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## 5

- 1 

# Chapter 5 **Fuel Program**  **Costs 5.1**  **Methodology** This chapter provides a summary of the methodology

used and the results obtained from our cost anal ys es of the proposed gasoline sulfur control. We start by summarizing the refinery models used for our analysis. We then de scribe our detailed methodology for estimating the sulfur control costs for our proposed sulfur program followed by the results. We present the results from our energy

and supply

analyses for our proposed gasoline sulfur program. Finally, we discuss and compare the results of several cost anal ys es for various sulfur programs. 5.1.1 Overview When we began our planning for estimating the cost of additional reductions in gasoline sulfur, we considered two different options. One option for estimating the costs would be to utilize a linear programming (LP) model, while the second option would be to develop a refinery

- by

-refinery

cost model. While the LP refinery models are necessary

and appropriate for many anal ys es, they

also have several important limitations o f relevance here. When used to model the cost of nationwide fuel control programs on the entire refining industry, LP models are usually used to model groups of refineries in geographic regions called Petroleum Administration for Defense Districts (PADDs ) . The LP refinery model averages the costs over the refineries represented in the PADDs; however, the technology chosen by

the refinery

model would normally

be the lowest cost technology found by the refinery

model. This may

represent an unreasonable cho ice of technologies for individual refineries because of how refineries are configured and based on the sulfur control technologies installed for compliance with the Tier 2 gasoline sulfur program. While the choice of technologies can be limited based on an approximate analysis of what mix of technologies would best suit the group of refineries modeled in each PADD, this would only provide an approximate estimate of the cost incurred. Based on the quality

of input data to these LP models and the assumptions made for complying with a regulatory

requirement, LP refinery models may

overestimate or underestimate the program costs. For example, an LPrefinery model would not be a sensible tool for estimating the credit averaging and trading between re fineries. This could be partiall y overcome b y iterating between PADD refinery model runs, thus estimating the number of credits traded between PADDs and estimating the level of sulfur control in each PADD. However, the nee d to make multiple runs per PADD for each case, coupled with the need to run multiple control cases for different sulfur standards, would be very time consuming, costl y and still would only result in approximate estimates of the sulfur levels achieved and the cost incurred

. For this reas on, EPA developed a refinery

- by

-refinery cost model which models the capability for each refinery

to revamp existing or install new sulfur control technologies available to them to reduce their gasoline sulfur levels. Rather than start from scratch, we started from a refinery

- by

-refinery cost model developed by APT (Mathpro) for EPA to estimate the cost of benzene control under MSAT2. However, instead of using the representations of benzene control technology

contained in the model, we obtained information about gasoline desulfurization and represented the cost of this desulfurization in the refinery

- by

-refinery cost model.

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## 5

- 2 We believe the refinery

- by

- refinery cost model best estimates the cost of individual refineries, especially

when considering an averaging, banking and trading (ABT ) program and therefore is the best analysis tool for estimating nationwide costs. However, the refinery

- by

refinery cost model cannot estimate certain inputs necessary for estimating costs

. Because the refinery- specific information is not publicly available, it was necessary to find another way

to estimate this information. The inputs and outputs from LP refinery cost modeling provide this needed information and it was utilized in the refinery

-by

- refinery cost model. The information from LP refinery

modeling used in the refinery

-by

- refinery cost model is described in Section 5.1.3

. Since the refinery

-by

- refinery cost model contains confidential business information for each refinery, we could not publish the model or present some of the details of the model here. Therefore, to ensure its viability the refinery

-by

- refinery cost model was subjected to peer review by two refinery

industry consultants. Our review of most of the suggested changes recommended b y the peer reviewers suggested that there would be little to no change in our desulfurization cost estimate (some of the changes would increase the estimated costs, while others would reduce the estimated costs ) . Also, we anticipate making other improvements to the cost anal ys is conducted for the final rule, which would necessitate a second round of peer review. Therefore, the peer review comments will be addressed prior to undertaking the cost anal ys is for the final rulemaking along with the other changes that we will be making to our cost anal ys is . The peer review comments are contained in two report s submitted to the docket. The refinery

-by

- refinery

cost model focuses on reducing sulfur from the FCC naphtha because of its high sulfur c ontent. To comply with the 30

-ppm Tier 2 sulfur control program, most refiners installed FCC naphtha hydrotreaters (referred to as FCC postreaters) or FCC feed hydrotreaters (referred to as FCC pretreaters) to reduce that unit’s sulfur contribution to the ir gasoline pool. If refiners installed an FCC postreater under Tier 2, we modeled refiners revamping those units. However, if refiners relied on FCC pretreaters to comply with Tier 2, we assume d that grassroots FCC postreaters would have to be installed at those refineries to reduce its gasoline pool down to 10 ppm. However, since adding grassroots FCC pos treaters is relativel y expensive for the amount of sulfur reduction obtained, the ABT anal ys is we conducted avoided many of these ty pes of investments . Refineries with bo th pre and postreaters today could achieve further gasoline sulfur reductions less than 10 ppm at a relatively low incremental cost and sell the credits to those refiners who are operating refineries which would otherwise be faced with grassroots postreater investments. In addition to addressing the sulfur in the FCC naphtha, we believe that some refineries may need to reduce the sulfur in light straight run (LSR) naphtha . Some refineries might also need to reduce sulfur in butane, although we don’t expect refiners to need to address butane sulfur unless they are pursuing a very

stringent gas oline sulfur standard, e.g., 5 ppm. To better understand the desulfurization costs, we evaluated several different scenarios or cases. For a 10

-ppm average sulfur standard, we assessed the costs based on each refinery achieving the 10

-ppm standard with no averaging among refineries, an averaging program which assumed intra

- company transfers of sulfur credits, and an averaging program which assumed nationwide transfers of sulfur credits. To provide credits for averaging and trading under the 10

- ppm average standard, w e also evaluated refiners reducing their gasoline sulfur down to 5 ppm

. Since we had estimated costs for each refinery to get to 5 ppm sulfur, we also report out the cost

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## 5

- 3 for a 5 ppm average gasoline sulfur standard assuming no averaging between refineries

. The costs for the proposed sulfur program are based on a 10

-ppm sulfur standard with intra

- company credit transfers

. These different scenarios are summarized in Table 5

- 1

.

**Table 5**  **- 1**  **Sulfur Control Cases Evaluated for the Proposal** 10

-ppm Standard 5

-ppm Standard No ABT Program No ABT Program ABT Program with Intra

Company Credit Transfers (Proposed Rule Costs) N/A ABT Program with Nationwide Credit Transfers N/A 5.1.2 LP Refinery

Modeling Methodology and Results Although we used the refinery

- by

-refinery cost model to estimate gasoline desulfurization costs, certain input information was needed to estimate the costs with refinery

by

- refinery

cost model, and without access to detailed refinery

- specific information, we relied on output s from our LPrefinery modeling. Perhaps the most important input is the cost for making up the octane loss that occurs with desulfurization. Certain refinery operations information from the LP refinery

model was used for estimating the volume of gasoline produced in the refinery

by

- refinery

model, including the utilization factors of individ ual refinery

units, and the percentage that straight run naphtha, FCC naphtha and hydrocrackate comprises of the feed volume of their respective units. LPrefinery

models are detailed mathematical representations of refineries. They are used by indivi dual refining companies to project how best to operate their refineries. They are also used by

government agencies, such as EPA and DOE, as well as by refining industry associations and individual companies, to estimate the cost and supply impacts of fuel quality changes. LP refinery

models have been used for these purposes for decades and a certain protocol has been established to conduct these studies. Two different sets of refinery modeling runs from two different LP refinery models were used as inputs into the refinery

-by

- refinery cost model. The refinery

-by

- refinery cost model already contained the utilization factors and gasoline production volumes for individual refinery units from the anal ys is conducted by Mathpro for the MSAT2, and we continued to use that information for this cost anal ys is. The gasoline demand is expected to be fairly flat in the future, so using the previous refinery modeling work for these inputs will likely have little impact on the cost estimate. We plan on updating these inputs for the final rule to reflect more recent refinery modeling work. Additional refinery

modeling was conducted using the Haverl y GRTMPS refinery model. The primary

reason for conducting new LP refinery modeling anal ys is was to estimate the cost of making up the octane loss associated with desulfurization as well as estimate how gasoline qualities would be affected by the octane recovery to feed into the emissions inventory impact anal ys is discussed in Chapter 7 . While the gasoline demand and production volumes are not

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## 5

- 4 expected to change in the future, the cost of octane is expected to decrease dramaticall y due to expected much larger use of ethanol under the RFS2 rulemaking. The first step in conducting an LP refinery modeling anal ys is wa s the development of a base case. The base case is a refinery modeling case that calibrates the refinery model based on actual refinery

unit capacity

and input and output data. The base year for this study was the year 2000 for the Mathpro model and the ye ar 200 4 for the Haverl y model. Because much of the information available for establishing the base case is only available for PADDs of refineries, the LP refinery

modeling was conducted on a PADD

- wide basis. Refinery capacity information from the Oil and Gas J ournal was aggregated by PADD and entered into the LP refinery model. The feedstock volumes , including crude oil and gasoline blendstocks, were obtained from the Energy Information Administration (EIA) and entered into each PADD’s model. Similarly, product volumes such as gasoline, jet fuel , and diesel fuel were obtained from EIA and entered into the cost model. The environmental and ASTM fuel quality constraints in effect in the base ye ar were imposed on the products. This includes the Reformulated Gas oline program and the 500

-ppm highway

diesel fuel sulfur standard, and for the Haverl y LP refinery modeling, the first ye ar of the Tier 2 gasoline sulfur standard. This information was input into the LP refinery cost model for each PADD and each PADD mode l was run to model the U.S. refinery industry for the base year. The gasoline quality for each PADD refinery

model was then compared to the actual gasoline quality for conventional and reformulated gasoline which is available from the RFG data base. Each model was calibrated to closel y approximate the gasoline quality of each PADD. The second step in modeling is the development of a reference case. The purpose of the reference case is to model the refining industry operations and cost in a future year, which is the ye ar that the control program is modeled to be in effect (serving as a point of reference to the control cases for estimating costs and other impacts). The reference year for the Mathpro LP refinery modeling was 2012 while the reference year for the Haverl y refinery modeling was 2017 and 2030

. We developed two reference cases with the Haverl y model to model different control case scenarios. The reference case was created b y starting with the base cases for each PADD and adjusting each base c ase to model the future year, accounting for the changes between the two years. Two different ty

pes of adjustments were made to the base case refinery models to enable modeling the refining industry for the reference case. First, the change in certain inputs such as product volumes and energy prices need to be accounted for U.S. refinery gasoline, diesel fuel and jet fuel demands are projected ye ar-by

- ye ar by EIA in its Annual Energy Outlook (AEO) ; the projections from the AEO for the reference case are used in the refinery modeling analysis. The Mathpro LP refinery modeling relied on AEO 200 6 while the Haverly LP refinery

modeling relied on AEO 2011. This growth in demand is used to project refinery production for each PADD to meet that increased demand. This projected growth in U.S. refinery production was entered into the reference case version of the LP refinery model. The utility and crude oil and other feedstock prices which are projected b y E IA for the future year being modeled were also entered into the refinery

model as well as the estimated product prices

. The second adjustment made to model the reference cases was the application of fuel quality changes. Environmental programs which have been implemented or which will largely be implemente d by

the time that the prospective fuels control program would take effect were

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## 5

- 5 modeled in the reference case. These fuel quality changes include limits such as the 30

-ppm average gasoline sulfur standard, 15

-ppm caps on highway and nonroad diesel fuel and the MSAT2 benzene control program , in addition to the environmental programs which were already being modeled in the base case. For the Mathpro refinery modeling , which was conducted before the nonroad diesel fuel program and MSAT2 benzene control programs were finalized, those fuels control programs were not modeled in the reference case. Also, the implementation of EPAct require d a large increase in the amount of ethanol to be blended into gasoline to comply with the renewable fuels standard (RFS) , but not RFS2 . In its AEO 2006, EIA projected that the volume of ethanol blended into gasoline exceeded the RFS required amounts, resulting in 9.6 billion gallons of ethanol blended into gasoline by 2012. Other provisions of EPAct that were modeled with both the Mathpro and Haverly models included a de facto ban on MTBE and rescinding the RFG oxyg enate requirement . The reference case unit throughputs and gasoline blendstock volumes were used in the refinery

-by

- refinery cost model. For the Haverly refinery modeling work, in addition to the EPAct provisions, the RFS2 renewable fuels volumes were modeled for 2017. For the 2017 reference case, 17.8 billon gallons of ethanol were assumed to be blended into gasoline, and 3.9 billion gallons of renewable and cellulosic diesel fuel and biodiesel were assumed to be blended into diesel fuel for the control case. For gasoline, the ethanol volume beyond the E10 blendwall was assumed to be blended as E15. For the 2030 reference case, we modeled 22.2 billion gallons of corn and cellulosic ethanol, and 8.3 billion gallons of renewable diesel and biodiesel. The third step in conducting the LP refinery modeling was to run the various control cases. The control cases are created b y appl ying a specific fuel control standard to each PADD reference case. To single out a specific cost or other impact, the sole difference between the control case and the reference case is the parameter change being studie d

. For the Haverl y modeling, a control case was run to model the octane loss associated with desulfurization using 2017 as the year of analysis . Since we solel y wanted to identify the cost of recovering lost octane for the refinery

-by

- refinery modeling, this case was run b y reducing the octane value of the FCC naphtha b y one octane number, and this was the sole change relative to the reference case. The control case was run with capital costs evaluated at a 15 percent rate of return on investment (ROI) after taxes. A 

## The octane cost estimated by the LP cost model is 0.7 6 cents per octane number per gallon of FCC naphtha

. Because the octane loss associated with a specific technology may be lower or higher than 1 octane number, we scaled the octane cost based on the relative estimated octane loss on the FCC naphtha (i.e., a 1⁄2 octane loss of the FCC naphtha was estimated to cost 0.38 cents per gallon of FC C naphtha. Table 5

- 35 at the end of this chapter summarizes the data output from the refinery modeling from which we calculated the octane cost for u sing in the refinery

-by refinery cost model. It was necessary

to estimate the gasoline qualities for estimating the emissions impact of the proposed Tier 3 program. This was conducted in two separate steps. First it was necessary

A 

### Normally we conduct the refinery modeling assuming an after

-tax 15% ROI and adjust the costs to reflect a before

-tax 7% ROI to report the costs. However, in this case because the new capital investments were so minimal, we omitted the capital cost amortization adjustment because its effect on costs was judged to be negligible.

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## 5

- 6 to estimate the gasoline qualities of the 2017 and 2030 reference cases relative to the gasoline qualities of a revised base case. The sole differences that we modeled between the 2005 revised basecase and the 2017 and 2030 reference cases was the phase out of MTBE and the addition of ethanol. For the 2005 revised basecase we modeled 1.7 billion gallons of MTBE and 4.1 billion gallons of ethanol. For the 2017 and 2030 reference and control cases, we modeled 17.8 and 22.2 billion gallons of ethanol, respectively

. In 2017, we estimate d that approximately half the gasoline would be 10 percent ethanol and the about the other half would be 15 percent. To model the emissions impact of the different ethanol blends, we modeled two reference cases, one with 100 percent E10 and the other with 100 percent E15. These two ethanol cases were modeled in 2030 and we used the results for 2017 as well . The gasoline qualities for the reference and two ethanol cases are summarized in Table 5

- 57 to Table 5

- 61 in the appendix at the end of this chapter. The changes in gasoline quality are summarized in Table 5

- 2

. Because of the tendency

for the LP refinery

model to shift gasoline blendstocks around resulting in odd gasoline quality

changes in individual PADDs , we solely used the national average change in gasoline qualities and applied those changes for all E10 or E15 gasoline for the emissions anal ys is

. **Table 5**  **- 2**  **Difference i n Gasoline Qualities between E10 and E15 Control Cases with the**  **Reference Case**
Summe r Wi nte r Summe r Wi nte r E200 5. 08 2. 16 11. 08 9. 71 E300 2. 41 -1 .8 9 3. 58 3. 23 Aromati cs -2 .8 8 -1 .2 0 -5 .9 5 -3 .9 9 Ol efin s -0 .9 2 -1 .2 6 -1 .6 8 -1 .7 5 E200 -3 .2 9 6. 96 1. 10 11. 07 E300 -2 .8 2 2. 10 -4 .08 2. 68 Aromati cs -0 .1 7 -2 .7 0 -2 .0 3 -3 .2 2 Ol efin s -0 .3 1 -1 .2 6 -1 .5 5 -1 .46 E200 6. 06 5. 65 12. 03 15. 76 E300 3. 27 0. 76 3. 54 8. 51 Aromati cs -4 .9 3 -5 .8 6 -8 .43 -9 .89 Ol efin s -1 .0 6 -2 .5 6 -2 .1 3 -2 .03 E200 8. 78 5. 19 11. 29 10. 88 E300 0. 95 -0 .1 0 1. 58 3. 81 Aromati cs -2 .9 2 -5 .0 1 -4 .7 1 -7 .6 2 Ol efin s -1 .5 3 -1 .0 6 -1 .8 7 -1 .5 6 E200 3. 46 4. 65 8. 65 11. 77 E300 0. 88 0. 04 1. 08 4. 50 Aromati cs -2 .5 8 -3 .1 9 -5 .2 8 -5 .65 Ol efin s -0 .8 7 -1 .5 9 -1 .80 -1 .7 3 E15

US av g mi nus CA E10 PAD D 1

PAD D 2

PAD D 3

PAD Ds 4 & 5O C



## The second step for estimating gasoline qualities was to model the impact of desulfurization on gasoline qualities. The total impact of desulfurization on gasoline qualities is

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## 5

- 7 comprised of the reduction in gasoline sulfur, the associated reduction in olefins and the impacts of recovering the lost octane. The sulfur reduction is fixed by the standard and the olefins reduction is a function of the selectivity of the desulfuriz ation technologies. We reviewed the information that we had obtained for the gasoline desulfurization technologies and estimated that desulfurizing gasoline from 30 ppm to 10 ppm would result in a 1 percent reduction in olefin level. Since we estimated the cost of making up lost octane using the LP refinery model, we used that case for estimating the impact of octane recovery on gasoline qualities. The gasoline qualities for the reference case and the control case which reflects a 1 octane number loss in the FCC naphtha pool are summarized in Table 5

- 47 to Table 5

- 51 at the end of this chapter

. The difference in gasoline qualities between the reference and control cases is summarized in Table 5

- 3

. Because of the tendency for the LP refinery

model to shift gasoline blendstocks around resulting in odd gasoline quality changes in individual PADDs, we solel y used the national average change in gasoline qualities and applied those changes for all gasoline for the emissions anal ys is. After we integrated the gasoline desulfurization information into the refinery

-by

refinery cost model, we estimated that desulfurizing gasoline from 30 ppm down to 10 ppm would result in about a one

-half red uction in FCC naphtha octane ((R+M)/2) number. To estimate the changes in gasoline quality from a one -half octane number loss in FCC naphtha that we estimated, we divided the gasoline quality changes for one octane number in the FCC naphtha b y a factor of two resulting in half the changes in gasoline quality that we estimated for a one octane number change in FCC naphtha . The second set of columns in Table 5

- 3 summarizes the gasoline quality changes that we estimated for reducing the gasoline sulfur levels from 30 to 10 ppm. B

B 

### Since we completed the LP refinery modeling to estimate the cost for recovering the lost octane and the associated changes in gasoline quality, we found that other Tier 3 refinery modeling studies did not show the same increase in aromatics and decrease in E300 (see also 7.1.3.2). We then discovered that the LP refinery model that we have licensed to use required some improvements in how the refinery model was characterizing both the light

- cut and the heavy

- cut naphtha from the reformer streams to more accurately estimate the E300 and aromatics content of these streams. We have subse quently worked with a contractor to make these improvements to the LP refinery model and will reassess the changes in gasoline quality for the final rule analysis. Thus, while our modeling results shown in Table 5.3 show

a meaningful impact on aromatics and E300, we believe there will in fact be little or no change. Note that these improvements are not expected to have any impact on the cost estimates made by the refinery model.

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## 5

- 8 **Table 5**  **- 3**  **Differences in Gasoline Qualities Between the Control and Reference Cases**

Summe r Wi nte r Summe r Wi nte r E200 -0 .2 0 -0 .2 7 -0 .1 0 -0 .14 E300 -2 .0 3 -0 .6 3 -1 .0 1 -0 .3 2 Aromati cs 1. 14 0. 69 0. 57 0. 34 Ol efin s 0. 60 0. 01 0. 30 0. 01 E200 -0 .1 9 -0 .04 -0 .09 -0 .0 2 E300 -0 .0 6 -0 .1 2 -0 .0 3 -0 .0 6 Aromati cs 0. 48 0. 27 0. 24 0. 13 Ol efin s 0. 09 0. 03 0. 04 0. 01 E200 -1 .68 -0 .0 6 -0 .84 -0 .0 3 E300 -1 .9 9 -0 .3 5 -1 .00 -0 .1 7 Aromati cs 2. 50 0. 45 1. 25 0. 23 Ol efin s 0. 15 0. 04 0. 07 0. 02 E200 0. 50 -0 .69 0. 25 -0 .3 5 E300 0. 14 -1 .6 7 0. 07 -0 .84 Aromati cs 0. 10 -0 .3 2 0. 05 -0 .1 6 Ol efin s 0. 02 -0 .49 0. 01 -0 .2 5 E200 -1 .5 5 -2 .5 4 -0 .7 8 -1 .2 7 E300 -1 .49 -1 .3 7 -0 .7 5 -0 .68 Aromati cs 1. 26 0. 95 0. 63 0. 48 Ol efin s 0. 37 -0 .2 3 0. 18 -0 .1 2 US a vg mi nus CA Adjuste d for 1/2O N 2017 m in us 1 O N in FCC Na phtha
PAD D 1

PAD D 2

PAD D 3

PAD D 4 & 5O C



## 5.1.3 Summary

of Refinery

-by

- Refinery

Model Methodology The purpose of the refinery- by

-refinery cost model is to project how each refinery would reduce the sulfur in its gasoline pool to 10 ppm or lower and to estimate the cost for doing so. To do this we created a U.S. refining industry refinery

- by

-refinery

spreadsheet cost model u sing inputs from an LP refinery model case to allow us to better understand the gasoline sulfur control costs to individual refineries. This spreadsheet cost model also allowed us to model how costs would be affected b y an ABT program. The building of the refinery

-by

- refinery model consisted of two major steps. The first step was to estimate baseline operating conditions for each refinery. This involves estimating the volumes and sulfur levels of the gasoline blendstocks that comprise each refinery ’s g asoline. We chose to use information from 2009 for modeling the baseline operating conditions for the refineries as it’ s the latest year we had data for refiner operations and yields. Additionally, EIA projections indicate d that gasoline demand is expected to be essentiall y flat between 2009 and 2017, alleviating the need to adjust refinery operating throughputs and yields for future changes

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## 5

- 9 in gasoline demand 1



## . C 

## Because of these factors , the 2009 gasoline production volumes and refinery operating conditions can reasonabl y be projected to be at the same level in 2017 (the first year of implementation of the Tier 3 program) in estimating costs and refinery impacts. As a final adjustment to our estimated gasoline volumes and sulfur levels, we calibrated the model to actual refinery

gasoline volume and sulfur levels to ensure our model ’ s accuracy . To estimate the cost for each refiner to lower its gasoline pool down to 10 ppm, we use d our refinery

-by

- refinery

model to estimate the FCC naphtha volume, the sul fur level of the FCC naphtha, and the amount of sulfur reduction nee ded in FCC naphtha to meet a 10

-ppm sulfur standard at each refinery . We also incorporate d in our refinery

-by

- refinery model the impacts that FCC pretreaters have on FCC naphtha yi elds and sulfur levels, as well as the impact of refinery

- specific crude oil sulfur levels on FCC naphtha yields

. Similarly, we also use d the refinery

- by

-refinery

cost model to estimate the volume levels of light straight run naphtha (LSR) and natural gas liquid s (NGL) that require additional hydrotreating, as well as butane volumes that are directly

blended into the gasoline pool. The second step involves applying the various sulfur control technologies to each refinery as necessary

to meet the 10

-ppm sulfur standard. We expect that the majority of the sulfur reduction s necessary

to comply

with a 10

-ppm gasoline sulfur standard will come from reducing the sulfur level in their FCC naphtha. Using our refinery

-by

- refinery model we also estimate that a few refineries will add additional L SR/NGL hydrotreating capacity. We also evaluate each refiner’s cost to install new butane Merox extraction equipment to lower the sulfur level of butane that is directl y blended to the gasoline pool. Reducing the sulfur content of butane was assumed necessary to meet a 5

-ppm sulfur standard for our ABT cases . This assumption is conservative as many refiners may already have this equipment, or may purchase low

- sulfur butanes that have already b een treated b y their supplier. This al lows us to generate a cost estimate for the sulfur control technology in each refinery . The capital costs for installing the sulfur control technologies in each refinery were evaluated based on a 7 percent return on investment (ROI) before taxes. In the following sections, we present the various steps that were used in this refinery

-by

- refinery modeling anal ys is. 5.1.3.1 Estimating Individual Refinery Gasoline Blendstock Volumes In order to develop a baseline for our refinery

-by

- refinery anal ys is, it was necessary to understand the sulfur levels and volumes of the various blendstocks which make up each refinery ’s gasoline. Each refinery blends up its gasoline pool from the various gasoline blendstocks that are produced from the refinery units installed at each re finery . However, information on the volumes and sulfur levels of each gasoline blendstock produced b y each refinery is not publicl y available, so it was necessary to estimate them. Estimating each

C 

### Since we conducted the cost analysis for the proposed rulemaking, we put in place an additional round of greenhouse emission reductions (2017

– 2025) for light duty cars and trucks that will reduce future gasoline demand. When we model the costs for the final rulemaking, we will incorporate this reduction in gasoline demand in our costs analyses.

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## 5

- 10 refinery ’s gasoline blendstock volumes was accomplished u sing actual 2009 refinery specific throughput rates that we obtained from EIA for crude, FCC, cokers and hydrocracking units , and published refinery

unit capacity information for the other refinery units

. We used this information to estimate the extent that each refinery process unit is utilized, followed by a unit

specific anal ys is for estimating how each refinery unit produces material for blending into gasoline. After the unit

- by

-unit estimates are completed, we performed an overall check b y comparing our estimated gasoline volumes with reported gasoline volume s for each refinery, using EPA’s RFG database The model requires the total gasoline volume and each gasoline blendstock volume for each refinery

as an input. Although the model does estimate thi s volume of gasoline produced by each refinery

based on the estimated volumes of each gasoline blendstock, we chose to use actual 2009 gasoline production data reported b y refiners as for the total gasoline volume for each refinery

in our cost calculations

. To compl y with the RFG program, refiners report gasoline production volumes and sulfur levels for reformulated and conventional gasoline to EPA. We used this data and imputed each refiner’s 2009 total gasoline production and corresponding sulfur levels into our model. In the end, our completed refinery

- by

-refinery modeling estimates of gasoline produced on a national basis, correlated very well with the actual refinery production volume in 2009, with our estimated volumes having an overall error of approximately 0.5 percent relative to the reported refinery

production volumes. In order to minimize the impact of this error , we forced the estimated total refinery gate gasoline volume to match actual reported 2009 gasoline production volume across all the refineries. The unadjusted refinery

-by

- refinery estimates of FCC and L SR gasoline volumes, however, are used for estimating necessary equipment modifications and costs for sulfur removal. This is due to the fact that the refinery by refinery models estimates for each refiner ’ s FCC gasoline are likel y to be very close to actual FCC production, as we use actual refinery specific FCC charge throughput rates and account for the effects of FCC feed pretreating on FCC gasoline yields. Additionally, the cost for treating FCC gasoline in our Tier 3 programs, comprise over 85 percent of the total costs, while L SR comprises the bulk of the remaining costs. D



## 5.1.3.1.1 Principal Refinery Unit Volumes To estimate the production volumes for each of the refinery ’s gasoline blendstocks, the refinery

- by

-refinery

model needs process capacity information. The Oil and Gas Journal (OGJ) publishes and the E IA reports unit capacities for the principal refinery units for each refinery

in the U.S

. 2 , 3 

## We updated our database from these two sources to reflect capacity that was in place in 2009, the base year for the model. Where differences between the two databases existed , w e used the information that was judged best overall from the two sources and entered it into the refinery

- by

-refinery

cost model. These unit capacities indicate the maximum throughput rate for each individual unit , not the actual unit throughput rates for each facility, as this is proprietary

D 

### We did not account for any undercutting of the heavy FCC naphtha into jet and diesel fuel, nor did we account for the removal of any pentanes that might be occurring in refineries to comply with stringent summertime RVP standards, therefore our analysis is likely some what conservative and overestimates the costs.

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## 5

- 11 business information and not publicly available. In order to enhance our model, we obtained from EIA the actual 2009 annual unit throughput rates for each refiner’s crude and major refinery units ( FCC, cokers and hydrocracker units ) . With this information, the refinery

-by

refinery model was fine

- tuned to reflect each refinerie s gasoline blendstocks yields. Our use of this information significantly improve d our model’s ability to estimate FCC naphtha, as well as other gasoline blendstocks that each refinery makes. The FCC, coker and hydrocracker unit’s throughputs versus actual capacity that we obtained from EIA for each domestic refinery on a PADD average basis are listed in Table 5

- 4

. This information is presented on a PADD average to protect CBI. **Table 5**  **- 4**  **Process Capacity Utilization a**  

## Crude Throughput FCC

Throughput Coker

Throughput Hydrocracker

Throughput Total U.S. 0.8 43 0.84 0 0. 761 0.7 68 PADD 1 b 

## 0. 779 0. 754 0. 643 0.707 PADD 2 0.859 0.8 14 0.8 10 0. 774 PADD 3 0.85 8 0.880 0. 782 0. 637 PADD s 4/5 excluding California 0.817 0.79 4 0.824 0.90 3

a

### Actual unit throughput rates as a fraction of maximum unit capacity on a PADD basis b

### PADD 1 data includes Hovensa, VI 

## In the model, we also adjusted the refinery capacity information to account for refinery expansion s or refinery

shutdowns that we were aware of and are scheduled to occur over the next several ye ars. Refinery

expansions include tho se announced for WRB Refinery in Wood River Illinois, the Valero Refinery in Norco Louisiana , and the Marathon Refinery in Gary ville, Louisiana. For these expansions, there is limited public data on which of the specific process unit capacities would be increased, though each expansion project has information on the crude unit capacity increase. Since the data was limited , we increased all of the existing individual process unit capacities by the fractional increase in crude oil unit capacity at each of the expanding refineries. Refiners that we believe are permanentl y shutdown in PADD 1 were removed from our anal ys is but , consistent with recent import/export trends, we allowed PADD 3 to supply any lost capacity to PADD 1 as a result of this lost production. PADD 1 refiners that were presumed to be permanently shutdown are ; Giant refinery located in Yorktown, Virginia, Sunoco refinery

in Westville, New Jersey, and Shell Oil refinery in Bakersfie ld, California. 5.1.3.1.2 Other Refinery Unit Volumes The next step was to calculate actual unit throughput rates for the other refinery processes that produce gasoline blendstocks. These unit s include alkylation, dimerization , p oly merization, i somerization, naphtha reforming. All of these processes feedstocks are primarily supplied by the crude and FCC Units. Since this data is similarly not publicl y available we tuned these units to the EIA throughputs rates for crude and FCC units at each facility, with alkylation units running at the same throughput rates as the FCC and the remaining units running at the crude oil throughput ratesThe results of the capacity utilizations of these downstream units are summarized in Table 5

- 5 below.

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## 5

- 12 **Table 5**  **- 5**  **Other Unit Process Capacity Utilization**  **a** 

## Reformer Throughput Alkylation

Throughput Isomerization

Throughput Poly

/Dimersol Throughput PADD 1 0.774 0.886 0.931 1.000 PADD 2 0.859 0.878 0.859 0.859 PADD 3 0.85 8 0.880 0.85 8 0.345 PADD s 4/5 excluding California 0.817 0.794 0.714 0.100

a 

### Actual unit throughput rates as a fraction of maximum unit capacity on a PADD basis 

## With these inputs the refinery

-by

- refinery model now contained estimates of the feedstock charge rates for all of the gasoline blendstock producing units, though estimating refinery unit capacity

and capacity

utilization may

or may not translate directly

into the gasoline b lendstock volume produced b y a specific refinery unit. This is because some refinery units may also produce products other than gasoline blendstock. Additionally, some processes have volume loss of feedstock due to process reactions and conversions that take place that increase or decrease the density

and therefore the volume of products. To take this into account , a gasoline fraction yi eld factor has to be applied to each process to convert the process charge rate into the yi eld of gasoline blendstocks. The process fractional yields that were used in our refinery by refinery model were taken from our MSAT2 final r ule LP refinery

modeling work, which represented the U.S. refining industry on a PADD basis. The FCC unit process yi elds of naphtha blendstock are different for units with an FCC feed pretreater, versus those without feed pretreating. In our modeling we accounted for this by adjusting yields and sulfur levels of FCC units with pretreaters and those without a pretreater. The fractional yields of gasoline blendstock for the major process units and the 2009 throughputs for each of these units used in our model are summarized below in Table 5

- 6 and Table 5

- 7

.

**Table 5**  **- 6**  **Gasoline Blendstock Fraction Yields Per Process Unit Charge**

Crude FCC Units

Average Coker Hydrocracker PADD 1 0. 1 90 0.560 0.234 0.369 PADD 2 0.2 11 0.570 0.234 0.311 PADD 3 0. 188 0.554 0.239 0.212 PADD s 4/5 excluding California 0. 18 3 0. 565 0.234 0.276

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## 5

- 13 **Table 5**  **- 7**  **2009 Refinery Unit Throughputs (1 ,**  **000 BPSD)**

Crude FCC Units Coker Hydrocracker PADD 1 1 , 624 652 <3 a 

## <3 a 

## PADD 2 3 , 193 1 , 017 322 223 PADD 3 7 , 262 2 , 604 1 , 043 500 PADD s 4/5 excluding California 1 , 363 263 130 94

a 

### Since there are less than three refiners in this PADD with these units , the data wa s not reported to protect CBI information. 

## The FCC unit produces significant volumes of naphtha, a gasoline blendstock. The conversion percentage to naphtha is affected by the severity of the operation of the FCC unit. As shown in Table 5

- 6 above, the portion of FCC feedstock converted to naphtha ranged from 55 to 57 percent across the various PADDs. The range among individual refineries can be quite large, but we didn’t have access to refinery specific data for this. However, as a group there is expected to be differences between refineries with and without FCC pretreaters. Therefore, rather than simpl y use the PADD average conversion of FCC feedstock to naphtha for all refineries in a given PADD, the refinery

-by

- refinery model differentiates between refineries that have an FCC feedstock pretreater and those that do not. We have also quantified the gasoline blendstock fraction yield for FCC units that have both feed pretreater and postreater units. Historically, refiners have installed FCC feed pretreaters for economic reasons, as pretreaters increase FCC unit conversion to high value gasoline blendstock while decreasing the production of low value light cycle oils and residual material from FCC units. FCC feed pretreaters also have the benefit of reducing sulfur from the FCC feedstocks, resulting in the production of lower sulfur FCC naphtha and ultimately low er sulfur gasoline. In developing our refinery

- by

-refinery

model, we quantified the impact FCC feed pretreating and postreating has on FCC naphtha yi elds and sulfur levels based on our evaluation of information we received from technology

vendors. The re sults of this analysis are shown in Table 5

- 8 below. **Table 5**  **- 8**  **FCC Unit Gasoline Blendstock Fraction Yields** Average of All FCC Units FCC Units with

No Pretreater FCC Units with a

Pretreater Onl y FCC Units with a

Pretreater and Pos treater PADD 1 0.560 0.558 0.638 0.607 PADD 2 0.570 0.5 33 0.648 0.617 PADD 3 0.554 0.5 20 0.630 0.600 PADD 4/5 excluding California 0.565 0.5 48 0.642 0.612

5.1.3.1.2.1 Poly Gas and Alkylate 

## For the pol ym erization and alkyl ation units the capacity of the unit coupled with its estimated utilization rates listed in Table 5

- 5 is sufficient to establish the volume of gasoline blendstock produced b y these units. For example, a particular refinery unit in PADD 1 might have a 10,000 barrel per day alkylation unit. If the alkylation units in PADD 1 are estimated to

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## 5

- 14 be operating at 56 percent of its listed capacity in 2017 , the alkylate production is projected to be 5,600 barrels per day

at that refinery . Each of the refineries within a given PADD was assumed to have the same utilization rate for any alkyl ation units.

5.1.3.1.2.2 Light Straight Run Naphtha 

## The remaining gasoline blendstocks, including light straight run naphtha (LSR), coker naphtha and hydrocrackate cannot be estimated simply using the unit capacity

and unit utilization rate. In order to determine the volume of gasoline blendstock produced by each of these units , additional steps are required. LSR naphtha is principally comprised of five

- and six

carbon hydrocarbons which come directly from crude oil. Thus the volume of L SR for each refinery was based on the volume of crude oil processed b y each refinery as determined in Section 5.1.3.1.1 , as well as the percentag e of that crude oil that is L SR . The fraction of L SR in each refinery ’s crude oil was estimated on a PADD average basis using the LP refinery model since it is not available on a refinery

-by

- refinery basis . This percentage is based on the types and quality of crude oil processed by all the refineries in each PADD from our LP model 4



## . L SR as a percentage of crude oil is estimated to vary from 4 to 5 percent across the PADDs. These PADD level results are shown in Table 5

- 9 below.

**Table 5**  **- 9**  **LSR as a Percentage of Crude Oil by PADD**

PADD 1 PADD 2 PADD 3 PADD s 4/5 a 

## LSR as a Percentage of Crude Oil 4.5% 5.0% 4.4% 4.4%
a 

### Excluding California 

## After we calculated how much L SR is produced at each refinery we determine d how much of the L SR is used as a gasoline blendstock. L SR has several possible destinations that vary from refinery

to refinery . For each refinery, with the exception of those located in PADD 2, a portion of the L SR is designated to be sold into the petrochemicals market where it is processed into other hydrocarbon compounds. EIA publishes the volume of naphtha which is sold into the petrochemicals market in each PADD 5



## . This information is summarized in Table 5

- 10 below

. Since this information is not publicly available on a refinery

-by

- refinery basis , we assume d that the volume of L SR naphtha sold into the petrochemicals market by each refinery

is proportional to the refinery ’s percentage of the total volume of crude oi l processed in the PADD in which the refinery

is located. After accounting for the volume of LSR naphtha sold to the petrochemicals market, the balance of LSR naphtha is used as a feedstock for the isomerization unit if the refinery

has one. If a refinery does not have an isomerization unit , all of the L SR not sold to the petrochemical market is assumed to be used as a gasoline blendstock. Any volume of LSR at a given refinery

that exceeds the capacity of the isomerization unit at the facility is also as sumed to be used as a gasoline blendstock. However, if a refiner does not have enough naptha hydrotreating capacity to process all of the refiner’s L SR volume, we assumed that the refiner would use excess capacity in their FCC postreater, to reduce the sulfur content of the L SR blendstock.

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## 5

- 15 **Table 5**  **- 10**  **Refiner Sales of Naphtha in 2009 (1 ,**  **000 BPSD)** PADD 1 PADD 2 PADD 3 PADD 4/5 a 

## Naphtha Sold to the Petrochemical Industry 12.2 22.4 161.2 0 Sales of Special Na

phtha 0.8 0 31.4 0
a 

### Excluding California data 

## For further clarity

on gasoline blendstock yields from the model, the gasoline blendstock volumes of L SR and naphtha from the naphtha splitter overhead tower are adjusted to subtract sales of these blendstock s that are sent to the petrochemicals market. E 

## The values listed in Table 5

- 11 for LSR and naphtha splitter overhead are the volumes sent to gasoline, as a fraction of crude throughput. **Table 5**  **- 11**  **PADD Average Gasoline Blendstock Yields per Fraction of Crude Input** PADD 1 PADD 2 PADD 3 PADD ’s 4/5 a 

## LSR to Gasoline 0.0309 0.0286 0.0187 0.0381 Naphtha from Light Naphtha Splitter Overhead 0.0021 0.0081 0.0072 0.0093
a 

### Excluding California 

## In refineries with an isomerization unit , much of the L SR is processed into isomerate, the product produced b y the isomerization unit. The volume of isomerate produced is dependent on the volume of feedstock processed b y the isomerization unit up to its capacity . As described above, all of the LSR that is not assumed to be sold into the petrochemical markets is assumed to be sent to the isomerization unit, up to the maximum capacity of the isomerization unit. The isomerization unit produces a blendstock with a slightly higher energy

density and smaller volume compared to the feedstock volume. To account for this effect, t he volume of isomerate produced is estimated to be 1.6 percent less than the volume of L SR feedstock to the isomerization unit. Hydrocrackate and Coker Naphtha The hydrocracker and coker units also produce some light naphtha material which is blended into gasoline. Heavy naphtha is also produced in these units, which is feed to the reformer, as discussed in the next section. The light naphtha material produced b y the hydrocracker and coker are termed light hydrocrackate and light coker naphtha, respectively

. Based on LPrefinery modeling work done for the MSAT2 rule we estimated that the portion of the feedstock processed by each of these units converted to light coker naphtha and light hydrocrackate was 5 percent for coker units across all the PADDs, and ranges from 23 to 32 percent for hydrocracker units depending on the PADD. The light coker naphtha is poor in quality and require hydrotreating to removes sulfur, olefins and other impurities, before sending them to an isomerization unit, if a refiner has one. Table 5

- 12 below summarizes the percentage of the feedstock to these units that is converted to light naphtha and blended into gasoline.

E 

### Naphtha Splitter towers separate the naphtha feed stream into a light and heavy streams, whereby the heavy stream is typically reformer feedstock, while the light stre am is blend stock lighter than reformer feed.

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## 5

- 16 **Table 5**  **- 12**  **Isomer i** **zation Unit Feed Rates by PADD**

PADD 1 PADD 2 PADD3 PADD 4/5 a 

## Li ght Coker Naphtha (% of Coker Feed) 5.0% 5.0% 5.0% 5.0% Li ght Hydrocrackate (% of Hydrocracker Feed) 28.7% 32.0% 23.3% 27.2%

a 

### Excluding California



### 5.1.3.1.2.3 Reformate 

## The volume of reformate produced b y the reformer was estimated based on the volume of feed to the reformer as limited by each unit’s capacity . The feed to the reformer comes from variou s sources depending on the refinery configuration. For virtuall y all refineries, the heavy part of the straight run naphtha from the atmospheric crude tower is sent to the reformer , while the light naphtha is generally processed in the isomerization unit or blended directly into gasoline as discussed above . Those refineries with a hydrocracker or a coker will send the heavy naphtha from these units to the reformer as well. This reformate feed naphtha contains the six, seven, eight and usually

the nine carbon compounds from these various sources. In some cases, the six carbon compounds are separated from the rest of the reformate feedstock to reduce the benzene in the final reformate. The volume of the feed to the reformer is estimated based on a fractions of the material processed in the atmospheric crude tower, hydrocracker and coker on a PADD b y PADD basis using information from the LP refinery model

. The fraction of crude oil that is fed to the reformer from the atmospheric crude tower ranges from a

bout 13 to 16 percent of the crude oil input depending on the PADD. About 18 percent of the material processed in the coker unit is estimated to end up as feedstock to the reformer. The percentage of the feedstock processed in the hydrocracker that is fe d to the reformer ranges from 30 to 50 percent depending on the PADD in which the refinery is located. The variance in the fraction of hydrocracker material sent to the reformer is due to the significant flexibility that the hydrocracker has for producing either gasoline or diesel fuel. In certain PADDs, such as PADD 4 and 5, there is a higher relative demand for diesel fuel compared to gasoline so there is a lower conversion to naphtha than in other PADDs. The product from the reformer experiences a volume decrease of about 18 percent relative to the volume of feed , due to the conversion of straight chain and cyclical hydrocarbons to energy dense aromatics and other light products. This volume reduction and conversion to lighter products increases with the severity and thus the conversion of the reformer unit. All the refineries in each PADD are assumed to be operating their reformers at the same severity as estimated by the LP refinery model. Each of the values discussed in this paragraph are shown on a PADD b y PADD basis in Table 5

- 13 below. **Table 5**  **- 13**  **Reformer Feed Rates and Volume Loss** PADD 1 PADD 2 PADD3 PADD 4/5 a 

## Medium/Heavy Straight Run Naphtha (% of Crude Input) 13.8% 16.2% 14.0% 13.6% Medium/Heavy Coker Naphtha (% of Coker Feed) 18.4% 18.4% 18.4% 18.4%

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## 5

- 17 Medium/Heavy H ydrocrackate (% of Hydrocracker Feed) 35.4% 43.4% 50.2% 33.3% Volume Loss in Reformer 18% 17% 18% 19%
a 

### Excluding California



### 5.1.3.1.2.4 Purchased Blendstocks 

## Some gas oline blendstocks are purchased and blended into gasoline. The gasoline blendstocks ty

pically purchased include natural gasoline, alkylate, isooctene and ethanol. We did not have information on the volume of these gasoline blendstocks purchased and blended into gasoline b y each refinery, so we again relied on the information from EIA, which reports the consumption of these blendstocks on a PADD basis. The EIA information on the amount of pentane plus, naphtha ’ s and NGL s purchased in each PADD are listed in Table 5

- 14 below. Our RFG database has each refiners amount of ethanol blended into RFG, but does not contain the amount of ethanol that is splash blended into CG at terminals. We accounted for ethanol blended into CG, as wel l as the purchase of other gasoline blendstocks, by assuming that each refinery purchased a volume of any given gasoline blendstock purchased within their respective PADD proportional to that refinery ’s crude oil consumption within the PADD. Inthe 2009 RFG database, the ethanol volumes only averaged 2.7 percent of refiner’s gasoline production, which results in an over estimation of our refinery and program costs in this NPRM. Inour NPRM anal ys is, we did not include any desulfurization costs for Pentane plus and naphtha and lighter blendstocks , since we did not know the extent that they were being treated today

. However, the addition of these blendstocks, results in very negligible increases in demand for additional naphtha hydrotreating

. We will evaluate whether we need to include any costs for treating these streams in the final rule analysis. If there are costs, because the streams are so small, the costs would be negligible.**Table 5**  **- 14**  **Refiner Purchas es in 2009 (1**  **, 000 BPSD)**  **c** 

## PADD 1 PADD 2 PADD 3 PADD 4/5 a 

## Natural Gas Liquids 17.5 115.9 272.4 15.5 

## Naphtha’s and lighter 24.6 39.3 53.7 3.8 

## Pentane s Plus 0 41.8 94.9 25.7 

## Ethanol b 

### 57.3 66.9 77.3 0.40 Note s: a 

### Excluding California b 

### Ethanol from EPA RFG database, excluding volume s that are splash blended into conventional gasoline c 

### Natural Gas Liquids and Pentanes Plus are different names for the same hydrocarbon stream and we inadvertently found two different volumes for the same hydrocarbon stream and added them both as inputs into our refinery cost model. We will correct this in the final rulemaking analysis. Butane Volumes 

## To estimate the butane volumes in our refinery

- by

- refinery model we used an RVP balance equation. This equation states that the product of the overall RVP and volume of the gasoline pool is equal to the sum of the product of the RVP and volumes of the non

-butane components plus the product of the RVP and the volume of the butane blendstocks. This equation can be rearranged to solve for the volume of butane blendstocks as shown in Equation 5

- 1 below.

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## 5

- 18 **Equation 5**  **- 1**  **RVP Butane**  **Balance Equation Butane =**  **(A*** **D -** **B*D)/(C** **- A)**  Where: Butane = Volume o f Butane added in each refinery in BPSD A = Blended gasoline RVP average B = Non

-butane blendstock RVP average C = Butane RVP D = Volume of gasoline produced 

## The gasoline production volumes and RVP of the blended gasoline are reported to EPA by refiners for each refinery and were used for the A and D terms in Equation 5

- 1 . To calculate the RVP of the butane used as gasoline blendstock we first had to consider the relative proportion of isobutane versus n

-butane being used as a gasoline blendstock as their RVP values differ. This ratio was estimated on a PADD b y PADD basis from the LP modeling work. We then used a volume weighted average to calculate the RVP of the mixed butane stream blended into gasoline in each PADD. The informati on for these calculations is shown in Table 5

- 15 below . The non

-butane blendstock RVP was estimated by multiplying each individual gasoline blendstock RVP times the gasoline blendstocks volume fraction of each refineries gasoline poo l (CG and RFG) using 2009 ethanol volumes and taking the sum of all of these values

. The RVP value for each of these streams is shown in Table 5

- 16 below. With this information we were then able to estimate the volume of butane adde d to the gasoline blendstock at each refinery

. The annual volumes of butane added b y refineries on a PADD level are listed in Table 5

- 17

. The volume of butane blended into gasoline at each individual refinery varies based on the annual average gasoline RVP that the refinery produces ( the RVP of CG and RFG gasoline are volume weighted together), as well the variance in gasoline blendstock streams th at a particular refinery use s to produce CG and RFG gasoline. **Table 5**  **- 15**  **PADD Average Composition of Mixed Butanes Added to Gasoline** PADD 1 PADD 2 PADD 3 PADD ’s 4/5 a 

## Isobutane % 96% 32% 53% 66% N

-butane % 4% 68% 47% 34% Mixed Butane RVP (C) , psi 71.376 58.192 62.518 65.196
a 

### Excluding Cali fornia

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## 5

- 19 **Table 5**  **- 16**  **PADD Average RVP’s of Gasoline Blendstocks**

PADD 1 PADD 2 PADD 3 PADD ’s 4/5 a 

## LSR 12.0 12.0 12.0 12.0 Naphtha from Light Naphtha Splitter Overhead 3.0 3.0 3.0 3.0 Reformate 4.5 6.6 5.0 6.2 FCC Naphtha 4.6 4.6 4.6 4.6 Coker Naphtha 13.0 13.0 13.0 13.0 Isomerate C5 13.0 13.0 13.0 13.0 Isomerate C6 7.2 7.2 7.2 7.2 Natural Gas oline (NGL) 12.6 12.6 12.6 12.6 Poly merization Gasoline 2.8 2.8 2.8 2.8 Li ght Hydrocrackate 9.2 9.2 9.2 9.2 Alkylate, C3 3.6 3.6 3.6 3.6 Alkylate, C4 3.2 3.2 3.2 3.2 Dimersol 5.8 5.8 5.8 5.8 Ethanol 10.7 10.7 10.7 10.7
a 

### Excluding California data 

## Table **5 -**  **17 PADD Average Gasoline Data**  PADD 1 PADD 2 PADD 3 PADD ’s 4/5 a 

## Non

-butane blendstock RVP (B) , psi 6.4 6.3 5.7 6.3 Gasoline Pool Volume (D) , BPSD 738.2 1744 3487.8 500.3 Volume Butane Added, BPSD 21.4 95.1 143.1 25.7 Blended Gasoline RVP average (A) , psi 8.5 9 8 9.1
a 

### Excluding California data



## 5.1.3.2 Calibrating the B lendstock Volumes in the Refinery

- By

- Refinery Model After calculating gasoline volume estimates for each refinery in the refinery

- by

- refinery cost model , we calibrated these values against their reported gasoline blendstock volumes. Refiners report their production volumes for both conventional and reformulated gasoline to EPA to comply

with the gasoline reporting requirements. We used these reported volumes from 2009, along with LP modeling results from our MSAT2 Rule , to calibrate the refinery

-by

refinery model. Before making any adjustments, the refinery

-by

- refinery modeling estimates for gasoline produced on a national basis correlated very well with the reported refinery production volume in 2009, with volumes differing b y less than 0.5 percent from actual production . In order to eliminate this discrepancy we modified each refiner’s yields in our refinery

- by

-refinery anal ys is based on the 2009 data as reported by the refineries. The volume of each of the gasoline blendstocks, excluding the light straight run (LSR) and FCC gasoline streams, were increased or decreased proportionally

in order to align the aggregated national finished gasoline production volumes in our refinery

- by

- refinery model with the aggregated national finished gasoline production volume reported by US refineries in 2009.

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## 5

- 20 In making adjustments to the refinery

-by

- refinery anal ys is to better align its volumes with the reported gasoline volumes and sulfur levels , we did not make any changes to the production volumes of L SR or FCC gasol ine. The L SR and FCC gasoline volumes are left unchanged as these volumes are based on actual refinery

- specific FCC charge throughput rates

. This account s for the effects of FCC feed pretreating on FCC gasoline yields and is therefore likely to accuratel y reflect the production volumes for each individual refinery . Additionally, these volumes are of central importance to our anal ys is as they are used for estimating the equipment modifications necessary

for complying with new Tier 3 sulfur standards and the costs associated with additional sulfur removal. With these calibrated volumes for each of the gasoline blendstocks , the refinery

- by

refinery model can now be used to estimate the sulfur level that refiners must achieve in the FCC naphtha to meet the current sulfur limit under the Tier 2 standards. These volumes also allow us to model what modifications to existing equipment and refinery operations will be required to comply with the new Tier 3 sulfur standards 5.1.3.3 Refinery

Blendstock Sulfur Levels After determining the volume of each gasoline blendstock stream , we next estimated the sulfur level of each of the gasoline blendstocks for our modeling anal ys is using information we collected from literature reviews and discussions with refinery consultants and technology providers. We also considered the blendstock sulfur levels estimated for the MSAT2 rule and the estimates derived from our refinery

-by

- refinery model to estimate the sulfur levels of the blendstock streams. Establishing these sulfur levels is important as this sets a baseline for the refinery

- by

-refinery

model that represents our estimate for the current operations of each refinery

. This allows us to project what changes refiners would have to make in their refineries to comply

with the Tier 3 standards, and project the new investments and operating costs associated with these changes. The following section contains further detail s on how the sulfur content of each of the blendstocks was estimated. The results of this analys is can be found in Table 5

- 18 at the end of this section. The first stream we considered was the butanes that are used as a gasoline blendstock. The butanes used as gasoline blendstock within a refinery come from a variety

of sources. Much of the butane used as a gasoline blendstock is distilled from the crude oil or other blendstock streams within the refinery

. Refiners remov e the butanes from crude oil and sometimes gasoline blendstocks which contain some butane (i.e., FCC naphtha, hydrocrackate) and then blend them back into the gasoline up to the RVP or vapor/liquid limit applicable to the gasoline market that the gasoline is being sold into. During the summer months refiners usually have excess butane which cannot be blended into the gasoline pool because of the tighter RVP standards

. Many refiners store the ex cess butanes and then blend them back into gasoline in the winter months when the volatility

limits for gasoline are less stringent

. Other source s of butanes used as gasoline blendstocks are natural gas processers and crude oil drilling operations. The butanes from these sources are produced in downstream units which separate the various hydrocarbon components. Most of these downstream units “sweeten” the butanes using a Merox unit pri or to shipping them in pipelines or selling them directly to refiners

. The sweetening process re acts the hydrocarbon mercaptan compounds to disulfide compounds reducing their odor and corrosivity

. The sweetening process, however, does not lower the sulfur level. If the source natural gas well

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## 5

- 21 is very high in sulfur, the operator may need to use an extractive Merox treatment technology which actuall y removes the sulfur from the butane stream. This treatment generall y lowers the sulfur level of the butane s to under 5ppm. Butanes that are blended into gasoline have a sulfur limit of 30 ppm and those that are shipped through pipelines, regardless of their end use, have a limit of 140 ppm. Furthermore, many refiners have Merox units on site that are capabl e of removing sulfur from butanes that are either purchased or generated internally from refinery units. We were, however, unable to evaluate existing butane Merox treating capacity at NGL processers, crude drilling operations, or in refineries as there was no information available in the OGJ , from EIA , or other publically available sources. Because we do not know the prevalence of these units , we conservatively assumed in our baseline case that refiners are adding treated butanes with a sulfur content of 10 ppm to their gasoline pool. F 

## For hydro crackate, dimersol, and poly gas blendstock streams , we used the same sulfur levels that we estimatd for our MSAT2 rulemaking . The sulfur levels for these streams are inherently

low due to the dy

namics of process reactions in the hydrocracker, dimersol and poly merization units. Furthermore , it is unlikely that refiners have altered the se processes in their refineries since our anal ys is for the MSAT2 rule was completed. Alkylate blendstocks usually have a small amount of sulfur, usuall y less than 15 ppm. The primary

source of sulfur in alkylate is the sulfuric acid that is used as a catal ys t in the alkylation process. Finished product coalescers and knockout drums are used by refiners to remove impurities, including sulfuric compounds, from the alkyl ate product as it leaves the alkylation unit. This separation is imperfect, and a small quantity of the sulfuric compounds which remain in the alkyl ate account for the majority of its sulfur content. Prior to the enactment of the Tier 2 standards , the alkylate produced by most refineries contained 10 to 15 ppm sulfur which assumes that there was some carryover of sulfuric compounds into the alkylate . Based on our discussions with gasoline desulfurization technology v endors, however, refiners have installed new acid coalescers and knock out drums in recent ye ars. These new units improved the removal of residual sulfuric compounds and can produce an alkyl ate blendstock with a 5

-ppm sulfur level. This adjustment by ref iners seems to be a low cost method for reducing the sulfur content of alkyl ate. For our refinery

-by

- refinery baseline anal ys is, we assumed that refiners have already installed improved acid knockout drums and are currentl y producing a 5

-ppm alkylate. We also assumed that Hydro f luoric Acid (HF) alkylation processes had the same alkyl ate yi eld per feedstock throughput as a sulf uric acid alkyl ation unit in our refinery by refinery model

. W e assumed that the sulfur level of alkyl ate from an HF units also av erages 5 ppm sulfur , even though HF processing units use hydrofluoric acid as the processing catal ys t, instead of using sulfuric acid. The coker unit produces a gasoline blendstock with a significant amount of sulfur. These units convert the heavy porti on of crude oil, called residuals, into gasoline and diesel blendstocks through the use of heat and pressure. The gasoline blendstock produced by the coker can contain

F 

### After we completed our cost analysis, we met with UOP staff, including those who market their Merox technology for removing mercaptans from gasoline streams. The UOP staff said that pretty much all butanes are already being treated by Merox (or similar) extraction units. Thus, there would be no additional cost for treating butanes for complying with Tier 3. We will update our cost analysis to reflect this for the final rule cost analysis.

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## 5

- 22 more than 3 , 000 ppm sulfur. This stream is normally split into two different streams. The stream which contains the six to nine carbon hydrocarbons is processed in the naphtha hydrotreater, which reduces the sulfur level of this blendstock to below 1 ppm. This stream is then routed to the reformer for octane improvement. The five and six carbon hydrocarbon portion of coker naphtha is called light coker naphtha and usually contains on the order of several hundred ppm sulfur. Because of the instability of this stream due to its high olefin content , it is generall y processed b y the naphtha hydrotreater and sent to the isomerization unit if the refinery

has one . After being processed in the hydrotreater , the sulfur content of this stream is reduced to approximately 1 ppm. These treating pathways were assumed for each refinery in the refinery-by

- refinery

baseline anal ys is. Straight run naphtha is a gasoline blendstock which contains a moderate amount of sulfur. Straight run naphtha is the product stream from the atmospheric crude oil tower with a boiling point that falls within the boiling range of gasoline. The heaviest portion of straight run naphtha is higher in sulfur relative to the lighter portion of the straight run naphtha. The heavy portion of straight run naphtha is normally processed by

the reformer in order to improve its octane before being blended into gasoline. After this processing , the reformate has a sulfur level of less than 1 ppm. The light straight run naphtha (L SR) contains the five and part of the six carbon hydrocarbons and has on the order of 100 ppm sulfur before any hydrotreating. L SR that is routed as feedstock to isomerization units has its sulfur lowered to 1 ppm by processing in the naphtha hydrotreater. This hydrotreating is necessary to allow this material to be processed in the isomerization unit, as the catal ys ts in these units require low sulfur feedstocks to function properl y. Some refiners, however, do not have isomerization units or they produce LSR volumes that are greater than the capacity of their isomerization units. Even cases where there is in sufficient capacity in the isomerization units it is still desirable for refiners to hydrotreat as much of the L SR as possible since it is more cost

- effective to reduce the sulfur content of the LSR than the FCC naphtha. Refiners can either hydrotreat thi s volume of LSR in the naphtha hydrotreaters or in FCC naphtha postreaters. Natural Gas Liquids (NGL) have a composition that is similar to L SR, as it is comprised primarily of pentanes and hexanes . NGLs are produced from natural gas processers and crude oil drilling operations and the sulfur content of the NGLs can vary depending on its source , although we estimate that this stream averages about 100 . While some of the NGLs are treated to remove sulfur by

the NGL producers before being purchased by the refineries we did not have sufficient information to be able to determine the extent to which NGL s are treated before arriving at the refinery . For the baseline case in our refinery

-by

- refinery model we assumed that NGL liquids are purchased with a sulfur content of 100 ppm and hydrotreated based on capacity availability

at refineries in a similar manner as LSR. Based on the gasoline blendstock volumes and hydrotreating capacities as discussed in the previous sections , we estimated in the baseline case for our refinery

- by

-refinery anal ys is that refiners are hydrotreating 66 percent of the volumes of L SR and NGLs produced and purchased for gasoline blendstock usage on a national average basis . Our hydrotreating capacity evaluation for each refinery is discu ssed in more detail in Section 5.1.3.4

. As a result of the proposed sulfur standards under the Tier 3 program , we anticipate that refiners will revamp existing hydrotreaters and add new hydrotreating capacity to allow them to hydrotreat all of their L SR and NGLmaterial.

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## 5

- 23 We also assumed that all ethanol blended into gasoline has a sulfur content of 5 ppm. Ethanol produced at ethanol plants naturally ha s a negligible amount of sulfur. Before being sold, however, a denaturant is added to the ethanol. This denaturant most commonly used is natural gasoline, a C5 to C7 naphtha produced during natural gas processing. Natural gasoline has a sulfur content that ranges anywh ere from a few parts per million to a couple hundred parts per million sulfur. We assumed that the natural gasoline used as an ethanol denaturant is not hydrotreated and has an average sulfur level of 2 5 0 ppm. Ethanol contains 2 percent denaturant, which results in denatured ethanol having a sulfur level of 5 ppm . After determining the sulfur level for each of the gasoline blendstock streams as discussed above we can use this information, along with the gasoline production volumes and sulfur levels for the United States in 2009, to determine the sulfur level of the FCC naphtha stream on a national average basis. To do this we used the following equation , referred to as Equation 5

- 2 hereafter : FCC Naphtha Sulfur ppm = [ (A*B)

– (C*D+E* F+G*H+I*J+K*L+M*N+O*P+Q*R+S*T)] / Z Where: A = Refinery

Total Gasoline Yield, BPSD B = Refinery

Total Gasoline Sulfur level, ppm C = Butane to Gasoline, BPSD D = Butane Sulfur, ppm E = Alkyl ate BPSD F = Alkyl ate Sulfur, ppm G= Reformate BPSD H= Reformate Sulfur, ppm I = Coker Naphtha, BPSD J = Coker Naphtha Sulfur, ppm K= Hydro

- crackate BPSD L= Hydro

- crackate Sulfur, ppm M= Light Straight Run (LSR) and Natural Gas Liquids (NGL), BPSD N =L SR and NGL Sulfur, ppm O= Dimersol, BPSD P= DimersolSulfur, ppm Q= Poly merization BPSD R= Poly merization Sulfur, ppm S= Ethanol, B PSD T = Ethanol Sulfur, ppm Z= FCC Gasoline Yield, BPSD **Equation 5**  **- 2**  **Calculating FCC Naphtha Sulfur Content for Refinery -** **By -** **Refinery Model** We used this equation to assess two cases; a baseline case where the 30

-ppm Tier 2 sulfur standards were full y implemented and a control case that reflects the proposed 10

-ppm Tier 3 sulfur standards. The only terms in Equation 5

- 2 that change between the two cases are the national average sulfur level and the sulfur levels of the L SR, NGL, and FCC naphtha streams. The national average sulfur levels for the two cases were set at the sulfur limits under the Tier 2

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## 5

- 24 and Tier 3 programs

-- 30 ppm and 10 ppm , respectively . For the baseline case we assum ed that the sulfur level of the NGLand L SR streams was 34 ppm. This reflects our assessment of how these streams are currently being handled as discussed earlier in this section

. We estimate that 66 percent of the volume of NGL and LSR are hydrotreated before being blended into gasoline and have a very

low sulfur content of approximately 1 ppm

. The remaining 34 percent are untreated and have a sulfur content of approximately 100 ppm. For the Tier 3 control case we assumed that all of the NGL s and L SR were hydrotreated and therefore had an average sulfur content of 1 ppm. This information allowed us to solve Equation 5

- 2 for the FCC naphtha content. The resulting FCC naphtha sulfur numbers, along with our estimation of the gasoline blendstock sulfur levels and percent of total gasoline volume made up b y each blendstock are shown in Table 5

- 18 below.
**Table 5**  **- 18**  **Sulfur Levels for Gasoline Blendstocks in the Refine ry** **- By** **- Refinery Model**  Gasoline Blendstocks Baseline Tier 2 Case Proposed Tier 3

Case Year 2017 Proposed Tier 3

Case Year 2030 Percent of Total Volume Sulfur

Levels 30 ppm Percent of Total Volume Sulfur

Levels 10 ppm Percent of Total Volume Sulfur

Levels 1 0 ppm FCC Naphtha 37.2 80 a 

## 36.0 2 1 a 

## 3 5 .0 2 1 a 

## Reformate 22.5 0.5 21.8 0.5 21.2 0.5 Alkylate 12.7 5 12.5 5 12.1 5 Isomerate 3.2 0.5 3.1 0.5 3.1 0.5 Butane 4.0 10 4.0 10 3.8 10 Li ght Straight Run Naphtha (L SR) and Natural gas Liquids (NGL) 5.2 34 4.9 1 4.8 1 Hydrocrackate 3.0 8 2.9 8 2.8 8 Ethanol 9.9 5 12.5 5 15 5 Coker Naphtha 2.2 0.5 2.1 0.5 2.0 0.5 Other Gasoline Blendstocks 0.2 10 0.2 1 0 0.2 10 Total/Sulfur Average 100 30 100 10 100 10
a 

### These values are calculated using Equation 5

- 2 ; all other sulfur levels are assumed 

## The numbers in the table above represent national averages. While this is useful information , it is insufficient for us to be able to model the implications of the proposed Tier 3 standards for an individual refinery . Each refinery has a unique combination of processing units that will determine the cost and operational changes necessary for that refiner to comply with our proposed sulfur limit. While each of these processing units may impact the cos t for refiners to lower the sulfur content of the gasoline they produce we believe these costs will be dominated by the units responsible for the desulfurization of the FCC naphtha, and to a lesser extent the NGLs and L SR. This is because these are the only streams we anticipate would see significant sulfur reduction under the proposed Tier 3 sulfur standards. The units that are used to desulfurize these streams include the FCC unit pre

- and pos treaters and the naphtha hydrotreaters. It is important,

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## 5

- 25 therefore, to have a good understanding of which of these units are in place in each refinery, as well as the ty

pe and capacity

of these units, in order to allow us to most accuratel y estimate the cost of the Tier 3 sulfur standards to the refining industry

. We used the above FCC naphtha sulfur balance information as the basis of our vendor request for refiner modifications to FCC postreaters under Tier 3 . However, for the vendor request s, we used a preliminary model, where the FCC naphtha levels under Tier 2 averaged 75 ppm, while FCC naphtha levels under Tier 3 averaged 25 ppm for 10

- ppm sulfur gasoline , representing a 50 ppm sulfur reduction , close to the same delta presented in the table above

. The following section discusses our assessment of the desulf urization equipment currentl y being used in refineries. 5.1.3.4 Assessment of Refineries’ Existing Desulfurization Equipment Since the desulfurization cost of the Tier 3 program is largel y impacted b y the cost of lowering sulfur in FCC gasoline , it is important to understand what refiners are already doing to lower the sulfur content of the FCC gasoline blendstock to meet the Tier 2 sulfur standards. This was important to our analysis of the cost for each individual refiner to reduce the sulfur content of their ga soline to meet the proposed Tier 3 sulfur standard. Refiners that already have an FCC pretreater or postreater can revamp these units for a lower cost than installing grass roots units. It was also important to determine which refinerie s have an FCC feed pretreater, since these units increase the refinerie s FCC conversion and production of FCC naphtha and also lower the sulfur level of the FCC naphtha. To compile this information we anal yz ed capacity information for FCC naphtha pretreaters and postreaters for each refinery listed in the OGJ and the EIA database. If one of the databases showed that a refinery had FCC pretreating and/or post

- treating capacity, while the other did not, we assumed that the refinery did have the units listed with a capacity a s reported. For refineries that have FCC naphtha postreaters we next determined which vendor’s FCC naphtha desulfurization technology is installed in each refinery . To do this we conducted a public database search using OGJ, company web postings and, other refinery publications. To supplement this data we also had extensive discussions with many refiners to obtain confidential data from many of them on type and capacity of the desulfurization technology currentl y installed in their refineries as well as how their operations might be adjusted to meet the new Tier 3 sulfur standards. The various FCC naphtha desulfurization technologies that we identified as currently

being used by

refiners are CD Tech’s Cd Hydro and CDHDS, Axens Prime G and Prime G+, UOP’s ISAL and Selectfining, Exxon’s Scanfining I or II and Sinopec’s S

- Zorb. For refiners that we could not find or obtain information on the ty pe of desulfurization they were using , Axens was chosen as the default as they have the largest market share of desulfurization units in the U.S. T o confirm the accuracy of our work we reviewed our assessments with one of the main technology

vendors . Our desulfurization technology selection assumptions were adjusted based on feedback from the vendor. The aggregated results of this assessment are summarized in Table 5

- 19 below.

**Table 5**  **- 19**  **Postreater Technologies**  **Used By Refineries** 

CD Tech IFP/Axens Scanfining UOP I SAL S

- Zorb Refiners with Existing P ostreater 15 40 16 1 4

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## 5

- 26 The next step of our analysis was to determine which refineries use FCC feed hydrotreating technology (pretreaters) in addition to post

- treating units. FCC feed hydroteating was primaril y installed at refineries not as a sulfur control technology, but because of the economic benefits that can be obtained from hydro

- treating FCC feed. Hydrotreating the FCC feed increases the crackability of this stream by

saturating the components with hydrogen resulting in a higher paraffin content in the feed stream. Hydrotreating also removes FCC feed impurities such as nitrogen, metals, con

- carbon and sulfur, which improve FCC unit catalyst effects. An additional benefit of FCC feed pretreating is that it reduces the sulfur content of the FCC f eedstock b y 70 to 90 percent , resulting in the production of FCC naphtha with lower sulfur levels than what would be produced using FCC feed that is not hydrotreated. Our anal ys is indicates that approximately 53 refiners are currentl y using FCC feed pretreaters. Of the 53 refineries with pretreaters, 35 of also have FCC postreaters installed to comply with the Tier 2 gasoline sulfur standard

. The technologies used b y these 35 refineries are shown in Table 5

- 20 below. FCC naphtha produced using onl y an FCC pretreater operating at standard severity generally produce s a gasoline with a sulfur content that exceeds the Tier 2 standards. According to information from vendors , the average FCC naphtha sulfur level of refineries with an FC C feed pretreater operating at standard conditions without a postreater ranges from 200 to 500 ppm. Further reductions in the sulfur level of the FCC naphtha are possible using only

an FCC pretreater b y operating the pretreater at a higher severity or higher pressure (if the unit is designed to do so) . These high pressure FCC pretreating units were designed to be able to run at a high severity to further increase the crackability of the FCC feed and therefore increase the conversion rate of the FCC unit

. These more severe conditions also further reduce the sulfur level of the FCC naphtha. The naphtha produced from these units operating with high severity or high pressure has an average sulfur content ranging from 75 to 100 ppm, allowing these refineries to produce gasoline that meets the Tier 2 sulfur standards. Operating FCC pretreaters at the high severities necessary to meet the Tier 2 standards , however, also results in increased operating cost, as the pretreater requires more frequent catalys t chang eouts, consumes more hydrogen, and operates higher temperatures than pretreaters operating under standard conditions. **Table 5**  **- 20**  **Technologies Used By Refiners with FCC Pre and Postreater**  **s**

CD Tech IFP/Axens Sc anfining UOP I SAL S

- Zorb Refiners with FCC Pretreater and Naphtha Postreater 9 20 5 0 1
Our anal ys is also showed that there are several refineries that have an FCC unit but have installed neither an FCC naphtha postreater nor an FCC feed pretreater. The se are small refineries, or refineries that produce a refinery gate gasoline with a sulfur level below the Tier 2 cap of 80 ppm sulfur, but above the 30

-ppm average. These refiners are relyingon buying or sharing sulfur credits from other refineries that are over- complying with Tier 2 and make gasoline with a sulfur level less than 30 ppm. Finally, some refinerie s do not have an FCC unit and therefore have not installed FCC pos treaters to compl y with the Tier 2 sulfur standards. These refiners primarily use reformate, alkylate, LS R, butanes, and pentanes to make gasoline. Since these blendstocks all have low

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## 5

- 27 sulfur content this allows refiners to produce gasoline with a low enough sulfur content to meet the Tier 2 sulfur standards. A summary

of the number refineries which fall into differing categories of how they are complying with Tier 2 is shown in Table 5

- 21 below. **Table 5**  **- 21**  **Refinery FCC Naphtha Desulfurization Unit Characteriza tion** 

5.1.3.5 Crude Oil and FCC Feed Sul fur Levels After we had determined the desulfurization technology in place at each refinery, we sought to calculate the sulfur content of the FCC feedstock. Knowing this is important as it allows us to determine how far the sulfur level of the FCC naphtha , and ultimately the gasoline, produced at any given refinery can be reduced using the units currentl y in place at each refinery. It also helps us understand the extent to which the existing hydrotreaters are being taxed to comply with the Tier 2 gasoline sulfur standard. Some refinerie s may have excess capacity in their FCC naphtha pretreater or postreaters that would allow them to produce gasoline that would meet the proposed Tier 3 standards without having to revamp existing units or add grass roots units. These refineries will have much lower cost impacts than refineries that have to make more significant capital investments. The sulfur level of the FCC feedstock is primarily dependent on the sulfur level of the crude oil being processed by the refinery

and whether or not the refinery has an FCC feed pretreater. The first step, therefore, in determining the sulfur level of the FCC feedstock was to input the crude sulfur level for each refinery into our refinery

-by

- refinery model. For this, we obtaine d confidential business information ( CBI) from EIA on the annual average crude sulfur levels that each refinery

processed in 2009. This data, which is reported to EIA for each refinery, was used as the baseline crude sulfur level in our refinery

-by

- refinery anal ysis. Using this data, we then determined what each refiners FCC feed charge rate sulfur level would be, using a regression co

-relation we built from data on crude sulfur levels and FCC feedstock material , as discussed below

. We assumed that refinerie s today are primarily

processing heavy

gas oils (HGO) and vacuum gas oils (VGO) produced from each refinery ’s crude and coker units. To determine the volume of feedstock processed b y the FCC units we assumed that after distillation HGO makes up 20.5 percent (by volume) of the processed crude and VGO makes up an additional 15.6 percent of the crude

. 6 

## Together, these two streams comprise the FCC feed. The boiling point range that we assumed for VGO also contained some residual material , representing FCC feed with residual content . This was done to reflect the imperfect distillation cuts in crude towers and that some refiners use small amounts of residual material as FCC FCC Treatment Units Installed Number of Refineries No FCC Unit 14 FCC Unit, No Pretreater or Postreater 7 FCC Unit With Postreater Only 38 FCC Unit With Pretreater Only 17 FCC Unit With Pretreater and Postreater 35

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## 5

- 28 feedstock . The balance of the residual material, however, was excluded from the fee d to FCCs since this material makes a poor feedstock due to its high aromatics, metals and concarbon content. Each of these materials negatively affects the FCC gasoline conversion yields. Most refiners today

do not directly

use residuals as feedstock to their FCC units, but instead send them to be processed in coker units or use the residual material for fuel oil and asphalt production. The boiling point ranges that we used for HGO and VGO are listed Table 5

- 22 below.

**Table 5**  **- 22**  **Boiling Ranges of FCC Feedstocks**

TBP Initial TBP Final Heavy Gas Oil (HGO) 600°F 800°F Vacuum Gas Oil (VGO) a 

## 800°F 1,000°F
a 

### Contains some residual material 

## For our FCC feed sulfur regression, we used data obtained various crude oil assays that we obtained from Jacobs Engineering for work that Jacobs conducted for us. We used data from five specific crude ty pes, including West Texas intermediate , Bonny LightSaudi Heavy, Alaskan North Slope , and Mayan , and three blended crude assays. The equation for this regression, along with the estimated FCC feed sulfur contents for various crude oils are shown in Equation 5

- 3 and Table 5

- 23 below.

**Equation 5**  **- 3**  **FCC Feed Sulfur Content Based on Crude Sulfur Content** FCC Feed Sulfur Weight Percent = (Crude Sulfur Weight Percent) 0.8 

## * 1.1858 + 0.0409

**Table 5**  **- 23**  **FCC Feed Sulfur For Various Crude Sulfur Levels**  Crude Sulfur Level (Weight %) FCC Feed Sulfur Level (Weight %)

0.11% 0.24% 0.28% 0.47% 0.85% 1.08% 1.3% 1.50% 1.4% 1.59% 1.6% 1.77% 2.8% 2.74% 3.04% 2.93% 5.1.3.6 Impact of FCC Feed Pretreaters on FCC Feed Sulfur Levels With FC C feed sulfur estimated , the next step in our anal ys is was to consider the impact of pretreaters on the FCC feed sulfur levels for refineries that have these units. There are several factors that must be considered to determine the impact of the pretreaters on the FCC sulfur level, including the pressure at which the unit operates, the severity at which it is run, and whether or not the FCC naphtha will be postreated. To inform our understanding of how FCC pretreaters operate , we obtained guidance from technology

and catal ys t providers. From these discussions we learned that the capability for FCC pretreaters to remove sulfur from the gas oil feed varies significantly depending on the

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## 5

- 29 pressure at which the unit operates. FCC pretreaters can generally be subdivided into high pressure units (1400 psi and above), medium pressure units (900 to 1 , 400 psi), and low pressure units (below 900 psi). High pressure FCC pretreaters are capable of removing about 90 percent of the sulfur contained in the gas oil feed stock to the FCC unit, while low and medium pressure units are capable of removing 65 to 80 percent of the feed sulfur. Information we received from the vendors also indicated that refiners with both a pretreater and a postreater are producing FCC naphtha that ranges from 200 to 450 ppm before being processed by the postreater . Having a postreater allows these refineries to not have to operate their pretreaters at a high severity as the sulfur will further be reduced to levels necessary to meet the applic able standards in the post

treating units. Refiners with only a pretreater are making lower sulfur FCC naphtha in the 75 to 100 ppm range , according to vendor estimates

. With this information we used our refinery

-by

- refinery model to estimate the pretreater desulfurization rates required to get FCC naphtha sulfur levels within the ranges specified. We estimated that FCC units with a pretreater and a naphtha postreater are operating their pretreaters at a severity

which results in a 76 percent desulfurization of the FCC feed stream. This number represents the national average. While the actual severity at which the pretreating units are run varies on a refinery

-by

- refinery basis this average was used in our modeling for all refineries with both pretreating and postreating units due to a lack of refinery

- specific information . For FCC units with a feed pretreater but no postreater we calculated the FCC naphtha sulfur level required b y refiner to make a refinery gate gasoline that meets the Tier 2 standard. To do this calculation we used the gasoline yields from our refinery

-by

- refinery model along with the gasoline blendstock sulfur levels discussed above and shown in Table 5

- 18 . These calculations showed that refiners with FCC feed pretreating units , but no postreaters , need to produce FCC naphtha that averages about 85 ppm on a national level. This sulfur level corresponded to these refiners operating their pretreaters at a severity that results in a reduction of sulfur in the FCC f eed stream of approximately 91

- 92 percent . This number is close to the estimate we received from the vendors for this category of refineries and therefore was used in our refinery

-by

refinery model to determine the FCC feed sulfur level for refiners with pretreaters. After we have calculated the sulfur level of the FCC feed we must then take into consideration the impact the FCC unit itself has on the sulfur level of the FCC naphtha. We reviewed several literature sources 7 , 8 

## and found that the FCC naphtha sulfur level can be accuratel y determined b y dividing the FCC feed sulfur level b y 20 for refineries with an FCC feed pretreating unit. For refineries without an FCC feed pretreater , the FCC naphtha sulfur levels can be calculated by dividing the desulfurized FCC feed sulfur level by 10. In these cases the effect of the FCC unit itself on the sulfur level of the FCC naphtha is lower, as the FCC feed has already been through a desulfurization process. These factors, when combined with the sulfur levels o f the FCC streams as discussed above, allow us to calculate the sulfur level of the FCC naphtha before any post
- treating operations on a refinery

-by

- refinery basis. The results of this analysis are summarized in Tab le 5

- 24 below.

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## 5

- 30 **Tab le**  **5 -**  **24 FCC Naphtha Sulfur Levels for Various Refinery Configurations**  PADD 1 PADD 2 PADD 3 PADD 4/5 No Pretreater or Postreater N

. A

. a



## - <3 b 

## 606 784 Pretreater Onl y N

. A

. a 

## 73 74 82 Postreater Onl y 1348 1157 705 1036 Pretreater and Postreater 49 <3 b 

## 278 230
a 

### N.A.

– not applicable , no units of this type in the PADD b 

### Since there are less than three refiners in this PADD with the described configuration , the data was removed to protect potential CBI concerns . 

## This information, along with the information described in previous sections (e.g., gasoline blendstock volumes and sulfur levels, desulfurization equipment currentl y in place at refineri es, and crude oil sulfur levels) allows us to conduct the best analysis for the baseline case for our refinery

- by

-refinery model. This baseline case reflects what we believe the current operating conditions are at each refinery, including any modifications they have made to meet the Tier 2 sulfur standards. The next step of our analysis was to project what further changes, either to operations, adding new equipment or revamping existing units, each refiner would have to make to meet the proposed Tier 3 standards. After these changes are estimated, we can then estimate the cost associated with each of these changes, and ultimately the cost of the program. 5.1.4 Cost Inputs for the Sulfur Control Technologies After we determined the sulfur levels of the gasoline blendstocks for each refinery and the sulfur levels that these blend stocks would have to achieve to meet the proposed Tier 3 sulfur standards , the next step in our refinery

-by

- refinery analysis was to project the changes to refinery units and operations each refinery would have to make in order to comply with the proposed Tier 3 sulfur standard

. The first step refiners would take for further gasoline sulfur control would be to desulfurize the light straight run , natural gas liquids , and butane blendstocks. The costs to reduce the sulfur content of these streams is relatively low and would therefore be the most cost effective way

to further reduce the sulfur content of the finished gasoline. We also projected in our anal ys is for RFS2 that 50 percent of all gasoline produced b y refiners in 2017 would contain 15 percent ethanol. In 2030 we projected in our analysis for RFS 2 that almost all gasoline contains 15 percent ethanol. G 

## Because ethanol tends to be a relativel y low sulfur blendstock (assumed to be 5 ppm for our refinery

-by

- refinery model) increasing the amount of ethanol in the gasoline pool lowers the overall sulfur content of the gasoline. Reducing the sulfur content of the L SR , NGL , and butane stream s and increasing the ethanol content, however, would be insufficient to allow refiners to comply with the proposed T ier 3 standards. Refineries with an FCC unit would still have to reduce the sulfur content of their FCC naphtha blendstock in order to meet the Tier 3 standards.

G 

### In our Tier 3 cost analysis, we inadvertently only accounted for the ethanol volumes that are contained in the 2009 RFG database, not those mandated by RFS 2. For our final rulemaking cost analyiss, we will adjust our model to account for higher ethanol use in the future, which will slightly reduce our Tier 3 cost estimates, due to the dilution effects of ethanol.

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## 5

- 31 For each refinery

we considered two cases. In the first case each refinery had to meet the proposed Tier 3 gasoline sulfur standard of 10 ppm. In order to meet this standard , as discussed in 0 , we determined that they would have to reduce the sulfur level of their FCC naphtha stream to 25 ppm. We also considered a case where each refinery would reduce the sulfur level of their gasoline to 5 ppm. We assumed that to meet a 5

- ppm sulfur standard , refiners would desulfurize the butane blendstock to 10ppm in addition to further lowering sulfur in the FCC naphtha to 10 ppm. This information was used to help us determine which refineries might reduce the sulfur level of their gasoline below our proposed 10

-ppm standard to earn credits for our ABT scenarios discussed in Sections 5.2.1.2 and 5.2.1.3

. Our refinery

-by

- refinery

model assumed that reducing the sulfur content of the FCC naphtha to 25 ppm and 10 ppm for the two cases discussed above would require that each refinery that produces FCC naphtha have an FCC naphtha postreat er. In our final rule we plan to investigate the ability

of refineries with high pressure pretreaters to meet the required standards without the addition of postreaters. For companies that already have an FCC naphtha postreater we assumed that all that would be necessary to meet the proposed sulfur standards was to revamp their existing FCC postreating units. We received cost information from several vendors for revamping FCC postreating units and assumed a revamp cost for each refinery in line with the cost projections quoted by the vendor of the technology already in place in their refinery

. We assumed that refineries with FCC units that currently do not have an FCC postreater would have no choice other than to add a new gra ss roots FCC postreating unit . We ultimately only received cost information from one vendor for the cost of adding a new grass roots FCC postreating unit that fit the sulfur reduction requirements of the proposed Tier 3 program

. W e therefore assumed the cost for each refinery that would need to add a new FCC post

- treating unit would be in line with this estimate. More details on the costs used in our refinery

-by

- refinery model for the desulfurization of L SR, NGL, and butanes as well as the new FCC post

- treating units and revamps can be found in the following sections.

5.1.4.1 FCC Naphtha Desulfurization Costs T o estimate the cost for revamp ing existing FCC postreating units or for adding new postreating capacity, we contacted several technology vendors for cost estimates and reviewed literature, including cost information provided for the Tier 2 rulemaking . Because no two refineries are exactly

the same , the cost for new FCC postreater units or revamps to existing units will vary significantly

from refinery

to refinery . Some of the factors that have the most significant impact on the cost of FCC postreaters are the technology that the refiner used to comply with Tier 2, the volume of FCC naphtha, the sulfur content of the FCC unit feed and the level of desulfurization in the existing postre ater , and the location of the refinery . Based on feedback from vendors we considered three categories of FCC postreaters based on whether the FCC naphtha (the feed for the existing Tier 2 postreater) contained low (0

– 400 ppm) medium (400

– 1,200 ppm) or high (>1,200 ppm) levels of sulfur. Specific cost factors applicable to estimating unit revamps or grass units were also taken into account as described below . The following sections discuss in greater detail how the cost estimates we received from the vendors were used in our refinery

-by

- refinery anal ys is.

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## 5

- 32 5.1.4.1.1 Cost to Revamp Existing FCC Naphtha Postreaters We obtained information from several technology providers for the revamp costs of existing FCC postreaters. One of the estimates submitted was deemed not credible as inadequate information was provided and the capital and operating costs were extraordinarily high relative to the rest of the cost information we received. We believe it is likely that this cost estimate represented not only

a grass roots FCC postreater, but also significant refinery investment in other refinery

processes such as FCC feed pretreating, coker unit expansion etc. As these costs did not seem to be a reasonable representation of the revamp costs for FCC post treating, this estimate was not considered in our FCC postreater cost anal ys is. Some of the submitted information only

had cost information for our medium sulfur (400

– 1,200 ppm) FCC feed case. Another technology

provider did not provide cost estimates for producing an FC C naphtha with a sulfur level of 25 ppm, corresponding to a finished gasoline with 10 ppm sulfur, therefore, we needed to interpolate their cost information

. Because the cost information provided b y the technology

providers was labeled CBI , this cost information cannot be listed individually, however we aggreg ated the cost information we received for FCC postreater revamps to meet 10 ppm and 5 ppm sulfur levels in gasoline . The aggregated information is summarized in Table 5

- 26 and Table 5

- 27

. One of the vendors we contacted for a cost estimate for FCC naphtha desulfurization technology

provided information for several potential FCC postreater revamp cases. The first case was a no capital costs case where refiners made no equipment modifications, but rather solely made operational changes using their existing equipment installed for Tier 2 . The second case we requested was one where refiners would incur only minor capital costs and was intended to be us ed for anal yz ing program options with moderate octane costs. The third case we requested was one where refiners were willing to incur greater capital costs in order to minimize operating costs and octane loss. The majority of the vendors onl y supplied co st estimates for the third case, which included adding an additional catalyst reactor bed to the existing FCC postreater unit. This ensures that refiners will be able to run their existing FCC postreater at 4 to 5 year catal ys t cycle lengths, which is a critical feature for FCC unit operations. The costs for the FCC postreater revamps submitted by one of the vendors, however showed that for low (0

– 400 ppm) and medium (400

– 1,200 ppm) sulfur FCC naphtha sulfur levels, second case, with low capital costs , resulted in the lowest cents per gallon costs for meeting the proposed 10

- ppm Tier 3 standards. According to this vendor these cases also had a 4 to 5 year catal ys t cycle length, equivalent to the higher capital cost cases even though a second stage reactor was not required. We therefore assumed that refineries using this vendor’s technology

would choose the minor capital cost pathway for meeting the 10

-ppm Tier 3 standard when they

had low or medium sulfur levels in their FCC feed. The high capital cos t cases for producing gasoline to meet a 5 ppm sulfur standard from low and medium sulfur FCC feeds were found to have the lowest cost on a cents per gallon basis and were therefore selected by our model for these cases. One vendor onl y submitted informati on for postreater revamp cost estimates for FCC naphtha in the 400

– 1,200 ppm sulfur category that produced a 5

-ppm sulfur gasoline. In our refinery

- by

-refinery

model, however, we had multiple refineries with FCC feed sulfur levels in the 0

– 400 and >1, 200 ppm categories that use this vendor’s postreating technology . In order to

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## 5

- 33 apply this vendor’s cost estimate to cases of low (0

– 400 ppm) and high (>1,200 ppm) sulfur feed categories we adjusted this vendors 400

– 1,200 ppm postreater revamp cost base d on the cost differentials between the three FCC naphtha sulfur levels in the other vendors’ revamp estimates. We similarly

derived a postreater revamp cost estimate to produce a 10 ppm gasoline for this vendor using cost differentials between the 10 and 5 ppm cases from other vendors. For refineries currentl y employing technology by other vendors for which we had no specific cost information, we used an average of all of the vendors’ estimates to represent FCC postreater revamp costs for refiners using this particular technology in our refinery

- by

-refiner model. After we had determined cost estimates for the FCC postreater revamps based on information from the vendors the next step was to scale these costs based on the size of the FCC postreating unit present in each refinery . The vendor estimates submitted for revamp costs were based on various FCC postreater design volumes ranging from 10,000 BPSD to 45,000 BPSD depending on the base unit size used by the vendor. To determine how to apply these vendor costs to each refinery, we first calculated each refinery ’s maximum FCC naphtha production. The maximum production was derived b y assuming each refiner runs its FCC unit at its maximum nameplate throughput capacity (barrels per stream day) with the FCC naphtha yi eld rates discussed in Section 5.1.3.1.2 . We then increased the size of the FCC postreater b y 7.5 percent above each refinery ’s maximum FCC gasoline production rate as an over design factor to account for excess capacity that refiners generally design into their unit for processing additional flows of FCC naphtha (i.e, rerunning high sulfur FCC naphtha batches either from that refinery or from neighboring refineries) . After sizing the FCC postreater that would be required for each refinery we then scaled the costs given by the vendors using the six

- tenths rule as shown below. This is a “rule of thumb” cost estimating tool commonly used for cost estimating b y the refining and petrochemical industries for estimating the cost of a process unit based on a similar unit of differing size. Cost to Revamp an FCC Unit= A * (B/C) 0.6



## Where: A = Cost Estimate Received from the Vendor B = Size of the FCC Unit in the Refinery C = Size of the FCC Unit in the Vendor’s Estimate **Equat ion**  **5 -**  **4 Six** **- Tenths Rule for Estimating Capital Cost**  We also adjusted the costs submitted by the technology

providers based on the location of each refinery . We assumed that each vendor’s estimate was based on revamping an FCC postreater in PADD 3 (Gulf Coast) , which is the lowest cost region for installing new capital in refineries

. The cost for refineries that are not located in PADD 3 were adjusted upwards based on a ratio of the cost of refinery capital projects in the PADD in which they are located relative to PADD 3. An additional factor was applied to account for the “offsite” costs that are incurred when installing new capital in refineries. When vendors provide a cost estimate for their technology, this estimated cost is called the inside battery limits (I SBL) cost and it is solely for the immediate unit of interest. However, refiners may need to install peripheral capital to support the new unit, such as electrical switchgear, a control room, storage for feed, intermediate or unit products, and longer than anticipated pipeline runs

– these costs are usually considered Outside battery

limit (OSBL) costs, or offsite costs

. Insome cases, OSBL costs may include

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## 5

- 34 hydrogen and sulfur plant costs, although, for our anal ys is, we separatel y estimated the cost for providing additional hydrogen and for processing the removed sulfur and included this cost in our cost anal ys is. We estimate that the grassroots offsiste cost factors for very modest levels of de sulfurization inherent in this analysis are in the 1.2 to 1.3 range, and those for these very simple revamps are in the 1.1 to 1. 1 5 range (the ISBLcosts are multiplied by these factors to derive a total cost)

. These cost factors , as well as the utility p rices that we used in our refinery

by

- refinery

cost model , are shown in Table 5

- 25 below:

**Table 5**  **- 25**  **Cost Factors for Various PADDs** PADD 1 PADD 2 PADD 3 PADD 4 PADD 5 a 

## Capital Cost Factor 1.5 1.3 1 .0 1.4 1.2 Natural Gas ($/MMBTU) 7.88 7.86 5.64 7.06 7.44 Electricity

(¢/kW

-hr) 7.98 5.47 5.78 4.69 8.36 Steam ($/1 , 000 lb) 12.9 12.6 9.20 11.6 11.9 Offsite Capital Cost Factor

– New Units 1.26 1.26 1.20 1.30 1.30 Offsite Capital Cost Factor

– Unit Revamps 1.13 1.13 1.10 1.15 1.15

a 

### Excluding California 

## The volume

-weighted cost estimates for revamping FCC postreaters across the entire refining industry

as calculated by

our refinery

-by

- refinery

model are shown in Table 5

- 26 and Table 5

- 27 below. These costs are aggregate d cost estimates for the FCC revamp costs used in our refinery

-by

- refinery

model. In our model, we paired vendor cost data with refineries that are already using that particular vendor’s technology for their FCC postreating units. We further tailored the information provided b y the vendors to match the specific refinery configuration to the extent possible. The information that we received from the vendors and the individual refinery capital costs, however, cannot be shown due to CBI concerns. **Table 5**  **- 26**  **Revamp Cost for a 30,000 BPSD FCC Postreater for 10 -** **ppm Standard**  FCC Feed Sulfur Level a 

## 0

– 400 ppm 400

– 1,200 ppm >1,2 00 ppm Volume Weighted Averageb 

## Capital Cost ($/B I SBL) 235 382 505 265 Hydrogen (scf/bbl) 36.8 25.9 25.9 31.3 Fuel Gas (kBTU/bbl) 15.5 15.4 8.51 14.4 Electricity

(kWh/bbl) 0.14 0.27 0.52 0.223 Octane Loss (R+M)/2 0.56 0.46 0.42 0.492 Olefin Decreas e (vol%) 2.67 2.14 1.97 2.39 Catalyst Cost ($/B) 0.01 0.01 0.01 0.010 Steam (lb/bbl) 0.61 30.88 0.61 13.44
a 

### $/B = dollars per barrel, scf/bbl = standard cubic feet per barrel; kBTU/bbl = thousand BTU per barrel; kWh/bbl = kilowatt

- hour s per barrel ; (R+M)/2 = (research octane + motor octane)/2; vol% = volume percent; $/B = dollars per barrel; lb/bbl = pounds of steam per barrel of feed. b 

### Of the refineries that are expected to revamp their FCC naphtha hydrotreater for the no ABT case, 36 have FCC naphtha sulfur levels in the 0

– 400 ppm range, 20 have FCC naphtha sulfur levels in the 400

– 1200 ppm range and 13 have FCC naphtha sulfur levels greater than 1200 ppm.

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## 5

- 35 **Table 5**  **- 27**  **Revamp Cost for a 30,000 BPS D FCC Postreater for 5 ppm Standard**  **a** 

## FCC Feed Sulfur Level 0

– 400 ppm 400

– 1,200 ppm >1,200 ppm Volume Weighted Average Capital Cost ($/B I SBL) 400 578 600 444 Hydrogen (scf/bbl) 36.2 52.6 56.3 38 Fuel Gas (KBTU/bbl) 22.7 14.6 13.2 17.2 Electricity

(kWh/bbl) 0.30 0.52 0.52 0.42? Octane Loss (R+M)/2 0.60 0.77 0.90 0.62 Olefin Decrease 2.81 3.38 3.96 2.37 Catalyst Cost ($/B) 0.00 0.01 0.00 0.004 Steam (lb/bbl) 23.61 30.88 0.61 26.9
a 

### Assumes every refinery is complying with a 5 ppm gasoline sulfur standard 

## We also found that there were 11 refineries that had an existing FCC postreaters that were not sized large enough to process their maximum FCC naphtha production volume. For these refineries we assigned additional capital costs to debottleneck the existing first stage reactor in order to increase the postreater capacity so that it could accommodate maximum FCC naphtha production. For each refinery with an existing unit that could not process more than 70 percent of our estimate of a refiner’s max imum FCC naphtha production we added capital costs to revamp and expand the first stage to increase its capacity to allow the postreater to process 100 percent of its maximum FCC naphtha rate. For the capital costs for this debottlenecking we used 35 perc ent of the cost of a new grass roots unit (discussed below) for the volume of the expansion. We once again used the six

- tenths rule to adjust the capital cost for the volume expansion needed versus the cost for the 30,000 BPSD grass roots treater used for technology vendor estimates.

5.1.4.1.2 Cost for Grassroots FCC Postreaters While all refineries that already have FCC postreaters should be able to meet the proposed Tier 3 standards by revamping their existing postreaters, refineries that do not currentl y have an FCC postreater would have to add a grass roots FCC postreater. To determine the cost of building grass roots FCC postreating units at a refinery we similarl y requested cost estimates from vendors. Onl y one of the vendors that supplied FCC postreating equipment submitted information on the cost of a grass roots FCC postreating unit for desulfurizing FCC naphtha with a feed sulfur content of 100 ppm. Based on the calculation methodology shown in Equation 5

- 2 , we estimate that refineri es that require a grass roots postreater will already have an FCC feed sulfur level that averages between 85 and 100 ppm as these refineries already have FCC feed pretreaters. The other grassroots vendor estimate we received , as well as those we received for Tier 2, represented a grass roots postreater with an FCC feed sulfur content of about 800 ppm. The s e estimate s w ere deemed to be not representative of the costs to refineries that would be installing grass roots postreating units as the capital, hydro gen, and other operating costs would be much higher for an FCC feed sulfur of 800 ppm vs. 100 ppm. We did not consider this other vendor’s cost estimate for a grass roots postreater and therefore rel ies on a single vendor’s cost estimate for grass roots F CC postreating units for the Tier 3 program. In our FRM analys is we attempt to incorporate additional information from other vendors and literature sources. This one

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## 5

- 36 vendor cost estimate seemed reasonable relative to the other cost data that we have for higher levels of desulfurization. The vendor estimate submitted for a grass roots postreater was based on a postreater with a capacity of 30,000 BPSD capable of producing an FCC naphtha with a sulfur level of 10 ppm, corresponding to a gasoline sulfur leve l of 5 ppm. To scale the cost submitted by the technology vendor to be applicable to a specific refinery, we used a similar methodology to that which was used for postreater revamps. We first determined the appropriate size for each unit based on each re finers maximum FCC naphtha production rate, adding 7.5 percent above each refinery ’s maximum FCC gasoline production rate as an over design factor. We then used the six

- tenths rule (Equation 5

- 4 ) to scale the cost reported by the vendor up or down as appropriate based on the relative volume of the grass roots unit required by the refinery

and the size on which the vendor’s cost estimate was based. We once again assumed that the capital cost from the technology

vendor was representative of a refinery in PADD 3 and adjusted the cost based on the cost of refinery

capital projects in the PADD in which they are located relative to PADD 3. Finally, we used a new unit offsite adjustment factor as listed in Table 5

- 25 to determine the final cost of a grass roots FCC postreater for each refinery . The costs to produce an FCC naphtha with a sulfur level of 25 ppm (corresponding to a 10

-ppm gasoline) were estimated based on the grass roots postreater unit that makes FCC naphtha for the 5

-ppm standard. These costs are summarized in Table 5

- 28 and Table 5

- 29 below. **Table 5**  **- 28**  **Cost for a 30,000 BPSD Grass Roots FCC Postre ater for 10**  **- ppm Standard** 

FCC Feed Sulfur Level 100 ppm Capital Cost ($/B I SBL) 1500 Hydrogen (scf/bbl) 62.1 Fuel Gas (KBTU/bbl) 4.95 Electricity

(kWh/bbl) 1.06 Octane Loss (R+M)/2 0.55 Olefin Decrease 2.65 Catalyst Cost ($/B) 0.04 Steam (lb/bbl) 20 .0

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## 5

- 37 **Table 5**  **- 29**  **Cost for a 30,000 BPSD Grass Roots FCC Postreater for 5 -**  **ppm Standard**

FCC Feed Sulfur Level 100 ppm Capital Cost ($/B I SBL) 1500 Hydrogen (scf/bbl) 133 Fuel Gas (kBTU/bbl) 9 Electricity

(kWh/bbl) 1.06 Octane Loss (R+M)/2 1.00 Olefin Decrease 5.15 Catalyst Cost ($/B) 0.04 Steam (lb/bbl) 20.0 5.1.4.2 Li ght Straight Run and Natural Gas Liquids Desulfurization Costs Another action refiners may need to take to reduce the sulfur content of their gasol ine is to desulfurize their light straight run naphtha (LSR) and natural gas liquids (NGL) blendstocks. While these blendstocks have lower sulfur contents than the FCC naphtha , they may be cheaper to desulfurize for refineries that are not already treating these streams . Many refineries can desulfurize some or all of these blendstocks using existing excess capacity in their naphtha hydrotreaters or FCC naphtha postreaters. Further, as opposed to hydrotreating FCC naphtha which contains olefins , the L SR and NGL blendstocks contain no olefins and therefore, hydrotreating them does not result in octane loss and has a lower hydrogen consumption

. The combination of the potential for using excess capacity in existing units and low operating costs result in the relativel y low desulfurization costs for the L SR and NGL blendstocks. From our discussions with refiners, several refineries indicated that they would install new standalone hydrotreaters for processing LSR and NGL blendstocks, though it is unclear which other refineries will have to add equipment to desulfurize L SR and NGL

. For our Tier 3 cost estimates, however, we have conservativel y used our refinery

-by

- refinery model to estimate the costs for other refiners to hydrotreat all refiner volumes of L SR and NGL by install ing additional hydrotreating equipment

. T o determine the cost to desulfurize the L SR and NGL blendstocks we first had to determine the volume of blendstock that requires desulfurization. Our determination of the quantity

of L SR and NGL u sed as gasoline blendstock at each refinery is discussed in Section 5.1.3.1.2 . From this total we then subtracted the volume of LSR processed in the isomerization unit. Because the isomerization units require a low sulfur feedsto ck we assume all the feed to this unit is treated b y the naphtha hydrotreater. The next step in our assessment of the desulfurization costs of the L SR and NGL blendstocks was to estimate the extent to which these blendstocks are already being treated at re fineries to meet the existing Tier 2 sulfur standards. Based on our discussion with refining consultants, vendors and refiners, it appears that in response to the Tier 2 standards refiners have altered their operations to use excess capacity in their FCC naphtha postreaters and naphtha hydrotreaters to reduce the sulfur content of LSR and NGL blendstocks. Since information on the extent to which these streams are currentl y being hydrotreated is not publicly available we estimated these volumes using the c apacities of the FCC postreaters and reformer feed hydrotreaters under normal refiner crude throughputs and yields from the refinery

-by

- refinery model.

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## 5

- 38 We evaluated each refinery ’s capacity to hydrotreat L SR and NGL using existing equipment by

first determining the volume that can be processed in their naphtha hydrotreaters. We assumed that every

refinery ’s production volume of straight run and coker naphtha s , as determined in Section 5.1.3.1 , are processed in the refinery ’s reform er feed hydrotreater and that any capacity up to 85 percent of the unit’s maximum capacity can be used to treat L SR or NGL. If a refinery

had insufficient excess capacity in their naphtha hydrotreater to treat all of the LSR and NGL volumes we next determined if there was excess capacity in that refinery’s FCC postreater. We allowed LSR and NGL to be processed using excess FCC postreating capacity in refineries where the capacity of the FCC postreater exceeds 120 percent of that required to process a refinery ’s maximum FCC naphtha yield as determined b y the refinery

-by

- refinery model. Only

several refiners had excess FCC postreating capacity available for the treating of LSR or NGL feedstocks, as the capacity of most FCC postreaters was less than 120 perc ent of the maximum FCC naphtha production rate. We assumed that refiners are currentl y using any excess hydrotreating capacity in their naphtha hydrotreating and FCC postreating units to desulfurize L SR and NGL in response to the Tier 2 sulfur standards. T o meet the proposed Tier 3 sulfur standard 10 ppm and the 5 ppm level we considered for the ABT cases , we assumed that refiners would desulfurize all of the LSR and NGL blendstocks. We assumed that L SR and NGL purchased b y refiners would be hydrotreated in addition to that processed by the isomerization unit and that blended directly into the gasoline. To determine which of the refineries in our refinery

- by

- refinery model would need to add hydrotreating capacity, we evaluated each refinery

based on their maximum crude processing rate and yields. We used our model to increase each refinery ’s yi eld of coker naphtha, reformer naphtha, isomerate, L SR and NGL to correspond to a crude utilization rate of 100 percent . We then used these maximum production volumes to evaluate whether or not each refinery could process all of the L SR and NGL using excess naphtha hydrotreater and FCC postreating capacity. If a refinery did not have sufficient excess hydrotreating capacity for all of the L SR and NGL in these unit s we assumed the refinery

would have to either revamp their existing equipment or add new hydrotreating capacity . If the additional capacity needed at any given refinery exceeded the existing naphtha hydrotreater capacity b y less than 30 percent we assume d the necessary capacity could be added by revamping the existing unit. (For our FRM, we will also evaluate if refiners could also use the caustic M erox extraction process to lower the sulfur level in L SR and NGL blendstocks , and if so, are they

already do ing that today). If, however, the additional capacity required exceeded the existing reformer feed hydrotreater capacity b y m ore than 30 percent we assumed the refinery would install a new stand

- alone hydrotreater to desulfurize the excess L SR and NGL. Ba sed on available capacity in our refinery

- by

-refinery model and 2009 crude throughput data , we estimated that refiners are already hydrotreating 66 percent of the L SR and NGL that are directl y blended into gasoline (excluding LSR processed in the isomerization units). The results of this assessment are shown in Table 5

- 30 below. **Table 5**  **- 30**  **Refineries Adding Hydrotreating Capacity for LSR and NGL**

New Hydrotreater (No FCC Unit) New Hydrotreater

(with FCC Unit) Revamped

Hydrotreater (No FCC Unit) Revamped

Hydrotreater (with FCC Unit) Number of Refineries 4 11 1 7

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## 5

- 39 We conservativel y evaluated the capital cost required for hydrotreater revamps and new units by assuming that refiners will siz e their hydrotreater equipment needs to treat all production volumes of L SR and NGL based on each refinery’ s maximum crude run rate. The operating costs used in our refinery

-by

- refinery model, however, are based on LSR and NGL blendstock rates from the mo dels yields at the 2009 operational crude throughputs as discussed in Section 5.1.3.1 . Sizing the equipment this way allows each refiner to have excess hydrotreater capacity utilization, which is beneficial in the event of process unit shutdowns and to reprocess blendstocks from abnormal operations. Our estimate for the cost of adding a new hydrotreater at a refinery was obtained from Gary and Handework’s Petroleum Refining Technology and Economics , page 182

- 183, Curve C, Table 9.1 , 30,000 BSD unit . The capital cost for a grass roots hydrotreater listed by this source was for a hydrotreater with a capacity of 30,000 BPSD and was based on 1999 dollars. We multiplied this cost by

1.534 to determine the equivalent cost in 2010 dollar s based on the relative increase in the Nelson Refining Construction index from 1999 to 2010 (listed as 1497 and 2296 respectivel y). We used the six

- tenths rule to scale the capital cost listed in Petroleum Refining Technology

and Economics to those of di ffering capacities based on relative size of the desired unit. We assumed a hydrogen consumption of 40 SCF/Bbl for the processing of LSR and NGL blendstocks which we obtained from the Jacobs Refining LP modeling database for naphtha hydrotreating as this information was not presented in the literature source. For refineries that only

required a revamp of existing units we assumed a capital cost equivalent to 40 percent of the cost of a new hydrotreating unit of equal size. We assumed equivalent operating costs for new hydrotreating units and revamped units. The capital and operating costs for these hydrotreating units that were used in our model is shown in Table 5

- 3 1 below. **Table 5**  **- 3**  **1 Capital and Operating Costs for LSR and NGL Hydrotreaters**  New Hydrotreating Units Revamped Hydrotreating Units Capital ($/BBL IS BL) 1380 550 Hydrogen (SCF/BBL) 40 40 Fuel Gas (kBTU/BBL) 100 100 Electricity

(kWh/BBL) 2.0 2.0 Octane Loss (R+M)/2 0.0 0. 0 Change in Ol e fins (vol%) 0.0 0.0 Steam (lb/BBL) 6.0 6.0 Catalyst Cost ($/BBL) 0.03 0.03

5.1.4.3 Butane Desulfurization Costs After considering the desulfurization of L SR and NGL we then estimated the cost to each refinery for desulfurizing the butane that is blended into gasoline. For the baseline case without ABT where each refinery had to meet the 10

-ppm sulfur standard we did not assume any cost associated with butane desulfurization, as we assumed that any refiners likely to reduce the sulfur content of the butane stream already had the necessary equipment. To estimate the costs for each refinery

to produce a 5

-ppm gasoline for our ABT cases, however, we assumed refineries would reduce the sulfur content of any butane blended into gasoline using extractive desulfurization units (such as Merox or Merichem) which extract mercaptan sulfur (the bulk of

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## 5

- 40 sulfur species in butanes) from butane volumes that are added to each refiner’s gasoline pool. We accounted for butane treating cost in our refinery

-by

- refinery model by adding capital to install Merox treating units to each refinery . This is likely a conservative estimate based on our lack of information on which refineries may already have these units. We set up the model to size the Merox treater based on each refinery’ s maximum addition of butane volume to the gasoline pool, using the amount that is blended in the winter, as winter grade gasoline has the highest seasonal gasoline RVP limits and therefore allows for the highest levels of butane blending

. A s with some of the LS R and NGL desulfurization units, it is unclear if additional butane desulfurization units will be added to meet the Tier 3 standards. As a conservative estimate , though, we have included the cost of adding these units to our program c osts. To calculate the volume of butanes added to winter grade gasoline we us ed the refinery

by

- refinery

model estimate of the full year addition of butane to each refiners CG and RFG gasoline grades which was based on the EPA annual gasoline database. The winter addition of butane volumes w as assumed to be 66 percent of the total annual volume of butanes added to a refiner ’ s gasoline pool on a yearl y basis

. The capital cost we used was for a 10 ,000 BPSD Merox unit and was listed in 1995 dollars

. 9 

## We multiplied this cost by 1.64 to determine the equivalent cost in 2010 dollars based on the relative increase in the Nelson Refining Construction index from 1995 to 2010. We then multiplied the maximum winter daily butane volume by 1.08 to account for an ov er design factor to size the equipment . We next used the six

tenths rule to scale the capital cost listed in Petroleum Refining Technology and Economics to those of differing capacities based on relative size of the desired unit in BPSD divided by 10,000 (the size of the unit the cost is based on). Finall y, we applied offsite and PADD location factor adjustments as listed in Table 5

- 25 . For the operating cost we assumed that each unit had an annual fixed operating cost of 6.7 percent of the total installed capital cost. To this we added an operating cost of 0.03¢ per gallon based on an operating cost figure from literature listed in 1995 dollars and scaled to 2010 dollars using appropriate factors. Operating costs were presumed to represent all process energy and utility

costs, as well as costs associated with purchasing caustic. **Table 5**  **- 32**  **Merox Treating cost for Sulfur Removal from Butane** Size, BPSD Capital costs, $ MM Operating Costs, ¢ /gal 10,000 3.28 0.03 5.1.5 Overall Cost Methodology

5.1.5.1 Sulfur Costs without ABT Program While we are proposing an ABT program as described in Section V.E.1 of the preamble , we also evaluated a scenario with no averaging, banking, or trading between refineries. Under this scenario, every

individual re finery

would comply

with the 10

-ppm annual average sulfur standard, and none would lower their annual average sulfur below 10 ppm. This evaluation provided a reference point for determining the impacts of a n ABT program on compliance costs. In complying with the 10

-ppm sulfur standard, our refinery

- by

-refinery analysis concluded that some refineries would do so with revamps to existing equipment while others would need to install new grassroots equipment. Those refineries whose average sulfur levels are already at or below the 10

-ppm standard would not need to do anything. Because the most

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## 5

- 41 recentl y available data was for 2009 when some phase

- ins under Tier 2 were still effective, we made adjustments to en sure that refinery

- specific sulfur levels represented levels after all Tier 2 phase

- ins had expired. For instance, if any refinery exhibited an annual average sulfur level above the 80

-ppm cap based on 2009 data, we assumed that their current annual average sulfur level was 30 ppm. Further discussion of our refinery

-by

- refinery analysis can be found in Section 5.1.3

. To determine the impacts on cost of the 10

-ppm sulfur standard without ABT, we volume

-weighted the refinery

- specifi c ¢/gal costs calculated according to the refinery

-by

refinery modeling using 2009 gasoline production data for each refinery . Likewise, we determined nationwide capital costs by summing the individual revamp and/or grassroots equipment costs across all refineries. In these calculations, we assumed that all earl y credit generation and phase

- ins had expired, consistent with our approach to the ABT analysis. The results of our analysis of costs under a scenario without ABT are provided in Section 5.2.1.1 below. 5.1.5.2 Sulfur Costs with ABT Program As described in Section V.E.1 of the preamble, we are proposing an ABT program that is designed to ease the overall burden on the industry while still achieving the 10

-ppm annual average sulfur s tandard for the nation as a whole. Under the proposed ABT program, refineries that can reduce sulfur below 10 ppm at a relativel y low cost can generate credits which can then be sold to refineries for whom the cost of attaining the 10 ppm sulfur standard would be relativel y high. The net effect of this credit trading would be expected to reduce the overall cost of the program. To estimate the impact that the ABT program could have on nationwide average fuel costs, we began with the refinery

- by

-refinery co sts described in Section 5.2.1 .1 for sulfur reductions down to either 10 ppm or 5 ppm. We then determined the lowest cost option among three alternatives for each refinery : 1. The refinery

reduces its sulfur to 10 ppm. H 

## 2. The refinery

reduces its sul fur to 5 ppm and generates credits (in ppm

- gal) for the increment between 10 ppm and 5 ppm. 3. The refinery

does not lower sulfur, but instead obtains credits to comply with the 10

-ppm standard. A fourth category

applied to refineries whose average gasol ine sulfur levels are already below 10 ppm. All such refineries were assumed to generate credits for the increment between 10 ppm and their current sulfur level.

H 

### No refinery compliance margins were included in this analysis.

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## 5

- 42 To optimize the nationwide average costs under an ABT program, we determined the credit price at which the total number of credits generated was equal to the total number of credits consumed. To simplify the modeling of how an ABT program might operate, we focused on the circumstances that refineries would face in the longer term, specifically af ter 2020. This approach meant that the ABT program modeling did not consider the impact on gasoline sulfur levels of delayed compliance for small refiners and small volume refineries, nor did it consider the generation and use of any earl y sulfur credits. Moreover, our ABT modeling considered onl y gasoline sold for use outside of California, and only gasoline produced by

domestic refineries (not imports). Since the cost information available for this NPRM was limited to the costs of reducing sulfur to e ither 10 ppm or 5 ppm (under which FCC gasoline sulfur levels would be reduced to either 25 or 10 ppm , respectivel y), we were not able to estimate refinery

- specific costs of reducing sulfur to other levels. As a result, our ABT modeling could not account for scenarios in which a refinery

makes some capital investments to lower sulfur to some interim level, such as 20 ppm, and then obtains credits in order to demonstrate compliance with the 10

-ppm standard. Our ABT anal ys is also could not account for credit generation at sulfur levels other than 5 ppm. Our ABT anal ys is, then, most likely underestimates the cost savings that could occur due to ABT since the greatest efficiencies are achieved when every refinery has the option of using any combination of cap ital investments and credits generation or use. For the final rule, we may investigate methods for expanding our ABT anal ysis to examine these ty pes of scenarios. We evaluated two ABT scenarios designed to bound the likely outcomes. In the first scenario , we assumed perfect nationwide credit trading in which all credit generators make their credits available to any refinery that needs them, regardless of their ownership. As described in Section V.E.1 of the preamble, the proposed ABT program is designed such that it could operate in this way . However, such perfect nationwide trading may not be realistic. Under Tier 2 today, there is still a considerable amount of inter

- company trading occurring, but a significant fraction of Tier 2 sulfur credits are bought and sold within companies. I 

## Under Tier 3, it will be more difficult to generate credits, and also more difficult to make up for deficits. Consequently, we also investigated a second ABT scenario in which trading between companies does not occur and averaging would only

occur within companies that own more than one refinery . Under this second scenario, individual companies might decide to bank credits for their own use, declining to make credits that they

generate at one of their facilities available to other companies. They might do this, for instance, to address unplanned equipment downtime or other circumstances that could make future compliance more difficult. While we do anticipate some trading to occur between companies, we believe that this s econd, more limited scenario more closel y represents how our proposed ABT program might actuall y operate. As a result , the within

- company credit trading scenario is the primary scenario that we used to estimate overall costs for our proposed program. It represents a somewhat conservative scenario with respect to estimation of costs. The results of both scenarios are described in Sections 5.2.1.2 and 5.2.1.3 below.

I 

### Based on Tier 2 sulfur compliance data, of the 26 companies that purchased sulfur credits in 2010, eight bought credits only from their own company, and another five bought credits both from their own company and from other companies. The remainder bought credits only from other companies.

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## 5

- 43 Since an ABT program would allow some ref ineries to continue producing gasoline with an average sulfur level above 10 ppm, we also investigated whether any areas of the country might experience inordinately high sulfur levels as a result, and if so whether those higher sulfur levels might be prob lematic in terms of either vehicle performance or local air quality . While we were not able to model the distribution of all gasoline from the point of production to the point of consumption, we did compare average sulfur levels at each refinery's location to the location of nearb y ozone nonattainment areas (based on the designation status with respect to the 1997 ozone NAAQS). A discussion of our anal ys is of sulfur levels by refinery and location can be found in Section 5.2.1 below. **5.2 Estimated Tier 3 Sulf**  **ur Control Costs** 5.2.1 Sulfur Cost Results

5.2.1.1 C ost of the Sulfur Program without ABT Without ABT, all refineries would be required to meet the 10

-ppm annual average sulfur standard. We estimate that 13 refineries are already at or below 10 ppm, and thus their cost s of compliance would be zero. The remaining refineries would incur ¢/gal costs at various levels depending on their particular configurations and the steps they would need to take. While we estimate that the nationwide average cost of compliance would b e 0.97 ¢/gal under this scenario, two refineries would incur costs above 6 ¢/gal. The distribution of costs is shown in Figure 5

- 1 a s a function of the number of refineries.

0 5 10 15 20 25 30 35 40 45 50

0. 00 0. 50 1. 00 1. 50 2. 00 2. 50 3. 00 3. 50 4. 00 4. 50 5. 00 5. 50 6. 00 6. 50 7. 00 7. 50 

### N **u m**  **b e**  **r o**  **f r**  **e f**  **i n**  **e r**  **i e**  **s**

**ce nt**  **s/ gal**  **lo n**  Nationw id e av er age= 0 .97 c/gal



## Figure **5 -**  **1 Distribution of Compliance Costs**  **by Refinery for 10 ppm**  **w ithout ABT**  **Program**

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## 5

- 44 In order to enable evaluation of the costs of the program with ABT, we also needed to estimate the costs for each refiner to reach 5 ppm. The distribution of costs for this scenario is shown below.

0

5 10 15 20 25 30 35 40

0. 00 0. 50 1. 00 1. 50 2. 00 2. 50 3. 00 3. 50 4. 00 4. 50 5. 00 5. 50 6. 00 6. 50 7. 00 7. 50 

### N **u m**  **b e**  **r o**  **f r**  **e f**  **i n**  **e r**  **i e**  **s**

**cents/ga llo**  **n** Nationw id e av er age = 1 .38 c/gal



## Figure **5 -**  **2 Distribution of Compliance Costs by Refinery for 5 ppm w** **ithout ABT Program**

5.2.1.2 Cost o f Sulfur Control Program with ABT Under a scenario in which credit trading onl y occurs between refineries within the same company, we determined that about 23 percent of refineries would be involved in either generating or consuming credits. Table 5

- 33 summarizes our estimate of the amount of credit trading that would occur under this scenario. **Table 5**  **- 33**  **Impacts of ABT Program with Intra** **- Company**  **Credit Transfers** Number of refineries whose sulfur is already below 10 ppm, and which generate credits a 

## 3 Number of refineries which l ower their sulfur to 5 ppm and generate credits 15 Number of refineries that do not lower their sulfur but instead consume credits 8 Number of refineries that lower sulfur to 10 ppm and neither generate nor consume credits 85

a 

### Additional refineries als o have sulfur levels below 10 ppm, but do not generate credits under this scenario.

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## 5

- 45 The nationwide average cost of compliance with the 10

-ppm sulfur standard would be reduced from 0.97 ¢/gal without ABT to 0.89 ¢/gal under company- onl y trading. J 

## However, there would continue to be a significant variation in costs by refinery as illustrated in Figure 5

- 3

.

0 5 10 15 20 25 30 35 40 45 50

- 0. 5 0 0. 5 1 1. 5 2 2. 5 3 3. 5 4 4. 5 5 5. 5 6 6. 5**N u** **m b** **e r** **o f** **r e** **f i** **n e** **r i** **e s** 



### ce **nt s/ga**  **llon** Nationw ide av er age= 0 .89 c/gal



## Figure **5 -** **3 Distribution of Compliance Costs by Refinery**  **for 10 -** **ppm A** **verage Standar d** 

**with ABT Program and Intra** **- Company**  **Credit Tra**  **nsfers** Inthis figure, refineries with negative costs are those whose sulfur levels were already below 10 ppm and who would generate and sell credits. While there are several refineries with costs above 3 ¢/gal in this scenario, in practice we would expect such refineries to incur lower costs by pursuing some combination of lowering their gasoline sulfur to some level above 10 ppm and also purchasing credits to cover the remaining sulfur reductions needed to reach 10 ppm. The anal ys is we conducted f or this draft RIA was unable to capture such nuances, but we will be investigating them for the final rule. Figure 5

- 4 illustrates how the cumulative distribution of costs by volume would chan ge under this scenario. In general, the distribution would shift downward slightly in comparison to a scenario in which there was a 10 ppm average standard but no ABT program.

J 

### Approximately 55% of this desululfurization cost is com prised of the variable cost, and the majority of that is due to the cost of recovering the octane lost when the hydrotreater unit saturates the octane

-rich olefins contained in the FCC naphtha. Another 30% of the cost is due to the capital cost amorti zed over the volume of gasoline. Finally, about 15% of the cost is due to the fixed operating cost which includes the maintenance of the new equipment and taxes.

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## 5

- 46 0 1 2 3 4 5 6

0 20000 40000 60000 80000 100000 120000**C e** **n t** **s /** **g a** **l l** **o n** 



### Cumul **at ive**  **gas ol**  **in e**  **vol ume**  **( mill**  **gal lo**  **ns)** Di st ri bution wi th no ABT

Di st ri bution wi th company- onlyt ra di ng



## Figure **5 -**  **4 Distribution of Co**  **sts by Volume for 10**  **- ppm Average Standard**  **with ABT**

**Program and Intra** **- Company**  **Credit Tra**  **nsfers** Since we estimate that 85 out of 1 11 refineries would meet the 10

-ppm sulfur standard without the use of credits under the intra

- company trading scenario , only ab out 5 percent of gasoline would continue to have an annual average sulfur level above 10 ppm. These refineries tend to be smaller than average. The distribution of sulfur levels under this scenario is shown in Figure 5

- 5

.

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## 5

- 47 0 10 20 30 40 50 60 70 80 90 100

5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85**N u** **m b** **e r** **o f** **r e** **f i** **n e** **r i** **e s** 



### Sul **fur (ppm)**  

## Figure **5 -**  **5 Distribution of Sulfur Levels by Refinery with ABT Program and**  **Intra****** **Company Credit**  **Tra nsfers**  Of the 5 percent of gasoline volume that would have average sulfur levels above 10 ppm under this scenario, nearl y half would be below 20 ppm, and a majority would be below 30 ppm. Moreover, as noted above, we would expect refineries with the highest sulfur levels to pursue some combination of lowering their gasoline sulfur to some level above 10 ppm and also purchasing credits to cover the remaining sulfur reductions needed to attain the 10

-ppm standard. We also investigated whether the existence of refineries producing gasoline with average sulfur levels higher than 10 ppm after 2020 might contribute to local are as where the average sulfur level is higher than 10 ppm, and whether this might be problematic in terms of either vehicle performance/emissions or local air quality. To do this, we compared the location of refineries with sulfur levels higher than 10 ppm to the location of other refineries serving similar areas. We also compared the location of refineries to areas that have historically been in nonattainment for ozone. As shown above in Table 5

- 33 , we estimated that eight refineries would have annual average sulfur levels above 10 ppm under company

- onl y credit trading. Three of these refineries serve areas that are, at a minimum, several hundred miles away from historical ozone nonattainment areas. The remaining five refineries with average sulfur levels above 10 ppm supply areas that are also supplied by other refineries whose average sulfur levels would be 10 ppm or lower. As a result, gasoline with higher sulfur levels would likely be diluted by

gasoline with lower sulfur levels, and we would not expect any ozone non - attainment area to receive gasoline with an average sulfur level higher than 20 ppm.

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## 5

- 48 5.2.1.3 Cost of Sulfur Control Program with ABT and Nationwide Credit Transfers Although we believe that credit trading will occur primari ly between refineries within the same company, we also investigated a scenario in which credit tra nsfers would occur between all refineries regardless of location or company. For this scenario, we determined that more than 60 percent of refineries would b e involved in either generating or consuming credits. Table 5

- 34 summarizes our estimate of the amount of credit trading that would occur under this scenario.

**Table 5**  **- 34**  **Impacts of ABT P rogram with Nationwide**  **Credit Tra**  **nsfers** Number of refineries whose sulfur is already below 10 ppm, and which generate credits 12 Number of refineries which lower their sulfur to 5 ppm and generate credits 34 Number of refineries that do not lower their sulfur but instead consume credits 25 Number of refineries that lower sulfur to 10 ppm and neither generate nor consume credits 40 The nationwide average cost of compliance with the 10

-ppm sulfur standard would be reduced from 0.97 ¢/gal without any ABT program to 0.79 ¢/gal under nationwide trading. There would continue to be some variation in costs by re finery as illustrated in Figure 5

- 6 , though the distribution would not be as wide as under the intra

- company credit transfer scenario

.

0 5 10 15 20 25 30 35 40 45

- 0. 5 0. 0 0. 5 1. 0 1. 5 2. 0 2. 5 3. 0 3. 5 4. 0 4. 5 5. 0 5. 5 6. 0 6. 5**N u** **m b** **e r** **o f** **r e** **f i** **n e** **r i** **e s** 



### ce **nt s/** **gal lo**  **n** Nationw ide ave ra ge= 0 .79 c/gal



## Figure **5 -**  **6 Distribution of Refinery Compliance Costs with ABT Program and Nationwide**  **Credit Tra**  **nsfers**

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## 5

- 49 Figure 5

- 7 illustrates how the cumulative distribution of costs by volume would change under this scenario. In comparison to a scenario wherein credit trading occurs only between refineries within the same company, the downward shift in the distribution would be more pronounced.

0

1 2 3 4 5 6

0 20000 40000 60000 80000 100000 120000**C e** **n t** **s /** **g a** **l l** **o n** 



### Cumul **at iv** **e gas**  **olin e**  **vol ume**  **( mi**  **ll ga**  **llo ns**  **)** Di st ri bution wi th n o ABT

Di st ri bution wi th nationw ide tr ading



## Figure **5 -**  **7 Distribution of Compliance Costs by Volume with ABT Program and**  **Nationwide Credit**  **Tra nsfers**  Under a scenario in which credit transfers occur nationwide, we estimate that 25 out of 111 refineries, or about 23 percent , would not lower their sulfur l evels and would instead obtain credits. These refineries tend to be smaller than average, and represent about 17 percent of gasoline volume. The distribution of sulfur levels under this scenario is shown in Figure 5

- 8

.

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## 5

- 50 0 10 20 30 40 50 60 70 80 90 100

5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85**N u** **m b** **e r** **o f** **r e** **f i** **n e** **r i** **e s** 



### Sulfur **(ppm)** 

## Figure **5 -**  **8 Distribution of Sulfur Levels by Refinery with ABT Program and Nationwide**  **Credit Tra**  **nsfers** Of the 17 percent of gasoline volume that would have average sulfur levels above 10 ppm under this scenario, the vast majority would be below 30 ppm. As for the previous scenario under which credit transfers would occur onl y within companies, we investigated the localized impact of higher sulfur levels under a scenario in which credit transfers occur nationwide and thu s there are more refineries with average sulfur levels above 10 ppm. Under this scenario, most refineries with average sulfur levels higher than 10 ppm supply

areas that are also supplied by refineries with sulfur levels at 10 ppm or below. We expect the dilution of higher sulfur with lower sulfur in such areas to result in annual average sulfur levels no higher than about 20 ppm. Of those refineries projected to have average sulfur levels higher than 10 ppm under this scenario and which are the primary or only suppliers of gasoline to a particular area, none of the affected areas have historically been in nonattainment for ozone. **5.3 O**  **ther Cost Studies** Other other cost studies were recently conducted to estimate the cost of additional reduction in gasoline sulfur. We evaluated each of these studies and compare them to our own cost anal ys is. The International Council for Clean Transportation (ICCT) retained Mathpro in October 2011 to study

the cost of a 10 ppm average gasoline sulfur standard as well as a 1 psi reduction in RVP. 10 

## Since the lower RVP standard was modeled as a separate step from the low sulfur standard, we were able to isolate the gasoline sulfur reduction costs from the low RVP costs.

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## 5

- 51 ICCT’s estimated cost for a 10 ppm average gasoline sul fur standard is 0.8 cents per gallon which reflects the capital costs amortized assuming a before

- tax 7 percent rate of return on investment. This cost reflects an assumption that the capital cost for revamps of FCC postreaters is 30 percent of the capital costs for a grassroots FCC postreater . Mathpro also anal yz ed costs assuming that the capital cost for revamps of FCC postreaters are 50 percent of a grassroots FCC postreaters , which is 1.1 cents per gallon. ICCT’s cost estimate for compl ying with a 1 0 ppm average gasoline sulfur standard is very close to ours. In 2008 The Alliance retained Mathpro to use its LP refinery cost model to estimate the costs of what they

termed National Clean Gasoline (NCG) in PADDs 1, 2 and 3 (generall y speaking, this is the part of the U.S. east of the Rocky Mountains ). 11 

## Achieving NCG would entail reducing gaso line sulfur to 5 ppm under a 10

-ppm cap standard and the reduction of gasoline RVP to 7 psi. For the low

- RVP standard, a 1

-psi waiver was allowed for conventional ga soline, but not for current low

- RVP areas. The study also evaluated two sensitivity cases which increases the stringency of the distillation index (DI) from 1250 to 1200. The Alliance study also evaluated crude oil price as a second sensitivity case, evaluating crude oil prices at $51 /bbl and $125/bbl. The Alliance studied three different cases. The first case applied the 10

-ppm sulfur cap to RFG. The second case applied the 10

-ppm sulfur cap and the 7.0

-psi low

- RVP standard to RFG as well as 7.0

- and 7.8

-psi low

- RVP gasoline. The third case applies the 10

-ppm sulfur cap and 7.0

-psi RVP standard to all RFG and CG. Of these three cases, the first case is most relevant because appl ying the fuels changes to RFG solel y applies the 10

-ppm sulfur cap to RFG and does not involve any

changes in RVP. However, the 10

-ppm sulfur cap standard studied b y the Alliance is still 5 ppm more stringent than the 10

- ppm average standard that we are proposing. The Alliance cost estimate for Case 1 is 1.6 cents per g allon for RFG in PADDs 1, 2 and 3. This cost estimate is based on amortizing the capital costs on a 10 percent after

- tax return on investment (ROI). We adjusted the cost estimate to amortize the capital costs based on a before tax 7 percent ROI and adjus ted the costs to 2010 dollars which increases the costs to 1. 75 cents per gallon. The 1.75 ¢ /gal cost estimate is based on a crude oil price of $51/bbl. The Alli ance estimated the cost of a 10

-ppm sulfur cap standard on RFG assuming that crude oil is pri ced at $125/bbl. At the $125/bbl crude oil price, the Alliance study estimates that it costs 2.50 ¢/gal to re quire that RFG compl y with a 10

-ppm sulfur cap standard. Adjusting the Alliance costs to reflect a 7 percent before tax ROIand 2010 dollars increases the Alliance costs based on a $125/bbl crude oil price to 2.69 ¢/gal

. For our cost anal ys is we anal yz ed the cost of sulfur control assuming that crude oil is priced at $91.8/bbl. We can interpolate between the Alliance costs based on $51 and $125 per barrel crude oil prices, which results in a single cost which is 2.3 cents per gallon . We also estimated a cost for refiners lowering their gasoline sulfur to 5 ppm using the refinery

-by

refinery cost model and our cost is 1. 38 ¢/gal

. In response to the Alliance study, API retained Baker and O’Brien (BOB) in 2010 to study the cost of additional gasoline sulfur control and an increase in RVP using a refinery

-by

refinery cost approach with BOB’s Prism model. 12 

## The Prism model is largely a spreadsheet c ost model with blending optimization. The primary case anal yz ed b y the APIstudy is the cost

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## 5

- 52 of reducing gasoline sulfur to an average of 10 ppm and reducing gaso line RVP to 7.0 psi without a 1

-psi waiver for blending 10 percent ethanol. The study also analyzed thre e other sensitivity

cases: 1) a 5

- ppm average gasoline sulfur standard with 7 psi RVP limit on conventional gasoline without a 1

-psi waiver; 2) a 10

-ppm average g asoline sulfur standard and a 7.8

-psi RVP limit on conventional gasoline without a 1

-psi waiver; and 3) a 10

-ppm average gasoline sulfur standard with a 7.8

-psi RVP limit on all conventional gasoline with a 1

-psi waiver. In an addendum to its fuels study report released in 2011, APIcontracted with Baker and O’Brien to study a sensitivity case 4, which is a sulfur only case, using its PRI SM refinery model. From our understanding of the study, the study parameters seemed to be about the same as the original study, except that APIsolel y studied a 10 ppm average gasoline sulfur standard (not including any RVP control), the same sulfur standard that we are proposing. However, API also assumed that a 20 ppm cap standard would also be in place which would not allow the application of an averaging, banking and trading (ABT) program to optimize refinery investments and minimize overall costs. APImade a series of conclusions based on the study . Perhaps the most important difference with the original study is that API concluded that no t a single refinery would shut down as a result of the proposed 10 ppm gasoline sulfur control standard, even though API did not study the flexibilities of an ABT program and used excessively high capital costs for a grassroots FCC postreater (see below). Like the original study, API did not report average co sts, but reported the marginal costs for the cost study . Marginal costs reflect the cost of the program to the refinery

or refineries which would incur the highest costs, assuming that the highest cost refineries would set the price (or in this case, the price increase) of gasoline. The report concluded that marginal costs after the imposition of a 10 ppm gasoline sulfur program would increase the price of gasoline by 6 to 9 cents per gallon in most markets. APIdid not define how its statement “in most markets” would appl y to the US gasoline suppl y. API also did not provide any justification why

it assumed that the refineries that would experience the highest desulfurization cost under Tier 3 would also be the same refineries which sets the gasoline pri ce in the gasoline market today

. Although API did not provide an average gasoline desulfurization cost in its report, we could calculate an average cost based on the gasoline volume and total annual costs provided. The total cost reported in the report f or the 10 ppm average gasoline sulfur standard is $2390MM/y

r and the non - California gasoline volume is 7343 thousand barrels per day

. This results in an average per

- gallon desulfurization cost of $0.89/bbl or 2.12 c/gal. The difference between the averag e cost and marginal cost (price increase) that API is projecting is profit. API is projecting that the oil industry would profit from 10 ppm low sulfur standard by the roughl y 4 to 7 cents per gallon difference between the average cost and the two marginal price values. That per

- gallon profit translates into $4 to $8 billion dollars per year in profit. The average cost of the 10 ppm average gasoline sulfur standard was calculated using API ’s methodology

for amortizing capital investments. To facilitate a fairer comparison between the API cost study and our cost study, we adjusted the API costs to be on a similar basis as our costs. We adjusted the APIcosts to reflect a before

- tax 7 percent return on investment (ROI) for capital invested for the hydro treaters and hydrogen plants instead of the after

- tax 15

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## 5

- 53 percent ROI used b y AP I. This lowered the API estimated costs from 2.12 c/gal to 1.58 c/gal. API ’s 1.58 cents per gallon cost is still higher than our 0.89 c/gal cost with an ABT program that assum es intercompany trading of credits, and higher than our 0.97 c/gal for the case which assumes no ABT program. Thus comparing “apples

- to
- apples” to the to the extent possible, API ’s 1. 58 c/gal estimated cost for compl ying with a 10 ppm average gasoline sul fur standard compares very

favorabl y with our own cost estimates, and not at all near the 25 c/gal value that was sometimes quoted from the first APIstudy

. The remaining cost difference between our estimated costs and those by API are the capital cost as sumptions that APIused , as discussed below

. While little detail is is provided by API about what hardware comprises their desulfurization unit s , the inside battery limits (I SBL) and total capital costs for the FCC postreaters and FCC pretreaters are provided in API ’s report. API’s FCC pretreaters capital costs are consistent with the capital costs that we have used for this unit. However, the FCC postreater costs used b y APIare much higher than what we used and have been used in the past by others. AP I’s capital cost for a grassroots FCC postreater is $228 million for a 35,000 bbl/day unit, or $6540 per/bbl per day . API’s capital cost includes the outside battery limit (OSBL) costs . In contrast, the ISBL capital cost that we used for a grassroots FCC postreater is $1500/bbl

- day

for a 30,000 bbl/day

grassroots unit , which increases to $1875/bbl/day when the offsite costs are added on

. Thus, the APIcapital costs are about 3 1⁄2 times higher than the capital costs that we are using for a grassroots FCC p ostreater . To check our capital costs, we found other capital cost estimates to which we could compare our costs, including the capital costs used by the National Petroleum Council when it studied the cost of gasoline desulfurization prior to Tier 2. Table 5

- 35 contains a cost comparison of ISBL , and ISBL and OSBL FCC postreater capital costs. **Table 5**  **- 35**  **Capital Cost Comparison** Technology EPA

(Tier 3) API Mathpro

(ICCT) Jacobs Exxon

Scanfining (NPC) IFP

Prime G (NPC) CDTech

(NPC) Phillips S

- Zorb (NPC) IS BL Capital Cost ( $/bbl/day) 1500

- - 2440 1045 1410 960 860 IS BL and OSBL Capital Cost ($/bbl/day) 1875 6540 1800 3538 1360 1833 1248 1118

Table 5

- 35 shows that, c ompared to the average of the rest of the capital cost estimates, the APIcapital cost for FCC postreater is about four times higher. Compared to the next highest cost estimate, which is the FCC postreater capital cost from the Jacobs data base in the Hav erl y refinery cost model that we use, K 

## the APIcapital costs are almost two times higher. An important distinction must be made with respect to the severity of desulfurization for the capital cost comparison made in Table 5

- 27

. For compl ying with the Tier 2 gasoline sulfur

K 

### The installed capital cost for an FCC postreater from the Jacobs data base was adjusted to current year dollars. This estimated installed capital cost is several years old and may not represent Jacobs current cost estimate for a FCC postreater.

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## 5

- 54 standard (Jacobs and NPC costs), a ty pical refinery

would have installed an FCC postreater to desulfurize the FCC naphtha from about 800 ppm down to about 75 ppm, a 725 ppm, or a 91 percent sulfur reduction. Inthe case of a grassroots postreater that would be installed for Tier 3, the postreater would treat FCC naphtha already low in sulfur due to the pretreater installed before the FCC unit (these refineries are currentl y complying with Tier 2 using an FCC pretreater) . Thus, the new grassroots FCC postreater would onl y have to reduce the FCC naphtha from 100 ppm to 25 ppm, a much smaller 75 ppm or 75 percent sulfur reduction. A grassroots FCC postreater installed for Tier 2 would typically remove 10 times more sulfur than one installed for Tier 3. This is important because a significant portion of the FCC postreater capital cost is devoted to avoiding the recombination reactions which occur when hydrogen sulfide concentrations are high and react with the ole fins contained in the FCC naphtha. Thus, a grassroots FCC postreater installed for Tier 3 would be expected to be significantly lower in capital cost compared to a Tier 2 FCC postreater . When APIpresented the costs to us, they stated that their grassroo ts capital costs were based on an actual installation for the Tier 2 program. This could be one reason why the capital costs used b y AP I for its cost study of the Tier 3 program are so high. Another way to assess the APIcapital cost for the FCC postreaters is to compare it to the FCC pretreater cost that API is using. FCC pretreaters are much higher pressure units and use more expensive metallurgy than FCC postreaters and, for these two reasons, are much more expensive than FCC postreaters on a per-barrel basis. However, API’s FCC postreater capital costs are about 50 percent more expensive than its FCC pretreater capital costs, which is inconsistent with the design requirements of the units. API ’s estimated range of capital cost for revamping an FCC postreater is also higher than our range of capital cost for revamping an FCC postreater , when assessing the revamped costs as a percentage of the capital cost for a grassroots unit. APIestimates that revamping an FCC postreater would cost 30 to 70 percent of the capital cost for a grassroots FCC unit. Our capital cost estimate for revamping an FCC naphtha postreaters from 17 to 50 percent of the capital cost for a grassroots FCC postreater , however, most of the revamps are estimated to cost at the lower end of that range. The Emissions Control Technology Association (ECTA) retained personne l within Navigant Economics to study the costs of a 10 ppm average gasoline sulfur standard and assess the ICCT and API cost studies. 13 

## The authors made a number of conclusions. After reviewing both the ICCT and API studies, the authors found that a primary difference in estimated costs between the two studies was the capital costs. The authors contacted vendor companies that license FCC postreater technologies and surveyed the companies to find out what the capital costs are for a FCC postreater. As a result of the survey, the report authors concluded that API’s capital costs were too high, and those used in the ICCT study were about right. The authors found that Baker and O’Brien has a history of exaggerating the economic impacts of EPA rules, citing the costs and other impacts of its analysis of the 2007 on

-highway heavy

- duty

proposed rulemaking. The authors concluded that the impact of a 10 ppm gasoline sulfur standard on the average refining cost would likely be closer to the 1 cent per gallon estimate by the ICCT study

. Furthermore, the report ’s authors also pointed out that the marginal cost analysis conducted by APIdid not consider the proposed averaging banking and trading (ABT) program that we were expected to propose, which would reduce the marginal costs of the Tier 3 proposed rule . Because API ’s addendums to its original report came out many months after its original report, we originall y assessed the m ost similar case to our proposal from API’s original study . This was

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## 5

- 55 sensitivity

case 3, which studied a 10

-ppm average gasoline sulfur standard with a 7.8

-psi RVP limit on all conventional gasoline with a 1

-psi waiver. One of the most important conclusi ons by APIwith respect to sensitivity case 3 was the projected 623 thousand barrels per day (about 6.5 percent of total gasoline demand) reduction in U.S. gasoline production due to reduced blending of light hydrocarbons in response to RVP control and the closure of 4 refineries caused b y the investment hurdle of complying with both the sulfur and RVP standards evaluated. Because of API ’s significant projected impacts, which differed from those made b y the Alliance and b y ECTA in their studies, we looked closel y at this projected impact. We found that this projection for a large shortfall in supply is similar to previous projections made by APIfor earlier rulemakings. Baker and O’brien made a very dire projection for diesel fuel supply when anal yz ing the final highway and proposed nonroad diesel fuel sulfur regulations for the proposed nonroad diesel rulemaking back in 2003. 14 

## API ’s projection was that 12 refineries would be shutdown and that U.S. refiners would exit the diesel market resulting in a shor tage of diesel fuel supply of 639 thousand barrels per day and to make up the shortfall, the distillate market would need to be supplied b y i mports. Since that projection was made back in 2003 and the highway diesel fuel program is fully implemented and the nonroad diesel fuel program is mostly implemented, we can look at the impacts to see how well API’s projection played out. First, with respect to imports, the distillate import/export market was fairly stable at about 200 thousand barrels per day of net imports during the period 2003 to 2005, before the highway and nonroad programs started. If we add the expected increase in imports estimated by API caused b y the UL SD highway rule, API projected the imports to increase to 549 thousand barrels per day in 2006. When the temporary compliance option of the UL SD highway rule ended in 2010 and nonroad diesel (excluding locomotive and marine diesel because those requirements don’t start until 2012) must comply with the ULSD nonroad diesel rule in 2010, APIe stimated that imports will increase to 829 thousand barrels per day including the baseline imports. However, what actually

occurred is that imports not only did not increase, but they actuall y decreased to the point that the U.S. became net exporters of 4 28 thousand barrels per day of distillate. 15 16 

## Thus, API was off b y over 1200 thousand barrels per day in its estimate of distillate production in 2010 by U.S. refiners. Figure 5

- 9 summarizes the imports and exports of diesel fue l and gasoline during the period when the clean fuels regulations were being phased in.

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## 5

- 56 **Figure 5**  **- 9**  **Petroleum Product Imports and Exports During the Implementation of**  **Clean Fuels Regulations**  One reason why APIwas so far off in its projection that U.S. distillate supply would decrease significantly

is that it had projected that 12 refineries would shut down due to the highway and nonroad rulemakings, but, in fact, there were very few refinery

shutdowns. 17 18 

## Between 2003 and 2011 when the highway and nonroad diesel fuel UL SD programs were phasing in (as well as Tier 2, MSAT2, RFS1 and RFS2), there was a total of 5 refinery shutdowns of refineries which produce transportation fuels. However, also during this tim e period there were reactivations of three previously shutdown transportation fuel producing refineries. Considering both the shutdown refineries and reactivated refineries, there was a net shutdown of two transportation fuel producing refinery closures. It is unclear why those 5 transportation fuel producing refineries shutdown , but there is no evidence to suggest they were caused b y the diesel rules

. There are many factors which cause refinery shutdowns. To understand these factors it is necessary to revisit the history

of the U.S. refining industry

. 19 

## During the second crude oil embargo which occurred during the Carter Administration, subsidies were established that incentivized the construction of many small refineries. After crude oil prices dropp ed, those subsidies ended and many of those refineries were not economicall y competitive with larger refineries. Over time the number of refineries decreased and the remaining refineries were expanded to supply the U.S. market. This is part of a rational ization that most any industry experiences as the industry matures. Figure 5

- 10 and Table 5

- 36 summarize the changes in the number of refineries, the average size of refineries, and the total production capacity of the U.S. refining industry based on data from the Energy In formation Administration (EIA).

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## 5

- 57 **Figure 5**  **- 10**  **Refining Industry Statistics**
**Table 5**  **- 36**  **U.S. Refinery Industry Statistics**  Year 1982

- 1992 1993

– 2002 2003

- 2011 Net Change in the Number of Operable Refineries - 102

- 50

- 2 Change in Average Refinery Size (kbbl/day) +18,400 +31,800 +11,000 Change in Total U.S. Operating Refinery Capacity (MMbbl/day) - 1.2 +1.6 +0.4 Figure 5

- 10 and Table 5

- 36 show that there were many refinery closures during the 1980s and 1990s, although over time the number of refinery closures was diminishing. Therefore, the refinery closures which occurred during the 2003 to 2011 time frame could very well be due to this rationalization process reflecting a maturing industry

. In fact, examining the trend, the number of net refinery

shutdowns is virtually

flat during the 2003 to 2011 time frame relative to the previous periods

. This is clearly a rationalization of the refining industry because as refineries were closing, the average refinery size increased over each of the periods. Finall y, the total U.S. refinery

capac ity decreased and increased back to its 1982 levels during the 1980s and earl y 90s (decrease was likely due to the corporate average fuel economy standards) , but showed a modest increase from the late 1990 ’ s through 2011. **5.4 Projected Energy Impacts and Impa**  **cts on Permitting** Our refinery

-by

- refinery

model was also used to determine the impact the Tier 3 standards would have on the energy related CO2 emissions and permitting of existing refineries. While the Tier 3 proposal will reduce emissions from vehicles , the addition of grass roots units

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## 5

- 58 and revamping of existing units which we project will happen as a result of the Tier 3 sulfur standards are likel y to result in some increased emissions of regulated air pollutants at refineries

. Refinery projects designed to meet the new fuel standards could trigger preconstruction air permitting requirements under the Clean Air Act and EPA’s New Source Review (NSR) regulations. To address this concern, we used our refinery

- by

-refinery model to estimate the likely proc ess and equipment changes that may be required to meet the Tier 3 gasoline standards. This information was submitted to EPA’s Office of Air Quality Planning and Standards (OAQPS) to provide the inputs that are necessary for the modeling and analysis of th e refinery emissions and permitting impacts of the Tier 3 fuel standards. Using our refinery

-by

- refinery model we generated refinery

- specific estimates of the increased energy, hydrogen, and gasoline octane demands that we estimate will result from the proposed Tier 3 standards. We also estimated the increase in sulfur plant recovery unit (SRU) loading/operations for the 111 U.S. refineries that we modeled in our anal ysis. Energy demand includes fuel that is needed to generate refinery process heat, steam and electricity

. Hydrogen demand is associated with increased hydrotreating of Fluid Catal ytic Cracking (FCC) naphtha and light straight run (LSR) streams. Increased gasoline octane demand results from refineries having to replace octane that is lost due to increased FCC naphtha hydrotreating. Increased SRU loading results from the increased fuel desulfurization and associated H2S generation. All of these incremental demands will be referred to as “demands” in the following sections. We used our refinery-by

- refinery

model to calculate the increase in these various demands for several scenarios where sulfur averaging, banking, and trading (ABT) was not allowed and each refinery had to meet the 10ppm standard, as well as scenarios that allowed ABT between refineries owned b y the same parent company to minimize the cost of compliance with the Tier 3 standards. 5.4.1 Emissions Impacts of Different Production Volumes In addition to considering scenarios with and without ABT we also considered the impacts on emissi ons and permitting of different gasoline production volumes for each refinery. In the first case, called the normal case, we considered the incremental demands for each refinery assuming no change in gasoline production volume. We also considered a case, called the maximum demand case, where each refinery maximized gasoline production based on currentl y existing refinery

capacity and equipment. 5.4.1.1 Normal Case The normal case was estimated using each refinery’s predicted yi elds of FCC naphtha and L SR from our refinery

- by

- refinery model, along with each refinery ’s total gasoline production volume from EPA’s RFG database. For each refinery the refinery

-by

- refinery

model generated specific Tier 3 demands for hydrogen, steam, fuel gas, electricity and gasoline octane based on the desulfurization technology used b y each refinery

for any FCC postreating and L SR hydrotreating. To determine the FCC postreating demands the model considers each refinery ’s volume of FCC naphtha under normal operations, the FCC naphtha sulfur level at the refinery prior to postreating, and the process requirements of the FCC postreater technology used b y that refinery . The demands are calculated by multiplying the FCC naphtha volume by the demands from the use of the associated FCC postreating technology

. Table 5

- 26 through Table 5

- 29 show

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## 5

- 59 the FCC postreater technology demand averages as applied to refineries on a national basis for the 5 and 10 ppm gasoline sulfur standards. Note that the demands vary significantly

with the FCC naphtha sulfur level prior to postreating. Similarly, the normal case demands for any L SR blendstocks that require additional hydrotreating as a result of the Tier 3 standards were determined based on each refinery ’s yi eld of L SR blendstock under normal operations and the demands for the additional L SR hydrotreating. These demands, on a national average basis, are listed in Table 5

- 3 1 . The normal case demands for FCC postreating and L SR hydrotreating were then summed to determine the increase in energy, hydrogen, and octane demand. To determine the additional sulfur removed from gasoline we first calculated the difference between the current gasoline sulfur level of the gasoline produced at each refinery according to their compliance reports to EPA and the proposed Tier 3 standard. This difference was multiplied by the refinery ’s gasoline production volume and divided by

the number of days of operation to calculate the additional sulfur removal level at each refinery . This sulfur removal information was then used to determine the increase in SRU loading on a fractional basis by dividing the additional sulfur removal as a result of the Tier 3 standards (in tons of sulfur per day) b y the refineries SRU process capacity.

5.4.1.2 Maximum Case We also considered a second demand case, called the maximum case, in which we calculated the demands that result from the Tier 3 standards if each refinery maximizes gasoline production based on currently existing refinery capacity . For this case we first determined each refiners FCC unit process capacity utilization rate in the normal case. The annual FCC unit feedstock charge rate for each refinery as reported in the 2009 EIA data was divided by the FCC unit design cap acity as reported in the Oil and Gas Journal (OGJ) to calculate the capacity utilization rate for the normal case. These normal capacity utilization rates were then scaled up to reflect maximum capacity utilization rates, and further adjusted using an overdesign factor. For refineries projected to meet the proposed Tier 3 standards b y revamping existing FCC postreating units we assumed that their maximum gasoline production rate was equal to the rate produced running the FCC unit at 92% of the refinery ’s maximum FCC design capacity. There were several refineries that are currently operating their FCC unit greater than a 92% capacity utilization rate. We assumed that these refineries were already operating at their maximum annual capacity utilization rate

. For refineries projected to install a new FCC postreater we similarly

assumed that the new unit would be scaled to process the output of the FCC unit operating with a 92% utilization rate. For new FCC postreaters, however, we increased the results by 15 % as an overdesign factor and adjusted the results accordingl y. A similar sizing approach was taken for refineries we projected would revamp or add new LSR hydrotreating capacity to compl y with the proposed Tier 3 standards. The results represent a “maximum” annual gasoline production case for each refinery under the Tier 3 standards based on each refiners FCC unit design capacity. These cases represent a scenario where each refinery projects emissions based on the maximum achievable annual production rate for their existing processing units. These cases reflect each refiner’s potential emissions impacts as a result of the proposed Tier 3 standards, rather than the existing

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## 5

- 60 Tier 2 standards, when operating at maximum FCC rates as opposed to normal operati on more indicative of national gasoline demand. 5.4.2 Refinery

Demand Sourcing After determining the increased demands for each refinery as a result of the proposed Tier 3 regulations we next developed cases for each refinery demand scenario that represented dif ferent options for sourcing these demands. Some refiners may choose to produce all of the required hydrogen and electricity, as well as make up for all of the lost octane at their refinery. Others may

choose to purchase some or all of the hydrogen, electricity, and high octane blendstocks that they

would need to comply

with the Tier 3 standards from external suppliers. These decisions have a significant impact on the emissions and permitting impacts of the proposed Tier 3 regulations. In order to bound all possible scenarios we considered both high and low impact cases for each refinery demand scenario. In the high impact scenarios we assume that each refinery produces all of the required hydrogen , and electricity needs while making up for any gasoline octane loss at their refinery . In the low impact scenarios we assume that all the necessary

hydrogen, electricity, and high octane blendstocks are purchased from an external supplier. In both cases we assumed that fuel gas demands would increase to meet the increased thermal demands at the refinery . In the high impact scenarios the refinery ’s fuel gas needs would be further increased to produce the needed hydrogen and electricity while replac ing the lost octane in their gasoline. We consulted literature sources to determine the conversion factors from MBTU fuel gas to 1 , 000 standard cubic feet (scf) of hydrogen20 

## and 1 , 000 pounds of steam21 

## that are typical for refineries. We also assumed a standard conversion efficiency from fuel gas to electricity

for our modeling. These conversion factors are shown in Table 5

- 37 below. **Table 5**  **- 37**  **Fuel Gas Required to Produce Hydrotreater Utilities** Utility Fuel Gas Required (M BTU) Hydrogen (1 , 000 SCF) 239 Steam (1 , 000 lbs) 1530 Electricity

(1 kWh) 5.1 We also had to determine the fuel gas demands that would be required to make up for lost octane in our high impacts scenario. For this anal ysis w e assumed that all lost octane in the gasoline that results from increased FCC postreating to meet the proposed Tier 3 standards would be recovered b y running the reformers at the refineries at a higher severity as opposed to sourcing it from ethanol or other means . This would increase the octane of the refor mate and offset the octane losses from the FCC naphtha, resulting in no change in the octane of the overall gasoline pool. Running the reformer at a higher severity requires a higher reactor processing temperature and an increased volumetric rate for the pumps and compressors. These changes further increase the fuel gas and electricity demands of the refinery . We estimated these demands using information we obtained from our Jacob’s refinery LP modeling anal ys is. The estimates we used for the fuel gas and electricity demands for increasing gasoline octane are shown in Table 5

- 38 below. These demand increases were only used for the high impact

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## 5

- 61 scenarios. For the low impact scenarios we assumed that lost octane was recovered b y purchasing high octane blendstocks resulting in no fuel gas or electricity demand increases at the refinery

. **Table 5**  **- 38**  **Energy Required to Increase Gasoline Octane** Utility Amount Required to Increase

Octane a 

## 1 Point (per barrel gasoline) Fuel Gas (M BTU) 1.87 Electricity

(kWh) 0.057 Note: a 

### (R + M)/2 method 

## 5.4.3 Refinery

Demand Impacts Using our refinery

-by

- refinery model, along with the technology vendor data for new and revamped FCC postreating and LSR hydrotreating data (shown in Table 5

- 26 through Table 5

- 29 and Table 5

- 3 1 ) we were able to calculate the increases in refinery demands as a result of our proposed Tier 3 regulations for each of the vari ous scenarios outlined in the previous sections. This information is summarized in Table 5

- 39 and Table 5

- 40 below. The refineries have been identified by

randoml y assigned numbers to protect confidential business information (CBI). This information was submitted to OAQPS to serve as the basis for their emissions and permitting anal ys is of the Tier 3 regulations. Based on the data provided b y EPA, OAQPS determined that the increased demands that result from the Tier 3 regulations would exceed the permitting thresholds under the New Source Review (NSR) regulations, including the Prevention of Significant Deterioration (PSD) and/or the Nonattainment New Source Review (NA NSR) for 16 refineries in the low impact s cenarios and 22 refineries in the high impact scenarios. An additional 7 refineries in the low impacts scenarios, and 13 refineries in the high impact scenarios, would exceed the threshold to trigger reviews for greenhouse gas emissions only

. A technical memorandum describing the OAQPS analysis and results is in the public docket for this proposal. 22

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## 5

- 62 **Table 5**  **- 39**  **Tier 3 Refinery Energy, Hydrogen and Sulfur Plant**  **Demand Increases (10 ppm, No ABT Case**  **s )** 

Refinery Number Demand Estimates Fuel Gas Demands Sulfur Plant Production Hydrogen Low Impact Cases (Million BTU/Yr) High Impact Cases (Million BTU/Yr) Sulfur

Production Increase (Tons Sulfur/Day) Sulfur Plant

Capacity Increase (Percent of Existing Facility) Hydrogen

Demand Increase (million scf/year) Normal Volumes Maximum

Volumes Normal

Volumes Maximum

Volumes 1 117,423 117,423 243,241 243,241 0.28 0.02 426 2 0 0 0 0 0.00 0.00 0 3 2,239,110 2,739,637 2,566,562 3,140,286 0.00 0.00 863 4 173,672 173,672 569,009 569,009 0.43 0.03 1,628 5 46,380 58,279 261,528 328,624 0.13 0.04 655 6 4,433 7,291 14,523 23,888 0.04 1.96 42 7 60,923 69,776 199,605 228,609 0.10 0.03 571 8 23,941 29,792 134,995 167,988 0.17 0.07 338 9 107,543 135,777 222,775 281,262 0.20 0 .18 390 10 25,924 29,812 146,179 168,106 0.10 0.08 366 11 13,984 16,250 78,855 91,630 0.09 0.05 198 12 76,663 92,786 251,175 303,997 0.43 0.07 719 13 51,432 51,432 168,509 168,509 0.47 1.18 482 14 0 0 6,444 6,444 0.00 0.00 27 15 16,876 16,876 89,463 89,463 0.07 0.13 219 16 831,027 1,244,900 899,341 1,347,235 0.26 0.22 218 17 31,964 31,964 82,442 82,442 2.19 0.96 206 18 150,568 150,568 311,900 311,900 0.22 0.03 547 19 27,087 44,061 152,736 248,452 0.26 a 

### 383 20 43,909 46,106 143,861 151,058 0.37 0 .08 412 21 165,539 212,719 343,091 440,875 0.17 0.04 538 22 14,886 16,690 38,395 43,048 0.01 0.02 96 23 83,222 83,222 272,663 272,663 0.41 0.12 780 24 190,870 210,535 206,560 227,841 0.33 0.29 50 25 702,808 702,808 798,012 798,012 0.10 0.09 256 26 20 ,503 22,001 67,175 72,082 0.90 0.60 192 27 0 0 0 0 0.00 0.00 0 28 3,145,454 3,528,532 3,223,899 3,616,532 0.31 0.07 201 29 0 0 0 0 0.00 0.00 0 30 64,080 66,959 165,279 172,703 0.15 0.01 414 31 0 0 0 0 0.00 0.00 0 32 62,002 62,002 159,918 159,918 0.35 3.46 400 33 1,693,620 1,948,219 1,832,841 2,108,370 0.27 0.03 444 34 16,574 24,879 93,456 140,290 0.15 0.21 234 35 10,469 10,469 12,340 12,340 0.04 0.96 6 36 337,961 411,915 365,743 445,776 0.15 a 

### 89 37 5,175 5,175 29,180 29,180 0.13 3.30 73 38 0 0 2,907 2,907 0.00 0.00 12

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## 5

- 63 Refinery Number Demand Estimates Fuel Gas Demands Sulfur Plant Production Hydrogen Low Impact Cases (Million BTU/Yr) High Impact Cases (Million BTU/Yr) Sulfur

Production Sulfur Plant

Capacity Hydrogen

Demand 39 21,773 21,773 71,336 71,336 0.58 0.93 204 40 19,171 23,883 91,207 113,621 0.04 0.01 214 41 177,093 203,657 636,542 732,024 0.30 0.03 1,288 42 3,288 4,683 10,773 15,343 0.03 0.97 31 43 41,705 43,146 107,567 111,284 0.52 0.26 269 44 3,609,133 4,265,613 3,905,818 4,616,262 0.66 0.22 946 45 27,946 41,431 105,829 156,897 0.06 a 

### 221 46 6,846 8,054 38,603 45,416 0.05 0.55 97 47 1,416,139 1,416,139 1,532,550 1,532,550 0.25 0.03 371 48 21,918 41,206 45,403 85,358 0.02 0.01 80 4 9 7,024 7,191 18,116 18,547 0.19 2.16 45 50 2,170,692 2,170,692 2,349,131 2,349,131 0.61 0.23 569 51 0 0 0 0 0.00 0.00 0 52 3,945,526 3,984,109 4,269,863 4,311,617 0.61 0.03 1,034 53 102,473 124,044 264,305 319,941 0.46 a 

### 662 54 40,155 51,299 108,185 138,209 0.11 0.09 236 55 21,405 26,758 120,695 150,884 0.16 0.13 302 56 26,807 28,515 70,005 74,463 0.04 0.13 144 57 91,964 107,033 518,563 603,534 0.00 0.03 1,299 58 0 0 0 0 0.00 0.00 0 59 52,160 62,683 108,050 129,848 0.10 0.03 189 60 109,050 10 9,050 357,285 357,285 0.62 0.11 1,022 61 23,773 23,773 36,151 36,151 0.04 0.00 52 62 9,233 9,655 30,251 31,632 0.04 1.96 87 63 136,167 175,790 282,068 364,148 0.08 0.01 494 64 54,151 60,794 165,033 185,278 0.24 0.12 221 65 360,695 402,762 390,346 435, 870 0.05 0.19 95 66 8,113 8,589 20,926 22,152 0.04 0.39 52 67 26,289 34,157 67,806 88,100 0.19 0.17 170 68 89,955 103,448 507,237 583,323 0.20 0.02 1,271 69 30,259 33,479 99,139 109,690 0.14 0.14 284 70 9,369 20,299 61,521 133,298 0.20 0.03 103 71 37 ,188 37,188 121,841 121,841 1.31 0.44 349 72 1,079,231 1,299,822 1,167,948 1,406,672 0.09 0.14 283 73 15,845 17,618 51,915 57,724 0.03 0.00 149 74 38,525 40,291 101,764 106,429 0.09 0.04 215 75 0 0 0 0 0.00 0.00 0 76 14,588 14,588 47,795 47,795 0.03 0 .00 137 77 16,875 20,135 43,524 51,932 0.13 0.70 109 78 139,558 139,558 289,093 289,093 0.16 0.02 507 79 0 0 0 0 0.00 0.00 0 80 64,517 76,071 65,729 77,500 0.07 0.10 234 81 2,009,982 2,009,982 2,280,122 2,280,122 0.24 0.05 729 82 58,475 60,441 191,58 3 198,026 0.26 a 

### 548

### *** E.O. 12866 Review

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## 5

- 64 Refinery Number Demand Estimates Fuel Gas Demands Sulfur Plant Production Hydrogen Low Impact Cases (Million BTU/Yr) High Impact Cases (Million BTU/Yr) Sulfur

Production Sulfur Plant

Capacity Hydrogen

Demand 83 2,008,357 2,021,700 2,173,451 2,187,891 0.48 0.09 526 84 0 0 0 0 0.00 0.00 0 85 23,472 27,526 132,354 155,214 0.27 0.14 332 86 20,570 24,731 115,988 139,454 0.00 0.00 291 87 97,698 112,353 363,505 418,031 0.35 0.10 752 88 4,17 1 5,743 27,391 37,710 0.08 0.12 46 89 147,823 147,823 306,331 306,331 0.13 0.01 495 90 786,104 984,013 850,725 1,064,903 0.30 0.18 206 91 786,104 984,013 850,725 1,064,903 0.41 1.47 206 92 25,608 25,608 53,152 53,152 0.03 0.08 56 93 35,993 47,565 36,6 69 48,459 0.05 a 

### 131 94 4,151,496 4,231,505 4,606,346 4,695,121 0.65 0.08 1,307 95 1,232 2,692 8,090 17,675 0.01 0.03 14 96 2,457 3,308 13,417 18,060 0.02 a 

### 33 97 28,695 28,695 74,012 74,012 0.52 a 

### 185 98 0 0 0 0 0.00 0.00 0 99 46,468 50,408 152,246 165,155 0.26 0.66 436 100 2,591,010 2,708,025 2,804,001 2,930,635 0.83 0.13 679 101 0 0 0 0 0.00 0.00 0 102 32,339 57,437 111,894 198,734 0.12 0.06 221 103 0 0 0 0 0.00 0.00 0 104 74,538 74,538 154,710 154,710 0.00 0.00 162 105 5,400 5,668 35,458 37, 218 0.00 0.00 59 106 139,029 139,029 455,507 455,507 0.25 0.02 1,303 107 0 0 11,540 11,540 0.05 a 

### 48 108 8,314 8,879 17,223 18,393 0.00 0.00 30 109 1,485,414 1,704,414 1,607,521 1,844,524 0.32 0.05 389 110 122,762 122,762 279,765 279,765 0.22 0.06 515 111 27,548 33,475 155,338 188,757 0.10 0.07 389 a 

### The refinery did not have published information on the capacity of the existing sulfur plant.

### *** E.O. 12866 Review

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## 5

- 65 **Table 5**  **- 40**  **Tier 3 Refinery Energy, Hydrogen and Sulfur Plant**  **Demand Increase (10 ppm, ABT Cases)** 

Refinery Number Demand Estimates Fuel Gas Demands Sulfur Plant Production Hydrogen Low Impact Cases (Million BTU/Yr) High Impact Cases (Million BTU/Yr) Sulfur

Production Increase (Tons Sulfur/Day) Sulfur Plant

Capacity Increase (Percent of Existing Facility) Hydrogen

Demand Increase (million scf/day) Normal Volumes Maximum

Volumes Normal

Volumes Maximum

Volumes 1 20,503 22,001 67,175 72,082 0.90 0.60 192 2 64,080 66,959 229,725 240,045 0.22 0.02 467 3 323,504 388,955 476,338 572,710 0.00 0.00 528 4 89,955 103,448 507,237 583,323 0.20 0.02 1,271 5 0 0 0 0 0.00 0.00 0 6 426,001 692,966 627,257 1,020,346 0.29 a 

### 696 7 0 0 0 0 0.00 0.00 0 8 26,807 28,515 70,005 74,463 0.04 0.13 144 9 117,423 117,423 243,241 24 3,241 0.28 0.02 426 10 5,400 5,668 35,458 37,218 0.00 0.00 59 11 1,525,387 1,525,387 1,558,831 1,558,831 0.51 1.28 64 12 8,113 8,589 20,926 22,152 0.04 0.39 52 13 7,024 7,191 18,116 18,547 0.19 2.16 45 14 74,538 74,538 154,710 154,710 0.00 0.00 162 1 5 0 0 0 0 0.00 0.00 0 16 2,591,010 2,708,025 2,804,001 2,930,635 0.83 0.13 679 17 177,093 203,657 636,542 732,024 0.30 0.03 1,288 18 0 0 0 0 0.00 0.00 0 19 19,171 23,883 91,207 113,621 0.04 0.01 214 20 26,289 34,157 67,806 88,100 0.19 0.17 170 21 2,2 39,110 2,739,637 2,566,562 3,140,286 0.00 0.00 863 22 83,222 83,222 272,663 272,663 0.41 0.12 780 23 147,823 147,823 306,331 306,331 0.13 0.01 495 24 0 0 2,907 2,907 0.00 0.00 12 25 2,273,706 2,751,864 2,323,556 2,812,199 0.50 0.08 96 26 0 0 0 0 0.00 0.00 0 27 107,543 135,777 222,775 281,262 0.20 0.18 390 28 16,875 20,135 43,524 51,932 0.13 0.70 109 29 150,568 150,568 311,900 311,900 0.22 0.03 547 30 0 0 0 0 0.00 0.00 0 31 30,259 33,479 99,139 109,690 0.14 0.14 284 32 0 0 0 0 0.00 0.00 0 33 139, 558 139,558 289,093 289,093 0.16 0.02 507 34 9,369 20,299 61,521 133,298 0.20 0.03 103 35 0 0 6,444 6,444 0.00 0.00 27 36 0 0 0 0 0.00 0.00 0 37 109,050 109,050 357,285 357,285 0.62 0.11 1,022 38 0 0 0 0 0.00 0.00 0

### *** E.O. 12866 Review

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## 5

- 66 Refinery Number Demand Estimates Fuel Gas Demands Sulfur Plant Production Hydrogen Low Impact Cases (Million BTU/Yr) High Impact Cases (Million BTU/Yr) Sulfur

Production Sulfur Plant

Capacity Hydrogen

Demand 39 10,469 10,469 12,340 12,340 0.0 4 0.96 6 40 210,772 269,511 319,729 408,832 0.07 0.00 379 41 173,672 173,672 569,009 569,009 0.43 0.03 1,628 42 21,773 21,773 71,336 71,336 0.58 0.93 204 43 3,145,454 3,528,532 3,223,899 3,616,532 0.31 0.07 201 44 337,961 411,915 365,743 445,776 0.15 a 

### 89 45 3,945,526 3,984,109 4,269,863 4,311,617 0.61 0.03 1,034 46 97,698 112,353 363,505 418,031 0.35 0.10 752 47 1,416,139 1,416,139 1,532,550 1,532,550 0.25 0.03 371 48 16,876 16,876 89,463 89,463 0.07 0.13 219 49 433,258 526,468 637,943 775,189 0. 14 0.09 707 50 4,433 7,291 14,523 23,888 0.04 1.96 42 51 58,475 60,441 191,583 198,026 0.26 a 

### 548 52 2,170,692 2,170,692 2,349,131 2,349,131 0.61 0.23 569 53 8,497 8,497 12,247 12,247 0.00 0.00 16 54 31,964 31,964 82,442 82,442 2.19 0.96 206 55 336,6 35 420,834 495,673 619,649 0.19 0.15 550 56 32,339 57,437 111,894 198,734 0.12 0.06 221 57 38,525 40,291 101,764 106,429 0.09 0.04 215 58 54,151 60,794 165,033 185,278 0.24 0.12 221 59 0 0 0 0 0.00 0.00 0 60 23,773 23,773 36,151 36,151 0.04 0.00 52 6 1 190,870 210,535 206,560 227,841 0.33 0.29 50 62 3,288 4,683 10,773 15,343 0.03 0.97 31 63 0 0 0 0 0.00 0.00 0 64 2,008,357 2,021,700 2,173,451 2,187,891 0.48 0.09 526 65 2,457 3,308 13,417 18,060 0.02 a 

### 33 66 41,705 43,146 149,509 154,676 0.63 0.31 304 67 46,468 50,408 152,246 165,155 0.26 0.66 436 68 1,079,231 1,299,822 1,167,948 1,406,672 0.09 0.14 283 69 3,071 3,325 7,294 7,896 0.00 0.00 17 70 4,123,377 4,123,377 4,213,781 4,213,781 0.38 0.03 174 71 786,104 984,013 850,725 1,064,903 0.30 0.18 206 72 37,188 37,188 121,841 121,841 1.31 0.44 349 73 0 0 0 0 0.00 0.00 0 74 40,155 51,299 108,185 138,209 0.11 0.09 236 75 1,485,414 1,704,414 1,607,521 1,844,524 0.32 0.05 389 76 122,762 122,762 279,765 279,765 0.22 0.06 515 77 102,473 124,044 264 ,305 319,941 0.46 a 

### 662 78 0 0 0 0 0.00 0.00 0 79 3,609,133 4,265,613 3,905,818 4,616,262 0.66 0.22 946 80 43,909 46,106 143,861 151,058 0.37 0.08 412 81 1,693,620 1,948,219 1,832,841 2,108,370 0.27 0.03 444 82 0 0 0 0 0.00 0.00 0

### *** E.O. 12866 Review

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## 5

- 67 Refinery Number Demand Estimates Fuel Gas Demands Sulfur Plant Production Hydrogen Low Impact Cases (Million BTU/Yr) High Impact Cases (Million BTU/Yr) Sulfur

Production Sulfur Plant

Capacity Hydrogen

Demand 83 60,923 69,776 19 9,605 228,609 0.10 0.03 571 84 4,171 5,743 27,391 37,710 0.08 0.12 46 85 4,151,496 4,231,505 4,606,346 4,695,121 0.65 0.08 1,307 86 8,314 8,879 17,223 18,393 0.00 0.00 30 87 5,175 5,175 29,180 29,180 0.13 3.30 73 88 96,113 113,326 98,454 116,085 0.13 0.17 543 89 988,379 1,480,617 1,109,185 1,661,587 0.31 0.26 412 90 0 0 0 0 0.00 0.00 0 91 9,233 9,655 30,251 31,632 0.04 1.96 87 92 21,918 41,206 45,403 85,358 0.02 0.01 80 93 14,886 16,690 38,395 43,048 0.01 0.02 96 94 35,993 47,565 36,669 48,459 0. 05 a 

### 131 95 202,851 261,880 506,929 654,442 0.15 0.01 1,146 96 786,104 984,013 850,725 1,064,903 0.41 1.47 206 97 25,924 29,812 146,179 168,106 0.10 0.08 366 98 1,232 2,692 8,090 17,675 0.01 0.03 14 99 369,152 432,912 543,551 637,434 0.30 0.15 603 10 0 0 0 0 0 0.00 0.00 0 101 28,695 28,695 74,012 74,012 0.52 a 

### 185 102 828,747 828,747 965,965 965,965 0.13 0.11 412 103 0 0 11,540 11,540 0.06 a 

### 48 104 13,984 16,250 78,855 91,630 0.09 0.05 198 105 62,002 62,002 159,918 159,918 0.35 3.46 400 106 260,6 61 391,286 383,805 576,142 0.17 0.25 426 107 194,048 194,048 294,359 294,359 0.07 0.00 349 108 0 0 0 0 0.00 0.00 0 109 428,992 479,023 481,425 537,572 0.08 0.27 179 110 52,160 62,683 108,050 129,848 0.10 0.03 189 111 0 0 0 0 0.00 0.00 0 a 

### T he refinery did not have published information on the capacity of the existing sulfur plant.

### *** E.O. 12866 Review

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## 5

- 68 

# Chapter 5 **Appendix LP Refinery Modeling Output Tables** 

### *** E.O. 12866 Review

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## 5

- 69 **Table 5**  **- 41**  **Volume and Cost Information Used for Estimating the Cost of Octane** 

PAD D PAD D 1 PAD D 2 PAD D 3 PAD D 4/ 5 US A Su mme r 33, 001 90, 996 248, 651 20, 296 392, 943 Wi nt er 33, 692 137, 617 302, 644 29, 719 503, 671 Tota l 66, 693 228, 613 551, 294 50, 015 896, 614 Referenc e 10, 021, 915 19, 715, 175 51, 232, 848 11, 926, 884 92, 896, 822 Cont rol 9, 961, 128 19, 662, 097 51, 072, 893 11, 913, 432 92, 609, 550 Di ffe renc e -287, 272 ($/ bbl ) -0. 3203965 (c /g al ) -0. 7628488 FC C Napht ha Vo lu me( kb bl )

Cos t Obj F unc tio n ($000)

### *** E.O. 12866 Review

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## 5

- 70 **Table 5**  **- 42**  **PADD 1 Unit Capacity and Throughput Volumes from LP Refinery Modeling (Thousand bbl/day)**  PADD 1 Re fi ne ry Uni ts Su mmer Wi nter Su mme r Winte r Su mme r Wi nter Crud e To we r 1, 260 1,982 2,791 1,982 2, 792 0 1 Vacu umTowe r 492 788 1,159 788 1, 159 0 0 Sats Gas P la nt 0 110 120 109 120 -1 0 Uns ats Ga s P la nt 0 157 93 157 93 0 0 FCC DeC5 To we r 0 0 0 0 0 0 0 FCC 490 490 291 490 291 0 0 FCC Spl it

ter 0 0 0 21 0 21 0 Hy drocracker 22 69 69 69 69 0 0 H-Oi l Uni t 0 0 0 0 0 0 0 De la ye d Coker 44 153 292 153 292 0 0 Visbreaker 0 0 0 0 0 0 0 The rmal Na phth a S pl it

te r 0 18 35 18 35 0 0 CR U Re forme r 223 281 337 284 337 3 0 SR U Re fo rmer 0 0 0 0 0 0 0 BT X Re forme r 0 29 36 25 36 -4 0 C4 Isomeri za ti on 32 32 32 32 32 0 0 C5/C 6 Isom eri za ti on 7 126 149 133 158 7 9 HF A lkyla ti on 40 40 20 40 20 0 0 H2 SO4 Al kylati on 29 47 44 49 44 3 0 Dim ersol 0 0 0 0 0 0 0 Ca t P oly 5 1 1 1 1 0 0 Is ooctan e 0 0 0 0 0 0 0 DH T - To ta l 334 299 530 299 530 0 0 DH T 2n d RC T - To ta l 0 240 460 240 460 0 0 DH T Arom S at uration 0 0 0 0 0 0 0 NHT - To tal F d 274 571 650 590 651 19 0 CG H - Ge ne ri c 119 158 158 158 158 0 0 CG H - Ole fi n S at'n 119 0 0 0 0 0 0 FCCU F d HD T 44 1,459 1,459 1,459 1, 459 0 0 LSR S pl it ter 0 87 51 100 50 13 -1 LSR B z Saturator 0 0 0 0 0 0 0 Re fo rmate S atu ra tor 0 1 1 1 1 0 0 Re fo rmate S pl it

ter 0 3 3 3 3 0 0 SDA 32, 600 33 33 33 33 0 0 MTB E 3 0 0 0 0 0 0 TA ME 0 0 0 0 0 0 0 Hy drogenP la nt

- T otal MS CF 64 974 1,007 974 1, 008 0 1 Lu be Uni t 146 53 53 53 53 0 0 Su lfu r P la nt 1, 434 1 2 1 2 0 0 Me ro x Jet 0 0 0 0 0 0 0 Me ro x Diesel 0 0 0 0 0 0 0 BT X Re forme r - T

ower fe ed 13 11 13 11 13 0 0 BT X Re forme r - E xt ra ct fe ed 23 23 23 23 23 0 0 To lue ne D eal ky

at io n 0 0 0 0 0 0 0 Cu men e 0 0 0 0 0 0 0 Cy cloh ex an e 0 0 0 0 0 0 0 Control C ase Mi nus1

ON Control C ase Re la ti ve

to Ref C ase 2017 Re f c ase Act ua l Capacit y in2009

### *** E.O. 12866 Review

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## 5

- 71 **Table 5**  **- 43**  **PADD 2 Unit Capacity and Throughput Volumes from LP Refinery Modeling**  **(Thousand bbl/day)** PADD 2 Re fi ne ry Uni ts Su mme r Wi nter Su mme r Winte r Su mme r Wi nter Crud e Towe r 3, 612 2, 996 3,831 2, 996 3,840 0 10 Vacu um To we r 1, 452 1, 326 1,660 1, 326 1,664 0 4 Sats Gas P lant 0 167 171 169 175 2 4 Uns ats Gas P lant 0 255 301 255 302 0 1 FCC DeC5 To we r 0 0 0 0 0 0 0 FCC 1, 144 852 1,036 852 1,039 0 3 FCC Spl it

te r 0 500 594 500 596 0 2 Hy drocracker 234 216 216 216 216 0 0 H-Oi l Uni t 0 0 0 0 0 0 0 Del ay ed Coker 375 280 329 280 329 0 0 Visbr eaker 0 0 0 0 0 0 0 The rmal Nap ht ha S pli tter 0 34 40 34 40 0 0 CR U Re fo rme r 807 516 529 540 542 24 13 SR U Re fo rme r 0 0 0 0 0 0 0 BT X Re fo rme r 0 42 54 42 54 0 0 C4 Is omerizati on 15 65 60 65 63 0 3 C5/C6 Is om eri za ti on 157 168 125 170 141 2 16 HF A lkyl at ion 156 126 78 126 78 0 0 H2 SO4 Al kyla ti on 81 81 40 81 40 0 0 Dim ersol 3 0 0 0 0 0 0 Cat P oly 4 0 0 0 0 0 0 Is ooctan e 0 0 0 0 0 0 0 DH T - To tal 1, 056 691 577 691 577 0 0 DH T 2 nd RC T - To tal 0 512 528 512 529 0 0 DH T A rom S at ura ti on 6 0 0 0 0 0 0 NHT - To ta l F d 1, 038 818 929 823 932 5 3 CG H - Gen eric 282 127 176 133 177 5 1 CG H - Olefi n Sat'n 282 0 0 0 0 0 0 FCCU F d HD T 521 521 521 521 521 0 0 LSR S pl it te r 0 71 100 75 100 4 0 LSR B z Sa tu rator 0 0 0 0 0 0 0 Re fo rma te S at urator 0 1 1 1 1 0 0 Re fo rma te S pl it

te r 0 3 3 3 3 0 0 SDA 32, 600 0 36 0 36 0 0 MTBE 0 0 0 0 0 0 0 TA ME 0 0 0 0 0 0 0 Hy drogenP la nt

- To tal MS CF 799, 200 1, 004 1,066 985 1,058 -1 9 -7 Lu be Uni t 66 24 24 24 24 0 0 Su lfur P la nt 1, 434 4 5 4 5 0 0 Merox J et 0 0 0 0 0 0 0 Merox D ie sel 0 0 0 0 0 0 0 BT X Re fo rme r - Towe r fee d 18 16 18 16 18 0 0 BT X Re fo rme r - E xt ra ct

fe ed 34 34 34 34 34 0 0 To lu en e De al ky

at ion 0 0 0 0 0 0 0 Cu men e 0 0 0 0 0 0 0 Cy cl oh ex an e 0 0 0 0 0 0 0 2017 Re f c ase Control C ase Mi nus1 ON Control C ase Re la ti ve

to Re f C ase Act ua l Capacit y in2 009

### *** E.O. 12866 Review

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## 5

- 72 **Table 5**  **- 44**  **PADD 3 Unit Capacity and Throughput Volumes from LP Refinery Modeling (Thousand bbl/day)**  PADD 3 Refi ne ry Uni ts Su mme r Wi nte r Su mmer Wi nter Su mme r Wi nter Crud e To we r 8, 735 5, 576 5, 706 5, 589 5, 706 13 0 Va cu um To we r 3, 963 2, 587 2, 647 2, 593 2, 647 6 0 Sa ts Ga s Pl ant 0 534 522 541 523 8 0 Unsats Ga s Pl ant 0 839 728 839 730 0 3 FCC DeC5 To we r 0 0 0 0 0 0 0 FCC 2, 808 2, 808 2, 411 2, 808 2, 422 0 11 FCC Spl it

te r 0 1, 636 1, 207 1, 636 1, 218 0 11 Hy drocracker 523 1, 416 1, 416 1, 397 1, 397 -19 -19 H-Oi l Uni t 0 144 144 144 144 0 0 Del ay ed Coker 1, 350 625 648 628 649 2 2 Vis breaker 51 0 51 0 49 0 -2 The rma l Na phth a Spl itte r 0 74 79 74 79 0 0 CR U Re fo rme r 1, 765 524 410 613 454 89 44 SR U Re fo rme r 0 0 0 0 0 0 0 BT X Re fo rme r 0 381 383 385 383 4 0 C4 Is om erizat ion 50 133 133 133 133 0 0 C5/C6Isomeri za ti on 199 47 0 75 0 28 0 HF A lkyla ti on 295 235 148 235 148 0 0 H2S O4 A lkyl at ion 290 290 267 290 270 0 3 Dim ersol 19 0 0 0 0 0 0 Cat P ol y 23 0 0 0 0 0 0 Is ooctan e 0 0 0 0 0 0 0 DH T - To tal 2, 606 2, 080 2, 032 2, 086 2, 038 5 6 DH T 2 nd RC T - To ta l 0 1, 592 1, 565 1, 599 1, 570 6 6 DH T A rom S atura ti on 4 0 0 0 0 0 0 NHT - To ta l F d 2, 284 1, 177 1, 041 1, 206 1, 049 30 8 CG H - Ge ne ri c 905 173 18 196 26 23 8 CG H - Ole fi n Sat'n 905 0 0 0 0 0 0 FCCU F d HD T 1, 375 1, 559 1, 559 1, 559 1, 559 0 0 LSR S pl it te r 0 1 1 1 1 0 0 LSR B z S aturator 0 0 0 0 0 0 0 Reformate S aturator 0 10 1 10 1 0 0 Reformate S pl it

te r 0 30 3 30 3 0 0 SDA 32, 600 263 263 263 263 0 0 MT BE 28 0 0 0 0 0 0 TA ME 3 0 0 0 0 0 0 Hy drogenP la nt

- To ta l MS CF 1, 569, 400 5, 345 5, 487 5, 217 5, 414 -129 -73 Lu be Uni t 1, 169 506 506 506 506 0 0 Su lfur P la nt 1, 434 15 13 15 13 0 0 Me rox J et 0 0 0 0 0 0 0 Me rox D iesel 0 0 0 0 0 0 0 BT X Re fo rme r - To we r fe ed 146 146 146 146 146 0 0 BT X Re fo rme r - E xtra ct

fe ed 318 318 318 318 318 0 0 To lue ne D eal ky

at ion 0 0 0 0 0 0 0 Cu me ne 0 0 0 0 0 0 0 Cy cl oh ex an e 0 0 0 0 0 0 0 Actu al Capacit y in2 009 2017 Re f case Co ntrol C ase Mi nus 1 ON Co nt rol C ase Rela ti ve

to Re f C ase

### *** E.O. 12866 Review

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## 5

- 73 **Table 5**  **- 45**  **PADD 4 and PADD 5OC Unit Capacity and Throughput Volumes from LP Refinery Modeling (Thousand bbl/day)**  PADD 4 an d 5OC Refi ne ry Uni ts Su mme r Wi nte r Su mmer Wi nter Su mme r Wi nter Crud e To we r 1, 796 1, 518 1, 558 1, 518 1, 558 0 0 Va cu um To we r 599 559 541 559 541 0 0 Sa ts Ga s Pl ant 0 71 71 71 68 0 -3 Unsats Ga s Pl ant 0 66 70 66 70 0 0 FCC DeC5 To we r 0 0 0 0 0 0 0 FCC 344 224 224 224 224 0 0 FCC Spl it

te r 0 132 140 132 140 0 0 Hy drocracker 91 144 194 144 194 0 0 H-Oi l Uni t 0 0 0 0 0 0 0 Del ay ed Coker 143 133 133 133 133 0 0 Vis breaker 56 41 20 41 20 0 0 The rma l Na phth a Spl itte r 0 17 16 17 16 0 0 CR U Re fo rme r 0 0 0 0 0 0 0 SR U Re fo rme r 287 214 211 236 248 0 37 BT X Re fo rme r 0 0 0 0 0 0 0 C4 Is om erizat ion 19 19 19 19 19 0 0 C5/C6Isomeri za ti on 43 2 0 2 0 0 0 HF A lkyla ti on 37 19 36 19 36 0 0 H2S O4 A lkyl at ion 38 38 38 38 38 0 0 Dim ersol 1 1 0 1 0 0 0 Cat P ol y 10 0 0 0 0 0 0 Is ooctan e 0 0 0 0 0 0 0 DH T - To tal 404 492 483 492 483 0 0 DH T 2 nd RC T - To ta l 0 331 331 331 331 0 0 DH T A rom S atura ti on 0 0 0 0 0 0 0 NHT - To ta l F d 326 426 435 434 434 0 -1 CG H - Ge ne ri c 66 0 0 0 0 0 0 CG H - Ole fi n Sat'n 66 0 0 0 0 0 0 FCCU F d HD T 89 89 89 89 89 0 0 LSR S pl it te r 0 100 100 100 100 0 0 LSR B z S aturator 0 0 0 0 0 0 0 Reformate S aturator 0 10 4 1 1 0 -3 Reformate S pl it

te r 0 30 11 3 3 0 -8 SDA 32, 600 14 28 14 28 0 0 MT BE 0 0 0 0 0 0 0 TA ME 0 0 0 0 0 0 0 Hy drogenP la nt

- To ta l MS CF 373, 900 518 619 499 603 0 -16 Lu be Uni t 0 0 0 0 0 0 0 Su lfur P la nt 1, 434 2 2 2 2 0 0 Me rox J et 0 0 0 0 0 0 0 Me rox D iesel 0 0 0 0 0 0 0 BT X Re fo rme r - To we r fe ed 0 0 0 0 0 0 0 BT X Re fo rme r - E xtra ct

fe ed 0 0 0 0 0 0 0 To lue ne D eal ky

at ion 0 0 0 0 0 0 0 Cu me ne 0 0 0 0 0 0 0 Cy cl oh ex an e 0 0 0 0 0 0 0 2017 Re f case Co ntrol C ase Mi nus 1 ON Co nt rol C ase Rela ti ve

to Re f C ase Actu al Capacit y in2 009

### *** E.O. 12866 Review

**– Revised Version** 

**– Do Not Cite, Quote, or Release**  **During Review *****



## 5

- 74 **Table 5**  **- 46**  **U.S. (except CA) Unit Capacity and Throughput Volumes from LP Refinery**  **Modeling (Thousa nd bbl/day)**  PADDs 1 -4 a nd 5 OC Re fi ne ry Un its Su mme r Winte r Su mme r Winte r Su mme r Wi nte r Crud e To we r 15, 403 12, 071 13, 886 12, 084 13,897 13 11 Vacu um To wer 6, 505 5, 260 6, 007 5, 266 6,012 6 5 Sats Gas P la nt 0 882 885 890 886 9 1 Uns ats Ga s Pl ant 0 1, 317 1, 192 1, 317 1,196 0 3 FCC DeC5 To we r 0 0 0 0 0 0 0 FCC 4, 786 4, 373 3, 962 4, 373 3,976 0 13 FCC Spl it

te r 0 2, 267 1, 941 2, 288 1,954 20 12 Hyd ro cracker 869 1, 845 1, 895 1, 826 1,876 -2 0 -2 0 H-Oi l Uni t 0 144 144 144 144 0 0 Del ay ed Coker 1, 912 1, 190 1, 401 1, 193 1,403 2 2 Vis breaker 107 41 71 41 70 0 -2 The rmal Na phth a Spl it

ter 0 143 170 144 171 0 0 CR U Re fo rme r 2, 794 1, 321 1, 276 1, 437 1,333 115 57 SR U Re former 287 214 211 236 248 0 37 BT X Re fo rmer 0 452 473 452 473 1 0 C4 Is omeri za ti on 116 250 245 249 247 -1 2 C5/C6 Is omeri za ti on 406 343 275 380 299 37 25 HF A lkyl at ion 528 420 281 420 281 0 0 H2 SO4 Al kyla ti on 438 455 389 458 392 3 3 Dim er sol 23 1 0 1 0 0 0 Cat P oly 42 1 1 1 1 0 0 Is ooctan e 0 0 0 0 0 0 0 DH T - To ta l 4, 400 3, 562 3, 622 3, 567 3,628 5 6 DH T 2n d RC T - T

otal 0 2, 676 2, 885 2, 682 2,891 6 6 DH T AromS aturat io n 10 0 0 0 0 0 0 NHT - T otalFd 3, 921 2, 992 3, 056 3, 054 3,066 53 10 CG H - Ge ne ri c 1, 373 459 352 487 361 28 9 CG H - Ole fi n Sa t' n 1, 373 0 0 0 0 0 0 FCCUF d HD T 2, 029 3, 628 3, 628 3, 628 3,628 0 0 LSR S pl it te r 0 259 252 276 251 17 -1 LSR B z Saturator 0 0 0 0 0 0 0 Re fo rma te S aturator 0 22 7 13 4 0 -3 Re fo rma te S pl it

te r 0 66 20 39 12 0 -8 SDA 130, 400 310 359 310 359 0 0 MT BE 31 0 0 0 0 0 0 TA ME 3 0 0 0 0 0 0 Hyd ro genP la nt

- Tota l MS CF 2, 742, 564 7, 841 8, 178 7, 675 8,084 -1 47 -9 5 Lu be Uni t 1, 380 582 582 582 582 0 0 Su lfur P la nt 5, 736 22 22 22 22 0 0 Me ro x Jet 0 0 0 0 0 0 0 Me ro x Diesel 0 0 0 0 0 0 0 BT X Re fo rmer - Tower

fe ed 177 173 177 173 177 0 0 BT X Re fo rmer - E xtra ct

fe ed 375 375 375 375 375 0 0 To lue ne D eal ky

ati on 0 0 0 0 0 0 0 Cu me ne 0 0 0 0 0 0 0 Cy cl oh ex an e 0 0 0 0 0 0 0 2017 Re f case Contro l C ase Mi nus1 ON Co nt ro l C ase Re la ti ve

to Re f C ase Actu al Capacity in2 009

### *** E.O. 12866 Review

**– Revised Version** 

**– Do Not Cite, Quote, or Release**  **During Review *****



## 5

- 75 **Table 5**  **- 47**  **PADD 1 Gasoline Qualities Estimated by LP Refinery Modeling**

CG RFG Pool CG RFG Pool CG RFG Pool CG RFG Pool En ergy( MMBTU/ bbl) 4. 84 4. 96 4. 85 4. 87 4. 82 4. 85 4. 84 4. 95 4. 88 4. 87 4. 81 4. 85 De nsi ty ( lb/bbl) 254. 7 261. 9 255. 3 255. 7 258. 1 256. 7 255. 0 261. 7 257. 6 255. 7 258. 2 256. 7 Sul fu r ( ppm) 23. 6 22. 0 23. 5 22. 2 24. 9 23. 3 23. 4 21. 2 22. 6 22. 6 24. 9 23. 6 % at 200 45. 9 45. 5 45. 9 48. 7 52. 2 50. 2 45. 3 46. 2 45. 7 48. 4 52. 0 49. 9 % at 300 81. 8 75. 8 81. 2 81. 5 79. 1 80. 5 81. 0 76. 5 79. 2 80. 8 78. 6 79. 9 RV P ( psi ) 9. 11 7. 00 8. 92 12. 15 11. 93 12. 06 9. 11 7. 00 8. 28 12. 17 11. 94 12. 07 T10 ( F) 124 137 125 104 106 105 124 137 129 104 106 105 T50 ( F) 208 209 208 202 195 199 209 208 209 203 196 200 T90 ( F) 335 362 338 336 347 341 339 359 347 339 349 344 Dri vea bility 1145 1195 1150 1100 1092 1097 1152 1187 1166 1105 1095 1101 Va por Lock 137. 4 148. 8 138. 4 120. 1 120. 1 120. 1 137. 6 148. 6 141. 9 120. 1 120. 1 120. 1 Aromati cs ( vol %) 20. 8 22. 0 20. 9 21. 5 21. 2 21. 3 22. 1 22. 0 22. 0 22. 3 21. 7 22. 0 Be nze ne ( vol %) 0. 42 0. 42 0. 42 0. 50 0. 63 0. 55 0. 45 0. 51 0. 47 0. 51 0. 63 0. 56 Ol efins ( vol%) 9. 17 11. 48 9. 38 8. 61 8. 30 8. 48 9. 09 11. 35 9. 98 8. 74 8. 15 8. 50 Alc ohol ( vol%) 11. 2 13. 8 11. 4 11. 1 13. 7 12. 2 11. 2 13. 8 12. 2 11. 1 13. 7 12. 2 Ox yg en ( wt%) 4. 23 5. 06 4. 31 4. 19 5. 12 4. 57 4. 22 5. 07 4. 56 4. 19 5. 12 4. 57 Volumes ( kbbl/da y) 1, 693, 907 169, 974 1, 863, 881 345, 786 240, 886 586, 672 1, 709, 571 1, 118, 250 2, 827, 821 1, 623, 409 1, 130, 922 2, 754, 331 Gasol ine Qual it ies an d V olume 2017 Re f Case 2017 m inus 1 O N in FCC naphtha Summer Wi nte r Summe r Wi nter



## Table **5 -**  **48 PADD 2 Gasoline Qualities Estimated by LP Refinery Modeling** 

CG RFG Pool CG RFG Pool CG RFG Pool CG RFG Pool En ergy( MMBTU/ bbl) 4. 91 4. 97 4. 92 4. 89 4. 84 4. 88 4. 91 4. 97 4. 92 4. 88 4. 83 4. 88 De nsi ty ( lb/bbl) 259. 9 262. 4 260. 3 259. 1 258. 4 259. 1 260. 0 262. 1 260. 3 259. 3 258. 4 259. 2 Sul fu r ( ppm) 27. 4 20. 3 26. 3 25. 2 22. 7 25. 1 26. 5 18. 9 25. 3 25. 2 22. 4 25. 0 % at 200 56. 2 52. 4 55. 6 58. 0 59. 2 58. 1 56. 0 52. 4 55. 5 57. 9 59. 3 58. 0 % at 300 82. 9 80. 0 82. 4 81. 7 82. 9 81. 8 82. 8 80. 2 82. 4 81. 6 82. 9 81. 7 RV P ( psi ) 9. 03 7. 00 8. 72 11. 55 11. 47 11. 55 9. 03 7. 00 8. 72 11. 56 11. 47 11. 55 T10 ( F) 124 137 126 108 109 108 124 137 126 108 109 108 T50 ( F) 187 195 188 184 181 183 188 195 189 184 181 183 T90 ( F) 330 343 332 335 330 335 331 342 332 336 330 335 Dri vea bility 1077 1133 1086 1048 1036 1047 1079 1132 1088 1049 1036 1048 Va por Lock 134. 2 146. 4 136. 1 120. 1 120. 1 120. 1 134. 3 146. 4 136. 2 120. 1 120. 1 120. 1 Aromati cs ( vol %) 21. 2 21. 2 21. 2 22. 1 20. 1 21. 9 21. 8 21. 2 21. 7 22. 4 20. 0 22. 2 Be nze ne ( vol %) 0. 77 0. 88 0. 79 0. 49 0. 67 0. 50 0. 76 0. 88 0. 78 0. 50 0. 65 0. 51 Ol efins ( vol%) 8. 66 5. 44 8. 16 9. 10 8. 50 9. 06 8. 83 5. 08 8. 25 9. 14 8. 40 9. 08 Alc ohol ( vol%) 11. 2 13. 8 11. 6 11. 2 12. 0 11. 3 11. 2 13. 8 11. 6 11. 2 12. 0 11. 3 Ox yg en ( wt%) 4. 17 5. 06 4. 31 4. 18 4. 48 4. 20 4. 16 5. 07 4. 31 4. 18 4. 48 4. 20 Volumes ( kbbl/da y) 1, 799, 149 334, 626 2, 133, 775 1, 710, 734 139, 111 1, 849, 845 1, 799, 149 334, 626 2, 133, 775 1, 710, 734 139, 111 1, 849, 845 Gasol ine Qual it ies an d V olume 2017 Re f Case 2017 m inus 1 O N in FCC naphtha Summer Wi nte r Summe r Wi nter

### *** E.O. 12866 Review

**– Revised Version** 

**– Do Not Cite, Quote, or Release**  **During Review *****



## 5

- 76 **T able**  **5 -**  **49 PADD 3 Gasoline Qualities Estimated by LP Refinery Modeling** 

CG RFG Pool CG RFG Pool CG RFG Pool CG RFG Pool En ergy( MMBTU/ bbl) 5. 06 4. 90 5. 01 4. 99 4. 98 4. 98 5. 02 5. 00 5. 01 4. 99 4. 96 4. 98 De nsi ty ( lb/bbl) 259. 5 254. 7 258. 2 254. 8 255. 8 255. 1 258. 6 261. 2 259. 3 255. 0 255. 6 255. 2 Sul fu r ( ppm) 28. 0 27. 2 27. 8 28. 0 28. 0 28. 0 28. 0 27. 2 27. 8 28. 0 28. 0 28. 0 % at 200 59. 0 59. 4 59. 1 59. 6 61. 4 60. 1 59. 5 51. 8 57. 4 59. 3 62. 0 60. 0 % at 300 83. 6 88. 2 84. 9 85. 1 85. 3 85. 2 84. 0 80. 0 82. 9 84. 6 85. 4 84. 8 RV P ( psi ) 9. 07 7. 00 8. 49 11. 45 11. 33 11. 42 9. 07 7. 00 8. 49 11. 47 11. 29 11. 42 T10 ( F) 124 137 128 109 110 109 124 137 128 109 110 109 T50 ( F) 182 181 181 180 177 179 180 196 185 181 175 179 T90 ( F) 327 306 321 320 319 320 325 343 330 322 319 321 Dri vea bility 1057 1053 1056 1024 1013 1021 1052 1137 1075 1028 1009 1023 Va por Lock 133. 1 144. 0 136. 1 120. 1 120. 1 120. 1 132. 9 146. 6 136. 7 120. 1 120. 1 120. 1 Aromati cs ( vol %) 20. 8 6. 5 16. 9 15. 0 15. 2 15. 1 19. 8 18. 3 19. 4 15. 6 15. 3 15. 5 Be nze ne ( vol %) 0. 62 0. 61 0. 61 0. 58 0. 52 0. 56 0. 61 0. 61 0. 61 0. 58 0. 61 0. 58 Ol efins ( vol%) 13. 42 1. 72 10. 18 10. 82 10. 90 10. 84 13. 07 3. 17 10. 33 10. 90 10. 82 10. 88 Alc ohol ( vol%) 11. 2 13. 7 11. 9 11. 2 13. 7 11. 8 11. 2 13. 7 11. 9 11. 2 13. 7 11. 8 Ox yg en ( wt%) 4. 15 5. 20 4. 44 4. 23 5. 17 4. 47 4. 16 5. 07 4. 42 4. 22 5. 18 4. 47 Volumes ( kbbl/da y) 1, 276, 784 488, 041 1, 764, 825 1, 400, 642 497, 125 1, 897, 767 1, 276, 784 488, 041 1, 764, 825 1, 400, 642 497, 125 1, 897, 767 Gasol ine Qual it ies an d V olume 2017 Re f Case 2017 m inus 1 O N in FCC naphtha Summer Wi nte r Summe r Wi nter



## Table **5 -**  **50 PADD 4 and 5OC Gasoline Qualities Estimated by LP Refinery Modeling** 

CG RFG Pool CG RFG Pool CG RFG Pool CG RFG Pool En ergy( MMBTU/ bbl) 4. 96 0. 00 4. 96 4. 95 0. 00 4. 95 4. 96 0. 00 4. 96 4. 95 0. 00 4. 95 De nsi ty ( lb/bbl) 263. 3 0. 0 263. 3 261. 2 0. 0 261. 2 263. 5 0. 0 263. 5 261. 1 0. 0 261. 1 Sul fu r ( ppm) 25. 0 0. 0 25. 0 28. 0 0. 0 28. 0 24. 6 0. 0 24. 6 28. 0 0. 0 28. 0 % at 200 58. 5 0. 0 58. 5 58. 6 0. 0 58. 6 59. 0 0. 0 59. 0 57. 9 0. 0 57. 9 % at 300 85. 5 0. 0 85. 5 84. 7 0. 0 84. 7 85. 7 0. 0 85. 7 83. 0 0. 0 83. 0 RV P ( psi ) 9. 34 0. 00 9. 34 11. 52 0. 00 11. 52 9. 34 0. 00 9. 34 11. 55 0. 00 11. 55 T10 ( F) 122 0 122 108 0 108 122 0 122 108 0 108 T50 ( F) 182 0 182 182 0 182 181 0 181 184 0 184 T90 ( F) 318 0 318 322 0 322 317 0 317 329 0 329 Dri vea bility 1048 0 1048 1031 0 1031 1045 0 1045 1042 0 1042 Va por Lock 131. 8 0. 0 131. 8 120. 0 0. 0 120. 0 131. 6 0. 0 131. 6 120. 1 0. 0 120. 1 Aromati cs ( vol %) 24. 4 0. 0 24. 4 23. 8 0. 0 23. 8 24. 5 0. 0 24. 5 23. 4 0. 0 23. 4 Be nze ne ( vol %) 0. 84 0. 00 0. 84 1. 09 0. 00 1. 09 0. 86 0. 00 0. 86 1. 10 0. 00 1. 10 Ol efins ( vol%) 5. 70 0. 00 5. 70 5. 47 0. 00 5. 47 5. 72 0. 00 5. 72 4. 98 0. 00 4. 98 Alc ohol ( vol%) 11. 3 0. 0 11. 3 11. 1 0. 0 11. 1 11. 3 0. 0 11. 3 11. 3 0. 0 11. 3 Ox yg en ( wt%) 4. 15 0. 00 4. 15 4. 08 0. 00 4. 08 4. 14 0. 00 4. 14 4. 18 0. 00 4. 18 Volumes ( kbbl/da y) 701, 850 0 701, 850 734, 023 0 734, 023 701, 850 0 701, 850 744, 898 0 744, 898 Gasol ine Qual it ies an d V olume 2017 Re f Case 2017 m inus 1 O N in FCC naphtha Summer Wi nte r Summe r Wi nter

### *** E.O. 12866 Review

**– Revised Version** 

**– Do Not Cite, Quote, or Release**  **During Review *****



## 5

- 77 **Table 5**  **- 51**  **U.S. (except CA)**  **Gasoline Qualities Estimated by Refinery Modeling**

CG RFG Pool CG RFG Pool CG RFG Pool CG RFG Pool En ergy( MMBTU/ bbl) 4. 93 4. 93 4. 93 4. 93 4. 91 4. 93 4. 92 4. 96 4. 93 4. 91 4. 85 4. 90 De nsi ty ( lb/bbl) 258. 6 258. 5 258. 6 257. 8 256. 9 257. 6 258. 6 261. 7 259. 4 257. 4 257. 5 257. 4 Sul fu r ( ppm) 26. 1 24. 0 25. 8 26. 4 26. 3 26. 4 25. 7 22. 3 24. 8 25. 5 25. 6 25. 5 % at 200 54. 0 54. 7 54. 1 57. 9 58. 5 58. 0 53. 9 48. 7 52. 5 55. 4 55. 4 55. 4 % at 300 83. 1 83. 3 83. 1 83. 3 83. 2 83. 3 82. 9 78. 0 81. 6 82. 3 80. 8 82. 0 RV P ( psi ) 9. 10 7. 00 8. 78 11. 56 11. 52 11. 55 9. 10 7. 00 8. 55 11. 71 11. 72 11. 72 T10 ( F) 124 137 126 108 108 108 124 137 127 107 107 107 T50 ( F) 192 190 191 184 182 184 192 202 195 189 189 189 T90 ( F) 329 328 329 328 328 328 330 352 336 333 339 334 Dri vea bility 1090 1104 1092 1041 1038 1041 1091 1165 1111 1059 1066 1061 Va por Lock 134. 6 145. 7 136. 3 120. 1 120. 1 120. 1 134. 6 147. 7 138. 1 120. 1 120. 1 120. 1 Aromati cs ( vol %) 21. 4 14. 1 20. 3 20. 0 17. 6 19. 6 21. 8 20. 9 21. 5 20. 8 19. 8 20. 5 Be nze ne ( vol %) 0. 63 0. 67 0. 64 0. 63 0. 57 0. 62 0. 64 0. 60 0. 63 0. 60 0. 62 0. 61 Ol efins ( vol%) 9. 55 4. 65 8. 80 9. 00 9. 81 9. 14 9. 50 8. 21 9. 16 8. 91 8. 92 8. 91 Alc ohol ( vol%) 11. 2 13. 8 11. 6 11. 2 13. 4 11. 6 11. 2 13. 8 11. 9 11. 2 13. 6 11. 8 Ox yg en ( wt%) 4. 18 5. 13 4. 33 4. 18 5. 05 4. 33 4. 18 5. 07 4. 41 4. 19 5. 08 4. 41 Volumes ( kbbl/da y) 5, 471, 690 992, 641 6, 464, 331 4, 191, 185 877, 122 5, 068, 307 5, 487, 354 1, 940, 917 7, 428, 271 5, 479, 683 1, 767, 158 7, 246, 841 Gasol ine Qual it ies an d V olume 2017 Re f Case 2017 m inus 1 O N in FCC naphtha Summer Wi nte r Summe r Wi nter

### *** E.O. 12866 Review

**– Revised Version** 

**– Do Not Cite, Quote, or Release**  **During Review *****



## 5

- 78 **Table 5**  **- 52**  **PADD 1 Unit Capacity and Throughput Volumes from LP Refinery Modeling (Thousand**  **bbl/day)**
PADD 1 Re fi ne ry Uni ts Su mmer Winte r Su mmer Wi nte r Su mmer Winte r Su mmer Winte r Su mmer Winter Crud e Towe r 1, 260 1, 156 1, 716 757 1, 267 -400 -449 757 1, 267 -400 -4 49 Vacu umTo we r 492 507 738 332 550 -175 -187 332 550 -175 -1 87 Sats Ga s Pl ant 0 104 62 70 50 -34 -1 2 72 47 -32 -15 Unsa ts Gas P la nt 0 185 226 156 191 -29 -3 6 156 191 -29 -36 FCC DeC5 To wer 0 0 0 0 0 0 0 0 0 0 0 FCC 490 678 827 565 691 -113 -136 565 691 -113 -1 36 FCC Spl itte r 0 387 467 324 391 -63 -7 6 324 391 -63 -76 Hyd rocracker 22 52 82 52 82 0 0 52 82 0 0 H-Oi l Uni t 0 0 0 0 0 0 0 0 0 0 0 Del ay ed Coker 44 22 94 22 82 0 -1 2 22 82 0 -12 Visbr eaker 0 0 0 0 0 0 0 0 0 0 0 The rmal Naphtha S pl it

te r 0 3 11 3 10 0 -1 3 10 0 -1 CR U Re fo rmer 223 138 223 90 154 -48 -7 0 134 154 -3 -70 SR U Re fo rmer 0 0 0 0 0 0 0 0 0 0 0 BT X Re fo rmer 0 36 36 36 36 0 0 36 36 0 0 C4 Is omeriz

ation 32 53 0 32 0 -21 0 32 0 -21 0 C5/C6 Is omeriz

ation 7 51 95 32 32 -19 -6 3 17 8 -34 -87 HF A lkyla ti on 40 40 20 40 20 0 0 40 20 0 0 H2 SO4 Al ky

la ti on 29 125 68 94 20 -31 -4 8 77 20 -48 -48 Dim ersol 0 0 0 0 0 0 0 0 0 0 0 Cat P oly 5 1 31 1 32 0 1 8 32 7 1 Is ooctan e 0 0 0 0 0 0 0 0 0 0 0 DH T - Total 334 431 742 300 572 -130 -170 310 572 -121 -1 70 DH T 2 nd RC T - To ta l 0 0 0 0 0 0 0 0 0 0 0 DH T A ro m S atu rati on 0 0 0 0 0 0 0 0 0 0 0 NHT - To ta l F d 274 263 397 165 286 -98 -111 152 286 -111 -1 11 CG H - Gen eric 119 161 158 159 158 -2 0 158 158 -3 0 CG H - Ole fi n S at'n 119 0 0 0 0 0 0 0 0 0 0 FCCU F d HD T 44 460 460 396 396 -63 -6 3 396 396 -63 -63 LSR S pl it te r 0 1 51 1 24 0 -2 7 1 40 0 -11 LSR B z S atura to r 0 0 0 0 0 0 0 0 0 0 0 Re fo rmate Satu rator 0 21 1 19 1 -2 0 10 1 -11 0 Re fo rmate Spl it

te r 0 63 3 57 3 -6 0 30 3 -33 0 SDA 0 33 33 33 33 0 0 33 33 0 0 MTB E 3 0 0 0 0 0 0 0 0 0 0 TA ME 0 0 0 0 0 0 0 0 0 0 0 Hyd rogenP la nt - To ta l MS CF 63, 700 645 935 538 788 -107 -147 518 795 -127 -1 40 Lu be Uni t 146 53 53 53 53 0 0 53 53 0 0 Su lfur P la nt 1, 434 1 1 1 1 0 0 1 1 0 0 Merox Jet 0 0 0 0 0 0 0 0 0 0 0 Merox D iesel 0 0 0 0 0 0 0 0 0 0 0 BT X Re fo rmer - T

ower feed 13 13 13 13 13 0 0 13 13 0 0 BT X Re fo rmer - E xtract feed 23 23 23 23 23 0 0 23 23 0 0 To lue ne D eal ky

atio n 0 0 0 0 0 0 0 0 0 0 0 Cu men e 0 0 0 0 0 0 0 0 0 0 0 Cy clohex an e 0 0 0 0 0 0 0 0 0 0 0 Re fe rence 2005 in 2030 100% E10 C ase in 2030 E10 Case Re la ti ve to

Re f C ase 100% E15 Case in 2030 E15 Case Relati ve to

Re f C ase Actua l Capacity in2 009

### *** E.O. 12866 Review

**– Revised Version** 

**– Do Not Cite, Quote, or Release**  **During Review *****



## 5

- 79 **Table 5**  **- 53**  **PADD 2 Unit Capacity and Throughput Volumes from LP Refinery Modeling (Thousand bbl/day)** 
PADD 2 Re fi ne ry Uni ts Su mmer Winte r Su mmer Wi nte r Su mmer Winte r Su mmer Winte r Su mmer Winter Crud e Towe r 3, 612 2, 638 4, 141 2, 494 3, 972 -145 -169 2, 206 3, 830 -432 -3 11 Vacu umTo we r 1, 452 1, 092 1, 770 1, 026 1, 711 -66 -5 8 905 1, 656 -186 -1 14 Sats Ga s Pl ant 0 162 137 136 144 -26 7 107 120 -55 -18 Unsa ts Gas P la nt 0 248 332 204 319 -44 -1 3 166 302 -82 -31 FCC DeC5 To wer 0 0 0 0 0 0 0 0 0 0 0 FCC 1, 144 864 1, 144 666 1, 080 -197 -6 4 569 1, 031 -295 -1 13 FCC Spl itte r 0 503 653 6 628 -496 -2 4 0 595 -503 -58 Hyd rocracker 234 234 234 234 234 0 0 234 234 0 0 H-Oi l Uni t 0 0 0 0 0 0 0 0 0 0 0 Del ay ed Coker 375 153 395 129 375 -24 -2 1 86 355 -67 -40 Visbr eaker 0 0 0 0 0 0 0 0 0 0 0 The rmal Naphtha S pl it

te r 0 19 48 16 45 -3 -3 10 43 -8 -5 CR U Re fo rmer 807 393 613 376 515 -18 -9 8 329 496 -64 -1 16 SR U Re fo rmer 0 0 0 0 0 0 0 0 0 0 0 BT X Re fo rmer 0 42 54 42 54 0 0 42 54 0 0 C4 Is omeriz

ation 15 50 0 27 27 -23 27 10 15 -40 14 C5/C6 Is omeriz

ation 157 157 300 157 129 0 -171 100 0 -57 -3 00 HF A lkyla ti on 156 121 78 78 92 -44 14 78 78 -44 0 H2 SO4 Al ky

la ti on 81 81 71 79 81 -2 10 40 65 -40 -6 Dim ersol 3 0 0 0 0 0 0 0 0 0 0 Cat P oly 4 0 29 0 3 0 -2 6 0 8 0 -21 Is ooctan e 0 0 0 0 0 0 0 0 0 0 0 DH T - Total 1, 056 827 644 874 610 47 -3 4 762 581 -66 -63 DH T 2 nd RC T - To ta l 0 0 0 0 0 0 0 0 0 0 0 DH T A ro m S atu rati on 6 0 0 0 0 0 0 0 0 0 0 NHT - To ta l F d 1, 038 621 1, 007 597 966 -24 -4 1 495 924 -125 -83 CG H - Gen eric 282 242 233 1 183 -241 -4 9 0 179 -242 -54 CG H - Ole fi n S at'n 282 0 0 0 0 0 0 0 0 0 0 FCCU F d HD T 521 521 521 650 650 129 129 521 521 0 0 LSR S pl it te r 0 100 100 93 100 -7 0 77 71 -23 -29 LSR B z S atura to r 0 0 0 0 0 0 0 0 0 0 0 Re fo rmate Satu rator 0 2 10 1 1 -1 -9 1 1 -1 -9 Re fo rmate Spl it

te r 0 5 30 3 3 -2 -2 7 3 3 -2 -27 SDA 0 36 36 36 36 0 0 36 36 0 0 MTB E 0 0 0 0 0 0 0 0 0 0 0 TA ME 0 0 0 0 0 0 0 0 0 0 0 Hyd rogenP la nt - To ta l MS CF 799, 200 1, 149 1, 149 1, 197 1, 224 48 75 1, 086 1, 086 -63 -63 Lu be Uni t 66 24 24 24 24 0 0 24 24 0 0 Su lfur P la nt 1, 434 4 5 4 5 0 0 3 5 -1 0 Merox Jet 0 0 0 0 0 0 0 0 0 0 0 Merox D iesel 0 0 0 0 0 0 0 0 0 0 0 BT X Re fo rmer - T

ower feed 18 16 18 16 18 0 0 16 18 0 0 BT X Re fo rmer - E xtract feed 34 34 34 34 34 0 0 34 34 0 0 To lue ne D eal ky

atio n 0 0 0 0 0 0 0 0 0 0 0 Cu men e 0 0 0 0 0 0 0 0 0 0 0 Cy clohex an e 0 0 0 0 0 0 0 0 0 0 0 Re fe rence 2005 in 2030 100% E10 C ase in 2030 E10 Case Re la ti ve to

Re f C ase 100% E15 Case in 2030 E15 Case Relati ve to

Re f C ase Actua l Capacity in2 009

### *** E.O. 12866 Review

**– Revised Version** 

**– Do Not Cite, Quote, or Release**  **During Review *****



## 5

- 80 **Table 5**  **- 54**  **PADD 3 Unit Capacity and Throughput V olumes from LP Refinery Modeling**  **(Thousand bbl/day)**
PADD 3 Re fi ne ry Uni ts Su mmer Winte r Su mmer Wi nte r Su mmer Winte r Su mmer Winte r Su mmer Winter Crud e Towe r 8, 735 7, 741 7, 111 7, 477 7, 036 -264 -7 5 7, 203 6, 648 -538 -4 64 Vacu umTo we r 3, 963 3, 514 3, 210 3, 381 3, 264 -133 54 3, 275 3, 022 -239 -1 88 Sats Ga s Pl ant 0 635 427 624 471 -11 44 612 423 -23 -4 Unsa ts Gas P la nt 0 679 675 690 612 10 -6 3 607 571 -73 -1 04 FCC DeC5 To wer 0 0 0 0 0 0 0 0 0 0 0 FCC 2, 808 2, 075 2, 154 2, 103 1, 901 28 -252 1, 820 1, 794 -255 -3 60 FCC Spl itte r 0 6 1, 153 161 435 155 -719 0 848 -6 -3 05 Hyd rocracker 667 1, 797 1, 797 2, 020 2, 020 223 223 1, 937 1, 937 140 140 H-Oi l Uni t 0 0 0 0 0 0 0 0 0 0 0 Del ay ed Coker 1, 350 992 853 933 881 -59 28 886 769 -106 -85 Visbr eaker 51 0 0 0 0 0 0 0 0 0 0 The rmal Naphtha S pl it

te r 0 120 103 113 107 -7 3 107 93 -13 -10 CR U Re fo rmer 1, 765 1, 517 1, 140 1, 130 904 -387 -236 1, 149 863 -368 -2 77 SR U Re fo rmer 0 0 0 0 0 0 0 0 0 0 0 BT X Re fo rmer 0 265 261 261 261 -4 0 261 261 -4 1 C4 Is omeriz

ation 50 50 0 50 0 0 0 50 0 0 0 C5/C6 Is omeriz

ation 199 130 58 229 50 99 -7 134 0 4 -58 HF A lkyla ti on 295 148 148 148 148 0 0 148 148 0 0 H2 SO4 Al ky

la ti on 290 234 235 252 197 18 -3 8 197 179 -37 -56 Dim ersol 19 0 0 0 0 0 0 0 0 0 0 Cat P oly 23 0 0 0 0 0 0 0 0 0 0 Is ooctan e 0 0 0 0 0 0 0 0 0 0 0 DH T - Total 2, 606 2, 159 1, 867 1, 726 1, 689 -434 -178 1, 872 1, 675 -288 -1 92 DH T 2 nd RC T - To ta l 0 0 0 0 0 0 0 0 0 0 0 DH T A ro m S atu rati on 4 0 0 0 0 0 0 0 0 0 0 NHT - To ta l F d 2, 284 1, 648 1, 198 1, 474 1, 076 -174 -122 1, 828 1, 300 180 102 CG H - Gen eric 905 1 1 26 1 25 0 1 1 0 0 CG H - Ole fi n S at'n 905 0 0 0 0 0 0 0 0 0 0 FCCU F d HD T 1, 375 1, 844 1, 844 1, 850 1, 630 6 -213 1, 562 1, 559 -282 -2 85 LSR S pl it te r 0 1 1 100 1 99 0 1 1 0 0 LSR B z S atura to r 0 0 0 0 0 0 0 0 0 0 0 Re fo rmate Satu rator 0 327 76 91 10 -236 -6 5 330 272 3 196 Re fo rmate Spl it

te r 0 980 227 273 31 -707 -196 989 815 9 588 SDA 0 263 263 263 263 0 0 263 263 0 0 MTB E 28 0 0 0 0 0 0 0 0 0 0 TA ME 3 0 0 0 0 0 0 0 0 0 0 Hyd rogenP la nt - To ta l MS CF 1, 569, 400 5, 529 5, 529 5, 931 5, 931 402 402 5, 670 5, 670 141 141 Lu be Uni t 1, 169 440 440 440 440 0 0 440 440 0 0 Su lfur P la nt 1, 434 15 13 14 14 -1 1 13 12 -1 0 Merox Jet 0 0 0 0 0 0 0 0 0 0 0 Merox D iesel 0 0 0 0 0 0 0 0 0 0 0 BT X Re fo rmer - T

ower feed 0 96 94 94 94 -2 0 94 94 -2 0 BT X Re fo rmer - E xtract feed 0 211 208 208 208 -3 0 208 208 -3 0 To lue ne D eal ky

atio n 0 0 0 0 0 0 0 0 0 0 0 Cu men e 0 0 0 0 0 0 0 0 0 0 0 Cy clohex an e 0 0 0 0 0 0 0 0 0 0 0 Re fe rence 2005 in 2030 100% E10 C ase in 2030 E10 Case Re la ti ve to

Re f C ase 100% E15 Case in 2030 E15 Case Relati ve to

Re f C ase Actua l Capacity in2 009

### *** E.O. 12866 Review

**– Revised Version** 

**– Do Not Cite, Quote, or Release**  **During Review *****



## 5

- 81 **Table 5**  **- 55**  **PADD 4 and 5OC Unit Capacity and Throughput Volumes from LP Refinery Modeling (Thousand bbl/day)** 
PADD 4 an d 5O C Re fi ne ry Uni ts Su mmer Winte r Su mmer Wi nte r Su mmer Winte r Su mmer Winte r Su mmer Winter Crud e Towe r 1, 796 1, 513 1, 547 1, 418 1, 442 -95 -104 1, 400 1, 400 -113 -1 46 Vacu umTo we r 599 655 632 607 578 -48 -5 5 588 560 -67 -73 Sats Ga s Pl ant 0 92 57 82 53 -10 -4 75 39 -17 -18 Unsa ts Gas P la nt 0 113 115 104 105 -9 -1 0 101 100 -12 -14 FCC DeC5 To wer 0 0 0 0 0 0 0 0 0 0 0 FCC 344 392 382 360 345 -32 -3 7 344 331 -47 -51 FCC Spl itte r 0 218 222 202 204 -15 -1 8 182 196 -35 -26 Hyd rocracker 91 141 191 141 191 0 0 141 191 0 0 H-Oi l Uni t 0 0 0 0 0 0 0 0 0 0 0 Del ay ed Coker 143 162 162 137 137 -25 -2 5 133 129 -29 -33 Visbr eaker 56 0 0 7 3 7 3 26 8 26 8 The rmal Naphtha S pl it

te r 0 19 19 16 16 -3 -3 17 15 -2 -3 CR U Re fo rmer 0 0 0 0 0 0 0 0 0 0 0 SR U Re fo rmer 287 129 201 95 73 -33 -128 69 27 -60 -1 74 BT X Re fo rmer 0 0 0 0 0 0 0 0 0 0 0 C4 Is omeriz

ation 19 45 0 40 8 -5 8 40 6 -5 5 C5/C6 Is omeriz

ation 43 78 2 0 0 -78 -2 3 0 -75 -2 HF A lkyla ti on 37 37 37 37 37 0 0 37 37 0 0 H2 SO4 Al ky

la ti on 38 74 74 64 64 -10 -1 0 60 60 -14 -14 Dim ersol 1 0 1 1 1 0 0 1 1 1 0 Cat P oly 10 0 0 0 0 0 0 0 0 0 0 Is ooctan e 0 0 0 0 0 0 0 0 0 0 0 DH T - Total 404 575 578 528 527 -48 -5 1 518 507 -57 -71 DH T 2 nd RC T - To ta l 0 0 0 0 0 0 0 0 0 0 0 DH T A ro m S atu rati on 0 0 0 0 0 0 0 0 0 0 0 NHT - To ta l F d 326 313 349 292 297 -21 -5 3 288 287 -25 -62 CG H - Gen eric 66 78 74 66 60 -11 -1 4 65 60 -12 -14 CG H - Ole fi n S at'n 66 0 0 0 0 0 0 0 0 0 0 FCCU F d HD T 89 139 189 139 189 0 0 139 177 0 -12 LSR S pl it te r 0 100 100 89 88 -11 -1 2 85 100 -15 0 LSR B z S atura to r 0 0 0 0 0 0 0 0 0 0 0 Re fo rmate Satu rator 0 2 10 1 1 -1 -9 1 1 -1 -9 Re fo rmate Spl it

te r 0 5 30 3 3 -2 -2 7 3 3 -2 -27 SDA 0 28 28 28 28 0 0 28 28 0 0 MTB E 0 0 0 0 0 0 0 0 0 0 0 TA ME 0 0 0 0 0 0 0 0 0 0 0 Hyd rogenP la nt - To ta l MS CF 373, 900 705 785 679 826 -26 40 688 809 -18 23 Lu be Uni t 0 0 0 0 0 0 0 0 0 0 0 Su lfur P la nt 1, 434 2 2 2 2 0 0 2 2 0 0 Merox Jet 0 0 0 0 0 0 0 0 0 0 0 Merox D iesel 0 0 0 0 0 0 0 0 0 0 0 BT X Re fo rmer - T

ower feed 0 0 0 0 0 0 0 0 0 0 0 BT X Re fo rmer - E xtract feed 0 0 0 0 0 0 0 0 0 0 0 To lue ne D eal ky

atio n 0 0 0 0 0 0 0 0 0 0 0 Cu men e 0 0 0 0 0 0 0 0 0 0 0 Cy clohex an e 0 0 0 0 0 0 0 0 0 0 0 Re fe rence 2005 in 2030 100% E10 C ase in 2030 E10 Case Re la ti ve to

Re f C ase 100% E15 Case in 2030 E15 Case Relati ve to

Re f C ase Actua l Capacity in2 009

### *** E.O. 12866 Review

**– Revised Version** 

**– Do Not Cite, Quote, or Release**  **During Review *****



## 5

- 82 **Table 5**  **- 56**  **U.S. (except CA) Unit Capacity and Throughput Volumes from LP Refinery**  **Modeling (Thousand bbl/day)**
PADDs 1 -4 and 5OC Re fi ne ry Uni t Su mmer Winte r Su mmer Wi nte r Su mmer Winte r Su mmer Winte r Su mmer Winter Crud e Towe r 15, 403 13,049 14, 515 12, 146 13, 717 -903 -798 11, 567 13, 145 -1,482 -1,370 Vacu umTo we r 6, 505 5, 768 6, 350 5, 346 6, 104 -422 -246 5, 100 5, 788 -668 -5 62 Sats Ga s Pl ant 0 993 683 912 718 -81 35 865 629 -128 -54 Unsa ts Gas P la nt 0 1, 225 1, 348 1, 153 1, 227 -72 -122 1, 030 1, 163 -195 -1 85 FCC DeC5 To wer 0 0 0 0 0 0 0 0 0 0 0 FCC 4, 786 4, 008 4, 506 3, 694 4, 018 -314 -489 3, 298 3, 846 -710 -6 60 FCC Spl itte r 0 1, 114 2, 494 694 1, 658 -420 -837 506 2, 030 -608 -4 64 Hyd rocracker 1, 013 2, 223 2, 303 2, 446 2, 526 223 223 2, 363 2, 443 140 140 H-Oi l Uni t 0 0 0 0 0 0 0 0 0 0 0 Del ay ed Coker 1, 912 1, 329 1, 505 1, 222 1, 475 -108 -3 0 1, 127 1, 334 -202 -1 71 Visbr eaker 107 0 0 7 3 7 3 26 8 26 8 The rmal Naphtha S pl it

te r 0 159 181 147 178 -12 -3 137 161 -23 -20 CR U Re fo rmer 2, 794 2, 048 1, 976 1, 596 1, 572 -453 -404 1, 613 1, 513 -436 -4 63 SR U Re fo rmer 287 129 201 95 73 -33 -128 69 27 -60 -1 74 BT X Re fo rmer 0 344 351 340 351 -4 0 340 351 -4 1 C4 Is omeriz

ation 116 199 0 149 35 -49 34 132 20 -67 20 C5/C6 Is omeriz

ation 406 415 455 418 212 2 -244 253 8 -162 -4 47 HF A lkyla ti on 528 346 283 302 297 -44 14 302 282 -44 0 H2 SO4 Al ky

la ti on 438 513 448 488 363 -25 -8 5 374 324 -139 -1 24 Dim ersol 23 0 1 1 1 0 0 1 1 1 0 Cat P oly 42 1 60 1 35 0 -2 5 8 40 7 -20 Is ooctan e 0 0 0 0 0 0 0 0 0 0 0 DH T - Total 4, 400 3, 993 3, 831 3, 428 3, 398 -565 -432 3, 462 3, 336 -531 -4 95 DH T 2 nd RC T - To ta l 0 0 0 0 0 0 0 0 0 0 0 DH T A ro m S atu rati on 10 0 0 0 0 0 0 0 0 0 0 NHT - To ta l F d 3, 921 2, 844 2, 952 2, 527 2, 625 -317 -327 2, 763 2, 797 -81 -1 55 CG H - Gen eric 1, 373 481 466 252 402 -229 -6 4 225 398 -257 -68 CG H - Ole fi n S at'n 1, 373 0 0 0 0 0 0 0 0 0 0 FCCU F d HD T 2, 029 2, 964 3, 014 3, 035 2, 866 71 -148 2, 619 2, 653 -345 -3 60 LSR S pl it te r 0 202 252 283 213 81 -3 9 164 212 -38 -40 LSR B z S atura to r 0 0 0 0 0 0 0 0 0 0 0 Re fo rmate Satu rator 0 351 97 112 13 -239 -8 3 342 275 -10 178 Re fo rmate Spl it

te r 0 1, 054 290 337 40 -717 -250 1, 025 824 -29 534 SDA 0 359 359 359 359 0 0 359 359 0 0 MTB E 31 0 0 0 0 0 0 0 0 0 0 TA ME 3 0 0 0 0 0 0 0 0 0 0 Hyd rogenP la nt - To ta l MS CF 1, 238, 369 8, 029 8, 399 8, 346 8, 769 317 370 7, 962 8, 360 -67 -38 Lu be Uni t 1, 380 516 516 516 516 0 0 516 516 0 0 Su lfur P la nt 5, 736 21 21 20 22 -1 0 19 20 -2 -1 Merox Jet 0 0 0 0 0 0 0 0 0 0 0 Merox D iesel 0 0 0 0 0 0 0 0 0 0 0 BT X Re fo rmer - T

ower feed 127 124 125 123 125 -2 0 123 125 -2 0 BT X Re fo rmer - E xtract feed 268 268 265 265 265 -3 0 265 265 -3 0 To lue ne D eal ky

atio n 0 0 0 0 0 0 0 0 0 0 0 Cu men e 0 0 0 0 0 0 0 0 0 0 0 Cy clohex an e 0 0 0 0 0 0 0 0 0 0 0 100% E15 Case in 2030 E10 Case Re la ti ve to Re f C ase 100% E10 C ase in 2030 Re fe rence 2005 in 2030 E15 Case Relati ve to Re f C ase Actua l Capacity in2 009

### *** E.O. 12866 Review

**– Revised Version** 

**– Do Not Cite, Quote, or Release**  **During Review *****



## 5

- 83 **Table 5**  **- 57**  **PADD 1 Gasoline Qualities for the E10 and E15 Cases relative to the Reference Case** 

CG RFG Pool CG RFG Pool CG RFG Pool CG RFG Pool CG RFG Pool CG RFG Pool Ene rgy ( MMB TU/ bbl) 5.18 5. 09 5. 14 5. 11 4. 93 5. 02 5. 05 5. 04 5. 04 5. 02 4. 91 4. 98 4. 93 4. 93 4. 93 4. 87 4. 82 4. 85 De nsi ty ( lb /bbl) 257. 70 259. 91 258. 80 255. 81 252. 05 253. 91 257. 59 260. 94 258. 89 255. 60 255. 72 255. 65 259. 60 260. 61 260. 01 257. 91 255. 72 257. 01 Sulfur (ppm) 27. 5 23. 3 25. 4 22. 4 16. 9 19. 6 23. 7 23. 6 23. 7 20. 9 18. 0 19. 8 28. 0 28. 0 28. 0 12. 6 17. 6 14. 7 % at 200 45. 8 50. 8 48. 3 44. 6 62. 4 53. 6 54. 8 51. 1 53. 3 53. 3 59. 4 55. 7 59. 8 58. 7 59. 4 60. 9 66. 7 63. 3 % at 300 76. 6 81. 4 79. 0 75. 8 89. 2 82. 6 81. 6 81. 2 81. 4 78. 1 84. 6 80. 7 81. 5 84. 1 82. 6 83. 0 89. 8 85. 8 RVP (psi) 7.92 6. 54 7. 23 12. 61 13. 19 12. 90 9. 27 7. 00 8. 39 13. 78 13. 39 13. 62 8. 27 7. 00 7. 75 13. 29 12. 92 13. 14 T1 0 ( F) 131. 2 140. 0 135. 6 101. 4 97. 7 99. 6 122. 6 137. 1 128. 2 94. 0 96. 5 95. 0 129. 0 137. 1 132. 3 97. 1 99. 5 98. 1 T5 0 ( F) 208. 5 198. 2 203. 3 210. 9 174. 5 192. 5 190. 1 197. 5 193. 0 193. 0 180. 5 188. 1 179. 8 182. 1 180. 7 177. 5 165. 7 172. 7 T9 0 ( F) 358. 5 336. 6 347. 6 362. 1 301. 3 331. 4 336. 0 337. 6 336. 7 351. 6 322. 1 340. 0 336. 3 324. 3 331. 4 329. 5 298. 3 316. 7 Dri ve abi lit y 1180. 7 1141. 2 1161. 0 1147. 0 971. 4 1058. 2 1090. 3 1135. 7 1107. 9 1071. 7 1008. 4 1046. 8 1069. 1 1076. 0 1072. 0 1007. 7 944. 7 981. 9 Va por Lock 143. 8 149. 5 146. 6 119. 1 109. 7 114. 3 133. 4 146. 9 138. 7 109. 7 109. 7 109. 7 137. 1 144. 3 140. 0 109. 7 109. 7 109. 7 Ar omatics (vol%) 27. 9 20. 2 24. 1 27. 0 14. 8 20. 8 22. 0 20. 0 21. 2 20. 3 18. 5 19. 6 18. 5 17. 6 18. 1 18. 8 14. 0 16. 8 Benzene ( vol %) 0.58 0. 57 0. 58 0. 61 0. 56 0. 59 0. 51 0. 57 0. 53 0. 52 0. 58 0. 54 0. 73 0. 89 0. 79 0. 46 0. 55 0. 50 Olefins( vol%) 11. 0 10. 4 10. 7 10. 6 16. 8 13. 8 9. 1 10. 9 9. 8 10. 2 16. 0 12. 5 8. 5 9. 8 9. 0 7. 9 17. 9 12. 0 Alc ohol ( vol%) 0.50 4. 89 2. 68 0. 00 4. 94 2. 50 10. 00 10. 00 10. 00 10. 00 10. 00 10. 00 15. 00 15. 00 15. 00 15. 00 15. 00 15. 00 Oxyge n ( wt%) 0.74 2. 56 1. 65 0. 15 2. 50 1. 34 3. 74 3. 69 3. 72 3. 77 3. 77 3. 77 5. 57 5. 55 5. 56 5. 61 5. 65 5. 63 Vo lu mes ( kbbl /day) 1, 399, 252 1, 387, 051 2, 786, 303 1, 338, 953 1, 368, 062 2, 707, 015 1, 760, 831 1, 121, 463 2, 882, 294 1, 698, 176 1, 106, 878 2, 805, 054 1, 736, 796 1, 204, 323 2, 941, 119 1, 619, 601 1, 125, 767 2, 745, 368 Gasol ine Qual ities and Vo lu me for

PADD 1 2005 i n 2030 E10 E15 Wi nte r Summer Wi nter Summer Wi nter Summer



## Table **5 -**  **58 PADD 2 Gasoline Qualities for the E10 and E15 Cases relative to the Reference Case** 

CG RFG Pool CG RFG Pool CG RFG Pool CG RFG Pool CG RFG Pool CG RFG Pool Ene rgy ( MMB TU/ bbl) 5.18 5. 02 4. 97 4. 99 4. 75 4. 95 4. 99 5. 03 4. 99 4. 87 4. 89 4. 88 4. 94 4. 93 4. 94 4. 83 4. 81 4. 83 De nsi ty ( lb /bbl) 257. 79 258. 55 259. 05 255. 20 251. 15 254. 54 258. 09 259. 13 258. 25 256. 71 256. 01 256. 59 260. 15 259. 67 260. 07 258. 46 256. 91 258. 20 Sulfur (ppm) 27. 4 9. 7 20. 7 25. 0 16. 9 23. 7 23. 3 17. 9 22. 4 24. 1 24. 1 24. 1 28. 0 28. 0 28. 0 26. 8 26. 7 26. 8 % at 200 45. 7 53. 7 56. 1 48. 8 68. 4 51. 9 53. 4 49. 7 52. 8 58. 9 59. 0 58. 9 57. 5 55. 8 57. 2 62. 7 64. 8 63. 0 % at 300 76. 6 85. 0 84. 6 79. 7 93. 7 82. 0 81. 7 82. 2 81. 7 83. 9 84. 9 84. 1 80. 3 81. 3 80. 5 84. 2 86. 7 84. 6 RVP (psi) 7.91 7. 00 8. 73 13. 97 12. 70 13. 76 9. 28 7. 00 8. 92 13. 31 13. 31 13. 31 8. 28 7. 00 8. 08 13. 07 12. 93 13. 05 T1 0 ( F) 131. 2 137. 1 126. 0 92. 8 100. 9 94. 1 122. 6 137. 1 124. 9 97. 0 97. 0 97. 0 128. 9 137. 1 130. 2 98. 5 99. 4 98. 6 T5 0 ( F) 208. 6 192. 3 187. 4 202. 3 162. 3 195. 8 192. 9 200. 4 194. 1 181. 7 181. 5 181. 6 184. 6 188. 0 185. 1 173. 9 169. 6 173. 2 T9 0 ( F) 358. 7 320. 2 322. 3 344. 5 280. 8 334. 2 335. 6 333. 0 335. 2 325. 4 320. 8 324. 6 341. 6 337. 2 340. 9 323. 8 312. 8 322. 0 Dri ve abi lit y 1181. 5 1102. 5 1073. 5 1090. 7 918. 9 1062. 8 1098. 0 1139. 7 1104. 7 1015. 8 1010. 7 1015. 0 1088. 7 1106. 7 1091. 6 993. 4 970. 6 989. 7 Va por Lock 143. 9 146. 0 135. 9 110. 3 110. 3 110. 3 133. 9 147. 4 136. 0 110. 3 110. 3 110. 3 137. 8 145. 3 139. 0 110. 3 110. 3 110. 3 Ar omatics (vol%) 27. 9 18. 9 22. 2 24. 7 12. 3 22. 7 22. 5 19. 5 22. 0 20. 4 18. 2 20. 0 20. 3 19. 2 20. 2 20. 0 16. 9 19. 5 Benzene ( vol %) 0.58 0. 56 0. 54 0. 58 0. 57 0. 58 0. 51 0. 56 0. 52 0. 50 0. 55 0. 51 0. 55 0. 76 0. 58 0. 67 0. 65 0. 67 Olefins( vol%) 11. 5 3. 8 8.8 13. 0 6. 8 12. 0 8. 8 6. 7 8. 5 10. 7 11. 2 10. 7 7. 3 7. 0 7. 2 10. 5 10. 6 10. 6 Alc ohol ( vol%) 0.42 10. 00 8. 80 0. 00 10. 00 1. 62 10. 00 10. 00 10. 00 10. 00 10. 00 10. 00 15. 00 15. 00 15. 00 15. 00 15. 00 15. 00 Oxyge n ( wt%) 0.40 3. 73 3. 27 0. 00 3. 84 0. 62 3. 74 3. 72 3. 73 3. 76 3. 77 3. 76 5. 56 5. 57 5. 56 5. 60 5. 63 5. 60 Vo lu mes ( kbbl /day) 1, 772, 351 329, 642 1, 759, 558 1, 685, 250 326, 672 2, 011, 922 1, 802, 319 342, 519 2, 144, 838 1, 751, 081 339, 433 2, 090, 514 1, 841, 582 342, 519 2, 184, 101 1, 751, 081 339, 433 2, 090, 514 Gasol ine Qual ities and Vo lu me for

PADD 2 Wi nte r Summer Wi nter Summer Wi nter Summer E15 E10 2005 i n 2030

### *** E.O. 12866 Review

**– Revised Version** 

**– Do Not Cite, Quote, or Release**  **During Review *****



## 5

- 84 **Table 5**  **- 59**  **PADD 3 Gasoline Qualities for the E10 and E15 Cases relative to the Reference Case** 

CG RFG Pool CG RFG Pool CG RFG Pool CG RFG Pool CG RFG Pool CG RFG Pool Ene rgy ( MMB TU/ bbl) 5.18 5. 16 5. 18 5. 13 5. 18 5. 14 5. 07 5. 11 5. 08 5. 07 5. 00 5. 05 4. 95 4. 95 4. 95 4. 91 4. 84 4. 89 De nsi ty ( lb /bbl) 258. 31 258. 54 258. 37 256. 15 254. 74 255. 78 258. 18 259. 96 258. 66 256. 90 255. 26 256. 48 260. 34 260. 35 260. 35 258. 80 254. 37 257. 67 Sulfur (ppm) 27. 6 24. 8 26. 8 25. 7 22. 4 24. 7 24. 1 24. 9 24. 3 22. 8 23. 1 22. 9 27. 8 26. 0 27. 3 13. 1 21. 6 15. 3 % at 200 44. 8 51. 4 46. 6 43. 7 56. 5 45. 8 54. 0 49. 0 52. 7 50. 7 53. 7 51. 4 58. 8 58. 3 58. 6 59. 9 66. 5 61. 6 % at 300 75. 9 82. 7 77. 8 75. 5 83. 3 76. 8 81. 1 80. 8 81. 0 76. 8 79. 8 77. 6 80. 6 83. 1 81. 3 83. 4 90. 9 85. 3 RVP (psi) 7.94 6. 54 7. 55 12. 47 11. 65 12. 34 8. 85 7. 00 8. 35 12. 02 11. 83 11. 97 7. 85 7. 00 7. 61 11. 43 11. 00 11. 32 T1 0 ( F) 131. 1 140. 0 133. 5 102. 3 107. 5 103. 2 125. 3 137. 1 128. 5 105. 2 106. 4 105. 5 131. 7 137. 1 133. 1 108. 9 111. 6 109. 6 T5 0 ( F) 210. 4 197. 0 206. 7 212. 6 186. 6 208. 4 191. 6 201. 8 194. 4 198. 4 192. 3 196. 9 181. 9 182. 8 182. 2 179. 7 166. 2 176. 2 T9 0 ( F) 361. 9 330. 7 353. 3 363. 6 328. 2 357. 6 338. 1 339. 4 338. 4 357. 6 343. 9 354. 1 340. 3 328. 9 337. 2 327. 5 293. 7 318. 9 Dri ve abi lit y 1189. 8 1131. 7 1173. 7 1154. 8 1049. 1 1137. 5 1100. 8 1150. 5 1114. 2 1110. 6 1080. 5 1102. 9 1083. 6 1082. 8 1083. 4 1029. 9 959. 7 1012. 0 Va por Lock 144. 0 149. 3 145. 5 120. 1 120. 1 120. 1 135. 9 147. 6 139. 1 120. 1 120. 1 120. 1 139. 7 144. 4 141. 0 120. 1 120. 1 120. 1 Ar omatics (vol%) 29. 2 19. 7 26. 6 27. 6 20. 0 26. 1 22. 4 19. 5 21. 6 20. 8 18. 4 20. 2 19. 1 15. 6 18. 1 17. 9 11. 0 16. 2 Benzene ( vol %) 0.59 0. 58 0. 59 0. 59 0. 58 0. 58 0. 52 0. 51 0. 52 0. 50 0. 57 0. 52 0. 73 0. 90 0. 77 0. 40 0. 59 0. 45 Olefins( vol%) 11. 5 1. 1 8.6 11. 5 9. 8 11. 0 9. 4 2. 7 7. 6 8. 4 8. 5 8. 5 7. 9 2. 8 6. 5 7. 5 13. 5 9. 0 Alc ohol ( vol%) 0.90 5. 00 2. 03 0. 00 4. 00 0. 63 10. 00 10. 00 10. 00 10. 00 10. 00 10. 00 15. 00 15. 00 15. 00 15. 00 15. 00 15. 00 Oxyge n ( wt%) 0.67 2. 54 1. 19 0. 00 2. 50 0. 40 3. 73 3. 71 3. 73 3. 75 3. 78 3. 76 5. 55 5. 55 5. 55 5. 59 5. 68 5. 61 Vo lu mes ( kbbl /day) 1, 257, 764 480, 771 1, 738, 535 1, 400, 629 489, 720 1, 890, 349 1, 306, 897 479, 961 1, 786, 858 1, 492, 196 508, 849 2, 001, 045 1, 306, 897 499, 552 1, 806, 449 1, 433, 678 488, 895 1, 922, 573 Gasol ine Qual ities and Vo lu me for

PADD 3 Wi nte r Summer 2005 i n 2030 E10 E15 Summer Wi nter Summer Wi nter

### *** E.O. 12866 Review

**– Revised Version** 

**– Do Not Cite, Quote, or Release**  **During Review *****



## 5

- 85 **Table 5**  **- 60**  **PADD 4 and 5OC Gasoline Qualities for the E10 and E15 Cases relative to the Reference Case**

CG RFG Pool CG RFG Pool CG RFG Pool CG RFG Pool CG RFG Pool CG RFG Pool Ene rgy ( MMB TU/ bbl) 5.06 0. 00 5. 06 5. 00 0. 00 5. 00 4. 95 0. 00 4. 95 4. 89 0. 00 4. 89 4. 89 0. 00 4. 89 4. 80 0. 00 4. 80 De nsi ty ( lb /bbl) 258. 41 0. 00 258. 41 253. 46 0. 00 253. 46 258. 55 0. 00 258. 55 254. 99 0. 00 254. 99 260. 44 0. 00 260. 44 256. 45 0. 00 256. 45 Sulfur (ppm) 24. 8 0. 0 24. 8 24. 4 0. 0 24. 4 28. 0 0. 0 28. 0 28. 0 0. 0 28. 0 28. 0 0. 0 28. 0 25. 8 0. 0 25. 8 % at 200 53. 3 0. 0 53. 3 59. 2 0. 0 59. 2 62. 1 0. 0 62. 1 64. 4 0. 0 64. 4 64. 6 0. 0 64. 6 70. 1 0. 0 70. 1 % at 300 90. 7 0. 0 90. 7 92. 2 0. 0 92. 2 91. 6 0. 0 91. 6 92. 1 0. 0 92. 1 92. 2 0. 0 92. 2 96. 0 0. 0 96. 0 RVP (psi) 8.07 0. 00 8. 07 13. 00 0. 00 13. 00 9. 08 0. 00 9. 08 12. 96 0. 00 12. 96 8. 08 0. 00 8. 08 12. 59 0. 00 12. 59 T1 0 ( F) 130. 3 0. 0 130. 3 99. 0 0. 0 99. 0 123. 8 0. 0 123. 8 99. 2 0. 0 99. 2 130. 2 0. 0 130. 2 101. 5 0. 0 101. 5 T5 0 ( F) 193. 0 0. 0 193. 0 181. 1 0. 0 181. 1 175. 1 0. 0 175. 1 170. 5 0. 0 170. 5 170. 0 0. 0 170. 0 158. 9 0. 0 158. 9 T9 0 ( F) 294. 6 0. 0 294. 6 287. 8 0. 0 287. 8 290. 3 0. 0 290. 3 288. 3 0. 0 288. 3 287. 5 0. 0 287. 5 270. 5 0. 0 270. 5 Dri ve abi lit y 1069. 1 0. 0 1069. 1 979. 5 0. 0 979. 5 1001. 4 0. 0 1001. 4 948. 5 0. 0 948. 5 992. 8 0. 0 992. 8 899. 4 0. 0 899. 4 Va por Lock 140. 4 0. 0 140. 4 111. 9 0. 0 111. 9 131. 9 0. 0 131. 9 110. 3 0. 0 110. 3 136. 4 0. 0 136. 4 110. 3 0. 0 110. 3 Ar omatics (vol%) 20. 4 0. 0 20. 4 20. 3 0. 0 20. 3 17. 4 0. 0 17. 4 15. 3 0. 0 15. 3 15. 7 0. 0 15. 7 12. 7 0. 0 12. 7 Benzene ( vol %) 1.17 0. 00 1. 17 1. 12 0. 00 1. 12 1. 19 0. 00 1. 19 1. 18 0. 00 1. 18 1. 19 0. 00 1. 19 0. 73 0. 00 0. 73 Olefins( vol%) 9. 7 0. 0 9.7 8. 8 0. 0 8. 8 8. 1 0. 0 8. 1 7. 8 0. 0 7. 8 7. 8 0. 0 7. 8 7. 3 0. 0 7. 3 Alc ohol ( vol%) 0.00 0. 00 0. 00 0. 00 0. 00 0. 00 10. 00 0. 00 10. 00 10. 00 0. 00 10. 00 15. 00 0. 00 15. 00 15. 00 0. 00 15. 00 Oxyge n ( wt%) 0.01 0. 00 0. 01 0. 00 0. 00 0. 00 3. 73 0. 00 3. 73 3. 78 0. 00 3. 78 5. 55 0. 00 5. 55 5. 64 0. 00 5. 64 Vo lu mes ( kbbl /day) 889, 157 0 889, 157 733, 803 0 733, 803 718, 402 0 718, 402 762, 467 0 762, 467 718, 402 0 718, 402 762, 467 0 762, 467 Gasol ine Qual ities and Vo lu me for

PADDs 4 & 5OC 2005 i n 2030 E10 E15 Summer Wi nter Summer Wi nter Summer Wi nte r

### *** E.O. 12866 Review

**– Revised Version** 

**– Do Not Cite, Quote, or Release**  **During Review *****



## 5

- 86 **Table 5**  **- 61**  **U.S. (except**  **CA) Gasoline Qualities for the E10 and E15 Cases relative to the Reference Case**

CG RFG Pool CG RFG Pool CG RFG Pool CG RFG Pool CG RFG Pool CG RFG Pool Ene rgy ( MMB TU/ bbl) 5.16 5. 10 5. 10 5. 06 4. 96 5. 03 5. 02 5. 06 5. 03 4. 97 4. 93 4. 96 4. 93 4. 93 4. 93 4. 86 4. 82 4. 85 De nsi ty ( lb /bbl) 257. 99 259. 40 258. 71 255. 37 252. 52 254. 52 258. 01 260. 38 258. 62 256. 20 255. 65 256. 06 260. 06 260. 39 260. 15 258. 11 255. 59 257. 45 Sulfur (ppm) 27. 1 21. 6 24. 5 24. 4 18. 1 22. 5 24. 2 22. 9 23. 9 23. 3 20. 4 22. 6 28. 0 27. 5 27. 8 19. 0 20. 2 19. 3 % at 200 46. 8 51. 4 50. 4 47. 8 62. 0 51. 7 55. 1 50. 4 53. 9 55. 8 57. 9 56. 3 59. 4 58. 1 59. 1 62. 5 66. 3 63. 5 % at 300 78. 8 82. 2 81. 5 79. 3 88. 5 81. 9 82. 8 81. 3 82. 4 81. 4 83. 4 81. 9 82. 3 83. 4 82. 6 85. 3 89. 5 86. 4 RVP (psi) 7.95 6. 61 7. 78 13. 07 12. 77 13. 00 9. 15 7. 00 8. 60 13. 07 12. 97 13. 04 8. 15 7. 00 7. 84 12. 65 12. 44 12. 59 T1 0 ( F) 131. 0 139. 5 132. 1 98. 5 100. 4 98. 9 123. 4 137. 1 126. 9 98. 5 99. 2 98. 7 129. 7 137. 1 131. 7 101. 2 102. 5 101. 5 T5 0 ( F) 206. 4 197. 0 199. 0 204. 3 175. 4 196. 4 189. 4 199. 1 191. 9 187. 9 183. 8 186. 9 180. 6 183. 2 181. 3 174. 4 166. 5 172. 3 T9 0 ( F) 348. 7 332. 9 336. 2 346. 2 304. 3 334. 5 330. 5 337. 3 332. 2 336. 7 327. 5 334. 3 332. 7 327. 6 331. 3 319. 1 299. 7 314. 1 Dri ve abi lit y 1164. 5 1133. 3 1131. 2 1106. 9 981. 0 1072. 0 1083. 8 1140. 1 1098. 3 1048. 3 1027. 6 1043. 0 1069. 2 1082. 8 1072. 8 994. 1 953. 0 983. 4 Va por Lock 143. 3 148. 9 142. 9 115. 4 112. 1 114. 5 134. 0 147. 2 137. 4 112. 7 112. 5 112. 6 137. 8 144. 5 139. 6 112. 6 112. 4 112. 6 Ar omatics (vol%) 27. 0 19. 9 23. 8 25. 5 15. 6 22. 6 21. 7 19. 8 21. 2 19. 8 18. 4 19. 4 18. 9 17. 4 18. 5 18. 1 13. 8 17. 0 Benzene ( vol %) 0.68 0. 57 0. 64 0. 67 0. 56 0. 64 0. 60 0. 55 0. 59 0. 60 0. 57 0. 59 0. 73 0. 87 0. 77 0. 55 0. 58 0. 56 Olefins( vol%) 11. 1 7. 4 9.6 11. 4 13. 7 12. 1 8. 9 8. 1 8. 7 9. 6 13. 2 10. 5 7. 9 7. 6 7. 8 8. 5 15. 5 10. 4 Alc ohol ( vol%) 0.48 5. 68 3. 69 0. 00 5. 49 1. 53 10. 00 10. 00 10. 00 10. 00 10. 00 10. 00 15. 00 15. 00 15. 00 15. 00 15. 00 15. 00 Oxyge n ( wt%) 0.49 2. 73 1. 73 0. 04 2. 70 0. 77 3. 74 3. 70 3. 73 3. 76 3. 77 3. 76 5. 56 5. 55 5. 56 5. 60 5. 66 5. 62 Vo lu mes ( kbbl /day) 5, 318, 524 2, 197, 464 7, 173, 553 5, 158, 635 2, 184, 454 7, 343, 089 5, 588, 449 1, 943, 943 7, 532, 392 5, 703, 920 1, 955, 160 7, 659, 080 5, 603, 677 2, 046, 394 7, 650, 071 5, 566, 827 1, 954, 095 7, 520, 922 Gasol ine Qual ities and Vo lu me for

PADDs 1- 4 & 5O C 2005 i n 2030 E10 E15 Summer Wi nter Summer Wi nter Summer Wi nte r

### *** E.O. 12866 Review

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## 5

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2 

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3 

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### *** E.O. 12866 Review

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## 5

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