*** Draft – Do Not Cite, Quote, or Release During Review *** 

Regulatory Impact Analysis 

Petroleum Refineries

New Source Performance Standards Ja 

January 2012 

U.S. Environmental Protection Agency 

Office of Air and Radiation 

Office of Air Quality Planning and Standards 

Research Triangle Park, NC 27711 

 
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ii 

CONTACT INFORMATION 

This document has been prepared by staff from the Office of Air Quality Planning and 

Standards, U.S. Environmental Protection Agency and RTI International. Questions related to 

this document should be addressed to Alexander Macpherson, U.S. Environmental Protection 

Agency, Office of Air Quality Planning and Standards, C445-B, Research Triangle Park, North 

Carolina 27711 (email: macpherson.alex@epa.gov). 

ACKNOWLEDGEMENTS

In addition to EPA staff from the Office of Air Quality Planning and Standards, 

personnel from RTI International contributed significant data and analysis to this document 

under contract number EP-D-06-003. 

 
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iii 

TABLE OF CONTENTS 

TABLE OF CONTENTS .................................................................................................................... III

LIST OF TABLES .............................................................................................................................. V

LIST OF FIGURES ........................................................................................................................... VI

1. EXECUTIVE SUMMARY ........................................................................................................ 1-1

1.1 INTRODUCTION ............................................................................................................................................ 1-1

1.2 REASON FOR TODAY’S ACTION: MARKET FAILURE OR OTHER SOCIAL PURPOSE ........................................ 1-2

1.3 RESULTS ...................................................................................................................................................... 1-2

1.4 REFERENCES ................................................................................................................................................ 1-3

2 INDUSTRY PROFILE ............................................................................................................. 2-1

2.1 INTRODUCTION ............................................................................................................................................ 2-1

2.2 THE SUPPLY SIDE ......................................................................................................................................... 2-1

2.2.1 Production Process, Inputs, and Outputs ........................................................................................... 2-1

2.2.2 Emissions and Controls in Petroleum Refining ................................................................................. 2-9

2.2.3 Costs of Production .......................................................................................................................... 2-10

2.3 THE DEMAND SIDE .................................................................................................................................... 2-14

2.3.1 Product Characteristics .................................................................................................................... 2-14

2.3.2 Uses and Consumers ........................................................................................................................ 2-14

2.3.3 Substitution Possibilities in Consumption ....................................................................................... 2-16

2.4 INDUSTRY ORGANIZATION ......................................................................................................................... 2-16

2.4.1 Market Structure .............................................................................................................................. 2-16

2.4.2 Characteristics of U.S. Petroleum Refineries and Petroleum Refining Companies ......................... 2-20

2.5 MARKETS ................................................................................................................................................... 2-27

2.5.1 U.S. Petroleum Consumption .......................................................................................................... 2-27

2.5.2 U.S. Petroleum Production .............................................................................................................. 2-33

2.5.3 International Trade ........................................................................................................................... 2-34

2.5.4 Market Prices ................................................................................................................................... 2-37

2.5.5 Profitability of Petroleum Refineries ............................................................................................... 2-38

2.5.6 Industry Trends ................................................................................................................................ 2-40

2.6 REFERENCES .............................................................................................................................................. 2-44

3 NSPS REGULATORY OPTIONS, COSTS AND EMISSION REDUCTIONS FROM COMPLYING 

WITH THE NSPS .......................................................................................................................... 3-1

4 ECONOMIC IMPACT ANALYSIS: METHODS AND RESULTS ................................................. 4-1

5 SMALL BUSINESS ANALYSIS AND EXECUTIVE ORDERS ..................................................... 5-1

5.1 RESULTS OF SMALL BUSINESS ANALYSIS .................................................................................................... 5-1

5.2 UNFUNDED MANDATES ............................................................................................................................... 5-1

5.3 ENVIRONMENTAL JUSTICE ........................................................................................................................... 5-1

6 HUMAN HEALTH BENEFITS OF EMISSIONS REDUCTIONS .................................................. 6-1

6.1 CALCULATION OF PM2.5-RELATED HUMAN HEALTH BENEFITS ................................................................... 6-1

6.2 SOCIAL COST OF CARBON AND GREENHOUSE GAS BENEFITS .................................................................... 6-14

6.3 ENERGY DISBENEFITS ................................................................................................................................ 6-17

6.4 TOTAL MONETIZED BENEFITS .................................................................................................................... 6-18

6.5 UNQUANTIFIED BENEFITS .......................................................................................................................... 6-18
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6.5.1 Additional SO2 and NO2 Benefits .................................................................................................... 6-19

6.5.2 Ozone Benefits ................................................................................................................................. 6-21

6.5.3 Visibility Impairment ....................................................................................................................... 6-21

6.6 CHARACTERIZATION OF UNCERTAINTY IN THE MONETIZED BENEFITS ...................................................... 6-22

6.7 REFERENCES .............................................................................................................................................. 6-27

7 COMPARISON OF BENEFITS AND COSTS ............................................................................. 7-1

APPENDIX A PARENT COMPANY INFORMATION FOR PETROLEUM REFINERIES ..................... A-1

 
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LIST OF TABLES 

Table 2-1. Types and Characteristics of Raw Materials used in Petroleum Refineries ....................................... 2-8

Table 2-2. Major Refinery Product Categories .................................................................................................... 2-8

Table 2-3. Labor, Material, and Capital Expenditures for Petroleum Refineries (NAICS 324110) .................. 2-12

Table 2-4. Costs of Materials Used in Petroleum Refining Industry ................................................................. 2-13

Table 2-5. Major Refinery Products .................................................................................................................. 2-15

Table 2-6. Market Concentration Measures of the Petroleum Refining Industry: 1985 to 2007 ....................... 2-19

Table 2-7. Number of Petroleum Refineries, by State ....................................................................................... 2-21

Table 2-8. Full Production Capacity Utilization Rates for Petroleum Refineries .............................................. 2-22

Table 2-9. Characteristics of Small Businesses in the Petroleum Refining Industry ......................................... 2-28

Table 2-10. Total Petroleum Products Supplied (millions of barrels per year) ................................................... 2-33

Table 2-11. U.S. Refinery and Blender Net Production (millions of barrels per year) ........................................ 2-34

Table 2-12. Value of Product Shipments of the Petroleum Refining Industry .................................................... 2-35

Table 2-13. Imports of Major Petroleum Products (millions of barrels per year) ................................................ 2-36

Table 2-14. Exports of Major Petroleum Products (millions of barrels per year) ................................................ 2-36

Table 2-15. Average Price of Major Petroleum Products Sold to End Users (cents per gallon) ......................... 2-37

Table 2-16. Producer Price Index Industry Data: 1995 to 2010 .......................................................................... 2-38

Table 2-17. Mean Ratios of Profit before Taxes as a Percentage of Net Sales for Petroleum Refiners, Sorted by 

Value of Assets ................................................................................................................................. 2-39

Table 2-18. Net Profit Margins for Publicly Owned, Small Petroleum Refiners: 2010 ...................................... 2-40

Table 2-19. Forecasted Average Price of Major Petroleum Products Sold to End Users in 2009 Currency (cents 

per gallon) ........................................................................................................................................ 2-41

Table 2-20. Total Petroleum Products Supplied (millions of barrels per year) ................................................... 2-41

Table 2-21. Selected Refinery Construction Projects: 2008–2014 ...................................................................... 2-42

Table 2-22. Full Production Capacity Utilization Rates for Petroleum Refineries .............................................. 2-43

Table 3-1. National Incremental Emission Reductions for Petroleum Refinery Flares Subject to Amended 

Standards Under 40 CFR part 60, subpart Ja (Fifth Year After Applicability Date) .......................... 3-2

Table 3-2. National Incremental Cost Impacts and Cost-Effectiveness for Petroleum Refinery Flares Subject to 

Amended Standards Under 40 CFR part 60, subpart Ja (Fifth Year After Applicability Date) ......... 3-2

Table 6-1: Human Health Effects of PM2.5 .......................................................................................................... 6-3

Table 6-2: General Summary of Monetized PM-Related Health Benefits Estimates for Petroleum Refineries 

NSPS Reconsideration (millions of 2006$)*

 .................................................................................... 6-11

Table 6-3: Summary of Reductions in Health Incidences from PM2.5 Benefits for Petroleum Refineries NSPS 

Reconsideration* .............................................................................................................................. 6-12

Table 6-4: All PM2.5 Benefits Estimates for the Petroleum Refineries NSPS Reconsideration at discount rates of 

3% and 7% in 2017 (in millions of 2006$)*..................................................................................... 6-13

Table 6-5. Social Cost of Carbon (SCC) Estimates (per tonne of CO2) for 2017a ............................................. 6-16

Table 6-6. Monetized SCC-Derived Benefits of CO2 Emission Reductions in 2017 (millions of 2006$)a,b ..... 6-17

Table 7-1. Summary of the Monetized Benefits, Social Costs, and Net Benefits for the Final Petroleum 

Refineries NSPS in 2017 (millions of 2006$)1

 ................................................................................... 7-1

Table A-1. Parent Company Information for Petroleum Refineries .................................................................... A-2
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LIST OF FIGURES 

Figure 2-1. Outline of the Refining Process ......................................................................................................... 2-3

Figure 2-2. Desalting Process ............................................................................................................................... 2-3

Figure 2-3. Atmospheric Distillation Process ....................................................................................................... 2-4

Figure 2-4. Vacuum Distillation Process .............................................................................................................. 2-5

Figure 2-5. Petroleum Refinery Expenditures .................................................................................................... 2-10

Figure 2-6. Employment Distribution of Companies Owning Petroleum Refineries (N=61) ............................ 2-23

Figure 2-7. Average Revenue of Companies Owning Petroleum Refineries by Employment (N=61) .............. 2-24

Figure 2-8. Revenue Distribution of Companies Owning Petroleum Refineries (N=61) ................................... 2-25

Figure 2-9. Total Petroleum Products Supplied (millions of barrels per year) ................................................... 2-32

Figure 6-1: Breakdown of Monetized PM2.5 Health Benefits using Mortality Function from Pope et al. (2002)6-10

Figure 6-2: Total Monetized PM2.5 Benefits of Final Petroleum Refineries Reconsideration in 2017 ............... 6-14

Figure 6-3: Breakdown of Monetized Benefits for Final Petroleum Refineries NSPS Reconsideration by Pollutant

 18

Figure 6-4. Percentage of Adult Population by Annual Mean PM2.5 Exposure in the Baseline ......................... 6-24

Figure 6-5. Cumulative Distribution of Adult Population by Annual Mean PM2.5 Exposure in the Baseline .... 6-25

Figure 7-1. Net Benefits for Final Petroleum Refineries NSPS Reconsideration at 3% discount rate* ............... 7-2

Figure 7-2. Net Benefits for Final Petroleum Refineries NSPS Reconsideration at 7% discount rate* ............... 7-3
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1. EXECUTIVE SUMMARY 

1.1 Introduction 

On June 24, 2008, EPA promulgated amendments to the Standards of Performance for 

Petroleum Refineries and new standards of performance for petroleum refinery process units 

constructed, reconstructed, or modified after May 14, 2007. EPA subsequently received three 

petitions for reconsideration of these final rules. On September 26, 2008, EPA granted 

reconsideration and issued a stay for the issues raised in the petitions regarding process heaters 

and flares. On December 22, 2008, EPA addressed those specific issues by proposing 

amendments to certain provisions for process heaters and flares. This final regulation includes 

emissions limits for new and modified/reconstructed sources, and these limits are set for sulfur 

dioxide (SO2), nitrogen oxides (NOx), volatile organic compounds (VOC), and other pollutants. 

The petroleum refining industry comprises establishments primarily engaged in refining 

crude petroleum into refined petroleum. Examples of refined petroleum products include 

gasoline, kerosene, asphalt, lubricants, solvents, and a variety of other products. Petroleum 

refining falls under the North American Industrial Classification System (NAICS) 324110. 

This regulatory impact analysis (RIA) was prepared in response to requirements under 

Executive Order 12866. The RIA presents the results of analyses undertaken in support of this 

final rule including compliance costs, benefits, economic impacts, and impacts to small 

businesses. This RIA is organized as follows: 

 Section 1: Executive Summary, 

 Section 2 and an Appendix A: Profile of the Petroleum Refinery Industry, 

 Section 3: NSPS Regulatory Alternatives, and Costs and Emission Reductions From 

Complying with the NSPS 

 Section 4: Economic Impacts of the NSPS, 

 Section 5: Potential Impacts on Small Businesses, 

 Section 6: Benefits of the NSPS, and 

 Section 7: Comparison of Benefits and Costs 
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1.2 Reason for Today’s Action: Market Failure or Other Social Purpose 

The petroleum refinery NSPS is of sufficient impact to be considered as falling under the 

requirements for Executive Order 12866 (OMB, 2003). This final regulation is being issued in 

response to a decision between U.S. EPA and various parties requiring review of the existing 

NSPS. Among the reasons a regulation such as this one may also be issued is to address market 

failure. The major types of market failure include: externality, market power, and inadequate or 

asymmetric information. Correcting market failures is a reason for regulation, but it is not the 

only reason. Other possible justifications include improving the functioning of government, 

removing distributional unfairness, or promoting privacy and personal freedom. 

1.3 Results 

EPA has characterized the facilities and companies potentially affected by the NSPS by 

examining existing refineries and the companies that own them. EPA projects that new refineries 

and processes will be similar to existing ones, and that the companies owning new sources will 

also be similar to the companies owning existing refineries. EPA has collected data on 148 

existing refineries, owned by 64 companies. Of the affected parent companies, thirty-six are 

identified as small entities based on the Small Business Administration size standard criteria for 

NAICS 324110, for they employ 1,500 or fewer employees. 

EPA estimates that complying with the final NSPS will have an annualized cost savings 

of approximately $79 million per year (2006 dollars) in 2017. Given that there are cost savings, 

EPA anticipates that the NSPS will have no negative impacts on the market for petroleum 

products. Based on sales data obtained for the affected small entities, as well as expected 

annualized cost savings, EPA estimates that the NSPS will not result in a SISNOSE (significant 

economic impact on a substantial number of small entities). 

In the year of full implementation (2017), EPA estimates that the total monetized benefits 

of the final NSPS are $270 million to $580 million and $240 million to $530 million, at 3% and 

7% discount rates, respectively (Table 1-1). All estimates are in 2006 dollars for the year 2017. 

Using alternate relationships between PM2.5 and premature mortality supplied by experts, higher 

and lower benefits estimates are plausible, but most of the expert-based estimates fall between 
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these estimates. In addition, direct exposure to SO2 and NOx benefits, ozone benefits, ecosystem 

benefits, and visibility benefits have not been monetized in this analysis. 

In the year of full implementation (2017), EPA estimates the net benefits of the final 

NSPS are $340 million to $660 million and $320 million to $610 million, at 3% and 7% discount 

rates, respectively (Table 1-1). All estimates are in 2006 dollars for the year 2017. 

Table 1-1. Summary of the Monetized Benefits, Social Costs, and Net Benefits for the 

Final Petroleum Refineries NSPS in 2017 (millions of 2006$)1

 3% Discount Rate 7% Discount Rate 

Final Major Source NESHAP 

Total Monetized Benefits2 $270 to $580 $240 to $530 

Total Compliance Costs3 -$79 -$79 

Net Benefits $340 to $660 $320 to $610 

Non-monetized Benefits 

Health effects from SO2, NO2, and ozone exposure 

Health effects from PM exposure from VOCs 

Ecosystem effects 

Visibility impairment 

1

All estimates are for the implementation year (2017), and are rounded to two significant figures. 2

 The total monetized benefits reflect the human health benefits associated with reducing exposure to PM2.5 through 

reductions of PM2.5 precursors such as NOx and SO2 as well as CO2 benefits. It is important to note that the 

monetized benefits do not include the reduced health effects from direct exposure to SO2 and NOx, ozone 

exposure, ecosystem effects, or visibility impairment. Human health benefits are shown as a range from Pope et 

al. (2002) to Laden et al. (2006). These models assume that all fine particles, regardless of their chemical 

composition, are equally potent in causing premature mortality because the scientific evidence is not yet 

sufficient to allow differentiation of effects estimates by particle type. The net present value of reduced CO2

emissions is calculated differently than other benefits. This table includes monetized climate benefits using the 

global average social cost of carbon (SCC) estimated at a 3 percent discount rate because the interagency 

workgroup deemed the SCC estimate at a 3 percent discount rate to be the central value. 

3 The engineering compliance costs are annualized using a 7 percent discount rate. 

1.4 References 

Laden, F., J. Schwartz, F.E. Speizer, and D.W. Dockery. 2006. Reduction in Fine Particulate Air 

Pollution and Mortality. American Journal of Respiratory and Critical Care Medicine. 173: 

667-672. 

Office of Management and Budget. Circular A-4, September 17, 2003. Available on the 

Internet at http://www.whitehouse.gov/omb/circulars_a004_a-4. 
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Pope, C.A., III, R.T. Burnett, M.J. Thun, E.E. Calle, D. Krewski, K. Ito, and G.D. Thurston. 

2002. “Lung Cancer, Cardiopulmonary Mortality, and Long-term Exposure to Fine 

Particulate Air Pollution.” Journal of the American Medical Association 287:1132-1141. 
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2 INDUSTRY PROFILE 

2.1 Introduction 

This industry profile of the petroleum refining industry provides information that will 

support this and subsequent regulatory impact analyses (RIAs) and economic impact analyses 

(EIAs) that will assess the impacts of these standards. 

At its core, the petroleum refining industry comprises establishments primarily engaged 

in refining crude petroleum into finished petroleum products. Examples of these petroleum 

products include gasoline, kerosene, asphalt, lubricants, and solvents, among others. 

Firms engaged in petroleum refining are categorized under the North American Industry 

Classification System (NAICS) code 324110. In 2010, 148 establishments owned by 64 parent 

companies were refining petroleum in the continental United States. In 2009, the petroleum 

refining industry shipped products valued at over $436 billion (U.S. Census Bureau, Sector 31: 

2009 and 2008). 

This industry profile report is organized as follows. Section 3.2 provides a detailed 

description of the inputs, outputs, and processes involved in petroleum refining. Section 3.3 

describes the applications and users of finished petroleum products. Section 3.4 discusses the 

organization of the industry and provides facility- and company-level data. In addition, small 

businesses are reported separately for use in evaluating the impact on small business to meet the 

requirements of the Small Business Regulatory Enforcement and Fairness Act (SBREFA). 

Section 3.5 contains market-level data on prices and quantities and discusses trends and 

projections for the industry. 

2.2 The Supply Side 

Estimating the economic impacts of any regulation on the petroleum refining industry 

requires a good understanding of how finished petroleum products are produced (the “supply 

side” of finished petroleum product markets). This section describes the production process used 

to manufacture these products as well as the inputs, outputs, and by-products involved. The 

section concludes with a description of costs involved with the production process. 

2.2.1 Production Process, Inputs, and Outputs 

Petroleum pumped directly out of the ground, known as crude oil, is a complex mixture 

of hydrocarbons (chemical compounds that consist solely of hydrogen and carbon) and various 

impurities such as salt. To manufacture the variety of petroleum products recognized in everyday 
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life, this tar-like mixture must be refined and processed over several stages. This section 

describes the typical stages involved in this process as well as the inputs and outputs. 

2.2.1.1 The Production Process 

The process of refining crude oil into useful petroleum products can be separated into two 

phases and a number of supporting operations. These phases are described in detail in the 

following section. In the first phase, crude oil is desalted and then separated into its various 

hydrocarbon components (known as “fractions”). These fractions include gasoline, kerosene, 

naphtha, and other products (EPA, 1995). 

In the second phase, the distilled fractions are converted into petroleum products (such as 

gasoline and kerosene) using three different types of downstream processes: combining, 

breaking, and reshaping (EPA, 1995). An outline of the refining process is presented in Figure 2-

1. 

Desalting. Before separation into fractions, crude oil is treated to remove salts, 

suspended solids, and other impurities that could clog or corrode the downstream equipment. 

This process, known as “desalting,” is typically done by first heating the crude oil, mixing it with 

process water, and depositing it into a gravity settler tank. Gradually, the salts present in the oil 

will be dissolved into the process water (EPA, 1995). After this takes place, the process water is 

separated from the oil by adding demulsifier chemicals (a process known as chemical separation) 

and/or by applying an electric field to concentrate the suspended water globules at the bottom of 

the settler tank (a process known as electrostatic separation). The effluent water is then removed 

from the tank and sent to the refinery wastewater treatment facilities (EPA, 1995). This process 

is illustrated in Figure 2-2. 
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Figure 2-1. Outline of the Refining Process 

Source: U.S. Department of Labor, Occupational Safety and Health Administration (OSHA). 2003. OSHA 

Technical Manual, Section IV: Chapter 2, Petroleum Refining Processes. TED 01-00-015. Washington, DC: U.S. 

DOL. Available at <http://www.osha.gov/dts/osta/otm/otm_iv/otm_iv_2.html>. As obtained on October 23, 2006. 

Figure 2-2. Desalting Process 

Source: U.S. Department of Labor, Occupational Safety and Health Administration (OSHA). 2003. OSHA 

Technical Manual, Section IV: Chapter 2, Petroleum Refining Processes. TED 01-00-015. Washington, DC: U.S. 

DOL. Available at <http://www.osha.gov/dts/osta/otm/otm_iv/otm_iv_2.html>. As obtained on October 23, 2006. 
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Atmospheric Distillation. The desalted crude oil is then heated in a furnace to 750°F and 

fed into a vertical distillation column at atmospheric pressure. After entering the tower, the 

lighter fractions flash into vapor and travels up the tower. This leaves only the heaviest fractions 

(which have a much higher boiling point) at the bottom of the tower. These fractions include 

heavy fuel oil and asphalt residue (EPA, 1995). 

As the hot vapor rises, its temperature is gradually reduced. Lighter fractions condense onto 

trays located at successively higher portions of the tower. For example, motor gasoline will 

condense at higher portion of the tower than kerosene because it condenses at lower temperatures. 

This process is illustrated in Figure 2-3. As these fractions condense, they will be drawn off their 

respective trays and potentially sent downstream for further processing (OSHA, 2003; EPA, 1995). 

Figure 2-3. Atmospheric Distillation Process 

Source: U.S. Department of Labor, Occupational Safety and Health Administration (OSHA). 2003. OSHA 

Technical Manual, Section IV: Chapter 2, Petroleum Refining Processes. TED 01-00-015. Washington, DC: U.S. 

DOL. Available at <http://www.osha.gov/dts/osta/otm/otm_iv/otm_iv_2.html>. As obtained on October 23, 2006. 

Vacuum Distillation. The atmospheric distillation tower cannot distil the heaviest 

fractions (those at the bottom of the tower) without cracking under requisite heat and pressure. 

So these fractions are separated using a process called vacuum distillation. This process takes 

place in one or more vacuum distillation towers and is similar to the atmospheric distillation 

process, except very low pressures are used to increase volatization and separation. A typical 

first-phase vacuum tower may produce gas oils or lubricating-oil base stocks (EPA, 1995). This 

process is illustrated in Figure 2-4. 
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Figure 2-4. Vacuum Distillation Process 

Source: U.S. Department of Labor, Occupational Safety and Health Administration (OSHA). 2003. OSHA 

Technical Manual, Section IV: Chapter 2, Petroleum Refining Processes. TED 01-00-015. Washington, DC: U.S. 

DOL. Available at <http://www.osha.gov/dts/osta/otm/otm_iv/otm_iv_2.html>. As obtained on October 23, 2006. 

Downstream Processing. To produce the petroleum products desired by the market 

place, most fractions must be further refined after distillation or “downstream.” These 

downstream processes change the molecular structure of the hydrocarbon molecules by breaking 

them into smaller molecules, joining them to form larger molecules, or shaping them into higher 

quality molecules (EPA, 1995). 

Downstream processes include thermal cracking, coking, catalytic cracking, catalytic 

hydrocracking, hydrotreating, alkylation, isomerization, polymerization, catalytic reforming, 

solvent extraction, merox, dewaxing, propane deasphalting and other operations (EPA, 1995). 

2.2.1.2 Supporting Operations 

In addition to the processes described above, there are other refinery operations that do 

not directly involve the production of hydrocarbon fuels, but serve in a supporting role. Some of 

the major supporting operations are described in this section. 

Wastewater Treatment. Petroleum refining operations produce a variety of wastewaters 

including process water (water used in process operations like desalting), cooling water (water 

used for cooling that does not come into direct contact with the oil), and surface water runoff 

(resulting from spills to the surface or leaks in the equipment that have collected in drains). 
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Wastewater typically contains a variety of contaminants (such as hydrocarbons, 

suspended solids, phenols, ammonia, sulfides, and other compounds) and must be treated before 

it is recycled back into refining operations or discharged. Petroleum refineries typically utilize 

two stages of wastewater treatment. In primary wastewater treatments, oil and solids present in 

the wastewater are removed. After this is completed, wastewater can be discharged to a publicly 

owned treatment facility or undergo secondary treatment before being discharged directly to 

surface water. In secondary treatment, microorganisms are used to dissolve oil and other organic 

pollutants that are present in the wastewater (EPA, 1995; OSHA, 2003). 

Gas Treatment and Sulfur Recovery. Petroleum refinery operations such as coking and 

catalytic cracking emit gases with a high concentration of hydrogen sulfide mixed with light 

refinery fuel gases (such as methane and ethane). Sulfur must be removed from these gases in 

order to comply with Clean Air Act’s SOx emission limits and to recover saleable elemental 

sulfur. 

Sulfur is recovered by first separating the fuel gases from the hydrogen sulfide gas. Once 

this is done, elemental sulfur is removed from the hydrogen sulfide gas using a recovery system 

known as the Claus Process. In this process, hydrogen sulfide is burned under controlled 

conditions producing sulfur dioxide. A bauxite catalyst is then used to react with the sulfur 

dioxide and the unburned hydrogen sulfide to produce elemental sulfur. However, the Claus 

process only removed 90% of the hydrogen sulfide present in the gas stream, so other processes 

must be used to recover the remaining sulfur (EPA, 1995). 

Additive Production. A variety of chemicals are added to petroleum products to 

improve their quality or add special characteristics. For example, ethers have been added to 

gasoline to increase octane levels and reduce CO emissions since the 1970s. 

The most common ether additives being used today are methyl tertiary butyl ether 

(MTBE), and tertiary amyl methyl ether (TAME). Larger refineries tend to manufacture these 

additives themselves by reacting isobutylene (a by-product of several refinery processes) with 

methanol (OSHA, 2003). 

Heat Exchangers, Coolers, and Process Heaters. Petroleum refineries require very 

high temperatures to perform many of their refining processes. To achieve these temperatures, 

refineries use fired heaters fueled by refinery or natural gas, distillate, and residual oils. This heat 

is managed through heat exchanges, where are composed of bundles of pipes, tubes, plate coils, 
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and other equipment that surround heating or cooling water, steam, or oil. Heat exchanges 

facilitate the indirect transfer of heat as needed (OSHA, 2003). 

Pressure Release and Flare Systems. As liquids and gases expand and contract through 

the refining process, pressure must be actively managed to avoid accident. Pressure-relief 

systems enable the safe handling of liquids and gases that that are released by pressure-relieving 

devices and blow-downs. According to the OSHA Technical Manual, “pressure relief is an 

automatic, planned release when operating pressure reaches a predetermined level. A blow-down 

normally refers to the intentional release of material, such as blow-downs from process unit 

startups, furnace blow-downs, shutdowns, and emergencies” (OSHA, 2003). 

Blending. Blending is the final operation in petroleum refining. It is the physical mixture 

of a number of different liquid hydrocarbons to produce final petroleum products that have 

desired characteristics. For example, additives such as ethers can be blended with motor gasoline 

to boost performance and reduce emissions. Products can be blended in-line through a manifold 

system, or batch blended in tanks and vessels (OSHA, 2003). 

2.2.1.3 Inputs 

The inputs in the production process of petroleum products include general inputs such as 

labor, capital, and water. The inputs specific to this industry are crude oil and the variety of 

chemicals used in producing petroleum products. These two specific inputs are discussed below. 

Crude Oil. Contrary to popular conception, crude oils are complex, heterogeneous 

mixtures. Crude oils contain many different hydrocarbon compounds that vary in appearance and 

composition from one oil field to another. An “average” crude oil contains about 84% carbon; 

14% hydrogen; and less than 2% sulfur, nitrogen, oxygen, metals, and salts (OSHA, 2003). 

In 2004, the petroleum refining industry used 5.6 billion barrels of crude oil in the 

production of finished petroleum products (EIA, 2005).1

Common Refinery Chemicals. In addition to crude oil, a variety of chemicals are used 

in the production of petroleum products. The specific chemicals used will depend on specific 

characteristics of the product in question. Table 2-1 lists the most common chemicals used by 

petroleum refineries, their characteristics, and their applications. 

 

1

 A barrel is a unit of volume that is equal to 42 U.S. gallons. 
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Table 2-1. Types and Characteristics of Raw Materials used in Petroleum Refineries 

Type Description 

Crude Oil Heterogeneous mixture of different hydrocarbon compounds. 

Oxygenates Substances which, when added to gasoline, increase the amount of oxygen in that 

gasoline blend. Ethanol, methyl tertiary butyl ether (MTBE), ethyl tertiary butyl 

ether (ETBE), and methanol are common oxygenates. 

Caustics Caustics are added to desalting water to neutralize acids and reduce corrosion. 

They are also added to desalted crude in order to reduce the amount of corrosive 

chlorides in the tower overheads. They are used in some refinery treating processes 

to remove contaminants from hydrocarbon streams. 

Leaded Gasoline Additives Tetraethyl lead (TEL) and tetramethyl lead (TML) are additives formerly used to 

improve gasoline octane ratings but are no longer in common use except in 

aviation gasoline 

Sulfuric Acid and 

Hydrofluoric Acid 

Sulfuric acid and hydrofluoric acid are used primarily as catalysts in alkylation 

processes. Sulfuric acid is also used in some treatment processes. 

Source: U.S. Department of Labor, Occupational Safety and Health Administration (OSHA). 2003. OSHA 

Technical Manual, Section IV: Chapter 2, Petroleum Refining Processes. TED 01-00-015. Washington, DC: U.S. 

DOL. Available at <http://www.osha.gov/dts/osta/otm/otm_iv/otm_iv_2.html>. As obtained on October 23, 2006. 

In 2004, the petroleum refining industry used 581 million barrels of natural gas liquids 

and other liquids in the production of finished petroleum products (EIA, 2005). 

2.2.1.4 Types of Product Outputs 

The petroleum refining industry produces a number of products that tend to fall into one 

of three categories: fuels, finished nonfuel products, and feedstock for the petrochemical 

industry. Table 2-2 briefly describes these product categories. A more detailed discussion of 

petroleum fuel products can be found in Section 3.3. 

Table 2-2. Major Refinery Product Categories 

Product Category Description 

Fuels Finished Petroleum products that are capable of releasing energy. These products 

power equipment such as automobiles, jets, and ships. Typical petroleum fuel 

products include gasoline, jet fuel, and residual fuel oil. 

Finished nonfuel products Petroleum products that are not used for powering machines or equipment. These 

products typically include asphalt, lubricants (such as motor oil and industrial 

greases), and solvents (such as benzene, toluene, and xylene). 

Feedstock Many products derived from crude oil refining, such as ethylene, propylene, 

butylene, and isobutylene, are primarily intended for use as petrochemical 

feedstock in the production of plastics, synthetic fibers, synthetic rubbers, and other 

products. 

Source: U.S. Department of Labor, Occupational Safety and Health Administration (OSHA). 2003. OSHA 

Technical Manual, Section IV: Chapter 2, Petroleum Refining Processes. TED 01-00-015. Washington, DC: U.S. 

DOL. Available at <http://www.osha.gov/dts/osta/otm/otm_iv/otm_iv_2.html>. As obtained on October 23, 2006. 
*** Draft – Do Not Cite, Quote, or Release During Review ***

2-9 

2.2.2 Emissions and Controls in Petroleum Refining 

Petroleum refining leads to emissions of metals; spent acids; numerous toxic organic 

compounds; and gaseous pollutants, including carbon monoxide (CO), sulfur oxides, (SOx), 

nitrogen oxides (NOx), particulates, ammonia (NH3), hydrogen sulfide (H2S), and volatile 

organic compounds (VOCs). 

2.2.2.1 Gaseous and VOC Emissions 

As previously mentioned, CO, SOx, NOx, NH3, and H2S emissions are produced along 

with petroleum products. Sources of these emissions from refineries include fugitive emissions 

of the volatile constituents in crude oil and its fractions, emissions from the burning of fuels in 

process heaters, and emissions from the various refinery processes themselves. 

Fugitive emissions occur as a result of leaks throughout the refinery. Although individual 

leaks may be small, the sum of all leaks can result in a lot of hazardous emissions. These 

emissions can be reduced by purchasing leak-resistant equipment and maintaining an ongoing 

leak detection and repair program (EPA, 1995). 

The numerous process heaters used in refineries to heat process streams or to generate 

steam (boilers) for heating or other uses can be potential sources of SOx, NOx, CO, and 

hydrocarbons emissions. Emissions are low when process heaters are operating properly and 

using clean fuels such as refinery fuel gas, fuel oil, or natural gas. However, if combustion is not 

complete, or the heaters are fueled using fuel pitch or residuals, emissions can be significant 

(EPA, 1995). 

The majority of gas streams exiting each refinery process contain varying amounts of 

refinery fuel gas, H2S, and NH3. These streams are directed to the gas treatment and sulfur 

recovery units described in the previous section. Here, refinery fuel gas and sulfur are recovered 

using a variety of processes. These processes create emissions of their own, which normally 

contain H2S, SOx, and NOx gases (EPA, 1995). 

Emissions can also be created by the periodic regeneration of catalysts that are used in 

downstream processes. These processes generate streams that may contain relatively high levels 

of CO, particulates, and VOCs. However, these emissions are treated before being discharged to 

the atmosphere. First, the emissions are processed through a CO boiler to burn CO and any 

VOCs, and then through an electrostatic precipitator or cyclone separator to remove particulates 

(EPA, 1995). 
*** Draft – Do Not Cite, Quote, or Release During Review ***

2-10 

2.2.2.2 Wastewater and Other Wastes 

Petroleum refining operations produce a variety of wastewaters including process water 

(water used in process operations like desalting), cooling water (water used for cooling that does 

not come into direct contact with the oil), and surface water runoff (resulting from spills to the 

surface or leaks in the equipment that have collected in drains). This wastewater typically 

contains a variety of contaminants (such as hydrocarbons, suspended solids, phenols, NH3, 

sulfides, and other compounds) and is treated in on-site facilities before being recycled back into 

the production process or discharged. 

Other wastes include forms of sludges, spent process catalysts, filter clay, and incinerator 

ash. These wastes are controlled through a variety of methods including incineration, land filling, 

and neutralization, among other treatment methods (EPA, 1995). 

2.2.3 Costs of Production 

Between 1995 and 2009, expenditures on input materials accounted for the largest cost to 

petroleum refineries—amounting to 95% of total expenses (Figure 2-5). These material costs 

included the cost of all raw materials, containers, scrap, and supplies used in production or repair 

during the year, as well as the cost of all electricity and fuel consumed. 

Average Percentage 

(1995–2009) 

Figure 2-5. Petroleum Refinery Expenditures 

Sources: U.S. Department of Commerce, Bureau of the Census. 2007. 2006 Annual Survey of Manufactures. 

Obtained through American Fact Finder Database 

<http://factfinder.census.gov/home/saff/main.html?_lang=en>. 
*** Draft – Do Not Cite, Quote, or Release During Review ***

2-11 

 U.S. Department of Commerce, Bureau of the Census. 2006. 2005 Annual Survey of Manufactures. 

M05(AS)-1. Washington, DC: Government Printing Office. Available at 

<http://www.census.gov/prod/2006pubs/ 

 U.S. Department of Commerce, Bureau of the Census. 2003a. 2001 Annual Survey of Manufactures. 

M01(AS)-1. Washington, DC: Government Printing Office. Available at 

<http://www.census.gov/prod/2003pubs/ 

 U.S. Department of Commerce, Bureau of the Census. 2001. 1999 Annual Survey of Manufactures. 

M99(AS)-1 (RV). Washington, DC: Government Printing Office. Available at 

<http://www.census.gov/prod/2001pubs/ 

 U.S. Department of Commerce, Bureau of the Census. 1998. 1996 Annual Survey of Manufactures. 

M96(AS)-1 (RV). Washington, DC: Government Printing Office. Available at 

<http://www.census.gov/prod/3/98pubs/ 

 U.S. Department of Commerce, Bureau of the Census. 1997. 1995 Annual Survey of Manufactures. 

M95(AS)-1. Washington, DC: Government Printing Office. Available at 

<http://www.census.gov/prod/2/manmin/ 

U.S. Census Bureau, American FactFinder; “Sector 31: Annual Survey of Manufactures: 

General Statistics: Statistics for Industry Groups and Industries: 2009 and 2008 “ Release Date: 

12/3/10; (Data accessed on 10/10/11). [Source for 2008 and 2009 numbers] 

http://factfinder.census.gov/servlet/IBQTable?_bm=y&-NAICSASM=324110&-ds_name=

AM0931GS101&-ib_type=NAICSASM&-_industry=324110&-_lang=en

U.S. Census Bureau, American FactFinder; “Sector 31: Manufacturing: Industry Series: 

Detailed Statistics by Industry for the United States: 2007” Release Date 10/30/09; (Data accessed 

on 10/11/11). [Source for 2007 numbers] http://factfinder.census.gov/servlet/IBQTable?_bm=y&-

geo_id=01000US&-ds_name=EC0731I1&-NAICS2007=324110&-_lang=en

Labor and capital accounted for the remaining expenses faced by petroleum refiners. 

Capital expenditures include permanent additions and alterations to facilities and machinery and 

equipment used for expanding plant capacity or replacing existing machinery. A detailed 

breakdown of how much petroleum refiners spent on each of these factors of production over 

this 15-year period is provided in Table 2-3. A more exhaustive assessment of the costs of 

materials used in petroleum refining is provided in Table 2-4. 
*** Draft – Do Not Cite, Quote, or Release During Review ***

2-12 

Table 2-3. Labor, Material, and Capital Expenditures for Petroleum Refineries 

(NAICS 324110) 

 Payroll ($millions) Materials ($millions) Total Capital ($millions) 

Year Reported 2005 Reported 2005 Reported 2005 

1995 3,791 4,603 112,532 136,633 5,937 7,209 

1996 3,738 4,435 132,880 157,658 5,265 6,247 

1997 3,885 4,595 127,555 150,865 4,244 5,020 

1998 3,695 4,415 92,212 110,187 4,169 4,982 

1999 3,983 4,682 114,131 134,146 3,943 4,635 

2000 3,992 4,509 180,568 203,967 4,685 5,292 

2001 4,233 4,743 158,733 177,838 6,817 7,638 

2002 4,386 4,947 166,368 187,646 5,152 5,811 

2003 4,752 5,227 185,369 203,893 6,828 7,510 

2004 5,340 5,635 251,467 265,369 6,601 6,966 

2005 5,796 5,796 345,207 345,207 10,525 10,525 

2006 5,984 5,751 396,980 381,546 11,175 10,741 

2007 6,357 5,885 470,946 435,965 17,105 15,834 

2008 6,313 5,415 649,784 557,380 17,660 15,148 

2009 6,400 5,776 398,679 359,790 16,824 15,183 

Note: Adjusted for inflation using the producer price index industry for total manufacturing industries (Table 5-6). 

Sources: U.S. Department of Commerce, Bureau of the Census. 2007. 2006 Annual Survey of Manufactures. Obtained 

through American Fact Finder Database <http://factfinder.census.gov/home/saff/main.html?_lang=en>. 

 U.S. Department of Commerce, Bureau of the Census. 2006. 2005 Annual Survey of Manufactures. M05(AS)-1. 

Washington, DC: Government Printing Office. Available at <http://www.census.gov/prod/2006pubs/ 

am0531gs1.pdf>. As obtained on October 23, 2007.

 U.S. Department of Commerce, Bureau of the Census. 2003a. 2001 Annual Survey of Manufactures. M01(AS)-1. 

Washington, DC: Government Printing Office. Available at <http://www.census.gov/prod/2003pubs/ 

m01as-1.pdf>. As obtained on October 23, 2006. 

 U.S. Department of Commerce, Bureau of the Census. 2001. 1999 Annual Survey of Manufactures. M99(AS)-1 

(RV). Washington, DC: Government Printing Office. Available at <http://www.census.gov/prod/2001pubs/ 

m99-as1.pdf>. As obtained on October 23, 2006. 

 U.S. Department of Commerce, Bureau of the Census. 1998. 1996 Annual Survey of Manufactures. M96(AS)-1 

(RV). Washington, DC: Government Printing Office. Available at <http://www.census.gov/prod/3/98pubs/ 

m96-as1.pdf>. As obtained on October 23, 2006. 

 U.S. Department of Commerce, Bureau of the Census. 1997. 1995 Annual Survey of Manufactures. M95(AS)-1. 

Washington, DC: Government Printing Office. Available at <http://www.census.gov/prod/2/manmin/ 

asm/m95as1.pdf>. As obtained on October 23, 2006. 

 U.S. Census Bureau, American FactFinder; “Sector 31: Annual Survey of Manufactures: General Statistics: 

Statistics for Industry Groups and Industries: 2009 and 2008 “ Release Date: 12/3/10; (Data accessed on 

10/10/11). [Source for 2008 and 2009 numbers] http://factfinder.census.gov/servlet/IBQTable?_bm=y&-

NAICSASM=324110&-ds_name=AM0931GS101&-ib_type=NAICSASM&-_industry=324110&-_lang=en

 U.S. Census Bureau, American FactFinder; “Sector 31: Manufacturing: Industry Series: Detailed Statistics by 

Industry for the United States: 2007” Release Date 10/30/09; (Data accessed on 10/11/11). [Source for 2007 

numbers] <http://factfinder.census.gov/servlet/IBQTable?_bm=y&-geo_id=01000US&-ds_name=EC0731I1&-

NAICS2007=324110&-_lang=en> 
*** Draft – Do Not Cite, Quote, or Release During Review ***

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Table 2-4. Costs of Materials Used in Petroleum Refining Industry 

 2007 2002 

Material 

Delivered 

Cost ($103) 

Percentage 

of Material 

Costs 

Delivered 

Cost ($103) 

Percentage 

of Material 

Costs 

Petroleum Refineries NAICS 324110 

Total materials 440,165,193 100.00% 157,415,200 100.00% 

Domestic crude petroleum, including lease 

condensate 

133,567,383 30.3% 63,157,497 40.1% 

Foreign crude petroleum, including lease 

condensate 

219,780,279 49.9% 69,102,574 43.9% 

Foreign unfinished oils (received from 

foreign countries for further processing) 

D 2,297,967 1.5% 

Ethane (C2) (80% purity or more) — D 

Propane (C3) (80% purity or more) — 118,257 0.1% 

Butane (C4) (80% purity or more) 7,253,910 1.7% 1,925,738 1.2% 

Gas mixtures (C2, C3, C4) — 1,843,708 1.2% 

Isopentane and natural gasoline 5,117,182 1.2% 810,530 0.5% 

Other natural gas liquids, including plant 

condensate 

3,356,718 0.8% 455,442 0.3% 

Toluene and xylene (100% basis) 1,801,972 0.4% 159,563 0.1% 

Additives (including antioxidants, 

antiknock compounds, and inhibitors) 

D 40,842 0.0% 

Other additives (including soaps and 

detergents) 

— 709 0.0% 

Animal and vegetable oils — D 

Chemical catalytic preparations D D 

Fats and oils, all types, purchased 87,038 0.0% — — 

Sodium hydroxide (caustic soda) (100% 

NaOH) 

209,918 0.1% 129,324 0.1% 

Sulfuric acid, excluding spent (100% 

H2SO4) 

67,458 0.0% 189,912 0.1% 

Metal containers D 9,450 0.0% 

Plastics containers D D 

Paper and paperboard containers 1,819 0.0% D 

Cost of materials received from petroleum 

refineries and lube manufacturers 

20,951,741 4.8% 8,980,758 5.7% 

All other materials and components, parts, 

containers, and supplies 

24,839,320 5.6% 5,722,580 3.6% 

Materials, ingredients, containers, and 

supplies 

4,745,614 1.1% 576,175 0.4% 

Sources: U.S. Department of Commerce, Bureau of the Census. 2004. 2002 Economic Census, Industry Series—

Shipbuilding and Repair. Washington, DC: Government Printing Office. Available at 

<http://www.census.gov/prod/ec02/ec0231i324110.pdf>. As obtained on October 23, 2006. 

 U.S. Census Bureau, American FactFinder; “Sector 31: Manufacturing: Industry Series: Materials 

 Consumed by Kind for the United States: 2007” Release Date 10/30/09; (Data accessed on 10/11/11). [

 Source for 2007 numbers] <http://factfinder.census.gov/servlet/IBQTable?_bm=y&-ds_name=EC0731I3&-

 NAICS2007=324110&-ib_type=NAICS2007&-geo_id=&-_industry=324110&-_lang=en&-

 fds_name=EC0700A1> 
*** Draft – Do Not Cite, Quote, or Release During Review ***

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2.3 The Demand Side 

Estimating the economic impact the regulation will have on the petroleum refining 

industry also requires characterizing various aspects of the demand for finished petroleum 

products. This section describes the characteristics of finished petroleum products, their uses and 

consumers, and possible substitutes. 

2.3.1 Product Characteristics 

Petroleum refining firms produce a variety of different products. The characteristics these 

products possess largely depend on their intended use. For example, the gasoline fueling our 

automobiles has different characteristics than the oil lubricating the car’s engine. However, as 

discussed in Section 3.1.4, finished petroleum products can be categorized into three broad 

groups based on their intended uses (EIA, 1999a): 

 fuels—petroleum products that are capable of releasing energy such as motor 

gasoline 

 nonfuel products—petroleum products that are not used for powering machines or 

equipment such as solvents and lubricating oils 

 petrochemical feedstocks—petroleum products that are used as a raw material in the 

production of plastics, synthetic rubber, and other goods 

A list of selected products from each of these groups is presented in Table 2-5 along with a 

description of each product’s characteristics and primary uses. 

2.3.2 Uses and Consumers 

Finished petroleum products are rarely consumed as final goods in themselves. Instead, 

they are used as primary inputs in the creation of a vast number of other goods and services. For 

example, goods created from petroleum products include fertilizers, pesticides, paints, thinners, 

cleaning fluids, refrigerants, and synthetic fibers (EPA, 1995). Similarly, fuels made from 

petroleum are used to run vehicles and industrial machinery and generate heat and electrical 

power. As a result, the demand for many finished petroleum products is derived from the 

demand for the goods and services they are used to create. 

The principal end users of petroleum products can be separated into five sectors: 

 Residential sector—private homes and residences 

 Industrial sector—manufacturing, construction, mining, agricultural, and forestry 

establishments 

 Transportation sector—private and public vehicles that move people and 

commodities such as automobiles, ships, and aircraft 
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2-15 

 Commercial sector—nonmanufacturing or nontransportation business establishments 

such as hotels, restaurants, retail stores, religious and nonprofit organizations, as well 

federal, state, and local government institutions 

 Electric utility sector—privately and publicly owned establishments that generate, 

transmit, distribute, or sell electricity (primarily) to the public; nonutility power 

producers are not included in this sector 

Table 2-5. Major Refinery Products 

Product Description 

Fuels 

Gasoline A blend of refined hydrocarbons, motor gasoline ranks first in usage among petroleum 

products. It is primarily used to fuel automobiles and lightweight trucks as well as 

boats, recreational vehicles, lawn mowers, and other equipment. Other forms of 

gasoline include Aviation gasoline, which is used to power small planes. 

Kerosene Kerosene is a refined middle-distillate petroleum product that finds considerable use 

as a jet fuel. Kerosene is also used in water heaters, as a cooking fuel, and in lamps. 

Liquefied petroleum gas 

(LPG) 

LPG consists principally of propane (C3H8) and butane (C4H10). It is primarily used 

as a fuel in domestic heating, cooking, and farming operations. 

Distillate fuel oil Distillate fuel oil includes diesel oil, heating oils, and industrial oils. It is used to 

power diesel engines in buses, trucks, trains, automobiles, as well as other machinery. 

Residual fuels Residual fuels are the fuels distilled from the heavier oils that remain after 

atmospheric distillation, they find their primary use generating electricity in electric 

utilities. However, residual fuels can also be used as fuel for ships, industrial boiler 

fuel, and commercial heating fuel. 

Petroleum coke Coke is a high carbon residue that is the final product of thermal decomposition in the 

condensation process in cracking. Coke can be used as a low-ash solid fuel for power 

plants. 

Finished Nonfuel Products 

Coke In addition to use as a fuel, petroleum coke can be used a raw material for many 

carbon and graphite products such as furnace electrodes and liners. 

Asphalt Asphalt, used for roads and roofing materials, must be inert to most chemicals and 

weather conditions. 

Lubricants Lubricants are the result of a special refining process that produce lubricating oil base 

stocks, which are mixed with various additives. Petroleum lubricating products 

include spindle oil, cylinder oil, motor oil, and industrial greases. 

Solvents A solvent is a fluid that dissolves a solid, liquid, or gas into a solution. Petroleum 

based solvents, such as Benzyme, are used to manufacture detergent and synthetic 

fibers. Other solvents include toluene and xylene. 

Feedstock 

Ethylene Ethylene is the simplest alkene and has the chemical formula C2H4. It is the most 

produced organic compound in the world and it is used in the production of many 

products. For example, one of ethylene’s derivatives is ethylene oxide, which is a 

primary raw material in the production of detergents. 

Propylene Propylene is an organic compound with the chemical formula C3H6. It is primarily 

used the production of polypropylene, which is used in the production of food 

packaging, ropes, and textiles. 

Sources: U.S. Department of Labor, Occupational Safety and Health Administration (OSHA). 2003. OSHA 

Technical Manual, Section IV: Chapter 2, Petroleum Refining Processes. TED 01-00-015. Washington, DC: U.S. 

DOL. Available at <http://www.osha.gov/dts/osta/otm/otm_iv/otm_iv_2.html>. As obtained on October 23, 2006. 
*** Draft – Do Not Cite, Quote, or Release During Review ***

2-16 

 U.S. Department of Energy, Energy Information Administration (EIA). 1999. 

Of these end users, the transportation sector consumes the largest share of petroleum 

products, accounting for 67% of total consumption in 2005 (EIA, 2006a). In fact, petroleum 

products like motor gasoline, distillate fuel, and jet fuel provide virtually all of the energy 

consumed in the transportation sector (EIA, 1999a). 

Of the three petroleum product categories, end-users primarily consume fuel. Fuel 

products account for 9 out of 10 barrels of petroleum used in the United States (EIA, 1999a). In 

2005, motor gasoline alone accounted for 49% of demand for finished petroleum products (EIA, 

2006a). 

2.3.3 Substitution Possibilities in Consumption 

A major influence on the demand for finished petroleum products is the availability of 

substitutes. In some sectors, like the transportation sector, it is currently difficult to switch 

quickly from one fuel to another without costly and irreversible equipment changes, but other 

sectors can switch relatively quickly and easily (EIA, 1999a). 

For example, equipment at large manufacturing plants often can use either residual fuel 

oil or natural gas. Often coal and natural gas can be easily substituted for residual fuel oil at 

electricity utilities. As a result, we would expect demand in these industries to be more sensitive 

to price (in the short run) than in others (EIA, 1999a). 

However, over time, demand for petroleum products could become more elastic. For 

example, automobile users could purchase more fuel-efficient vehicles or relocate to areas that 

would allow them to make fewer trips. Technological advances could also create new products 

that compete with petroleum products that currently have no substitutes. An example of such a 

technological advance would be the invention of ethanol (an alcohol produced from biomass), 

which can substitute for gasoline in spark-ignition motor vehicles (EIA, 1999a). 

2.4 Industry Organization 

This section examines the organization of the U.S. petroleum refining industry, including 

market structure, firm characteristics, plant location, and capacity utilization. Understanding the 

industry’s organization helps determine how it will be affected by new emissions standards. 

2.4.1 Market Structure 

Market structure characterizes the level and type of competition among petroleum 

refining companies and determines their power to influence market prices for their products. For 
*** Draft – Do Not Cite, Quote, or Release During Review ***

2-17 

example, if an industry is perfectly competitive, then individual producers cannot raise their 

prices above the marginal cost of production without losing market share to their competitors. 

Understanding pricing behavior in the petroleum refining industry is crucial for performing 

subsequent EIAs. 

According to basic microeconomic theory, perfectly competitive industries are 

characterized by unrestricted entry and exit of firms, large numbers of firms, and undifferentiated 

(homogenous) products being sold. Conversely, imperfectly competitive industries or markets 

are characterized by barriers to entry and exit, a smaller number of firms, and differentiated 

products (resulting from either differences in product attributes or brand name recognition of 

products). This section considers whether the petroleum refining industry is competitive based 

on these three factors. 

2.4.1.1 Barriers to Entry 

Firms wanting to enter the petroleum refining industry may face at least two major 

barriers to entry. First, according to a 2004 Federal Trade Commission staff study, there are 

significant economies of scale in petroleum refinery operations. This means that costs per unit 

fall as a refinery produces more finished petroleum products. As a result, new firms that must 

produce at relatively low levels will face higher average costs than firms that are established and 

produce at higher levels, which will make it more difficult for these new firms to compete 

(Nicholson, 2005). This is known as a technical barrier to entry. 

Second, legal barriers could also make it difficult for new firms to enter the petroleum 

refining industry. The most common example of a legal barrier to entry is patents—intellectual 

property rights, granted by the government, that give exclusive monopoly to an inventor over his 

invention for a limited time period. In the petroleum refining industry, firms rely heavily on 

process patents to appropriate returns from their innovations. As a result, firms seeking to enter 

the petroleum refining industry must develop processes that respect the novelty requirements of 

these patents, which could potentially make entry more difficult for new firms (Langinier, 2004). 

A second example of a legal barrier would be environmental regulations that apply only to new 

entrants or new pollution sources. Such regulations would raise the operating costs of new firms 

without affecting the operating costs of existing ones. As a result, new firms may be less 

competitive. 

Although neither of these barriers is impossible for new entrants to overcome, they can 

make it more difficult for new firms to enter the market for manufactured petroleum products. As 

a result, existing petroleum refiners could potentially raise their prices above competitive levels 
*** Draft – Do Not Cite, Quote, or Release During Review ***

2-18 

with less worry about new firms entering the market to compete away their customers with lower 

prices. It was not possible during this analysis to quantify how significant these barriers would be 

for new entrants or what effect they would have on market prices. However, existing firms 

would still face competition from each other. In an unconcentrated industry, competition among 

existing firms would work to keep prices at competitive levels. 

2.4.1.2 Measures of Industry Concentration 

Economists often use a variety of measures to assess the concentration of a given 

industry. Common measures include four-firm concentration ratios (CR4), eight-firm 

concentration ratios (CR8), and Herfindahl-Hirschmann indexes (HHI). The CR4s and CR8s 

measure the percentage of sales accounted for by the top four and eight firms in the industry. The 

HHIs are the sums of the squared market shares of firms in the industry. These measures of 

industry concentrated are reported for the petroleum refining industry (NAICS 324110) in Table 

2-6 for selected years between 1985 and 2007. 

Between 1990 and 2000, the HHI rose from 437 to 611, which indicates an increase in 

market concentration over time. This increase is partially due to merger activity during this time 

period. Between 1990 and 2000, over 2,600 mergers occurred across the petroleum industry; 

13% of these mergers occurred in the industry’s refining and marketing segments (GAO, 2007). 

From 2000 to 2007 the HHI rose again. 

Unfortunately, there is no objective criterion for determining market structure based on 

the values of these concentration ratios. However, accepted criteria have been established for 

determining market structure based on the HHIs for use in horizontal merger analyses (U.S. 

Department of Justice and the Federal Trade Commission, 1992). According to these criteria, 

industries with HHIs below 1,000 are considered unconcentrated (i.e., more competitive); 

industries with HHIs between 1,000 and 1,800 are considered moderately concentrated (i.e., 

moderately competitive); and industries with higher HHIs are considered heavily concentrated. 

Based on this criterion, the petroleum refining industry continues to be unconcentrated even in 

recent years. 

A more rigorous examination of market concentration was conducted in a 2004 Federal 

Trade Commission (FTC) staff study. This study explicitly accounted for the fact that a refinery 

in one geographic region may not exert competitive pressure on a refinery in another region if 

transportation costs are high. This was done by comparing HHIs across Petroleum 

Administration for Defense Districts (PADDs). PADDs separate the United States into five 

geographic regions or districts. They were initially created during World War II to help manage 
*** Draft – Do Not Cite, Quote, or Release During Review ***

2-19 

the allocation of fuels during wartime. However, they have remained in use as a convenient way 

of organizing petroleum market information (FTC, 2004). 

Table 2-6. Market Concentration Measures of the Petroleum Refining Industry: 1985 to 

2007 

Measure 1985 1990 1996 2000 2001 2002 2003 2007 

Herfindahl-Hirschmann Index 

(HHI) 

493 437 412 611 686 743 728 807 

Four-firm concentration ratio (CR4) 34.4 31.4 27.3 40.2 42.5 45.4 44.4 47.5 

Eight-firm concentration ratio 

(CR8) 

54.6 52.2 48.4 61.6 67.2 70.0 69.4 73.1 

Sources: Federal Trade Commission (FTC). 2004. “The Petroleum Industry: Mergers, Structural Change, and 

Antitrust Enforcement.” Available at <http://www.ftc.gov/opa/2004/08/oilmergersrpt.shtm>. As obtained on 

February 6, 2007. 

 U.S. Census Bureau, American FactFinder; “Sector 31: Manufacturing: Subject Series: Concentration Ratios: 

Share of Value of Shipments Accounted for by the 4, 8, 20, and 50 Largest Companies for Industries: 2007 “ 

Release Date 1/7/2011; (Data accessed on 10/12/11) [Source for 2007 

numbers]<http://factfinder.census.gov/servlet/IBQTable?_bm=y&-ds_name=EC0731SR12&-

NAICS2007=324110&-ib_type=NAICS2007&-NAICS2007sector=*6&-industrySel=324110&-geo_id=&-

_industry=324110&-_lang=en> 

This study concluded that these geographic markets were not highly concentrated. 

PADDs I, II, and III (East Coast, Midwest, and Gulf Coast) were sufficiently connected that they 

exerted a competitive influence on each other. The HHI for these combined regions was 789 in 

2003, indicating a low concentration level. Concentration in PADD IV (Rocky Mountains) was 

also low in 2003, with an HHI of 944. PADD V gradually grew more concentrated in the 1990s 

after a series of significant refinery mergers. By 2003, the region’s HHI was 1,246, indicating a 

growth to a moderate level of concentration (FTC, 2004). 

2.4.1.3 Product Differentiation 

Another way firms can influence market prices for their product is through product 

differentiation. By differentiating one’s product and using marketing to establish brand loyalty, 

manufacturers can raise their prices above marginal cost without losing market share to their 

competitors. 

While we saw in Section 3.3 that there are a wide variety of petroleum products with 

many different uses, individual petroleum products are by nature quite homogenous. For 

example, there is little difference between premium motor gasoline produced at different 

refineries (Mathtech, 1997). As a result, the role of product differentiation is probably quite 

small for many finished petroleum products. However, there are examples of relatively small 
*** Draft – Do Not Cite, Quote, or Release During Review ***

2-20 

refining businesses producing specialty products for small niche markets. As a result, there may 

be some instances where product differentiation is important for price determination. 

2.4.1.4 Competition among Firms in the Petroleum Refining Industry 

Overall, the petroleum industry is characterized as producing largely generic products for 

sale in relatively unconcentrated markets. Although it is not possible to quantify how much 

barriers to entry and other factors will affect competition among firms, it seems unlikely that 

individual petroleum refiners would be able to significantly influence market prices given the 

current structure of the market. 

2.4.2 Characteristics of U.S. Petroleum Refineries and Petroleum Refining Companies 

A petroleum refinery is a facility where labor and capital are used to convert material 

inputs (such as crude oil and other materials) into finished petroleum products. Companies that 

own these facilities are legal business entities that conduct transactions and make decisions that 

affect the facility. The terms “facility,” “establishment,” and “refinery” are synonymous in this 

report and refer to the physical location where products are manufactured. Likewise, the terms 

“company” and “firm” are used interchangeably to refer to the legal business entity that owns 

one or more facilities. This section presents information on refineries, such as their location and 

capacity utilization, as well as financial data for the companies that own these refineries. 

2.4.2.1 Geographic Distribution of U.S. Petroleum Refineries 

There are approximately 148 petroleum refineries operating in the United States, spread 

across 32 states. The number of petroleum refineries located in each of these states is listed in 

Table 2-7. This table illustrates that a significant portion of petroleum refineries are located 

along the Gulf of Mexico region. The leading petroleum refining states are Texas, Louisiana, and 

California. 

2.4.2.2 Capacity Utilization 

Capacity utilization indicates how well current refineries meet demand. One measure of 

capacity utilization is capacity utilization rates. A capacity utilization rate is the ratio of actual 

production volumes to full-capacity production volumes. For example, if an industry is 

producing as much output as possible without adding new floor space for equipment, the 

capacity utilization rate would be 100 percent. On the other hand, if under the same constraints 

the industry were only producing 75 percent of its maximum possible output, the capacity 

utilization rate would be 75 percent. On an industry-basis, capacity utilization is highly variable 

from year to year depending on economic conditions. It is also variable on a company-by-
*** Draft – Do Not Cite, Quote, or Release During Review ***

2-21 

company basis depending not only on economic conditions, but also on a company’s strategic 

position in its particular industry. While some plants may have idle production lines or empty 

floor space, others need additional space or capacity. 

Table 2-8 lists the capacity utilization rates for petroleum refineries from 2000 to 2010. It 

is interesting to note the significant drop in capacity utilization in 2005. This would seem counter 

intuitive since there does not appear to be evidence that demand for petroleum products is not 

dropping. To understand why this might be the case, one must first realize that the capacity 

Table 2-7. Number of Petroleum Refineries, by State 

State Number of Petroleum Refineries 

Alabama 3 

Alaska 6 

Arkansas 2 

California 20 

Colorado 2 

Delaware 1 

Georgia 1 

Hawaii 2 

Illinois 4 

Indiana 2 

Kansas 3 

Kentucky 2 

Louisiana 19 

Michigan 1 

Minnesota 2 

Mississippi 3 

Montana 4 

Nevada 1 

New Jersey 5 

New Mexico 3 

North Dakota 1 

Ohio 4 

Oklahoma 6 

Pennsylvania 5 

Tennessee 1 

Texas 26 

Utah 5 

Virginia 1 

Washington 5 

West Virginia 1 

Wisconsin 1 

Wyoming 6 

Total 148 

Source: U.S. Energy Information Administration (EIA), Form EIA-820, “Annual Refinery Report. Table 1. Number 

and Capacity of Operable Petroleum Refineries by PAD District and State as of January 1, 2011” Release 

Date: June 24, 2011; (Data accessed on 10/12/11). [Source for 2011 numbers.] 

<http://www.eia.gov/petroleum/refinerycapacity/> 
*** Draft – Do Not Cite, Quote, or Release During Review ***

2-22 

utilization ratio in petroleum industry represents the utilization of the atmospheric crude oil 

distillation units. 

This is calculated for the petroleum industry by dividing the gross input to atmospheric 

crude oil distillation units (all inputs involved in atmospheric crude oil distillation, such as crude 

oil) by the industry’s operational capacity. 

Table 2-8. Full Production Capacity Utilization Rates for Petroleum Refineries 

Year 

Petroleum Refineries 

Capacity Utilization Rates 

(NAICS 324110) 

Gross Input to Atmospheric 

Crude Oil Distillation Units 

(1,000s of barrels per day) 

Operational Capacity 

(1,000s of barrels per day) 

2000 92.6 15,299 16,525 

2001 92.6 15,352 16,582 

2002 90.7 15,180 16,744 

2003 92.6 15,508 16,748 

2004 93.0 15,783 16,974 

2005 90.6 15,578 17,196 

2006 89.7 15,602 17,385 

2007 88.5 15,450 17,450 

2008 85.3 15,027 17,607 

2009 82.9 14,659 17,678 

2010 86.4 15,177 17,575 

Sources: U.S. Department of Energy, Energy Information Administration (EIA). 2007a. “Refinery Utilization and 

 Capacity.” Available at <http://tonto.eia.doe.gov/dnav/pet/ pet_pnp_unc_dcu_nus_m.htm>. As obtained on 

 January, 2007. 

 U.S. Energy Information Administration (EIA), “Refinery Utilization and Capacity.” Available at 

http://www.eia.gov/dnav/pet/pet_pnp_unc_dcu_nus_a.htm; Release date: 7/28/11; (Data accessed on 

10/11/11). [Source for 2007-2010 numbers] 

Operational capacity increased from 16,974,000 barrels per calendar day in 2004 to 

17,196,000 barrels per calendar day in 2005. However, gross inputs fell from 15,783,000 barrels 

per calendar day in 2004 to 15,578,000 in 2005. This indicates that capacity utilization sagged 

due to a drop in production inputs. In 2006, gross inputs grew 0.15% to 15,602,000 barrels per 

day. However, since operational capacity grew much faster (from 17,196,000 to 17,385,000 or 

1.00%), capacity utilization rates for the industry continued to fall. Capacity utilization rates 

continued to fall through 2009. From 2009 to 2010 gross inputs increased from 14,659,000 

barrels per day to 15,177,000, increasing capacity utilization rates in 2010. 

2.4.2.3 Characteristics of Small Businesses Owning U.S. Petroleum Refineries 

According to the Small Business Administration (SBA), a small business in the 

petroleum refining industry is defined for government procurement purposes as having 1,500 or 
*** Draft – Do Not Cite, Quote, or Release During Review ***

2-23 

fewer employees and an Operable Atmospheric Crude Oil Distillation capacity of no more than 

125,000 barrels per calendar day total (SBA, 2011). We applied this definition in defining a 

small business refiner in our proposal RIA. However, as part of a response to a comment made 

on the proposal, we define a small business only as having 1,500 or fewer employees. 

As of January 2011, there were 148 petroleum refineries operating in the continental 

United States and US territories with a cumulative capacity of processing over 17 million barrels 

of crude per calendar day (EIA, 2011a). We identified 64 parent companies owning refineries in 

the United States and were able to collect employment and sales data for 61 (95%) of them. 

The distribution of employment across companies is illustrated in Figure 2-6. As this 

figure shows, 36 companies (59% of the 61 total) employee fewer than 1,500 workers and would 

be considered small businesses. These firms earned an average of $1.36 billion of revenue per 

year, while firms employing more than 1,500 employees earned an average of $82.5 billion of 

revenue per year (Figure 2-7). A distribution of the number of firms earning different levels of 

revenue is presented in Figure 2-8. 

Figure 2-6. Employment Distribution of Companies Owning Petroleum Refineries 

(N=61) 

Sources: Employment Data from Petroleum Refinery Emissions Information Collection, where available, 

Component 1, OMB Control No. 2060-0657. 

 Hoovers 2011 Online Data, accessed through University of South Carolina’s Moore School of Business 

Library. Hoovers 2011 Online Data reflects either actual data for 2010/2011 reported by companies, 

estimated data for 2011, or occasionally 2009 values. 

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

<100 100‐250 250‐500 500‐1000 1000‐1500 >1500

Share of firms (%)

Number of Employees
*** Draft – Do Not Cite, Quote, or Release During Review ***

2-24 

 Million Dollar Database online, 2011, accessed through University of South Carolina’s Moore School of 

Business Library. Million Dollar Online Data reflects either actual data for 2011 reported by companies or 

estimated data for 2011. 

 Ward’s Business Directory of Public and Private Companies, 2011, accessed at James Branch Cabell 

Library (Virginia Commonwealth University). Ward’s Business Directory compiles financial data from 

several sources such as annual reports, company websites, and phone interviews. If financial data from 

private companies is unavailable, Ward’s staff estimates the information. 

 Copyright 2011 Harte-Hanks Market Intelligence, Inc., All Rights Reserved. CI Technology Database, 

September 2011. 

 Reference USA, accessed thru Jefferson Madison Regional Library, Charlottesville, Virginia. 

 Copyright 2011 Experian Information Solutions, Inc., Experian Business Reports accessed through 

LexisNexis at James Branch Cabell Library (Virginia Commonwealth University). Experian Business 

Reports reflects the most recent data reported by a company, which may be 2010 or 2011. 

 Global Duns Market Identifiers, accessed through LexisNexis at University of Virginia’s Alderman 

Library. 

Figure 2-7. Average Revenue of Companies Owning Petroleum Refineries by 

Employment (N=61) 

Sources: Employment Data from Petroleum Refinery Emissions Information Collection, where available, 

Component 1, OMB Control No. 2060-0657. 

 Hoovers 2011 Online Data, accessed through University of South Carolina’s Moore School of Business 

Library. Hoovers 2011 Online Data reflects either actual data for 2010/2011 reported by companies, 

estimated data for 2011, or occasionally 2009 values. 

 Million Dollar Database online, 2011, accessed through University of South Carolina’s Moore School of 

Business Library. Million Dollar Online Data reflects either actual data for 2011 reported by companies or 

estimated data for 2011. 

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

90,000

<100 100‐250 250‐500 500‐1000 1000‐1500 >1500

Average revenue

($ millions)

Number of Employees
*** Draft – Do Not Cite, Quote, or Release During Review ***

2-25 

 Ward’s Business Directory of Public and Private Companies, 2011, accessed at James Branch Cabell 

Library (Virginia Commonwealth University). Ward’s Business Directory compiles financial data from 

several sources such as annual reports, company websites, and phone interviews. If financial data from 

private companies is unavailable, Ward’s staff estimates the information. 

 Copyright 2011 Harte-Hanks Market Intelligence, Inc., All Rights Reserved. CI Technology Database, 

September 2011. 

 Reference USA, accessed thru Jefferson Madison Regional Library, Charlottesville, Virginia. 

 Copyright 2011 Experian Information Solutions, Inc., Experian Business Reports accessed through 

LexisNexis at James Branch Cabell Library (Virginia Commonwealth University). Experian Business 

Reports reflects the most recent data reported by a company, which may be 2010 or 2011. 

 Global Duns Market Identifiers, accessed through LexisNexis at University of Virginia’s Alderman 

Library. 

Figure 2-8. Revenue Distribution of Companies Owning Petroleum Refineries (N=61) 

Sources: Employment Data from Petroleum Refinery Emissions Information Collection, where available, 

Component 1, OMB Control No. 2060-0657. 

 Hoovers 2011 Online Data, accessed through University of South Carolina’s Moore School of Business 

Library. Hoovers 2011 Online Data reflects either actual data for 2010/2011 reported by companies, 

estimated data for 2011, or occasionally 2009 values. 

 Million Dollar Database online, 2011, accessed through University of South Carolina’s Moore School of 

Business Library. Million Dollar Online Data reflects either actual data for 2011 reported by companies or 

estimated data for 2011. 

 Ward’s Business Directory of Public and Private Companies, 2011, accessed at James Branch Cabell 

Library (Virginia Commonwealth University). Ward’s Business Directory compiles financial data from 

several sources such as annual reports, company websites, and phone interviews. If financial data from 

private companies is unavailable, Ward’s staff estimates the information. 

 Copyright 2011 Harte-Hanks Market Intelligence, Inc., All Rights Reserved. CI Technology Database, 

September 2011. 

 Reference USA, accessed thru Jefferson Madison Regional Library, Charlottesville, Virginia. 

0%

10%

20%

30%

40%

50%

60%

<5 5‐10 10‐50 50‐100 100‐500 500‐1000 >1000

Share of firms (%)

Revenue ($millions)
*** Draft – Do Not Cite, Quote, or Release During Review ***

2-26 

 Copyright 2011 Experian Information Solutions, Inc., Experian Business Reports accessed through 

LexisNexis at James Branch Cabell Library (Virginia Commonwealth University). Experian Business 

Reports reflects the most recent data reported by a company, which may be 2010 or 2011. 

 Global Duns Market Identifiers, accessed through LexisNexis at University of Virginia’s Alderman 

Library. 

Employment, crude capacity, and location information are provided in Table 2-9 for each 

refinery owned by a parent company employing 1,500 employees or less. Similar information 

can be found for all 64 companies owning petroleum refineries in Appendix A. 

In Section 3.4.2.1, we discussed how petroleum refining operations are characterized by 

economies of scale—that the cost per unit falls as a refinery produces more finished petroleum 

products. This means that smaller petroleum refiners face higher per unit costs than larger 

refining operations because they produce fewer petroleum products. As a result, some smaller 

firms have sought to overcome their competitive disadvantage by locating close to productconsuming areas to lower transportation costs and serving niche product markets (FTC, 2004). 

A good example of a firm locating close to prospective customers is Countrymark 

Cooperative, Inc., which was started in the 1930s for the express purpose of providing farmers in 

Indiana with a consistent supply of fuels, lubricants, and other products. A good example of a 

firm producing niche products is Calumet Specialty Product Partners. The firm produces both 

basic fuels like gasoline, diesel fuel and jet fuel and specialty products like lubricating oils, 

solvents, waxes, and other petroleum products. However, the firm’s specialty products unit is its 

largest unit (Hoovers, 2011 online). Also Arabian American Development Company’s South 

Hampton Resources facility specializes in producing high purity solvents for the plastics and 

foam industries. 

However, recent developments are making these factors less important for success in the 

industry. For example, the entry of new product pipelines is eroding the locational advantage of 

smaller refineries (FTC, 2004). This trend can possibly be illustrated by the fact that most 

refineries owned by small businesses tend to be located in relatively rural areas (see Table 2-9). 

The median population density of counties occupied by small refineries is 103 people per square 

mile. This could suggest that refineries do not rely on the population surrounding them to support 

their refining operations. 

 Capacity information for the refineries owned by small businesses also suggests that 

fewer small businesses are focusing on developing specialty products or serving local customers 

as major parts of their business plan. For example, in 2006 29 small refineries had a collective 
*** Draft – Do Not Cite, Quote, or Release During Review ***

2-27 

crude refining capacity of 778,920 barrels per calendar day or 857,155 barrels per stream day 

(EIA, 2006c). Approximately 21% of this total capacity was devoted to producing specialty 

products or more locally focused products such as aromatics, asphalt, lubricants, and petroleum 

coke. The remaining 79% was used to produce gasoline, kerosene, diesel fuel, and liquefied 

petroleum gases. Similarly, in 2011, approximately 20% of small businesses’ total capacity was 

dedicated to producing specialty products and 80% was dedicated to producing fuel products. 

As discussed in Section 3.4.1.3, fuel products tend to be quite homogenous (gasoline from one 

refinery is not very different from gasoline from another refinery), and they are also normally 

transported by pipeline. 

2.5 Markets 

This section provides data on the volume of petroleum products produced and consumed 

in the United States, the quantity of products imported and exported, and the average prices of 

major petroleum products. The section concludes with a discussion of future trends for the 

petroleum refining industry. 

2.5.1 U.S. Petroleum Consumption 

Figure 2-9 illustrates the amount of petroleum products supplied between 2000 and 2010 

(measured in millions of barrels of oil). These data represent the approximate consumption of 

petroleum products because it measures the disappearance of these products from primary 

sources (i.e., refineries, natural gas processing plants, blending plants, pipelines, and bulk 

terminals). 
*** Draft – Do Not Cite, Quote, or Release During Review ***

2-28 

Table 2-9. Characteristics of Small Businesses in the Petroleum Refining Industry 

Parent Company 

Parent 

Company 

Type 

Cumulative 

Crude 

Capacity 

(bbl/cd) 

Parent 

Company 

Employment 

(#) Facility Name 

Facility 

City 

Facilit

y State Facility County

Facility 

County 

Populatio

Density (200

AGE Refining, Inc. Private 14,021 124 AGE Refining Inc San Antonio TX Bexar County 1,117 American Refining Group, Inc. 

Private 10,000 323 American 

Refining Group Inc 

Bradford PA McKean County 47 

Arabian American Development Co 

Public 0 145 South Hampton 

Resources Inc. 

Silsbee TX Hardin County 54 

BTB Refining Private 0 37 Trigeant Ltd. Corpus 

Christi 

TX Nueces County 375 

Calcasieu Refining Company Private 78,000 92 Calcasieu 

Refining Co. 

Lake Charles 

LA Calcasieu Parish 171 

Calumet Specialty Products Partners, L.P. 

Public 57,000 654 Calumet 

Shreveport LLC 

Shreveport LA Caddo Parish 286 

Calumet Specialty Products Partners, L.P. 

Public 13,020 654 Calumet 

Lubricants Co LP 

Cotton Valley 

LA Caddo Parish 286 

Calumet Specialty Products Partners, L.P. 

Public 8,300 654 Calumet 

Lubricants Co LP 

Princeton LA Caddo Parish 286 

CHS, Inc. Public 59,600 287 Cenex Harvest 

States 

Laurel MT Yellowstone 

County 

49 

Connacher Oil and Gas, Limited 

Public 10,000 170 Montana Refining 

Co. 

Great Falls MT Cascade County 30 

CVR Energy, Inc. Public 115,700 371 Coffeyville 

Resources Rfg&Mktg LLC 

Coffeyville KS Montgomery 

County 

56 

Countrymark Cooperative Private 26,500 425 Countrymark 

Cooperative, Inc. 

Mt. Vernon IN Posey County 66 

Cross Oil Refining & Marketing, Inc. 

Private 7,500 110 Martin Midstream 

Partners LP 

Smackover AR Union County 44 

Foreland Refining Corp. Private 2,000 27 Foreland Refining 

Co. 

Ely NV White Pine 

County 

1 

Frontier Oil Corp. Private 47,000 723 Frontier Refining 

Inc 

Cheyenne WY Laramie County 30 
*** Draft – Do Not Cite, Quote, or Release During Review ***

2-29 

Table 2-9. Characteristics of Small Businesses in the Petroleum Refining Industry (continued) 

Parent Company 

Parent 

Company 

Type 

Cumulative 

Crude 

Capacity 

(bbl/cd) 

Parent 

Company 

Employment 

(#) Facility Name 

Facility 

City 

Facilit

y State Facility County

Facility 

County 

Populatio

Density (200

Frontier Oil Corp. Private 138,000 723 Frontier El 

Dorado Refining Co 

El Dorado KS Butler County 42 

Garco Energy Private 3,600 16 Garco Energy 

LLC 

Douglas WY Converse 

County 

3 

Gary-Williams Energy Corporation 

Private 70,000 260 Wynnewood 

Refining Co. 

Wynnewood OK Garvin County 34 

Goodway Refining, LLC Private 4,100 17 Goodway 

Refining LLC 

Atmore AL Escambia 

County 

41 

Gulf Atlantic Operations LLC 

Private 32 Gulf Atlantic 

Operations LLC 

Mobile Bay AL Mobile County 324 

Holly Corporation Public 25,050 1,321 Holly Refining & 

Marketing Co 

Woods Cross 

UT Davis County 785 

Holly Corporation Public 105,000 1,321 Navajo Refining 

Co. 

Artesia NM Eddy County 12 

Holly Corporation Public 70,300 1,321 Holly Refining & 

Marketing Co 

Tulsa East OK Tulsa County 988 

Holly Corporation Public 85,000 1,321 Holly Refining & 

Marketing Co 

Tulsa West OK Tulsa County 988 

Hunt Refining Co. Private 36,000 1,100 Hunt Refining Co. Tuscaloosa AL Tuscaloosa 

County 

125 

Hunt Refining Co. Private 11,000 1,100 Hunt Southland 

Refining Co 

Sandersville MS Lamar County 79 

Kern Oil & Refining Co. Private 26,000 346 Kern Oil & 

Refining Co. 

Bakersfield CA Kern County 81 

Lion Oil Co. Private 75,000 350 Lion Oil Co. El Dorado AR Union County 44 National Cooperative Refinery Association 

Public 85,500 612 National 

Cooperative Refinery Association 

McPherson KS McPherson 

County 

33 

NuStar Energy LP Public 70,000 1,492 Nustar Asphalt 

Refining LLC 

Paulsboro NJ Gloucester 784 

NuStar Energy LP Public 28,000 1,492 Nustar Asphalt 

Refining LLC 

Savannah GA Chatham 530 
*** Draft – Do Not Cite, Quote, or Release During Review ***

2-30 

Table 2-9. Characteristics of Small Businesses in the Petroleum Refining Industry (continued) 

Parent Company 

Parent 

Company 

Type 

Cumulative 

Crude 

Capacity 

(bbl/cd) 

Parent 

Company 

Employment 

(#) Facility Name 

Facility 

City 

Facilit

y State Facility County

Facility 

County 

Populatio

Density (200

Pasadena Refining Systems Inc. 

Private 120,000 348 Pasadena Refining 

Systems Inc. 

Pasadena TX Harris County 1967 

Pelican Refining Co LLC Private 0 33 Pelican Refining 

Co. LLC 

Lake Charles 

LA Calcasieu Parish 171 

Petro Star Inc. Private 19,700 400 Petro Star Inc. North Pole AK Fairbanks North 

Star 

11 

Petro Star Inc. Private 55,000 400 Petro Star Inc. Valdez AK Valdez Cordova 0.3 Placid Refining Private 57,000 207 Placid Refining 

Inc. 

Port Allen LA West Baton 

Rouge Parish 

113 

San Joaquin Refining Co. Private 15,000 108 San Joaquin 

Refining Co., Inc. 

Bakersfield CA Kern County 81 

Santa Maria Refining Company 

Private 9,500 47 Greka Energy Santa Maria CA Santa Barbara 

County 

146 

Silver Eagle Refining Inc. Private 3,000 60 Silver Eagle 

Refining 

Evanston WY Uinta County 10 

Silver Eagle Refining Inc. Private 10,250 60 Silver Eagle 

Refining 

Woods Cross 

UT Davis County 785 

Somerset Oil Inc. Private 5,500 11 Somerset Energy 

Refinery LLC 

Somerset KY Pulaski County 85 

US Oil & Refining Co. Private 38,800 182 US Oil & Refining 

Co. 

Tacoma WA Pierce County 417 

Ventura Refining & Transmission, LLC 

Private 12,000 37 Ventura Refining 

& Transmission LLC 

Thomas OK Custer County 27 

Western Refining, Inc. Public 122,000 636 Western Refining 

Company LP 

El Paso TX El Paso County 671 

Western Refining, Inc. Public 66,300 636 Western Refining 

Yorktown Inc 

Yorktown VA York County 533 

Western Refining, Inc. Public 16,800 636 Western Refining 

Southwest Inc 

Bloomfield NM San Juan County 21 

Western Refining, Inc. Public 21,100 636 Western Refining 

Southwest Inc 

Gallup NM McKinley 

County 

14 
*** Draft – Do Not Cite, Quote, or Release During Review ***

2-31 

Table 2-9. Characteristics of Small Businesses in the Petroleum Refining Industry (continued) 

Parent Company 

Parent 

Company 

Type 

Cumulative 

Crude 

Capacity 

(bbl/cd) 

Parent 

Company 

Employment 

(#) Facility Name 

Facility 

City 

Facility 

State Facility County

Facility 

County 

Populatio

Density (200

World Oil Marketing Co. Private 8,500 65 Lunday-Thagard 

Co. 

South Gate CA Los Angeles 

County 

2,344 

Wyoming Refining Co. Private 14,000 96 Wyoming 

Refining Co 

New Castle WY Weston County 3 

Total 1,875,641 11,264 

Sources: U.S. Census Bureau, American Fact Finder, “2010 Census Summary File 1 Population, Housing Units, Area & Density: 2010

100% Data 2010 Census” (Data accessed on 10/21/2011); http://factfinder2.census.gov/faces/tableservices/jsf/pages/productvi

 Hoovers 2011 Online Data, accessed through University of South Carolina’s Moore School of Business Library. Hoovers 201

either actual data for 2010/2011 reported by companies, estimated data for 2011, or occasionally 2009 values. 

 Million Dollar Database online, 2011, accessed through University of South Carolina’s Moore School of Business Library. Mi

reflects either actual data for 2011 reported by companies or estimated data for 2011. 

 Ward’s Business Directory of Public and Private Companies, 2011, accessed at James Branch Cabell Library (Virginia Comm

Ward’s Business Directory compiles financial data from several sources such as annual reports, company websites, and phone data from private companies is unavailable, Ward’s staff estimates the information. 

 Copyright 2011 Harte-Hanks Market Intelligence, Inc., All Rights Reserved. CI Technology Database, September 2011.  Reference USA, accessed thru Jefferson Madison Regional Library, Charlottesville, Virginia.  Copyright 2011 Experian Information Solutions, Inc., Experian Business Reports accessed through LexisNexis at James Branc

(Virginia Commonwealth University). Experian Business Reports reflects the most recent data reported by a company, which 

 Global Duns Market Identifiers, accessed through LexisNexis at University of Virginia’s Alderman Library.  Employment Data from Petroleum Refinery Emissions Information Collection, where available, Component 1, OMB Control  Energy Information Administration (EIA), Form EIA 820, “Annual Refinery Report,” Table 3. Capacity of Operable Petroleum 

Individual Refinery as of January 1, 2011 <http://www.eia.gov/petroleum/refinerycapacity/> 
*** Draft – Do Not Cite, Quote, or Release During Review ***

2-32 

Between 2000 and 2004, U.S. consumption of petroleum products increased by 5%. 

Consumption leveled off by 2007 and dropped by 9% between 2007 and 2009 (Figure 2-9). This 

reduced growth was primarily the result of less jet fuel, residual fuel, distillate fuel, and other 

products being consumed in recent years. Consumption of all petroleum products, except for 

motor gasoline, increased between 2009 and 2010, but the total consumption of petroleum 

products did not reach 2000-2004 levels. The cumulative decrease in consumption over the 11 

year period is 3% (Table 2-10). 

Figure 2-9. Total Petroleum Products Supplied (millions of barrels per year) 

Sources: U.S. Department of Energy, Energy Information Administration (EIA). 1996–2007. “Petroleum Supply 

Annuals, Volume 1.” Available at <http://www.eia.doe.gov/oil_gas/petroleum/data_publications/ 

petroleum_supply_annual/psa_volume1/psa_volume1.html>. As obtained on October 31, 2007. 

 U.S. Department of Energy. 2011 Energy Information Administration (EIA). 1996–2011. “Petroleum 

Supply Annuals, Volume 1.” (Data accessed on October 7, 2011) [Source for 2007–2010 numbers.] 

<http://www.eia.gov/dnav/pet/pet_sum_snd_d_nus_mbbl_a_cur.htm>. 
*** Draft – Do Not Cite, Quote, or Release During Review ***

2-33 

Table 2-10. Total Petroleum Products Supplied (millions of barrels per year) 

Year 

Motor 

Gasoline Jet Fuel 

Distillate 

Fuel Oil 

Residual 

Fuel Oil 

Liquefied 

Petroleum Gases 

Other 

Products Total 

2000 3,101 631 1,362 333 816 967 7,211 

2001 3,143 604 1,404 296 746 978 7,172 

2002 3,229 591 1,378 255 789 969 7,213 

2003 3,261 576 1,433 282 757 1,003 7,312 

2004 3,333 597 1,485 316 780 1,076 7,588 

2005 3,343 613 1,503 336 741 1,057 7,593 

2006 3,377 596 1,522 251 749 1,055 7,551 

2007 3,389 592 1,532 264 761 1,011 7,548 

2008 3,290 563 1,444 228 715 896 7,136 

2009 3,284 509 1,325 187 749 799 6,852 

2010 3,282 523 1,387 195 793 820 7,001 

Sources: Annuals, Volume 1.” Available at <http://www.eia.doe.gov/oil_gas/petroleum/data_publications/ 

petroleum_supply_annual/psa_volume1/psa_volume1.html>. As obtained on October 31, 2007. 

 U.S. Department of Energy. 2011 Energy Information Administration (EIA). 1996–2011. “Petroleum 

Supply Annuals, Volume 1.” (Data accessed on October 11, 2011) [Source for 2007–2010 numbers.] 

<http://www.eia.gov/dnav/pet/pet_sum_snd_d_nus_mbbl_a_cur.htm>. 

2.5.2 U.S. Petroleum Production 

Table 2-11 reports the number of barrels of major petroleum products produced in the 

United States between 2000 and 2010. U.S. production of petroleum products at refineries and 

blenders grew steadily, resulting in a 7% cumulative increase for the period However, in 2005 

and 2009 production declined by slightly. 
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Table 2-11. U.S. Refinery and Blender Net Production (millions of barrels per year) 

Year 

Motor 

Gasoline Jet Fuel 

Distillate 

Fuel Oil 

Residual 

Fuel Oil 

Liquefied 

Petroleum Gases 

Other 

Products Total 

2000 2,910 588 1,310 255 258 990 6,311 

2001 2,928 558 1,349 263 243 968 6,309 

2002 2,987 553 1,311 219 245 990 6,305 

2003 2,991 543 1,353 241 240 1,014 6,383 

2004 3,025 566 1,396 240 236 1,057 6,520 

2005 3,036 564 1,443 229 209 1,015 6,497 

2006 3,053 541 1,475 232 229 1,032 6,561 

2007 3,051 528 1,509 246 239 464 6,568 

2008 3,129 546 1,572 227 230 950 6,641 

2009 3,207 510 1,478 218 227 1,418 6,527 

2010 3,306 517 1,542 213 240 1,747 6,735 

Sources: U.S. Department of Energy, Energy Information Administration (EIA). 1996–2007. “Petroleum Supply 

Annuals, Volume 1.” Available at <http://www.eia.doe.gov/oil_gas/petroleum/data_publications/ 

petroleum_supply_annual/psa_volume1/psa_volume1.html>. As obtained on October 31, 2007. 

 U.S. Department of Energy. 2011 Energy Information Administration (EIA). 1996–2011. “Petroleum 

Supply Annuals, Volume 1.” (Data accessed on October 7, 2011) [Source for 2007–2010 numbers.] 

<http://www.eia.gov/dnav/pet/pet_pnp_refp_dc_nus_mbbl_a.htm>. 

 The 2005 decline in production (0.35%) was possibly the result of damage inflicted by 

two hurricanes (Hurricane Katrina and Hurricane Rita) on the U.S. Gulf Coast—the location of 

many U.S. petroleum refineries (Section 3.4.2). According to the American Petroleum Institute, 

approximately 30% of the U.S. refining industry was shut down as a result of the damage (API, 

2006). The 2009 decline in production (1.72%) was probably the result of the global economic 

crisis. Additional production data are presented in Table 2-12, which reports the value of 

shipments of products produced by the petroleum refining industry between 1997 and 2009. 

2.5.3 International Trade 

International trade trends are shown in Tables 3-13 and 3-14. Between 1995 and 2006, 

imports and exports of petroleum products increased by 123% and 51% respectively. Between 

1995 and 2006, while imports of most major petroleum products grew at approximately the same 

rate, the growth of petroleum product exports was driven largely by residual fuel oil and other 

petroleum products. More recently, between 2008 and 2010 exports of petroleum products such 

as motor gasoline, jet fuel, distillate fuel oil and liquefied petroleum gases have also increased. 

Since 2006, industry import and export trends have diverged significantly. Between 2006 

and 2010 imports declined by 28%, returning close to 2001 levels. Exports grew at an average 

annual rate of 12%. Exports in 2010 were 2.4 times the level of exports in 2001. The United 

States, however, still remains a net importer of petroleum products. In 2010, U.S. net imports 
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were 98 million barrels. These imports made up 10% of the country’s imports and accounted for 

around 1% of total petroleum products consumed in that year. 

Table 2-12. Value of Product Shipments of the Petroleum Refining Industry 

Year Millions of $Reported Millions of $2005 

1997 152,756 180,671 

1998 114,439 136,746 

1999 140,084 164,651 

2000 210,187 237,425 

2001 195,898 219,476 

2002 186,761 210,647 

2003 216,764 238,425 

2004 290,280 306,328 

2005 419,063 419,063 

2006 489,051 470,037 

2007 551,997 510,996 

2008 682,756 585,664 

2009 436,974 394,348 

Note: Numbers were adjusted for inflation using producer price index industry data for Total Manufacturing 

Industries (Table 2-16). 

Sources: U.S. Department of Commerce, Bureau of the Census. 2007. 2006 Annual Survey of Manufactures. 

Obtained through American Fact Finder Database 

<http://factfinder.census.gov/home/saff/main.html?_lang=en>. 

 U.S. Department of Commerce, Bureau of the Census. 2003b. 2001 Annual Survey of Manufactures. 

M01(AS)-2. Washington, DC: Government Printing Office. Available at 

<http://www.census.gov/prod/2003pubs/m01as-2.pdf>. As obtained on March 4, 2008. 

 U.S. Department of Commerce, Bureau of the Census, FactFinder. 2011. 2009 Annual Survey of 

Manufactures. 1996–2011. Obtained through American Fact Finder Database. (Data accessed on October 

14, 2011.) [Source for 2007–2009 numbers] <http://factfinder.census.gov/servlet/ 

DatasetMainPageServlet?_lang=en&_ts=336651423017&_ds_name=AM0931GS101&_program=EAS>. 
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Table 2-13. Imports of Major Petroleum Products (millions of barrels per year) 

Year 

Motor 

Gasoline Jet Fuel 

Distillate 

Fuel Oil 

Residual 

Fuel Oil 

Liquefied 

Petroleum Gases 

Other 

Products Total 

1995 97 35 71 68 53 262 586 

1996 123 40 84 91 61 322 721 

1997 113 33 83 71 62 345 707 

1998 114 45 77 101 71 324 731 

1999 139 47 91 86 66 344 774 

2000 156 59 108 129 79 343 874 

2001 166 54 126 108 75 400 928 

2002 182 39 98 91 67 396 872 

2003 189 40 122 119 82 397 949 

2004 182 47 119 156 96 520 1,119 

2005 220 69 120 193 120 587 1,310 

2006 173 68 133 128 121 687 1,310 

2007 151 79 111 136 90 688 1,255 

2008 110 38 78 128 93 700 1,146 

2009 82 29 82 121 66 597 977 

2010 49 36 83 134 56 584 942 

Sources: U.S. Department of Energy, Energy Information Administration (EIA).1996–2007. “Petroleum Supply 

Annuals, Volume 1.” Available at <http://www.eia.doe.gov/oil_gas/petroleum/data_publications/ 

petroleum_supply_annual/psa_volume1/psa_volume1.html>. As obtained on October 31, 2007. 

 U.S. Department of Energy. 2011 Energy Information Administration (EIA). 1996–2011. “Petroleum 

Supply Annuals, Volume 1.” (Data accessed on October 7, 2011.) [Source for 2007–2010 numbers.] 

<http://www.eia.gov/dnav/pet/pet_move_imp_dc_NUS-Z00_mbbl_a.htm> 

Table 2-14. Exports of Major Petroleum Products (millions of barrels per year) 

Year 

Motor 

Gasoline Jet Fuel 

Distillate 

Fuel Oil 

Residual 

Fuel Oil 

Liquefied 

Petroleum Gases 

Other 

Products Total 

1995 38 8 67 49 21 128 312 

1996 38 17 70 37 19 138 319 

1997 50 13 56 44 18 147 327 

1998 46 9 45 50 15 139 305 

1999 40 11 59 47 18 124 300 

2000 53 12 63 51 27 157 362 

2001 48 10 44 70 16 159 347 

2002 45 3 41 65 24 177 356 

2003 46 7 39 72 20 186 370 

2004 45 15 40 75 16 183 374 

2005 49 19 51 92 19 183 414 

2006 52 15 79 103 21 203 472 

2007 46 15 98 120 21 213 513 

2008 63 22 193 130 25 216 649 

2009 71 25 214 152 36 224 723 

2010 108 31 239 148 48 270 843 

Sources: U.S. Department of Energy, Energy Information Administration (EIA). 1996–2007. “Petroleum Supply 

Annuals, Volume 1.” Available at <http://www.eia.doe.gov/oil_gas/petroleum/data_publications/ 

petroleum_supply_annual/psa_volume1/psa_volume1.html>. As obtained on October 31, 2007. 
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 U.S. Department of Energy. 2011 Energy Information Administration (EIA). 1996–2011. “Petroleum 

Supply Annuals, Volume 1.” (Data accessed on October 7, 2011.) [Source for 2007–2010 numbers] 

<http://www.eia.gov/dnav/pet/pet_move_exp_dc_NUS-Z00_mbbl_a.htm>. 

2.5.4 Market Prices 

The average nominal prices of major petroleum products sold to end users are provided 

for selected years in Table 2-15.2

 As these data illustrate, nominal prices rose substantially 

between 2005 and 2008. In 2009 there was a drop in prices, resulting in a return to 2005 price 

levels for most products. In 2010 nominal prices increased. During the 2008–2010 period, the 

most volatile price was jet fuel price: it declined by 44% in 2009 and increased by 29% in 2010. 

Table 2-15. Average Price of Major Petroleum Products Sold to End Users (cents per 

gallon) 

Product 1995 2000 2005 2008 2009 2010 

Motor gasoline 76.5 110.6 183 278 189 230 

No. 1 distillate fuel 62.0 98.8 183 298 214 271 

No. 2 distillate fuel 56.0 93.4 178 314 184 232 

Jet fuel 54.0 89.9 174 305 170 220 

Residual fuel oil 39.2 60.2 105 196 134 171 

Note: Prices do not include taxes. 

Sources: U.S. Department of Energy, Energy Information Administration (EIA). 2007b. “Refiner Petroleum Product 

Prices by Sales Type.” Available at <http://tonto.eia.doe.gov/dnav/pet/pet_pri_refoth_dcu_nus_m.htm>. As 

obtained on January 11, 2008. 

 U.S. Department of Energy. 2011 Energy Information Administration (EIA). 1996–2011. “Petroleum 

Supply Annuals, Volume 1.” (Data accessed on October 7, 2011.) [Source for 2007–2010 

numbers.]<http://www.eia.gov/dnav/pet/pet_pri_refoth_dcu_nus_a.htm>. 

The nominal prices domestic petroleum refiners receive for their products have been 

volatile, especially compared to prices received by other U.S. manufacturers. This trend is 

demonstrated in Table 2-16 by comparing the producer price index (PPI) for the petroleum 

refining industry against the index for all manufacturing industries. Between 1995 and 2010, prices 

received by petroleum refineries for their products rose by 288%, while prices received by all 

manufacturing firms rose by 41%. In 2009, both price indexes experienced a decline from 2008 

levels, however the decrease was 36% for petroleum refineries and 5% for all manufacturing firms. 

 

2

 Sales to end users are those made directly to the consumer of the product. This includes bulk consumers, such as 

agriculture, industry, and utilities, as well as residential and commercial consumers. 
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Table 2-16. Producer Price Index Industry Data: 1995 to 2010 

 Petroleum Refining (NAICS 32411) Total Manufacturing Industries 

Year PPI 

Annual Percentage 

Change in PPI PPI 

Annual Percentage 

Change in PPI 

1995 74.5 3% 124.2 3% 

1996 85.3 14% 127.1 2% 

1997 83.1 −3% 127.5 0% 

1998 62.3 −25% 126.2 −1% 

1999 73.6 18% 128.3 2% 

2000 111.6 52% 133.5 4% 

2001 103.1 −8% 134.6 1% 

2002 96.3 −7% 133.7 −1% 

2003 121.2 26% 137.1 3% 

2004 151.5 25% 142.9 4% 

2005 205.3 36% 150.8 6% 

2006 241.0 17% 156.9 4% 

2007 266.9 11% 162.9 4% 

2008 338.3 27% 175.8 8% 

2009 217.0 −36% 167.1 −5% 

2010 289.4 33% 175.4 5% 

Sources: U.S. Bureau of Labor Statistics (BLS). 2007. “Producer Price Index Industry Data: Customizable Industry 

Data Tables.” Available at <http://www.bls.gov/ppi/>. As obtained on October 11, 2007. 

 U.S. Bureau of Labor Statistics (BLS). 2011. “Producer Price Index Industry Data: Customizable Industry 

Data Tables.” (Data accessed on October 11, 2011.) [Source for 2007–2010 

numbers]<http://data.bls.gov/cgi-bin/dsrv?pc>. 

2.5.5 Profitability of Petroleum Refineries 

Estimates of the mean profit (before taxes) to net sales ratios for petroleum refiners are 

reported in Table 2-17 for the 2006–2007 and 2009-2010 fiscal years. These ratios were 

calculated by Risk Management Associates by dividing net income into revenues for 44 firms for 

the 2006-2007 fiscal year and 43 firms for the 2009-2010 fiscal year. They are broken down 

based on the value of assets owned by the reporting firms. 
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2-39 

Table 2-17. Mean Ratios of Profit before Taxes as a Percentage of Net Sales for Petroleum 

Refiners, Sorted by Value of Assets 

Fiscal Year 

Total 

Number of 

Statements 

0 to 

500,000 

500,000 to 

2 Million 

2 Million 

to 10 

Million 

10 Million 

to 50 

Million 

50 Million 

to 100 

Million 

100 Million 

to 250 

Million 

All 

Firms 

4/1/2006–

3/31/2007 

44 — — 4.6 6.5 — — 6.7 

4/1/2009–

3/31/2010 

43 — — 5.5 — — — 4.1 

Sources: Old Source: Risk Management Association (RMA). 2008. Annual Statement Studies 2007–2008. 

Pennsylvania: RMA, Inc. 

 New Source: Risk Management Association (RMA). 2011. Annual Statement Studies 2010–2011. 

Pennsylvania: RMA, Inc. 

As these ratios demonstrate, firms that reported a greater value of assets also received a 

greater return on sales. For example, for the 2006–2007 fiscal year, firms with assets valued 

between $10 and $50 million received a 6.5% average return on net sales, while firms with assets 

valued between $2 and $10 million only received a 4.6% average return. Firms with assets 

valued between $2 and 10 million received 5.5% average return between 2009 and 2010. The 

data for other asset size categories is not shown for the fiscal year 2009–2010 because RMA 

received fewer than 10 financial statements in those categories and RMA does not consider those 

samples to be representative. The average return on sales for the entire industry was 6.7% during 

the 2006–2007 fiscal year and declined to 4.1% during the 2009–2010 fiscal year. 

Obtaining profitability information specifically for small petroleum refining companies 

can be difficult as most of these firms are privately owned. However, some of the small, 

domestic petroleum refining firms identified in Section 3.4.2.3 are publicly owned companies—

the Arabian American Development Co., CVR Energy Inc., Calumet Specialty Products 

Partners, L.P., Holly Corporation, and Western Refining, Inc. Profit ratios were calculated for 

these companies using data obtained from their publicly available 2010 income statements. 

These ratios are presented in Table 2-18. 
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Table 2-18. Net Profit Margins for Publicly Owned, Small Petroleum Refiners: 2010 

Company 

Net Income 

($millions) 

Total Revenue 

($millions) 

Net Profit Margin 

(%) 

Arabian American Development Co. 2.69 139.11 1.93% 

Calumet Specialty Products Partners 16.70 2,190.80 0.76% 

CVR Energy Inc. 14.30 4,079.80 0.35% 

Holly Corporation 133.10 8,323.00 1.60% 

Western Refining, Inc. −17.05 7,965.10 −0.21% 

Sources: Holly Corporation, EDGAR database Holly Corporation 10K. February 25, 2011. 10K for year ended 

December 31, 2010. (Data accessed on 10/23/11) [Source for 2010 numbers.] 

http://files.shareholder.com/downloads/FTO/1428853845x0xS950123-11-18524/48039/filing.pdf> 

 Western Refining, Thomson Reuters Western Refining, Inc. 10K. March 8, 2011. 10K for year ended 

December 31, 2010. (Data accessed on 10/23/11) [Source for 2010 numbers.] http://phx.corporateir.net/phoenix.zhtml?c=194293&p=irol-sec> 

 Arabian American Develop Co., South Hampton Resources, Inc. Arabian American Development Co. Q4 

& FY2010 Financial Results. (Data accessed on 10/21/11) [Source for 2010 numbers.] 

http://www.arabianamericandev.com/images/uploads/investor/2010eoyearningspresentation.pdf> 

 Calumet Specialty Products Partners, Morningstar for Calumet Specialty Products Partners 10K. February 

22, 2011. 10K for year ended December 31, 2010. (Data accessed on 10/21/11) [Source for 2010 numbers.] 

http://quote.morningstar.com/stock-filing/Annual-Report/2010/12/31/t.aspx?t=XNAS:CLMT&ft=10-

K&d=c7dd2813722445ded56c7e3aefebf2ca> 

 CVR Energy Inc., EDGAR database for CVR Energy Inc. 10K. March 7, 2011. 10K for year ended 

December 31, 2010. (Data accessed on 10/23/11) [Source for 2010 numbers.] 

<http://www.sec.gov/Archives/edgar/data/1376139/000095012311022741/y90110e10vk.htm> 

2.5.6 Industry Trends 

The Energy Information Administration’s (EIA’s) 2011 Annual Energy Outlook provides 

forecasts of average petroleum prices, petroleum product consumption, and petroleum refining 

capacity utilization to the year 2035. Trends in these variables are affected by many factors that 

are difficult to predict, such as energy prices, U.S. economic growth, advances in technologies, 

changes in weather patterns, and future public policy decisions. As a result, the EIA evaluated a 

wide variety of cases based on different assumptions of how these factors will behave in the 

future. This section focuses on the EIA’s “reference case” forecasts, which assume that current 

policies affecting the energy sector will remain unchanged throughout the projection period 

(EIA, Form EIA-820). 

According to the 2011 Annual Energy Outlook’s reference forecast, world oil prices 

(defined as the average price of low-sulfur, light crude oil) are expected to steadily increase over 

the next 10 years as the amount of oil demanded by non-OECD and OECD countries increases. 

Since crude oil is the primary input in petroleum refining, an increase in its price would likewise 

represent an increase in production costs of petroleum refiners. As a result, the prices of 
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petroleum products sold to end users are expected to rise over the same period (Table 2-19). 

Higher prices and tighter fuel efficiency standards (enlarged production of non-oil fuels) will 

moderate the growth in petroleum products consumed by the recovering US economy (Table 2-

20). Between 2011 and 2019, the prices of major petroleum products are expected to rise 

approximately from 32% to 49%, while consumption of all of those products is expected to rise 

by 7%. In particular the price of the most supplied product, motor gasoline, is projected to rise 

by 38% and its consumption is projected to slightly increase by 2%. 

Table 2-19. Forecasted Average Price of Major Petroleum Products Sold to End Users in 

2009 Currency (cents per gallon) 

Product 2011 2012 2013 2014 2015 2016 2017 2018 2019 

Motor gasoline 286.1 291.3 312.3 326.9 342.1 353.6 369.5 382.9 395.5 

Jet fuel 233.0 252.2 261.8 270.4 280.3 297.9 314.5 330.8 346.1 

Distillate fuel 302.6 289.8 301.9 313.9 326.9 345.8 364.1 382.3 400.4 

Residual fuel oil 186.2 183.1 191.3 202.9 213.6 225.9 236.8 249.1 259.9 

LPGs 178.9 180.5 186.7 193.6 200.4 208 217 226.2 235.4 

Sources: U.S. Department of Energy, Energy Information Administration (EIA). 2007c. “Annual Energy Outlook.” 

Available at <http://www.eia.doe.gov/oiaf/archive/aeo07/pdf/0383(2007).pdf>. As obtained on January 21, 

2007. 

 U.S. Department of Energy, Energy Information Administration (EIA). 2011. “Annual Energy Outlook.”; 

(Data accessed on October 11, 2011) [Source for 2011–2019 numbers.] 

<http://www.eia.gov/forecasts/aeo/pdf/0383(2011).pdf>. 

Table 2-20. Total Petroleum Products Supplied (millions of barrels per year) 

Year 

Motor 

Gasoline Jet Fuel 

Distillate 

Fuel Oil 

Residual 

Fuel Oil 

Liquefied 

Petroleum Gases 

Other 

Products Total 

2011 3,317 515 1,367 199 768 806 6,972 

2012 3,407 554 1,451 219 823 838 7,291 

2013 3,424 555 1,501 218 835 866 7,400 

2014 3,429 560 1,501 216 843 876 7,425 

2015 3,432 564 1,509 217 848 888 7,459 

2016 3,438 569 1,524 217 850 891 7,490 

2017 3,416 575 1,538 218 850 891 7,487 

2018 3,392 580 1,550 218 850 881 7,472 

2019 3,371 585 1,563 218 850 876 7,463 

Sources: U.S. Department of Energy, Energy Information Administration (EIA). 2007c. “Annual Energy Outlook.” 

Available at <http://www.eia.doe.gov/oiaf/archive/aeo07/pdf/0383(2007).pdf>. As obtained on January 21, 

2007. 

 U.S. Department of Energy, Energy Information Administration (EIA). 2011. “Annual Energy Outlook.”; 

(Data accessed on October 11, 2011) [Source for 2016–2019 numbers.] 

<http://www.eia.gov/forecasts/aeo/pdf/0383(2011).pdf>. 

In 2008, operational capacity of U.S. petroleum refineries was expected to grow for the 

foreseeable future. The expansion of dozens of petroleum refineries had been announced 
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(Reuters, 2007). The Oil & Gas Journal’s (O&J) 2008 Worldwide Construction Update survey 

alone catalogued over 40 refining construction projects that had been announced in the United 

States. Table 2-21 lists selected refinery construction projects from the 2008 and 2011 O&J 

Worldwide Construction Update surveys. The projects listed include two refinery expansion 

projects and six new processes (distillation units, delayed cokers, and mild hydrocrackers) from 

the 2008 survey and two refinery expansion projects from the 2011 survey. 

Table 2-21. Selected Refinery Construction Projects: 2008–2014 

Company and Location Project 

Projected Added 

Capacity 

(barrels per day) 

Expected 

Completion 

Cenex Harvest States, Laurel, MT New delayed coker unit N/A 2008 

Frontier Oil Corp, El Dorado, KS New crude distillation unit 15,000 2008 

 New vacuum distillation unit 15,000 2008 

Holly Corp, Woods Cross, UT New Mild hydrocracker 15,000 2008 

Artesia, NM New Mild hydrocracker 15,000 2008 

Motiva Enterprises LLC, Port Arthur, 

TX 

Refinery expansion 325,000 2010 

Placid Refining Inc. New crude distillation unit 25,000 2010 

Sinclair Oil Corp, Tulsa, OK Refinery Expansion 45,000 2011 

Valero Energy Corp., Sunray, TX Refinery Expansion 25,000 2014 

Tesoro Corp., Mandan, ND Refinery Expansion 10,000 2012 

Sources: Oil and Gas Journal. April 7, 2008.Worldwide Construction Update. 

Oil and Gas Journal. April 4, 2011. Worldwide Construction Update 

 http://bismarcktribune.com/news/local/article_52ec198a-53d8-11e0-ad90-001cc4c03286.html 

In particular, several U.S. refineries are planning projects to expand their ability to handle 

cheaper and lower-quality varieties of crude oil (known as “heavy crudes”). For example, 

ConocoPhillips will be expanding its capacity to handle heavy crude oils at its refinery in 

Billings, Montana, to 46,000 barrels per day (Reuters, 2007). 

In addition to these expansions, in 2008 two entirely new refineries were potentially 

going to be constructed within the next 5 years. The first was the Arizona Clean Fuels Refinery 

in Phoenix. This facility was projected to cost $3 billion to construct and would be capable of 

producing 6 million gallons of gasoline, diesel, and jet fuel per day (Arizona Clean Fuels, 2007). 

Second, a proposal to construct the MHA Nation Clean Fuels Refinery in North Dakota was 
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2-43 

being reviewed. If constructed, this facility would be capable of producing 15,000 barrels of fuel 

per day (EPA, 2006). However, O&J’s Worldwide Construction Update Surveys for 2009 and 

2010 showed projects on hold and completion date delays due to lower petroleum product 

demand in North America. The April 2009 survey found that Marathon Oil Corp. planned to 

delay the expansion of its 100,000 barrels per day refinery in southwest Detroit. The company 

intended to finish the project in the fourth quarter of 2010. However two factors—namely a 

slowdown in gasoline demand and a delay in the Company’s Canadian crude production—

changed the date of completion to the middle of 2012. Construction on this project began in June 

of 2008, but is continuing at a slower pace than originally planned. Similarly the April 2009 

Survey found that Motiva Enterprises LLC, which is a joint venture between Shell Oil Company 

and Saudi Refining Inc., has delayed the expansion of its 285,000 barrels per day refinery at Port 

Arthur, Texas from late 2010 to the first quarter of 2012. The November 2009 Survey showed 

that Irving Oil Corporation and BP PLC suspended plans to build a 300,000 barrels per day 

refinery at St. John, NB. The companies conducted an 18 month feasibility study and found the 

project “was not viable at a time of global economic recession and dampening forecasts of 

petroleum product demand in America.” 

Overall, the EIA forecasts that U.S. operational capacity will decrease by a total of 5% 

between 2011 and 2019 (Table 2-22). The rate of capacity utilization is projected to average 86% 

during this period. 

Table 2-22. Full Production Capacity Utilization Rates for Petroleum Refineries 

Year 

Petroleum Refineries 

Capacity Utilization Rates 

(NAICS 324110) 

Gross Input to Atmospheric 

Crude Oil Distillation Units 

(1,000s of barrels per day) 

Operational Capacity 

(1,000s of barrels per day) 

2011 85.0% 14,946 17,583 

2012 83.2% 14,672 17,635 

2013 84.2% 14,836 17,626 

2014 84.7% 14,851 17,524 

2015 84.9% 14,847 17,497 

2016 85.6% 14,853 17,342 

2017 86.5% 14,827 17,142 

2018 87.5% 14,778 16,887 

2019 88.2% 14,743 16,706 

Sources: U.S. Department of Energy, Energy Information Administration (EIA). 2007c. “Annual Energy Outlook.” 

Available at <http://www.eia.doe.gov/oiaf/archive/aeo07/pdf/0383(2007).pdf>. As obtained on January 21, 

2007. 

 U.S. Department of Energy, Energy Information Administration (EIA). 2011. ”Annual Energy Outlook.”; 

(Data accessed on October 11, 2011) [Source for 2016–2019 numbers.] 

<http://www.eia.gov/forecasts/aeo/pdf/0383(2011).pdf>. 
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2.6 References 

American Petroleum Institute (API). 2006. “FYI on Refineries: Operating at Record Levels.” 

Available at <http://new.api.org/aboutoilgas/sectors/refining/upload/ 

FYI_Refineries.pdf>. As obtained on October 31, 2006. 

Arizona Clean Fuels. 2007. Company Home Page. Available at 

<http://www.arizonacleanfuels.com/>. As obtained on February 5, 2007. 

Arabian American Develop Co., South Hampton Resources, Inc. Arabian American 

Development Co. Q4 & FY2010 Financial Results. (Data accessed on 10/21/11) [Source 

for 2010 numbers.] <http://www.arabianamericandev.com/images/uploads/investor/ 

2010eoyearningspresentation.pdf> 

Arabian American Development Co. April 6, 2007. 10K for year ended December 31, 2006. 

EDGAR Database. Available at <http://www.sec.gov/Archives/edgar/data/ 

7039/000095013407007709/0000950134-07-007709-index.htm>. 

Calumet Specialty Products Partners, Morningstar for Calumet Specialty Products Partners 10K. 

February 22, 2011. 10K for year ended December 31, 2010. (Data accessed on 10/21/11) 

[Source for 2010 numbers.] <http://quote.morningstar.com/stock-filing/AnnualReport/2010/12/31/t.aspx?t=XNAS:CLMT&ft=10-

K&d=c7dd2813722445ded56c7e3aefebf2ca> 

Calumet Specialty Products Partners. February 23, 2007. 10K for year ended December 31, 

2006. EDGAR Database. Available at <http://www.sec.gov/Archives/edgar/data/ 

1340122/000095013407003992/h43776e10vk.htm>. 

Copyright 2011 Experian Information Solutions, Inc., Experian Business Reports accessed 

through LexisNexis at James Branch Cabell Library (Virginia Commonwealth 

University). 

Copyright 2011 Harte-Hanks Market Intelligence, Inc., All Rights Reserved. CI Technology 

Database, September 2011. 

CVR Energy Inc. 2006. Google Finance. Available at 

<http://finance.google.com/finance?q=NYSE:CVI>. As obtained on February 28, 2008. 

CVR Energy Inc., EDGAR database for CVR Energy Inc. 10K. March 7, 2011. 10K for year 

ended December 31, 2010. (Data accessed on 10/23/11) [Source for 2010 numbers.] 

<http://www.sec.gov/Archives/edgar/data/1376139/000095012311022741/y90110e10vk.

htm> 

Dun & Bradstreet Small Business Solutions. Small Business Database. Available at 

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Inc. 
*** Draft – Do Not Cite, Quote, or Release During Review ***

2-45 

Energy Information Administration (EIA), Form EIA-820, “Annual Refinery Report.” Table 3. 

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<http://www.eia.gov/petroleum/refinerycapacity/> 

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and Antitrust Enforcement.” Available at <http://www.ftc.gov/opa/2004/08/ 

oilmergersrpt.shtm>. As obtained on February 6, 2007. 

Gale Research Inc. 2007. Ward’s Business Directory of U.S. Private and Public Companies. 

Detroit: Gale Research. 

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Prices.” Available at <http://www.gao.gov/new.items/d07902t.pdf>. As obtained on 

February 6, 2007. 

Global Duns Market Identifiers, accessed through LexisNexis at University of Virginia’s 

Alderman Library. 

Holly Corporation. March 1, 2007. 10K for year ended December 31, 2006. EDGAR Database. 

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d44106e10vk.htm>. 

Holly Corporation, EDGAR database for Holly Corporation 10K. February 25, 2011. 10K for 

year ended December 31, 2010. (Data accessed on 10/23/11) [Source for 2010 numbers.] 

<http://files.shareholder.com/downloads/FTO/1428853845x0xS950123-11-

18524/48039/filing.pdf> 

Hoovers 2011 Online Data, accessed through University of South Carolina’s Moore School of 

Business Library. Hoovers 2011 Online Data reflects either actual data for 2010/2011 

reported by companies or estimated data for 2011. 

Hoovers. 2007. Free Content, Company Information. Available at 

<http://www.hoovers.com/free/>. As obtained on April 11, 2007. 

Langinier, Corrine. 2004. “Are Patents Strategic Barriers to Entry?” Journal of Economics and 

Business 56:349-361. 

MathTech, Inc. 1997. “Industry Profile for the Petroleum Refinery NESHAP.” Available at 

<http://www.epa.gov/ttnecas1/regdata/IPs/Petroleum%20Refinery%20 

(Sulfur%20Recovery%20Units,%20Catalytic%20Crackin.pdf>. As obtained on October 

31, 2006. 

Million Dollar Database online, 2011, accessed through University of South Carolina’s Moore 

School of Business Library. Million Dollar Online Data reflects either actual data for 

2011 reported by companies or estimated data for 2011. 
*** Draft – Do Not Cite, Quote, or Release During Review ***

2-46 

Nicholson, Walter. 2005. Microeconomic Theory: Basic Principles and Extensions. Mason, OH: 

South-Western Publishing. 

Oil and Gas Journal, December 6, 2010 

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2060-0657 

Reference USA, accessed thru Jefferson Madison Regional Library, Charlottesville, Virginia. 

Oil and Gas Journal. April 7, 2008.Worldwide Construction Update.. 

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Pennsylvania: RMA, Inc. 

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2011. 

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U.S. Bureau of Labor Statistics (BLS). 2007. “Producer Price Index Industry Data: Customizable 

Industry Data Tables.” Available at <http://www.bls.gov/ppi/>. As obtained on October 

11, 2007. 

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General Statistics: Statistics for Industry Groups and Industries: 2009 and 2008 “ Release 

Date: 12/3/10 ; (Data accessed on 10/10/11). [Source for 2008 and 2009 numbers] 

<http://factfinder.census.gov/servlet/IBQTable?_bm=y&-NAICSASM=324110&-

ds_name=AM0931GS101&-ib_type=NAICSASM&-_industry=324110&-_lang=en> 
*** Draft – Do Not Cite, Quote, or Release During Review ***

2-47 

U.S. Census Bureau, using American FactFinder; “Sector 31: Manufacturing: Industry Series: 

Detailed Statistics by Industry for the United States: 2007” Release Date 10/30/09; (Data 

accessed on 10/11/11). [Source for 2007 numbers] 

<http://factfinder.census.gov/servlet/IBQTable?_bm=y&-geo_id=01000US&-

ds_name=EC0731I1&-NAICS2007=324110&-_lang=en> 

U.S. Census Bureau, using American FactFinder; “Sector 31: Manufacturing: Industry Series: 

Materials Consumed by Kind for the United States: 2007” Release Date 10/30/09; (Data 

accessed on 10/11/11). [Source for 2007 numbers] <http://factfinder.census.gov/ 

servlet/IBQTable?_bm=y&-ds_name=EC0731I3&-NAICS2007=324110&-

ib_type=NAICS2007&-geo_id=&-_industry=324110&-_lang=en&-

fds_name=EC0700A1> 

U.S. Census Bureau, using American FactFinder; “Sector 31: Manufacturing: Subject Series: 

Concentration Ratios: Share of Value of Shipments Accounted for by the 4, 8, 20, and 50 

Largest Companies for Industries: 2007.” Release Date 1/7/2011; (Data accessed on 

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servlet/IBQTable?_bm=y&-ds_name=EC0731SR12&-NAICS2007=324110&-

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_industry=324110&-_lang=en> 

U.S. Department of Commerce, Bureau of the Census, FactFinder. 2011. 2009 Annual Survey of 

Manufactures. 1996–2011. Obtained through American FactFinder Database. (Data 

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Manufacturers. M95(AS)-1. Washington, DC: Government Printing Office. Available at 

<http://www.census.gov/prod/2/manmin/asm/m95as1.pdf>. As obtained on October 23, 

2006. 

U.S. Department of Commerce, Bureau of the Census. 1998. 1996 Annual Survey of 

Manufacturers. M96(AS)-1 (RV). Washington, DC: Government Printing Office. 

Available at <http://www.census.gov/prod/3/98pubs/m96-as1.pdf>. As obtained on 

October 23, 2006. 

U.S. Department of Commerce, Bureau of the Census. 2000. “Population Density by County: 

Census 2000 Summary File 1 (SF 1) 100-Percent Data”. Available through American 

FactFinder <http://factfinder.census.gov/home/saff/main.html?_lang=en>. As obtained 

on February 21, 2008. 

U.S. Department of Commerce, Bureau of the Census. 2001. 1999 Annual Survey of 

Manufacturers. M99(AS)-1 (RV). Washington, DC: Government Printing Office. 

Available at <http://www.census.gov/prod/2001pubs/m99-as1.pdf>. As obtained on 

October 23, 2006. 
*** Draft – Do Not Cite, Quote, or Release During Review ***

2-48 

U.S. Department of Commerce, Bureau of the Census. 2003a. 2001 Annual Survey of 

Manufacturers. M01(AS)-1. Washington, DC: Government Printing Office. Available at 

<http://www.census.gov/prod/2003pubs/m01as-1.pdf>. As obtained on October 23, 2006. 

U.S. Department of Commerce, Bureau of the Census. 2003b. 2001 Annual Survey of 

Manufacturers. M01(AS)-2. Washington, DC: Government Printing Office. Available at 

<http://www.census.gov/prod/2003pubs/m01as-2.pdf. As obtained on March 4, 2008. 

U.S. Department of Commerce, Bureau of the Census. 2004. 2002 Economic Census, Industry 

Series—Petroleum Refineries. Washington, DC: Government Printing Office. Available 

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2006. 

U.S. Department of Commerce, Bureau of the Census. 2006. 2005 Annual Survey of 

Manufacturers. M05(AS)-1. Washington, DC: Government Printing Office. Available at 

<http://www.census.gov/prod/2005pubs/am0431gs1.pdf>. As obtained on October 23, 

2006. 

U.S. Department of Commerce, Bureau of the Census. 2007. 2006 Annual Survey of 

Manufacturers. Obtained through American Fact Finder Database 

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mbbl_a_cur.htm>. 

U.S. Department of Energy, 2011 Energy Information Administration (EIA). 1996–2011. 

“Petroleum Supply Annuals, Volume 1.” (Data accessed on October 7, 2011) [Source for 

2007–2010 numbers.] <http://www.eia.gov/dnav/pet/pet_pnp_refp_dc_nus_ 

mbbl_a.htm>. 

U.S. Department of Energy, 2011 Energy Information Administration (EIA). 1996–2011. 

“Petroleum Supply Annuals, Volume 1.” (Data accessed on October 7, 2011.) [Source for 

2007–2010 numbers.] <http://www.eia.gov/dnav/pet/pet_move_imp_dc_NUSZ00_mbbl_a.htm> 

U.S. Department of Energy, 2011 Energy Information Administration (EIA). 1996–2011. 

“Petroleum Supply Annuals, Volume 1.” (Data accessed on October 7, 2011.) [Source for 

2007–2010 numbers] <http://www.eia.gov/dnav/pet/pet_move_exp_dc_NUSZ00_mbbl_a.htm>. 

U.S. Department of Energy, 2011 Energy Information Administration (EIA). 1996–2011. 

“Petroleum Supply Annuals, Volume 1.” (Data accessed on October 7, 2011.) [Source for 

2007–2010 numbers.]<http://www.eia.gov/dnav/pet/pet_pri_refoth_dcu_nus_a.htm>. 
*** Draft – Do Not Cite, Quote, or Release During Review ***

2-49 

U.S. Department of Energy, Energy Information Administration (EIA). 1996–2007. “Petroleum 

Supply Annuals, Volume 1.” Available at <http://www.eia.doe.gov/oil_gas/ 

petroleum/data_publications/petroleum_supply_annual/psa_volume1/psa_ 

volume1.html>. As obtained on October 31, 2007. 

U.S. Department of Energy, Energy Information Administration (EIA). 2006a. “A Primer on 

Gasoline Prices.” Available at <http://www.eia.doe.gov/bookshelf/brochures/ 

gasolinepricesprimer/printerversion.pdf>. As obtained on October 31, 2007. 

U.S. Department of Energy, Energy Information Administration (EIA). 1999a. “Petroleum: An 

Energy Profile 1999.” DOE/EIA-0545(99). Available at <http://tonto.eia.doe.gov/ 

FTPROOT/petroleum/054599.pdf>. As obtained on October 23, 2006. 

U.S. Department of Energy, Energy Information Administration (EIA). 2006b. “Refinery 

Capacity Report 2006.” Available at <http://www.eia.doe.gov/oil_gas/petroleum/ 

data_publications/refinery_capacity_data/refcapacity.html/>. As obtained on October 23, 

2006. 

U.S. Department of Energy, Energy Information Administration (EIA). 2006c. “Petroleum 

Supply Annual 2005, Volume 1.” Available at <http://www.eia.doe.gov/pub/oil_gas/ 

petroleum/data_publications/petroleum_supply_annual/psa_volume1/historical/2005/psa

_volume1_2005.html>. As obtained on October 31, 2007. 

U.S. Department of Energy, Energy Information Administration (EIA). 2007a. “Refinery 

Utilization and Capacity.” Available at <http://tonto.eia.doe.gov/dnav/pet/ 

pet_pnp_unc_dcu_nus_m.htm>. As obtained on January 7, 2008. 

U.S. Department of Energy, Energy Information Administration (EIA). 2007b. “Refiner 

Petroleum Product Prices by Sales Type.” Available at <http://tonto.eia.doe.gov/ 

dnav/pet/pet_pri_refoth_dcu_nus_m.htm>. As obtained on January 11, 2008. 

U.S. Department of Energy, Energy Information Administration (EIA). 2007c. “Annual Energy 

Outlook.” Available at <http://www.eia.doe.gov/oiaf/archive/aeo07/pdf/0383(2007).pdf>. 

As obtained on January 21, 2007. 

U.S. Department of Energy, Energy Information Administration (EIA). 2011, “Annual Energy 

Outlook.” (Data accessed on October 11, 2011) [Source for 2011–2019 

numbers.]<http://www.eia.gov/forecasts/aeo/pdf/0383(2011).pdf>. 

U.S. Department of Justice and the Federal Trade Commission. 1992. Horizontal Merger 

Guidelines. Available at <http://www.ftc.gov/bc/docs/horizmer.htm>. As obtained on 

October 28, 2006. 

U.S. Department of Labor, Occupational Safety and Health Administration (OSHA). 2003. 

OSHA Technical Manual, Section IV: Chapter 2, Petroleum Refining Processes. TED 01-

00-015. Washington, DC: U.S. DOL. Available at <http://www.osha.gov/dts/osta/ 

otm/otm_iv/otm_iv_2.html>. As obtained on October 23, 2006. 
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2-50 

U.S. Energy Information Administration (EIA), 2011a. “Refinery Utilization and Capacity.” 

Available at http://www.eia.gov/dnav/pet/pet_pnp_unc_dcu_nus_a.htm; Release date: 

7/28/11; (Data accessed on 10/11/11). [Source for 2007–2010 numbers] 

U.S. Energy Information Administration (EIA), Form EIA-820, “Annual Refinery Report. Table 

1. Number and Capacity of Operable Petroleum Refineries by PAD District and State as 

of January 1, 2011” Release Date: June 24, 2011; (Data accessed on 10/12/11). [Source 

for 2011 numbers.] <http://www.eia.gov/petroleum/refinerycapacity/> 

U.S. Environmental Protection Agency. 1995. “EPA Office of Compliance Sector Notebook 

Project: Profile of the Petroleum Refining Industry.” EPA/310-R-95-013. Washington, 

DC: U.S. EPA. Available at <http://www.epa.gov/compliance/resources/ 

publications/assistance/sectors/notebooks/petrefsn.pdf>. As obtained on October 23, 

2006. 

U.S. Environmental Protection Agency. 2006. “Proposed MHA Nation Clean Fuels Refinery.” 

Available at <http://www.epa.gov/Region8/compliance/nepa/refinerydeis.html>. As 

obtained on February 6, 2007. 

Ward’s Business Directory of Public and Private Companies, 2011, accessed at James Branch 

Cabell Library (Virginia Commonwealth University). 

Western Refining, Inc. March 8, 2007. 10K for year ended December 31, 2006. EDGAR 

Database. Available at <http://www.sec.gov/Archives/edgar/data/1339048/000095 

013407005096/h44360e10vk.htm>. 

Western Refining, Thomson Reuters Western Refining, Inc. 10K. March 8, 2011. 10K for year 

ended December 31, 2010. (Data accessed on 10/23/11) [Source for 2010 numbers.] 

<http://phx.corporate-ir.net/phoenix.zhtml?c=194293&p=irol-sec> 
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3- 1

3 NSPS REGULATORY OPTIONS, COSTS AND EMISSION REDUCTIONS 

FROM COMPLYING WITH THE NSPS 

The emissions reduction and cost impacts presented in this section for flares are revised 

estimates for the impacts of the final requirements of 40 CFR part 60, subpart Ja for flares, as 

amended by this action. The impacts are expressed as incremental differences between the 

impacts of petroleum refinery process units complying with the final amendments to subpart Ja 

and the current NSPS requirements of 40 CFR part 60, subpart J (i.e., baseline). The impacts are 

presented for petroleum refinery flares that commence construction, reconstruction or 

modification over the next 5 years. We anticipate that there will be 400 affected flares over the 

next 5 years, or about three flares per refinery, and we estimate that 30 percent of the 400 

affected flares, or 120 flares, either would meet the definition of “emergency flare” in 40 CFR 

part 60, subpart Ja or would be equipped with a flare gas recovery system. Therefore, the values 

presented in this section include the costs and emissions reductions for 400 flares to comply with 

the flare management plan and root cause and corrective action analyses requirements and for 

280 flares to comply with the sulfur and flow monitoring requirements. The cost and emissions 

reductions for the affected flares to comply with the short-term H2S concentration of 162 ppmv 

in the fuel gas are included in the baseline rather than the incremental impacts because this limit 

is unchanged from the requirements in subpart J. For further detail on the methodology of these 

calculations, see Documentation of Impact Estimates for Fuel Gas Combustion Device and Flare 

Regulatory Options for Amendments to the Petroleum Refinery NSPS, in Docket ID No. EPAHQ-OAR-2007-0011. 

We estimate that the final requirements for flares will reduce emissions of SO2 by 3,200 

tons per year (tons/yr), NOx by 1,100 tons/yr and VOC by 3,400 tons/yr from the baseline. The 

estimated annual cost, including annualized capital costs, is a cost savings of about $79 million 

(2006 dollars) due to the replacement of some natural gas purchases with recovered flare gas and 

the retention of intermediate and product streams due to a reduction in the number of 

malfunctions associated with refinery process units and ancillary equipment connected to the 

flare. The overall cost effectiveness is a cost savings of about $10,000 per ton of combined 

pollutants removed. The estimated nationwide 5-year incremental emissions reductions and cost 

impacts for the final standards are summarized in Tables 3-1 and 3-2 below. 
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3- 2

Table 3-1. National Incremental Emission Reductions for Petroleum Refinery Flares 

Subject to Amended Standards Under 40 CFR part 60, subpart Ja (Fifth Year After 

Applicability Date) 

Subpart Ja Requirements 

Total capital 

cost ($1,000) 

Total annual 

cost without 

credit 

($1,000/yr) 

Natural gas 

offset/ product 

recovery credit 

($1,000) 

Total Annual 

Cost ($1,000/ 

yr) 

Estimates from June 2008 Final 

Rule 40,000 -7,000 

Revised Estimates for Amendments 460,000 100,000 -180,000 -79,000 

Table 3-2. National Incremental Cost Impacts and Cost-Effectiveness for Petroleum 

Refinery Flares Subject to Amended Standards Under 40 CFR part 60, subpart Ja (Fifth 

Year After Applicability Date) 

Subpart Ja Requirements 

Annual 

emission 

reductions 

(tons SO2/yr) 

Annual 

emission 

reductions 

(tons NOx/yr) 

Annual 

emission 

reductions 

 (tons VOC/yr) 

Cost 

effectiveness 

($/ton emissions 

reduced) 

Estimates from June 2008 Final 

Rule 80 6 200 -23,000 

Revised Estimates for Amendments 3,200 1,100 3,400 -10,000 

The cost, environmental and economic impacts for the final amendments to 40 CFR part 

60, subpart Ja for process heaters are not expected to be different than those reported for the final 

June 2008 standards. We expect owners and operators to install the same technology to meet 

these final amendments that we anticipated they would install to meet the June 2008 final subpart 

Ja requirements (i.e., ultra-low NOx burners). We did revise our emissions estimates based on the 

type of process heater, creating separate impacts for forced draft process heaters and natural draft 

process heaters. Dividing process heaters into separate subcategories, based on the draft type, 

required us to develop new distributions of baseline emissions for each type of process heater. 

The baseline emissions estimates for natural draft process heaters are slightly lower than those 

developed for the existing subpart Ja requirements (per affected process heater), but the average 

emission reduction achieved by ultra-low NOx burners was adjusted to 80 percent (rather than 75 

percent used for generic process heaters). For forced draft process heaters, the baseline (i.e., 

uncontrolled) emissions rate for forced draft process heaters was revised slightly upward, based 

on the available emissions data. Because of these differences, the mix of controls needed to meet 
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3- 3

a 40 ppmv emissions limit was no longer cost effective for forced draft process heaters, but the 

emission reductions associated with process heaters complying with the 60 ppmv standard were 

higher than those previously estimated for generic process heaters. Thus, the creation of new 

subcategories of process heaters with different emissions limits for each subcategory did not 

impact the control or compliance methods used by the facilities (i.e., BSER in all cases was 

based on the performance of advanced combustion monitoring controls in conjunction with ultralow NOx burners) and did not change the estimated compliance costs. As we do not have 

adequate data regarding the prevalence of natural draft process heaters versus forced draft 

process heaters that will become subject to the rule, we used the emission reductions estimated 

for the two different types of process heaters as a means to bound the range of anticipated NOx

emission reductions to be from 7,100 to 8,600 tons/yr in the fifth year after promulgation (see 

Revised NOx Impact Estimates for Process Heaters, in Docket ID No. EPA-HQ-OAR-2007-

0011). We estimated the emission reductions to be 7,500 tons/yr for the June 2008 final 

standards, which falls well within the anticipated range of emissions reductions for the standards 

we are finalizing here. Given the uncertainty in the emissions estimates, as well as the 

uncertainty in the relative number of natural draft process heaters versus forced draft process 

heaters, we concluded that the impacts previously developed for subpart Ja accurately represent 

the impacts for process heaters in these final amendments. 

We note that, in the preamble to the June 2008 final standards, we estimated costs and 

emissions reductions for 30 fuel gas combustion devices, but we subsequently determined that 

those estimates did not fully account for the number of affected flares (which, at the time, were 

considered a subset of fuel gas combustion devices). Therefore, in the preamble to the December 

2008 proposed amendments, we presented revised emission reduction and cost estimates for 

affected fuel gas combustion devices. Because these final amendments consider flares to be a 

separate affected source, the emission reductions and costs for fuel gas combustion devices are 

not affected by these final amendments and are not included in this action. Rather, the final 

emission reduction and cost estimates for fuel gas combustion devices are very close to the 

impacts presented in the June 2008 final rule; the details of the analysis and the final impacts are 

presented in Documentation of Impact Estimates for Fuel Gas Combustion Device and Flare 

Regulatory Options for Amendments to the Petroleum Refinery NSPS, in Docket ID No. EPAHQ-OAR-2007-0011. 
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3- 4

The final amendments to 40 CFR part 60, subpart J are technical corrections or 

clarifications to the existing rule and should have no negative emissions impacts. 
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4-1 

4 ECONOMIC IMPACT ANALYSIS: METHODS AND RESULTS 

The economic impact analysis (EIA) is designed to inform decision makers about the 

potential economic consequences of a regulatory action. The analysis consists of estimating the 

social costs of a regulatory program and the distribution of these costs across stakeholders 

(consumers and producers). As defined in EPA’s (2000) Guidelines for Preparing Economic 

Analyses,1

 social costs are the value of the goods and services lost by society resulting from 

using resources to comply with and implement a regulation and reductions in output. 

For this rule, annual cost savings of $79 million (2006 dollars) are expected in the fifth 

year. Based on the cost savings estimated for this rule, no negative economic impacts are 

expected. We therefore did not include a detailed economic impact analysis of this rule in the 

RIA. 

This rule is not a “significant energy action” as defined in Executive Order 13211, 

“Actions Concerning Regulations That Significantly Affect Energy Supply, Distribution, or Use” 

(66 FR 28355 [May 22, 2001]) because it is not likely to have a significant adverse effect on the 

supply, distribution, or use of energy. Since there is a cost savings associated with compliance 

with this rule, there will be no increase in domestic prices, and no significant increase in our 

dependence on foreign energy supplies. Finally, today’s action will have no adverse effect on 

crude oil supply, coal production, electricity production, and energy distribution. Based on the 

findings from the analysis of impacts on energy markets, we conclude that today’s action is not a 

“significant energy action” as defined in Executive Order 13211. 

 

1

 These guidelines are currently under review by the Agency. 
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5- 1

5 SMALL BUSINESS ANALYSIS AND EXECUTIVE ORDERS 

The Regulatory Flexibility Act (RFA) generally requires an agency to prepare a 

regulatory flexibility analysis of any rule subject to notice and comment rulemaking 

requirements under the Administrative Procedure Act or any other statute unless the agency 

certifies that the rule will not have a significant economic impact on a substantial number of 

small entities.1

 

In indicated in Section 2, 36 small companies owning petroleum refineries are classified 

as small according to the Small Business Administration. As previously discussed, small 

businesses in the petroleum refining industry (NAICS code 324110) are defined for the purposes 

of this rule as having 1,500 or fewer employees.2 

5.1 Results of Small Business Analysis 

After considering the economic impact of today’s action on small entities, we certify that 

this action will not have a significant economic impact on a substantial number of small entities. 

Of the affected entities, none are estimated to incur any annualized compliance cost, but should 

expect cost savings as mentioned in Section 4 of this RIA. 

5.2 Unfunded Mandates 

This rule does not contain a Federal mandate that may result in expenditures of $100 

million or more for State, local, and tribal governments, in the aggregate, or the private sector in 

any one year. The costs of the final amendments would not increase costs associated with the 

final rule. Thus, this rule is not subject to the requirements of sections 202 or 205 of the 

Unfunded Mandates Reform Act of 1995 (UMRA). 

This rule is also not subject to the requirements of section 203 of UMRA because it 

contains no regulatory requirements that might significantly or uniquely affect small 

governments. The proposed amendments contain no requirements that apply to such 

governments, and impose no obligations upon them. 

5.3 Environmental Justice 

Executive Order 12898 (59 FR 7629, February 16, 1994) establishes Federal executive 

policy on environmental justice. Its main provision directs Federal agencies, to the greatest 

extent practicable and permitted by law, to make environmental justice part of their mission by 

 

1

 Small entities include small businesses, small organizations, and small governmental jurisdictions. 

2

 Refer to http://www.sba.gov/content/table-small-business-size-standards for more information on SBA small 

business size standards. 
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5- 2

identifying and addressing, as appropriate, disproportionately high and adverse human health or 

environmental effects of their programs, policies, and activities on minority populations and lowincome populations in the United States. 

EPA has determined that this final rule will not have disproportionately high and adverse 

human health or environmental effects on minority or low-income populations because it 

increases the level of environmental protection for all affected populations without having any 

disproportionately high and adverse human health or environmental effects on any population, 

including any minority or low-income population. This rule is a nationwide standard that will 

yield reductions in various criteria pollutant emissions from new, modified, and reconstructed 

process heaters and flares at petroleum refineries, thus decreasing the amount of such emissions 

to which all affected populations are exposed. 

 
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6-1 

6 HUMAN HEALTH BENEFITS OF EMISSIONS REDUCTIONS 

Synopsis 

In this section, we provide an estimate of the monetized benefits for the final Petroleum 

Refineries NSPS Reconsideration associated with reducing exposure to ambient particulate 

matter (PM) by reducing emissions of PM2.5 precursors including SO2, NOx, and VOCs, as well 

as climate benefits associated with reducing emissions of CO2. SO2, NOx, and VOCs are 

precursors to PM2.5, and NOx and VOCs are precursors to ozone. These estimates reflect the 

monetized human health benefits of reducing cases of morbidity and premature mortality among 

populations exposed to PM2.5 reduced by this reconsideration. We estimate the total monetized 

benefits to be $270 million to $580 million at a 3% discount rate and $240 million to $530 

million at a 7% discount rate in the fifth year (2017). All estimates are in 2006$. 

 

These estimates reflect EPA’s most current interpretation of the scientific literature. 

Higher or lower estimates of benefits are possible using other assumptions; examples of this are 

provided in Figure 6-2 on page 6-14). Data, resource, and methodological limitations prevented 

EPA from monetizing the benefits from several important benefit categories, including benefits 

from reducing direct exposure to NO2 and SO2, ozone exposure, ecosystem effects, and visibility 

impairment. 

6.1 Calculation of PM2.5-Related Human Health Benefits 

This final NSPS Reconsideration would reduce emissions of SO2, NOX, and VOCs. 

Because these emissions are precursors to PM2.5, reducing these emissions would also reduce 

PM2.5 formation, human exposure and the incidence of PM2.5-related health effects. Due to 

analytical limitations, it was not possible to provide a comprehensive estimate of PM2.5-related 

benefits or provide estimates of the health benefits associated with direct exposure to SO2 and 

NOx or exposure to ozone. Instead, we used the “benefit-per-ton” approach to estimate these 

benefits. The methodology employed in this analysis is similar to the work described in Fann, 

Fulcher, and Hubbell (2009), but represents an improvement that EPA believes would provide 

more reliable estimates of PM2.5-related health benefits for emissions reductions in specific 

sectors. The key assumptions are described in detail below. These PM2.5 benefit-per-ton 

estimates provide the total monetized human health benefits (the sum of premature mortality and 

premature morbidity) of reducing one ton of PM2.5 from a specified source. EPA has used the 
*** Draft – Do Not Cite, Quote, or Release During Review ***

6-2 

benefit per-ton technique in several previous RIAs, including the recent SO2 NAAQS RIA (U.S. 

EPA, 2010). 

The Integrated Science Assessment (ISA) for Particulate Matter (U.S. EPA, 2009b) 

identified the human health effects associated with ambient PM2.5, which include premature 

morality and a variety of morbidity effects associated with acute and chronic exposures. Table 6-

1 shows the quantified and unquantified benefits captured in those benefit-per-ton estimates, but 

this table does not include entries for the unquantified health effects associated with exposure to 

ozone, SO2, and NOx nor welfare effects such as ecosystem effects and visibility that are 

described in section 6.2. It is important to emphasize that the list of unquantified benefit 

categories is not exhaustive, nor is quantification of each effect complete. 
*** Draft – Do Not Cite, Quote, or Release During Review ***

6-3 

Table 6-1: Human Health Effects of PM2.5 

Category Specific Effect 

Effect Has 

Been 

Quantified 

Effect Has 

Been 

Monetized 

More 

Information 

(refers to 

CSAPR RIA) 

Improved Human Health 

Reduced incidence of 

premature mortality 

from exposure to PM2.5

Adult premature mortality based on cohort 

study estimates and expert elicitation 

estimates (age >25 or age >30) 

  Section 5.4 

Infant mortality (age <1)   Section 5.4 

Reduced incidence of 

morbidity from 

exposure to PM2.5

Non-fatal heart attacks (age > 18)   Section 5.4 

Hospital admissions—respiratory (all 

ages)   Section 5.4 

Hospital admissions—cardiovascular (age 

>20)   Section 5.4 

Emergency room visits for asthma (all 

ages)   Section 5.4 

Acute bronchitis (age 8-12)   Section 5.4 

Lower respiratory symptoms (age 7-14)   Section 5.4 

Upper respiratory symptoms (asthmatics 

age 9-11)   Section 5.4 

Asthma exacerbation (asthmatics age 6-

18)   Section 5.4 

Lost work days (age 18-65)   Section 5.4 

Minor restricted-activity days (age 18-65)   Section 5.4 

Chronic Bronchitis (age >26)   Section 5.4 

Emergency room visits for cardiovascular 

effects (all ages) -- -- Section 5.4 

Strokes and cerebrovascular disease (age 

50-79) -- -- Section 5.4 

Other cardiovascular effects (e.g., other 

ages) -- -- PM ISA2

Other respiratory effects (e.g., pulmonary 

function, non-asthma ER visits, nonbronchitis chronic diseases, other ages and 

populations) 

-- -- PM ISA2

Reproductive and developmental effects 

(e.g., low birth weight, pre-term births, 

etc) 

-- -- PM ISA2,3

Cancer, mutagenicity, and genotoxicity 

effects -- -- PM ISA2,3

1 We assess these benefits qualitatively due to time and resource limitations for this analysis. 2

 We assess these benefits qualitatively because we do not have sufficient confidence in available data or methods. 3

 We assess these benefits qualitatively because current evidence is only suggestive of causality or there are other 

significant concerns over the strength of the association. 

Consistent with the Portland Cement NESHAP (U.S. EPA, 2009a), the benefits estimates 

utilize the concentration-response functions as reported in the epidemiology literature, as well as 

the 12 functions obtained in EPA’s expert elicitation study as a sensitivity analysis. 
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6-4 

 One estimate is based on the concentration-response (C-R) function developed from 

the extended analysis of American Cancer Society (ACS) cohort, as reported in Pope 

et al. (2002), a study that EPA has previously used to generate its primary benefits 

estimate. When calculating the estimate, EPA applied the effect coefficient as 

reported in the study without an adjustment for assumed concentration threshold of 10 

μg/m3 as was done in recent (2006-2009) Office of Air and Radiation RIAs. 

 One estimate is based on the C-R function developed from the extended analysis of 

the Harvard Six Cities cohort, as reported by Laden et al (2006). This study, 

published after the completion of the Staff Paper for the 2006 PM2.5 NAAQS, has 

been used as an alternative estimate in the PM2.5 NAAQS RIA and PM2.5 benefits 

estimates in RIAs completed since the PM2.5 NAAQS. When calculating the 

estimate, EPA applied the effect coefficient as reported in the study without an 

adjustment for assumed concentration threshold of 10 μg/m3 as was done in recent 

(2006-2009) RIAs. 

 Twelve estimates are based on the C-R functions from EPA’s expert elicitation study 

(Roman et al., 2008) on the PM2.5 -mortality relationship and interpreted for benefits 

analysis in EPA’s final RIA for the PM2.5 NAAQS. For that study, twelve experts 

(labeled A through L) provided independent estimates of the PM2.5 -mortality 

concentration-response function. EPA practice has been to develop independent 

estimates of PM2.5 -mortality estimates corresponding to the concentration-response 

function provided by each of the twelve experts, to better characterize the degree of 

variability in the expert responses. 

The effect coefficients are drawn from epidemiology studies examining two large 

population cohorts: the American Cancer Society cohort (Pope et al., 2002) and the Harvard Six 

Cities cohort (Laden et al., 2006).6

 These are logical choices for anchor points in our 

presentation because, while both studies are well designed and peer reviewed, there are strengths 

and weaknesses inherent in each, which we believe argues for using both studies to generate 

benefits estimates. Previously, EPA had calculated benefits based on these two empirical 

studies, but derived the range of benefits, including the minimum and maximum results, from an 

expert elicitation of the relationship between exposure to PM2.5 and premature mortality (Roman 

et al., 2008).7 Within this assessment, we include the benefits estimates derived from the 

 

6

 These two studies specify multi-pollutant models that control for SO2, among other co-pollutants. 7

 Please see the Section 5.2 of the Portland Cement RIA in Appendix 5A for more information regarding the change 

in the presentation of benefits estimates. 
*** Draft – Do Not Cite, Quote, or Release During Review ***

6-5 

concentration-response function provided by each of the twelve experts to better characterize the 

uncertainty in the concentration-response function for mortality and the degree of variability in 

the expert responses. Because the experts used these cohort studies to inform their 

concentration-response functions, benefits estimates using these functions generally fall between 

results using these epidemiology studies (see Figure 6-2). In general, the expert elicitation 

results support the conclusion that the benefits of PM2.5 control are very likely to be substantial. 

Readers interested in reviewing the general methodology for creating the benefit-per-ton 

estimates used in this analysis should consult the draft Technical Support Document (TSD) on 

estimating the benefits per ton of reducing PM2.5 and its precursors from the petroleum refineries 

sector (U.S. EPA, 2012). The primary difference between the estimates used in this analysis and 

the estimates reported in Fann, Fulcher, and Hubbell (2009) is the air quality modeling data 

utilized. While the air quality data used in Fann, Fulcher, and Hubbell (2009) reflects broad 

pollutant/source category combinations, the source apportionment modeling data used in this 

analysis is sector-specific. As a result, the benefit-per-ton estimates presented herein better 

reflect the geographic areas and population likely to be affected by the proposed rule. In this 

analysis, we apply these national benefit-per-ton estimates calculated for this sector separately 

for SO2 and NOx and multiply them by the corresponding emission reductions. 

These models assume that all fine particles, regardless of their chemical composition, are 

equally potent in causing premature mortality because the scientific evidence is not yet sufficient 

to allow differentiation of effects estimates by particle type. SO2 and NOx are the primary PM2.5

precursors affected by this rule. Even though we assume that all fine particles have equivalent 

health effects, the benefit-per-ton estimates vary between precursors depending on the location 

and magnitude of their impact on PM2.5 levels, which drive population exposure. The sectorspecific modeling does not provide estimates of the PM2.5-related benefits associated with 

reducing VOC emissions, but these unquantified benefits are generally small compared to other 

PM2.5 precursors (U.S. EPA, 2012). 

The benefit-per-ton coefficients in this analysis were derived using modified versions of 

the health impact functions used in the PM NAAQS Regulatory Impact Analysis. Specifically, 

this analysis uses the benefit-per-ton method first applied in the Portland Cement NESHAP RIA 

(U.S. EPA, 2009a), which incorporated three updates: a new population dataset, an expanded 

geographic scope of the benefit-per-ton calculation, and the functions directly from the 
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6-6 

epidemiology studies without an adjustment for an assumed threshold.8 Removing the threshold 

assumption is a key difference between the method used in this analysis of PM benefits and the 

methods used in RIAs prior to Portland Cement proposal, and we now calculate incremental 

benefits down to the lowest modeled PM2.5 air quality levels. 

Based on our review of the current body of scientific literature, EPA now estimates PMrelated mortality without applying an assumed concentration threshold. EPA’s Integrated 

Science Assessment for Particulate Matter (U.S. EPA, 2009b), which was reviewed by EPA’s 

Clean Air Scientific Advisory Committee (U.S. EPA-SAB, 2009a; U.S. EPA-SAB, 2009b), 

concluded that the scientific literature consistently finds that a no-threshold log-linear model 

most adequately portrays the PM-mortality concentration-response relationship while 

recognizing potential uncertainty about the exact shape of the concentration-response function. 

Consistent with this finding, we have conformed the previous threshold sensitivity 

analysis to the current state of the PM science by incorporating a “Lowest Measured Level” 

(LML) assessment, which is a method EPA has employed in several recent RIAs including the 

Cross-State Air Pollution Rule (U.S. EPA, 2011b). This information allows readers to determine 

the portion of population exposed to annual mean PM2.5 levels at or above the LML of each 

study; in general, our confidence in the estimated PM mortality decreases as we consider air 

quality levels further below the LML in major cohort studies that estimate PM-related mortality. 

While an LML assessment provides some insight into the level of uncertainty in the estimated 

PM mortality benefits, EPA does not view the LML as a threshold and continues to quantify PMrelated mortality impacts using a full range of modeled air quality concentrations. It is important 

to emphasize that we have high confidence in PM2.5-related effects down to the lowest LML of 

the major cohort studies, which is 5.8 μg/m3

. Just because we have greater confidence in the 

benefits above the LML, this does not mean that we have no confidence that benefits occur 

below the LML. For a summary of the scientific review statements regarding the lack of a 

threshold in the PM2.5-mortality relationship, see the Technical Support Document (TSD) 

entitled Summary of Expert Opinions on the Existence of a Threshold in the ConcentrationResponse Function for PM2.5-related Mortality (U.S. EPA, 2010b). 

 

8

 The benefit-per-ton estimates have also been updated since the Portland Cement RIA to incorporate a revised VSL, 

as discussed below. 
*** Draft – Do Not Cite, Quote, or Release During Review ***

6-7 

For this analysis, policy-specific air quality data is not available due to time or resource 

limitations. For these rules, we are unable to estimate the percentage of premature mortality 

associated with this specific rule’s emission reductions at each PM2.5 level. However, we believe 

that it is still important to characterize the distribution of exposure to baseline air quality levels. 

As a surrogate measure of mortality impacts, we provide the percentage of the population 

exposed at each PM2.5 level using the source apportionment modeling used to calculate the 

benefit-per-ton estimates for this sector. It is important to note that baseline exposure is only one 

parameter in the health impact function, along with baseline incidence rates population, and 

change in air quality. In other words, the percentage of the population exposed to air pollution 

below the LML is not the same as the percentage of the population experiencing health impacts 

as a result of a specific emission reduction policy. The most important aspect, which we are 

unable to quantify for rules without rule-specific air quality modeling, is the shift in exposure 

associated with this specific rule. Therefore, caution is warranted when interpreting the LML 

assessment for this rule. The results of this analysis are provided in Section 6.3. 

As is the nature of RIAs, the assumptions and methods used to estimate air quality 

benefits evolve over time to reflect the Agency’s most current interpretation of the scientific and 

economic literature. For a period of time (2004-2008), the Office of Air and Radiation (OAR) 

valued mortality risk reductions using a value of statistical life (VSL) estimate derived from a 

limited analysis of some of the available studies. OAR arrived at a VSL using a range of $1 

million to $10 million (2000$) consistent with two meta-analyses of the wage-risk literature. 

The $1 million value represented the lower end of the interquartile range from the Mrozek and 

Taylor (2002) meta-analysis of 33 studies. The $10 million value represented the upper end of 

the interquartile range from the Viscusi and Aldy (2003) meta-analysis of 43 studies. The mean 

estimate of $5.5 million (2000$)9 was also consistent with the mean VSL of $5.4 million 

estimated in the Kochi et al. (2006) meta-analysis. However, the Agency neither changed its 

official guidance on the use of VSL in rulemakings nor subjected the interim estimate to a 

scientific peer-review process through the Science Advisory Board (SAB) or other peer-review 

group. 

During this time, the Agency continued work to update its guidance on valuing mortality 

risk reductions, including commissioning a report from meta-analytic experts to evaluate 

methodological questions raised by EPA and the SAB on combining estimates from the various 

data sources. In addition, the Agency consulted several times with the Science Advisory Board 

 

9

 After adjusting the VSL for a different currency year (2006$) and to account for income growth to 2015 of the $5.5 

million value, the VSL is $7.4 million. 
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6-8 

Environmental Economics Advisory Committee (SAB-EEAC) on the issue. With input from the 

meta-analytic experts, the SAB-EEAC advised the Agency to update its guidance using specific, 

appropriate meta-analytic techniques to combine estimates from unique data sources and 

different studies, including those using different methodologies (i.e., wage-risk and stated 

preference) (U.S. EPA-SAB, 2007). 

 

Until updated guidance is available, the Agency determined that a single, peer-reviewed 

estimate applied consistently best reflects the SAB-EEAC advice it has received. Therefore, the 

Agency has decided to apply the VSL that was vetted and endorsed by the SAB in the Guidelines 

for Preparing Economic Analyses (U.S. EPA, 2000)10 while the Agency continues its efforts to 

update its guidance on this issue. This approach calculates a mean value across VSL estimates 

derived from 26 labor market and contingent valuation studies published between 1974 and 

1991. The mean VSL across these studies is $6.3 million (2000$).11 The Agency is committed 

to using scientifically sound, appropriately reviewed evidence in valuing mortality risk 

reductions and has made significant progress in responding to the SAB-EEAC’s specific 

recommendations. 

In implementing these rules, emission controls may lead to reductions in ambient PM2.5 

below the National Ambient Air Quality Standards (NAAQS) for PM in some areas and assist 

other areas with attaining the PM NAAQS. Because the PM NAAQS RIAs also calculate PM 

benefits, there are important differences worth noting in the design and analytical objectives of 

each RIA. The NAAQS RIAs illustrate the potential costs and benefits of attaining a new air 

quality standard nationwide based on an array of emission control strategies for different sources. 

In short, NAAQS RIAs hypothesize, but do not predict, the control strategies that States may 

choose to enact when implementing a NAAQS. The setting of a NAAQS does not directly result 

in costs or benefits, and as such, the NAAQS RIAs are merely illustrative and are not intended to 

be added to the costs and benefits of other regulations that result in specific costs of control and 

emission reductions. However, some costs and benefits estimated in this RIA account for the 

same air quality improvements as estimated in the illustrative PM2.5 NAAQS RIA. 

 

10 In revised Economic Guidelines (U.S. EPA, 2010c), EPA retained the VSL endorsed by the SAB with the 

understanding that further updates to the mortality risk valuation guidance would be forthcoming in the near future. 

Therefore, this report does not represent final agency policy. 11 In this analysis, we adjust the VSL to account for a different currency year ($2006) and to account for income 

growth to 2015. After applying these adjustments to the $6.3 million value, the VSL is $8.5 million. 
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6-9 

By contrast, the emission reductions for this RTR rule are from a specific class of wellcharacterized sources (i.e., petroleum refining facilities). In general, EPA is more confident in 

the magnitude and location of the emission reductions for these rules. It is important to note that 

emission reductions anticipated from these rules do not result in emission increases elsewhere. 

Emission reductions achieved under these and other promulgated rules will ultimately be 

reflected in the baseline of future NAAQS analyses, which would reduce the incremental costs 

and benefits associated with attaining the NAAQS. EPA remains forward looking towards the 

next iteration of the 5-year review cycle for the NAAQS, and as a result does not issue updated 

RIAs for existing NAAQS that retroactively update the baseline for NAAQS implementation. 

For more information on the relationship between the NAAQS and rules such as analyzed here, 

please see Section 1.2.4 of the SO2 NAAQS RIA (U.S. EPA, 2010a). 

 
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6-10 

Figure 6.1 illustrates the relative breakdown of the monetized PM2.5 health benefits. 

Figure 6-1: Breakdown of Monetized PM2.5 Health Benefits using Mortality Function 

from Pope et al. (2002)* 

*This pie chart breakdown is illustrative, using the results based on Pope et al. (2002) as an example. Using the 

Laden et al. (2006) function for premature mortality, the percentage of total monetized benefits due to adult 

mortality would be 97%. This chart shows the breakdown using a 3% discount rate, and the results would be similar 

if a 7% discount rate was used. 

 Table 6-2 provides a general summary of the monetized PM-related health benefits by 

precursor, including the emission reductions and benefit-per-ton estimates at discount rates of 

3% and 7%.12 Table 6-3 provides a summary of the reductions in health incidences as a result of 

the pollution reductions. In Table 6-4, we provide the benefits using our anchor points of Pope 

et al. and Laden et al. as well as the results from the expert elicitation on PM mortality. Figure 

 

12 To comply with Circular A-4, EPA provides monetized benefits using discount rates of 3% and 7% (OMB, 2003). 

These benefits are estimated for a specific analysis year (i.e., 2017), and most of the PM benefits occur within 

that year with two exceptions: acute myocardial infarctions (AMIs) and premature mortality. For AMIs, we 

assume 5 years of follow-up medical costs and lost wages. For premature mortality, we assume that there is a 

“cessation” lag between PM exposures and the total realization of changes in health effects. Although the 

structure of the lag is uncertain, EPA follows the advice of the SAB-HES to assume a segmented lag structure 

characterized by 30% of mortality reductions in the first year, 50% over years 2 to 5, and 20% over the years 6 to 

20 after the reduction in PM2.5 (U.S. EPA-SAB, 2004). Changes in the lag assumptions do not change the total 

number of estimated deaths but rather the timing of those deaths. Therefore, discounting only affects the AMI 

costs after the analysis year and the valuation of premature mortalities that occur after the analysis year. As such, 

the monetized benefits using a 7% discount rate are only approximately 10% less than the monetized benefits 

using a 3% discount rate. 

Adult Mortality ‐ Pope et

al. 93%

ChronicBronchitis 4%

AMI 2%

Acute Respiratory Symptoms

0.5%

InfantMortality 0.4%

Work Loss Days 0.2%

HospitalAdmissions, Cardio

0.2%

HospitalAdmissions, Resp

0.04%

AsthmaExacerbation 0.01%

Acute Bronchitis 0.01%

UpperResp Symp 0.00%

LowerResp Symp 0.00%

ERVisits, Resp 0.00%

Other1%
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6-11 

6-2 provides a visual representation of the range of PM2.5-related benefits estimates using 

concentration-response functions supplied by experts. 

Table 6-2: General Summary of Monetized PM-Related Health Benefits Estimates for 

Petroleum Refineries NSPS Reconsideration (millions of 2006$)*

Pollutant 

Emissions 

Reductions 

(tons) 

Benefit 

per ton 

(Pope, 

3%) 

Benefit 

per ton 

(Laden, 

3%) 

Benefit 

per ton 

(Pope, 

7%) 

Benefit 

per ton 

(Laden, 

7%) 

Total Monetized 

Benefits (millions 

of 2006$ at 3%) 

Total Monetized 

Benefits (millions 

of 2006$ at 7%) 

PM2.5 Precursors 

 SO2 3,050 $65,000 $160,000 $58,000 $140,000 $210 to $510 $190 to $460 

 NOX 590 $6,400 $16,000 $5,700 $14,000 $7.1 to $18 $6.4 to $16 

 Total $220 to $530 $190 to $480 

*

 All estimates are for the analysis year (2017), and are rounded to two significant figures so numbers may not sum 

across columns. It is important to note that the monetized benefits do not include reduced health effects from direct 

exposure to SO2 and NOx, ozone exposure, ecosystem effects, or visibility impairment. These estimates do not 

include CO2 benefits estimated at $49 million (3% discount rate). All fine particles are assumed to have equivalent 

health effects, but the benefit per ton estimates vary because each ton of precursor reduced has a different propensity 

to form PM2.5. The monetized benefits incorporate the conversion from precursor emissions to ambient fine 

particles. Confidence intervals are unavailable for this analysis because of the benefit-per-ton methodology. 

 
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6-12 

Table 6-3: Summary of Reductions in Health Incidences from PM2.5 Benefits for 

Petroleum Refineries NSPS Reconsideration* 

Avoided Premature Mortality

Pope et al. 26 

Laden et al. 66 

Avoided Morbidity 

Chronic Bronchitis 19 

Emergency Department Visits, Respiratory 19 

Hospital Admissions, Respiratory 5 

Hospital Admissions, Cardiovascular 10 

Acute Bronchitis 43 

Lower Respiratory 550 

Upper Respiratory 420 

Minor Restricted Activity Days 23,000 

Work Loss Days 3,800 

Asthma Exacerbation 920 

Acute Myocardial Infarction 27 

* All estimates are for the analysis year (2017) and are rounded to whole numbers with two significant figures. All 

fine particles are assumed to have equivalent health effects because the scientific evidence is not yet sufficient to 

allow differentiation of effects estimates by particle type. Confidence intervals are unavailable for this analysis 

because of the benefit-per-ton methodology. 
*** Draft – Do Not Cite, Quote, or Release During Review ***

6-13 

Table 6-4: All PM2.5 Benefits Estimates for the Petroleum Refineries NSPS 

Reconsideration at discount rates of 3% and 7% in 2017 (in millions of 

2006$)* 

 3% 7% 

Benefit-per-ton Coefficients Derived from Epidemiology Literature

Pope et al. $220 $190 

Laden et al. $530 $480 

Benefit-per-ton Coefficients Derived from Expert Elicitation 

Expert A $560 $510 

Expert B $430 $380 

Expert C $430 $380 

Expert D $300 $270 

Expert E $700 $630 

Expert F $390 $350 

Expert G $260 $230 

Expert H $320 $290 

Expert I $420 $380 

Expert J $350 $310 

Expert K $83 $74 

Expert L $290 $260 

*

All estimates are rounded to two significant figures. These estimates do not include CO2 benefits estimated at $49 

million (3% discount rate). The benefits estimates from the Expert Elicitation are provided as a reasonable 

characterization of the uncertainty in the mortality estimates associated with the concentration-response function. 

Confidence intervals are unavailable for this analysis because of the benefit-per-ton methodology 
*** Draft – Do Not Cite, Quote, or Release During Review ***

6-14 

Figure 6-2: Total Monetized PM2.5 Benefits of Final Petroleum Refineries 

Reconsideration in 2017 

*This graph shows the estimated benefits at discount rates of 3% and 7% using effect coefficients derived from the 

Pope et al. study and the Laden et al study, as well as 12 effect coefficients derived from EPA’s expert elicitation on 

PM mortality. The results shown are not the direct results from the studies or expert elicitation; rather, the estimates 

are based in part on the concentration-response function provided in those studies. These estimates do not include 

CO2 benefits estimated at $49 million (3% discount rate). 

6.2 Social Cost of Carbon and Greenhouse Gas Benefits 

EPA has assigned a dollar value to reductions in carbon dioxide (CO2) emissions using 

recent estimates of the “social cost of carbon” (SCC). The SCC is an estimate of the monetized 

damages associated with an incremental increase in carbon emissions in a given year. It is 

intended to include (but is not limited to) changes in net agricultural productivity, human health, 

property damages from increased flood risk, and the value of ecosystem services due to climate 

change. The SCC estimates used in this analysis were developed through an interagency process 

that included EPA and other executive branch entities, and concluded in February, 2010. EPA 

first used these SCC estimates in the benefits analysis for the final joint EPA/DOT Rulemaking 

to establish Light-Duty Vehicle Greenhouse Gas Emission Standards and Corporate Average 

Fuel Economy Standards; see the rule’s preamble for discussion about application of SCC (75 

$0

$100

$200

$300

$400

$500

$600

$700

Pope et al.

Laden et al.

Millions(2006$)

PM2.5mortality benefits estimates derived from 2 epidemiology functions and 12 expert functions

3% DR

7% DR
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6-15 

FR 25324; 5/7/10). The SCC Technical Support Document (SCC TSD) provides a complete 

discussion of the methods used to develop these SCC estimates.13 

The interagency group selected four SCC values for use in regulatory analyses, which we 

have applied in this analysis: $5, $21, $35, and $65 per metric ton of CO2 emissions14 in 2010, in 

2007 dollars. The first three values are based on the average SCC from three integrated 

assessment models, at discount rates of 2.5, 3, and 5 percent, respectively. SCCs at several 

discount rates are included because the literature shows that the SCC is quite sensitive to 

assumptions about the discount rate, and because no consensus exists on the appropriate rate to 

use in an intergenerational context. The fourth value is the 95th percentile of the SCC from all 

three models at a 3 percent discount rate. It is included to represent higher-than-expected impacts 

from temperature change further out in the tails of the SCC distribution. Low probability, high 

impact events are incorporated into all of the SCC values through explicit consideration of their 

effects in two of the three models as well as the use of a probability density function for 

equilibrium climate sensitivity. Treating climate sensitivity probabilistically results in more high 

temperature outcomes, which in turn lead to higher projections of damages. 

The SCC increases over time because future emissions are expected to produce larger 

incremental damages as physical and economic systems become more stressed in response to 

greater climatic change. Note that the interagency group estimated the growth rate of the SCC 

directly using the three integrated assessment models rather than assuming a constant annual 

growth rate. This helps to ensure that the estimates are internally consistent with other modeling 

assumptions. The SCC estimates for the analysis years of 2014, in 2005 dollars are provided in 

Table 6-5. 

 

13Docket ID EPA-HQ-OAR-2009-0472-114577, Technical Support Document: Social Cost of Carbon for 

Regulatory Impact Analysis Under Executive Order 12866, Interagency Working Group on Social Cost of 

Carbon, with participation by Council of Economic Advisers, Council on Environmental Quality, Department of 

Agriculture, Department of Commerce, Department of Energy, Department of Transportation, Environmental 

Protection Agency, National Economic Council, Office of Energy and Climate Change, Office of Management 

and Budget, Office of Science and Technology Policy, and Department of Treasury (February 2010). Also 

available at http://www.epa.gov/otaq/climate/regulations.htm 14The interagency group decided that these estimates apply only to CO2 emissions. Given that warming profiles and 

impacts other than temperature change (e.g., ocean acidification) vary across GHGs, the group concluded 

“transforming gases into CO2-equivalents using GWP, and then multiplying the carbon-equivalents by the SCC, 

would not result in accurate estimates of the social costs of non-CO2 gases” (SCC TSD, pg 13). 
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6-16 

Table 6-5. Social Cost of Carbon (SCC) Estimates (per tonne of CO2) for 2017a

Discount Rate and Statistic SCC estimate (2006$) 

5% (Average) $5.9 

3% (Average) $24.1 

2.5% (Average) $38.6 

3% (95th percentile) $73.9 

a The SCC values are dollar-year and emissions-year specific. SCC values represent only a partial accounting of 

climate impacts. 

When attempting to assess the incremental economic impacts of carbon dioxide 

emissions, the analyst faces a number of serious challenges. A recent report from the National 

Academies of Science (NRC, 2009) points out that any assessment will suffer from uncertainty, 

speculation, and lack of information about (1) future emissions of greenhouse gases, (2) the 

effects of past and future emissions on the climate system, (3) the impact of changes in climate 

on the physical and biological environment, and (4) the translation of these environmental 

impacts into economic damages. As a result, any effort to quantify and monetize the harms 

associated with climate change will raise serious questions of science, economics, and ethics and 

should be viewed as provisional. 

The interagency group noted a number of limitations to the SCC analysis, including the 

incomplete way in which the integrated assessment models capture catastrophic and noncatastrophic impacts, their incomplete treatment of adaptation and technological change, 

uncertainty in the extrapolation of damages to high temperatures, and assumptions regarding risk 

aversion. The limited amount of research linking climate impacts to economic damages makes 

the interagency modeling exercise even more difficult. The interagency group hopes that over 

time researchers and modelers will work to fill these gaps and that the SCC estimates used for 

regulatory analysis by the Federal government will continue to evolve with improvements in 

modeling. Additional details on these limitations are discussed in the SCC TSD. 

In light of these limitations, the interagency group has committed to updating the current 

estimates as the science and economic understanding of climate change and its impacts on 

society improves over time. Specifically, the interagency group has set a preliminary goal of 

revisiting the SCC values within two years or at such time as substantially updated models 

become available, and to continue to support research in this area. 
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6-17 

Applying the global SCC estimates to the estimated reductions in CO2 emissions for the 

range of policy scenarios, we estimate the dollar value of the climate-related benefits captured by 

the models for each analysis year. For internal consistency, the annual benefits are discounted 

back to net present value (NPV) terms using the same discount rate as each SCC estimate (i.e., 

5%, 3%, and 2.5%) rather than 3% and 7%.15 These estimates are provided in Table 6-6. 

Table 6-6. Monetized SCC-Derived Benefits of CO2 Emission Reductions in 2017 (millions 

of 2006$)a,b

Discount Rate and Statistic Benefits (millions of 2006$) 

Tons of CO2 2,021,067 

5% (Average) $12 

3% (Average) $49 

2.5% (Average) $78 

3% (95th percentile) $149 

a The SCC values are dollar-year and emissions-year specific. SCC values represent only a partial accounting of 

climate impacts. 

b

 The tonnes of CO2 emission reductions in this table have been reduced from 2,168,419 tonnes to reflect the 

anticipated emission increases associated with the energy disbenefits described in section 6.3. 

6.3 Energy Disbenefits 

In this section, we provide an estimate of the energy disbenefits associated with the 

increased emissions from additional energy usage.16 We estimate that electricity usage associated 

with operation of the control devices would increase by 158 GWh/yr nationwide.17 This 

electricity usage is anticipated to increase emissions of pollutants from electric utility boilers 

(EGU boilers) that supply electricity to the non-EGU boiler facilities by 147,352 tonnes CO2. In 

the calculation of CO2 benefits, we have already subtracted these CO2 emission increases 

associated with increased electricity usage from the CO2 emission reductions associated with the 

regulatory requirements in the benefits shown in Table 6-6. 

 

15It is possible that other benefits or costs of proposed regulations unrelated to CO2 emissions will be discounted at 

rates that differ from those used to develop the SCC estimates. 16As we use the term “energy disbenefits” in this analysis, we are not referring to the cost of purchasing additional 

electricity or fuel, which are captured within the cost estimates. We use the term to refer to the increase in 

emissions associated with additional energy use. 17 See Documentation of Impact Estimates for Fuel Gas Combustion Device and Flare Regulatory Options for 

Amendments to the Petroleum Refinery NSPS, in Docket ID No. EPA-HQ-OAR-2007-0011. 
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6-18 

6.4 Total Monetized Benefits 

The total monetized benefits of this rulemaking include both the PM-related health 

benefits as well as the CO2-related climate benefits. We estimate the total monetized benefits to 

be $270 million to $580 million at a 3% discount rate and $240 million to $530 million at a 7% 

discount rate in the fifth year (2017). All estimates are in 2006$. Figure 6-3 provides a visual 

representation of the breakdown of total monetized benefits by pollutant. 

Figure 6-3: Breakdown of Monetized Benefits for Final Petroleum Refineries NSPS 

Reconsideration by Pollutant 

* This chart uses the results based on Pope et al. (2002) and a 3% discount rate as an example. 

6.5 Unquantified Benefits 

The monetized benefits estimated in this RIA only reflect a subset of benefits attributable 

to the health effect reductions associated with ambient fine particles. Data, time, and resource 

limitations prevented EPA from quantifying the impacts to, or monetizing the benefits from 

several important benefit categories, including benefits from reducing direct exposure to SO2 and 

NOx, ozone exposure, ecosystem effects, and visibility impairment. NOx and SO2 emissions 

SO2

79%

NOX

3%

CO2

18%
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6-19 

also contribute to adverse welfare effects, including acidic deposition in aquatic and terrestrial 

ecosystems and visibility impairment. 

6.5.1 Additional SO2 and NO2 Benefits 

In addition to being a precursor to PM2.5, SO2 and NOx emissions are also associated with 

a variety of respiratory health effects. Unfortunately, we were unable to estimate the health 

benefits associated with reduced SO2 and NO2 exposure in this analysis because we do not have 

air quality modeling data available. Therefore, this analysis only quantifies and monetizes the 

PM2.5 benefits associated with the reductions in SO2 and NO2 emissions. 

Following an extensive evaluation of health evidence from epidemiologic and laboratory 

studies, the U.S. EPA has concluded that there is a causal relationship between respiratory health 

effects and short-term exposure to SO2 (U.S. EPA, 2008b). According to summary of the ISA in 

EPA’s risk and exposure assessment (REA) for the SO2 NAAQS, “the immediate effect of SO2 

on the respiratory system in humans is bronchoconstriction” (U.S. EPA, 2009b). Asthmatics are 

more sensitive to the effects of SO2 likely resulting from preexisting inflammation associated 

with this disease. A clear concentration-response relationship has been demonstrated in 

laboratory studies following exposures to SO2 at concentrations between 20 and 100 ppb, both in 

terms of increasing severity of effect and percentage of asthmatics adversely affected. Based on 

our review of this information, we identified four short-term morbidity endpoints that the SO2

ISA identified as a “causal relationship”: asthma exacerbation, respiratory-related emergency 

department visits, and respiratory-related hospitalizations. The differing evidence and associated 

strength of the evidence for these different effects is described in detail in the SO2 ISA. The SO2 

ISA also concluded that the relationship between short-term SO2 exposure and premature 

mortality was “suggestive of a causal relationship” because it is difficult to attribute the mortality 

risk effects to SO2 alone. Although the SO2 ISA stated that studies are generally consistent in 

reporting a relationship between SO2 exposure and mortality, there was a lack of robustness of 

the observed associations to adjustment for pollutants. 

Following an extensive evaluation of health evidence from epidemiologic and laboratory 

studies, the Integrated Science Assessment (ISA) for Nitrogen Dioxide concluded that there is a 

likely causal relationship between respiratory health effects and short-term exposure to NO2 

(U.S. EPA, 2008c). Persons with preexisting respiratory disease, children, and older adults may 

be more susceptible to the effects of NO2 exposure. Based on our review of this information, we 

identified four short-term morbidity endpoints that the NO2 ISA identified as a “likely causal 

relationship”: asthma exacerbation, respiratory-related emergency department visits, and 
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6-20 

respiratory-related hospitalizations. The differing evidence and associated strength of the 

evidence for these different effects is described in detail in the NO2 ISA. The NO2 ISA also 

concluded that the relationship between short-term NO2 exposure and premature mortality was 

“suggestive but not sufficient to infer a causal relationship” because it is difficult to attribute the 

mortality risk effects to NO2 alone. Although the NO2 ISA stated that studies consistently 

reported a relationship between NO2 exposure and mortality, the effect was generally smaller 

than that for other pollutants such as PM. 

SO2 and NOx emissions also contribute to a variety of adverse welfare effects, including 

acidic deposition, visibility impairment, nutrient enrichment (NOx only) and enhanced mercury 

methylation (SO2 only). Deposition of sulfur and nitrogen causes acidification, which can cause 

a loss of biodiversity of fishes, zooplankton, and macro invertebrates in aquatic ecosystems, as 

well as a decline in sensitive tree species, such as red spruce (Picea rubens) and sugar maple 

(Acer saccharum) in terrestrial ecosystems. In the northeastern United States, the surface waters 

affected by acidification are a source of food for some recreational and subsistence fishermen 

and for other consumers and support several cultural services, including aesthetic and 

educational services and recreational fishing. Biological effects of acidification in terrestrial 

ecosystems are generally linked to aluminum toxicity, which can cause reduced root growth, 

which restricts the ability of the plant to take up water and nutrients. These direct effects can, in 

turn, increase the sensitivity of these plants to stresses, such as droughts, cold temperatures, 

insect pests, and disease leading to increased mortality of canopy trees. Terrestrial acidification 

affects several important ecological services, including declines in habitat for threatened and 

endangered species (cultural), declines in forest aesthetics (cultural), declines in forest 

productivity (provisioning), and increases in forest soil erosion and reductions in water retention 

(cultural and regulating). (U.S. EPA, 2008d) 

Deposition of nitrogen is also associated with aquatic and terrestrial nutrient enrichment. 

In estuarine waters, excess nutrient enrichment can lead to eutrophication. Eutrophication of 

estuaries can disrupt an important source of food production, particularly fish and shellfish 

production, and a variety of cultural ecosystem services, including water-based recreational and 

aesthetic services. Terrestrial nutrient enrichment is associated with changes in the types and 

number of species and biodiversity in terrestrial systems. Excessive nitrogen deposition upsets 

the balance between native and nonnative plants, changing the ability of an area to support 

biodiversity. When the composition of species changes, then fire frequency and intensity can 

also change, as nonnative grasses fuel more frequent and more intense wildfires. (U.S. EPA, 

2008d) 
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6-21 

Mercury is a highly neurotoxic contaminant that enters the food web as a methylated 

compound, methylmercury (U.S. EPA, 2008d). The contaminant is concentrated in higher 

trophic levels, including fish eaten by humans. Experimental evidence has established that only 

inconsequential amounts of methylmercury can be produced in the absence of sulfate (U.S. EPA, 

2008d). Current evidence indicates that in watersheds where mercury is present, increased 

sulfate deposition very likely results in methylmercury accumulation in fish (Drevnick et al., 

2007; Munthe et al, 2007). The NOx/SOx Ecological ISA concluded that evidence is sufficient 

to infer a casual relationship between sulfur deposition and increased mercury methylation in 

wetlands and aquatic environments (U.S. EPA, 2008d). 

Reducing SO2 and NOx emissions and the secondary formation of PM2.5 would improve 

the level of visibility throughout the United States. Fine particles with significant lightextinction efficiencies include sulfates, nitrates, organic carbon, elemental carbon, and soil 

(Sisler, 1996). These suspended particles and gases degrade visibility by scattering and 

absorbing light. Higher visibility impairment levels in the East are due to generally higher 

concentrations of fine particles, particularly sulfates, and higher average relative humidity levels. 

In fact, particulate sulfate is the largest contributor to regional haze in the eastern U.S. (i.e., 40% 

or more annually and 75% during summer). In the western U.S., particulate sulfate contributes 

to 20-50% of regional haze (U.S. EPA, 2009c). Visibility has direct significance to people’s 

enjoyment of daily activities and their overall sense of wellbeing. Good visibility increases the 

quality of life where individuals live and work, and where they engage in recreational activities. 

6.5.2 Ozone Benefits 

In the presence of sunlight, NOx and VOCs can undergo a chemical reaction in the 

atmosphere to form ozone. Reducing ambient ozone concentrations is associated with 

significant human health benefits, including mortality and respiratory morbidity (U.S. EPA, 

2008a). Epidemiological researchers have associated ozone exposure with adverse health effects 

in numerous toxicological, clinical and epidemiological studies (U.S. EPA, 2006c). These health 

effects include respiratory morbidity such as fewer asthma attacks, hospital and ER visits, school 

loss days, as well as premature mortality. 

6.5.3 Visibility Impairment 

Reducing secondary formation of PM2.5 would improve visibility throughout the U.S. 

Fine particles with significant light-extinction efficiencies include sulfates, nitrates, organic 

carbon, elemental carbon, and soil (Sisler, 1996). Suspended particles and gases degrade 

visibility by scattering and absorbing light. Higher visibility impairment levels in the East are 
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6-22 

due to generally higher concentrations of fine particles, particularly sulfates, and higher average 

relative humidity levels. Visibility has direct significance to people’s enjoyment of daily 

activities and their overall sense of wellbeing. Good visibility increases the quality of life where 

individuals live and work, and where they engage in recreational activities. Previous analyses 

(U.S. EPA, 2006; U.S. EPA, 2011a; U.S. EPA, 2011b) show that visibility benefits are a 

significant welfare benefit category. Without air quality modeling, we are unable to estimate 

visibility related benefits, nor are we able to determine whether VOC emission reductions would 

be likely to have a significant impact on visibility in urban areas or Class I areas. 

6.6 Characterization of Uncertainty in the Monetized Benefits 

In any complex analysis, there are likely to be many sources of uncertainty. Many inputs 

are used to derive the final estimate of economic benefits, including emission inventories, air 

quality models (with their associated parameters and inputs), epidemiological estimates of 

concentration-response (C-R) functions, estimates of values, population estimates, income 

estimates, and estimates of the future state of the world (i.e., regulations, technology, and human 

behavior). For some parameters or inputs it may be possible to provide a statistical 

representation of the underlying uncertainty distribution. For other parameters or inputs, the 

necessary information is not available. As discussed in the PM2.5 NAAQS RIA (Table 5.5) (U.S. 

EPA, 2006), there are a variety of uncertainties associated with these PM benefits. Therefore, 

the estimates of annual benefits should be viewed as representative of the magnitude of benefits 

expected, rather than the actual benefits that would occur every year. 

It is important to note that the monetized benefit-per-ton estimates used here reflect 

specific geographic patterns of emissions reductions and specific air quality and benefits 

modeling assumptions. For example, these estimates do not reflect local variability in population 

density, meteorology, exposure, baseline health incidence rates, or other local factors. Use of 

these $/ton values to estimate benefits associated with different emission control programs (e.g., 

for reducing emissions from large stationary sources like EGUs) may lead to higher or lower 

benefit estimates than if benefits were calculated based on direct air quality modeling. Great care 

should be taken in applying these estimates to emission reductions occurring in any specific 

location, as these are all based on national or broad regional emission reduction programs and 

therefore represent average benefits-per-ton over the entire United States. The benefits-per-ton 

for emission reductions in specific locations may be very different than the estimates presented 

here. 
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6-23 

PM2.5 mortality benefits are the largest benefit category that we monetized in this 

analysis. To better characterize the uncertainty associated with mortality impacts that are 

estimated to occur in areas with low baseline levels of PM2.5, we included the LML assessment. 

For this analysis, policy-specific air quality data is not available due to time or resource 

limitations, thus we are unable to estimate the percentage of premature mortality associated with 

this specific rule’s emission reductions at each PM2.5 level. As a surrogate measure of mortality 

impacts, we provide the percentage of the population exposed at each PM2.5 level using the 

source apportionment modeling used to calculate the benefit-per-ton estimates for this sector. A 

very large proportion of the population is exposed at or above the lowest LML of the cohort 

studies (Figures 6-4 and 6-5), increasing our confidence in the PM mortality analysis. Figure 6-4 

shows a bar chart of the percentage of the population exposed to various air quality levels in the 

pre- and post-policy policy. Figure 6-5 shows a cumulative distribution function of the same 

data. Both figures identify the LML for each of the major cohort studies. As the policy shifts 

the distribution of air quality levels, fewer people are exposed to PM2.5 levels at or above the 

LML. Using the Pope et al. (2002) study, the 77% of the population is exposed to annual mean 

PM2.5 levels at or above the LML of 7.5 μg/m3. Using the Laden et al. (2006) study, 25% of the 

population is exposed above the LML of 10 μg/m3.

 As we model avoided premature deaths 

among populations exposed to levels of PM2.5, we have lower confidence in levels below the 

LML for each study. It is important to emphasize that we have high confidence in PM2.5-related 

effects down to the lowest LML of the major cohort studies. Just because we have greater 

confidence in the benefits above the LML, this does not mean that we have no confidence that 

benefits occur below the LML. 

A large fraction of the baseline exposure occurs below the level of the National Ambient 

Air Quality Standard (NAAQS) for annual PM2.5 at 15 μg/m3, which wasset in 2006. It is 

important to emphasize that NAAQS are not set at a level of zero risk. Instead, the NAAQS 

reflect the level determined by the Administrator to be protective of public health within an 

adequate margin of safety, taking into consideration effects on susceptible populations. While 

benefits occurring below the standard may be less certain than those occurring above the 

standard, EPA considers them to be legitimate components of the total benefits estimate. 
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6-24 

Figure 6-4. Percentage of Adult Population by Annual Mean PM2.5 Exposure in the 

Baseline 

 
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6-25 

Figure 6-5. Cumulative Distribution of Adult Population by Annual Mean PM2.5 

Exposure in the Baseline 

Above we present the estimates of the total benefits, based on our interpretation of the 

best available scientific literature and methods and supported by the SAB-HES and the NAS 

(NRC, 2002). The benefits estimates are subject to a number of assumptions and uncertainties. 

For example, for key assumptions underlying the estimates for premature mortality, which 

typically account for at least 90% of the total benefits, we were able to quantify include the 

following: 

1. PM2.5 benefits were derived through benefit per-ton estimates, which do not reflect 

local variability in population density, meteorology, exposure, baseline health 

incidence rates, or other local factors that might lead to an over-estimate or underestimate of the actual benefits of controlling directly emitted fine particulates. 

2. We assume that all fine particles, regardless of their chemical composition, are 

equally potent in causing premature mortality. This is an important assumption, 

because PM2.5 produced via transported precursors emitted from EGUs may differ 
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6-26 

significantly from direct PM2.5 released from diesel engines and other industrial 

sources, but no clear scientific grounds exist for supporting differential effects 

estimates by particle type. 

3. We assume that the health impact function for fine particles is linear down to the 

lowest air quality levels modeled in this analysis. Thus, the estimates include health 

benefits from reducing fine particles in areas with varied concentrations of PM2.5,

including both regions that are in attainment with fine particle standard and those that 

do not meet the standard down to the lowest modeled concentrations. 

4. To characterize the uncertainty in the relationship between PM2.5 and premature 

mortality (which typically accounts for 85% to 95% of total monetized benefits), we 

include a set of twelve estimates based on results of the expert elicitation study in 

addition to our core estimates. Even these multiple characterizations omit the 

uncertainty in air quality estimates, baseline incidence rates, populations exposed and 

transferability of the effect estimate to diverse locations. As a result, the reported 

confidence intervals and range of estimates give an incomplete picture about the 

overall uncertainty in the PM2.5 estimates. This information should be interpreted 

within the context of the larger uncertainty surrounding the entire analysis. For more 

information on the uncertainties associated with PM2.5 benefits, please consult the 

PM2.5 NAAQS RIA (Table 5.5). 

This RIA does not include the type of detailed uncertainty assessment found in the PM 

NAAQS RIA because we lack the necessary air quality input and monitoring data to run the 

benefits model. In addition, we have not conducted any air quality modeling for this rule. 

Moreover, it was not possible to develop benefit-per-ton metrics and associated estimates of 

uncertainty using the benefits estimates from the PM RIA because of the significant differences 

between the sources affected in that rule and those regulated here. However, the results of the 

Monte Carlo analyses of the health and welfare benefits presented in Chapter 5 of the PM RIA 

can provide some evidence of the uncertainty surrounding the benefits results presented in this 

analysis. 

 
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6-27 

 

6.7 References 

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type in estimates of the human health benefits of reducing a ton of air pollution.” Air Qual 

Atmos Health 2:169–176. 

Kochi, I., B. Hubbell, and R. Kramer. 2006. “An Empirical Bayes Approach to Combining 

Estimates of the Value of Statistical Life for Environmental Policy Analysis.” 

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spatial analysis of the American Cancer Society study linking particulate air pollution and 

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Laden, F., J. Schwartz, F.E. Speizer, and D.W. Dockery. 2006. Reduction in Fine Particulate Air 

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Office of Management and Budget (OMB). 2003. Circular A-4: Regulatory Analysis. 

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Pope, C.A., III, R.T. Burnett, M.J. Thun, E.E. Calle, D. Krewski, K. Ito, and G.D. Thurston. 

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U.S. Environmental Protection Agency (U.S. EPA). 2000. Guidelines for Preparing Economic 

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Summary of Expert Opinions on the Existence of a Threshold in the Concentration-Response 
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Function for PM2.5-related Mortality. Research Triangle Park, NC. June. Available on the 

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Air Act from 1990 to 2020. Office of Air and Radiation, Washington, DC. March. 

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Market Estimates throughout the World.” Journal of Risk and Uncertainty 27(1):5-76. 
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6-1 

7 COMPARISON OF BENEFITS AND COSTS 

EPA estimates the range of benefits of this reconsideration to be $270 million to $580 

million at a 3% discount rate and $240 million to $530 million at a 7% discount rate in 2017. 

The annualized costs are a cost savings of $79 million at a 7% interest rate. Thus, net benefits 

are $340 million to $660 million at a 3% discount rate for the benefits and $320 million to $610 

million at a 7% discount rate. All estimates are in 2006$. 

Table 7-1 shows a summary of the monetized benefits, social costs, and net benefits. 

Figure 7-1 shows the full range of net benefits estimates (i.e., benefits minus annualized costs) 

utilizing the 14 different PM2.5 mortality functions at the 3% discount rate, and Figure 7-2 shows 

this information at a 7% discount rate. EPA believes that the benefits of this rule are likely to 

exceed the costs by a substantial margin even when taking into account uncertainties in the cost 

and benefit estimates. 

Table 7-1. Summary of the Monetized Benefits, Social Costs, and Net Benefits for the 

Final Petroleum Refineries NSPS in 2017 (millions of 2006$)1

 3% Discount Rate 7% Discount Rate 

Total Monetized Benefits2 $270 to $580 $240 to $530 

Total Compliance Costs3 -$79 -$79 

Net Benefits $340 to $660 $320 to $610 

Non-monetized Benefits 

Health effects from ozone, SO2, NO2 exposure 

Health effects from PM2.5 exposure from VOCs 

Ecosystem effects 

Visibility impairment 

1

All estimates are for the implementation year (2017), and are rounded to two significant figures. 2

 The total monetized benefits reflect the human health benefits associated with reducing exposure to PM2.5 through 

reductions of PM2.5 precursors such as NOx and SO2 as well as CO2 benefits. It is important to note that the 

monetized benefits do not include the reduced health effects from direct exposure to SO2 and NOx, ozone 

exposure, ecosystem effects, or visibility impairment. Human health benefits are shown as a range from Pope et 

al. (2002) to Laden et al. (2006). These models assume that all fine particles, regardless of their chemical 

composition, are equally potent in causing premature mortality because the scientific evidence is not yet 

sufficient to allow differentiation of effects estimates by particle type. The net present value of reduced CO2

emissions is calculated differently than other benefits. This table includes monetized climate benefits using the 

global average social cost of carbon (SCC) estimated at a 3 percent discount rate because the interagency 

workgroup deemed the SCC estimate at a 3 percent discount rate to be the central value. 3

 The engineering compliance costs are annualized using a 7 percent discount rate. 
*** Draft – Do Not Cite, Quote, or Release During Review ***

6-2 

Figure 7-1. Net Benefits for Final Petroleum Refineries NSPS Reconsideration at 3% 

discount rate* 

*Net Benefits are quantified in terms of PM2.5 and CO2 benefits at a 3% discount rate for 2017. This graph shows 14 

benefits estimates combined with the cost estimate. All combinations are treated as independent and equally 

probable. All fine particles are assumed to have equivalent health effects, but the benefit per ton estimates vary 

because each ton of precursor reduced has a different propensity to become PM2.5. The monetized benefits 

incorporate the conversion from precursor emissions to ambient fine particles. 

$0

$100

$200

$300

$400

$500

$600

$700

$800

$900

Pope et al.

Laden et al.

Millions (2006$)

Cost estimate combinedwith total monetized benefits estimates derived from2epidemiology functions and 12 expert

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

6-3 

Figure 7-2. Net Benefits for Final Petroleum Refineries NSPS Reconsideration at 7% 

discount rate* 

*Net Benefits are quantified in terms of PM2.5 benefits at a 7% discount rate and CO2 benefits at a 3% discount rate 

for 2017. This graph shows 14 benefits estimates combined with the cost estimate. All combinations are treated as 

independent and equally probable. All fine particles are assumed to have equivalent health effects, but the benefit 

per ton estimates vary because each ton of precursor reduced has a different propensity to become PM2.5. The 

monetized benefits incorporate the conversion from precursor emissions to ambient fine particles. 

$0

$100

$200

$300

$400

$500

$600

$700

$800

Pope et al.

Laden et al.

Millions (2006$)

Cost estimate combinedwith total monetized benefits estimates derived from2epidemiology functions and 12 expert

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

A-1 

APPENDIX A 

PARENT COMPANY INFORMATION FOR PETROLEUM REFINERIES 

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

A-2 

Table A-1. Parent Company Information for Petroleum Refineries 

Facility Name City State 

Capacity 

(bbl/cd) Parent Company Name 

Parent Company 

Sales 

Parent Company 

Employment 

AGE Refining Inc San Antonio TX 14,021 AGE Refining, Inc. 65.00 124 

Alon Bakersfield 

Operating Inc 

Bakersfield CA Alon Israel Oil Company 

LTD 

7,283.06 12,000 

Alon Refining Krotz 

Springs Inc 

Krotz Springs LA 80,000 Alon Israel Oil Company 

LTD 

7,283.06 12,000 

Alon USA Energy Inc. Big Spring TX 67,000 Alon Israel Oil Company 

LTD 

7,283.06 12,000 

American Refining Group 

Inc 

Bradford PA 10,000 American Refining 

Group, Inc. 

737.19 323 

Big West Oil Co. North Salt Lake UT 29,400 Flying J Oil & Gas Inc. 1,719.00 15,000 

BP Exploration Alaska Inc Prudhoe Bay AK 12,780 BP PLC 297,107.00 12,633 

BP Products North 

America Inc 

Whiting IN 405,000 BP PLC 297,107.00 12,633 

BP Products North 

America Inc 

Texas City TX 406,570 BP PLC 297,107.00 12,633 

BP West Coast Products 

LLC 

Los Angeles CA 253,000 BP PLC 297,107.00 12,633 

BP West Coast Products 

LLC 

Ferndale WA 225,000 BP PLC 297,107.00 12,633 

BP-Husky Refining LLC Toledo OH 131,400 BP PLC 297,107.00 12,633 

Calcasieu Refining Co. Lake Charles LA 78,000 Calcasieu Refining 

Company 

291.74 92 

Calumet Lubricants Co LP Cotton Valley LA 13,020 Calumet Specialty 

Products Partners, L.P. 

2,190.75 654 

Calumet Lubricants Co LP Princeton LA 8,300 Calumet Specialty 

Products Partners, L.P. 

2,190.75 654 

Calumet Shreveport LLC Shreveport LA 57,000 Calumet Specialty 

Products Partners, L.P. 

2,190.75 654 

Cenex Harvest States Laurel MT 59,600 CHS, Inc. 23.30 287 

Chalmette Refining LLC Chalmette LA 192,500 ExxonMobil Corp. 383,221.00 83,600 

Chevron USA Inc. Perth Amboy NJ 80,000 Chevron Corporation 204,928.00 58,267 

Chevron USA Inc. Salt Lake City UT 45,000 Chevron Corporation 204,928.00 58,267 

Chevron USA Inc. Pascagoula MS 330,000 Chevron Corporation 204,928.00 58,267 

Chevron USA Inc. El Segundo CA 273,000 Chevron Corporation 204,928.00 58,267 

Chevron USA Inc. Richmond CA 245,271 Chevron Corporation 204,928.00 58,267 

Chevron USA Inc. Honolulu HI 54,000 Chevron Corporation 204,928.00 58,267 

Citgo Corpus Christi TX 163,000 CITGO Petroleum 

Corporation 

475.80 3,506 

Citgo Petroleum Corp. Lake Charles LA 427,800 CITGO Petroleum 

Corporation 

475.80 3,506 

Coffeyville Resources Rfg 

& Mktg LLC 

Coffeyville KS 115,700 CVR Energy, Inc. 4,079.77 371 

ConocoPhillips Sweeny TX 247,000 ConocoPhillips 198,655.00 29,700 

ConocoPhillips Linden NJ 238,000 ConocoPhillips 198,655.00 29,700 

ConocoPhillips Wilmington CA 139,000 ConocoPhillips 198,655.00 29,700 

ConocoPhillips SF—Rodeo CA 120,200 ConocoPhillips 198,655.00 29,700 

ConocoPhillips Belle Chasse LA 247,000 ConocoPhillips 198,655.00 29,700 

ConocoPhillips Alaska Inc Prudhoe Bay AK 15,000 ConocoPhillips 198,655.00 29,700 

ConocoPhillips Co Trainer PA 185,000 ConocoPhillips 198,655.00 29,700 

(continued) 
*** Draft – Do Not Cite, Quote, or Release During Review ***

A-3 

Table A-1. Parent Company Information for Petroleum Refineries (continued) 

Facility Name City State 

Capacity 

(bbl/cd) Parent Company Name 

Parent Company 

Sales 

Parent Company 

Employment 

ConocoPhillips Company Westlake LA 239,400 ConocoPhillips 198,655.00 29,700 

ConocoPhillips Company Ponca City OK 198,400 ConocoPhillips 198,655.00 29,700 

ConocoPhillips Company Billings MT 58,000 ConocoPhillips 198,655.00 29,700 

ConocoPhillips Company Ferndale WA 100,000 ConocoPhillips 198,655.00 29,700 

Countrymark Cooperative, 

Inc. 

Mt. Vernon IN 26,500 Countrymark 

Cooperative 

862.97 425 

Deer Park Refining LTD 

Partnership 

Deer Park TX 327,000 Royal Dutch Shell, PLC 378,152.00 93,000 

Delaware City Refining Co 

LLC 

Delaware City DE 182,200 PBF Holdings LLC Not Listed Not Listed 

Delek Refining Ltd Tyler TX 60,000 Delek US Holdings, Inc. 3,755.60 3,296 

Equistar Chemicals LP Channelview TX Lyondell Basell 

Industries N.V. 

27,684.00 14,000 

Ergon Refining Inc. Vicksburg MS 23,000 Ergon, Inc. 3,830.00 1,625 

Ergon West Virginia Inc. Newell WV 20,000 Ergon, Inc. 3,830.00 1,625 

Excel Paralubes Westlake LA Koch Industries Inc 9,182.50 62,544 

ExxonMobil Corp. Beaumont TX 344,500 ExxonMobil Corp. 383,221.00 83,600 

ExxonMobil Corp. Torrance CA 149,500 ExxonMobil Corp. 383,221.00 83,600 

ExxonMobil Oil Corp Baytown TX 560,640 ExxonMobil Corp. 383,221.00 83,600 

ExxonMobil Refining & 

Supply Co 

Baton Rouge LA 502,000 ExxonMobil Corp. 383,221.00 83,600 

ExxonMobil Refining & 

Supply Co 

Billings MT 60,000 ExxonMobil Corp. 383,221.00 83,600 

ExxonMobil Refining & 

Supply Co 

Joliet IL 238,600 ExxonMobil Corp. 383,221.00 83,600 

Flint Hills Resources Corpus Christi TX 290,078 Koch Industries Inc 9,182.50 62,544 

Flint Hills Resources North Pole AK 219,500 Koch Industries Inc 9,182.50 62,544 

Flint Hills Resources Saint Paul MN 262,000 Koch Industries Inc 9,182.50 62,544 

Foreland Refining Co. Ely NV 2,000 Foreland Refining Corp. 12.55 27 

Frontier El Dorado 

Refining Co 

El Dorado KS 138,000 Frontier Oil Corp. 5,884.91 723 

Frontier Refining Inc Cheyenne WY 47,000 Frontier Oil Corp. 5,884.91 723 

Garco Energy LLC Douglas WY 3,600 Garco Energy 11.44 16 

Goodway Refining LLC Atmore AL 4,100 Goodway Refining, LLC 2.00 17 

Greka Energy Santa Maria CA 9,500 Santa Maria Refining 

Company 

2.80 47 

Gulf Atlantic Operations Mobile Bay AL 20,000 Gulf Atlantic Operations 

LLC 

76.99 32 

Hess Corporation Port Reading NJ Hess Corporation 34,613.00 13,800 

Holly Refining & 

Marketing Co 

Woods Cross UT 25,050 Holly Corporation 8,323.00 1,321 

Holly Refining & 

Marketing Co 

Tulsa East OK 70,300 Holly Corporation 8,323.00 1,321 

Holly Refining & 

Marketing Co 

Tulsa West OK 85,000 Holly Corporation 8,323.00 1,321 

Houston Refining LP Houston TX 280,390 Lyondell Basell 

Industries N.V. 

27,684.00 14,000 

Hunt Refining Co. Tuscaloosa AL 36,000 Hunt Refining Co. 4,871.00 346 

Hunt Southland Refining 

Co 

Sandersville MS 11,000 Hunt Refining Co. 4,871.00 1,100 

(continued) 
*** Draft – Do Not Cite, Quote, or Release During Review ***

A-4 

Table A-1. Parent Company Information for Petroleum Refineries (continued) 

Facility Name City State 

Capacity 

(bbl/cd) Parent Company Name 

Parent Company 

Sales 

Parent Company 

Employment 

Kern Oil & Refining Co. Bakersfield CA 26,000 Kern Oil & Refining Co. 282.00 105 

Lima Refining Company Lima OH 155,000 Husky Energy, Inc. 18,174.36 4,491 

Lion Oil Co. El Dorado AR 75,000 Lion Oil Co. 169.60 350 

Little America Refining 

Co. 

Evansville WY 24,500 Sinclair Co.’s 7,753.46 7,000 

Lunday-Thagard Co. South Gate CA 8,500 World Oil Marketing Co. 35.40 65 

Marathon Petroleum Co. 

LLC 

Robinson IL 206,000 Marathon Oil Corp 73,621.00 29,677 

Marathon Petroleum Co. 

LLC 

Catlettsburg KY 212,000 Marathon Oil Corp 73,621.00 29,677 

Marathon Petroleum Co. 

LLC 

Detroit MI 106,000 Marathon Oil Corp 73,621.00 29,677 

Marathon Petroleum Co. 

LLC 

Canton OH 78,000 Marathon Oil Corp 73,621.00 29,677 

Marathon Petroleum Co. 

LLC 

Texas City TX 76,000 Marathon Oil Corp 73,621.00 29,677 

Marathon Petroleum Co. 

LLC 

Garyville LA 464,000 Marathon Oil Corp 73,621.00 29,677 

Martin Midstream Partners 

LP 

Smackover AR 7,500 Cross Oil Refining & 

Marketing, Inc. 

265.00 110 

Montana Refining Co. Great Falls MT 10,000 Connacher Oil and Gas, 

Limited 

574.19 265 

Motiva Enterprises Port Arthur TX 285,000 Motiva Enterprises LLC 26,400.00 2,900 

Motiva Enterprises LLC Norco LA 233,500 Motiva Enterprises LLC 26,400.00 2,900 

Motiva Enterprises LLC Convent LA 235,000 Motiva Enterprises LLC 26,400.00 2,900 

Murphy Oil USA Inc. Superior WI 34,300 Murphy Oil Corp 23,345.07 8,994 

Murphy Oil USA Inc. Meraux LA 125,000 Murphy Oil Corp 23,345.07 8,994 

National Cooperative 

Refinery Association 

McPherson KS 85,500 National Cooperative 

Refinery Association 

2,810.30 612 

Navajo Refining Co. Artesia NM 105,000 Holly Corporation 8,323.00 1,321 

Nustar Asphalt Refining 

LLC 

Paulsboro NJ 70,000 NuStar Energy LP 4,403.06 1,492 

Nustar Asphalt Refining 

LLC 

Savannah GA 28,000 NuStar Energy LP 4,403.06 1,492 

Paramount Petroleum Co Long Beach CA 31,500 Alon Israel Oil Company 

LTD 

7,283.06 12,000 

Paramount Petroleum 

Corp. 

Paramount CA 53,000 Alon Israel Oil Company 

LTD 

7,283.06 12,000 

Pasadena Refining Systems 

Inc. 

Pasadena TX 100,000 Pasadena Refining 31.00 348 

Paulsboro Refining Co 

LLC 

Paulsboro NJ 160,000 PBF Holding Company 

LLC 

Not Listed Not Listed 

PDV Midwest Refining Lemont IL 167,000 Petróleos de Venezuela 

S.A. (PDVSA) 

75.00 102,750 

Pelican Refining Co. LLC Lake Charles LA Pelican Refining Co LLC 4.00 33 

Petro Star Inc. North Pole AK 19,700 Petro Star Inc. 887.00 400 

Petro Star Inc. Valdez AK 55,000 Petro Star Inc. 887.00 400 

Placid Refining Inc. Port Allen LA 57,000 Placid Refining 3,351.84 207 

Premcor Refining Group 

Inc 

Memphis TN 180,000 Valero Energy 82,233.00 20,313 

(continued) 
*** Draft – Do Not Cite, Quote, or Release During Review ***

A-5 

Table A-1. Parent Company Information for Petroleum Refineries (continued) 

Facility Name City State 

Capacity 

(bbl/cd) Parent Company Name 

Parent Company 

Sales 

Parent Company 

Employment 

Premcor Refining Group 

Inc 

Port Arthur TX 292,000 Valero Energy 82,233.00 20,313 

San Joaquin Refining Co., 

Inc. 

Bakersfield CA 15,000 San Joaquin Refining Co. 3.50 108 

Shell Chemical LP St. Rose LA 55,000 Royal Dutch Shell, PLC 378,152.00 93,000 

Shell Chemical LP Saraland AL 80,000 Royal Dutch Shell, PLC 378,152.00 93,000 

Shell Oil Products US Anacortes WA 145,000 Royal Dutch Shell, PLC 378,152.00 93,000 

Shell Oil Products US Martinez CA 156,400 Royal Dutch Shell, PLC 378,152.00 93,000 

Silver Eagle Refining Evanston WY 3,000 Silver Eagle Refining Inc. 225.87 60 

Silver Eagle Refining Woods Cross UT 10,250 Silver Eagle Refining Inc. 225.87 60 

Sinclair Wyoming 

Refining Co 

Sinclair WY 74,000 Sinclair Co.’s 7,753.46 7,000 

Somerset Energy Refinery 

LLC 

Somerset KY 5,500 Somerset Oil Inc. 16.90 11 

South Hampton Resources 

Inc. 

Silsbee TX Arabian American 

Development Co 

139.11 145 

St Paul Park Refining Co. 

LLC 

Saint Paul MN 74,000 Northern Tier Energy 

LLC 

Not listed Not Listed 

Suncor Energy Inc. Commerce City 

West 

CO 67,000 Suncor Energy Inc. 34,398.09 12,978 

Suncor Energy Inc. Commerce City 

East 

CO 36,000 Suncor Energy Inc. 34,398.09 12,978 

Sunoco, Inc. Marcus Hook PA 178,000 Sunoco, Inc. 37,489.00 4,544 

Sunoco, Inc. Toledo OH 160,000 Sunoco, Inc. 37,489.00 4,544 

Sunoco, Inc. (R&M) Philadelphia PA 335,000 Sunoco, Inc. 37,489.00 4,544 

Tenby Inc. Oxnard CA 2,800 Ten By Inc. NotListed NotListed 

Tesoro Alaska Petroleum 

Co 

Kenai AK 68,000 Tesoro Corp 20,583.00 5,261 

Tesoro Hawaii Corp Ewa Beach HI 93,500 Tesoro Corp 20,583.00 5,261 

Tesoro Refining & 

Marketing Corporation 

Martinez CA 166,000 Tesoro Corp 20,583.00 5,261 

Tesoro Refining & 

Marketing Corporation 

Wilmington CA 94,300 Tesoro Corp 20,583.00 5,261 

Tesoro West Coast Mandan ND 58,000 Tesoro Corp 20,583.00 5,261 

Tesoro West Coast Salt Lake City UT 57,500 Tesoro Corp 20,583.00 5,261 

Tesoro West Coast Anacortes WA 120,000 Tesoro Corp 20,583.00 5,261 

Total Petrochemicals Inc Port Arthur TX 232,000 Total SA 186,158.80 92,855 

Trigeant Ltd. Corpus Christi TX BTB Refining 5.00 37 

United Refining Co. Warren PA 65,000 United Refining 

Company 

2,654.40 4,434 

US Oil & Refining Co. Tacoma WA 38,800 US Oil & Refining Co. 26.90 182 

Valero Energy Corporation Three Rivers TX 93,000 Valero Energy 82,233.00 20,313 

Valero Energy Corporation Sunray TX 156,000 Valero Energy 82,233.00 20,313 

Valero Refining Co 

California 

Benicia CA 132,000 Valero Energy 82,233.00 20,313 

Valero Refining Co 

California 

Wilmington 

Asphalt Plant 

CA 6,300 Valero Energy 82,233.00 20,313 

Valero Refining Co 

California 

Wilmington 

Refinery 

CA 78,000 Valero Energy 82,233.00 20,313 

Valero Refining Co 

Oklahoma 

Ardmore OK 85,000 Valero Energy 82,233.00 20,313 

(continued) 
*** Draft – Do Not Cite, Quote, or Release During Review ***

A-6 

Table A-1. Parent Company Information for Petroleum Refineries (continued) 

Facility Name City State 

Capacity 

(bbl/cd) Parent Company Name 

Parent Company 

Sales 

Parent Company 

Employment 

Valero Refining Co Texas 

LP 

Corpus Christi TX 142,000 Valero Energy 82,233.00 20,313 

Valero Refining Co Texas 

LP 

Houston TX 88,000 Valero Energy 82,233.00 20,313 

Valero Refining Co Texas 

LP 

Texas City TX 225,000 Valero Energy 82,233.00 20,313 

Valero Refining New 

Orleans LLC 

Norco LA 205,000 Valero Energy 82,233.00 20,313 

Ventura Refining & 

Transmission LLC 

Thomas OK 12,000 Ventura Refining & 

Transmission, LLC 

3.10 37 

Western Refining 

Company LP 

El Paso TX 122,000 Western Refining, Inc. 7,965.05 636 

Western Refining 

Southwest Inc 

Bloomfield NM 16,800 Western Refining, Inc. 7,965.05 636 

Western Refining 

Southwest Inc 

Gallup NM 21,100 Western Refining, Inc. 7,965.05 636 

Western Refining 

Yorktown Inc 

Yorktown VA 66,300 Western Refining, Inc. 7,965.05 636 

WRB Refining LLC Borger TX 146,000 ConocoPhillips 198,655.00 29,700 

WRB Refining LLC Wood River IL 362,000 ConocoPhillips 198,655.00 29,700 

Wynnewood Refining Co. Wynnewood OK 70,000 Gary-Williams Energy 

Corporation 

49.90 260 

Wyoming Refining Co New Castle WY 14,000 Wyoming Refining Co. 125.00 96 

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Library. Hoovers 2011 Online Data reflects either actual data for 2010/2011 reported by companies, 

estimated data for 2011, or occasionally 2009 values. 

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Business Library. Million Dollar Online Data reflects either actual data for 2011 reported by companies or 

estimated data for 2011. 

 Ward’s Business Directory of Public and Private Companies, 2011, accessed at James Branch Cabell 

Library (Virginia Commonwealth University). Ward’s Business Directory compiles financial data from 

several sources such as annual reports, company websites, and phone interviews. If financial data from 

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 Copyright 2011 Harte-Hanks Market Intelligence, Inc., All Rights Reserved. CI Technology Database, 

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United States 

Environmental Protection 

Agency 

Office of Air and Radiation 

Office of Air Quality Planning and Standards 

Research Triangle Park, NC 

December 2011