID, Value of Distributed Preprocessing of Biomass Feedstocks to a Bioenergy Industry, Paper No: 066151 Presented at the ASABE Annual Inte rnational Meeting, 2006, Oregon Conven tion Center Portland, Oregon, 9 - 12 July 2006

liii Roger G. Ginder, Professor of Economics, Department of Economics, Iowa State University, Ames, Iowa 50011, Potential Infrastructure Constr aints on Current Corn Based and Fu ture Biomass Based U.S. Ethanol Production, Working Paper # 07018 , July 2007

liv E-mailed file from Robert Perlack, U. S. Department of Agriculture, May 2008.

lv Phillips, S, Thermochemical Ethanol via Indi rect Gasification and Mixed Alcohol Synthesis of Lignocellulosic Biomass; NREL, April, 2007.

lvi Aden, Andy, Mixed Alcohols from Woody Biom ass – 2010, 2015, 2022, Nati onal Renewable Energy Laboratory (NREL), September, 23 2009.

lvii OECD, “Biofuels: Linking Support to Perfo rmance,” ITF Round Tables No. 138, March 2008.

lviii International Energy Agency (IEA), “Biofuels fo r Transport: An Internatio nal Perspective,” 2004.

lix Goldemberg, J. as sited in Rothkopf, Garten, “A Bl ueprint for Green Energy in the Americas,” 2006.

lx Unicamp, “A Expans ā o do Proalcool como Programa de De senvolvimento Nacional,” Powerpoint presentation at Ethanol Seminar in BNDES, 2006. As quoted in OECD, “Biofuels: Linking Support to Performance,” ITF Round Tables No. 138, March 2008.

lxi Ibid.

lxii Ibid.

lxiii Ibid. lxiv Macedo. I.C., “Green house gases emissions in the production and use of ethanol from sugarcane in Brazil: The 2005/2006 Averages and a Prediction for 2020,” Biomass and Bioenergy , 2008. lxv Ibid. lxvi Smeets E, Junginger M, Faaij A, Walter A, Dolzan P, Turkenburg W, “The sustainability of Brazilian ethanol-An Assessment of the possi bilities of certified production,” Biomass and Bioenergy , 2008. lxvii Official Statistics of the U.S. Department of Commerce, USITC

lxviii Davis, Ryan. November 2009. Techno-economic analys is of microalgae-derived biofuel production. National Renewable Energy Laborator y. Technical Memorandum to EPA.

lxix Sun, A. et al., “Techno-Economic Analysis of Al gae Biofuel Deployment.” Presented at the 2009 Algae Biomass Summit, San Diego, CA (October 2009) as noted in report by Davis, Ryan, op. sit.

lxx Haas, M.J, A process model to estimate biodiesel producti on costs, Bioresource Technology 97 (2006) 671- 678.

lxxi Capital cost and other details taken from Syntroleum Corp Investor Presentation materials dated November 2009, available in th e docket or at http://www.syntroleum.com/Presentations/SyntroleumInvestorPresentation.November%205.2009.FINAL.pdf

lxxii A New Development in Renewable Fuels: Green Diesel, AM-07-10 Annual Meeting NPRA, March 18-20, 2007.

lxxiii Per EPA phone discussion July 23, 2007. lxxiv Ryan Davis, National Renewable Energy Laborator y, Golden Colorado 80401-3392, Technical Memo to EPA “ Techno-economic Analysis of Current Technolog y for Fischer Tropsch Fuels Production. August 2009.165 lxxv “Analysis of Fuel Ethanol Transpor tation Activity and Potential Distribution Constraints”, prepared for EPA by Oak Ridge National Laboratory, March 2009.

lxxvi BNSF railway biodiesel freight co st information can be found at http://www.bnsf.com/markets/agri cultural/bnsf4024/cur/itm31001.txt

lxxvii 2007 National Association of C onvenience Stores State of the Industry survey data www.nacsonline.com as reported in the National Petroleum Ne ws MarketFacts 2007, October 2007.

lxxviii National Petroleum News, “2008 marketfacts”, www.npnweb.com

79 Modeling the Effect of Renewable Fuels Standards 2, Prepared for the Environmental Protection Agency by Jacobs Consultancy under contract with Southwest Research Associates, August 2008.

80 Table 12, Reference and High Price Cases, Annual Energy Outlook 2008; Energy Information Administration, Department of Energy, June 2008.

81 Table 2, Reference Case, Annual Energy Outlook 2007; Energy Information Administration, Department of Energy, February 2007.

82 Table 2, Reference Case, Annual Energy Outlook 2008; Energy Information Administration, Department of Energy, June 2008.

83 D5798-99 (Reapproved 2004), ASTM International.

84 National Association of Convenience Stores (NACS) online annual price resource kit, NACS, February 2, 2006.

85 Combined local, state and federal gasoline taxes, American Petroleum Institute, January 2008.

86 Greene, David L.; Alternative Fuel Market Share as a Function of Fuel Availability and Price Advantage, 1997.

87 Brownstone, D., Small, K., 2005. Valuing time and reliability: assessing the evidence from road pricing demonstrations. Trans

. Res. Part A 39, 279-293.

88 Brownstone, D., Ghose, D., Golob, T., Kazimi, C., Van Amelsf ort, D., 2003. Driver's willingness-to-pay to reduce travel time: evidence from the San Diego I-15 Congestion Pricing Project. Trans. Res. Part A 37, 373-387.

89 Lam, T., Small, K., 2001. The value of time and reliability: measurement from a value pricing experiment. Trans. Res. Part E 37 (2- 3), 231-251.

90 Steimetz, S., Brownstone, D., 2005. Estimating consumers' 'Value of time' with noisy data: a multiple imputation approach. Tr ans. Res. Part B 39, 865-889.

91 Spot Annual Crude Oil Prices for Western Texas Intermediate (WTI), Cushing Oklahoma; http://tonto.eia.doe.gov/dnav/pet/hist/rwtca.htm ; Energy Information Adminstration, 2008.

92 National Annual Average Gasoline and Diesel Fuel Prices (all grades); http://tonto.eia.doe.gov/dnav/pet/pet_pri_gnd_dcus_nus_a.htm ; Energy Information Adminstration, 2008.