EnSys	RTI	 2011

Peer	Review	of

EPA	Refinery	Cost	Model:

Gasoline	Sulfur	Reduction

Final Report

December 19 2011

Prepared for

Lester Wyborny

Russ Smith

U.S. Environmental Protection Agency

Office of Transportation and Air Quality (OTAQ)

1200 Pennsylvania Ave., NW

Washington, DC 20460

EPA Contract Number EP-C-08-008

RTI Sub-contract Number 4-312-0211577

Prepared by

Martin R. Tallett & Daniel N. Dunbar

EnSys Energy & Systems, Inc.

1775 Massachusetts Avenue

Lexington, MA 02420
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Table	of	Contents

1 INTRODUCTION.............................................................................................................................................1

2 SUMMARY.....................................................................................................................................................2

2.1 ADEQUACY OF CURRENT MODEL FORMULATION DATA & RESULTS.............................................................................2

2.2 PROPOSED RECOMMENDATIONS FOR CHANGES AND THEIR IMPACTS ON ESTIMATED COSTS ............................................2

3 REGULATORY CONTEXT .................................................................................................................................3

4 COMMENTARY & FINDINGS ..........................................................................................................................3

4.1 MODEL VERSION PROVIDED TO ENSYS ..................................................................................................................3

4.2 EPA METHODOLOGY/MODELING APPROACH AS A MEANS TO ASSESS COSTS OF GASOLINE SULFUR REDUCTION ................4

4.2.1 Summary of EPA Methodology ................................................................................................................4

4.2.2 Estimation of Blendstock Volumes by Refinery ........................................................................................4

4.2.3 Sulfur Levels Assigned to Blendstocks......................................................................................................5

4.2.4 FCC Gasoline Sulfur Level Back-calculation..............................................................................................6

4.3 KEY DETERMINANTS OF COSTS IN MODEL ..............................................................................................................6

4.3.1 FCC Gasoline Volume & Sulfur Level ........................................................................................................6

4.3.2 Assumed Target Sulfur Levels ..................................................................................................................6

4.3.3 Vendor Cost Data & Transposition into Model ........................................................................................7

4.3.3.1 Cost Bases Requested by EPA ......................................................................................................................... 7

4.3.3.2 Vendor Processing Schemes ........................................................................................................................... 7

4.3.3.3 Vendor 1 ......................................................................................................................................................... 8

4.3.3.4 Vendor 2 ......................................................................................................................................................... 9

4.3.3.5 Vendor 3 ....................................................................................................................................................... 10

4.3.3.6 Other Vendors & Average Costs ................................................................................................................... 10

4.3.3.7 All Vendor Capital Costs................................................................................................................................ 11

4.3.3.8 Capital Costs (ISBL and Total)........................................................................................................................ 11

4.3.3.9 Octane Loss................................................................................................................................................... 11

4.3.4 Other Key Cost Parameters....................................................................................................................11

4.3.4.1 Capital Cost Power Factor............................................................................................................................. 11

4.3.4.2 Natural Gas, Electricity & Steam Prices......................................................................................................... 12

4.3.4.2.1 Natural Gas............................................................................................................................................... 12

4.3.4.2.2 Electricity.................................................................................................................................................. 13

4.3.4.2.3 Steam ....................................................................................................................................................... 13

4.3.4.3 Hydrogen Cost............................................................................................................................................... 13

4.3.4.4 Cost of Octane Loss....................................................................................................................................... 14

4.3.4.5 E10/E15......................................................................................................................................................... 15

4.4 ADDITIONAL FACTORS INFLUENCING COSTS..........................................................................................................16

4.4.1 LSR Sulfur Reduction ..............................................................................................................................16

4.4.2 Other......................................................................................................................................................16

4.5 MODEL RESULTS, PROPOSED PREMISE ADJUSTMENTS AND THEIR IMPACTS................................................................16

4.5.1 Results from Current Cost Model...........................................................................................................16

4.6 DETAILED MODEL INTEGRITY FINDINGS/ISSUES.....................................................................................................17
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4.6.1 Approach Employed by EnSys................................................................................................................18

4.6.2 General Comments on Model Structure.................................................................................................18

4.6.3 Specific Data & Equations Integrity .......................................................................................................19

4.6.3.1 Capital, Fixed & Variable Operating Cost Formulae...................................................................................... 19

4.7 POTENTIAL FOR MODEL IMPROVEMENT ..............................................................................................................19

4.8 UTILITY FOR FORWARD LOOKING REGULATORY ANALYSES.......................................................................................19
EnSys	RTI	 2011

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1 Introduction

The EPA Office of Transportation and Air Quality (OTAQ) contracted EnSys Energy to undertake one of 

two “peer reviews” of the EPA’s Refinery-by-Refinery Cost Model (the EPA Refinery Cost Model). The 

EPA Model was originally developed by EPA OTAQ for benzene level analysis using extensive MathPro 

fuels blending and LP data. The version of the Model delivered to EnSys for review had been extended 

and “re-purposed” by EPA OTAQ to estimate costs for reducing sulfur in U.S. gasoline from the present 

30 ppm limit to 10 and 5 ppm. As for the original benzene-oriented model, the current Model 

calculates costs for each U.S. refinery that produces finished gasoline. 

EnSys’ review focused on the Model methodology, the associated data sources and data development 

process and the specific data and equations applied in the Model. Our remit was to consider solely the 

adequacy of the model to capture costs for U.S. gasoline sulfur reduction to 10-5 ppm from current 

levels. 

The Sections below comprise our review. 

 Section 2 Summary summarizes our review and findings

 Section 3 Regulatory Context provides an outline of the regulatory context for the use of the 

EPA Model, and hence for the peer review

 Section 4 Commentary & Findings comprises the core of our review

o Section 4.1 summarizes the specific Model version supplied to EnSys for review

o Section 4.2 first summarizes EnSys’ understanding of the EPA methodology as 

understood by EnSys. Our intent here was to “track” the key data items and decisions in 

the methodology as a key first step in reviewing it. The balance of Section 4.2 then 

reviews the key elements in the EPA Model methodology

o Section 4.3 focuses in on the factors which we considered as key to EPA’s determination 

of sulfur reduction costs. The section thus covers volume and sulfur level for FCC 

gasoline, the (adequacy of the) vendor data obtained and used by EPA OTAQ, the 

transposition of that data into the Model and the effect of other key assumptions 

affecting costs. 

o Section 4.4 comments on additional elements in the potential costs of meeting 10-5 

ppm standards, notably LSR sulfur reduction

o Section 4.5 sets out EnSys’ recommendations for adjustments to the EPA cost 

assumptions and our assessment of the resulting impacts on estimated costs

o Section 4.6 sets out EnSys’ review of the details of Model data and equation integrity 

and lists items that we see needing to be changed 

o Section 4.7 summarizes the need and potential we see for Model improvement

o Section 4.8 comments on the utility of the EPA Refinery Cost Model for regulatory use 

and describes some of the factors EnSys sees impacting U.S. refining to 2017 – and 
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which therefore need to be taken into account in any rigorous analysis of Tier 3 gasoline 

costs. 

2 Summary

Section 4 of this report contains specific findings and commentary, including to the Model cell level. 

Below, we summarize our main findings. 

2.1 Adequacy	of	Current	Model	Formulation	Data	&	Results

The EPA Refinery Costs Model comprises 1 main and 7 linked workbooks. EnSys was only able to 

examine the single main workbook although we understand the role of the secondary workbooks was 

essentially limited to passing in data. Based on our review, the EPA Model contains a small number of 

errors that were identified by EnSys plus a number of key data values that could or should be reviewed 

prior to any further Model use by the EPA. A Model version was supplied back to the EPA which already 

embodied a number of changes made by EnSys and which could form a starting point for further review 

by the EPA. 

2.2 Proposed	Recommendations	for	Changes	and	Their	Impacts	on	Estimated	

Costs

The body of this report contains a number of recommendations for Model improvements. Most center 

on corrections and adjustments to key formulae and data which have a direct impact on computed costs 

of sulfur reduction. Making these adjustments raises assessed costs although not dramatically. 

In addition, EnSys has proposed a series of changes that would reduce the risk of errors in the Model

and make it easier to understand, to trace calculations from source data to results, to adjust and 

therefore audit. These center not so much on specific values or formulae structures as on applying 

available Excel modeling and documentation techniques such as using explicit named variables and 

ranges in formulae, using cell comments and other documentation etc. 
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3 Regulatory	Context

EPA OTAQ plans to use the Refinery Costs Model as part of its review in connection with potential Tier 3 

Motor Vehicle and Emission Standards1. This proposed rule was initiated in February 2010. According 

to EPA, “the standards in this rule will lead to reductions in ozone, particulate matter, nitrogen dioxide, 

and mobile air source toxics”. With respect to gasoline, EnSys understands that the rule could set new 

standards for volatility (Reid Vapor Pressure), sulfur and possibly other properties. According to the 

EPA website, the Notice of Proposed Rule Making for Tier 3 standards is projected for publication in 

February 2012. EnSys understands that EPA intends to use the Refinery Cost Model in developing the 

NPRM - but only with respect to the estimation of sulfur reduction costs, not for RVP reduction or any 

other potential aspects of the rule2. 

4 Commentary	&	Findings

The Sections below provide an overview of the EPA OTAQ methodology, a detailed assessment of the 

parameters that, in our view, will most impact gasoline sulfur reduction costs, resulting recommended 

changes to costs premises in the Model and calculation of their effects, commentary on other detailed 

data and formula issues within the Model and, finally, summary recommendations for Model changes.

4.1 Model	Version	Provided	to	EnSys	

The Model version EnSys reviewed was titled as “Rev3” and dated December 1st 2011. Specifically one 

multi-page Excel workbook was provided for our review. We note, however, that the Rev3.xls 

workbook linked to 7 external Excel workbooks. None of those was available or was included in our 

review. Our understanding from EPA was that the external files were not essential to our purposes

since their primary purpose was to pass data in to the main Model workbook. We did not see any errors 

relating to these external links but were, of course, not able to cross-check and validate them. 

 

1

Control of Air Pollution from Motor Vehicles: Tier 3 Motor Vehicle and Emission Standards; Docket No: EPA-HQOAR-2011-0135. 

2 While the EPA Refinery Cost Model is being applied by OTAQ in a regulatory context that could impact several 

gasoline qualities, the Model is its current form provides insights solely into the costs of gasoline sulfur reduction. 
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4.2 EPA	Methodology/Modeling	Approach	as	a	Means	to	Assess	Costs	of	

Gasoline	Sulfur	Reduction

4.2.1 Summary	of	EPA	Methodology

The EPA Model supplied to EnSys uses a mix of public and proprietary refinery-by-refinery data to first 

estimate gasoline blendstock volumes, total gasoline production and reported pool gasoline sulfur level. 

It then uses cross-checks of the estimated gasoline production from blendstocks to compare against 

total reported gasoline production from official figures. Next, it uses estimates for all gasoline blend 

components other than FCC gasoline, together with officially reported refinery gasoline product pool

sulfur to back calculate FCC gasoline sulfurs by refinery. The model does not use that information 

directly but average levels were applied by the EPA as the basis for seeking FCC gasoline hydro-treating 

data from vendors whose processes are employed in U.S. refineries for desulfurizing FCC gasoline. The

Model then applies capital cost, hydrogen consumption and utilities data for FCC gasoline 

desulfurization in the Model to each refinery. The general approach is to assume each refinery stays 

with its current technology supplier and to apply data relevant to that technology for revamping the 

existing installed FCC hydro-treater to a more severe duty in line with reduced gasoline sulfur target. 

For refineries that have no current FCC gasoline hydro-treater, (generally they have an FCC feed hydrotreater), construction of a new FCC gasoline hydro-treater is assumed. Potential need to desulfurize 

LSR is also assessed on a refinery-by-refinery basis and the associated costs estimated. Capital 

investment plus capital recovery, fixed and variable costs are estimated on a refinery-by-refinery basis 

and then summed to create total national level investment and c/gal fully built up costs. 

4.2.2 Estimation	of	Blendstock	Volumes	by	Refinery

We undertook a brief review of yields from units other than the FCC, comparing with those in the EnSys 

WORLD Model. The only unit where yields warranted further comment was the hydro-cracker. (See 

below.) We note that the estimation method used data from a third party refinery LP model (MathPro), 

with variations by PADD, that has been calibrated and applied to a significant number of U.S. regional 

and national studies. 

As noted, the hydrocrackate yields in the EPA Model are taken from MathPro data. We were not able to 

identify exactly which values were used for estimated HCR gasoline yield but we note that (a) the stated 

hydrocrackate gasoline yields vary substantially from PADD to PADD and (b) that the hydrocrackate 

yields are high. Given today’s growing emphasis on maximizing distillate yields, (which can mean a 

hydrocrackate gasoline yield of less than 10%), we would advise that EPA double-check the yields used. 
EnSys	RTI	 2011

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We would expect them increasingly today and in the future to correspond to maximum distillate 

production. 

 

4.2.3 Sulfur	Levels	Assigned	to	Blendstocks

We reviewed the sulfur levels used by EPA in the Model as tabulated below. This included a close crosscheck of values against those in the EnSys WORLD Model. 

Gasoline Blendstock Sulfur Levels in EPA Model

Blendstock Value in Model ppm S

Butane 10

LSR 1

Coker naphtha 1

NGL 1

Poly gasoline 1

Isomerate 1

Dimate 3

Hydrocrackate 8

Alkylate 5

Reformate 1

Ethanol 10

FCC naphtha (back calculated) 40 - 130

All of the values being used by EPA fall within plausible ranges on the basis that all streams will have 

been either Merox sweetened or hydro-treated before blending into gasoline products. Absence of 

such treating will lead to higher values on a case by case basis. We note, however, that using 

conservatively low sulfur values leads to higher back-calculated FCC naphtha estimated sulfur levels. As 

a test, we dropped the sulfur level on all components (FCC naphtha aside) to 0 ppm. The effect was to 

raise average estimated FCC naphtha sulfur by around 1.7 ppm and maximum refiner-specific sulfur by 

around 7 ppm. These effects are limited, indicating the calculation of sulfur reduction costs is relatively 

insensitive to variations in assumed typical sulfur levels of non FCC naphtha blend stocks. 

 
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4.2.4 FCC	Gasoline	Sulfur	Level	Back-calculation

We were not able to cross-check EPA’s formulae in detail for back-calculating the sulfur level of FCC 

naphtha refinery by refinery. The values appear to be sound. For the different Tier 2 scenarios 

calculated in the Data for 2009 Model page, we note that the average (non-weighted) FCC naphtha 

sulfur level is estimated to lie in the range of 64-68 ppm with maxima around 120-130 and minima 

around 40 ppm. Given that EPA assumed an average level of 75 ppm to assess costs for sulfur 

reduction, these estimates of actual 2009 FCC naphtha sulfur levels imply a modest degree of 

conservatism in the EPA calculations, i.e. the use of 75 ppm when the actual average appears closer to 

65 ppm. 

The EPA Model uses a regression to estimate raw VGO sulfur as a function of crude sulfur. The 

regression is based on data from 8 crudes and produces a near 99% R squared. We believe this is a 

reasonable approach with acceptable range of uncertainty given the overall uncertainty level in this type 

of modeling approach. 

 

4.3 Key	Determinants	of	Costs	in	Model

4.3.1 FCC	Gasoline	Volume	&	Sulfur	Level

Costs for sulfur reduction of U.S. gasoline are clearly primarily dependent on the volume and sulfur level 

of FCC naphtha. We did not research external literature to cross-check EPA’s method for FCC naphtha 

volume calculation but their ability to use actual CBI refinery by refinery 2009 FCC charge rates is a key 

factor that in turn leaves open only the question of FCC yields. Broadly, we found the yield data 

reasonable, especially given the back-calculation against national gasoline production contained in the 

Model.

4.3.2 Assumed	Target	Sulfur	Levels

The extent of any “giveaway” assumed for actual blend standards against nominal standards can affect 

costs. For the 10 and 5 ppm standards being evaluated, EPA OTAQ had allowed for only 1 ppm sulfur 

“giveaway” i.e. effective ex refinery gate sulfur targets of 9 and 4 ppm. EPA’s underlying rationale for 

the small levels of giveaway used was that, under Tier 3, an emissions Averaging, Banking and Trading 

(ABT) program would apply and that, under this, across a whole calendar year, refiners and blenders 

would be able to move close to the mandatory limit, for instance edging blended gasoline sulfur levels 

up toward the end of the year if they had produced below spec early in the year. 
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As a cross-check on the validity of this assumption, EnSys obtained from the EPA 2009 data for gasoline 

sulfur by refinery. The chart below summarizes 2009 data for some 92 refineries producing Tier 2 

gasoline. The graph clearly shows the effect of the ABA program which is also in effect under Tier 2. 

Produced gasoline sulfur levels range from 2 to 84 ppm but we understand from EPA that the weighted 

average is right on 30 ppm3. The implication is that individual refinery sulfur reduction programs 

required to meet a 10 or 5 ppm standard will vary widely, with some refineries already producing 

gasoline below 10 ppm, but on average the reduction needed is going to be from 30 to either 10 or 5 

ppm. Thus, EPA are correct to have not allowed for any significant “giveaway” in the Model.

4.3.3 Vendor	Cost	Data	&	Transposition	into	Model

4.3.3.1 Cost	Bases	Requested	by	EPA

Based on the data and gasoline sulfur targets requested of vendors, the EPA Model contained costs for 

gasoline sulfur reduction from an estimated 25 ppm actual (30 ppm nominal) to 10 and 5 ppm 

nominal/actual. 

4.3.3.2 Vendor	Processing	Schemes

 

3

The linear arithmetic average of the values supplied is 31.5 ppm but the refineries producing high sulfur gasoline 

are likely to be older smaller units, hence the lower weighted average. 

0

20

40

60

80

100

0 20 40 60 80 100

ppm sulfur

number of reporting refineries

US Finished Gasoline Sulfur by

Refinery 2009
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4.3.3.3 Vendor	1

Vendor 1 supplied data for a range of processing schemes including covering 75-25 and 75-10 ppm 

extensions of existing FCC naphtha hydrotreaters using their technology and starting from differing 

initial FCC gasoline sulfur levels. The cases include both Minimum Investment and Minimum Octane Loss 

scenarios. In summary, we have some difficulties with both the initial vendor data and with the way 

EPA has applied these in the Model. The vendor cases for unit revamps to add 75-25 and 75-10 ppm 

capability presented different levels of investment, octane loss, delta olefins, hydrogen and utilities 

consumptions depending on the sulfur level of the original raw FCC gasoline. EPA then applied these 

variances in the Model as a function of their estimated raw FCC gasoline sulfur for those refineries which 

were assessed to already have a vendor FCC gasoline hydrotreater. 

We understand that the EPA took very specific vendor cases and applied them in the Model. We note 

this creates a level of precision that goes beyond the limited differentiation supplied by all the other 

vendors, i.e. single data points or averages had to be employed for all but one other vendor. The 

vendor data show incremental hydrogen consumptions for 75-25 ppm revamps running from 45 down 

to 31 and then back up to 45 scf/bbl as original FCC gasoline sulfur drops; then 66 to 60 to 100 for the 

corresponding 75-10 ppm cases. Given the necessity to consider average/typical situations in this 

analysis, we have difficulty with the inflections in these numbers; it is difficult to consider them as 

credible. Similarly, EPA’s interpretation of vendor capital cost data for the revamp cases lead to base 

ISBL costs of $157.50/bbl for a 75-25 ppm revamp where the raw FCC feed had been 200 ppm, $50/bbl 

for raw 800 ppm and $548/bbl for raw 2000 ppm. The numbers are inconsistent with EPA’s 

corresponding values for 75-10 ppm cases, namely $450, $600 and $700/bbl respectively. We 

understand that the EPA was interpreting highly specific vendor cases (which incorporated variations in 

process configuration and capex/opex trade-offs) but we have difficulty with the inflections in the above 

data for 75-25 ppm cases and also the extent to which 75-25 ppm costs varied so much based on 

original raw FCC gasoline sulfur level. We recommend that EPA revisit the capital costs, and also the 

hydrogen consumptions across these cases. 

The EPA also used data from the same vendor for construction of a new 100-10 ppm unit and applied 

this both directly for situations where a refinery has no existing FCC gasoline treater (but would 

generally have an FCC feed hydrotreater to bring FCC gasoline sulfur down to broadly the 100 ppm level) 

and, with adjustments, to generate corresponding data for a new 100-25 ppm unit. The stated ISBL cost 

is $1500/bbl/sd for the 100-10 ppm unit. (It is broadly in line with the $1,830/bbl/sd used in the recent 

MathPro study given that the latter included both ISBL and OSBL costs.) It is stated by the vendor as 

applying to Minimum Investment scenarios. We believe, as discussed elsewhere, that EPA should 

consider applying a contingency factor to this and potentially all capital costs. We also note that the 

$1500/bbl/sd figure appears to omit catalyst cost, stated by the vendor as 20 to 35 percent of ISBL 

capital cost for the revamp cases. It is recommended that the vendor be contacted to provide 

clarification concerning this point. 
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Further, EPA applied the $1500/bbl to both the 100-10 and 100-25 units. Data from Vendor 3 (below)

would suggest a moderate difference of around 5% should be applied. (Arguably the main cost that 

would differ would be that of the reactor. This can often comprise around 15% of total ISBL cost and so 

with a one third increase in reactor cost, 5% in total ISBL appears plausible for the shift in duty from 100-

25 to 100-10 ppm.) 

The $1500/bbl figure puts the revamp capital costs into some perspective. For the 75-10 ppm unit 

revamps, these range from 30 – 47% of new unit cost, depending on original FCC gasoline value. These 

factors are reasonable as “industry typical” estimates4. In contrast, EPA’s original capital costs for 75-25 

ppm unit revamps were 10%, 3% and 36% of the $1500/bbl figure. We aware of instances where 

revamp costs can be low as little by way of hardware changes would be required and we also 

understand that EPA was reflecting very specific vendor cases. We still have difficulty though with these 

values as stated and would suggest EPA review them with the vendor to confirm whether the vendor

truly believes they are realistic. (One point of comparison would be the same vendor’s fractions of new 

unit capital cost for the 75-10 ppm cases.) 

We have similar concerns with the EPA’s derived numbers for hydrogen consumptions. Firstly, with 

figures as low 14 and 6 scf/bbl, we see some of these levels as unrealistically low. Secondly, they appear

inconsistent between 75-25 and 75-10 ppm cases. We recommend the EPA review these numbers with 

the vendor and at least ensure consistency. Note that Handwerk recommends applying a 2 to 10 

multiplier to stoichiometric hydrogen consumption to reflect makeup hydrogen loss5. EnSys applied 

some very rough and ready adjustments in the Model spreadsheet to both hydrogen and capital costs to 

gauge their effect.

 

4.3.3.4 Vendor	2

This vendor supplied limited data around one case for construction of a unit that would take predesulfurized FCC gasoline at 75 ppm down to 10 ppm. The case assumed that 30,000 bpd of whole FCC 

gasoline would be split into LCN and HCN and only the HCN further processed in order to minimize 

olefins/octane reduction. The capital cost quoted for the unit related to a processing capacity for the 

HDS unit of somewhat over 23,000 bpsd. EPA interpreted this as a 30,000 bpsd unit in its calculation in 

the Model of capital cost per b/sd. Given the vendor stated that the new equipment centered solely on 

a new polishing reactor with ancillary facilities (no FCC naphtha splitter or LCN HDS unit), we took the 

view that the stated capital cost should be applied only to the 23,000 bpsd rate; also that that approach 

appears to be more consistent with the costs developed for other vendors. In the Model, we adjusted 

the throughput basis to 23,000 bpsd from 30,000 bpsd. We understand, however, that the vendor, 

subsequent to our assessment, confirmed that the capacity is 30,000 bpsd. 

 

4 We note that the Model Utility & Capital Costs page includes a 40% revamp factor which is used in the 

computation of LSR HDT costs. 

5

Petroleum Refining Technology & Economics, 4th Edition. Handwerk, 2001, page 181.
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4.3.3.5 Vendor	3

Vendor 3 supplied data for single stage units running 800-75 and 800-10 ppm sulfur and for two-stage 

units wherein the first stage ran 800-75 ppm and the second stage either 75-25 or 75-10 ppm. To 

estimate capital costs for 75-25 and 75-10 ppm reductions, EPA subtracted the cost for the 800-75 ppm 

single stage unit from that for the two stage 800-25 or 800-10 ppm units. This may be plausible but see 

further discussion below. Using this method, EPA made what we believe was an error (Vendor Cost 

Info, cell D111) in computing the capital cost for the 75-10ppm unit. They assumed it was the same as 

for the 75-25 ppm unit. EnSys substituted the vendor-provided capital cost for the two-stage 800-10 

ppm unit. Doing this and then subtracting off the capital cost for the single stage 800-75 ppm unit led to 

a more realistic estimated cost for 75-10 ppm, a cost that is now 20% higher than that for 75-25 ppm. 

A second issue relates to EPA’s method for computing hydrogen consumption. They used the same 

method as for capital cost, this even though the vendor supplied data for hydrogen consumptions for 

each stage in the two-stage units. For the 75-10 ppm unit, EPA’s estimated hydrogen is 56.4 scf/bbl. 

This number cross-checks very closely with the hydrogen consumption given by the vendor for the 

second stage in two-stage 800-10 ppm unit. However, EPA’s value of 18 scf/bbl for 75-25 ppm by 

difference compares with vendor data of 45 scf/bbl based on the second stage of the two-stage 800-25 

ppm unit. In our view, 18 scf/bbl appears low and 45 scf/bbl more reasonable. For the other utilities, 

and for octane loss and olefins change, EPA had no option but to take the delta between the single stage 

800-75 and the two-stage 800-25 and 800-10 ppm cases. 

We understand that the vendor was asked to provide these cases as if the refiner would decide to build 

one or other of the units from scratch. In reality, the situation is generally one where the, say, 800-75 

ppm unit already exists and the question is - what is the cost of extending the duty of the existing unit 

down to 25/10 ppm via revamp? We suggest that the EPA go back to the vendor to seek their opinion 

on whether considering the costs in this light would make a difference, including on how EPA has to date 

developed its 75-25 or 75-10 ppm costs by difference. We also suggest that the EPA review with the 

vendor the differences on hydrogen consumption to obtain the vendor’s view on which approach gives 

the more realistic results. 

4.3.3.6 Other	Vendors	&	Average	Costs

The EPA also applied average costs and related data. We suggest the EPA check the formulae to see if 

these best represent actual averages. 

The EPA also received data from two other vendors but had decided not to use either. One set of data 

appeared to be for a specification that was unrelated to the issue at hand. The other set of data related 
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to a little used technology. EPA took the conservative view to apply data averaged from Vendors 1, 2 

and 3. Hydrogen consumptions were higher than for the little used technology. Given the data 

supplied to the EPA, we support their decision to not use the above two data sets. However, we would 

recommend that the EPA, if feasible, go back to the vendors to seek clarifications. 

4.3.3.7 All	Vendor	Capital	Costs

In the Model, EPA applied scale, location, offsites (OSBL) and over-design factors to the capital costs. 

Our experience has been that vendor-supplied costs data, which is what EPA relied upon, tend to also be 

relatively optimistic. (One vendor stated its supplied capital cost had an accuracy of +/- 50%.) In the 

light of uncertainties in the costs of unit construction, we would therefore suggest that the EPA 

consider applying a contingency factor to all the capital costs, potentially of around 20%. Again, the 

option to apply a factor was added in the Model spreadsheet. 

4.3.3.8 Capital	Costs	(ISBL	and	Total)

The vendors reviewed above provided their capital cost estimates on an ISBL basis. EPA applied their 

own OSBL factors. These appeared reasonable for process unit revamps where infrastructure is in place.

4.3.3.9 Octane	Loss

We were not able to cross-check the vendor data for olefins reduction and octane loss. Vendors A and C 

estimated octane loss at 1.0 for unit revamps, somewhat higher than the 0.6 value estimated by EPA. 

Again, it would be helpful to test the impact of level of assumed octane loss on resulting costs in the 

Model. 

4.3.4 Other	Key	Cost	Parameters

4.3.4.1 Capital	Cost	Power	Factor

The EPA Model uses a scaling power factor of 0.65. This appears reasonable and if anything 

conservative. As noted elsewhere, however, this figure is hard-coded into all pertinent formulae. The 

Model would be improved by assigning to a specific cell a name and the value and then referring to it. 

That way, formulae would be more transparent and the sensitivity of results to say using 0.60 as against 

0.65 could be tested. 
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4.3.4.2 Natural	Gas,	Electricity	&	Steam	Prices

4.3.4.2.1 Natural	Gas

In the EPA Model, prices for natural gas and electricity were understood to be taken from the EIA AEO 

2010 Reference Case. Base costs by PADD were escalated up to 2017 costs (expressed in 2009 constant 

dollars) using a factor. The resulting 2017 costs ranged from around $5.60 to $7.90 per million Btu 

depending on the PADD, as summarized in the table below. To check these values, EnSys gathered data 

from the EIA Natural Gas Monthly to first provide current natural gas prices. Specifically, we:

1. downloaded data for Major Industrial User natural gas prices by state for the period January 

2010 through September 2011 (the latest month available)

2. established average prices across the Jan 2010 – Sept 2011 period for every state

3. identified each state within each PADD that contains refineries (for instance in PADD1 only 

New Jersey, Delaware and Pennsylvania are relevant, New York, Vermont etc. are not as 

potentially suppliers of natural gas to refiners)

4. developed an average for each PADD based on the states that contain refineries (again for 

PADD1: NJ, DE, PA).

We then compared these current prices with the base prices by PADD used by the EPA. The comparison 

is included in the table below. The comparison indicates that the EPA base prices understate the 

differences that exist between PADD’s for major industrial user prices, i.e. the cost increases in moving 

from PADD3 (the lowest cost PADD) to other PADD’s. The last two columns in the table compare the 

2017 prices currently in the EPA Model with prices that would result from, in general, adding the 

$0.43/mmBtu difference between the PADD3 2017 and 2010/11 prices to the EIA 2010/11 industrial 

user prices to arrive at a revised set of prices for 2017. EPA may wish to use another methodology but 

our overall reaction is that the 2017 prices should reflect sharper distinctions between PADDs, this 

unless the EIA, say, has a clear basis for these deltas changing in the future6. 

Overall, we recommend EPA review the natural gas prices used, especially outside PADD3. Natural gas 

price can be expected to have an appreciable impact both as fuel and as feedstock for hydrogen 

production. For both natural gas and electricity prices, we would recommend that EPA update to the 

AEO 2011. We note that a recent MathPro report for the ICCT, “Refining Economics of a National Low 

Sulfur, Low RVP Gasoline Standard”, October 25th, 2011, used AEO 2011 projections. Exhibit A-6 

indicated lower natural gas prices for their study year 2015 than for 2010. (This EIA projection seems to 

EnSys somewhat unexpected given natural gas prices are currently at historical lows and, reportedly, the 

 

6

 The overall factor used by the EPA to go from Base 2009 prices to 2017 prices appears to be correct as the AEO 

2010 had $4.32/mmBtu for average U.S. industrial user price for 2009 and $6.70 for 2017. We note though that 

these AEO prices were in $2008 constant dollars and it is not clear whether the EPA prices reflect a conversion 

from 2008 to 2009 dollars, a change that would slightly increase the values used. 
EnSys	RTI	 2011

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costs of shale gas production are running above the $4/mmBtu level producer price, indicating a 

likelihood of increases in the future.) 

Natural Gas Prices Comparison ($2009/million Btu)

EPA Base 2009 EIA 2010/2011 EPA 2017 Revised 2017

PADD1 4.87 9.96 7.88 10.30

PADD2 4.86 7.44 7.86 7.87

PADD3 3.49 5.21 5.64 5.64

PADD4 4.36 6.34 7.06 6.77

PADD5 ex CA 4.60 8.33 7.44 8.76

PADD5 CA n.a. 7.04 7.44 7.49

4.3.4.2.2 Electricity

Electricity prices are generally likely to have less of an impact on fuels costs than do prices of natural 

gas. EnSys did not check the electricity prices used by the EPA so thoroughly. We note though that EPA 

does increase prices by a factor of 1.45 to arrive at 2017 prices versus the 2009 base levels EPA uses. 

We note that the AEO 2010 shows U.S. industrial end use price declining in $2008 from 6.8 c/kwh in 

2009 to 6.1 c/kWh in 2017. Given EIA’s projected increase in natural gas prices, we would support the 

factor used by the EPA. Our main question is that the base prices used by EPA for electricity, which 

average 4.46 c/kWh, appear low relative to the AEO 6.8 c/kWh for industrial users, i.e. arguably the base 

levels should be increased leading to 2017 prices that are higher than the current 4.7 – 8.4 c/kWh in the 

EPA Model. 

4.3.4.2.3 Steam

EnSys identified two errors in the Model with respect to steam costs calculation. One error was that the 

EPA Model was picking up only steam variable cost by PADD, not total cost. The error was marked and 

corrected. The effect was to add 0.02 c/gal to total sulfur reduction costs. The second error was that 

the Model’s formulae for steam generation capital cost contained a built in value of 0.04 for 

amortization instead of using the 0.11 value EPA used elsewhere in the model. Making this correction 

nearly tripled the steam capital cost contribution and raised total steam cost by over 20%. The effect on 

total gasoline sulfur reduction costs (10 ppm) was to add a further 0.03 c/gal. 

4.3.4.3 Hydrogen	Cost

In the EPA Model, hydrogen costs are developed for each PADD against a 2017 timeframe using data for 

hydrogen production from natural gas via steam reforming. We undertook an analysis of the hydrogen 

costs in the EPA Model. We checked costs calculated by the EPA against costs calculated using the data 

for the hydrogen plant in the EnSys WORLD Model. The results (PADD3 basis) came out within a few 

percent of the EPA figure for $/000 SCF H2. We also checked the EPA hydrogen cost on a $/BFOE basis 
EnSys	RTI	 2011

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against natural gas price on the same basis. The typical view is that hydrogen is around 2 times natural 

gas price on a BFOE basis. The EPA factor comes out at almost exactly 2. As a further check, we altered 

the EPA amortization factor from 0.11 to 0.243, a commonly used value for “hurdle rate” required 

capital recovery factor. Making this change altered the BFOE basis hydrogen to natural gas price ratio to 

2.37. This is essentially identical to the 2.38 factor quoted by Baker & O’Brien in a July 2011 report for 

the American Petroleum Institute on the costs of U.S. gasoline and sulfur reduction7. In all in all, we 

believe these cross-checks reinforce the values for hydrogen cost in the EPA Model. 

4.3.4.4 Cost	of	Octane	Loss

In the Model, the EPA gathered together a number of estimates for cost of octane. These included:

1. A stated historical cost of $5.29/bbl for premium – regular 2008-2011. This equates to around 

$0.90/bbl per octane

2. A "refiner cost” of $1.19/bbl. We are unclear whether this was per octane or PRM-UNL delta

3. Run results by PADD from the EPA GRTMPS LP model. These were, apparently for PRM-UNL, 

respectively: P1 $1.91, P2 $1.56, P3 $2.07, P4 $1.21, P5 ex CA $1.21, P5 CA $2.52, i.e. around 

$0.20 - $0.45/bbl per octane.

The LP results were lower - on a $/bbl per octane basis – than the historical levels. They showed highest 

costs for California and for PADD3 which did not seem entirely realistic. 

To cross-check these values, we looked at other sources. We examined available Bloomberg pricing 

data as EIA data do not now provide sufficient grade breakdown. The Bloomberg data show that:

 Costs per octane averaged around $0.45/bbl from 2000 through 2004 then rose and have since 

remained around the $1/bbl per octane range, broadly consistent with EPA’s stated historical 

$0.90/bbl per octane 

 On a nationwide basis, costs have changed little between 2005-2007 and 2008-2011 but there 

have been changes within regions. Octane costs in PADD1 (NYH) and PADD3 (USGC) and for 

PADD5 LA CARBOB have gone down whereas those for the Midwest and for PADD5 LA CG have 

risen. This may relate to changes in ethanol supply, demand, distribution and also blending 

methods

 

7

Potential Supply and Cost Impacts of Lower Sulfur, Lower RVP Gasoline, Baker & O’Brien, July 2011. Since Baker & 

O’Brien state “The cost of purchased hydrogen was assumed to be 2.38 times the cost of natural gas on an energyequivalent basis. Such a value has historically been adequate to encourage third-party companies to build 

hydrogen production capacity” we equate this to being based on a “hurdle rate” cost of capital. Their stated 

factors in building up capital recovery were 10% after-tax rate of return based on 15 year operating life, 10 year 

accelerated depreciation schedule, 38% tax rate and 2 year construction period. 
EnSys	RTI	 2011

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 In terms of regional differences, PADD1 costs have been consistently above PADD3 whereas the 

recent rise in PADD2 costs has moved those from below to above PADD3. PADD5 costs have 

fluctuated but have roughly in line with those for PADD3.

As a further cross-check, we examined results from EnSys WORLD Model cases from our 2010 Keystone 

XL study for the DOE and DOS. For the 2015 case, these showed costs ranging from a low of around 

$0.25/bbl per octane for PADD3 CG and $0.45/bbl for PADD3 RFG to $0.45/bbl for PADD1 RFG and 

around $0.40/bbl for PADD5 CG and $0.70/bbl per octane for PADD5 CARB RFG. In the 2020 case, the 

octane costs were appreciably lower. This would be expected since the cases assumed rising ethanol 

supply into gasoline over time in line with RFS-2. 

We were not able to test the effects of assuming different levels of octane cost in the Model. We 

understand, however, the EPA used relatively low per octane costs. We believe the above data could 

be useful in providing guidance to the EPA. It looks as though:

1. Costs will have declined by 2016/2017 because of rising ethanol production and moves to take 

full advantage of ethanol’s high octane. (This could be a factor in the historical versus LP 

results, i.e. if the real world distribution system was historically not taking full advantage of 

ethanol’s octane but the LP model did then that would account for real world octane costs 

significantly above LP results. As industry better optimizes blends over time to more fully 

apply ethanol’s high octane then octane costs should drop and real world versus LP results 

narrow.)

2. Comparison of recent real world costs with WORLD LP results would suggest that 2016/2017 

octane costs could be at least 50% less than those for 2008-2011, potentially even lower, i.e. 

somewhere in the $0.50 - $0.25/bbl national average per octane

3. Arguably, differences in octane costs by region would still apply, with PADD1 potentially 

around $0.10 - $0.20/bbl per octane above PADD3 and PADD’s 2 and 5 potentially broadly the 

same as PADD3 for lack of any ability to clearly differentiate. 

All of the above data and projections (aside possibly from the EPA GRTMPS LP results) were based on 

E10 and E85 blending, not E15. Moving to E15 would argue for octane costs at the lower end of the 

estimated ranges. 

4.3.4.5 E10/E15

As stated above, we understand that the EPA’s cost projections for gasoline sulfur reduction in the 

Model are based on presuming E15. The MathPro 2015 cases for the ICCT assumed E10 plus E85. We 

believe it would be useful if the Model could have the flexibility to examine the impacts of sulfur 

reduction at 10% as well as 15% ethanol. The effect would be to raise sulfur reduction costs as 

concentrations of FCC gasolines would be higher. 
EnSys	RTI	 2011

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4.4 Additional	Factors	Influencing	Costs

4.4.1 LSR	Sulfur	Reduction

LSR sulfur reduction is the second main factor applied in the Model to achieve gasoline pool sulfur 

reduction. We support the EPA view that this is a relatively low cost option and therefore likely to be 

employed. We briefly checked the EPA rationale for assessing, refinery by refinery, what if any LSR HDT 

capacity would be added and whether it would be revamp or new. Again, this logic was complex. In our 

view it works recognizing the limitations in our review.

We next focused on the LSR HDT costs in the Model. The base capital cost taken by EPA from 

Handwerk appears reasonable as does the hydrogen consumption. We note, however, that EPA do not 

appear to apply the Overdesign factor of 1.15 they hold in the Utility & Capital Costs page for either LSR 

HDT revamp or new unit or the 0.85 factor present for capacity utilization. We suggest EPA check this 

and apply at least the service factor if not both of these factors. To gauge the effect, EnSys applied both 

factors. 

4.4.2 Other

The EPA Model does not appear to explicitly consider cost factors outside of FCC gasoline and LSR 

desulfurization units. Arguably, there should be some small additions to acid gas and sulfur recovery 

plants although these might be considered part of offsites. 

 

4.5 Model	Results,	Proposed	Premise	Adjustments	and	Their	Impacts	

4.5.1 Results	from	Current	Cost	Model

The table below breaks out the impacts in the 10 ppm case of the changes we made or proposed to the 

Model. These included formula corrections and suggested changes to data values. As is evident, the 

effects are minor with the potential exception of changes to vendor capital cost, hydrogen consumption 

and related values8. As previously discussed, the need for and extent of any such modifications is the 

 

8

The capital cost impacts are based upon use of EPA’s 11% p.a. capital recovery / amortization factor. We note 

that, if the industry standard 24.3% is used – it is typically employed to reflect the “hurdle rate” of return for new 
EnSys	RTI	 2011

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subject, in large part, of obtaining further clarifications from the vendors regarding the data they 

supplied. Actual appropriate changes may be significantly lower than those indicated below. 

Summary of Impacts on Costs of Proposed Model Changes c/gal Total U.S. Gasoline

individual effect (10 ppm) cumulative effect (10 ppm)

Corrected steam cost lookup 

formula +0.02 +0.02

Corrected steam amortization 

formula +0.03 +0.05

Adjusted non PADD3 natural gas 

prices +0.02 +0.07

Vendor capital cost, hydrogen 

and related adjustments up to +0.26 up to +0.33

LSR HDT service and over design 

factor adjustments +0.03 +0.36

to 2.2 c/gal at 10 ppm and 2.54 at 5 ppm. Use of 24.3% arguably indicates the upper end of the range 

for estimated average costs. 

The data in the table represent only preliminary values prior to EPA’s further review and adjustments to 

the Model. Note, we did not test for the effects of potential changes in octane cost.

We would further point out that, at present, the Model only reports at the national level. We 

recommend that reporting be extended to the PADD level. This would both provide additional insights 

and add a form of sanity cross-checking based on the relative c/gal costs assessed by PADD. 

4.6 Detailed	Model	Integrity	Findings/Issues

The EPA requested that EnSys assess the integrity of the refinery-by-refinery cost model by working 

through the equations present in the spreadsheet. As mentioned in a prior Section, the Model version 

EnSys reviewed was titled as “Rev3” and dated December 1st 2011. Specifically one multi-page Excel 

workbook was provided for our review. As noted elsewhere, the Rev3.xls workbook linked to 7 external 

Excel workbooks. None of those was available or was included in our review. Our understanding from 

EPA was that the external files were not essential to our purposes. We did not observe any errors 

relating to these external links but were, of course, not able to cross-check and validate the links. 

The following describes our approach taken and specific findings. 

 

unit construction whereas EPA’s 11% reflects estimated long run achieved return on capital – then estimated total 

sulfur reduction costs rise by around 0.65 c/gal. 
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4.6.1 Approach	Employed	by	EnSys

The time available for EnSys to review the EPA Model was limited to 5 days (with 2 people reviewing). 

We were therefore not able to rigorously analyze and check every formula or parameter. We 

consequently focused first on what we considered were the key parameters that would have the most 

significant impacts on results, i.e. applying the EPA methodology as developed. That part of our analysis 

is the focus of Section 4. 

We used that analysis also as the basis for a more detailed probe. We tracked specific key formulae, 

such as for calculation of capital costs, in doing so finding certain errors as noted in Section 4. In 

addition, we tracked the full set of formulae for one refinery rigorously and spot-checked for others, in 

that regard finding no errors in the formulae we examined. 

4.6.2 General	Comments	on	Model	Structure

The above line of approach was consistent with our focus on factors which could impact cost results. A 

second focus of our review was on the quality of the Model in terms of its use of sound Excel modeling 

practices. In that regard, we believe the Model can be significantly improved. The following, based on 

our findings, is not necessarily an exhaustive list:

 the same data item appears to be entered in more than one place in the model

 at times data are labeled as say (2009) “capacity” when in fact the numbers represent actual 

(2009) charge rate. An example is Page T3, column R. It is under a heading for 2009 capacity 

whereas the values entered are 2009 charge rate

 while the spreadsheet does contain a number of defined names, this facility is generally not 

used in formulae; rather formulae generally contain only cell references and consequently are 

difficult to follow and more prone to error

 in numerous formulae, values are hard wired when, in our view, they should not be; for 

example, base unit capacities relating to data supplied by vendors are hardwired into capital 

cost calculation formulae rather than being explicitly referenced; capital cost power factors are 

hard wired in. This approach significantly increases the chance of errors, makes the Model 

more difficult to understand and review in terms of key premises and logic used and makes it 

more difficult to alter premises and test the effects of doing same 

 there is a near total lack of internal documentation including such useful items as Excel cell 

comments. 

Overall, these make the Model more difficult to adjust, cross-check and keep accurate; also to hand on 

efficiently and reliably to a new user. 
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4.6.3 Specific	Data	&	Equations	Integrity

4.6.3.1 Capital,	Fixed	&	Variable	Operating	Cost	Formulae

EnSys explicitly checked these key formulae item by item9. The formulae appear correct recognizing 

that the capital cost formulae contain hard wired values for vendor base unit capacity and for power 

factor for capital cost scaling base on actual estimated FCC gasoline treater capacity versus vendor base 

capacity. 

EnSys undertook its analysis using selected formulae in the COSTS 10ppm page. We spot checked 

additional formulae in the same page and also in the COSTS 5ppm page. The latter page appeared to be 

correctly picking up vendor-derived data for 5ppm (not 10ppm) cases. 

4.7 Potential	for	Model	Improvement

As stated at various points across Section 4, the Model as it stands today does contain a small number of

formula errors and a number of data values which warrant further review. EPA’s correction of these 

errors and review of selected data items should improve the Model. 

Specific opportunities exist in the form of adopting better practice and discipline regarding using explicit 

variables wherever possible, naming cells and ranges and using these in formulae, extending the use of 

LOOKUP and related formulae which tend to ensure correct values are produced and using cell 

comment and other techniques to establish and maintain better internal documentation. 

4.8 Utility	for	Forward	Looking	Regulatory	Analyses	

The EPA Refinery Cost Model is fundamentally a static analytical tool, although it can be updated to new 

historical base year data. It also is currently limited to addressing costs of gasoline sulfur reduction only. 

Thus, while it can make a contribution to EPA’s current assessment of the costs of potential Tier 3 

regulations, which could include RVP as well as sulfur reduction, the Model’s analytical scope is limited. 

Arguably, for rigorous analyses, the EPA has the choice of using either the Refinery Cost Model or LP 

modeling. Each method has its pros and cons. The former, as noted, is restricted in its scope and ability 

to look forward. The latter (LP) has the benefit that it can assess multiple regulatory changes and their 

interactions – not just one – and can and should take into account the changes that are likely to occur 

 

9

For instance the formulae in Columns BX through CB Page COST 10ppm. 
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across U.S. refining over the several years to the analytical time horizon. That said, at least equal rigor 

needs to be applied to an LP as to a spreadsheet model, in part to obviate the risk in an LP to under or 

over optimize and/or generate extreme solutions. Also, the spreadsheet model is able to compute 

(approximate) gasoline sulfur reduction costs by individual refinery whereas the LP will almost inevitably 

deal with aggregated groups of refineries. 

Given the EPA’s analytical timeframe of (around) 2017, to be realistic and defensible, any rigorous 

assessment of costs needs to take into consideration a range of developments – and uncertainties -

impacting U.S. refining. The following is a partial list:

 Current major projects under way at selected U.S. refineries that will add and modify capacity, 

including ability to process higher volumes of heavy Canadian crudes. (See below for a listing of 

current major projects.) 

 Flat to declining U.S. gasoline demand in association with rising ethanol supply; sensitivity of 

refining situation and sulfur recovery costs to actual levels of U.S. gasoline demand and future 

ethanol supply achieved

 Potential shifts over time in FCC feedstocks and operating modes, notably: shift towards more 

resid in FCC feed as VGO is increasingly “pulled away” to hydro-cracking units as demand for 

distillates grows, FCC catalyst/operating shifts to lower gasoline higher distillate (LCO) and also 

higher propane yields; potential resulting impacts on FCC gasoline qualities, volumes and thus 

concentration in the U.S. gasoline pool

 Extent to which current trends for growth in U.S. refined products exports will continue and 

their potential impacts on U.S. refining

 Potentially substantial changes in U.S. domestic oil liquids supply, both light sweet crudes from 

the Bakken , Eagle Ford, Niobrara, Utica shale and other plays and the potential impacts of rising 

NGL’s supply

 Potential for continuing growth in Canadian oil sands production and exports to the U.S.

 Sensitivity of U.S. crude slates, by region, to the above supply developments combined with 

logistics developments (Keystone XL and other projects that could influence crude dispositions 

especially to PADD3 refineries).

Without taking account of these and other factors, EPA analyses could either under or over state costs 

and/or be subject to criticism for lack of realism10. 

 

10 The changes in Lower 48 liquids production together with rising Canadian production are creating potentially 

fundamental – and rapid - shifts in the U.S. liquids balance with significant implications for U.S. refining. 
EnSys	RTI	 2011

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Major U.S. Refinery Projects

Refinery Crude capacity 

000bpd

Incremental heavy 

crude processing 

000bpd

Start up

WRB Refining Wood River Illinois 75 130 2011/12

WRB Refining Borger Texas 50 110 2011/12

Marathon Detroit Michigan 13 80 2H 2012

BP Whiting Indiana 35 260 2013

Motiva Port Arthur Texas 325 Up to 325 (1) 1H2012

Valero Sunray, Corpus Christi and Three Rivers Texas 

– minor debottlenecking to process additional Eagle 

Ford etc. 

1. Whether the newly expanded Motiva refinery will process primarily heavy Western Canadian or Saudi 

crudes has been the subject of recent debate.