Control of Air Pollution from Motor 

Vehicles: Tier 3 Motor Vehicle Emission 

and Fuel Standards Final Rule 

Regulatory Impact Analysis
Assessment and Standards Division 

Office of Transportation and Air Quality 

U.S. Environmental Protection Agency

Control of Air Pollution from Motor 

Vehicles: Tier 3 Motor Vehicle Emission 

and Fuel Standards Final Rule 

Regulatory Impact Analysis

EPA-420-R-14-005 

March 2014
i 

Table of Contents 

EXECUTIVE SUMMARY 

Executive Summary ................................................................................................................ ES-1 

CHAPTER 1 VEHICLE PROGRAM TECHNOLOGICAL FEASIBILITY 

1.1 Introduction ...................................................................................................................... 1-1 

1.2 FTP NMOG+NOX Feasibility ......................................................................................... 1-1 

1.3 SFTP NMOG+NOX Feasibility ..................................................................................... 1-28 

1.4 Technology Description for NMOG+NOX Control ..................................................... 1-30 

1.5 PM Feasibility ................................................................................................................. 1-42 

1.6 Evaporative Emissions Feasibility ................................................................................ 1-52 

1.7 ORVR for Complete HDGVs over 10,000 lbs GVWR ................................................ 1-63 

1.8 Onboard Diagnostics for Vehicles less than 14,000 lbs GVWR ................................. 1-64 

CHAPTER 2 VEHICLE PROGRAM COSTS 

2.1 Changes to Vehicle Costs between Proposed and Final Rules ..................................... 2-1 

2.2 General Methodology ....................................................................................................... 2-2 

2.3 Individual Technology Costs ......................................................................................... 2-11 

2.4 Evaporative Emission, Canister Bleed, and Leak Controls ....................................... 2-20 

2.5 Vehicle Package Costs .................................................................................................... 2-27 

2.6 Operating Costs .............................................................................................................. 2-37 

2.7 Vehicle Program Costs ................................................................................................... 2-41 

CHAPTER 3 ESTABLISHING NEW EMISSION TEST FUEL PARAMETERS 

3.1 Assessment of Current Gasoline Properties .................................................................. 3-1 

3.2 Gasoline Emission Test Fuel Specifications ................................................................. 3-18 

3.3 Changes to ASTM Test Methods .................................................................................. 3-20 

CHAPTER 4 FUEL PROGRAM FEASIBILITY 

4.1 Overview of Refining Operations ................................................................................... 4-1 

4.2 Feasibility of Removing Sulfur from Gasoline .............................................................. 4-4 
ii 

4.3 Sulfur Credits ................................................................................................................. 4-26 

4.4 Sulfur Level Analysis ..................................................................................................... 4-28 

4.5 Lead Time Assessment ................................................................................................... 4-33 

CHAPTER 5 FUEL PROGRAM COSTS 

5.1 Methodology ..................................................................................................................... 5-1 

5.2 Estimated Tier 3 Sulfur Control Costs ......................................................................... 5-60 

5.3 Other Cost Studies ......................................................................................................... 5-73 

5.4 Projected Energy Impacts and Impacts on Permitting .............................................. 5-79 

5.5 Fuel Quality Requirements for Denatured Fuel Ethanol ........................................... 5-90 

5.6 Gasoline Additives .......................................................................................................... 5-90 

5.7 Downstream Pentane Blending ..................................................................................... 5-91 

CHAPTER 6 HEALTH AND ENVIRONMENTAL EFFECTS ASSOCIATED WITH 

EXPOSURE TO CRITERIA AND TOXIC POLLUTANTS 

6.1 Health Effects of Criteria and Toxic Pollutants ............................................................ 6-1 

6.2 Environmental Effects of Criteria and Toxic Pollutants ............................................ 6-19 

CHAPTER 7 IMPACTS OF THE RULE ON EMISSIONS AND AIR QUALITY 

7.1 Criteria and Toxic Pollutant Emission Impacts ............................................................ 7-1 

7.2 Criteria and Toxic Pollutant Air Quality Impacts ...................................................... 7-52 

7.3 Greenhouse Gas Emission Impacts ............................................................................ 7-128 

CHAPTER 7 APPENDIX: ADDITIONAL AIR TOXICS EMISSIONS AND AIR 

QUALITY MODELING RESULTS 

7A.1 Air Toxics Emissions ..................................................................................................... 7A-1 

7A.2 Seasonal Air Toxics Air Quality Modeling Results for 2018 ..................................... 7A-3 

7A.3 Seasonal Air Toxics Air Quality Modeling Results for 2030 ................................... 7A-10 

CHAPTER 8 COMPARISON OF PROGRAM COSTS TO PROGRAM EMISSION 

REDUCTIONS AND AIR QUALITY BENEFITS 

8.1 Cost-Benefit Analysis ....................................................................................................... 8-1 
iii 

CHAPTER 9 ECONOMIC IMPACT ANALYSIS 

9.1 Introduction ...................................................................................................................... 9-1 

9.2 Impacts on Vehicle Manufacturing Sector .................................................................... 9-2 

9.3 Impacts on Petroleum Refinery Sector .......................................................................... 9-8 

CHAPTER 10 FINAL REGULATORY FLEXIBILITY ANALYSIS 

10.1 Introduction .................................................................................................................... 10-1 

10.2 Overview of the Regulatory Flexibility Act ................................................................. 10-1 

10.3 Need for the Rulemaking and Rulemaking Objectives ............................................... 10-2 

10.4 Definition and Description of Small Entities ............................................................... 10-3 

10.5 Summary of Small Entities to Which the Rulemaking Will Apply ........................... 10-4 

10.6 Related Federal Rules .................................................................................................... 10-5 

10.7 Reporting, Recordkeeping, and Other Compliance Requirements ........................... 10-5 

10.8 Regulatory Alternatives ................................................................................................. 10-6 

10.9 Economic Effects .......................................................................................................... 10-20
iv 

List of Acronyms 

A/F air/fuel ratio 

AAM Alliance of Automobile Manufacturers 

ABT averaging, banking, and trading 

ACS American Cancer Society 

AGO atmospheric gasoil 

AHS U.S. Census Bureau’s American Housing Survey 

AIRS Aerometric Information Retrieval System 

AML acute myeloid leukemia 

ANPRM Advanced Notice of Proposed Rulemaking 

API American Petroleum Institute 

ASTM American Society for Testing and Materials 

bbl barrel 

BCA benefit-cost analysis 

BenMAP Environmental Benefits Mapping and Analysis Program 

BTU British Thermal Unit 

C-R concentration response 

CAA Clean Air Act 

CAP Compliance Assurance Program (2000) 

CARB California Air Resources Board 

CASAC Clean Air Science Advisory Committee 

CBI confidential business information 

DF Deterioration Factor 

CG conventional gasoline 

CMAQ Community Multiscale Air Quality model 

CML chronic myeloid leukemia 

CO carbon monoxide 

CO2 carbon dioxide 

COI cost of illness 

COPD chronic obstructive pulmonary disease 

cpsi cells per square inch 

CR concentration-response 

CRC Coordinating Research Council 

CRDM Climatological Regional Dispersion Model 

DMC direct manufacturing costs 

DOE U.S. Department of Energy 

E0 ethanol-free gasoline 

E10 gasoline containing 10 percent ethanol by volume 

E15 gasoline containing 15 percent ethanol by volume 

ECA Emission Control Area 

EGR exhaust gas recirculation 

EHC electrically heated catalyst 

EIA Energy Information Administration 

EISA Energy Independence and Security Act of 2007 

EPA or Agency U.S. Environmental Protection Agency 
v 

EPAct Energy Policy Act of 2005 

ERIC Emissions Reduction and Intercept Control (system) 

ESPN EPA speciation network 

EvOH ethyl vinyl alcohol 

FBP final boiling point 

FCC fluidized catalytic cracker 

FTP Federal Test Procedure 

GC/MS gas chromatography/mass spectrometry 

GDI gasoline direct injection 

GDP gross domestic product 

GPA Geographic Phase-in Area 

GVWR gross vehicle weight rating 

HAP Hazardous Air Pollutant 

HAPEM Hazardous Air Pollutant Exposure Model 

HC hydrocarbon 

HCUP Healthcare Cost and Utilization Program 

HDGV heavy-duty gasoline vehicle 

HDV heavy-duty vehicle 

HEGO heated exhaust gas oxygen (sensor) 

HEI Health Effects Institute 

I/M inspection/maintenance 

IBP initial boiling point 

ICI independent commercial importer 

ICM indirect cost multiplier 

IRFA Initial Regulatory Flexibility Analysis 

IRIS Integrated Risk Information System 

LCO light cycle oil 

LDT light-duty truck 

LDV light-duty vehicle 

LEV low emission vehicle 

LM locomotive and marine diesel fuel 

LML lowest measured level 

LPG liquid petroleum gas 

MDPV medium-duty passenger vehicle 

MECA Manufacturers of Emission Controls Association 

MLE maximum likelihood estimate 

MRAD minor restricted activity days 

MSAT mobile source air toxic 

MSAT2 Regulations for Control of Hazardous Air Pollutants from Mobile Sources, 

72 FR 8428, 2/26/07

MSCF thousand standard cubic feet 

MTBE methyl tertiary-butyl ether 

MY model year 

NAAQS National Ambient Air Quality Standards 

NAC NOX adsorption catalyst 

NAICS North American Industrial Classification System 

NAPAP National Acid Precipitation Assessment Program 
vi 

NATA National-Scale Air Toxics Assessment 

NEMA Northeast Mid-Atlantic 

NESHAP National Emissions Standards for Hazardous Air Pollutants 

NFRAQS Northern Front Range Air Quality Study 

NGL natural gas liquids 

NLEV national low emission vehicle 

NMHC non-methane hydrocarbons 

NMMAPS National Morbidity, Mortality, and Air Pollution Study 

NMOG non-methane organic gases 

NO2 nitrogen dioxide 

NOX oxides of nitrogen 

NPC National Petroleum Council 

NPRA National Petrochemical & Refiners Association 

NPRM Notice of Proposed Rulemaking 

NRC National Research Council 

NSR New Source Review 

OAQPS Office of Air Quality Planning and Standards 

OAR EPA’s Office of Air and Radiation 

OBD on-board diagnostics 

OC/EC organic carbon/elemental carbon 

OMB Office of Management and Budget 

OMS Office of Mobile Sources 

ORNL Oak Ridge National Laboratory 

OSC oxygen storage components 

OSTP (White House) Office of Science and Technology Policy 

OTAG Ozone Transport Assessment Group 

PADD Petroleum Administrative Districts for Defense 

PAN peroxy acetyl nitrate 

PCM powertrain control module 

Pd palladium 

PFI port fuel injection 

PGM platinum group metals 

PM particulate matter 

PNGV Partnership for a New Generation of Vehicles 

POM polycyclic organic matter 

ppm part per million 

PSD Prevention of Significant Deterioration 

Pt platinum 

R+M/2 average octane, or antiknock index 

R&D research and development 

REL reference exposure level 

RFA Regulatory Flexibility Act 

RfC reference concentration 

RfD reference dose 

RFG reformulated gasoline 

RFS2 Renewable Fuel Standard Program, 75 FR 14670, 3/26/2010 
vii 

Rh rhodium 

ROI return on investment 

ROTR Regional Ozone Transport Rule 

RPE retail price equivalent 

RRF relative reduction factor 

RVP Reid vapor pressure 

S-R Source-Receptor Matrix 

S&P DRI Standard & Poor’s Data Research International 

SAB Science Advisory Board 

SBA U.S. Small Business Administration 

SBAR or the Panel Small Business Advocacy Review Panel 

SBREFA Small Business Regulatory Enforcement Fairness Act 

SCR selective catalytic reduction 

SER Small Entity Representative 

SFTP Supplemental Federal Test Procedure 

SIC Standard Industrial Classification 

SIGMA Society of Independent Gasoline Marketers of America 

SIP State Implementation Plan 

SMAT Speciated Modeled Attainment Test 

SO2 sulfur dioxide 

SOX oxides of sulfur 

SRU sulfur recovery unit 

SULEV super ultra low emission vehicle 

SVM small volume manufacturer (of vehicles) 

SVOC semivolatile organic compound 

SwRI Southwest Research Institute 

T10 average temperature at which 10 percent of gasoline is distilled 

T50 average temperature at which 50 percent of gasoline is distilled 

T90 average temperature at which 90 percent of gasoline is distilled 

TC total technology costs 

TGDI turbocharged gasoline direct injection 

THC total hydrocarbons 

TOG total organic gases 

TW test weight 

UAM Urban Airshed Model 

UCL upper confidence limit 

UEGO universal exhaust gas oxygen (sensor) 

ULEV ultra low emission vehicle 

UMRA Unfunded Mandates Reform Act 

UV ultra violet 

VGO vacuum gasoil 

VTB vacuum tower bottoms 

VMT vehicle miles traveled 

VNA Voronoi Neighbor Averaging 

VOC volatile organic compound 

VSL value of a statistical life 
viii 

WLD work loss days 

WTP willingness to pay 
ix 

This Page Intentionally Left Blank 
ES-1

Executive Summary 

EPA is adopting a comprehensive program to address air pollution from passenger cars 

and trucks. The final program, known as “Tier 3,” will establish more stringent vehicle emissions 

standards and reduce the sulfur content of gasoline, considering the vehicle and its fuel as an 

integrated system The final Tier 3 standards will reduce concentrations of multiple air pollutants 

(ambient concentrations of ozone, particulate matter (PM), nitrogen dioxide (NO2), and mobile 

source air toxics (MSATs)) across the country and help state and local agencies in their efforts to 

attain and maintain health-based National Ambient Air Quality Standards (NAAQS). 

This Regulatory Impact Analysis provides technical, economic, and environmental 

analyses of the new standards. Chapter 1 contains our technical feasibility justification for the 

final vehicle emission standards, and Chapter 2 contains the estimated costs of the final vehicle 

standards. In addition to the vehicle emission and gasoline standards, we are adopting an update 

to the specifications of the emission test fuel with which vehicles demonstrate compliance with 

emissions standards; our analysis of the emission test fuel parameter changes is found in Chapter 

3. Chapters 4 and 5 contain our technical feasibility and cost analyses for the final gasoline 

sulfur standards, respectively. Chapter 6 describes the health and welfare effects associated with 

the air pollutants that will be impacted by the rule. Chapter 7 describes our analysis of the 

emission and air quality impacts of the Tier 3 rule. Our estimates of the program-wide costs, the 

societal benefits, and the cost per ton of emissions reduced due to the final Tier 3 program are 

presented in Chapter 8. Chapter 9 contains our analysis of the final rule’s economic impacts, and 

Chapter 10 provides the results of our small business final regulatory flexibility analysis. 

Tier 3 Standards 

Vehicle Emission Standards 

The Tier 3 standards include light- and heavy-duty vehicle tailpipe emission standards 

and evaporative emission standards. 

Light-Duty Vehicle, Light-Duty Truck, and Medium-Duty Passenger Vehicle Tailpipe 

Emission Standards

The standards in this category apply to all light-duty vehicles (LDVs, or passenger cars),

light-duty trucks (LDT1s, LDT2s, LDT3s, and LDT4s) and Medium-Duty Passenger Vehicles, 

or MDPVs. The new standards are for the sum of NMOG and NOX emissions, presented as 

NMOG+NOX, and for PM. For these pollutants, the standards are measured on test procedures 

that represent a range of vehicle operation, including the Federal Test Procedure (or FTP, 

simulating typical driving) and the Supplemental Federal Test Procedure (or SFTP, a composite 

test simulating higher temperatures, higher speeds, and quicker accelerations). 

The FTP and SFTP NMOG+NOX standards are fleet-average standards, meaning that a 

manufacturer will calculate the weighted average emissions of the vehicles it sells in each model 

year and compare that average to the applicable standard for that model year. The fleet average 
ES-2

standards for NMOG+NOX evaluated over the FTP will begin in MY 2017 and then decline 

through MY 2025, as summarized in Table ES-1. Similarly, the NMOG+NOX standards 

measured over the SFTP will also be fleet-average standards, declining from MY 2017 until MY 

2025, as shown in Table ES-2. 

Table ES-1 LDV, LDT, and MDPV Fleet Average NMOG+NOX FTP Standards (mg/mi) 

Model Year

2017a2018 2019 2020 2021 2022 2023 2024 2025

and later

LDV/LDT1b86 79 72 65 58 51 44 37 30

LDT2,3,4 and 

MDPV 101 92 83 74 65 56 47 38 30

a

For vehicles above 6000 lbs GVWR, the fleet average standards will apply beginning in MY 2018. 

b These standards will apply for a 150,000 mile useful life. Manufacturers can choose to certify their LDVs and 

LDV1s to a useful life of 120,000 miles. If any of these families are certified to the shorter useful life, a 

proportionally lower numerical fleet-average standard will apply, calculated by multiplying the respective 

150,000 mile standard by 0.85 and rounding to the nearest mg. 

Table ES-2 LDV, LDT, and MDPV Fleet-Average NMOG+NOX SFTP Fleet Average 

Standards (mg/mi) 

Model Year

2017a2018 2019 2020 2021 2022 2023 2024 2025

and later

NMOG + NOX 103 97 90 83 77 70 63 57 50

a

 For vehicles above 6000 lbs GVWR, the fleet average standards will apply beginning in MY 2018. 

The PM standard on the FTP for certification testing is 3 mg/mi for all vehicles and for 

all model years. Manufacturers can phase in their vehicle models as a percent of sales through 

MY 2022. The FTP PM standards will apply to each vehicle separately (i.e., not as a fleet 

average). The program also includes a separate FTP PM requirement of 6 mg/mi for the testing 

of in-use vehicles that will apply during the percent phase-in period only. Table ES-3 presents 

the FTP certification and in-use PM standards and the phase-in percentages. 
ES-3

Table ES-3 Phase-In for FTP PM Standards 

2017a2018 2019 2020 2021 2022 and 

later

Phase-In

(percent of U.S. sales) 20 20 40 70 100 100

Certification Standard 

(mg/mi) 3 3 3 3 3 3

In-Use Standard 

(mg/mi) 6 6 6 6 6 3

a

 For vehicles above 6000 lbs GVWR, the FTP PM standards will apply beginning in MY 2018. 

The Tier 3 program also includes certification PM standards evaluated over the SFTP 

(specifically the US06 component of the SFTP procedure) of 10 mg/mi for MYs 2017 and MY 

2018, and a single final standard of 6 mg/mi for MY 2019 and later. For MYs 2019 through 

2023, an in-use standard of 10 mg/mi will also apply. 

Heavy-Duty Tailpipe Emission Standards

There are new Tier 3 exhaust emissions standards for complete heavy-duty vehicles 

(HDVs) between 8,501 and 14,000 lb GVWR. Vehicles in this GVWR range are often referred 

to as Class 2b (8,501-10,000 lb) and Class 3 (10,001-14,000 lb) vehicles, and are typically fullsize pickup trucks and work vans. The key elements of these standards include a combined 

NMOG+NOX declining fleet average standard, new stringent PM standards phasing in on a 

separate schedule, extension of the regulatory useful life to 150,000 miles, and a new 

requirement to meet standards over the SFTP that will address real-world driving modes not 

well-represented by the FTP cycle alone. Table ES-4 presents the HDV fleet average 

NMOG+NOX standard, which becomes more stringent in successive model years from 2018 to 

2022, with voluntary standards available in 2016 and 2017. 

The PM standards are 8 mg/mi for Class 2b vehicles and 10 mg/mi for Class 3 vehicles, 

to be phased in on a percent-of-sales basis at 20-40-70-100 percent in 2018-2019-2020-2021, 

respectively. 

Table ES-4 HDV Fleet Average NMOG+NOX Standards (mg/mi) 

Voluntary Required Program

Model Year 2016 2017 2018 2019 2020 2021 2022 and later

Class 2b 333 310 278 253 228 203 178

Class 3 548 508 451 400 349 298 247

The new SFTP requirements for HDVs include NMOG+NOX, carbon monoxide (CO) 

and PM standards. Compliance will be evaluated from a weighted composite of measured 

emissions from testing over the FTP cycle, the SC03 cycle, and an aggressive driving cycle, with 

the latter tailored to various HDV sub-categories: the US06 cycle for most HDVs, the highway 
ES-4

portion of the US06 cycle for low power-to-weight Class 2b HDVs, and the LA-92 cycle for 

Class 3 HDVs. 

Evaporative Emission Standards

To control evaporative emissions, more stringent standards will require covered vehicles 

to have essentially zero fuel vapor emissions in use, including more stringent evaporative 

emissions standards, new test procedures, and a new fuel/evaporative system leak standard. Tier 

3 also includes refueling emission standards for complete heavy-duty gasoline vehicles 

(HDGVs) over 10,000 lbs GVWR. There are phase-in flexibilities as well as credit and 

allowance programs. The standards, harmonized with California’s zero evaporative emissions 

standards, are designed to essentially eliminate fuel vapor-related evaporative emissions. The 

Tier 3 evaporative emission standards will be phased in over a period of six MYs 2017-2022 as 

shown in Table ES-5. 

Table ES-5 Default Phase-in Schedule for Tier 3 

Evaporative Emission Standards 

Model year Minimum 

percentage of 

vehicles subject to 

the Tier 3 standards

2017 40%1,2,3

2018 60%

2019 60%

2020 80%

2021 80%

2022 100%

1

 The phase-in percentage for model year 2017 applies 

only for vehicles at or below 6,000 pounds GVWR. 

2

 The leak standard does not apply for model year 2017. 

3

 There are three options for the 2017 MY, only one is shown here. 

Table ES-6 presents the evaporative hot soak plus diurnal emission standards by vehicle 

class. Manufacturers may comply on average within each of the four vehicle categories but not 

across these categories. Tier 3 also includes separate high altitude emission standards for these 

vehicle categories. 

Table ES-6 Evaporative Emission Standards (g/test) 

Vehicle Category Highest Diurnal + Hot Soak Level

(over both 2-day and 3-day diurnal tests)

LDV, LDT1 0.300

LDT2 0.400

LDT3, LDT4, MDPV 0.500

HDGVs 0.600
ES-5

There is a new testing requirement referred to as the bleed emission test procedure. 

Manufacturers will be required to measure diurnal emissions over the 2-day diurnal test 

procedure from just the fuel tank and the evaporative emission canister and comply with a 0.020 

g/test standard for all LDVs, LDTs, and MDPVs without averaging. The canister bleed emission 

standard test will apply only for low altitude testing conditions, but there is proportional control 

at higher altitudes. 

EPA is including these Tier 3 evaporative emission controls for HDGVs as part of the 

overall scheme for LDVs and LDTs. The individual vehicle emission standard will be 0.600 

g/test for both the 2-day and 3-day evaporative emission tests, the high altitude standard will be 

1.75 g/test and the canister bleed test standard will be 0.030 g/test. 

We are adding a new standard and test procedure related to controlling vapor leaks from 

vehicle fuel and vapor control systems. The standard, which will apply to all LDVs, LDTs, 

MDPVs, and Class 2b/3 HDGVs, will prohibit leaks larger than 0.02 inches of cumulative 

equivalent diameter in the fuel/evaporative system. The Tier 3 evaporative emission standards 

program requirements will be phased in over a period of six model years between MYs 2017 and 

2022, with the leak test phasing in beginning in 2018 MY as a vehicle is certified to meet Tier 3 

evaporative emission requirements. 

There are new refueling emission control requirements for complete HDGVs equal to or 

less than 14,000 lbs GVWR (i.e., Class 2b/3 HDGVs), that start in the 2018 model year. For 

complete HDGVs > 14,000 lbs GVWR the refueling emission control requirement start in the 

2022 model year. 

We are adopting and incorporating by reference the current CARB onboard diagnostic 

system (OBD) regulations effective for the 2017 MY plus two minor provisions to enable OBDbased leak detection to be used in IUVP testing. EPA will retain the provision that certifying 

with CARB’s program will permit manufacturers to seek a separate EPA certificate on that basis. 

Emissions Test Fuel Requirements 

There are several changes to our federal gasoline emissions test fuel. Key changes 

include: 

Moving away from “indolene” (E0) to a test fuel containing 10 percent ethanol by 

volume (E10); 

Lowering octane to match regular-grade gasoline (except for premium-required 

vehicles); 

Adjusting distillation temperatures, aromatics and olefins to better match today’s inuse fuel and to be consistent with anticipated E10 composition; and 

Lowering the existing sulfur specification and setting a benzene specification to be 

consistent with proposed Tier 3 gasoline sulfur requirements and recent MSAT2 

gasoline benzene requirements. 
ES-6

E85 and premium test fuel specifications. 

Gasoline Sulfur Standards 

Under the Tier 3 fuel program, federal gasoline will contain no more than 10 parts per 

million (ppm) sulfur on an annual average basis beginning January 1, 2017. There will be an 

averaging, banking, and trading (ABT) program that would allow refiners and importers to 

spread out their investments through an early credit program and rely on ongoing nationwide 

averaging to meet the 10 ppm sulfur standard. There will be a three-year delay for small refiners 

and “small volume refineries” (refiners processing less than or equal to 75,000 barrels per 

calendar day). In addition, we are maintaining the current refinery gate and downstream sulfur 

caps of 80 ppm and 95 ppm, respectively.

Projected Impacts 

Changes to Analyses Since Proposal 

Since the proposal, we have made several updates to the analyses that estimate the 

projected impacts of the Tier 3 standards. We made several changes to our baseline (also 

referred to as the “reference case”), which is our projection of future conditions if the Tier 3 

standards were not finalized. Specifically, our baseline now accounts for the fact that California 

and twelve additional states have adopted California’s Low Emission Vehicle III (LEV III) 

program. This change reduces the emissions and air quality impacts of the Tier 3 standards (and 

thus the monetized benefits), and it also reduces the cost of the Tier 3 vehicle standards. In 

addition, the baseline now accounts for the light-duty greenhouse gas emissions standards for 

2017 and later model years, and the greenhouse gas emissions standards for medium- and heavyduty engines and vehicles. This update affects the per-vehicle technology costs but has little 

impact on the emissions and air quality benefits of the Tier 3 program, because it is included in 

both the baseline and control cases. Finally, the baseline now uses the U.S. Energy Information 

Administration’s Annual Energy Outlook 2013 (AEO2013) as the source for future renewable 

fuel volumes and blends and future gasoline consumption. AEO2013 projects significantly lower 

gasoline consumption than AEO2011 (which was used in the proposal’s analysis), and this 

reduces the total cost of the Tier 3 fuel program. There are a number of other updates to our 

cost, emissions, air quality, and benefits analyses, as detailed in the RIA. Among the most 

significant are the changes to the vehicle and fuel cost estimates, which have resulted in costs 

that are lower than projected in the proposal. The updates with the most significant impacts on 

the per-vehicle costs include a more robust estimate of catalyst loading costs and the new 

baseline fleet that reflects implementation of the most recent greenhouse gas emissions 

standards. Both of these updates reduced per-vehicle costs. Total vehicle program costs were 

also significantly reduced because costs are no longer incurred for vehicles sold in states that 

have adopted the California LEV III program. With respect to fuel costs, the change with the 

most significant impact on per-gallon costs is the inclusion of nationwide credit trading (i.e., 

between companies). The proposal’s primary cost analysis was based only on trading within 

companies (although we also presented in the proposal the cost if trading between firms 

occurred). The reduction in per-gallon costs, when combined with significantly lower 
ES-7

projections of gasoline consumption from AEO2013, resulted in lower fuel program costs than 

the proposal had estimated. 

Emission and Air Quality Impacts 

The Tier 3 vehicle and fuel-related standards together will reduce emissions of NOX, 

VOC, PM2.5, and air toxics. The gasoline sulfur standards, which will take effect in 2017, will 

provide large immediate reductions in emissions from existing gasoline vehicles and engines. 

The emission reductions will increase over time as newer vehicles become a larger percentage of 

the fleet (e.g., in 2030, 70 percent of the miles travelled are from vehicles that meet the fully 

phased-in Tier 3 standards). Projected emission reductions from the Tier 3 standards for 2018 

and 2030 are shown in Table ES-7. We expect these reductions to continue beyond 2030 as more 

of the fleet continues to turn over to Tier 3 vehicles. 

Table ES-7 Estimated Emission Reductions from the Final Tier 3 Standards 

(Annual U.S. short tons) 

2018 2030

Tons Percent of Onroad 

Inventory

Tons Percent of Onroad 

Inventory

NOX 264,369 10% 328,509 25%

VOC 47,504 3% 167,591 16%

CO 278,879 2% 3,458,041 24%

Direct PM2.5 130 0.1% 7,892 10%

Benzene 1,916 6% 4,762 26%

SO2 14,813 56% 12,399 56%

1,3-Butadiene 257 5% 677 29%

Formaldehyde 513 2% 1,277 10%

Acetaldehyde 600 3% 2,067 21%

Acrolein 40 3% 127 15%

Ethanol 2,704 2% 19,950 16%

We project that the Tier 3 vehicle and fuel standards will reduce nitrous oxide (N2O) and 

methane (CH4) emissions from vehicles. The reductions in these potent greenhouse gases will be 

partially offset by the increase in CO2 emissions from refineries. The combined impact is a net 

decrease on a CO2-equivalent basis (2.5 to 2.7 million metric tons of CO2-equivalent reduced in 

2030). 

Reductions in emissions of NOX, VOC, PM2.5 and air toxics are projected to lead to 

nationwide decreases in ambient concentrations of ozone, PM2.5, NO2, CO, and air toxics. 

Specifically, the Tier 3 standards will significantly decrease ozone concentrations across the 

country, with an estimated population-weighted average decrease of 0.49 ppb in 2018 and 0.98

ppb in 2030. Few other strategies exist that would deliver the reductions needed for states to 

meet the current ozone standards. The Tier 3 standards will decrease ambient annual PM2.5 

concentrations across the county as well, with an estimated population-weighted average 

decrease of 0.04 μg/m3by 2030. Decreases in ambient concentrations of air toxics are also 
ES-8

projected with the Tier 3 standards, including notable nationwide reductions in benzene 

concentrations. 

Costs and Benefits 

The costs that will be incurred from our final program fall into two categories – costs 

from the Tier 3 vehicle exhaust and evaporative standards and from reductions in sulfur content 

of gasoline. All costs represent the fleet-weighted average of light-duty vehicles and trucks. All 

costs are represented in 2011 dollars. 

Vehicle Costs

The vehicle costs include the technology costs projected to meet the exhaust and 

evaporative standards, as show in Table ES-8. The fleet mix of light-duty vehicles, light duty 

trucks, and medium-duty trucks reflects the MY 2017-2025 light-duty and MY2014-2018 heavyduty GHG final rulemakings. 

Table ES-8 Annual Vehicle Technology Costs, 2011$

Year Vehicle Exhaust 

Emission Control 

Costs

($Million)

Vehicle Evaporative 

Emission Control 

Costs

($Million)

Operating Costs

($Million)

Facility Costs 

($Million)

Total Vehicle 

Costs

($Million)a

2017 $268 $26 $0 $4 $297

2030 $664 $113 -$19 $4 $761

a

These estimates include costs associated with the Tier 3 vehicle standards in all states except California and 

states that have adopted the LEV III program. 

Fuel Costs

The fuel costs consist of the additional operating costs and capital costs to the refiners to 

meet the sulfur average of 10 ppm. The sulfur control costs assume a cost of 0.65 cents per 

gallon which includes the refinery operating and capital costs. The annual fuel costs of the 

program are listed in Table ES-9. 

Table ES-9 Annual Fuel Costs, 2011$

Year Fuel Sulfur Control Costs ($Million)a

2017 $804

2030 $696

a

These estimates include costs associated with the Tier 3 fuel 

standards in all states except California. 

Total Costs

The sum of the vehicle technology costs to control exhaust and evaporative emissions, in 

addition to the costs to control the sulfur level in the fuel, represent the total costs of the 
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program, as shown in Table ES-10. The final fuel standards are projected to lead to an average 

cost of 0.65 cents per gallon of gasoline, and the vehicle standards would have an average 

technology cost of $72 per vehicle 

Table ES-10: Total Annual Vehicle and Fuel Control Costs, 2011$

Year Total Vehicle and Fuel Control Costs

($Million)a

2017 $1,101

2030 $1,457

a

These estimates include costs associated with both the Tier 3 vehicle 

standards in all states except California and states that have adopted the 

LEV III program, and the Tier 3 fuel standards in all states except 

California. 

Benefits

Exposure to ambient concentrations of ozone, PM2.5, and air toxics is linked to adverse 

human health impacts such as premature deaths as well as other important public health and 

environmental effects. The final Tier 3 standards are expected to reduce these adverse impacts 

and yield significant benefits, including those we can monetize and those we are unable to 

quantify. 

The range of quantified and monetized benefits associated with this program are 

estimated based on the risk of several sources of PM- and ozone-related mortality effect 

estimates, along with other PM and ozone non-mortality related benefits information. Overall, 

we estimate that the final rule will lead to a net decrease in PM2.5- and ozone-related health and 

environmental impacts. The estimated range of total monetized ozone- and PM-related health 

impacts is presented in Table ES-11. 

Table ES-11: Estimated 2030 Monetized PM-and Ozone-Related Health Benefits 

(Billions, 2011$)a

Description 2030

Total Estimated Health Benefitsb,c,d,e

 3 percent discount rate

 7 percent discount rate

$7.4 - $19

$6.7 - $18

Notes: 

a

 Totals are rounded to two significant digits and may not sum due to rounding. 

b

 Total includes ozone and PM2.5 estimated benefits. Range was developed by adding the estimate from the 

Bell et al., 2004 ozone premature mortality function to PM2.5-related premature mortality derived from the 

American Cancer Society cohort study (Krewski et al., 2009) for the low estimate and ozone premature 

mortality derived from the Levy et al., 2005 study to PM2.5-related premature mortality derived from the 

Six-Cities (Lepeule et al., 2012) study for the high estimate.

c Annual benefits analysis results reflect the use of a 3 percent and 7 percent discount rate in the valuation 

of premature mortality and nonfatal myocardial infarctions, consistent with EPA and OMB guidelines for 

preparing economic analyses. 
ES-10

d Valuation of premature mortality based on long-term PM exposure assumes discounting over the SAB 

recommended 20-year segmented lag structure described in the Regulatory Impact Analysis for the 2006 

PM National Ambient Air Quality Standards (September, 2006). 

e Not all possible benefits are quantified and monetized in this analysis; the total monetized benefits 

presented here may therefore be underestimated. 

We estimate that by 2030, the annual emission reductions of the Tier 3 standards will

annually prevent between 660 and 1,500 PM-related premature deaths, between 110 and 500 

ozone-related premature deaths, 81,000 work days lost, and approximately 1.1 million minor 

restricted-activity days. The estimated annual monetized health benefits of the proposed Tier 3 

standards in 2030 (2011$) will be between $7.4 and $19 billion, assuming a 3-percent discount 

rate (or between $6.7 billion and $18 billion assuming a 7-percent discount rate). 

Comparison of Costs and Benefits

Using a conservative benefits estimate, the 2030 benefits outweigh the costs by a factor 

of 4.5. Using the upper end of the benefits range, the benefits could outweigh the costs by a 

factor of 13. Thus, even taking the most conservative benefits assumptions, benefits of the final 

standards are projected to outweigh the costs. The results are shown in Table ES-12.

Table ES-12 Summary of Annual Benefits and Cost Associated with the Final Tier 3 

Program (Billions, 2011$)a

Description 2030

Vehicle Program Costs

Fuels Program Costs

Total Estimated Costsb

$0.76

$0.70

$1.5

Total Estimated Health Benefitsc,d,e,f

 3 percent discount rate

 7 percent discount rate

$7.4 - $19

$6.7 - $18

Annual Net Benefits (Total Benefits – Total Costs)

 3 percent discount rate

 7 percent discount rate

$5.9 - $18

$5.2 - $17

Notes: 

a

 All estimates represent annual benefits and costs anticipated for the year 2030. Totals are rounded to two 

significant digits and may not sum due to rounding. 

b

 The calculation of annual costs does not require amortization of costs over time. Therefore, the estimates of annual 

cost do not include a discount rate or rate of return assumption (see Chapter 2 of the RIA for more information on 

vehicle costs, Chapter 5 for fuel costs, and Section 8.1.1 for a summary of total program costs). 

c

 Total includes ozone and PM2.5 estimated benefits. Range was developed by adding the estimate from the Bell et 

al., 2004 ozone premature mortality function to PM2.5-related premature mortality derived from the American 

Cancer Society cohort study (Krewski et al., 2009) for the low estimate and ozone premature mortality derived from 

the Levy et al., 2005 study to PM2.5-related premature mortality derived from the Six-Cities (Lepeule et al., 2012) 

study for the high estimate. 

d Annual benefits analysis results reflect the use of a 3 percent and 7 percent discount rate in the valuation of 

premature mortality and nonfatal myocardial infarctions, consistent with EPA and OMB guidelines for preparing 

economic analyses. 
ES-11

e Valuation of premature mortality based on long-term PM exposure assumes discounting over the SAB 

recommended 20-year segmented lag structure described in the Regulatory Impact Analysis for the 2012 PM 

National Ambient Air Quality Standards (December, 2012).

f Not all possible benefits or disbenefits are quantified and monetized in this analysis. Potential benefit categories 

that have not been quantified and monetized are listed in Table 8-5.

Economic Impact Analysis 

The rule will affect two sectors directly: vehicle manufacturing and petroleum refining. 

The estimated increase in vehicle production cost because of the rule is expected to be small 

relative to the costs of the vehicle. Some or all of this production cost increase will be expected 

to be passed through to consumers. This increase in price is expected to lower the quantity of 

vehicles sold, though because the expected cost increase is small, we expect the decrease in sales 

to be negligible. This decrease in vehicle sales is expected to decrease employment in the 

vehicle manufacturing sector. However, costs related to compliance with the rule should also 

increase employment in this sector. While it is unclear which of these effects will be larger, 

because the increase in vehicle production costs and the decrease in vehicle sales are minor, the 

impact of the rule on employment in the vehicle manufacturing sector is expected to be small as 

well. The key change for refiners from the proposed standards will be more stringent sulfur 

requirements. Analogous to vehicle sales, this change to fuels is expected to increase 

manufacturers’ costs of fuel production. Some or all of this increase in production costs is 

expected to be passed through to consumers which should lead to a decrease in fuel sales. As 

with the vehicle manufacturing sector, we expect the decrease in fuel sales to negatively affect 

employment in this sector, while the costs of compliance with the rule will be expected to 

increase employment. It is not evident whether the rule will increase or decrease employment in 

the refining sector as a whole. However, given the small anticipated increase in production costs 

of less than one cent per gallon and the small likely decrease in fuel sales, we expect that the rule 

will not have major employment consequences for this sector. 
1-1 

Chapter 1 Vehicle Program Technological Feasibility 

1.1 Introduction 

For the vehicles and emissions addressed in this final rule, EPA has comprehensively 

assessed the technological phenomena related to the generation of emissions of interest, the 

nature of the technological challenges facing manufacturers to produce emission reductions of 

the scale described in the Preamble, and the technologies that we expect to be available to 

manufacturers to meet those challenges during the rule implementation time frame. Our 

feasibility assessment recognizes that the Tier 3 program is composed of several new 

requirements for all types of new vehicles, including a range of vehicle classes from small cars to 

large pick-up trucks and MDPVs, and even heavy-duty vehicles with diverse applications and 

specific engine designs matched to the needs of the users. This assessment also recognizes the 

critical role of gasoline sulfur content in making it possible for us to adopt emission standards at 

these very stringent levels, particularly for certain vehicle types. We provide below a full 

assessment of our current knowledge of the effects of gasoline sulfur on current vehicle 

emissions as well as our projections of how sulfur can be expected to affect compliance with the 

Tier 3 standards. 

Since there are multiple aspects to the Tier 3 program, it is necessary to consider 

technical feasibility in light of the different program requirements and their interactions with 

each other. For example, the technical feasibility of the finalized Tier 3 FTP NMOG+NOX and 

the PM standards is directly related to the specifications of the fuel, including fuel sulfur, RVP 

and ethanol content. Additionally, as mentioned above, the feasibility assessment must consider 

that different technologies may be needed on different types of vehicle applications (i.e., cars 

versus trucks) and must consider the effectiveness of these technologies to reduce emissions for 

the full useful life of the vehicle while operating on in-use fuels. Certain smaller vehicles with 

correspondingly small engines may be less challenged to meet FTP standards than larger 

vehicles with larger engines. Conversely, these smaller vehicles may have more difficulty 

meeting the SFTP requirements than the larger and more powerful vehicles. Additionally, the 

ability to meet the SFTP emission requirements can also be impacted by the path taken to meet 

the FTP requirements (i.e., larger volume catalysts for US06 emissions control vs. smaller 

catalysts for improved FTP cold-start emissions control). 

The rule also contains revised evaporative emission standards to be met on 9RVPE10 test 

fuel for LDVs, LDTs, MDPVs, and HDGVs, as well as leak standard for all gasoline-powered 

LDVs, LDTs, MDPVs, and HDGVs rated at or below 14,000 lbs GVWR and new OBD 

requirements for LDVs, LDTs, MDPVs, and HDVs rated at or below 14,000 lbs GVWR. The 

feasibility of these standards is discussed below as well. 

1.2 FTP NMOG+NOX Feasibility 

The new emission requirements include stringent NMOG+ NOX standards over the FTP 

that would require new vehicle hardware and additional control of gasoline sulfur levels in order 

to achieve the 30 mg/mi fleet average level in 2025. The type of new hardware that would be 

required would vary depending on the specific application and emission challenges. Smaller 
1-2 

vehicles with corresponding smaller engines would generally need less new hardware while 

larger vehicles and other vehicles with larger engines may need additional hardware and 

improvements beyond what would be needed for the smaller vehicles with smaller engines. 

Additionally, the fleet-average nature of the standards allows more challenged vehicles to be 

offset by vehicles that could outperform the required fleet averages. 

In order to assess the technical feasibility of a 30 mg/mi NMOG+NOX national fleet 

average FTP standard and a 3 mg/mi PM vehicle standard, EPA conducted two primary analyses. 

The initial analyses performed were of the current Tier 2 and LEV II fleets. This provided a 

baseline for the current federal fleet emissions performance, as well as the emissions 

performance of the California LEV II fleet. The second consideration was a modal analysis of 

typical vehicle emissions under certain operating conditions. In this way EPA determined the 

specific emissions performance challenges that vehicle manufacturers would face in meeting the 

lower fleet average emission standards. Each of these considerations is described in greater 

detail below. 

1.2.1 Assessment of the Current Federal Fleet Emissions 

The current federal fleet is only required to be certified to an average of Tier 2 Bin 5, 

equivalent to 160 mg/mi NMOG+NOX.

A

 For example, in MY 2009 92 percent of passenger cars 

and LDT1s were certified to Tier 2 Bin 5 and 91 percent of LDT2s through LDT4s were certified 

to Tier 2 Bin 5. This was not an unexpected result as there was no motivation for vehicle 

manufacturers to produce a federal fleet that over-complied with respect to the Tier 2 standards. 

By comparison, in the MY 2009 California fleet, where compliance with the LEVII declining 

NMOG requirement and the “PZEV” program encouraged manufacturers to certify to cleaner 

levels, only 30 percent of the passenger cars and LDT1s were certified to Tier 2 Bin 5 and 60 

percent were certified to Tier 2 Bin 3. The situation regarding the truck fleet in California was 

similarly stratified, with 37 percent of the LDT2s through LDT4s being certified to Tier 2 Bin 5 

and 55 percent being certified to Tier 2 Bin 3. In many cases, vehicles were being certified to a 

lower standard in California and a higher standard federally. In the proposal, EPA stated a belief 

that the patterns described above indicated that much of the Tier 2 fleet could be certified to a 

lower federal fleet average immediately, with no major feasibility concerns.B 

For the final rule, we have looked at MY2013 certification data. The MY 2013 data 

indicate that more engine families are being certified to cleaner Tier 2 bins than what was 

observed in previous MYs. In fact, in MY2013, while only 68% of passenger car and LDT1 

families and 65% of LDT2s through LDT4s are certified to Tier 2 Bin 5, 31% of passenger car 

and LDT1 and 29% of LDT2 through LDT4 are now certified to Tier 2 Bins 2 through 4. This 

supports our stated belief that the Tier 2 fleet could be certified to a lower federal fleet average 

without feasibility concerns. Table 1-1 shows that 58 MY2013 engine families have certified 

 

A

 The current Tier 2 program does not combine NMOG and NOX emissions into one fleet-average standard. The 

fleet-average standard in that program is for NOX emissions alone. 

B

 Compliance with full useful life standards in California occurs at much lower in-use gasoline sulfur levels than is 

the case with federally certified vehicles. For further discussion of the impact of gasoline fuel sulfur on light-vehicle 

emissions feasibility and in-use compliance, please refer to Section 1.2.4. 
1-3 

emission levels well below the Tier 2 bin to which they have been certified. The table also 

shows that these engine families have emissions at or below the Tier 3 30 mg/mi NMOG+NOx 

level. 

Table 1-1 MY2013 Certified Engine Families with Certified Emission Levels at or Below 

the Tier 3 NMOG+NOx 30 mg/mi Standard

Mfr Model NMOG

(g/mi)

NOx

(g/mi)

Certified 

NMOG 

+NOx

(g/mi)

NMOG 

+NOx of 

Tier 2 bin

(g/mi)

Certified 

emissions 

at or below 

Tier 3 bin

Audi A3 0.005 0.011 0.016 0.085 20

BMW John Cooper Works All4 

Countryman 0.017 0.010 0.027 0.160 30

BMW 328i xDrive 0.010 0.010 0.020 0.160 30

BMW 328 Ci Convertible 0.010 0.010 0.020 0.160 30

BMW ActiveHybrid 7 0.012 0.010 0.022 0.160 30

BMW ActiveHybrid 7 0.012 0.010 0.022 0.160 30

Chrysler Patriot 4wd 0.003 0.020 0.023 0.160 30

Chrysler Patriot 2wd 0.003 0.010 0.013 0.160 20

Chrysler Dart 0.003 0.010 0.013 0.110 20

Ford Fusion FWD 0.006 0.010 0.016 0.085 20

Ford FOCUS 0.004 0.010 0.014 0.085 20

Ford MKZ (HEV) 0.011 0.000 0.011 0.085 20

Ford MKZ (HEV) 0.011 0.000 0.011 0.085 20

Ford C-Max (PHEV) 0.008 0.010 0.018 0.085 20

GM REGAL 0.020 0.000 0.020 0.110 30

GM MALIBU 0.005 0.010 0.015 0.110 20

GM MALIBU 0.005 0.010 0.015 0.110 20

GM XTS 0.008 0.020 0.028 0.110 30

Honda INSIGHT EX 0.009 0.010 0.019 0.085 20

Honda ILX HYBRID 0.011 0.010 0.021 0.085 30

Honda CIVIC HYBRID 0.012 0.010 0.022 0.085 30

Jaguar Cars XJ 3.0 0.008 0.020 0.028 0.160 30

Mazda Mazda 3 DI 5-Door 0.008 0.010 0.018 0.160 20

Mercedes-Benz GLK 350 4MATIC 0.008 0.010 0.018 0.110 20

Mercedes-Benz S 400 HYBRID 0.005 0.010 0.015 0.110 20

Mercedes-Benz E 400 HYBRID 0.007 0.010 0.017 0.110 20

Nissan NISSAN TITAN 4WD 

Crew Cab XE LWB 0.024 0.000 0.024 0.160 30

Nissan NISSAN VERSA S 0.018 0.000 0.018 0.160 20

Nissan NISSAN ALTIMA 2.5SL 0.010 0.000 0.010 0.160 20

Subaru OUTBACK WAGON 

AWD 0.005 0.020 0.025 0.110 30

Subaru OUTBACK WAGON 

AWD 0.005 0.020 0.025 0.110 30

Suzuki GRAND VITARA 4WD 0.024 0.005 0.029 0.160 30

Toyota TACOMA 2WD 0.012 0.010 0.022 0.160 30

Toyota RX 450h AWD 0.008 0.000 0.008 0.085 20

Toyota RX 450h AWD 0.007 0.000 0.007 0.085 20

Toyota FJ CRUISER 4WD 0.019 0.010 0.029 0.160 30

Toyota LX 570 0.019 0.010 0.029 0.160 30

Toyota iQ 0.017 0.010 0.027 0.160 30
1-4 

Toyota YARIS 0.018 0.010 0.028 0.160 30

Toyota PRIUS c 0.006 0.000 0.006 0.085 20

Toyota PRIUS v 0.004 0.000 0.004 0.085 20

Toyota PRIUS 0.005 0.000 0.005 0.085 20

Toyota PRIUS Plug-in Hybrid 0.005 0.000 0.005 0.085 20

Toyota ES 300h 0.008 0.000 0.008 0.085 20

Toyota ES 300h 0.007 0.000 0.007 0.085 20

Toyota Camry Hybrid XLE 0.006 0.010 0.016 0.085 20

Toyota CAMRY 0.006 0.020 0.026 0.160 30

Toyota GS 450h 0.006 0.010 0.016 0.085 20

Toyota LS 460 L AWD 0.018 0.010 0.028 0.160 30

Toyota LS 600h L 0.006 0.000 0.006 0.085 20

Volkswagen Jetta Hybrid 0.008 0.007 0.015 0.085 20

Volkswagen Eos 0.004 0.008 0.012 0.085 20

Volkswagen Eos 0.004 0.008 0.012 0.085 20

Volkswagen Eos 0.004 0.008 0.012 0.085 20

Volkswagen Jetta 0.010 0.002 0.012 0.085 20

Volkswagen Jetta 0.010 0.002 0.012 0.085 20

Volkswagen Jetta 0.010 0.002 0.012 0.085 20

Volkswagen Jetta 0.010 0.002 0.012 0.085 20

Looking at the MY2013 certification data more closely and in the context of Tier 3 

compliance, we find that 40 engine families are certified to emission levels low enough to 

provide sufficient compliance margin (30% compliance margin, or 70% of the standard) to 

enable Tier 3 compliance today.C Table 1-2 shows these 40 engine families, their certified 

emission levels, and the Tier 3 bin into which they could be certified while providing 30% 

compliance margin. 

Table 1-2 MY2013 Certified Engine Families with Certified Emission Levels that Could be 

Certified to Tier 3 Today* 

Mfr Model NMOG

(g/mi)

NOx

(g/mi)

Certified 

NMOG +NOx

(g/mi)

Possible Tier 

3 bin*

Audi A3 0.005 0.011 0.016 30

BMW 328i xDrive 0.010 0.010 0.020 30

BMW 328 Ci Convertible 0.010 0.010 0.020 30

Chrysler Patriot 2wd 0.003 0.010 0.013 20

Chrysler Dart 0.003 0.010 0.013 20

Ford Fusion FWD 0.006 0.010 0.016 30

Ford FOCUS 0.004 0.010 0.014 20

Ford MKZ (HEV) 0.011 0.000 0.011 20

Ford MKZ (HEV) 0.011 0.000 0.011 20

 

C

 We believe that manufacturers will target compliance margins of 20-40% under Tier 3, as discussed in section 

1.2.3 of this chapter. Here we have used 30% as it represents the midpoint of that expected range. 
1-5 

Ford C-Max (PHEV) 0.008 0.010 0.018 30

GM REGAL 0.020 0.000 0.020 30

GM MALIBU 0.005 0.010 0.015 30

GM MALIBU 0.005 0.010 0.015 30

Honda INSIGHT EX 0.009 0.010 0.019 30

Honda ILX HYBRID 0.011 0.010 0.021 30

Mazda Mazda 3 DI 5-Door 0.008 0.010 0.018 30

Mercedes-Benz GLK 350 4MATIC 0.008 0.010 0.018 30

Mercedes-Benz S 400 HYBRID 0.005 0.010 0.015 30

Mercedes-Benz E 400 HYBRID 0.007 0.010 0.017 30

Nissan NISSAN VERSA S 0.018 0.000 0.018 30

Nissan NISSAN ALTIMA 2.5SL 0.010 0.000 0.010 20

Toyota RX 450h AWD 0.008 0.000 0.008 20

Toyota RX 450h AWD 0.007 0.000 0.007 20

Toyota PRIUS c 0.006 0.000 0.006 20

Toyota PRIUS v 0.004 0.000 0.004 20

Toyota PRIUS 0.005 0.000 0.005 20

Toyota PRIUS Plug-in Hybrid 0.005 0.000 0.005 20

Toyota ES 300h 0.008 0.000 0.008 20

Toyota ES 300h 0.007 0.000 0.007 20

Toyota Camry Hybrid XLE 0.006 0.010 0.016 30

Toyota GS 450h 0.006 0.010 0.016 30

Toyota LS 600h L 0.006 0.000 0.006 20

Volkswagen Jetta Hybrid 0.008 0.007 0.015 30

Volkswagen Eos 0.004 0.008 0.012 20

Volkswagen Eos 0.004 0.008 0.012 20

Volkswagen Eos 0.004 0.008 0.012 20

Volkswagen Jetta 0.010 0.002 0.012 20

Volkswagen Jetta 0.010 0.002 0.012 20

Volkswagen Jetta 0.010 0.002 0.012 20

Volkswagen Jetta 0.010 0.002 0.012 20

*Including at least a 20% compliance margin (i.e., emissions 70% of the standard).

To support the FTP emission levels finalized for heavy duty vehicles, we analyzed the 

certification emission results from the 2010 through 2013 MY vehiclesD

. The new Tier 3 fleet 

average NMOG+NOX standard in 2022 for Class 2b vehicles is 178 mg/mi while the level for 

Class 3 vehicles is 247 mg/mi. Shown in Table 1-3 below are the emission levels of 2010 and 

2011 MY heavy-duty vehicle models operating on various fuels. It is important to note that while 

we are finalizing a useful life of 150,000 miles, the current heavy duty vehicle requirements and 

therefore the reported emission results represent the 120,000 miles deteriorated results either 

calculated using deterioration factors applied to the 4,000 mile test or actual aged vehicles and 

components. It will be important for manufacturers to carefully manage emissions deterioration 

throughout the useful life of the vehicle to meet useful life emission requirements, consistent 

with the challenge for light-duty applications. 

 

D

 Manufacturers will regularly carry-over data for several model years. Where available, the latest reported 

certification data was used for this analysis. 
1-6 

Table 1-3: 2010 thru 2013 MY Heavy Duty Vehicle FTP 120k Certification Results 

Manufacturer Models Fuel 

Type

NMOG 

Level a

(mg/mi)

NOX

Level

(mg/mi)

NMOG

+NOX

(mg/mi)

CO

(g/mi)

PM

(mg/

mi)

Class 2b

b

Altech F250 CNG 10 100 110 5.9 -

Chrysler Ram 2500 Gasoline 118 100 218 1.6 -

Chrysler Ram 2500 Diesel 63 200 263 .2 0

Chrysler Ram 2500 CNG 24 100 124 .8 -

Ford F250 Diesel 104 200 304 .9 10

General 

Motors

Silverado 

2500

Diesel 79 200 279 .7 1

MercedesBenzSprinter Diesel 4 100 104 .1 10

Nissan NV 3500 

4.0L

Gasoline 57 0 57 1.4

Nissan NV 3500 

5.6L

Gasoline 66 100 166 1.3 -

Class 3

b

Baytech Silverado 

3500

CNG 11 100 111 1.3 -

Chrysler Ram 3500 Gasoline 133 200 333 2.6 -

Chrysler Ram 3500 Diesel 52 400 452 .2 3

Ford E350 c Gasoline 51 82 133 2 -

Ford E350 cE85 70 65 135 1.1 -

Ford F350 Diesel 89 300 389 .9 20

Ford F350 Gasoline 79 130 209 3.2 -

Ford F350 E85 76 83 159 1.8 -

General 

Motors

Silverado 

3500

Gasoline 131 150 281 3.4 -

General 

Motors

Silverado 

3500

Diesel 54 200 254 .5 0

MercedesBenzSprinter Diesel 11 100 111 .2 0

Notes: 

a Diesel reported as NMHC 

b Gasoline Class 2b models from General Motors and Ford certified using worst case Class 3 data 

c Tested at LVW with MDPVs 

1.2.2 NMOG and NOX Emissions on the FTP 

To understand how several currently-used technologies described below could be used by 

manufacturers to reach the stringent Tier 3 NMOG+NOX standards, it is helpful to consider 
1-7 

emissions formation in common modes of operation for gasoline engines, or modal analysis.E 

As previously stated during the discussion of the NMOG+NOX standard, many gasoline engines 

produce very little NOX over the FTP. Thus, the challenge faced by manufacturers for producing 

Tier 3 compliant gasoline powertrains is to reduce the NMOG portion of the emissions. Based 

on modal analysis of a gasoline powered vehicle being operated on the FTP cycle, approximately 

90 percent of the NMOG emissions occur during the first 50 seconds after a cold start. In 

addition, about 60 percent of the NOX emissions occur in this same period. The remainder of the 

emissions, particularly NOX emissions, are made during warmed up operation when the emission 

controls rely primarily on very high conversion efficiency of the catalyst. This is possible when 

catalyst performance, both on warm-up and during hot operation is not impeded by sulfur in the 

fuel. Figure 1-1 below shows the second-by-second emissions for NMOG and NOX following a 

cold start. 

Thus, effective control of these cold-start emissions, especially NMOG emissions, would 

be the primary technological goal of manufacturers complying with the Tier 3 FTP standards. 

As discussed below, manufacturers are already applying several technologies capable of 

significant reductions in these cold start emission to vehicles currently on the road. 

Figure 1-1 Modal Analysis of NMOG and NOX Emissions (LA92) 

1.2.3 Compliance Margin 

Vehicle manufacturers have historically designed vehicles to meet emissions targets 

which are 50-70 percent of the emission standards after the catalytic converters have been 

thermally aged and exposed to expected normal levels observed in-use of catalyst poisons (e.g., 

 

E

 A modal analysis provides a second-by-second view of the total amount of emissions over the entire cycle being 

considered. 
1-8 

sulfur from fuel, phosphorous from lubricating oil, etc.) out to the vehicle’s full useful life. This 

difference is referred to as “compliance margin” and is a result of manufacturers’ efforts to 

address all the sources of variability and emissions control system degradation that could occur 

during the certification or in-use testing processes and during in-use operation. We believe that 

manufacturers will continue require a compliance margin however the combined MOG+NOX 

approach for Tier 3 will allow for some flexibility in the compliance margin targets. We expect 

that compliance margins for the Tier 3 combined standard will range from 20% to 40%, because 

the combined standard generally allows an increase in one emission constituent to be offset by a 

decrease in the other. Thus, the emission design targets for Tier 3 standards at full useful life 

would be approximately 18 to 24 mg/mi MOG+NOX for a Bin 30 certified vehicle at full useful 

life. These sources of variability include: 

Test-to-test variability (within one test site and lab-to-lab) 

Build variation and manufacturing tolerances 

Vehicle operation (for example: driving habits, ambient temperature, etc.) 

Fuel composition 

o The deleterious effects of fuel sulfur on exhaust catalysts and oxygen 

sensors 

o Other fuel composition impacts 

Oil consumption 

o The impact of direct emission of lubricating oil on semi-volatile organic 

PM emissions 

o The impact of oil additives and other components (e.g., phosphorous) and 

oil ash on exhaust catalysts and oxygen sensors 

For MY 2013, the compliance margin for a Tier 2 Bin 5 vehicle averaged approximately 

65 percent. In other words, actual vehicle emissions performance was on average about 35 

percent of a 160 mg/mi NMOG+NOX standard, or about 56 mg/mi. By comparison, for MY 

2013 California-certified vehicles, the average SULEV compliance margin was somewhat less 

for the more stringent standards, approximately 50 percent. We believe that the recent California 

experience is a likely indicator of the smaller compliance margins that manufacturers would 

design for in order to comply with the Tier 3 FTP standards. Thus, a typical Tier 2 Bin 5 

vehicle, performing at 35 percent of the current standard (i.e., at about 56 mg/mi) would need 

improvements sufficient to achieve the Tier 3 targets for the 30 mg/mi combined NMOG+NOX

standard. 

1.2.4 Impact of Gasoline Sulfur Control on the Feasibility of the Vehicle Emission Standards 

 In this section, we discuss the impact of gasoline sulfur control on the feasibility of the 

Tier 3 vehicle emissions standards and on the exhaust emissions of the existing in-use vehicle 

fleet. Section 1.2.4.1 describes the chemistry and physics of the impacts of gasoline sulfur 

compounds on exhaust catalysts. Sections 1.2.4.2, 1.2.4.3, and 1.2.4.4 summarize research on the 

impacts of gasoline sulfur on vehicles utilizing various degrees of emission control technology, 

with Section 1.2.4.2 summarizing historical studies on the impact of gasoline sulfur on vehicle 

emissions, Section 1.2.4.3 describing impacts on Tier 2 vehicles and the existing light-duty 

vehicle fleet, and Section 1.2.4.4 describing impacts on vehicles using technology consistent 
1-9 

with what we expect to see in the future Tier 3 vehicle fleet. Section 1.2.4.5 provides EPA’s 

assessment of the level of gasoline sulfur control necessary for light-duty vehicles to comply 

with Tier 3 exhaust emission standards. 

EPA’s primary findings are: 

• Reducing gasoline sulfur content to a 10 ppm average will provide immediate and 

significant exhaust emissions reductions to the current, in-use fleet of light-duty 

vehicles. 

• Reducing gasoline sulfur content to an average of 10 ppm will enable vehicle 

manufacturers to certify their entire product lines of new light-duty vehicles to the 

final Tier 3 Bin 30 fleet average standards. Without such sulfur control it would not 

be possible for vehicle manufacturers to reduce emissions sufficiently below Tier 2 

levels to meet the new Tier 3 standards because it would require offsetting 

significantly higher exhaust emissions resulting from the higher sulfur levels. EPA 

has not identified any existing or developing technologies that would compensate for 

or offset the higher exhaust emissions resulting from higher fuel sulfur levels. 

1.2.4.1 Gasoline Sulfur Impacts on Exhaust Catalysts 

Modern three-way catalytic exhaust systems utilize platinum group metals (PGM), metal 

oxides and other active materials to selectively oxidize organic compounds and carbon monoxide 

in the exhaust gases. These systems simultaneously reduce NOx when air-to-fuel ratio control 

operates in a condition of relatively low amplitude/high frequency oscillation about the 

stoichiometric point. Sulfur is a well-known catalyst poison. There is a large body of work 

demonstrating sulfur inhibition of the emissions control performance of PGM three-way exhaust 

catalyst systems.1,2,3,4,5,6,7,8,9,10 The nature of sulfur interactions with washcoat materials, active 

catalytic materials and catalyst substrates is complex and varies with catalyst composition, 

exhaust gas composition and exhaust temperature. The variation of these interactions with 

exhaust gas composition and temperature means that the operational history of a vehicle is an 

important factor; continuous light-load operation, throttle tip-in events and enrichment under 

high-load conditions can all impact sulfur interactions with the catalyst. 

Sulfur from gasoline is oxidized during spark-ignition engine combustion primarily to 

SO2 and, to a much lesser extent, SO3

-2. Sulfur oxides selectively chemically bind (chemisorb) 

with, and in some cases react with, active sites and coating materials within the catalyst, thus 

inhibiting the intended catalytic reactions. Sulfur oxides inhibit pollutant catalysis chiefly by 

selective poisoning of active PGM, ceria sites, and the alumina washcoating material (see Figure 

1-2).11 The amount of sulfur retained by an exhaust catalyst system is primarily a function of the 

concentration of sulfur oxides in the incoming exhaust gases, air-to-fuel ratio feedback and 

control by the engine management system, the operating temperature of the catalyst and the 

active materials and coatings used within the catalyst. 

In their supplemental comments on the proposed Tier 3 rule, API criticized the use of 

emissions data generated using gasoline with sulfur content outside of the range of 10 ppm to 30 
1-10 

ppm within EPA and other analyses of the impacts of gasoline sulfur on exhaust emissions from 

current in-use (Tier 2) and future (Tier 3) light-duty vehicles. Specific examples include: 

Comparisons of exhaust emissions at 5 ppm and 28 ppm gasoline sulfur levels 

within the recent EPA study of emissions from Tier 2 vehicles12

Comparison of exhaust emissions of a SULEV vehicle at 8 ppm and 33 ppm 

gasoline sulfur levels within the Takei et al. study13

Comparison of exhaust emissions of a PZEV vehicle at 3 ppm and 33 ppm 

gasoline sulfur levels within the Ball et al. study.14

The relationship between changes in gasoline sulfur content and NOx, HC, NMHC and 

NMOG emissions is typically linear. The linearity of sulfur impacts on NOx, NMHC and 

NMOG emissions is supported by past studies with multiple fuel sulfur levels all of which 

compare gasoline with differing sulfur levels that are below approximately 100 ppm (e.g. CRC 

E-60 and 2001 AAM/AIAM programs as well as by comments on this rulemaking submitted by 

MECA).15,16,17 An assumption of linearity of the effect of gasoline sulfur level on catalyst 

efficiency between any two test fuels with differing sulfur levels is reasonable given that the 

mass flow rate of sulfur in exhaust gas changes in proportion to its concentration in the fuel, and 

that the chemistry of adsorption of sulfur on the active catalyst sites is an approximately-firstorder chemisorption until all active sites within a catalyst reach an equilibrium state relative to 

further input of sulfur compounds. The relative linearity of the effect of gasoline sulfur level on 

NMOG and NOx emissions allows exhaust emissions results generated within EPA and other 

studies of gasoline sulfur at levels immediately above or below either 10 ppm or 30 ppm to be 

normalized to either 10 ppm sulfur (Tier 3 gasoline) or to 30 ppm sulfur (Tier 2 gasoline, which 

used in the analysis of the impacts of the Tier 3 gasoline standards on existing in-use vehicles 

and future Tier 3 vehicles. 

In their supplemental comments to the Tier 3 proposal, API also commented that EPA 

did not show the sulfur impact on exhaust emissions at intermediate sulfur levels between 10 

ppm and 30 ppm.18 In response, based on the relative linearity of the effect of gasoline sulfur 

level on NMOG and NOx emissions allowing exhaust emissions to be estimated for gasoline 

sulfur levels between 10 and 30 ppm, data in EPA’s analysis increased NMOG+NOx emissions 

(as fuel sulfur increases) that becomes more severe (i.e., higher percentage increase in 

NMOG+NOx emissions) for vehicles with extremely low19 exhaust emission (SULEV, PZEV, 

LEVIII, Tier 3) as described in further detail in Sections 1.2.4.4 and 1.2.4.5.
1-11 

100 Å

Catalytic Site Deactivated by Sulfur Poisoning

Active Catalytic Site

Alumina Washcoat

Monolith Substrate

Figure 1-2 Functional schematic showing selective poisoning of active catalytic sites by 

sulfur compounds. Adapted from Heck and Farrauto 2002.

20

Selective sulfur poisoning of platinum (Pt) and rhodium (Rh) is primarily from surfacelayer chemisorption. Sulfur poisoning of palladium (Pd) and ceria appears to be via 

chemisorption combined with formation of more stable metallic sulfur compounds, e.g. PdS and 

Ce2O2S, present in both surface and bulk form (i.e., below the surface layer).21,22,23,24

 Ceria, 

zirconia and other oxygen storage components (OSC) play an important role that is crucial to 

NOX reduction over Rh as the engine air-to-fuel ratio oscillates about the stoichiometric closedloop control point. 25 Ceria sulfation interferes with OSC functionality within the catalyst and 

thus can have a detrimental impact on the catalyst’s ability to effectively reduce NOx emissions. 

Water-gas-shift reactions are important for NOX reduction over catalysts combining Pd and ceria. 

This reaction can be blocked by sulfur poisoning and may be responsible for observations of 

reduced NOX activity over Pd/ceria catalysts even with exposure to fairly low levels of sulfur 

(equivalent to 15 ppm in gasoline).26, 27 Pd is also of increased importance for meeting Tier 3 

standards due to its unique application in the close-coupled-catalyst location required for 

vehicles certifying to very stringent emission standards. Close-coupling means that the exhaust 

catalyst is moved as close as possible to the engine’s exhaust ports within the packaging 

constraints of an engine compartment. This ensures that the catalyst reaches its minimal 

operational, or “light-off,” temperature as quickly as possible after the vehicle is started. It also 

means, however, that the exhaust catalyst(s) in the close-coupled location(s) are subject to higher 

exhaust temperatures during fully-warmed up operation. Pd is required in closed-coupled 

catalysts due to its resistance to high-temperature thermal sintering thereby maintaining 

sufficient durability of the emissions control system over the useful life of a vehicle. Sulfur 
1-12 

removal from Pd requires rich operation at higher temperatures than required for sulfur removal 

from other PGM catalysts.27

In addition to its interaction with catalyst materials, sulfur can also react with the washcoating itself to form alumina sulfate, which in turn can block coating pores and reduce gaseous 

diffusion to active materials below the coating surface (see Figure 1-2).28 This may be a 

significant mechanism for the observed storage of sulfur compounds at light and moderate load 

operation with subsequent, rapid release as sulfate particulate matter emissions when high-load, 

high-temperature conditions are encountered.29

Operating the catalyst at a sufficiently high temperature under net reducing conditions 

(e.g., air-to-fuel equivalence that is net fuel-rich of stoichiometry) can effectively release the 

sulfur oxides from catalyst components. Thus, regular operation at sufficiently high 

temperatures at net fuel-rich air-to-fuel ratios can minimize the effects of fuel sulfur levels on 

catalyst active materials and catalyst efficiency; however, it cannot completely eliminate the 

effects of sulfur poisoning. In current vehicles, desulfurization conditions occur typically at high 

loads when there is a degree of commanded enrichment (i.e., fuel enrichment commanded by the 

engine management system primarily for protection of engine and/or exhaust system 

components). A study of Tier 2 vehicles in the in-use fleet recently completed by EPA30 shows 

that emission levels immediately following high speed/load operation is still a function of fuel 

sulfur level for the gasoline used following desulfurization. If a vehicle operates on gasoline 

with less than 10 ppm sulfur, exhaust emissions stabilize over repeat FTP tests at emissions near 

those of the first FTP that follows the high speed/load operation and catalyst desulfurization. If 

the vehicle continues to operate on higher sulfur gasoline following desulfurization, exhaust 

emissions creep upward until a new equilibrium exhaust emissions level is established. This 

suggests that lower fuel sulfur levels achieve emission benefits unachievable by catalyst 

desulfurization procedures alone. Continued operation on gasoline with a 10 ppm average 

sulfur content or lower is necessary after catalyst desulfurization in order to achieve emissions 

reductions with the current in-use fleet.31 Furthermore, regular operation at the high exhaust 

temperatures and rich air-to-fuel ratios necessary for catalyst desulfurization is not desirable and 

may not be possible for future Tier 3 vehicles for several reasons: 

Thermal sintering and resultant catalyst degradation: The temperatures necessary 

to release sulfur oxides are high enough to lead to thermal degradation of the 

catalyst over time via thermal sintering of active materials. Sintering reduces the 

surface area available to participate in reactions and thus reduces the overall 

effectiveness of the catalyst. 

Operational conditions: It is not always possible to maintain fuel-rich operational 

conditions and exhaust catalyst temperatures that are high enough for sulfur 

removal because of cold weather, idle conditions and light-load operation. 

Increased emissions: In order to achieve greater emission reductions across a 

fuller range of in-use driving conditions, vehicle manufacturers’ use of 

commanded enrichment, which has been beneficial for sulfur removal, will be 

greatly reduced or eliminated under Tier 3. Additionally, the fuel-rich air-to-fuel 

ratios necessary for sulfur removal from active catalytic surfaces would result in 
1-13 

increased PM, NMOG, CO and air toxic emissions, particularly at the hightemperature, high load conditions (e.g., US06 or comparable) necessary for sulfur 

removal. Previously used levels of commanded enrichment (e.g., under Tier 2) 

would interfere with the strategies necessary to comply with more stringent Tier 3 

SFTP exhaust emissions standards. There are also additional provisions within the 

Tier 3 standards that further restrict the use of US06 and off-cycle commanded 

enrichment in an effort to reduce high-load and off-cycle PM, NMOG, CO and air 

toxic emissions.32

Expected changes to engine performance necessary to reduce fuel consumption 

and greenhouse gas emissions will improve the thermal efficiency of engines and 

may result in reduced exhaust temperatures. 

1.2.4.2 Previous Studies of Gasoline Sulfur Impacts 

This section summarizes studies to provide historical context regarding what is known 

about the direct impacts of gasoline sulfur on vehicle exhaust emissions. Reducing fuel sulfur 

levels has been the primary regulatory mechanism EPA has used to minimize sulfur 

contamination of exhaust catalysts and to ensure optimum emissions performance over the useful 

life of a vehicle. The impact of gasoline sulfur on exhaust catalyst systems has become even 

more important as vehicle emission standards have become more stringent. Studies have 

suggested a progressive increase in catalyst sensitivity to sulfur (in terms of percent conversion 

efficiency) when standards increase in stringency and emissions levels decrease. Emission 

standards under the programs that preceded the Tier 2 program (Tier 0, Tier 1 and National LEV, 

or NLEV) were high enough that the impact of sulfur was considered of little importance. The 

Tier 2 program recognized the importance of sulfur and reduced the sulfur levels in the fuel from 

around 300 ppm to 30 ppm in conjunction with the new emission standards.33

 At that time, very 

little work had been done to evaluate the effect of further reductions in fuel sulfur, especially on 

in-use vehicles that may have some degree of catalyst deterioration due to real-world operation 

or on vehicles with extremely low tailpipe emissions, as described earlier. 

In 2005, EPA and several automakers jointly conducted a research program, the Mobile 

Source Air Toxics (MSAT) Study that examined the effects of sulfur and other gasoline 

properties such as benzene and volatility on emissions from a fleet of nine Tier 2 compliant 

vehicles.34

 The study found significant reductions in NOX, CO and total hydrocarbons (HC) 

when the vehicles were tested on low sulfur fuel, relative to 32 ppm fuel. In particular, the study 

found a 48 percent increase in NOX over the FTP when gasoline sulfur was increased from 6 

ppm to 32 ppm. Given the preparatory procedures related to catalyst clean-out and loading used 

by these studies, these results may represent a “best case” scenario relative to what would be 

expected under more typical driving conditions. Nonetheless, these data suggested the effect of 

in-use sulfur loading was largely reversible for Tier 2 vehicles, and that there were likely to be 

significant emission reductions possible with further reductions in gasoline sulfur level. More 

recently, EPA completed a comprehensive study on the effects of gasoline sulfur on the exhaust 

emissions of Tier 2 vehicles at low to moderate mileage levels.35

 Further details of this study are 

summarized in Section 1.2.4.3of this preamble. 
1-14 

In the NPRM, we summarized the limited data available regarding the impact of gasoline 

sulfur on the near-zero exhaust emission vehicle technologies that will be necessary for Tier 3 

compliance. Vehicles certified to California LEV II SULEV and PZEV standards and federal 

Tier 2 Bin 2 standards achieve levels of exhaust emissions control consistent with the levels of 

control that will be necessary for Tier 3 compliance. While these vehicles represent only a 

relatively small subset (e.g., typically small light-duty vehicles and light-duty trucks with limited 

GVWR or towing utility) of the broad range of vehicles that will need to comply with Tier 3 

standards as part of a fleet-wide average, data on these vehicles provides an opportunity to study 

the impact of gasoline sulfur on near-zero exhaust emission technologies and is generally 

representative of technology that are expected to be used with mid-size and smaller light-duty 

vehicles for Tier 3 compliance. Vehicle testing by Toyota (Takei et al.) of LEV I, LEV II ULEV 

and prototype SULEV vehicles showed larger percentage increases in NOX and HC emissions 

for SULEV vehicles as gasoline sulfur increased from 8 ppm to 30 ppm, as compared to other 

LEV vehicles they tested36. Ball et al. of Umicore Autocat USA, Inc. studied the impact of 

gasoline fuel sulfur levels of 3 ppm and 33 ppm on the emissions of a 2009 Chevrolet Malibu 

PZEV37

 Umicore’s testing of the Malibu PZEV vehicle showed a pronounced and progressive 

trend of increasing NOX emissions (referred to as “NOX creep”) when switching from a 3 ppm 

sulfur gasoline to repeated, back-to-back FTP tests using 33 ppm sulfur gasoline. The PZEV 

Chevrolet Malibu, after being aged to an equivalent of 150,000 miles, demonstrated emissions at 

a level consistent with the Tier 3 Bin 30 NMOG+NOX standards when operated on 3 ppm sulfur 

fuel and for at least one FTP test after switching to 33 ppm certification fuel. Following 

operation over 2 FTP cycles on 33 ppm sulfur fuel, NOX emissions alone were more than double 

the Tier 3 30 mg/mi NMOG+NOX standard.10

 This represents a 70% NOX increase between 3 

ppm sulfur and 33 ppm sulfur gasolines, approximately 2-3 times of what has been previously 

reported for similar changes in fuel sulfur level for Tier 2 and older vehicles.38,39

Both the Umicore and Toyota studies suggest that the emissions from vehicles using 

near-zero exhaust emissions control technology similar to what is expected for compliance with 

the Tier 3 standards are more sensitive to changes in gasoline sulfur content at low (sub-30 ppm) 

sulfur concentrations than technology used to meet the higher Federal Tier 2 and California LEV 

II standards. The Umicore and Toyota studies clearly indicate that a progressive increase in 

catalyst sensitivity to sulfur continues as exhaust emissions decrease from levels required by 

federal Tier 2 and California LEV II emissions standards to the lower levels required by Tier 3 

emissions standards. In addition, although vehicles with Tier 2 technology have somewhat less 

sulfur sensitivity compared to future Tier 3 vehicles, there is still significant opportunity for 

further emissions reductions from the existing in-use fleet by reducing gasoline sulfur content 

from 30 ppm to 10 ppm. The results of recent testing demonstrating the potential for in-use 

emissions reductions from further gasoline sulfur control are summarized in Section 1.2.43). 

Recent data on the impact of gasoline sulfur on vehicles with exhaust emission control 

technologies that we expect to be used with Tier 3 vehicles is summarized in Sections 1.2.4.4 

and 1.2.4.5. 

1.2.4.3 EPA Testing of Gasoline Sulfur Effects on Tier 2 Vehicles and the In-Use Fleet 

Both the MSAT40 and Umicore41 studies showed the emission reduction potential of 

lower sulfur fuel on Tier 2 and later technology vehicles over the FTP cycle. However, assessing 

the potential for reduction on the in-use fleet requires understanding how sulfur exposure over 
1-15 

time impacts emissions, and what the state of catalyst sulfur loading is for the typical vehicle in 

the field. In response to these data needs, EPA conducted a new study to assess the emission 

reductions expected from the in-use Tier 2 fleet with a reduction in fuel sulfur level from current 

levels.42 It was designed to take into consideration what was known from prior studies on sulfur 

build-up in catalysts over time and the effect of periodic regeneration events that may result from 

higher speed and load operation over the course of day-to-day driving. 

The study sample described in this analysis consisted of 93 cars and light trucks recruited 

from owners in southeast Michigan, covering model years 2007-9 with approximately 20,000-

40,000 odometer miles.43 The makes and models targeted for recruitment were chosen to be 

representative of high sales vehicles covering a range of types and sizes. Test fuels were two 

non-ethanol gasolines with properties typical of certification test fuel, one at a sulfur level of 5 

ppm and the other at 28 ppm. All emissions data was collected using the FTP cycle at a nominal 

temperature of 75 °F. 

Using the 28 ppm test fuel, emissions data were collected from vehicles in their asreceived state as well as following a high-speed/load “clean-out” procedure consisting of two 

back-to-back US06 cycles intended to reduce sulfur loading in the catalyst. A statistical analysis 

of this data showed highly significant reductions in several pollutants including NOX and 

hydrocarbons, demonstrating that sulfur loadings have a large effect on exhaust catalyst 

performance, and that Tier 2 vehicles can achieve significant reductions based on removing, at 

least in part, the negative impact of the sulfur loading on catalyst efficiency (Table 1-4). For 

example, Bag 2 NOX emissions dropped 31 percent between the pre- and post-cleanout tests on 

28 ppm fuel. 
1-16 

Table 1-4 Percent Reduction in In-Use Emissions After the Clean-out 

Using 28 ppm Test Fuela

NOX

(p-value)

THC

(p-value)

CO

(p-value)

NMHC

(p-value)

CH4

(p-value)

PM

(p-value)

Bag 1 – – 6.0% 

(0.0151)

– – 15.4%

(< 

0.0001)

Bag 2 31.4% 

(0.0003)

14.9% 

(0.0118)

– 18.7% 

(0.0131)

14.4% 

(0.0019)

–

Bag 3 35.4% 

(<0.0001)

20.4% 

(<0.0001)

21.5% 

(0.0001)

27.7% 

(<0.0001)

10.3% 

(<0.0001)

24.5% 

(<0.0001)

FTP 

Composite

11.4% 

(0.0002)

3.8% 

(0.0249)

6.8% 

(0.0107)

3.5% 

(0.0498)

6.0% 

(0.0011)

13.7% 

(<0.0001)

Bag 1 – Bag 3 – – 7.2%

(0.0656)

– – –

 a

 The clean-out effect is not significant at α = 0.10 when no reduction estimate is provided. 

To assess the impact of lower sulfur fuel on in-use emissions, further testing was 

conducted on a representative subset of vehicles on 28 ppm and 5 ppm fuel with accumulated 

mileage. A first step in this portion of the study was to assess the differences in the effectiveness 

of the clean-out procedure under different fuel sulfur levels. Table 1-5 presents a comparison of 

emissions immediately following (<50 miles) the clean-out procedures at the low vs. high sulfur 

level. These results show significant emission reductions for the 5 ppm fuel relative to the 28 

ppm fuel immediately after this clean-out; for example, Bag 2 NOX emissions were 34 percent 

lower on the 5 ppm fuel vs. the 28 ppm fuel. This indicates that the catalyst is not fully 

desulfurized, even after a clean out procedure, as long as there is sulfur in the fuel. This further 

indicates that current sulfur levels in gasoline continue to have a long-term, adverse effect on 

exhaust emissions control that is not fully removed by intermittent clean-out procedures that can 

occur in day-to-day operation of a vehicle and demonstrates that lowering sulfur levels to 10 

ppm on average will significantly reduce the effects of sulfur impairment on emissions control 

technology. 

Table 1-5 Percent Reduction in Exhaust Emissions When Going from 28 ppm to 5 ppm 

Sulfur Gasoline for the First Three Repeat FTP Tests Immediately Following Clean-out

NOX

(p-value)

THC

(p-value)

CO

(p-value)

NMHC

(p-value)

CH4

(p-value)

PMa

Bag 1 5.3%

(0.0513)

6.8%

(0.0053)

6.2%

(0.0083)

5.7%

(0.0276)

14.0%

(<0.0001)

–

Bag 2 34.4%

(0.0036)

33.9%

(<0.0001)

–

a

26.4%

(0.0420)

49.4%

(<0.0001)

–

Bag 3 42.5%

(<0.0001)

36.9%

(<0.0001)

14.7%

(0.0041)

51.7%

(<0.0001)

28.5%

(<0.0001)

–

FTP Composite 15.0% 13.3% 8.5% 10.9% 23.6% –
1-17 

(0.0002) (<0.0001) (0.0050) (0.0012) (<0.0001)

Bag 1 – Bag 3 –

a

–

a

–

a

–

a

–

a

–

 a The effectiveness of clean-out cycle is not significant at α = 0.10.

To assess the overall in-use reduction between high and low sulfur fuel, a mixed model 

analysis of all data as a function of fuel sulfur level and miles driven after cleanout was 

performed. This analysis found highly significant reductions for several pollutants, as shown in 

Table 1-6. Reductions for Bag 2 NOX were particularly high, estimated at 52 percent between 28 

ppm and 5 ppm overall. For all pollutants, the model fitting did not find a significant miles-bysulfur interaction, suggesting the relative differences were not dependent on miles driven after 

clean-out. 

Table 1-6 Percent Reduction in Emissions from 28 ppm to 5 ppm Fuel Sulfur 

on In-Use Tier 2 Vehicles

NOX

(p-value)

THC

(p-value)

CO

(p-value)

NMHC

(p-value)

CH4

(p-value)

NOX+NMOG

(p-value) PMa

Bag 1 7.1%

(0.0216)

9.2%

(0.0002)

6.7%

(0.0131)

8.1%

(0.0017)

16.6%

(< 0.0001) N/A –

Bag 2 51.9%

(< 0.0001)

43.3%

(< 0.0001) –

a 42.7%

(0.0003)

51.8%

(< 0.0001) N/A –

Bag 3 47.8%

(< 0.0001)

40.2%

(< 0.0001)

15.9%

(0.0003)

54.7%

(< 0.0001)

29.2%

(< 0.0001) N/A –

FTP Composite 14.1%

(0.0008)

15.3%

(< 0.0001)

9.5%

(< 0.0001)

12.4%

(< 0.0001)

29.3%

(< 0.0001)

14.4%

(< 0.0001)

–

Bag 1 – Bag 3 –

a 5.9%

(0.0074) –

a

–

b

–

b N/A –

 a Sulfur level not significant at α = 0.10. 

 b Inconclusive because the mixed model did not converge. 

Major findings from this study include: 

Largely reversible sulfur loading is occurring in the in-use fleet of Tier 2 vehicles and 

has a measureable effect on emissions of NOX, hydrocarbons, and other pollutants of 

interest. 

The effectiveness of high speed/load procedures in restoring catalyst efficiency is 

limited when operating on higher sulfur fuel. 
1-18 

Reducing fuel sulfur levels from current levels to levels in the range of the Tier 3 

gasoline sulfur standards is expected to achieve significant reductions in emissions of 

NOX, hydrocarbons, and other pollutants of interest in the current in-use fleet. 

Assuming that the emissions impacts vs. gasoline sulfur content are approximately 

linear, changing gasoline sulfur content from 30 ppm to 10 ppm would result in 

NMOG+NOx emissions decreasing from 52 mg/mi to 45 mg/mi, respectively (a 13% 

decrease), and NOx emissions decreasing from 19 mg/mi to 16 mg/mi, respectively (a 

16% decrease), for the vehicles in the study. 

To evaluate the robustness of the statistical analyses assessing the overall in-use 

emissions reduction between operation on high and low sulfur fuel (Table 1-6), a series of 

sensitivity analyses were performed to assess the impacts on study results of measurements from 

low-emitting vehicles and influential vehicles, as documented in detail in the report.44

 The 

sensitivity analyses showed that the magnitude and the statistical significance of the results were 

not impacted and thus demonstrated that the results are statistically robust. We also subjected the 

design of the experiment and data analysis to a contractor-led independent peer-review process 

in accordance with EPA’s peer review guidance. The results of the peer review45,46 largely 

supported the study design, statistical analyses, and the conclusions from the program and raised 

only minor concerns that have not changed the overall conclusions and have subsequently been 

addressed in the final version of the report.47 

Overall, the reductions found in this study are in agreement with other low sulfur studies 

conducted on Tier 2 vehicles, namely MSAT and Umicore studies mentioned above, in terms of 

the magnitude of NOX and HC reductions when switching from 28 ppm to 5 ppm fuel.48 We 

have reviewed the results of the emission effects study performed by SGS, which was included 

with API’s comments on the Tier 3 proposal, and have concluded that these results are also 

consistent with the findings of EPA’s Tier 2 in-use study, specifically that exhaust emissions 

performance is sensitive to fuel sulfur level.49

 The SGS study also suggests that negative effects 

of exposure to a somewhat higher sulfur level (80 ppm in this case) are largely reversible for Tier 

2 vehicles, meaning that reducing fuel sulfur levels nationwide will bring significant immediate 

benefits by reducing emissions of the existing fleet. For further details regarding the Tier 2 InUse Gasoline Sulfur Effects Study, see the final report.50

As a follow-on phase to the Tier 2 in-use study, EPA analyzed five vehicles51 certified to 

Tier 2 Bin 4, LEV II ULEV and LEV II SULEV exhaust emissions standards to assess the 

gasoline sulfur sensitivity of Tier 2 and California LEV II vehicles with emission levels 

approaching or comparable to the Tier 3 standards. The analysis found that these low-emitting 

Tier 2 vehicles showed similar or greater sensitivity to fuel sulfur levels compared to the original 

Tier 2 test fleet – for example, a 24 percent reduction in FTP composite NOx emissions when 

sulfur is reduced from 28 ppm to 5 ppm.52 Test results discussed below in Section 1.2.4.4 also 

confirm that there is significantly increased sensitivity of exhaust emissions to gasoline sulfur as 

vehicle technologies advance towards exhaust emissions approaching near-zero emissions (e.g., 

Tier 3 Bin 50 and lower). The impact of fuel sulfur on vehicles with exhaust emission control 

technologies that we expect to be used with Tier 3 vehicles is summarized in the next two 

Sections (1.2.4.4 and 1.2.4.5). 
1-19 

EPA believes that the studies by EPA and others described in this Section strongly 

support our conclusion that reducing gasoline sulfur content to a 10 ppm average will result in 

significant exhaust emissions reductions from the current in-use fleet. However, some 

commenters have expressed concerns about the relevance and appropriateness of the data, as 

well as the conclusions drawn from them. The Summary and Analysis of Comments document, 

available in the docket for this rulemaking, provides our responses to those comments. 

1.2.4.4 Testing of Gasoline Sulfur Effects on Vehicles with Tier 3/LEV III Technology 

The Tier 3 fleet average exhaust emissions standards of 30 mg/mi NMOG+NOx will 

require large reductions of emissions across a broad range of light-duty vehicles and trucks with 

differing degrees of utility. Previous studies of sulfur impacts on extremely low exhaust 

emission vehicles (e.g., Toyota, Umicore) were limited to mid-size or smaller light-duty 

vehicles. There are currently nonhybrid LDT3 or any LDT4 vehicles certified at or below 

Federal Tier 2 Bin 3 or to the California LEV II SULEV exhaust emission standards. At the time 

of the Tier 3 NPRM, EPA was not aware of any existing data demonstrating the impact of 

changes in gasoline sulfur content on larger vehicles with technology comparable to what would 

be expected for compliance with Tier 3 exhaust emission standards. In their supplemental 

comments to the Tier 3 proposal, API criticized EPA’s reliance on emissions data from older 

vehicles that were not considered to be examples of future Tier-3-like vehicles. In order to 

further evaluate this issue, the Agency initiated a test program at EPA’s National Vehicle and 

Fuel Emissions Laboratory (NVFEL) in Ann Arbor, Michigan. The Agency obtained a heavylight-duty truck and applied changes to the design and layout of the exhaust catalyst system and 

to the calibration of the engine management system consistent with our engineering analyses of 

technology necessary to meet Tier 3 Bin 30 emissions with a 20 to 40% compliance margin at 

150,000 miles. EPA also requested that Umicore loan the Agency the vehicle tested in their 

study to undergo further evaluation of gasoline sulfur impacts on exhaust emissions. In addition, 

Ford Motor Company completed testing of fuel sulfur effects on a Tier 3/LEV III developmental 

heavy-light-duty truck and submitted a summary report of their findings as part of their 

supplemental comments to the Tier 3 NPRM. The results of these three test programs are 

summarized below. 

1.2.4.4.1 Ford Motor Company Tier 3 Sulfur Test Program 

Ford Motor Company recently completed testing of a heavy-light-duty truck (i.e., 

between 6000 and 8500 pounds GVWR) under development to meet the Tier 3 Bin 50 standards 

on two different fuel sulfur levels and submitted the resulting data to EPA as part of its 

supplemental comments. 53,54

 The test results from this vehicle are particularly important when 

considering the following factors: 

These are the first detailed emissions data submitted by a vehicle manufacturer to 

the Agency demonstrating emissions of a heavy-light-duty-truck consistent with 

Tier 3 Bin 50 or lower emissions levels. 

The truck tested uses a version of Ford’s 2.0 L GTDI engine, an engine with high 

BMEP (approximately 23-bar) that can allow significant engine displacement 
1-20 

downsizing while maintaining the truck’s utility. This is a key enabling GHG 

reduction strategy analyzed by EPA in the 2017-2025 GHG Final Rule.55 

The vehicle was specifically under development by a vehicle manufacturer with 

an engineering target of meeting Tier 3 Bin 50 and LEV III ULEV50 exhaust 

emissions standards. 

Turbocharged, downsized engines are key technologies within Ford’s strategy to reduce GHG 

emissions.56 EPA expects that trucks with configurations similar to this developmental Ford 

Explorer (downsized engines with reduced GHG emissions and very low emissions of 

NMOG+NOx) will become increasingly prevalent within the timeframe of the implementation of 

the Tier 3 regulations. 

The developmental truck used close-coupling of both catalyst substrates and relatively 

high PGM loading (150 g/ft3). Ford used accelerated aging of the catalysts and O2 sensors to an 

equivalent of 150,000 miles (the Tier 3 full useful life). The developmental hardware and engine 

management calibration configuration of this truck was designed to meet federalTier 3 Bin 50 

and California LEV III ULEV50 standards of 50 mg/mi NMOG+NOx at 150,000 miles. The 

emissions data submitted by Ford included NOx and NMHC emissions during operation on E10 

California LEV III certification fuel at two different sulfur levels, 10 ppm and 26.5 ppm. Ford 

did not provide NMOG emissions data but there was sufficient information for EPA to calculate 

NMOG emissions from the provided NMHC data using calculations from Title 40 CFR § 

1066.665. 

The truck demonstrated average FTP NMOG+NOx emissions of 37 mg/mi on the 10 ppm 

E10 California LEV III fuel, emissions that are consistent with compliance with Bin 50 and 

ULEV50 standards with a reasonable margin of compliance (emissions at approximately 70% of 

the standard). Retesting of the same vehicle on LEV3 E10 blended57 to 26.5 ppm S resulted in 

average NMOG+NOx emissions of 53 mg/mi, 6% above the Tier 3 Bin 50 standard. Ford found 

a high level of statistical significance with respect to the increase of emissions with increasing 

fuel sulfur. Assuming a linear effect of sulfur on emissions performance, NMOG+NOx 

emissions would be approximately 56 mg/mi at 30 ppm sulfur, which is approximately 12% 

above the Bin 50 exhaust emissions standard. This also represents an increase in NMOG+NOx 

emissions of 53% with an approximate doubling of NOx emissions and a 13 % increase in 

NMOG for 30 ppm sulfur gasoline vs. 10 ppm sulfur gasoline. 

The advanced technology Ford truck, which was shown to be capable of complying with 

the Tier 3 Bin 50 standard with a reasonable margin of compliance on 10 ppm sulfur gasoline, in 

effect reverted to approximately LEV II ULEV exhaust emissions levels when tested on higher 

sulfur gasoline, equivalent to the previous level of emissions control to which earlier models of 

this vehicle were certified for MY 2013. The effect of increasing gasoline sulfur levels from 10 

ppm to 30 ppm58 on this vehicle essentially negated the entire benefit of the advances in 

emissions control technology that were applied by the vehicle manufacturer to meet 

developmental goals for compliance with Tier 3 standards. This clearly indicates, for this 

vehicle model using technology representative of what would be expected for compliance with 

Tier 3 Bin 50 and post 2017 GHG standards, reducing gasoline sulfur to 10 ppm is needed for 

the advances in technology to achieve their intended effectiveness in reducing NMOG+NOx 
1-21 

emissions. The advances in vehicle technology and the reduction in gasoline sulfur clearly are 

both needed to achieve the emissions reductions called for by Tier 3. 

1.2.4.4.2 EPA Re-test of Umicore 2009 Chevrolet Malibu PZEV 

Ball et al. of Umicore Autocat USA, Inc. previously studied the impact of gasoline fuel 

sulfur levels of 3 ppm and 33 ppm on the emissions of a 2009 Chevrolet Malibu PZEV.59 In 

their supplemental comments to the Tier 3 proposal, API commented hat the composition of the 

two test fuels outside of sulfur content was not held constant and thus the exhaust emissions 

differences attributed to the difference in gasoline sulfur levels may have been due to other fuel 

property differences.60

 For example, the 3 ppm fuel used by Ball et al. was nonoxygenated EEE 

Clear test fuel (essentially, Tier 2 Federal certification gasoline except with near-zero sulfur) 

while the 33 ppm fuel was an oxygenated California Phase 2 LEV II certification fuel. Thus it 

was not entirely clear if the changes in NOx emissions observed between tests with the two fuels 

were significantly impacted by fuel composition variables other than gasoline sulfur content. 

EPA obtained the same test vehicle from Umicore for retesting at the EPA NVFEL facility using 

the 5 ppm and 28 ppm sulfur E0 test fuels and vehicle test procedures used in EPA gasoline 

sulfur effects testing on Tier 2 vehicles (see Section 1.2.4.2). 

In EPA’s retest of the 2009 Chevrolet Malibu PZEV, when sulfur was the only difference 

between the test fuels, the gasoline with higher sulfur resulted in significantly higher increases in 

NOx emissions with increasing fuel sulfur content than was observed in the previous testing by 

Ball et al. at Umicore. Assuming emissions impacts vs. gasoline sulfur content are 

approximately linear, the original data from Ball et al. result in a predicted increase in NOx 

emissions of approximately 40% when increasing gasoline sulfur from 10 ppm to 30 ppm. The 

EPA re-testing of the same vehicle that controlled for other fuel composition differences result in 

a predicted increase in NOx emissions of 93% when increasing gasoline sulfur from 10 ppm to 

30 ppm, with NOx emissions approximately doubling from 22 g/mi to 43 g/mi, with no 

statistically significant difference in NMOG emissions and with an increase in NMOG+NOx 

emissions of 56%. The approximate doubling in NOx emissions with the Malibu PZEV between 

10 ppm and 30 ppm sulfur was nearly identical to the results found during testing of the Tier 3 

Bin 50 developmental Ford Explorer discussed above. The results confirm that fuel 

compositional differences other than sulfur may have impacted exhaust emissions results in the 

Ball et al. study by masking a substantial portion of the effect of increased fuel sulfur on NOx 

emissions. When controlling for other fuel composition differences, the resultant increase in 

NOx exhaust emissions due to increasing gasoline sulfur was more than double that of the 

original Ball et al. study. The observed increase in NMOG+NOx emissions during EPA testing 

of the Malibu PZEV was also comparable to results found with the developmental Tier 3 Bin 50 

Ford Explorer. There was also a much higher increase in NOx and NMOG+NOx emissions for 

both the Malibu PZEV and the Tier 3 Bin 50 Explorer with increased gasoline sulfur than was 

observed with Tier 2 vehicles in the EPA Tier 2 in-use study.61 

1.2.4.4.3 EPA Prototype Tier 3 Heavy-light-duty Truck Test Program 

EPA purchased a 2011 Chevrolet Silverado heavy-light-duty (LDT4) pickup truck with a 

developmental goal of modifying the truck to achieve exhaust emissions consistent with 

compliance with the Tier 3 Bin 30 emissions standards. The truck was equipped with a 5.3L V8 
1-22 

with General Motors’ “Active Fuel Management” cylinder deactivation system. This particular 

truck was chosen in part because cylinder deactivation is a key technology for light-truck 

compliance with future GHG standards and in part because it achieved very low emissions in its 

OEM, Tier 2-compliant configuration (certified to Tier 2 Bin 4). A prototype exhaust system 

was obtained from MECA consisting of high-cell-density (900 cpsi) thin-wall (2.5 mil), highPGM, close-coupled Pd-Rh catalysts with an additional under-body Pd-Rh catalyst. The total 

catalyst volume was approximately 116 in3 with a specific PGM loading of 125 g/ft3

and 

approximate loading ratio of 0:80:5 (Pt:Pd:Rh). Third-party (non-OEM) EMS calibration tools 

were used to modify the powertrain calibration in an effort to improve catalyst light-off 

performance. The final test configuration used approximately 4 degrees of timing retard and 

approximately 200 rpm higher idle speed relative to the OEM configuration during and 

immediately following cold-start. The exhaust catalyst system and HEGO sensors were bench 

aged to an equivalent 150,000 miles using standard EPA accelerated catalyst bench-aging 

procedures.62 The truck was tested on California LEV III E10 certification fuel at 9 and 29 ppm 

gasoline sulfur levels. 

The EPA Tier 3 prototype Silverado achieved NMOG+NOx emissions of 18 mg/mi on 

the 9 ppm S fuel. The NMOG+NOx emissions were approximately 60% of the Bin 30 standard 

and thus are consistent with meeting the Tier 3 Bin 30 exhaust emissions standard with a 

moderate compliance margin. NMOG+NOx emissions increased to 29 mg/mi on the 29 ppm S 

fuel and one out of four tests exceeded the Bin 30 exhaust emissions standards. NMOG+NOx 

emissions would be at 19 mg/mi and 30 mg/mi with 10 ppm and 30 ppm gasoline sulfur, 

respectively, assuming a linear effect of sulfur on emissions performance. This represents an 

increase in NMOG+NOx emissions of approximately 55%, comparable to increases observed 

with both the EPA-tested Chevrolet Malibu PZEV and the developmental Tier 3 Bin 50 Ford 

Explorer. The impact of increased gasoline sulfur on NMOG+NOx emissions was due to 

comparable increases (on a percentage basis) in both NMOG and NOx emissions. This effect of 

gasoline sulfur on the Prototype Silverado truck’s emissions differed from the sulfur impacts 

observed on the developmental Ford Explorer, which primarily affected NOx emissions, and the 

Malibu PZEV, where the impact was entirely on NOx emissions. 

1.2.4.5 Gasoline Sulfur Level Necessary for New Light-duty Vehicles to Achieve Tier 3 

Exhaust Emissions Standards 

Meeting Tier 3 NMOG+NOx standards will require major reductions in exhaust 

emissions across the entire fleet of new light-duty vehicles. As discussed in previous sections, 

the Tier 3 program will require reductions in fleet average NMOG+NOx emissions of over 80 

percent for the entire fleet of light-duty vehicles and light-duty trucks. This significant level of 

fleet average emission reduction will require reductions from all parts of the fleet, including 

vehicles models with exhaust emissions currently at or near the level of the fully phased-in Tier 3 

FTP NMOG+NOx fleet average standard of 30 mg/mi. 

Compliance with the more stringent Tier 3 fleet average standards will require vehicle 

manufacturers to certify a significant amount of vehicles to bin standards that are below the Bin 

30 fleet average standard to offset other vehicles that are certified to bin standards that remain 

somewhat above the Bin 30 fleet average even after significantly reducing their emissions. At 

the same time, the stringency of the Tier 3 standards will push almost all vehicle models to be 
1-23 

close to or below the Bin 30 fleet average standard. There are only 2 compliance bins below Bin 

30, i.e., Bin 20 and Bin 0, available to offset emissions of vehicles certifying above Bin 30. 

There is also very limited ability for vehicle manufacturers to certify vehicles below the stringent 

Tier 3 fleet average exhaust emissions standard since Bin 20 and Bin 30 standards for individual 

vehicle certification families are approaching the engineering limits of what can be achieved for 

vehicles using an internal combustion engine and Bin 0 can only be achieved by electric-only 

vehicle operation. The result is that there is a very limited ability to offset sales of vehicles 

certified above the 30 mg/mi fleet average emission standard. This means in general that vehicle 

models currently with higher emissions will have to achieve significant emissions reductions to 

minimize the gap, if any, between their certified bin levels under Tier 3 and the Tier 3 Bin 30 

fleet average standard, and vehicle models currently at or below Bin 30 will also have to achieve 

further emissions reductions under Tier 3 to offset the vehicles that remain certified to bin 

standards somewhat above Bin 30 . The end result is a need for major reductions from all types 

of vehicles in the light-duty fleet, including those above as well as most vehicles that are already 

near, at, or below the Tier 3 Bin 30 fleet average standard. 

Achieving exhaust emissions reductions of over 80% for the fleet, with major reductions 

across all types of light-duty vehicles and light-duty trucks, will be a major technological 

challenge. Vehicles already have made significant advances in controlling cold start emissions 

and maximizing exhaust catalyst efficiency (e.g., improving warm-up and catalyst light-off after 

cold starts and maintaining very high catalyst efficiency once warmed up) in order to meet Tier 2 

and LEV II emissions standards. There are no “low-hanging fruit” remaining for additional 

NMOG+NOx reductions from light-duty vehicles from a technology perspective, meaning that 

vehicle manufacturers cannot merely change one aspect of emissions control and thereby achieve 

all of the required reductions. Instead, compliance with light-duty Tier 3 exhaust emissions 

standards will require significant improvements in all areas of emissions control – with further 

improvements in fuel-system management and mixture preparation during cold start, 

improvements in achieving catalyst light-off immediately after cold start, and improved catalyst 

efficiency during stabilized, fully-warmed-up conditions. Manufacturers will need further 

improvements in each of these areas with nearly every vehicle in order to comply with the fleetaverage Tier 3 standards. 

From a technology perspective, the most likely control strategies will involve using 

exhaust catalyst technologies and powertrain calibration primarily focused on reducing cold-start 

emissions of NMOG, and on reducing both cold-start and warmed-up (running) emissions of 

NOX. An important part of this strategy, particularly for larger vehicles having greater difficulty 

achieving cold-start NMOG emissions control, will be to reduce NOX emissions to near-zero 

levels. This will involve controlling engine-out NOx emissions during cold start, shortening the 

cold start period prior to catalyst light-off of NOx reduction reactions, and better controlling 

NOx emissions once the catalyst is fully warmed up. This is needed to allow a sufficient NMOG 

compliance margin so that vehicles can meet the combined NMOG+NOX emissions standards 

for their full useful life. 

While significant NMOG+NOx emissions reductions can be achieved from better control 

of cold start NMOG emissions, there are practical engineering limits to NMOG control for larger 

displacement vehicles (e.g., large light-duty trucks with significant payload and etrailer towing 

capabilities). This is based in part on the impact on NMOG emissions of the larger engine 
1-24 

surface-to-volume ratio and resultant heat conduction from the combustion chamber during 

warm-up. There are also tradeoffs between some cold-start NMOG controls and cold-start NOx 

control. For example, secondary air injection and/or leaner fueling strategies improve catalyst 

light-off for NMOG after a cold-start but also place OSC components in an oxidation state that 

limits potential for NOx reduction and thus often result in higher cold-start NOx emissions. 

Some applications achieve lower NMOG+NOx emissions without the use of secondary air 

injection by careful calibration, changes to the catalyst formulation and balancing of catalyst HC 

and NOx activity. The EPA Prototype Silverado and the developmental Ford Explorer are 

specific examples of this approach. 

Because of engineering limitations with large vehicles, heavy-light-trucks and other 

vehicles with significant utility, we expect many applications will need close to 100% efficiency 

in NOx control under fully warmed-up conditions and very fast light-off of NOx reduction 

reactions over the exhaust catalyst almost immediately after cold-start for those applications. 

This will require significant improvements in catalytic and engine-out NOx reduction compared 

with Tier 2 vehicles and will be especially important for heavier vehicles due to the challenges of 

achieving low NMOG. 

These technology improvements - improving warm-up and catalyst light-off after cold 

starts and maintaining very high catalyst efficiency - - once warmed up – all rely on 10 ppm 

average sulfur fuel to achieve the very significant emissions reductions required for the fleet to 

achieve the Tier 3 Bin 30 fleet average emissions standard. The evidence from the test results 

and specific vehicle examples discussed above clearly indicate that leaving the gasoline sulfur 

level at 30 ppm would largely negate the benefits of key technology improvements expected to 

be used for compliance with Tier 3 exhaust emissions standards. Without the lower 10 ppm 

gasoline sulfur content, the Tier 3 exhaust fleet average emissions standards would not be 

achievable across the broad range of vehicles that must achieve significant exhaust emissions 

reductions. 

One aspect of the need for sulfur levels of 10 ppm average stems from the fact that 

achieving the Tier 3 emission standards will require very careful control of the exhaust chemistry 

and exhaust temperatures to ensure high catalyst efficiency. The impact of sulfur on OSC 

components in the catalyst makes this a challenge even at relatively low (10 ppm) gasoline sulfur 

levels. NOX conversion by exhaust catalysts is strongly influenced by the OSC components like 

ceria. Ceria sulfation may play an important role in the large degradation of NOX emission 

control with increased fuel sulfur levels observed in the MSAT, Umicore and EPA Tier 2 In-Use 

Gasoline Sulfur Effects studies and the much more severe NOx emissions degradation observed 

in recent test data from PZEV and prototype/developmental Tier 3/LEV III vehicles. 63

The importance of lower sulfur gasoline is also demonstrated by the fact that vehicles 

certified to California SULEV are typically certified to higher bins for the federal Tier 2 

program. Light-duty vehicles certified to CARB SULEV and federal Tier 2 Bin 2 exhaust 

emission standards accounted for approximately 3.1 percent and 0.4 percent, respectively, of 

vehicle sales for MY2009. Light-duty vehicles certified to SULEV under LEV II are more 

typically certified federally to Tier 2 Bin 3, Bin 4 or Bin 5, and vehicles certified to SULEV and 

Tier 2 Bins 3-5 comprised approximately 2.5 percent of sales for MY2009. In particular, 

nonhybrid vehicles certified in California as SULEV are not certified to federal Tier 2 Bin 2 
1-25 

emissions standards even though the numeric limits for NOX and NMOG are shared between the 

California LEV II and federal Tier 2 programs for SULEV and Bin 2. Confidential business 

information shared by the auto companies indicate that the primary reason is an inability to 

demonstrate compliance with SULEV/Bin 2 emission standards after vehicles have operated inuse on gasoline with greater than 10 ppm sulfur and with exposure to the higher sulfur gasoline 

sold nationwide. While vehicles certified to the LEV II SULEV and Tier 2 Bin 2 standards both 

demonstrate compliance using certification gasoline with 15-40 ppm sulfur content, in-use 

compliance of SULEV vehicles in California occurs after significant, sustained operation on 

gasoline with an average of 10 ppm sulfur and a maximum cap of 30 ppm sulfur while federally 

certified vehicles under the Tier 2 program operate on gasoline with an average of 30 ppm sulfur 

and a maximum cap of 80 ppm sulfur. Although the SULEV and Tier 2 Bin 2 standards are 

numerically equivalent, the increased sulfur exposure of in-use vehicles certified under the 

federal Tier 2 program results in a need for a higher emissions compliance margin to take into 

account the impact of in-use gasoline sulfur on full useful life vehicle emissions. As a result, 

vehicles certified to California SULEV typically certify to emissions standards under the federal 

Tier 2 program that are 1-2 certification bins higher (e.g., SULEV certified federally as Tier 2 

Bin 3 or Bin 4) in order to ensure in-use compliance with emissions standards out to the full 

useful life of the vehicle when operating on higher-sulfur gasoline. 

There are currently no LDTs larger than LDT2 with the exception of a single hybrid 

electric SUV certified to Tier 2 Bin 2 or SULEV emissions standards. We expect that additional 

catalyst technologies, for example increasing catalyst surface area (volume or substrate cell 

density) and/or increased PGM loading, will need to be applied to larger vehicles in order to 

achieve the catalyst efficiencies necessary to comply with the Tier 3 standards, and any sulfur 

impact on catalyst efficiency will have a larger impact on vehicles and trucks that rely more on 

very high catalyst efficiencies in order to achieve very low emissions. The vehicle emissions data 

referenced in Section 1.2.4.4 represents the only known data on non-hybrid vehicles spanning a 

range from mid-size LDVs to heavy-light-trucks at the very low criteria pollutant emissions 

levels that will be needed to comply with the Tier 3 exhaust emissions standards. The 

developmental Ford Explorer, Chevrolet Malibu PZEV and EPA prototype Chevrolet Silverado 

vehicles described in Section 1.2.4.3 also represent a range of different technology approaches to 

both criteria pollution control and GHG reduction (e.g., use of secondary air vs. emphasizing 

cold-start NOx control, use of engine downsizing via turbocharging vs. cylinder deactivation for 

GHG control, etc.) and represent a broad range of vehicle applications and utility (mid-size 

LDV, LDT3, LDT4). All of the vehicles with Tier 3/LEV III technology demonstrated greater 

than 50% increases in NMOG+NOx emissions when increasing gasoline sulfur from 10 ppm to 

30 ppm. Two of the vehicles showed a doubling of NOx emissions when increasing gasoline 

sulfur from 10 ppm to 30 ppm. Both of the heavy-light-duty trucks with specific engineering 

targets of meeting Tier 3 emissions were capable of meeting their targeted emission standards 

with a sufficient compliance margin on 10 ppm sulfur gasoline and could not meet their targeted 

emissions standards or could not achieve a reasonable compliance margin when tested with 30 

ppm sulfur gasoline. 

The negative impact of gasoline sulfur on catalytic activity and the resultant loss of 

exhaust catalyst effectiveness to chemically reduce NOX and oxidize NMOG occur across all 

vehicle categories. However, the impact of gasoline sulfur on the effectiveness of exhaust 
1-26 

catalysts to control NOX emissions in the fully-warmed-up condition is particularly of concern 

for larger vehicles (the largest LDVs and LDT3s, LDT4s, and MDPVs). Manufacturers face the 

most significant challenges in reducing cold-start NMOG emissions for these vehicles. Because 

of the need to reach near-zero NOX emissions levels in order to offset engineering limitations on 

further NMOG exhaust emissions control with these vehicles, any significant degradation in 

NOX emissions control over the useful life of the vehicle would likely prevent some if not most 

larger vehicles from reaching a combined NMOG+NOX low enough to comply with the 30 

mg/mi fleet-average standard. Any degradation in catalyst performance due to gasoline sulfur 

would reduce or eliminate the margin necessary to ensure in-use compliance with the Tier 3 

emissions standards. Certifying to a useful life of 150,000 miles versus the current 120,000 

miles will further add to manufacturers’ compliance challenge for Tier 3 large light trucks (See 

Section IV.7.b of the preamble for more on the useful life requirements.) These vehicles 

represent a sufficiently large segment of light-duty vehicle sales now and for the foreseeable 

future such that their emissions could not be sufficiently offset (and thus the fleet-average 

standard could not be achieved) by certifying other vehicles to bins below the fleet average 

standard. 

As discussed above, achieving Tier 3 levels as an average across the light-duty fleet will 

require fleet wide reductions of approximately 80%. This will require significant reductions 

from all light duty vehicles, with the result that some models and types of vehicles will be at 

most somewhat above the Tier 3 level, and all other models will be at or somewhat below Tier 3 

levels. Achieving these reductions presents a major technology challenge. The required 

reductions are of a magnitude that EPA expects manufacturers to employ advances in technology 

in all of the relevant areas of emissions control – reducing engine-out emissions, reducing the 

time to catalyst lightoff, improving exhaust catalyst durability at 120,000 or 150,000 miles and 

improving efficiency of fully warmed up exhaust catalysts. All of these areas of emissions 

control need to be improved, and gasoline sulfur reduction to a 10 ppm average is a critical part 

of achieving Tier 3 levels through these emissions control technology improvements. 

The use of 10 ppm average sulfur fuel is an essential part of achieving Tier 3 levels while 

applying an array of advancements in emissions control technology to the light-duty fleet. The 

testing of Tier 2 and Tier 3 type technology vehicles, as well as other information, shows that 

sulfur has a very large impact on the effectiveness of the control technologies expected to be 

used in Tier 3 vehicles. Without the reduction in sulfur to a 10 ppm average, the major 

technology improvements projected under Tier 3 would only result in a limited portion of the 

emissions reductions needed to achieve Tier 3 levels. For example, without the reduction in 

sulfur from a 30 ppm to 10 ppm average, the technology improvements would not come close to 

achieving Tier 3 levels, and in some cases might have no more effectiveness than current Tier 2 

technology and achieve only approximately Tier 2 levels of exhaust emissions control. 

Achieving Tier 3 levels without a reduction in sulfur to 10 ppm levels would only be 

possible if there were technology improvements significantly above and beyond those discussed 

above. Theoretically, without reducing sulfur levels to 10 ppm average, emissions control 

technology improvements would need to provide upwards of twice as much, and in some cases 

significantly more than twice as much, emissions control effectiveness as the Tier 3 technology 

improvements discussed above in Section 1.2.4.4. EPA has not identified technology 

improvements that could provide such a large additional increase in emissions control 
1-27 

effectiveness, across the light-duty fleet, above and beyond that provided by the major 

improvements in technology discussed above, without any additional gasoline reductions in 

gasoline sulfur content. The impact of sulfur reduction on the effectiveness of the available 

technology improvements plays such a large role in achieving the Tier 3 levels that there would 

be no reasonable basis to expect that technology would be available, at the 30 ppm sulfur level, 

to fill the emission control gap left from no sulfur reduction, and achieve the very significant 

fleetwide reductions needed to meet the Tier 3 fleet average standards. In effect reducing sulfur 

from 30 ppm to 10 ppm has such a large impact on the ability of the technology improvements to 

achieve Tier 3 emissions levels that absent these sulfur reductions there is not a suite of 

technology advancements available to fill the resulting gap in emissions reductions. Technology 

would not be available that would achieve the Tier 3 Bin 30 average standard, across the fleet, 

with sulfur at 30 ppm levels, and as a result Tier 3 levels would not be technically feasible and 

achievable. 

This analysis also applies to gasoline sulfur levels between 10 and 30 ppm, e.g. 20 ppm. 

The Tier 3 required emissions reductions are so large and widespread across the fleet, and the 

technology challenges are sufficiently high, especially for heavier vehicles, that the large 

increase in emissions that would occur from a higher average sulfur level compared to a 10 ppm 

average would lead to an inability for vehicle technologies to widely achieve Tier 3 levels as a 

fleet wide average in order to meet the Tier 3 Bin 30 fleet average standard. 

EPA acknowledges that some models in the light-duty fleet, when viewed in isolation, 

may be able to achieve Tier 3 levels at current sulfur levels of 30 ppm average. Under the Tier 3 

fleet average standards, it is not sufficient for one or a few of a manufacturer’s vehicle models to 

meet Tier 3 levels because the manufacturer’s light-duty vehicle fleet as a whole must achieve 

the Tier 3 30 mg/mi exhaust emissions standard as a fleet-wide average. As discussed above, all 

vehicle models will need to achieve further reductions and be either below or no more than 

somewhat above Tier 3 levels to achieve the Tier 3 standard as a fleet wide average. Absent the 

reductions in sulfur levels to 10 ppm average, this is not achievable from a technology 

perspective. 

 As discussed in Section V.A.2 of the preamble, the 10 ppm standard for sulfur in 

gasoline represents the lowest practical limit from a standpoint of fuel production, handling and 

transport. While lowering gasoline sulfur to average levels below 10 ppm would further help 

ensure in-use vehicle compliance with the Tier 3 standards, the Agency believes that a gasoline 

sulfur standard of 10 ppm, combined with the advances in emissions control technology 

discussed above, will enable vehicle manufacturers to achieve compliance with a national fleet 

average standard of 30 mg/mi NMOG+NOX. Not only will a 10 ppm sulfur standard enable 

vehicle manufacturers to certify their entire product line of vehicles to the Tier 3 fleet average 

standards, but based on the results of testing both Tier 2 vehicles and SULEV vehicles as 

discussed above, reducing gasoline sulfur to a 10 ppm average should enable these vehicles to 

maintain their emission performance in-use over their full useful life. 
1-28 

1.3 SFTP NMOG+NOX Feasibility 

The new Tier 3 emission requirements include stringent NMOG+ NOX composite 

standards over the SFTP that will generally only require additional focus on fuel control of the 

engines and diligent implementation of new technologies like gasoline direct injection (GDI) and 

turbocharged engines. Additionally, the fleet-average nature of the standards will allow more 

challenged vehicles to be offset by vehicles that could outperform the required fleet averages. 

In order to assess the technical feasibility of a 50 mg/mi NMOG+NOX national fleet 

average SFTP composite standard EPA conducted an analysis of data from the in-use 

verification program (IUVP). The IUVP vehicles are tested by manufacturers at various ages and 

mileages and the results are reported to EPA. The analysis was performed on Tier 2 and LEV II 

vehicles. This provided a baseline for the current federal fleet emissions performance, as well as 

the emissions performance of the California LEV II fleet. 

1.3.1 Assessment of the Current Federal Fleet Emissions 

To investigate feasibility, we acquired and analyzed IUVP certification results for model 

years 2010 and 2011 which represent the most recent model years of which complete IUVP data 

sets are currently available. These data included FTP composites, as well as results for the US06, 

and SC03 cycles. We focused on results for hydrocarbons (HC) and NOX. For the FTP results 

HC represents non-methane organic gases (NMOG). The US06 and SC03 results represent 

NMHC+NOX. 

As a first step, we averaged the results by model year and test group (engine family). 

After compiling results on all three cycles for each test group, we calculated SFTP composite 

estimates for each engine family as 

.0SFTP 35 FTP( NOx NMOG .0)FTP 28 US06 .0 37 SC03

As a second step, we then averaged the SFTP composite results by standard level and 

vehicle class, focusing on results in Bins 2, 3 and 5, as well as vehicles certified to LEV-II LEV 

and SULEV standards. In averaging, we treated Bin 2 and LEV-II/SULEV standards as 

equivalent, and accordingly, pooled their results. Table 1-7 shows the numbers of test groups in 

each combination of standard level and vehicle class. 

Table 1-7 Numbers of Test Groups Certified to Selected Tier-2 and LEV-II Standards in 

Model Years 2010 and 2011

Standard Level Vehicle Class

LDV-LDT1 LDT2 LDT3 LDT4

Bin 2 + LEV-II/SULEV 88 3 1

Bin 3 26 1

Bin 5 331 37 13 14

LEV-II/LEV 124 17 4 4
1-29 

Figure 1-3 shows results for Bin-5 and LEV-II/LEV vehicles. It is clear that vehicles in 

all four vehicle classes, from LDV to LDT4, are certified to these standards. The means show a 

modest, but not striking increase with vehicle class, from approximately 30 mg/mi for LDV to 

approximately 50 mg/mi for LDT4. However, an equivalent trend among the maxima is not 

evident. The results also show that assuming equivalence between these two standards is 

reasonable. On average it is clear that test groups certified at the Bin-5 level are capable of 

meeting the target level of 50 mg/mi, although with small compliance margins. However, 

relatively small numbers of families exceed this level, ranging to over 100 mg/mi. 

Additionally, Figure 1-4 shows results for test groups certified to Bin-2 and Bin-3 

standards. For these test groups, a trend with vehicle class is not evident, although very small 

numbers of test groups are certified as trucks. In contrast to the Bin-5 vehicles, most families 

certified at the Bin-2 and Bin-3 levels are well below the 50-mg/mi level, and maxima are no 

higher than 7 percent below this level. 

Figure 1-3: Mean and Maximum Composite SFTP Results for HC+NOX for Test Groups 

certified to Bin-5 and LEV-II/LEV Standards (bars and error-bars represent means and 

maxima for sets of test groups, respectively) 
1-30 

Figure 1-4: Mean and Maximum Composite SFTP Results for HC+NOX for Test Groups 

certified to Bin-2 and Bin-3 Standards (bars and error-bars represent means and maxima 

for sets of test groups, respectively) 

1.4 Technology Description for NMOG+NOX Control 

A range of technology options exist to reduce NMOG and NOX emissions from both 

gasoline fueled spark ignition and diesel engines below the current Tier 2 standards. Available 

options include modifications to the engine calibration, engine design, exhaust system, and after 

treatment systems. The different available options have specific benefits and limitations. This 

section describes the technical challenges to reducing emissions from current levels, describes 

available technologies for reducing emissions, estimates the potential emissions reduction of the 

different technologies, describes if there are other ancillary benefits to engine and vehicle 

performance with the technology, and reviews the limits of each technology. Except where 

noted, these technologies are applicable to all gasoline vehicles covered by this rule. Unique 

diesel technologies are addressed in Section 1.4.2. 

1.4.1 Summary of the Technical Challenge for NMOG+NOX control 

The Tier 3 emission standards will require vehicle manufacturers to reduce the level of 

both NMOG and NOX emissions from the existing Tier 2 fleet by approximately 80 percent over 

the FTP by 2025. The FTP measures emissions during cold start, hot start, and warmed-up 

vehicle city driving. The majority of NMOG and NOX emissions from gasoline fueled vehicles 

measured during the FTP test historically occur during the cold start phase however emissions 

during warmed-up and hot operation cannot be ignored and must be limited in order to meet Tier 

3 standards. Figure 1-1, above, graphically demonstrates when NMOG and NOX emissions are 

produced during a cold start. As shown in the figure, approximately 90 percent of the NMOG 

emissions occur during the first 50 seconds after the cold start. In addition, about 60 percent of 

the NOX emissions occur during this same 50 second period. Unlike NMOG which is mostly 

controlled after the first 50 seconds, NOX emissions tend to be released throughout the remainder 

of the FTP test and are particularly sensitive to fuel sulfur content. Achieving the Tier 3 
1-31 

NMOG+NOX FTP emissions standard may require manufacturers to reduce both cold start 

NMOG and NOX emissions and further reduce NOX emissions when the vehicle is warmed up. 

The Tier 3 emission standards will also require manufacturers to maintain their current 

vehicle high load NMOG+NOX emission performance as measured during the US06 operation of 

the Supplemental Federal Test Procedure (SFTP). The US06 component of the SFTP is 

designed to simulate higher speeds and acceleration rates during warmed up vehicle operation. 

Significant quantities of NMOG and NOX emissions are produced during the US06 portion of the 

SFTP if enrichment events occur to reduce exhaust temperatures during high-load operation. 

Most vehicles are now avoiding these enrichment events during the US06 and achieve relatively 

low NMOG+NOX emissions. 

It is anticipated that manufacturers will change the design of their exhaust and catalyst 

systems to reduce catalyst light-off times and reduce warmed-up and hot running emissions, 

particularly NOX to almost zero, in order to achieve the Tier 3 30 mg/mi FTP NMOG+NOX

standard. Design changes to reduce catalyst light-off time can also result in higher catalyst 

temperatures during high-load operation as seen during the US06 test. To achieve the 

NMOG+NOX Tier 3 SFTP standard manufacturers will need to develop and implement 

technologies to manage catalyst temperatures during high-load operation without using fuel 

enrichment. 

In addition, it is anticipated that the technologies manufacturers will use for reducing 

warmed up NOX emissions during the FTP will also reduce NOX emissions during warmed up 

operation on the US06. 

For the catalyst to effectively reduce NMOG+NOX emissions it must reach the light-off 

temperature of approximately 250 °C. Emissions during the catalyst warm up period can be 

reduced by reducing the emissions produced by the engine during the catalyst warm up phase. 

Emissions can also be reduced by shortening the time period required for the catalyst to reach the 

light-off temperature. Reducing warmed-up NOX emissions requires improving the efficiency of 

the catalyst system which will generally require little to no presence of sulfur contaminants in the 

fuel.

To achieve the Tier 3 NMOG+NOX FTP emissions standards it is anticipated that vehicle 

manufacturers will focus on three areas to reduce emissions: 

• minimizing the emissions produced by the engine before the catalyst reaches the 

light-off temperature; 

• reducing the time required for the catalyst to reach the light-off temperature; and, 

• improving the NOX efficiency of the catalyst during warmed-up operation. 

It is anticipated that improvements in all three areas will be required particularly for 

heavier passenger cars, light-duty trucks in classes LDT3 and LDT4, and MDPVs. The NOX

efficiency during warmed-up operation of vehicles certified to the Tier 2 Bin 4 emission level 

and operating on low sulfur fuel (i.e. 10 ppm or lower) are such that it is anticipated that 
1-32 

reductions in cold start emissions are primarily what will be required to achieve the Tier 3 

NMOG+NOX standard. 

Heavy-duty trucks (8,501 up to 14,000 lbs) will have a similar challenge to meet their 

Tier 3 standards along with the new SFTP requirements for this vehicle class. In addition to the 

new test requirements and tighter standards, these vehicles useful life is being extended from 

120,000 to 150,000 miles. Unlike lighter weight vehicles, heavy-duty trucks tend to operate at 

higher loads for greater periods of time and therefore have different constraints to meet the new 

requirements and more stringent standards. 

For spark-ignition engines, the higher operating load of these vehicles limits the ability to 

move the catalyst close to the cylinder head due to durability concerns from higher thermal 

loading. This limit will constrain the ability of these trucks to quickly light-off the catalyst, it 

will, however, allow them to stay out of fuel-enriched operation to maintain catalyst 

temperatures when the vehicle is being operated under high load. The emissions produced 

during fuel-enrichment events, which occur at high loads can be significantly greater than the 

reductions achievable during the cold start and idle phase. Fuel enrichment events cause criteria 

pollutant and CO2 emission rates to increase and also reduces the vehicle’s fuel economy. To 

achieve the NMOG+NOX FTP emissions standards while also meeting the new SFTP 

requirements it is anticipated that heavy-duty vehicle manufacturers will focus on four areas for 

spark ignition engines: 

reducing the emissions produced by the engine before the catalyst reaches lightoff temperature; 

reducing the time required for the catalyst to reach the light-off temperature; 

improving the NOX efficiency of the catalyst during warmed up operation; and, 

minimizing the time spent in fuel enrichment to reduce the operating temperature 

of the catalyst. 

Compression ignition or diesel engines also have limitations with thermal goals and 

location of the emission control system on the vehicle. With the similar goal of providing engine 

exhaust heat to the catalysts, SCR and DPF, these emission control systems may compete with 

each other for thermal energy. Additionally, the SCR system and the DPF generally require 

sufficient capacity or size to handle the emissions from the engine which may limit the ability to 

locate them in the optimal location. 

To meet Tier 3 NMOG+NOX FTP emissions standards while also meeting the new SFTP 

requirements it is anticipated that heavy-duty vehicle manufacturers will focus on three areas for 

compression ignition: 

reducing the emissions produced by the engine while the catalysts and SCR 

system are being brought to proper operating temperature; 
1-33 

reducing the time required for the catalysts and SCR system to reach the proper 

operating temperature; 

improving the NOX efficiency of the SCR during warmed up operation through 

refinement in engine out emission controls and SCR strategies. 

1.4.1.1 Reducing Engine Emissions Produced Before Catalyst Light-Off 

During the first 50 seconds of the cold start phase of the FTP the engine is operating 

either at idle or low speed and load in non-hybrid vehicles. The engine temperature is between 

20 and 30 °C (68 and 86 °F). At these temperatures and under these low loads the cold engine 

produces lower concentrations of NOX than NMOG. As the engine warms up and as the load 

increases the concentration of NOX produced by the engine increases and the concentration of 

NMOG decreases. 

The design of the air induction system, combustion chamber, spark plug, and fuel 

injection system determines the quantity of fuel required for stable combustion to occur in the 

cold engine. Optimizing the performance of these components can provide reductions in the 

amount of fuel required to produce stable combustion during these cold operating conditions. 

Reductions in the amount of fuel required leads to reductions in cold start NMOG emissions. 

The design considerations to minimize cold start emissions are also dependent on the fuel 

injection method. Port fuel injected (PFI) engines have different design constraints than gasoline 

direct injection (GDI) spark ignition engines. For both PFI and GDI engines, however, attention 

to the details affecting the in cylinder air/fuel mixture can reduce cold start NMOG emissions. 

It has been shown that cold start NMOG emissions in PFI engines can be reduced by 

reducing the size of the fuel spray droplets and optimizing the spray targeting. Fuel impinging 

on cold engine surfaces in the cylinder does not readily vaporize and does not combust. 

Improving injector targeting to reduce the amount of fuel reaching the cylinder walls reduces the 

amount of fuel needed to create a combustible air fuel mixture. Reducing the size of the spray 

droplets improves the vaporization of the fuel and creation of a combustible mixture. 64

Droplet size can be reduced by modifying the injector orifice plate and also by increasing 

the fuel pressure. Reducing droplet size and improving fuel vaporization during cold start has 

been shown to reduce cold transient emissions by up to 40 percent during the cold start phase of 

the FTP emission test.65 This and other PFI injector technology improvements have been used to 

optimize the cold start performance of today’s vehicles certified to the CA LEV II SULEV 

standards. 

The mixture formation process in a DISI engine is different than a PFI engine. In a PFI 

engine the fuel is injected during the intake stroke of the engine in the intake runner. The fuel 

has time to evaporate during the intake stroke as the fuel and air are drawn into the cylinder. In 

addition, as the engine warms up the fuel can be injected into the intake runner and engine heat 

can assist in evaporating the fuel prior to the intake valve opening. 
1-34 

The DISI engine injects fuel at higher fuel pressures than PFI engines directly into the 

combustion chamber. In a DISI engine the fuel droplets need to evaporate and mix with the air 

in the cylinder in order to form a flammable mixture. 

Injecting directly into the cylinder reduces the time available for the fuel to evaporate and 

mix with the intake air in a DISI engine compared to a PFI engine. An advantage of the DISI 

design is that the fuel spray does not impinge on the walls of the intake manifold or other 

surfaces in the cylinder. 

DISI systems have the ability to split the injection timing event. At least one study has 

indicated that significant reductions in hydrocarbon emissions can be achieved by splitting the 

injections during the cold start of a DISI engine. An initial injection occurs during the intake 

stroke and a second injection is timed to occur during the compression stroke. This injection 

method reduced unburned hydrocarbon emissions 30 percent compared to a compression stroke 

only injection method.66 

These are two examples of specific engine design characteristics, fuel injector design and 

fuel system pressure on PFI engines and injection timing on GDI engines which can be used to 

reduce cold start NMOG emissions significantly during the engine warm up prior to the catalyst 

reaching the light-off temperature. 

Optimizing the fuel injection system design and calibration is anticipated to be used in all 

vehicle classes, including heavy-duty vehicles. It is anticipated that these described 

improvements, along with improvements to other engine design characteristics, will be used to 

reduce cold start emissions for passenger cars, LDTs, MDPVs, and HDTs. 

Because the engine is relatively cold and the operating loads are low during the first 50 

seconds of the FTP the engines typically do not produce significant quantities of NOX emissions 

during this phase. In addition manufacturers tend to retard the combustion timing during the 

catalyst warm up phase. Retarding combustion timing has been shown also to reduce the 

concentration of NMOG in the exhaust. This calibration method further reduces peak 

combustion temperatures while increasing the exhaust gas temperature compared to optimized 

combustion timing. The increased exhaust gas temperature leads to improved heating of the 

catalyst and reduced catalyst light-off times. Retarding combustion and other technologies for 

reducing catalyst light-off time are discussed in the following section. 

1.4.1.2 Reducing Catalyst Light-Off Time 

The effectiveness of current vehicle emissions control systems depends in large part on 

the time it takes for the catalyst to light-off, which is typically defined as the catalyst reaching a 

temperature of 250oC. In order to reduce catalyst light-off time, it is expected manufacturers will 

use technologies that will improve heat transfer to the catalyst during the cold start phase and 

improve catalyst efficiency at lower temperatures. Technologies to reduce catalyst light-off time 

include calibration changes, thermal management, close-coupled catalysts, catalyst PGM 

loading, and secondary air injection. It is anticipated that in some cases where the catalyst lightoff time and efficiency are not sufficient to reduce cold start NMOG emissions, hydrocarbon 

adsorbers may be utilized. The adsorbers trap hydrocarbons until such time that the catalyst is 
1-35 

fully warmed up and the emissions can be oxidized by the catalyst. Note that with the exception 

of hydrocarbon adsorbers each of these technologies addresses NMOG and NOX performance. 

The technologies are described in greater detail below. 

1.4.1.2.1 Calibration Changes to Reduce Catalyst Light-Off Time 

These include calibration changes to increase the temperature and mass flow of the 

exhaust prior to the catalyst reaching the light-off temperature. By reducing the time required for 

the catalyst to light-off engine calibration changes can affect NMOG and NOX emissions. 

Retarding combustion in a cold engine by retarding the spark advance is a well known 

method for reducing the concentration of NMOG emissions in the exhaust and increasing the 

exhaust gas temperature.67,68

 The reduction in NMOG concentrations is due to a large fraction of 

the unburned fuel within the cylinder combusting before the flame is extinguished on the 

cylinder wall. Reductions of total hydrocarbon mass of up to 40 percent have been reported 

from studies evaluating the effect of spark retard on exhaust emissions. 

In addition to reducing the NMOG exhaust concentrations retarding the spark advance 

reduces the torque produced by the engine. In order to produce the same torque and maintain the 

engine speed and load at the desired level when retarding the spark advance, the air flow into the 

engine is increased causing the manifold pressure to increase which can also improve 

combustion stability. Retarding the combustion process also results in an increase in the exhaust 

gas temperature. The retarded ignition timing during the cold start phase in addition to reducing 

the NMOG emissions increases the exhaust mass flow and exhaust temperature. These changes 

lead to a reduction in the time required to heat the catalyst. 

The torque produced by the engine will begin to vary as the spark retard amount reaches 

engine combustion limits. As the torque variations increase, the combustion process is 

deteriorating and the engine performance begins to degrade due to the partial burning. It is the 

level of this variability which defines the absolute maximum reduction in spark advance that can 

be utilized to reduce NMOG emissions and reduce the catalyst light-off time. 

Retarding combustion during cold start can be applied to spark-ignition engines in all 

vehicle classes. The exhaust temperatures and NMOG emission reductions will vary based on 

engine design. This calibration methodology is anticipated to be used to improve catalyst warmup times and reduce cold start NMOG emissions for all vehicle classes, passenger cars, LDTs, 

MDPVs, and HDTs. 

With the penetration of variable valve timing technology increasing in gasoline-fueled 

engines additional work is being performed to characterize the impact of valve timing on cold 

start emissions. The potential exists that calibration changes to the valve timing during the cold 

start phase will lead to additional reductions in cold start NMOG emissions. 69 

1.4.1.2.2 Exhaust System Thermal Management to Reduce Catalyst Light-Off Time 

This category of technologies includes all design attributes meant to conduct combustion 

heat into the catalyst with minimal cooling. This includes insulating the exhaust piping between 
1-36 

the engine and the catalyst, reducing the wetted area of the exhaust path, reducing the thermal 

mass of the exhaust system, and/or using close-coupled catalysts (i.e., the catalysts are packaged 

as close to the engine cylinder head as possible to mitigate the cooling effects of longer exhaust 

piping). By reducing the time required to light-off the catalyst, thermal management 

technologies reduce NMOG and NOX emissions. 

Moving the catalyst closer to the cylinder head is a means manufacturers have been using 

to reduce both thermal losses and the catalyst light-off time. Many vehicles today use closecoupled catalysts, a catalyst which is physically located as close as possible to the cylinder head. 

Moving the catalyst from an underbody location to within inches of the cylinder head reduces the 

light-off time significantly. 

Another means for reducing heat losses are to replace cast exhaust manifolds with thinwall stamped manifolds. Reducing the mass of the exhaust system reduces the heat losses of the 

system. In addition an insulating air gap can be added to the exhaust system which further 

reduces the heat losses from the exhaust system, insulating air gap manifolds are also known as 

dual-wall manifolds. 

With thin- and dual-wall exhaust manifolds, close-coupled catalyst housings can be 

welded to the manifold. This reduces the needed for manifold to catalyst flanges which further 

reduces the thermal inertia of the exhaust system. Close coupling of the catalyst and reducing 

the thermal mass of the exhaust system significantly reduces the light-off time of the catalyst 

compared to an underbody catalyst with flanges and pipes connected to a cast exhaust manifold. 

Using close-coupled catalysts reduces the heat losses between the cylinder head and 

catalyst. While reducing the time required to light-off the catalyst the close-coupled catalyst can 

be subject to higher temperatures than underbody catalysts during high load operating 

conditions. To ensure the catalyst does not degrade manufacturers currently use fuel enrichment 

to maintain the exhaust temperatures below the levels which would damage the catalyst. It is 

anticipated that to meet the Tier 3 SFTP standards, manufacturers will need to ensure that fuel 

enrichment is not required on the US06 portion of the FTP. Calibration measures, other than fuel 

enrichment, may be required to ensure the catalyst temperature does not exceed the maximum 

limits. 

Another technology beginning to be used for both reducing heat loss in the exhaust and 

limiting exhaust gas temperatures under high load conditions is integrating the exhaust manifold 

into the cylinder head. Honda utilized this technology on the Insight’s 1.0 L VTEC-E engine. 

The advantage of this technology is that it minimizes exhaust system heat loss during warm-up. 

In addition with the exhaust manifold integrated in the cylinder head the cooling system can be 

used to reduce the exhaust temperatures during high load operation. It is anticipated that 

manufacturers will further develop this technology as means to both quickly light-off the catalyst 

and reduce high-load exhaust temperatures. 

To achieve the Tier 3 NMOG and NOX emissions standards it is expected that 

manufacturers will optimize the thermal inertia of the exhaust system to minimize the time 

needed for the catalyst to achieve the light-off temperature. In addition, the manufacturers will 

need to ensure the high load performance does not cause thermal degradation of the catalyst 
1-37 

system. It is expected that methods and technologies will be developed to reduce the need to use 

fuel enrichment to reduce high load exhaust temperatures. 

Optimizing the catalyst location and reducing the thermal inertia of the exhaust system 

are design options manufacturers can apply to all vehicle classes (PCs, LDTs, MDPVs, and 

HDTs) for improving vehicle cold start emission performance. 

It is not anticipated HDTs with spark-ignition engines will utilize catalysts close-coupled 

to the exhaust manifold. The higher operating loads of these engines results in durability 

concerns due to high thermal loading. It is expected that manufacturers will work to optimize 

the thermal mass of the exhaust systems to reduce losses along with optimizing the underbody 

location of the catalyst. These changes are expected to improve the light-off time while not 

subjecting the catalysts to the higher thermal loadings from a close coupled location. 

1.4.1.2.3 Catalyst Design Changes 

A number of different catalyst design changes can be implemented to reduce the time for 

the catalyst to light-off. Changes include modifying the substrate design, replacing a large 

volume catalyst with a cascade of two or more catalysts, and optimizing the loading and 

composition of the platinum group metals (PGM). 

Progress continues to be made in the development of the catalyst substrates which 

provide the physical support for the catalyst components which typically include a high surface 

area alumina carrier, ceria used for storing oxygen, PGM catalysts, and other components. A 

key design parameter for substrates is the cell density. Today catalyst substrates can be 

fabricated with cell densities up to 900 and 1,200 cells per square inch (cpsi) with wall 

thicknesses approaching 0.05 mm. 

Increasing the surface area of the catalyst improves the performance of the catalyst. 

Higher substrate cell densities increases the surface area for a given catalyst volume. Higher 

surface areas improve the catalyst efficiency and durability reducing NMOG and NOX emissions. 

The limitation of the higher cell density substrates include increased exhaust system 

pressures at high load conditions. The cell density and substrate frontal area are significant 

factors that need to be considered to optimize the catalyst performance while limiting flow loss 

at high load operation. 

During the cold start phase of the FTP the engine speeds and load are low during the first 

50 seconds of the test. One method for reducing the catalyst light-off time is to replace a larger 

volume catalyst with two catalysts which total the same volume as the single catalyst. The 

reduced volume close-coupled catalyst reduces the heat needed for this front catalyst to reach the 

light-off temperature. The front catalyst of the two catalyst system will reach operating 

temperature before the larger volume single catalyst, reducing the light-off time of the system. 

All other parameters held constant, increasing the PGM loading of the catalyst also 

improves the efficiency of the catalyst. The ratio of PGM metals is important as platinum, 

palladium, and rhodium have different levels of effectiveness promoting oxidation and reduction 
1-38 

reactions. Therefore, as the loading levels and composition of the PGM changes the light-off 

performance for both NMOG and NOX need to be evaluated. Based on confidential 

conversations with manufacturers it appears that there is an upper limit to the PGM loading, 

beyond which further increases do not improve light-off or catalyst efficiency. 

To achieve the Tier 3 NMOG and NOX emission standards it is anticipated that 

manufacturers will make changes to catalyst substrates and PGM loadings. 70 To achieve the 

emission levels required to meet the Tier 3 NMOG+NOX standard of 30 mg/mi with a 

compliance margin will require very low sulfur levels in the fuel. As described in Section 

1.2.3.3 even low levels (greater than 10 ppm) of sulfur in gasoline inhibit the ability of PGM 

catalysts to achieve the low levels NOX emission levels of the Tier 3 standard. For the Tier 3 

FTP emission standards to be achieved and maintained, particularly in use, it is required that the 

sulfur content of the fuel be reduced to 10 ppm or lower. 

Manufacturers will optimize the design of their aftertreatment systems for their different 

vehicles. Primary considerations include cost, light-off performance, warmed-up conversion 

efficiency and the exhaust temperatures encountered by the vehicle during high load operation. 

Vehicles having low power to weight ratios will tend to have higher exhaust gas temperatures 

and exhaust gas flow which will result in a different design when compared to vehicles having 

higher power to weight ratios. 

Manufacturers and catalyst suppliers perform detailed studies evaluating the cost and 

emission performance of aftertreatment systems. It is anticipated that manufacturers will 

optimize their aftertreatment systems to achieve the Tier 3 standards and meet the durability 

criteria for all vehicle classes (PCs, LDTs, MDPVs, and HDTs). 

1.4.1.2.4 Secondary Air Injection 

By injecting air directly into the exhaust stream, close to the exhaust valve, combustion 

can be maintained within the exhaust, creating additional heat thereby further increasing the 

catalyst temperature. The air/fuel mixture must be adjusted to provide a richer exhaust gas for 

the secondary air to be effective. 

Secondary air injection has been used by a variety of passenger vehicle manufacturers to 

assist with achieving the emission levels required of the CA LEV II SULEV standard. 

Secondary air injection systems are used after the engine has started and once exhaust port 

temperatures are sufficiently high to sustain combustion in the exhaust port. When the 

secondary air pump is turned on the engine control module increases the amount of fuel being 

injected into the engine. Sufficient fuel is added so that the air/fuel ratio in the cylinder is rich of 

stoichiometry. The exhaust contains significant quantities of CO and hydrocarbons. The rich 

exhaust gas mixes with the secondary air in the exhaust port and the combustion process 

continues increasing the temperature of the exhaust and rapidly heating the manifold and closecoupled catalyst.71,72

Engines which do not use secondary air injection cannot operate rich of stoichiometry as 

the added enrichment would cause increased NMOG emissions. The richer cold start calibration 

used with vehicles that have a secondary air injection system provides a benefit as combustion 
1-39 

stability is improved. In addition, the richer calibration is not as sensitive to changes in fuel 

volatility. Less volatile fuels found in the market may result in poor start and idle performance 

on engines calibrated to run lean during the cold operation. Engines which use secondary air and 

have a richer warm up calibration would have a greater combustion stability margin. 

Manufacturers may perceive this to be a benefit for the operation of their vehicles during the cold 

start and warm up phase. 

Installing a secondary air injection system combined with calibration changes can be used 

by manufacturers to reduce the cold start emissions and improve the catalyst light-off on existing 

engine designs. It is anticipated that manufacturers will utilize this technology to improve the 

cold start performance on heavier vehicles and vehicles with low power to weight ratios. 

Secondary air injection has been used on vehicles to achieve the CA LEVII SULEV emission 

standards. This technology can be used on engines in all vehicle classes. 

It is anticipated that secondary air injection will be used primarily in combination with 

close coupled catalysts. Therefore, it is not anticipated that this technology will be used with 

HDTs as it is not expected that the catalyst in these vehicles will be moved to a location 

sufficiently close to the exhaust manifold to provide any improvement in catalyst light-off. 

HDTs tend to operate at higher loads and catalyst durability is a concern due to the 

increased thermal loading as the catalyst is moved closer to the cylinder head. Moving the 

catalyst closer to the exhaust manifold would result in increasing the time spent in fuel 

enrichment modes to ensure the temperatures are maintained below the threshold which would 

reduce the durability of the catalyst. Using fuel enrichment to control catalyst temperature 

causes significant increases in criteria pollutant emissions, CO2 emissions and reductions in fuel 

economy. 

1.4.1.2.5 Hydrocarbon Adsorbers 

Hydrocarbon adsorbers trap hydrocarbons emitted by the engine when the adsorber is at 

low temperatures. As the temperature of the hydrocarbon adsorber increases the trapped 

hydrocarbons are released. Passive adsorbers use an additional washcoat on an existing threeway catalyst. The adsorber is a zeolite-based material which absorbs hydrocarbons at low 

exhaust temperatures and desorbs hydrocarbons as the temperature increases. A significant 

technical challenge to using a passive adsorber is to design the system such that the three-way 

catalyst has reached the light-off temperature prior to the adsorber coating releasing the adsorbed 

hydrocarbons. 

Active adsorbers use a substrate with an adsorber washcoat over which the exhaust is 

directed when the exhaust temperature is below the desorption temperature of the material. Once 

the exhaust temperature reaches the desorption temperature the exhaust is routed such that it no 

longer passes over the adsorber. As the adsorber continues to heat in the exhaust the captured 

hydrocarbons are released and oxidized by the warmed-up catalyst system. 

Adsorbers have been used to reduce cold start NMOG emissions on CA LEV II SULEV 

vehicles. Additional work is being performed to further improve the performance of 

hydrocarbon adsorbers. 
1-40 

It is anticipated that if manufacturers have difficulty achieving the Tier 3 NMOG+NOX

emission standards because of challenging NMOG emission levels on the cold start,, they may 

evaluate hydrocarbon adsorbers as an option to further reduce the NMOG emissions during the 

cold start. One manufacturer used this approach to achieve the CA LEV II SULEV standard on a 

large displacement V-8 engine with the application of an active hydrocarbon adsorber.73

Hydrocarbon adsorbers can be used on all spark-ignition engines and all classes of 

vehicles. It is anticipated that these technologies may be required for engines with larger 

displacement and in some of the larger vehicles. It is anticipated that HDTs will be able to 

achieve the emissions levels required without the use of hydrocarbon adsorbers to meet the 

standard. 

1.4.1.3 Improving Catalyst NOX Efficiency during Warmed-up Operation 

Significant quantities of NOX emissions are produced by vehicles during warmed-up 

vehicle operation on the FTP for Tier 2certified vehicles. The stabilized NOX emission levels 

will need to be reduced to achieve the Tier 3 NMOG+NOX emission standard. Improving the 

NOX performance of the vehicle can be achieved by improving the catalyst efficiency during 

warmed-up operation. As previously described the performance of the catalyst can be improved 

by modifications to the catalyst substrate, increasing cell density, increasing PGM loadings and 

particularly important, reducing the sulfur level of gasoline. Three-way catalyst efficiency is 

also affected by frequency and amplitude of the air/fuel ratio. For some vehicles warmed-up 

catalyst NOX efficiency can be improved by optimizing the air/fuel ratio control and limiting the 

amplitude of the air fuel ratio excursions. It is anticipated that a combination of changes will be 

made by manufacturers including further improvements to air/fuel ratio calibration and catalyst 

changes including cell density and PGM loadings. 

A requirement to ensure that the NOX emission performance of the vehicles is maintained 

at or below the 30 mg/mi NMOG+NOX emission standard is reduced fuel sulfur concentrations. 

As described in detail in Section 1.2.3.3 further reductions in fuel sulfur concentration are 

required to ensure the catalyst performance is not degraded which causes increases in NOX

emissions beyond the Tier 3 standard. 

It is anticipated that manufacturers will use these catalyst and calibration technologies to 

improve the warmed up NOX emissions performance of vehicles in all classes, passenger cars, 

LDTs, MDPVs, and HDTs. 

1.4.1.4 EPA Estimates of Technology Improvements Required for Large LightDuty Trucks 

Discussions with and comments from vehicle manufacturers indicated that large lightduty trucks (e.g., pickups and full-size SUVs in the LDT3 and LDT4 categories) will likely be 

the most challenging light-duty vehicles to bring into compliance with the Tier 3 NMOG+NOX

standards at the 30 mg/mi corporate average emissions level. A similar challenge was addressed 

when large light-duty trucks were brought into compliance with the Tier 2 standards in the 

previous decade. Figure 1-5 provides a graphical representation of the effectiveness of Tier 3 

technologies when combined with gasoline sulfur control for large light-duty truck applications. 
1-41 

The Tier 3 technologies shown are those that can be utilized on existing vehicles and do not 

require engine design changes. A compliance margin is shown in both cases. Note that the 

graphical representation of the effectiveness of catalyst technologies on NOX and NMOG when 

going from Tier 2 to Tier 3 also includes a reduction in gasoline sulfur levels from 30 ppm to 10 

ppm. 

0

10

20

30

40

50

60

70

80

90

100

110

120

130

140

150

160

170

180

Tier 2 Bin 5 LDT3/4

w/30 ppm S Gasoline

Tier 3 LDT3/4

w/10 ppm S Gasoline

NMOG+NOx Emissoins (mg/mi)@ 120,000 miles

NMOG+NOx Emissons of Tier 3 LD3/T4

NMOG+NOx Emissions of Tier 2 Bin 5 LDT3/4 

60% 

Compliance

Margin

20-40% Compliance Margin

Tier 2 Bin 5 NMOG+NOx Standard

Tier 3 NMOG+NOx Standard

Passive HC Adsorber

Thermal Management

Secondary 

Air Injection

67% Emissions 

Reduction

Catalyst 

PGM Loading

Figure 1-5: Contribution of the expected Tier 3 technologies to large light-duty truck 

compliance with the Tier 3 standards with a comparison to Tier 2 Bin 5. The technologies 

and levels of control are based on a combination of confidential business information 

submitted by auto manufacturers and suppliers, public data and EPA staff engineering 

judgment. 

1.4.2 Diesel Technologies for Achieving Tier 3 NMOG and NOX Emission Requirements 

Compared to spark-ignition engines, diesel engines typically produce very low NMOG 

emissions. However, diesel engines do not operate at stoichiometry preventing them from using 

emission control approaches similar to spark-ignition engines to control NOX emissions. The 

technical challenge for diesel engines to achieve the Tier 3 NMOG+NOX emission levels will be 

to obtain significant NOX emission reductions. It is anticipated that improvements in NOX

emissions performance of diesel exhaust catalysts during the cold start phase will be a major 
1-42 

technical challenge. Depending on the performance of the exhaust catalyst system, additional 

reductions in warmed-up NOX emissions may also be required to achieve the Tier 3 emission 

levels. 

It is not anticipated that diesel engines will have difficulty achieving the Tier 3 SFTP 

emission standards. The exhaust catalyst system is fully warmed up and operational on the high 

load portion of the SFTP, the US06. It is anticipated that manufacturers may need to optimize 

the calibration of the selective catalytic reduction (SCR) system or the NOX adsorption catalyst 

(NAC) system to ensure the systems achieve the required performance. 

The technical task for achieving the Tier3 standards on all diesel engines in all vehicle 

classes will be to have the exhaust catalysts reach operating temperatures early in the cold-start 

phase of the FTP. To achieve these improvements it is anticipated that diesel manufacturers will 

focus on means to reduce NOX emissions during the engine warm-up phase after the cold start 

and reducing the time required for the SCR or NAC system to begin reducing (SCR) or capturing 

and reducing (NAC) the NOX. 

By controlling the timing of the fuel injection event, the number of fuel injection events 

and the timing of intake and exhaust valve events, the temperature of the exhaust can be 

increased. Diesel engine manufacturers will optimize the injection and valvetrain calibration to 

increase the exhaust temperature after the engine is started and before it has reached operating 

temperature. 

As with gasoline engines, locating the exhaust catalyst system closer to the cylinder head 

and air-gap insulating the exhaust system or reducing the mass of the exhaust components 

upstream of the catalysts can be used to build and maintain heat in the exhaust system. A variety 

of technologies are available to conduct combustion heat into the exhaust catalyst system with 

minimal cooling. This includes uses of dual-wall, air-gapped exhaust piping between the engine 

and the catalyst or trap; reducing the wetted area of the exhaust path; and reducing the thermal 

mass of the exhaust system through use of thinner wall materials. By reducing the time required 

to light-off the catalysts, thermal management technologies can reduce NOX emissions from 

diesel engines. Once light-off has been achieved, NOX emissions reduction for modern, basemetal zeolite SCR systems approaches that of modern three-way catalyst systems used for 

stoichiometric gasoline spark-ignition applications.74

1.5 PM Feasibility 

Particulate matter emitted from internal combustion engines is a multi-component 

mixture composed of elemental carbon (or soot), semi-volatile organic compounds, sulfate 

compounds (primarily sulfuric acid) with associated water, nitrate compounds and trace 

quantities of metallic ash. At temperatures above 1,300K, fuel hydrocarbons without access to 

oxidants can pyrolize to form particles of elemental carbon. Fuel pyrolysis can occur as the result 

of operation at richer than stoichiometric air-to-fuel ratio (primarily PFI gasoline GDI engines), 

direct fuel impingement onto surfaces exposed to combustion (primarily GDI and diesel engines) 

and non-homogeneity of the air-fuel mixture during combustion (primarily diesel engines). 

Elemental carbon particles that are formed can be oxidized during later stages of combustion via 

in-cylinder charge motion and reaction with oxidants. Semi-volatile organic compounds (SVOC) 
1-43 

are composed primarily of organic compounds from lubricant and partial combustion products 

from fuel. PM emissions from SVOC are typically gas phase when exhausted from the engine 

and contribute to PM emissions via particle adsorption and nucleation after mixing with air and 

cooling. Essentially, PM-associated SVOC represent the condensable fraction of NMOG 

emissions. Sulfur and nitrogen compounds are emitted primarily as gaseous species (SO2, NO 

and NO2). Sulfate compounds can be a significant contributor to PM emissions from stratified 

lean-burn gasoline engines and diesel engines, particularly under conditions where PGMcontaining exhaust catalysts used for control of gaseous and PM emissions oxidize a large 

fraction of the SO2 emissions to sulfate (primarily sulfuric acid). Sulfate compounds do not 

significantly contribute to PM emissions from spark-ignition engines operated at near 

stoichiometric air-fuel ratios due to insufficient availability of oxygen in the exhaust for 

oxidation of SO2 over PGM catalysts. 

Elemental carbon PM emissions can be controlled by: 

Reducing fuel impingement on piston and cylinder surfaces 

Inducing charge motion and air-fuel mixing via charge motion (e.g., tumble and 

swirl) or via multiple injection (e.g., GDI and diesel/common rail applications) 

Reducing or eliminating operation at net-fuel-rich air-to-fuel ratios (PFI gasoline 

and GDI applications) 

Use of wall-flow or partial-wall-flow exhaust filters (diesel applications) 

SVOC PM emissions can be controlled by: 

Reducing lubricating oil consumption 

Improvements in exhaust catalyst systems used to control gaseous NMOG 

emissions (e.g., increased PGM surface area in the catalyst, improvements in 

achieving catalyst light-off following cold-starts, etc.) 

Sulfate PM emission can be controlled by: 

Reducing or eliminating sulfur from fuels 

1.5.1 PM Emissions from Light-duty Tier 2 Vehicles 

In order to establish the feasibility of the Tier 3 PM emission standards, EPA conducted a 

test program to measure PM emissions from Tier 2 light-duty vehicles. The test program was 

designed to measure PM emissions from late model year vehicles that represented a significant 

volume of annual light duty-sales and included vehicles that ranged from small cars through 

trucks. In addition, GDI vehicles were included in the program as were vehicles with known 

high oil consumption. 
1-44 

The Agency investigated PM emissions from Tier 2 light-duty vehicles. Seventeen model 

year 2005-2010 Tier 2 Bin 4, 5, and 8 vehicles were tested at the U.S. EPA National Vehicle and 

Fuel Emissions Laboratory (NVFEL) facility. A summary of their characteristics are provided in 

Table 1-8. They included ten cars and seven trucks. Fifteen of these vehicles had accumulated 

102,000-124,000 miles prior to the launch of the test program. One vehicle had accumulated 

75,000 miles and another accumulated 21,000. Three cars and one truck were equipped with 

GDI engines. Twelve of the fifteen test vehicles had previously been used in the DOE V4 

Program. The remaining five vehicles were recruited in southeastern Michigan. One vehicle 

(vehicle K) was suspected of having atypically high oil consumption and had only 37,000 miles 

of mileage accumulation. Vehicle K was a duplicate of Vehicle C and was determined to 

consume two and one half times the average oil consumption of vehicle C and three vehicles of 

the same make, model and model year when tested within the DOE V4 program.F 

The twelve vehicles acquired from the DOE V4 Program were selected to represent a 

broad cross section of some of the highest sales vehicles in the U.S. market for model years 

2005-2009. These vehicles had originally been purchased by DOE with odometer readings 

ranging from 10,000-60,000 miles, placed in a mileage accumulation program and operated over 

the EPA Standard Road Cycle on a test track or on mileage accumulation dynamometers to 

110,000-120,000 miles.75 Immediately prior to inclusion in the EPA PM Test Program, the test 

vehicles were serviced per the manufacturer’s published service schedule and maintenance 

procedures and underwent engine oil aging over a distance of 1,000 miles accumulated over the 

EPA Standard Road Cycle to stabilize engine oil contribution to PM emissions76.

Three recruited test vehicles were selected because they used GDI technology. An 

additional GDI equipped vehicle was obtained from the DOE V4 Program An attempt was made 

to only recruit vehicles approaching the 120,000 mile useful life level. Testing was completed 

for two of the four vehicles prior to the proposal of this rule. All of the recruited test vehicles 

were thoroughly inspected, but otherwise tested as received. 

All vehicles were tested on an E15 fuel with RVP, aromatic content, sulfur content, T50 

and T90 of 9.1 psi, 23.8 vol%, 7 ppm, 160F and 311F, respectively. The properties of this fuel 

approximated those of a projected E15 market fuel. 

The test program included three cold start and three hot start UDDS tests and three US06 

tests conducted on each vehicle. FTP results were calculated for gaseous and PM emissions by 

applying the cold-start and hot-start weighting factors to the complete cold and hot UDDS 

results, respectively. This eliminated separate analysis of the typically very low concentration 

FTP phase-2 gaseous and PM emissions samples and represented one method proposed within 

40 CFR 1066 for increasing sample integration of measured gaseous and PM mass. During these 

tests, triplicate PM samples were collected in parallel on PTFE membranes and single 

(composite) PM samples were collected on primary and secondary quartz filters for TOT/TOR 

OC/EC PM speciation analysis. Additional quartz filters were collected to determine the 

 

F

 Vehicle K consumed approximately 1 quart per 3,000 miles vs. an average of approximately 1 quart per 8,000 

miles for the other four vehicles of this make, model and year tested within the DOE V4 program. 
1-45 

contribution of gas-phase artifact to the OC collected on the quartz filter samples. The 

compositing of quartz filters over three repeats of each test was done to enhance the precision of 

subsequent OC/EC thermogravimetric measurements. Single background (dilution air) PM 

samples were also taken during each emissions test. Weekly tunnel blank and field blank PM 

samples were also collected. 

The following parameters were measured: NOX, NMHC, NMOG, alcohols, carbonyls, 

CO, CH4, CO2 and fuel consumption and PM mass as per the 40 CFR 1065 and the proposed 40 

CFR part 1066 test procedures. Limited exhaust HC speciation was also performed. 

PM composition was determined from filter samples taken on both quartz filters and 

PTFE membranes. PM compositional analyses include determination of the contribution of 

elemental and organic carbon to PM mass,77 elemental analysis via EDXRF, sulfate analysis via 

ion chromatography and determination of the contribution of unresolved complex organic PM 

compounds by GC/MS. 

Note that during the compositional analysis of the PM, EPA discovered a significant 

amount of silicon deposited on some of the filters. The source of the silicon was determined to 

be a silicone elastomer transfer tube used to connect vehicles to the emissions measurement 

equipment. The data below reflect test results that are not subject to silicone contamination. For 

additional information, refer to our memo to the docket78 which describes the original analysis 

and corrective actions in greater detail. 
1-46 

Table 1-8: Vehicles Tested as part of EPA’s Light-Duty Vehicle PM Test Program 

Vehicle Make, Model

and Designation

Model 

Year

Certified to 

Emissions 

Standard

Odometer at 

Start of 

Program, miles

Fuel 

Deliverya

Used in 

DOE V4 

Program?

Honda Civic A 2009 Tier 2/Bin 5 121,329 PFI Yes

Toyota Corolla B 2009 Tier 2/Bin 5 120,929 PFI Yes

Honda Accord C 2007 Tier 2/Bin 5 123,695 PFI Yes

Dodge Caliber D 2007 Tier 2/Bin 5 114,706 PFI Yes

Chevrolet Impala E 2006 Tier 2/Bin 5 114,284 PFI Yes

Ford Taurus F 2008 Tier 2/Bin 5 115,444 PFI Yes

Toyota Tundra G 2005 Tier 2/Bin 5 121,243 PFI Yes

Chrysler Caravan H 2007 Tier 2/Bin 5 116,742 PFI Yes

Jeep Liberty I 2009 Tier 2/Bin 5 121,590 PFI Yes

Ford Explorer J 2009 Tier 2/Bin 4 121,901 PFI Yes

Honda Accord K 2007 Tier 2/Bin 5 36,958 PFI Yes

Ford F150 L 2005 Tier 2/Bin 8 111,962 PFI No

Chevrolet 

Silverado P 2006 Tier 2/Bin 8 110,898 PFI No

VW Passat M 2006 Tier 2/Bin 5 102,886 TGDI No

Manufacturer’s 

Development 

Vehicleb

N PC

None (Tier 

2/LEV II 

Prototype)*

120,011 TGDI No

Saturn Outlook O 2009 Tier 2/Bin 5 123,337 GDI Yes

Cadillac STS4 Q 2010 Tier 2/Bin 5 21,266 GDI No

Notes:

a

PFI is Naturally aspirated, port fuel injected; GDI is Naturally aspirated, gasoline direct 

injection; TGDI is Turbocharged, gasoline direct injection

b Manufacturer’s developmental vehicle. Vehicle used a spray-guided GDI fuel system 

with a centrally-mounted injector. Emissions were targeted at Tier 2 Bin 5 or better. 

1.5.1.1 PM Emissions Test Results 

The results of exhaust emissions tests conducted in this program are summarized in Table 

1-9 and Table 1-10 for the FTP and US06 test cycles, respectively. FTP NMOG +NOX and PM 

results are also plotted in Figure 1-7 and Figure 1-8, respectively. The US06 NMOG+NOX and 

PM results are shown in Figure 1-9 and Figure 1-10, respectively. In all figures, the vehicles are 

divided into two groups: PFI and GDI. Within each group they are listed in the sequence of 

increasing CO2 emissions on the FTP test cycle. The bars shown in the figures represent the 

means of triplicate measurements. The individual data points are indicated in all figures together 

with the corresponding standard deviations. Vehicle Q only had one valid PM test on the FTP 

test cycle and no error bars are plotted. 
1-47 

Table 1-9: FTP Composite Emissions Results 

Vehicle CO2 CO NOX NMOG NOX+NMOG PM

g/mile g/mile g/mile g/mile g/mile mg/mile

A 284.6 0.358 0.0239 0.0316 0.056 0.27

B 286.3 0.434 0.0461 0.0408 0.087 0.22

C 324.4 0.382 0.0231 0.0299 0.053 0.18

D 364.8 6.740 0.1432 0.0663 0.210 0.45

E 410.8 0.571 0.0600 0.0359 0.096 0.14

F 419.2 0.271 0.0151 0.0206 0.036 0.11

G 447.2 0.626 0.0424 0.0439 0.086 0.36

H 462.9 1.617 0.0507 0.0493 0.100 0.40

I 495.7 0.719 0.0317 0.0429 0.075 1.36

J 554.8 1.072 0.0281 0.0525 0.081 0.10

K 332.5 0.202 0.0165 0.0171 0.034 0.93

L 568.8 2.264 0.1024 0.0822 0.185 0.39

M 365.2 0.346 0.0342 0.0261 0.060 -

N 411.0 0.735 0.0279 0.0258 0.054 2.55

O 505.2 0.599 0.0173 0.0399 0.057 4.72

P 547.0 0.649 0.3578 0.0429 0.401 0.18

Q 465.0 0.475 0.0279 0.0221 0.050 7.15
1-48 

Table 1-10: US06 Emissions Results 

Vehicle

CO2 CO NOX NMOG NOX+NMOG PM

g/mile g/mile g/mile g/mile g/mile mg/mile

A 289.0 7.092 0.0212 0.0162 0.0374 0.76

B 312.8 9.315 0.0530 0.0248 0.0779 2.05

C 318.2 1.293 0.0257 0.0105 0.0362 1.05

D 413.7 9.077 0.1324 0.0127 0.1451 -

E 393.3 0.660 0.1019 0.0163 0.1183 0.46

F 422.8 1.237 0.0274 0.0124 0.0398 1.61

G 490.9 3.462 0.0369 0.0172 0.0540 -

H 467.0 1.128 0.0910 0.0134 0.1044 2.04

I 516.0 0.833 0.1852 0.0037 0.1889 3.31

J 555.9 3.015 0.1121 0.0159 0.1280 0.27

K 320.4 1.800 0.0247 0.0079 0.0326 2.84

L 595.6 5.519 0.0036 0.0125 0.0160 2.13

M 352.8 9.225 0.0481 0.0297 0.0779 -

N 401.7 0.330 0.1614 0.0048 0.1662 2.37

O 547.4 9.862 0.0377 0.0282 0.0659 -

P 529.1 2.728 0.1427 0.0116 0.1543 1.83

Q 436.6 2.595 0.0265 0.0204 0.0470 -

As shown in Figure 1-6, with the exception of one PFI passenger car (vehicle D), the FTP 

NMOG+NOX emissions of all tested vehicles remained below their respective fleet average 2017 

standards, but none performed below the 2025 standard. 

The FTP PM from PFI vehicles remained well below the Tier 3 PM standard of 3 

mg/mile, confirming that most current light duty vehicles are already capable of meeting the Tier 

3 PM standard (Figure 1-7). Two GDI vehicles demonstrated FTP PM emissions above final 

Tier 3 standard, indicating that additional combustion system development would be necessary 

in some vehicles to achieve compliance. 

As shown in Figure 1-8, with the exception of two LDTs (vehicles I and J), all vehicles 

met their respective fleet average 2017 (for vehicles below 6,000pounds GVWR) or 2018 (for 
1-49 

vehicles above 6,000 pounds GVWR) US06 NMOG+NOX standards. Five vehicles, four 

passenger cars (vehicles A, B, F and L) and one LDT (vehicle L), produced US06 NMOG+NOX

emissions lower than the 2025 standard. 

As in the case of FTP results, all PFI passenger cars remained well below the proposed 

US06 10 mg/mile standard (Figure 1-9). One GDI passenger car (vehicle N) performed well 

below its respective US06 PM standard and achieved PM emissions over the US06 comparable 

to its performance over the FTP. In summary, all of the vehicles tested met the Tier 3 US06 PM 

standards. 

The suspected high oil consumption vehicle (vehicle K) emitted 3 and 2.3 times more PM 

in this program than a comparable vehicle with average oil consumption (vehicle C) in the FTP 

and US06 tests, respectively. FTP NOx+NMOG (g/mile) 0.0

0.1

0.2

0.3

0.4

0.5

PFI (PC)

P C

A B C K D E F

PFI (LDT2)

LDT2

G H I

PFI (LDT3/4)

LDT3/4

P J L

GDI

P C P C P C LDT3

M N Q O

Figure 1-6: Composite FTP NMOG+NOX Emissions Results 
1-50 FTP PM (mg/mile) 0

2

4

6

8

PFI (PC)

P C

A B C K D E F

PFI (LDT2)

LDT2

G H I

PFI (LDT3/4)

LDT3/4

P J L

GDI

P C P C LDT3

N Q O

Figure 1-7: Composite FTP PM Emission Results US06 NOx+NMOG (g/mile) 0.0

0.1

0.2

0.3

0.4

0.5

PFI (PC)

P C

A B C K D E F

PFI (LDT2)

LDT2

G H I

PFI (LDT3/4)

LDT3/4

P J L

GDI

P C P C P C LDT3

M N Q O

Figure 1-8 US06 NMOG+NOX Emissions Results 
1-51 US06 PM (mg/mile) 0

2

4

6

8

PFI (PC)

P C

A B C K E F

PFI (LDT2)

LDT2

H I

PFI (LDT3/4)

LDT3/4

P J L

GDI

P C

N

Figure 1-9: US06 PM Emissions Results 

1.5.2 FTP PM Feasibility 

With regard to the feasibility of the light-duty fleet to meet the Tier 3 PM standards over 

the FTP and US06, we based our conclusions on the PM performance of the existing fleet. Data 

on both low and high mileage light-duty vehicles demonstrate that the majority of vehicles are 

currently achieving levels in the range of the Tier 3 FTP standards. A small number of vehicles 

are at or just over the finalized Tier 3 standard at low mileage and would require calibration 

changes, catalyst changes and/or further combustion system improvements to meet the new 

standards. It is our expectation that the same calibration and catalyst changes required to address 

NMOG would also provide some additional PM control. Vehicles that are currently 

demonstrating higher PM emissions over the FTP at higher mileages would likely be required to 

control oil consumption and combustion chamber deposits. 

1.5.3 SFTP PM

Also, US06 test data shows that many vehicles are already at or below the Tier 3 

standards for US06. Vehicles that are demonstrating high PM on the US06 would need to 

control enrichment and oil consumption. The oil consumption strategies are much like that 

described above for controlling oil consumption on the FTP. However, given the higher engine 

RPMs experienced on the US06 and the commensurate increase in oil consumption, 

manufacturers will most likely focus on oil sources stemming from the piston to cylinder 

interface and positive crankcase ventilation (PCV). With respect to enrichment, changing the 

fuel/air mixture by increasing the fuel fraction is no longer the only tool that manufacturers have 

available to them to protect engine and exhaust system components from over-temperature 

conditions. With application of electronic throttle controls on nearly every light-duty vehicle, 
1-52 

the manufacturer has the option to richen the air/fuel mixture by maintaining the amount of fuel 

being delivered and closing the throttle plate. Previously, on manual throttle control vehicles, 

the throttle plate position was established by the driver and the engine controls had no capability 

to change the amount of air in the intake. While it is possible that this solution may result in a 

small reduction in vehicle performance we believe that it is an effective way to reduce PM 

emissions over the US06 cycle. 

1.5.4 Full Useful Life: Durability and Oil Consumption 

Manufacturers have informed us that they have already or are planning to reduce oil 

consumption by improved sealing of the paths of oil into the combustion chamber, including 

improved piston-to-cylinder interfaces. They are taking or considering these actions to address 

issues of customer satisfaction, cost of ownership and improved emission control system 

performance as vehicles age. 

Over the past decade, many manufacturers have extended oil change intervals from the 

historically required 3,000 miles interval to a now typical 10,000 mile interval or more in some 

vehicle models. In order to allow for these longer intervals, improvements were made to limit 

pathways for oil to enter the combustion chamber, resulting in significantly reduced oil 

consumption. While customer satisfaction and longer oil change intervals, particularly for leased 

vehicles where owners may be less inclined to perform frequent oil changes, were a motivation 

for reducing oil consumption, improvements in the performance of the emission control system 

are a secondary benefit of reduced oil consumption. Oil consumption can damage catalytic 

converters by coating the areas of the catalyst that convert and oxidize the pollutants. Over time, 

this can cause permanent inactivity of those areas, resulting in reduced catalytic conversion 

efficiency. Reductions in oil consumption can extend the life of the catalytic converter and help 

manufacturers meet longer useful life requirements. This is particularly important on vehicles 

meeting the most stringent emission standards, because they will need to maintain high catalyst 

efficiencies in order to meet the stringent emission standards at higher mileage. 

1.6 Evaporative Emissions Feasibility 

The basic technology for controlling evaporative emissions was first introduced in the 

1970s. Manufacturers routed fuel tank and carburetor vapors to a canister filled with activated 

carbon, where vapors were stored until engine operation allowed for purge air to be drawn 

through the canister to extract the vapors for delivery to the engine intake. Over the past 30 

years, evaporative emission standards and test procedures have changed several times, most 

notably in the mid-1990s when enhanced evaporative controls were required to address 2- and 3- 

day diurnal emissions and running losses. Refueling emission controls were added with phase-in 

beginning in the 1998 MY. Almost universally manufacturers elected to integrate evaporative 

and refueling emission control systems. In the mid-2000s more stringent evaporative emission 

standards with E10 durability gasoline led to the development and adoption of technology to 

identify and eliminate permeation of fuel through fuel tanks, fuel lines, and other fuel-system 

components. 

The Tier 3 evaporative emission requirements include more stringent hot-soak plus 

diurnal standards that are expected to require new vehicle hardware and improved fuel system 
1-53 

designs. The type of new hardware that will be required will vary depending on the specific 

application and emission challenges and are described in the following section. Additionally, the 

fleet-average nature of the standards would allow more challenged vehicles to be offset by 

vehicles that could outperform the required fleet averages. 

In order to assess the technical feasibility of the evaporative emission standards, EPA 

conducted three analyses. The first analysis was a review of technology in the fleet as well as a 

literature review of the technologies used to meet PZEV “zero evap” requirements in California. 

The second analysis performed was based on the certification results for the current EPAcertified evaporative families. This provided a baseline for the current fleet emissions 

performance. The third analysis looked at the list of PZEV-certified vehicles in the California 

LEV II/ZEV fleets. The Tier 3 evaporative emission standards are similar to the current 

evaporative requirements for PZEVs in California. These analyses are described in greater detail 

below.

1.6.1 Tier 3 Evaporative Emissions/Leak Control Technology Approaches 

Vehicles designed to meet the Tier 3 evaporative emission standards for the full useful 

life will incorporate a variety of technologies. The choice of technologies will be based on three 

key elements. The first is related to hardware and designs focused on reducing emissions to 

achieve “zero” fuel vapor emissions. While the emission standards are not numerically zero, the 

2 and 3-day hot soak plus diurnal standards are intended primarily to allow for the non-fuel 

hydrocarbons which arise from the vehicle and its interior components. The push for “zero” fuel 

vapor emissions is emphasized by the inclusion of the canister bleed emission standard which is 

less than 10 percent of the hot soak plus diurnal standard. Thus, we expect the technology to 

focus on the largest remaining sources of emissions. The second element is related to full-life 

durability. Maintaining “zero” evaporative emission levels over many years and many miles of 

driving will require a focus on preventing the deterioration in fuel/evaporative control system 

performance which arises from factors such as vibration, environmental conditions, and fuel 

effects. The new leak standard and the related OBD evaporative control system leak monitoring 

requirement are intended to get focus on elements of technology and design which will reduce 

the impacts of these factors on in-use emissions by encouraging the use of more durable 

integrated technologies and systems. The third element is related to fuel effects. While EPA has 

kept the RVP of the fuel at 9 psi, the Tier 3 certification fuel includes 10 percent ethanol which 

will have to be further considered in choices of fuel system materials and vapor lines. EPA does 

not expect the change in certification fuel to affect refueling, spit back, or running loss 

compliance technology or strategies. 

While the three elements discussed above are important considerations in the evaporative 

emission control system design, there are two other factors which come into play when 

considering which technologies will come in to the fleet and on which vehicles. First, in many 

cases a given technology will provide emission reduction benefits against more than one 

emission standard. For example, improved activated carbon canister technology to meet the 

canister bleed standard will help to meet the hot soak plus diurnal standard or reducing 

fuel/evaporative system connection points to meet the leak standard will help to meet the hot 

soak plus diurnal standard. Second, to varying degrees, the technologies discussed below are in 

use in the fleet today, resulting in reduced emissions relative to the current requirements for 
1-54 

evaporative emission standards and improved durability. Thus, not every vehicle model will use 

every technology either because it is already being implemented or the required reductions to 

meet the Tier 3 emission targets are not large enough to warrant its application. 

In preparing this assessment EPA considered two key sources of information. The first 

was the developmental studies in the literature to identify the technologies best capable of 

reducing emissions.79,80 Second, we examined the technologies used on various PZEV zero evap 

vehicles certified in the CARB ZEV program. The technologies identified as a result of our 

review are summarized below first for technologies expected to see widespread use and then for 

technologies with a more limited application because they are in common use today. 

1.6.1.1 Technologies expected to see widespread use 

Engine/fuel system conversion: As projected in our final rule RIA for the 2017-2025 GHG 

emissions, EPA projects a significant movement from port fuel injection (PFI) engines to 

gasoline direct injection (GDI) engines. This ranges from 60-100 percent of products for all 

categories except gasoline-powered trucks over 14,000 lbs GVWR. This reduces air induction 

systems emissions by 90 percent since the GDI uses a different fuel injection timing strategy 

than the PFI.81

Air Induction System (AIS) Scrubber: For vehicles/engine models not converted to GDI, EPA 

projects the use of an AIS scrubber as is now used on some PZEV models. These would reduce 

air induction system emissions by about90 percent.82,83

Canister honeycomb: This is a lower gasoline working capacity activated carbon device designed 

to load and purge very easily and quickly. This device reduces canister bleed emissions by 90 

percent but also provides control for the hot soak plus diurnal test. It comes in various sizes and 

can be optimized based on the anticipated bleed emission rate. 

Fuel system architecture: This includes reducing connections and improve seals and o-rings and 

moving parts into the fuel tank: Vapor leaks from connections and the emission rates from these 

leaks is exacerbated if poor sealing techniques or low grade seal materials are use in connectors 

such as o-rings. Reducing connections in the fuel and evaporative systems and improving 

techniques and materials could reduce these emissions by 90 percent. This would reduce hot 

soak plus diurnal emissions, improve durability, and help to assure compliance with the leak 

standard. Another means to reduce leak-related vapor emissions is to move fuel evaporative 

system parts which are external to the fuel tank to the inside. Emissions from these parts would 

be completely eliminated. This would reduce hot soak plus diurnal emissions, improve 

durability, and help to assure compliance with the leak standard. 

OBD evaporative system leak monitoring: Beginning in the 2017 model year, the OBD system 

will need to be able to find, confirm, and signal a leak in the evaporative system of 0.020” 

cumulative diameter or greater. This is done on most vehicles today as a part of meeting CARB 

requirements, but will be mandatory under EPA regulations. 

The evaporative emission standards discussed above also apply to gaseous-fueled 

vehicles. EPA expects manufacturers to comply through the use of good design practices such as 
1-55 

those specified in published consensus standards to address issues such as leaks from microcracks and system connections and in a broader sense system mechanical and structural integrity. 

1.6.1.2 Technologies expected to be optimized if necessary to achieve further 

reductions: 

Upgrade canister and optimize purge: This strategy is mostly available for higher powered V-8 

engines. A canister with greater working capacity and/or more purge air volume could reduce 

hot soak plus diurnal emissions by 80-90 percent and create capacity for the hot soak plus diurnal 

and canister bleed emissions. However, it should be noted that the available emission reductions 

are not large, because of the amount of purge needed to accomplish these reductions relative to 

the reductions achieved from current canisters and purge strategies.84,85

Fuel tank and fuel line upgrades: Fuel vapor permeation contributes to hot soak plus diurnal 

emissions. There are upgrades to fuel line materials which could reduce emissions in models 

where these best practices are not yet used. In these situations, current permeation emission rates 

could be reduced by 90 percent. 

Improve fuel tank barrier layer and seam weld manufacturing: Fuel tanks are designed to limit 

permeation emissions. Fuel tanks are typically made of high-density polyethylene with an 

embedded barrier layer of ethyl vinyl alcohol (EvOH) representing about 1.8 percent of the 

average wall thickness for reducing permeation emissions. In some cases manufacturers could 

increase the EvOH barrier thickness to about 3 percent of the average wall thickness to provide a 

more uniform barrier layer, to provide better protection with ethanol-based fuels, and to improve 

permeation resistance generally. Recent developments in production processes have led to 

improved barrier coverage around the ends of the tank where the molded plastic is pinch-welded 

to form a closed vessel. This technology would likely be coupled with the increase in EvOH in 

the overall tank material or other techniques to reduce permeation from these seams. These 

changes are expected to decrease emission rates over the diurnal test from about 40 mg per day 

to 15 mg per day from the fuel tank assembly. It is likely that this change would be done as part 

of a fuel tank design changeover and not out of a normal tooling cycle. 

Upgrade fill tube material and connection to fuel tank: The connection of the fill tube to the fuel 

tank is the largest connection in the fuel system. Improving the security of the fill tube 

connection to the tank could reduce vapor leaks. The fill tube itself has a larger diameter than 

other fuel or vapor lines and thus has a relatively large diameter. For higher permeation 

resistance the tube can be upgraded to one having an FKM inner layer. We would expect such 

changes to occur together. 

Table 1-11 presents a summary of EPA projections of the application of the widespread 

technologies across the LDV, LDT, MDPV, and HDGV fleets. These projections are based on 

consideration of the most effective technologies to achieve the required reductions. In this 

context, effective means not only what technologies might provide the largest reductions which 

could be used to meet more than one standard, but also which technologies provide these 

reductions in the most cost efficient way. The baseline emission rates and percent efficiencies 

from the various technologies are both EPA estimates based on review of the literature and 

discussion with various manufacturers and vendors. The reductions achieved are larger than the 
1-56 

difference between the baseline and design target because of the need to cover for the non-fuel 

hydrocarbons which are measured in certification but decay in use. Note that the last column in 

Table 1-11 identifies which standards the technology will address. In some cases the expected 

emission reductions are larger from HDGVs. This is due primarily to the volume of their fuel 

tanks and unique aspects of some elements of their fuels systems relative to smaller passenger 

cars and light trucks. 
1-57 

Vehicle Class

nonfuel (g) 0.1 0.1 0.125 0.15 0.15 0.175 0.2 0.25

MSAT std(3d/2d)(g) 0.5/0.65 0.65/0.85 0.65/0.85 0.9/1.15 0.9/1.15 1.0/1.25 1.4/1.75 1.9/2.3

T3 std (g) 0.3 0.3 0.4 0.5 0.5 0.5 0.6 0.6

Canister bleed std (g) 0.02 0.02 0.02 0.02 0.02 0.02 0.03 0.03

MSAT Baseline (g) 1 0.47 0.47 0.42 0.72 0.72 0.72 0.96 0.96

T3 Target (g)2 0.2 0.2 0.3 0.37 0.37 0.37 0.45 0.45

Red Needed (g) 0.27 0.27 0.12 0.35 0.35 0.35 0.51 0.51

Red Achieved (g) 0.39 0.39 0.39 0.39 0.39 0.39 0.55 0.52

Current Control mg red & net red mg red & net red mg red & net red mg red & net red mg red & net red mg red & net red mg red & net red mg red & net red Standard

Technology Emissions Efficiency % applied mg % applied mg % applied mg % applied mg % applied mg % applied mg % applied mg % applied mg Addressed

Canister 

honeycomb 

35mmx75mm

150-200mg3 

(use 150mg)

90% 135_100% 135 135_100% 135 135_76% 103 135_10% 13 0 0 0 0 0 0 0 0 T3/ bleed

(V-4 & V-6)

Canister 

honeycomb 

35mmx50mm

150-225mg 

(use 150mg 

exc HDGV)

90% 0 0 0 0 135_24% 32 135_90% 122 135_100% 135 135_100% 135 200_100% 200 200-100% 200 T3/ bleed

(V-8)

AIS scrubber 150-300 mg 

(use 225 mg) 

exc HDGV4

90% 200_40% 80 200_27% 54 200_27% 54 200_27% 54 200_27% 54 200_27% 54 0 0 270_100% 270 T3

PFI to GDI5 150-300mg 

(use 225mg) 

exc HDGV

90% 200_60% 120 200_73% 146 200_73% 146 200_73% 146 200_73% 146 200_73% 146 270_100% 270 0 0 T3

Fuel system 

architecture

(a)reduce 

connections & 

improve seals/ orings 6

25-50mg 

(use 25mg) 

exc HDGV

90% 22_100% 22 22_100% 22 22_100% 22 22_100% 22 22_100% 22 22_100% 22 45_100% 45 45_100% 45 T3/leak

(b) move parts 

into tank

75-100mg 

(use 75mg)

100% 75_50% 37 75_50% 37 75_50% 37 75_50% 37 75_50% 37 75_50% 37 75_50% 37 _ _ T3/leak

OBD software 

upgrades7

n/a n/a 100% _ 100% _ !00% _ 100% !00% _ 100% _ 100% _ _ _ leak

1

 based on mean plus one standard deviation for 2013 MY 2-day cert results on Tier 2 fuel

2 100 mg or 25% below T3 std whichever is greater 

2

 (365 day per year)(1 gal per 5.6 lbs)(1 lb per 454g)(mg reduction/day)(1 g/1000 mg)(0.9 energy density effect); needs to be further multiplied by(15yr) (avg surv fraction for fleet)(gas price)

3

 based SAE 2001-01-0733

4

 based on SAE 2005-01-0113 and US patent 6464761

5

 % conversion from PFI to GDI based on RIA for 2017-2025 EPA GHG Final Rule

6

 reduce fuel/ evap system connections, improve seal material (FKM) in engine & fuel/ evap systems, and employ o-rings as needed

7

 Most manufacturers meet the 0.020" evaporative system leak monitoring provision now; no new hardware expected

LDV LDT1 LDT2 LDT3 LDT4 MDPV LHDGV HHDGV

 Table 1-11 Application of Evaporative Emission Control Technologies for Tier 3
1-58 

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1-59 

Table 1-12 presents the information for the technologies expected to see more limited 

use, but does not project application rates. It does show however, that these technologies would 

in most cases provide smaller reductions than those identified in Table 1-11. In the case of the 

upgraded canister and purge optimization, to the degree it is used it is more likely to be a 

replacement for the canister honeycomb on V-8 engines than as an additional technology by 

itself. 

Table 1-12 Technologies Which May Be Optimized If Necessary to Achieve Further 

Reductions in Tier 3

 

Upgrade 

canister & 

improve 

purge (mostly 

V-8s)

120-150mg 80-90% ~100mg

Improve fuel 

tank barrier 

layer 

thickness and 

reduce pinch 

seam gaps

75mg 70% ~50mg

Filler neck 

connection 

and materials 

ugrade1

60mg 80% ~50mg

Fuel line 

material 

upgrade

40mg 90% ~35mg

1 Kawasaki.M., et al, Low Gasoline Permeable Fuel 

 Filler Hose, SAE Technical Paper Series 971080, 1997.

1.6.2 Assessment of the Current EPA Certification Emissions 

EPA’s current evaporative emission standards vary by vehicle category. Table 1-13

shows the currently applicable hot-soak plus diurnal emission standards and Table 1-14 shows 

the Tier 3 standards.
1-60 

Table 1-13 Existing EPA Evaporative Emission Standards

Vehicle Category Hot-soak plus Diurnal (2-day) Hot-soak plus Diurnal (3-day)

LDV 0.65 g/test 0.50 g/ test

LDT1/LDT2 0.85 g/test 0.65 g/test

LDT3/LDT4 1.15 g/test 0.90 g/test

MDPV 1.25 g/test 1.00 g/test

HDGV <14,000 lbs 

GVWR 1.75 g/test 1.4 g/test

HDGV > 14,000 lbs 

GVWR 2.3 g/test 1.9 g/test

 

 Table 1-14 Final Tier 3 Evaporative Emission Standards

Vehicle Category/Averaging Sets Highest Hot Soak + Diurnal Level

(over both 2-day and 3-day diurnal tests)

LDV, LDT1 0.300 g/test

LDT2 0.400 g/test

LDT3, LDT4, MDPV 0.500 g/test

HDGVs 0.600 g/test

Based on MY2013 certification data, EPA analyzed the certification hot-soak plus diurnal 

emission levels for all vehicle categories that will be subject to the Tier 3 standards. The 

following figure shows the hot-soak plus diurnal certification levels (based on the 2-day diurnal 

test) for each vehicle category ordered from the lowest to the highest emission levels. (While not 

presented in this analysis, the data based on the 3-day diurnal tests shows a similar trend.) 

Figure 1-10 also shows the existing and Tier 3 evaporative emission standards.
1-61 

0

0.5

1

1.5

2

2.5

11 63 14 66 17 691 106 121 136 151 166 181 196 211 226 241 256 271 286 301 316 331 346 361 376 391 406 421 436 451 g HC/test

Families Certified

Cert. Levels

Tier 3 Stds

Existing Stds

LDV

LDV1/2

LDT3/4 MDPV

LHDGV

HHDGV

LDV/LDT1 LDT2

HDGV

LDT3/4,MDPV

Figure 1-10: MY2013 PZEV & Federal Hot-soak Plus Diurnal (2-Day) Emission 

Certification LevelsG

It should be noted that the current evaporative emission data is based on a different 

certification test fuel than what is being implemented for the Tier 3 program. While both the 

current and Tier 3 certification fuels have a Reid vapor pressure of nominally 9.0 psi, EPA’s 

current certification test fuel contains no ethanol, whereas the Tier 3 certification fuel contains 

10 percent ethanol. Nevertheless, EPA believes this information is still useful in gaging the level 

of effort needed by manufacturers to comply with the Tier 3 standards. It is generally 

understood that ethanol can impact permeation emissions from the fuel tank and fuel lines to 

some degree, but the bulk of evaporative emissions are from diurnal emissions which are 

primarily a function of the Reid vapor pressure of the fuel which will be maintained at 9.0 psi 

and therefore should not be impacted by the presence of ethanol in the certification fuel. 

As can be seen from the figure, there are many families certified below the Tier 3 hotsoak plus diurnal standards. Of the nearly 450 evaporative families included in the analysis, 40 

percent had certification levels below the Tier 3 standards. Some of these families (~50) are 

certified to the more stringent PZEV standards, upon which the Tier 3 evaporative emission 

standards are based, but most of the families are not. However, the Tier 3 evaporative emission 

standards include a new canister bleed test that is not required under the current EPA regulations. 

(The families certified to the PZEV requirements are subject to a similar requirement and would 

likely meet that new canister bleed test requirement and longer useful life period without further 

modification.) Therefore, even though many families are certified below the Tier 3 evaporative 

emission standards, manufacturers would still need to make additional changes with many of the 

evaporative control systems to ensure compliance with the standards. We expect that 

 

G

 Note that LHDGVs are vehicles rated 8,501-14,000 lbs GVWR; HHDGVs are vehicles rated greater than 14,000 

lbs GVWR. 
1-62 

manufacturers would use the technologies discussed above and use allowances and ABT to 

minimize costs and assist in an orderly phase-in of compliant products. In 2013, the baseline 

certification values used for our analysis were 0.41 g HC/test for LDVs, LDT1/2s, 0.5 for 

LDT3/4 and MDPVs, and 0.63 for HDGVs. 

1.6.3 Assessment of California-certified PZEVs 

Based on the California Air Resources Board’s MY2013 certification list, EPA identified 

the vehicles certified by manufacturers to the PZEV requirements. As noted earlier, the Tier 3 

evaporative emission standards are very similar to the PZEV evaporative emission requirements 

and, as allowed with one of the options for MY2017, manufacturers could sell their evaporative 

emission compliant PZEV vehicles nationwide in MY2017. Manufacturers have certified over 

50 models of passenger cars and light-duty trucks to the PZEV requirements. EPA believes that 

manufacturer’s experience with PZEV technologies will assist them as they work to apply 

similar technologies across their fleets to comply with the Tier 3 evaporative emission standards. 

As described in more detail above, EPA expects manufacturers will employ a number of 

technologies to meet the Tier 3 standards. The anticipated control technologies to comply with 

the emission standards have already been included on many of the PZEVs. Table 1-15 shows the 

12 manufacturers and over 50 models certified to the PZEV standards in MY2013. Two other 

manufacturers certified PZEVs in previous model years as well. 
1-63 

Table 1-15 List of MY2013 Models Certified to CARB’s PZEV RequirementsH

Manufacturer Models

AUDI/VOLKSWAGEN Audi A3, Volkswagen GTI, Volkswagen Jetta, Volkswagen Golf, 

Volkswagen Jetta Sportwagen, Volkswagen Jetta, Volkswagen 

Jetta GLI, Volkswagen GTI, Volkswagen CC, Volkswagen Beetle, 

Volkswagen Passsat

BMW BMW 128i, BMW 328i, BMW 328Ci

CHRYSLER Chrysler 200, Dodge Avenger

FORD Ford Escape Hybrid, C-MAX Hybrid, 

Ford Focus, Ford Fusion Hybrid

GENERAL MOTORS Chevy Volt, Chevy Malibu Hybrid, Chevy Cruze, Chevy Sonic, 

Buick LaCrosse, Buick Regal, Cadillac ATS, Chevy Equinox, 

Chevy Impala, GMC Terrain

HONDA Honda Civic GX (CNG), Honda Civic Hybrid,

Honda CR-Z Hybrid, Honda Insight, Honda Insight Hybrid, Honda 

Accord

HYUNDAI Elantra, Tucson, Sonata, Sonata Hybrid 

KIA Kia Sportage, Kia Forte, Kia Forte ECO, Kia Forte KOUP,

Kia Optima Hybrid

MAZDA Mazda 3

MERCEDES Mercedes S400 Hybrid, Mercedes C300/ 

C350/E350/GLK350/E400 Hybrid

SUBARU Subaru Legacy, Subaru Outback Wagon, Subaru Forester , Subaru 

Impreza, Subaru XV Crosstrek

TOYOTA Toyota Prius, Toyota Camry, Toyota Camry Hybrid, Toyota Prius 

Hybrid

1.7 ORVR for Complete HDGVs over 10,000 lbs GVWR 

 This final rule includes onboard refueling vapor recovery (ORVR) requirements 

for complete HDGVs over 10,000 lbs but equal to or less than 14,000 lbs GVWR beginning in 

the 2018 model year. Due to the similarity of the vehicle chassis and fuel systems and the 

commonality of chassis production lines, manufacturers have all implemented ORVR hardware 

on complete Class 3 HDGVs (!0,001-14,000 lbs GVWR) since the 2006 MY when the ORVR 

phase-in covering Class 2b vehicles (8,501- 10,000 lbs GVWR) ended. Today, about XX percent 

of Class 3 vehicles are incomplete chassis. EPA is including this requirement in Tier 3 to ensure 

no backsliding and to give states the opportunity to claim the ORVR reductions for Tier 3 

vehicles in their SIPs. This is especially important to states removing Stage II vapor recovery. 

Furthermore, EPA is including ORVR requirements for any complete HDGVs over 14,000 lbs 

GVWR effective in the 2022 model year when the Tier 3 evaporative emissions phase-in ends. 

 

H

 See http://driveclean.ca.gov/searchresults_by_smog.php?smog_slider_value=9&x=12&y=12, downloaded on 

December 6, 2013. 
1-64 

While sales of HDGVs over 14,000 lbs are relatively low, today all would be classified as 

incomplete chassis for the purposes of the ORVR requirement. 

 EPA is not extending the ORVR requirement to incomplete HDGV chassis in this 

rule. There is no question of the basic technical feasibility of the requirement. However, 

manufacturers have stated that ORVR for incomplete HDGVs presents some system design and 

integration issues with regard to the larger fuel tanks and vehicles with two tanks but more 

importantly with regard to the activities of secondary manufacturers. Close coordination and 

installation instructions are needed to ensure that integrated ORVR/evaporative control systems 

are installed in an effective and safe manner. EPA estimates that incomplete HDGV sales are 

about (85,000) per year, but with their low fuel economy (~15 mpg) control of refueling 

emissions through ORVR may become important as Stage II vapor recovery is removed in ozone 

nonattainment areas. 

The ORVR requirements discussed above also apply to gaseous-fueled vehicles. EPA 

expects manufacturers to comply through the use of good design practices such as those 

specified in published consensus standards to address issues such as refueling connections and 

system integrity. 

1.8 Onboard Diagnostics for Vehicles less than 14,000 lbs GVWR 

As part of the Tier 3 final rule, EPA is incorporating by reference the July 31, 2013 

version of the California ARB OBD II regulations for vehicles equal to or less than 14,000 lbs 

GVWR. These requirements apply in the 2017 MY, at least two years after they must be met in 

California. As permitted in EPA regulations, manufacturers generally receive an Executive Order 

for OBD compliance from the CARB for each test group and EPA will accept that Executive 

Order as evidence that the vehicles covered by the test group meet CARB requirements and 

therefore meet the identical EPA requirements. Thus, in the case of the 2017 model year 

requirements for EPA, we expect manufacturers will already comply with these requirements 

before 2017 for their LEV III vehicles and have Executive Orders available. 

EPA is adding two requirements related to the leak standard. The first is a requirement 

that manufacturers demonstrate before production that their vehicle test groups’ OBD-based 

evaporative system monitor can detect the presence of a leak with an effective leak diameter at or 

above 0.020 inches, illuminate the MIL, and store the appropriate a confirmed diagnostic trouble 

codes. Such activity is normally done as part of the evaporative system leak monitor 

development and is demonstrated in the Production Vehicle Evaluation Testing program 

prescribed in 13 CCR 1968.2(j). However, if the OBD-based evaporative system leak monitor is 

to be used in IUVP, its performance needs to be certified before production begins instead of 

afterwards. Since this requirement is compatible with CARBs current regulations for OBD-based 

evaporative system leak-based monitoring and the Production Vehicle Evaluation Testing 

program and is phasing in with the leak standard, there should be no feasibility or lead time 

issues. 

EPA is also implementing a requirement that OBD systems revise the software so that a 

scan readable record is created which indicates if the OBD-based evaporative system leak 

monitor has run within the previous 750 miles and if so what was the result. The means by 
1-65 

which this record will be created and stored is being done in a manner compatible with SAE 

J1979 as suggested by the commenters. Since this requirement is phasing in with the leak 

standard, there should be no feasibility or lead time issues. 
1-66 

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Edition. John Wiley and Sons, Inc. 

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 The Effects of Ultra-Low Sulfur Gasoline on Emissions from Tier 2 Vehicles in the In-Use Fleet, EPA-420-R-14-

002.

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Technology Engines. SAE Technical Paper 2000-01-2019. 

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Application. SAE Technical Paper 2011-01-0300. 

15 Coordinating Research Council. 2003. “The Effect of Fuel Sulfur on NH3 and Other Emissions from 2000-2001 

Model Year Vehicles.” CRC Project No. E-60 Final Report. Accessed on the Internet on 12/4/2013 at the following 

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17 Manufacturers of Emission Controls Association. 2013. “The Impact of Gasoline Fuel Sulfur on Catalytic 

Emission Control Systems.” 

18 American Petroleum Institute. 2013. Supplemental Comments of the American Petroleum Institute. 
1-67 

19

 Vehicles that meet the cleanest emission standards by demonstrating very low cold start NMOG and NOx 

emissions and zero or approaching zero running NMOG and NOx emissions. 

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Edition. John Wiley and Sons, Inc. 

21 Luo, T. Gorte, R.J. (2003). A Mechanistic Study of Sulfur Poisoning of the Water-Gas-Shift Reaction Over 

Pd/Ceria.” Catalysis Letters, 85, Issues 3-4, pg. 139-146. 

22 Li-Dun, A., Quan, D.Y. (1990). “Mechanism of sulfur poisoning of supported Pd(Pt)/Al2O3 catalysts for H2-O2

reaction.” Applied Catalysis 61, Issue 1, pg. 219-234. 

23 Waqif, M., Bazin, P., Saur, O. Lavalley, J.C., Blanchard, G., Touret, O. “Study of ceria sulfation.” Applied 

Catalysis B: Environmental 11 (1997) 193-205. 

24 Bazin, P., Saur, O. Lavalley, J.C., Blanchard, G., Visciglio, V., Touret, O. “Influence of platinum on ceria 

sulfation.” Applied Catalysis B: Environmental 13 (1997) 265-274.

25 Heck, R.M., Farrauto, R.J. (2002). Chapter 6: Automotive Catalyst in Catalytic Air Pollution Control, 2nd Edition.

John Wiley and Sons, Inc. 

26 Luo, T. Gorte, R.J. (2003) A Mechanistic Study of Sulfur Poisoning of the Water-Gas-Shift Reaction Over 

Pd/Ceria. Catalysis Letters, 85, Issues 3-4, pg. 139-146. 

27 Beck, D.D., Sommers, J.W. (1995) Impact of sulfur on the performance of vehicle aged palladium monoliths. 

Applied Catalysis B: Environmental 6, 185-200. 

28 Beck, D.D., Sommers, J.W. (1995) Impact of sulfur on the performance of vehicle aged palladium monoliths. 

Applied Catalysis B: Environmental 6, 185-200. 

29 Maricq, M. M. Chace, R.E., Xu, N., Podsiadlik, D.H. (2002). The Effects of the Catalytic Converter and Fuel 

Sulfur Level on Motor Vehicle Particulate Matter Emissions: Gasoline Vehicles.” Environmental Science and 

Technology, 36, No. 2 pg. 276-282. 

30 The Effects of Ultra-Low Sulfur Gasoline on Emissions from Tier 2 Vehicles in the In-Use Fleet, EPA-420-R-14-

002.

31 See Preamble Section IV.A.6.c and Chapter 1 of the RIA (Section 1.2.3.2) for more details on this study and its 

results. 

32 See §86.1811-17 (LD) within the Tier 3 regulations. Tier 3 restrictions to commanded enrichment are also 

discussed in further detail within Section IV.A.4.c of this preamble. 

33 Tier 2 Regulatory Impact Analysis, EPA 420-R-99-023, December 22, 1999, last accessed on the Internet on 

12/04/2013 at the following URL: http://epa.gov/tier2

34 Chapter 6 of the Regulatory Impact Analysis for the Control of Hazardous Air Pollutants from Mobile Sources 

Final Rule, EPA 420-R-07-002, February 2007, last accessed on the Internet on 12/04/2013 at the following URL: 

http://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P1004LNN.PDF. 

35 The Effects of Ultra-Low Sulfur Gasoline on Emissions from Tier 2 Vehicles in the In-Use Fleet, EPA-420-R-14-

002.

36 Takei, Y., Kungasa, Y., Okada, M., Tanaka, T. Fujimoto, Y. (2000). Fuel Property Requirement for Advanced 

Technology Engines. SAE Technical Paper 2000-01-2019. 
1-68 

37 Ball, D., Clark, D., Moser, D. (2011). Effects of Fuel Sulfur on FTP NOX Emissions from a PZEV 4 Cylinder 

Application. SAE Technical Paper 2011-01-0300. 

38 The Effects of Ultra-Low Sulfur Gasoline on Emissions from Tier 2 Vehicles in the In-Use Fleet, EPA-420-R-14-

002.

39 Shapiro, E. (2009). National Clean Gasoline – An Investigation of Costs and Benefits. Published by the Alliance 

of Automobile Manufacturers. 

40 Chapter 6 of the Regulatory Impact Analysis for the Control of Hazardous Air Pollutants from Mobile Sources 

Final Rule, EPA 420-R-07-002, February 2007, last accessed on the Internet on 12/04/2013 at the following URL: 

http://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P1004LNN.PDF 

41 Ball, D., Clark, D., Moser, D. (2011). Effects of Fuel Sulfur on FTP NOX Emissions from a PZEV 4 Cylinder 

Application. SAE Technical Paper 2011-01-0300 

42 The Effects of Ultra-Low Sulfur Gasoline on Emissions from Tier 2 Vehicles in the In-Use Fleet, EPA-420-R-14-

002.

43 The NPRM modeling was based on analysis of 81 passenger cars and trucks. Since the NPRM, twelve additional 

Tier 2 vehicles were tested and included in the statistical analysis described in the docketed final report, examining 

the effect of sulfur on emissions from Tier 2 vehicles. The analysis based on the complete set of 93 Tier 2 vehicles 

is reflected in the results presented in this Section and the emissions modeling for FRM. 

44 The Effects of Ultra-Low Sulfur Gasoline on Emissions from Tier 2 Vehicles in the In-Use Fleet, EPA-420-R-14-

002.

45 Peer Review of the Effects of Fuel Sulfur Level on Emissions from the In-Use Tier 2 Vehicles, EPA-HQ-OAR2011-0135-1847. 

46 EPA In-Use Sulfur Report – Response to Peer-Review Comments, EPA-HQ-OAR-2011-0135-1848.

47 The Effects of Ultra-Low Sulfur Gasoline on Emissions from Tier 2 Vehicles in the In-Use Fleet, EPA-420-R-14-

002.

48 Ball, D., Clark, D., Moser, D. (2011). Effects of Fuel Sulfur on FTP NOX Emissions from a PZEV 4 Cylinder 

Application. SAE Technical Paper 2011-01-0300. 

49 American Petroleum Institute. 2013. Supplemental Comments of the American Petroleum Institute. Available in 

the docket for this final rule, docket no. EPA-HQ-OAR-2011-0135

50 The Effects of Ultra-Low Sulfur Gasoline on Emissions from Tier 2 Vehicles in the In-Use Fleet, EPA-420-R-14-

002. 

51 The make and model of the tested vehicles are Honda Crosstour, Chevrolet Malibu, Chevrolet Silverado, Ford 

Focus and Subaru Outback. 

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002.

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Greenhouse Gas Requirements.” Attachment 2: “Tier 3 Sulfur Test Program – Ford Motor Company Summary 

Report.” Available within EPA Docket for this final rule, EPA-HQ-2011-0135.
1-69 

54 Dominic DiCicco, Ford Motor Company. 2013. “Additional data as requested. RE: Ford Supplemental Comments 

on Tier 3.” Available within EPA Docket for this final rule, EPA-HQ-2011-0135.

55 See 77 FR 62840-62862, October 15, 2012; and Joint Technical Support Document: Final Rulemaking for 2017-

2025 Light-Duty Vehicle Greenhouse Gas Emission Standards and Corporate Average Fuel Economy Standards 

(EPA-420-R-12-901), August 2012, Chapter 3.4.1.7 - 3.4.1.8 (pages 3-88 – 3-95). 

56 Ford Motor Company, 2012. “Sustainability 2011/2012 – Improving Fuel Economy.” Accessed on the Internet on 

11/21/2013 at: http://corporate.ford.com/microsites/sustainability-report-2011-12/environment-products-planeconomy. Available within EPA Docket for this final rule, EPA-HQ-2011-0135.

57 Ford used the same tert-butyl sulfide fuel sulfur additives used within the EPA testing in IV.A.6.c and d. 

58Emissions at 30 ppm sulfur estimated assuming approximately linear emissions effects between 10, 26.5 and 30 

ppm gasoline sulfur levels. 

59 Ball, D., Clark, D., Moser, D. (2011). Effects of Fuel Sulfur on FTP NOX Emissions from a PZEV 4 Cylinder 

Application. SAE Technical Paper 2011-01-0300. Available in the docket for this final rule. 

60 American Petroleum Institute. 2013. Supplemental Comments of the American Petroleum Institute. Available in 

the docket for this final rule, docket no. EPA-HQ-OAR-2011-0135

61 Add citation to document number and docket number for Tier 3 RIA 

62 U.S. Code of Federal Regulations, Title 40, §86.1823–08 “Durability demonstration procedures for exhaust 

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63 Heck, R.M., Farrauto, R.J. (2002). Chapter 6: Automotive Catalyst in Catalytic Air Pollution Control, 2nd Edition.

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69 Hattori, M., Inoue, T., Mashiki, Z., Takenaka, A., Urushihata, H., Morino, S., Inohara, T. “Development of 

Variable Valve Timing System Controlled by Electric Motor.” SAE Technical Paper 2008-01-1358.

70 Ball, D., Zammit, M., Wuttke, J., Buitrago, C. “Investigation of LEV-III Aftertreatment Designs.” SAE Technical 

Paper 2011-01-0301.
1-70 

71 Serrano, D., Lavy, J., Kleeman, A., Zinola, S., Dumas, J., Le Mirronet, S., Heitz, D. “Post Oxidation Study During 

Secondary Exhaust Air Injection for Fast Catalyst Light-Off.” SAE Technical Paper 2009-01-2706. 

72 Lee, D., Heywood, J. “Effects of Secondary Air Injection During Cold Start of SI Engines.” SAE Technical Paper 

2010-01-2124. 

73 Sano, K., Kawai, T., Yoshizaki, S., Iwamoto, Y. “HC Adsorber System for SULEVs of Large Volume 

Displacement.” SAE Technical Paper 2007-01-0929.

74 McDonald, J.F., Schenk, C., Sanchez, L.J., Nelson, B.J. “Testing of Catalytic Exhaust Emission Control Systems 

Under Simulated Locomotive Exhaust Conditions.” SAE Technical Paper No. 2011-01-1313. 

75 U.S. Code of Federal Regulations, Title 40, § 86.1823–08 Durability demonstration procedures for exhaust 

emissions. 

76 Christianson, Michael G. “Impact of Lubricating Oil Condition on Exhaust Particulate Matter Emissions from 

Light Duty Vehicles” SAE Technical Paper No. 2010-01-1560. 

77 NIOSH Reference Method 5040 - Elemental Carbon (Diesel Particulate Matter). NIOSH Manual of Analytical 

Methods (NMAM), Fourth Edition, 2003. 

78 Sobotowski, R. (February, 2013). Test Program to Establish LDV Full Useful Life PM Performance. 

Memorandum to the docket. 

79 Zhao, F. “Technologies for Near-Zero Gasoline-Powered Vehicles.” Society of Automotive Engineers, 2007 and 

“advanced Developments in Ultra-Clean Gasoline Powered Vehicles”. PT-104. Society of Automotive Engineers. 

2004.

80 “Evaporative Emission Control Technologies for Gasoline Powered Vehicles”, Manufacturers of Emission 

Controls Association, December, 2010. 

81 See Chapter 2.6 of the RIA for the rule, 2017 and Later Model Year Light-Duty Vehicle Greenhouse Gas 

Emissions and Corporate Average Fuel Economy Standards, .Fleet wide projections in Table 1-11 are based on 

weightings of the portions of V-4, V-6, and V-8s expected to be converted to GDI. 

82 Leffel,J, Abdolhosseini, R.,(2005) SAE Paper 2005-01-1104, “Requirements Setting, Optimization, and “Best Fit” 

Application of AIS Hydrocarbon Adsorption Devices for Engine Evaporative Emissions Breathing Loss Control”. 

83 Lebowitz, J., Lovette,J., Chan,C., and Frich,D., (2005) SAE Paper 2005-01-0113, “Activated Carbon Coated 

Polymeric Foam for Hydrocarbon Vapor Adsorption”. 

84 Williams,R. Clontz, C., (2001) SAE Paper 2001-01-0733, “Impact and Control of Canister Bleed Emissions”. 

85 Clontz.,R.,Elum,.M.,McRare,P.,Williams,R., (2007) SAE Paper 2007-01-1929, “Effects of Low Purge Vehicle 

Applications and Ethanol Containing Fuels on Evaporative Emissions Canister Performance”. 
2-1

Chapter 2 Vehicle Program Costs 

2.1 Changes to Vehicle Costs between Proposed and Final Rules 

 We have made several changes to vehicle program costs since the proposal, but two 

changes have significant impacts on the final rule costs and help to explain the large reduction in 

cost estimates between proposal and final rule. The first of these significant changes involves 

the catalyst platinum group metal (PGM) loading costs. As commenters pointed out, the cost 

estimates in the proposal have become dated, as they were based largely on four-year-old 

estimates of the CARB LEVIII program. For this final rule, we have developed a more robust 

catalyst loading cost estimate using a methodology suggested by one commenter.1 This more 

robust estimate results in lower costs than estimated in the proposal. 

The second significant contributer to reduced final rule cost estimates is the use of the 

MY 2017-2025 fleet mix projected to result from the most recent GHG and fuel economy rules. 

That projected fleet mix shows a large percentage of four-cylinder engines, which are less costly 

to modify to achieve Tier 3 compliance than the proposal’s projected MY 2012-2016 fleet mix, 

which included many more V-configuration six-cylinder (V6) and eight-cylinder (V8) engines. 

We mentioned in the preamble to the proposal our intention to use the projected MY 2017-2025 

fleet for our final rule cost analysis (see 78 FR 29970). 

We have made many other updates to the analysis for this final rule. For example, we 

reviewed the MY2013 certification database to evaluate the certified emissions levels of the 

fleet. We found that many vehicles are already being certified with emissions levels that would 

meet final Tier 3 standards. Further, many vehicles have certified emission levels that are 70% 

of the 0.30 g/mi NOx+NMOG standard, meaning that sufficient compliance margin exists for 

those vehicle to comply with Tier 3 without any additional costs. Our final rule estimates no 

exhaust emission-related Tier 3 costs for these vehicles (they still incur evaporative emissionrelated costs, discussed below). 

We have also concluded that active HC adsorbers, which we projected for use on some 

vehicles in the proposal, are not likely to be used. Instead, as we discuss in Section 2.3.6, those 

vehicles will probably use a passive HC adsorber. The passive HC adsorber is considerably less 

costly. We have also decreased our evaporative emission control costs, in part because of the 

high penetration of gasoline engines with direct injection projected by the MY 2017-2025 GHG 

and fuel economy rules. Direct injection removes a large source of evaporative emissions and, 

thus, means fewer vehicles need to add certain evaporative control technologies. We have also 

decreased the penetration rates of secondary air injection in the later years of the program, for 

reasons described below. Lastly, we have modified very slightly our indirect cost markups to 

account for the fact that most of the research and development efforts required of auto makers 

are in response to CARB’s LEVIII rule and need not be conducted again for Tier 3 compliance. 

We have made some changes that have increased costs, although these are smaller than 

those that have decreased costs so, on net, estimated vehicle-level costs are lower than in the 

proposal. One such change was to double the engine calibration costs (from roughly $2/vehicle 

to $5/vehicle), to cover expected calibration efforts associated with PM control on direct injected 
2-2

gasoline engines. We discuss this in more detail in Section 2.3.5, below. We have also 

increased the penetration rates of the technology we term “optimized thermal management” for 

some vehicle categories. We discuss our rationale for this change in Section 2.5, below. Another 

change was to update all costs from 2010 dollars to 2011 dollars.A 

With respect to total program costs, the significant change since proposal was to exclude 

costs incurred on vehicles sold in all states (California and elsewhere) that have adopted the 

California LEVIII program. As a result, our estimated costs per vehicle are applied to millions 

fewer vehicles in the final rule, thus making the total program costs considerably lower. And 

finally, we have included operating savings (fuel savings) associated with avoiding the loss of 

fuel that would have otherwise evaporated absent the new Tier 3 controls. The otherwise 

evaporated fuel is ultimately used to propel the vehicle, thus providing a savings to the 

consumer. We discuss operating costs in Section 2.6, below. 

2.2 General Methodology 

Although the increase in standard stringency is substantial for the vehicles affected by 

this final rule, we do not expect that the associated vehicle costs will be high. Our analysis 

shows that the federal fleet is already demonstrating actual emissions performance that is much 

cleaner than the level to which it is currently being certified. In fact, many MY2013 vehicles 

were certified to levels below the 30 mg combined NMOG+NOx standard, some of which were 

certified below 70 percent of the 30 mg standard, an important level since it provides necessary 

compliance margin. Although the vehicles that make up the federal light-duty fleet are capable 

of meeting lower standards there is no impetus for vehicle manufacturers to certify their 

respective fleets to anything lower than the current requirements. In addition, we anticipate that 

not every technology will be required on all vehicles to meet the standards. While catalyst 

loading and engine calibration changes will most likely be applied on all vehicles, only the most 

difficult powertrain applications will require very expensive emissions control solutions such as 

secondary air injection. We expect that manufacturers will implement emission control solutions 

as a function of increasing cost and will avoid implementing very expensive designs whenever 

possible. 

To determine the cost for vehicles, we first determined which technologies were most 

likely to be applied by vehicle manufacturers to meet the standards. These technologies are then 

combined into technology packages which reflect vehicle design attributes that directly 

contribute to a vehicle’s emissions performance. The attributes considered include vehicle type: 

car or truck, number of cylinders, engine displacement and the type of fuel used, either gas or 

diesel. We also created separate packages for light-duty and heavy-duty trucks and vans. 

Once we know the individual technologies that will likely be used, our next step is to 

estimate direct manufacturing costs (DMC) for those technologies. As part of this process, we 

 

A

 We have updated 2010 dollars to 2011 dollars using the Gross Domestic Product (GDP) price deflator as reported 

by the Bureau of Economic Analysis on May 30, 2013. The factor used, taken from Line 1 of Table 1.1.4 Price 

Indexes for Gross Domestic Product was 1.035 to convert from 2009$ and 1.021 to convert from 2010$. For 

example, to convert from 2010$ to 2011$, we calculated the (value in 2010$)x1.021=(value in 2011$). 
2-3

determine the model year for which our estimated cost is deemed valid—i.e., if a widget is 

estimated to cost $100, is that valid today when none have been sold or after a few years when 

thousands or millions have been sold? This “cost basis” serves as the point in time where 

learning effects—discussed below—are set to neutral. In other words, beyond that cost basis, 

learning effects serve to decrease the DMC of the technology and, in contrast, prior to that cost 

basis, the lack of any learning effects serves to increase the DMC of the technology. 

The next step is to apply an indirect cost multiplier (ICM) to estimate the indirect cost of 

the technology to the auto maker. This is the same process used in the recent MY 2012-2016 

and MY 2017-2025 GHG rules, and the proposal for this rule. The cost calculation approach 

presumes that the Tier 3 technologies will be purchased by original equipment manufacturers 

(OEMs) from Tier 1 suppliers. So, while the DMC estimates include the indirect costs and 

profits incurred by the supplier, the ICMs we apply are meant to cover the indirect costs incurred 

by OEMs to incorporate the new technologies into their vehicles and to cover the profits that the 

OEM must earn to remain viable. We discuss ICMs and indirect costs in more detail in Section 

2.2.2. 

We have also estimated costs associated with construction of new PM testing facilities. 

We have included these costs separately, rather than as part of the ICMs, since the work 

conducted to derive our ICMs (details below) did not include new facility construction by 

OEMs. We could have included a new factor within the ICM, but believed a separate analysis of 

these costs would be more transparent and allows an easier presentation of them as a line item 

cost in our analysis. We present the facility costs in Section 2.7.

The next step is to determine the penetration rate of each of the technologies. As noted 

above, we do not believe that each of the Tier 3 technologies will be applied to all 

engines/vehicles across the board. An obvious example of this would be the evaporative 

emission control technologies that will be added to gasoline vehicles but not to diesel vehicles.B

We expect many of the technologies to be used on only a portion of the Tier 3 fleet. Further, the 

Tier 3 standards are not implemented 100% in MY2017 and, instead, increase in stringency from 

MY2017 through MY2025. Additionally, and new for this final rule, we know that many 

vehicles are already being certified with emissions below the Tier 3 30 mg NMOG+NOx level, 

even if we give due consideration to compliance margin. Penetration rates and the resultant 

technology costs (i.e., inclusive of the penetration rates) are presented below in Section 2.5

where we also sum these costs to arrive at vehicle package costs. 

We have also estimated operating costs associated with the evaporative emission 

standards and present them in Section 2.6.

The final step is to calculate the vehicle program costs to arrive at annual costs of the Tier 

3 vehicle program. We present the vehicle program costs in Section 2.7.

 

B

 Diesel fuel has very low volatility so the fuel does not vaporize the way gasoline does. 
2-4

2.2.1 Direct Manufacturing Costs 

In making our estimates for both direct manufacturing cost (DMC) and application of 

technology, we have relied on our own technology assessments. These assessments include 

publicly available information, such as that developed by the California Air Resources Board, as 

well as confidential information supplied by individual manufacturers and suppliers.2 We have 

also considered the results of our own in-house testing.3 The technology packages that we 

developed represent what we consider to be the most likely average emissions control solution 

for each vehicle type. 

In general, we expect that the majority of vehicles will be able to comply with the Tier 3 

standards through refinements of current emissions control components and systems. Some 

vehicles, for example large trucks with large displacement engines, in particular LDT3s and 

LDT4s, may require additional emission controls such as HC adsorbers. Overall, smaller lighterweight vehicles will require less extensive improvements than larger vehicles and trucks. 

Specifically, we anticipate a combination of technology upgrades for reducing exhaust emissions 

as described below. 

2.2.2 Indirect Costs 

We are using an approach to estimating indirect costs that is consistent with that used in 

our recent 2017-2025 Greenhouse Gas (GHG) final rule.4

 Rather than a traditional retail price 

equivalent markup (RPE), as described below we are marking up DMCs using an indirect cost 

multiplier (ICM). Furthermore, we are applying the ICMs in a manner that differs from the 

traditional RPE approach in which the DMC would be multiplied by the RPE factor in any given 

year. As such, as the DMC decreased with learning, the product of the RPE factor and the DMC 

decreased along with it. However, we have more recently decided that learning impacts 

(discussed below) should be applied only to the DMC and not to the indirect costs. Our 

approach with ICMs, consistent with the recent 2017-2025 GHG final rule, is to determine the 

indirect costs based on the initial value of direct costs and then hold that constant until the longterm ICM is applied. This is done for all ICM factors except warranties, which are influenced by 

the learned value of direct costs.

The ICMs used in this final rule are the same as those used in the proposal with one 

exception. For this final rule, we have adjusted the R&D portion of the indirect costs to account 

for the fact that the research for Tier 3 compliance and a good portion of the development have 

been done or are being done in response to the California LEV III rule. Because that research 

and development work is attributable to the LEV III rule, we believe it is double counting to also 

consider it in the final Tier 3 costs. Below, we discuss this change in greater detail along with 

providing a comparison between ICMs in the proposal and this final rule. 

To produce a unit of output, auto manufacturers incur direct and indirect costs. Direct 

costs include the cost of materials and labor costs. Indirect costs may be related to production 

(such as research and development [R&D]), corporate operations (such as salaries, pensions, and 

health care costs for corporate staff), or selling (such as transportation, dealer support, and 

marketing). Indirect costs are generally recovered by allocating a share of the costs to each unit 

of goods sold. Although it is possible to account for direct costs allocated to each unit of goods 
2-5

sold, it is more challenging to account for indirect costs allocated to a unit of goods sold. To 

make a cost analysis process more feasible, markup factors, which relate total indirect costs to 

total direct costs, have been developed. These factors are often referred to as retail price 

equivalent (RPE) multipliers. 

Cost analysts and regulatory agencies including EPA have frequently used these 

multipliers to estimate the resultant impact on costs associated with manufacturers’ responses to 

regulatory requirements. The best approach to determining the impact of changes in direct 

manufacturing costs on a manufacturer’s indirect costs would be to actually estimate the cost 

impact on each indirect cost element. However, doing this within the constraints of an agency’s 

time or budget is not always feasible, and the technical, financial, and accounting information to 

carry out such an analysis may simply be unavailable. 

RPE multipliers provide, at an aggregate level, the relative shares of revenues (Revenue = 

Direct Costs + Indirect Costs + Net Income) to direct manufacturing costs. Using RPE 

multipliers implicitly assumes that incremental changes in direct manufacturing costs produce 

common incremental changes in all indirect cost contributors as well as net income. A concern 

in using the RPE multiplier in cost analysis for new technologies added in response to regulatory 

requirements is that the indirect costs of vehicle modifications are not likely to be the same for 

different technologies. For example, less complex technologies could require fewer R&D efforts 

or less warranty coverage than more complex technologies. In addition, some simple 

technological adjustments may, for example, have no effect on the number of corporate 

personnel and the indirect costs attributable to those personnel. The use of RPEs, with their 

assumption that all technologies have the same proportion of indirect costs, is likely to 

overestimate the costs of less complex technologies and underestimate the costs of more 

complex technologies. 

To address this concern, the agency has developed modified multipliers. These 

multipliers are referred to as indirect cost multipliers (ICMs). In contrast to RPE multipliers, 

ICMs assign unique incremental changes to each indirect cost contributor 

ICM = (direct cost + adjusted indirect cost + profit)/(direct cost) 

Developing the ICMs from the RPE multipliers requires developing adjustment factors 

based on the complexity of the technology and the time frame under consideration. The ICMs 

were developed in a peer-reviewed report from RTI International and were subsequently 

discussed in a peer-reviewed journal article.5 Note that the cost of capital (reflected in profit) is 

included because of the assumption implicit in ICMs (and RPEs) that capital costs are 

proportional to direct costs, and businesses need to be able to earn returns on their investments. 

The capital costs are those associated with the incremental costs of the new technologies. 

As noted above, for the analysis supporting the Tier 3 proposed rulemaking, EPA used 

the ICM approach but made some changes to both the ICM factors and to the method of applying 

those factors to arrive at a final cost estimate since the ICM work was originally done by RTI. 

Both of these changes make the ICMs used in this analysis consistent with those used in the MY 

2017-2025 GHG final rule. The first of these changes was done in response to continued 
2-6

thinking about how past ICMs have been developed and what are the most appropriate data 

sources to rely upon in determining the appropriate ICMs. We have a detailed discussion of this 

change in Chapter 3 of the joint TSD supporting the 2017-2025 GHG rule.6 Because that 

discussion is meant to present changes made in the time between the original RTI work (and the 

MY 2012-2016 GHG final rule) and the MY 2017-2025 GHG final rule, the full text is not really 

relevant in the context of Tier 3. The second change has been done both due to staff concerns 

and public feedback suggesting that the agency was inappropriately applying learning effects to 

indirect costs via the multiplicative approach to applying the ICMs. This change is detailed 

below because it is critical to understanding how indirect costs are calculated in the context of 

Tier 3. 

Table 2-1 shows the ICMs used in the proposal. As noted, these ICMs are consistent 

with those used in our recent MY 2017-2025 GHG final rule. Despite the fact that these ICMs 

were developed with GHG technologies in mind, we are using them here to estimate indirect 

costs associated with criteria emission control technology. We believe the ICMs are applicable 

here because, as with the GHG requirements, the technologies considered in Tier 3 are or can be 

provided to the auto maker by suppliers and their integration into the end vehicle involves the 

same sorts of methods and demands as integrating GHG improving technologies. 

Table 2-1 Indirect Cost Multipliers Used in the Proposal 

Complexity Near term Long term

Low 1.24 1.19

Medium 1.39 1.29

High1 1.56 1.35

High2 1.77 1.50

The second change noted above made to the ICMs has to do with the way in which they 

are applied. In the MY 2012-2016 GHG final rule, we applied the ICMs, as done in any analysis 

that relied on RPEs, as a pure multiplicative factor. This way, a direct manufacturing cost of, 

say, $100 would be multiplied by an ICM of 1.24 to arrive at a marked up technology cost of 

$124. However, as learning effects (discussed below) are applied to the direct manufacturing 

cost, the indirect costs are also reduced accordingly. Therefore, in year two the $100 direct 

manufacturing cost might reduce to $97 and the marked up cost would become $120 ($97 x 

1.24). As a result, indirect costs would be reduced from $24 to $23. Given that indirect costs 

cover many things such as facility-related costs, electricity, etc., it is perhaps not appropriate to 

apply the ICM to the learned direct costs, at least not for those indirect cost elements unlikely to 

change with learning. EPA believes that it is appropriate to allow only warranty costs to 

decrease with learning since warranty costs are tied to direct manufacturing costs (warranty 

typically involves replacement of actual parts which should be less costly with learning). The 

remaining elements of the indirect costs should remain constant year-over-year, at least until 

some of those indirect costs, such as R&D, are no longer attributable to the rulemaking effort 

that imposed them. 

As a result, the ICM calculation has become more complex than originally devised by 

RTI. We must first establish the year in which the direct manufacturing costs are considered 

“valid.” For example, a cost estimate might be considered valid today, or perhaps not until high 
2-7

volume production is reached—which will not occur until MY2015 or later. That year is known 

as the base year for the estimated cost. That cost is the cost used to determine the “nonwarranty” portion of the indirect costs. For example, the non-warranty portion of the medium 

complexity ICM in the short-term is 0.343 (the warranty versus non-warranty portions of the 

ICMs are shown in Table 2-2). Consider a technology with an estimated direct manufacturing 

cost of $70 and valid in MY2015. For this technology, the non-warranty portion of the indirect 

costs would be $24.01 ($70 x 0.343). This value would be added to the learned direct 

manufacturing cost for each year through 2018, the hypothetical last year of short term indirect 

costs for this technology. Beginning in 2019, when long-term indirect costs begin, the additive 

factor would become $18.13 ($70 x 0.259). Additionally, the $70 cost in MY2015 would 

become $67.90 in MY2016 due to learning (assuming a 3% learning-by-doing cost reduction 

from MY2015 to MY2016, or $70 x (1-3%)). So, while the warranty portion of the indirect costs 

would be $3.15 ($70 x 0.045) in MY2015, the warranty portion would decrease to $3.06 ($67.90 

x 0.045) in 2016 as warranty costs decrease with learning. The resultant indirect costs of the 

example technology would be $27.16 ($24.01+$3.15) in MY2015 and $27.07 ($24.01+$3.06) in 

MY2016, and so on for subsequent years. 

Table 2-2 Warranty and Non-Warranty Portions of ICMs used in the Proposal 

Near term Long term

Complexity Warranty Non-warranty Warranty Non-warranty

Low 0.012 0.230 0.005 0.187

Medium 0.045 0.343 0.031 0.259

High1 0.065 0.499 0.032 0.314

High2 0.074 0.696 0.049 0.448

With that as background, we have made minor changes relative to the proposal to the 

ICMs used in this final rule. We have made this change because we believe it is appropriate that 

the Tier 3 rule not incur costs for research and development that is being incurred by OEMs to 

comply with California’s LEV III. As such, we have considered half the R&D portion of the 

ICM to be research and half to be development. Further, we have set the research portion to 0.0 

and the development portion to 50% of the proposal level. These changes mean that our final 

rule cost estimates consider all research dollars and 50% of all development dollars to have been 

spent in complying with LEV III. The R&D portion of the proposal’s ICMs ranges from 3.6% to 

7% of total technology costs depending on complexity level. The changes described here result 

in the R&D portion ranging from 1% to 2% of total technology costs. In other words, a $100 

DMC would have resulted in a $124 total cost in the proposal (at low complexity in the near 

term, the ICM being 1.24). In the final rule, the $100 DMC will result in a $121 total cost (at 

low complexity in the near term, the ICM being 1.21). 

Table 2-3 shows the resultant warranty and non-warranty factors used in the final rule. 

These values are used in the final rule instead of those shown in Table 2-2. 
2-8

Table 2-3 Warranty and Non-Warranty Portions of ICMs used in the Final Rule 

Near term Long term

Complexity Warranty Non-warranty Warranty Non-warranty

Low 0.012 0.196 0.005 0.172

Medium 0.045 0.282 0.031 0.222

High1 0.065 0.417 0.032 0.301

High2 0.074 0.543 0.049 0.365

2.2.3 Cost Reduction through Manufacturer Learning 

For this final rule, we have not changed our estimates of learning and how learning will 

impact costs going forward from what was employed in the proposal. We consider there to be 

one learning effect—learning by doing—which results in cost reductions occurring with every 

doubling of production. In the past, we have referred to volume-based and time-based learning. 

Those terms were meant only to denote where on the volume learning curve a certain technology 

was—“volume-based learning” meant the steep portion of the curve where learning effects are 

greatest, while “time-based learning” meant the flatter portion of the curve where learning effects 

are less pronounced. Unfortunately, that terminology led some to believe that we were 

implementing two completely different types of learning—one based on volume of production 

and the other based on time in production. We now use new terminology—steep portion of the 

curve and flat portion of curve—simply meant to make clear that there is one learning curve and 

some technologies can be considered to be on the steep portion while others are well into the 

flatter portion of the curve. This updated terminology was described in the recent heavy-duty 

GHG final rule (see 76 FR 57320) and is entirely consistent with our approach used in the recent 

MY 2017-2025 GHG final rule (see 77 FR 62711). These two portions of the volume learning 

curve are shown in Figure 2-1. 
2-9

Figure 2-1 Steep and Flat Portions of the Volume Learning Curve 

For some of the technologies considered in this analysis, manufacturer learning effects 

would be expected to play a role in the actual end costs. The “learning curve” or “experience 

curve” describes the reduction in unit production costs as a function of accumulated production 

volume. In theory, the cost behavior it describes applies to cumulative production volume 

measured at the level of an individual manufacturer, although it is often assumed—as both 

agencies have done in past regulatory analyses—to apply at the industry-wide level, particularly 

in industries like the light duty vehicle production industry that utilize many common 

technologies and component supply sources. We believe there are indeed many factors that 

cause costs to decrease over time. Research in the costs of manufacturing has consistently 

shown that, as manufacturers gain experience in production, they are able to apply innovations to 

simplify machining and assembly operations, use lower cost materials, and reduce the number or 

complexity of component parts. All of these factors allow manufacturers to lower the per-unit 

cost of production. We refer to this phenomenon as the manufacturing learning curve. 

EPA included a detailed description of the learning effect in the MY 2012-2016 and 

2017-2025 light-duty GHG rules, the more recent heavy-duty GHG rule and the proposal to this 

rule.7

 In past rulemaking analyses, EPA has used a learning curve algorithm that applied a 

learning factor of 20 percent for each doubling of production volume. EPA has simplified the 

approach by using an “every two years” based learning progression rather than a pure production 

volume progression (i.e., after two years of production it was assumed that production volumes 
2-10

would have doubled and, therefore, costs would be reduced by 20 percent).C We apply learning 

effects on the steep portion of the learning curve for those technologies considered to be newer 

technologies likely to experience rapid cost reductions through manufacturer learning, and 

learning effects on the flat portion learning curve for those technologies considered to be more 

mature technologies likely to experience only minor cost reductions through manufacturer 

learning. As noted above, the steep portion learning algorithm results in 20 percent lower costs 

after two full years of implementation (i.e., the MY2016 costs would be 20 percent lower than 

the MYs 2014 and 2015 costs). Once two steep portion learning steps have occurred, flat portion 

learning at 3 percent per year becomes effective for 5 years. Beyond 5 years of learning at 3 

percent per year, 5 years of learning at 2 percent per year, then 5 at 1 percent per year become 

effective. 

For this analysis, learning effects are applied to all technologies because, while most are 

already widely used, the technologies would undergo changes relative to their Tier 2 level 

design, and we believe auto makers will find ways to reduce costs in the years following 

introduction. The steep portion learning algorithm has not been applied to any technologies in 

this analysis because we believe that the technologies considered in this analysis have already 

experienced the large cost reductions due to learning in the early years of use. The learning 

algorithm applied to each technology and the applicable timeframes are summarized in Table 

2-4.

Table 2-4 Learning Effect Algorithms Applied to Technologies Used in this Analysis 

Technology Steep learning Flat learning No learning

Catalyst Loading 2015-2025

Optimized Close-coupled Catalyst 2015-2025

Optimized Thermal Management 2015-2025

Secondary Air Injection 2015-2025

Engine Calibration 2015-2025

Hydrocarbon Adsorber 2015-2025

Evaporative Emissions Controls 2015-2025

Selective Catalytic Reduction Optimization 2015-2025

 

C

 To clarify, EPA has simplified the steep portion of the volume learning curve by assuming that production 

volumes of a given technology will have doubled within two years time. This has been done largely to allow for a 

presentation of estimated costs during the years of implementation, without the need to conduct a feedback loop that 

ensures that production volumes have indeed doubled. The assumption that volumes have doubled after two years is 

based solely on the assumption that year two sales are of equal or greater number than year one sales and, therefore, 

have resulted in a doubling of production. This could be done on a daily basis, a monthly basis, or, as we have done, 

a yearly basis. 
2-11

2.3 Individual Technology Costs 

2.3.1 Catalyst Platinum Group Metal (PGM) Loading 

Increased application of precious metals in the catalyst is expected to be one of the 

primary means of mitigating NMOG and NOx to meet the Tier 3 standards. Increasing the 

catalyst PGM loading results in greater catalyst efficiency. In the proposal, we noted that vehicle 

manufacturers and suppliers had supplied Confidential Business Information (CBI) that estimates 

the cost of increasing the PGM loading and modifications to increase the surface area within the 

catalyst. These costs ranged from $80 to $260 and were estimated as being incremental to an 

existing Tier 2 Bin 5 compliant vehicle. We went on to state that we believed that the 

incremental costs for PGM loading would be less than those CBI estimates we received, and we 

estimated the costs to be $60, $80, and $100 for an I4, V6 and V8, respectively (all in 2009 

dollars). 

For this final rule, we have updated our PGM loading costs using a more robust approach 

tailored after the methodology presented by ICCT in a recent SAE paper.8 In that paper, ICCT 

outlines a costing methodology based on PGM loads, swept volume ratio (the ratio of catalyst 

volume to engine displacement), and some equations that can be used to estimate catalyst 

washcoating and canning costs based on catalyst volume. This approach is actually similar to an 

approach used by EPA in past cost analyses that focused heavily on aftertreatment device costs.9

We have made these changes for several reasons, but primarily because some commenters 

believed our cost estimates were dated, having relied heavily on the CARB LEVIII analysis now 

several years old. We agreed with this assessment and also liked the ICCT methodology since it 

allows us to provide more detail behind the estimates and to be transparent with the estimate 

allowing others to adjust things in ways they may believe make more sense. 

In their recent SAE paper, ICCT estimates the PGM loading of Tier 2 catalysts at 0.1 g/L 

Platinum (Pt), 1.6 g/L Palladium (Pd) and 0.1 g/L Rhodium (Rh). Further, they estimate that the 

swept volume ratio of Tier 2 catalysts is 1.0 (i.e., the catalyst volume equals the engine 

displacement). They also provide 3 equations that can be used to estimate catalyst substrate, 

washcoating and canning costs. Those equations are shown in Table 2-5. ICCT also included 

labor costs in a manner described as consistent with past EPA work.D ICCT notes that their 

methodology considers the catalyst system as a unit and does not distinguish between close 

coupled and underfloor catalysts. This was done in an effort to simplify the approach even 

though close coupled and underfloor catalysts may well have different loadings. 

 

D

 ICCT references the source as EPA’s Nonroad Tier 4 Regulatory Impact Analysis (EPA420-R-04-007, May 

2004). In that analysis, a labor rate of $30/hour (2003$) was used. Updating that to 2011$ using the GDP price 

deflator mentioned earlier results in a labor rate of $36/hour for this analysis. 
2-12

Table 2-5 ICCT Equations for Estimating Catalyst Component Costs (2011$) 

Component ICCT Cost equation

Catalyst substrate $6.0xVol+$1.92

Catalyst washcoat $5.0xVol

Catalyst canning $2.4xVol

Note: Vol = catalyst volume

Source: SAE 2013-01-0534

In their comments, ICCT notes recent research by Honda and Johnson Matthey showing 

PGM usage could be reduced by 25% with respect to current Tier 2 Bin 5 levels and still provide 

LEVIII SULEV30 compliance (i.e., Tier 3 Bin 30). This could be done using an improved 

layered catalyst and improved oxygen storage capacity (OSC) via adding zirconia along with 

ceria. ICCT also notes research by Umicore showing LEV70 to SULEV30 reductions via a 32% 

increase in PGM loading on one vehicle and only 16% increase on another. ICCT notes that 

these two vehicles did increase catalyst volume between 40% and 200% which would serve to 

increase costs. In that study, Umicore stresses the importance of a combined NMOG+NOx 

standard versus separate NMOG and NOx standards noting that the combined standard is much 

less demanding.10 This is discussed in more detail in Chapter 1 of this RIA, but the combined 

standard provides much more flexibility to auto makers than does separate standards, thus 

allowing them to control costs much more effectively. What is important here is that the 

Umicore catalyst volume increases and subsequent costs were done assuming separate standards 

(the California PZEV standards), not a combined standard. Also important in the Umicore study 

was that the PZEV catalysts made no use of Pt for NMOG control, relying only on Pd for 

NMOG control and Rh for NOx control. This is important because Pd is, generally, less costly 

and exhibits less price volatility than Pt. All told, the increased costs in the Umicore study—

again, for separate, not a combined standard—were on the order of $15-$46, well below our 

NPRM costs of $60 to $100 (both in 2009$). ICCT also provided their assessment that a 20% 

increase in PGM loading is the most that would be required for Tier 3. 

We believe that, in general, catalyst loading will increase in the front most portion of the 

catalyst system but not necessarily the entire system. We believe this, in part, because of the 

strong cases made by commenters and in the recent studies mentioned. We also believe this 

because the Tier 3 standards are, in effect, cold start emission standards, and we believe that the 

catalyst loading will be increased for the purpose of controlling cold start emissions. This can be 

most effectively done by adding metals to the portion of the catalyst system that will reach 

operating temperatures most quickly—i.e., that portion closest to the point where gases are 

exhausted from the engine. As such, we have estimated that Pd loading will increase 50% and 

Rh loading 20% but only in the front most 50% of the catalyst system. We have also estimated 

that Pt will be eliminated in favor of Pd, and that total catalyst volume (swept catalyst volume, 

SVR) will increase by 20%. 
2-13

Using these metrics, the equations shown in Table 2-5 and the price of PGMs,E we can 

calculate the increased cost of any Tier 3 catalyst relative to its Tier 2 counterpart provided we 

know the Tier 2 catalyst system’s volume. For fleet average incremental costs, we need both the 

Tier 2 catalyst volumes for each vehicle in the fleet and the sales of each vehicle to get a proper 

sales weighted average catalyst cost. To get these, we have used the baseline file used in support 

of our recent GHG/CAFE final rule for MY 2017-2025. That baseline file represented the 2008 

model year fleet and has in it the engine displacement (i.e., the catalyst volume since we consider 

the SVR of Tier 2 catalysts to be 1.0) and the projected sales of each vehicle model in the lightduty fleet for MY 2012 through 2025. Using that fleet in conjunction with the projected 

MY2013 sales, we were able to calculate the catalyst costs shown in Table 2-6.

Table 2-6 Catalyst Loading Direct Manufacturing Costs for Gasoline Vehicles (2011$) 

Standard PC_I4_G PC_V6_G PC_V8_G LT_I4_G LT_V6_G LT_V8_G

Sales weighted engine 

displacement (L) 2.1 3.3 4.9 2.4 3.6 5.2

Sales weighted catalyst 

volume (L) Tier 2 2.1 3.3 4.9 2.4 3.6 5.2

PGM cost Tier 2 $94 $150 $223 $111 $164 $239

Substrate cost Tier 2 $14 $22 $31 $17 $24 $33

Washcoat cost Tier 2 $10 $16 $24 $12 $18 $26

Canning cost Tier 2 $5 $8 $12 $6 $9 $13

Labor cost Tier 2 $9 $9 $9 $9 $9 $9

Catalyst cost per 

vehicle Tier 2 $132 $204 $299 $155 $224 $320

Sales weighted catalyst 

volume (L) Tier 3 2.5 3.9 5.9 2.9 4.3 6.3

PGM cost Tier 3 $125 $200 $298 $148 $220 $319

Substrate cost Tier 3 $17 $26 $37 $19 $28 $40

Washcoat cost Tier 3 $12 $20 $29 $15 $22 $31

Canning cost Tier 3 $6 $9 $14 $7 $10 $15

Labor cost Tier 3 $9 $9 $9 $9 $9 $9

Catalyst cost per 

vehicle Tier 3 $169 $264 $387 $199 $289 $414

Sales weighted catalyst 

volume (L) Increment 0.4 0.7 1.0 0.5 0.7 1.0

PGM cost Increment $32 $50 $75 $37 $55 $80

Substrate cost Increment $2 $4 $6 $3 $4 $6

Washcoat cost Increment $2 $3 $5 $2 $4 $5

Canning cost Increment $1 $2 $2 $1 $2 $3

Labor cost Increment $0 $0 $0 $0 $0 $0

Catalyst cost per 

vehicle (2011$) Increment $37 $59 $88 $44 $65 $94

DMC in our proposal 

(2009$) Increment $62 $83 $104 $62 $83 $104

In their study, Umicore estimated the LEV-III PGM costs for a 2.0L engine ranging from 

$81-117. These estimates compare favorably to our estimate of $125 for an I4 passenger car. 

 

E

 For this analysis, we have used the PGM spot price as of July 16, 2013, reported at 9:30AM in New York. Those 

values were: Pt=$1,426/troy oz.; Pd=$735/troy oz.; Rh=$1,000/troy oz. 
2-14

While our final estimates are lower than those in our proposed rule, we consider these final rule 

costs to be much more robust, transparent and appropriate. Several years have passed since 

generating the catalyst loading costs presented in our proposal—as explained, they were 

generated as part of the LEV-III rule and our early work on Tier 3. Several commenters 

suggested that our proposed costs were now dated, and CARB also recommended that we revisit 

our cost estimates in light of the passage of time and more recent information.11

We consider these incremental costs to be applicable in MY2015 with flat learning 

applied thereafter. We also consider catalyst loading to be a low complexity technology with 

near term markup factors applied through 2022 and long term thereafter. The resultant DMC, 

indirect costs (IC) and total costs (TC) are shown in Table 2-7. Note that the values shown do 

not include penetration rates. 

Note that we have not changed the catalyst loading costs for heavy-duty vehicles relative 

to the proposal, with the exception of updating them to 2011 dollars. We do not show costs for 

diesel or >14,000 pound gasoline vehicles since those vehicles are not expected to incur any new 

catalyst loading costs. 
2-15

Table 2-7 Catalyst Loading Costs for Gasoline Vehicles (2011$) 

Vehicle 

category Cost 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025

PC I4 DMC $37 $36 $35 $34 $33 $32 $31 $31 $30 $29 $29 

PC V6 DMC $59 $57 $56 $54 $52 $51 $50 $49 $48 $47 $46 

PC V8 DMC $88 $85 $83 $80 $78 $76 $74 $73 $71 $70 $68 

LT I4 DMC $44 $43 $41 $40 $39 $38 $37 $36 $35 $35 $34 

LT V6 DMC $65 $63 $61 $59 $58 $56 $55 $54 $53 $51 $50 

LT V8 DMC $94 $91 $89 $86 $83 $81 $79 $78 $76 $75 $73 

Class 2b DMC $52 $50 $49 $47 $46 $44 $44 $43 $42 $41 $40 

Class 3 DMC $52 $50 $49 $47 $46 $44 $44 $43 $42 $41 $40 

PC I4 IC $8 $8 $8 $8 $8 $8 $8 $8 $7 $7 $7 

PC V6 IC $12 $12 $12 $12 $12 $12 $12 $12 $10 $10 $10 

PC V8 IC $18 $18 $18 $18 $18 $18 $18 $18 $16 $16 $16 

LT I4 IC $9 $9 $9 $9 $9 $9 $9 $9 $8 $8 $8 

LT V6 IC $14 $14 $13 $13 $13 $13 $13 $13 $11 $11 $11 

LT V8 IC $20 $20 $20 $20 $19 $19 $19 $19 $17 $17 $17 

Class 2b IC $11 $11 $11 $11 $11 $11 $11 $11 $9 $9 $9 

Class 3 IC $11 $11 $11 $11 $11 $11 $11 $11 $9 $9 $9 

PC I4 TC $45 $44 $43 $41 $40 $39 $39 $38 $36 $36 $35 

PC V6 TC $71 $70 $68 $66 $65 $63 $62 $61 $58 $57 $56 

PC V8 TC $106 $104 $101 $99 $96 $94 $92 $91 $87 $85 $84 

LT I4 TC $53 $52 $50 $49 $48 $47 $46 $45 $43 $43 $42 

LT V6 TC $79 $77 $75 $73 $71 $69 $68 $67 $64 $63 $62 

LT V8 TC $114 $111 $108 $106 $103 $100 $99 $97 $93 $91 $90 

Class 2b TC $63 $61 $59 $58 $57 $55 $54 $53 $51 $50 $49 

Class 3 TC $63 $61 $59 $58 $57 $55 $54 $53 $51 $50 $49 

PC=passenger car; LT=light truck; DMC=direct manufacturing cost; IC=indirect cost; TC=total cost; 2015 & 2016 

costs shown because the cost basis for the technology is 2015 where the learning factor=1.0; note that the costs 

shown do not include penetration rates so these costs represent technology costs, not package costs for packages of 

technologies expected to be applied to Tier 3 vehicles.

2.3.2 Optimized Close-coupled Catalyst 

Close-coupled catalyst technologies include improvements to the catalyst system design, 

structure, and packaging to reduce light-off time. As catalysts are moved closer to the engine the 

temperature of the exhaust gases to which catalysts are exposed under high load operation goes 

up substantially. As a result some of the materials used in the catalyst construction, as well as 

the precious metals used in close-coupled applications, must be improved to survive in the higher 

operating temperatures. In the proposal, we stated that cost estimates for close-coupled catalyst 

designs received from vehicle manufacturers ranged from $25 to $50, however, they did not 

include all of the considerations identified above. Consistent with the proposal but updated to 

2011 dollars, we have estimated the cost for an I4 gasoline engine to be $21, a V6 to be $41, and 

a V8 to be $62. As noted, all DMC are in 2011 dollars. 

We consider these incremental costs to be applicable in MY2015 with flat learning 

applied thereafter. We consider close coupled catalysts to be a low complexity technology with 

near term factors applied through 2022 and long term thereafter. The resultant costs are shown 

in Table 2-8. Note that the values shown do not include penetration rates. 
2-16

We do not show costs for any diesel or heavy-duty vehicles since those vehicles are not 

expected to incur new close coupled catalyst costs. 

Table 2-8 Optimized Close Coupled Catalyst Costs for Gasoline Vehicles (2011$) 

Vehicle 

category Cost 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025

PC I4

LT I4 DMC $21 $20 $19 $19 $18 $18 $17 $17 $17 $16 $16 

PC V6

LT V6 DMC $41 $40 $39 $38 $37 $36 $35 $34 $33 $33 $32 

PC V8

LT V8 DMC $62 $60 $58 $57 $55 $53 $52 $51 $50 $49 $48 

PC I4

LT I4 IC $4 $4 $4 $4 $4 $4 $4 $4 $4 $4 $4 

PC V6

LT V6 IC $9 $9 $9 $9 $9 $9 $9 $9 $7 $7 $7 

PC V8

LT V8 IC $13 $13 $13 $13 $13 $13 $13 $13 $11 $11 $11 

PC I4

LT I4 TC $25 $24 $24 $23 $23 $22 $22 $21 $20 $20 $20 

PC V6

LT V6 TC $50 $49 $48 $46 $45 $44 $43 $43 $41 $40 $39 

PC V8

LT V8 TC $75 $73 $71 $70 $68 $66 $65 $64 $61 $60 $59 

PC=passenger car; LT=light truck; DMC=direct manufacturing cost; IC=indirect cost; TC=total cost; 2015 & 2016 

costs shown because the cost basis for the technology is 2015 where the learning factor=1.0; note that the costs 

shown do not include penetration rates so these costs represent technology costs, not package costs for packages of 

technologies expected to be applied to Tier 3 vehicles.

2.3.3 Optimized Thermal Management 

Overall thermal management of the emissions control system to shorten the time it takes 

for the catalyst to light-off will most likely be a primary technology for mitigating NMOG on 

gasoline vehicles and NOx on diesel vehicles. This technology includes dual wall exhaust 

manifolds and pipe that will help maintain exhaust gas temperatures from the exhaust port of the 

engine to the close-coupled catalyst or, in the case of diesel engines, the Selective Catalyst 

Reduction (SCR) system. In some cases, the packaging of the exhaust system will be modified 

to reduce the wetted area of the exhaust path. This will, in turn, reduce the decrease in exhaust 

gas temperatures associated with a longer exhaust path. Consistent with the proposal and based 

on CBI submitted by exhaust system suppliers and vehicle manufacturers, we estimate that the 

cost of implementing dual wall exhaust designs are approximately $31 (2011$) for all engine 

applications. 

We consider these incremental costs to be applicable in MY2015 with flat learning 

applied thereafter. We consider optimized thermal management to be a low complexity 

technology with near term factors applied through 2022 and long term thereafter. The resultant 

costs are shown in Table 2-9. Note that the values shown do not include penetration rates. 

We do not show costs for >14,000 pound gasoline vehicles since those vehicles are not 

expected to incur new optimized thermal management costs. 
2-17

Table 2-9 Optimized Thermal Management Costs for Gasoline and Diesel Vehicles (2011$) 

Vehicle 

category

Cost 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025

PC

LT

Class 2b

Class 3

DMC $31 $30 $29 $28 $27 $27 $26 $26 $25 $25 $24 

PC 

LT

Class 2b

Class 3

IC $6 $6 $6 $6 $6 $6 $6 $6 $5 $5 $5 

PC 

LT

Class 2b

Class 3

TC $38 $37 $36 $35 $34 $33 $33 $32 $31 $30 $30 

PC=passenger car; LT=light truck; DMC=direct manufacturing cost; IC=indirect cost; TC=total cost; 2015 & 2016 

costs shown because the cost basis for the technology is 2015 where the learning factor=1.0; note that the costs 

shown do not include penetration rates so these costs represent technology costs, not package costs for packages of 

technologies expected to be applied to Tier 3 vehicles.

2.3.4 Secondary Air Injection 

Secondary air injection is a technology that provides a source of combustion air such that 

a portion of the exhaust gases are burned in the exhaust manifold. This technology provides 

increased heat in the exhaust system that provides for faster catalyst light-off. It is used only 

during cold start and requires that the air/fuel mixture is rich such that a small amount of fuel is 

available for combustion outside of the combustion chamber. We expect that some gasoline 

V6’s and V8’s will require the application of secondary air injection to reduce NMOG 

emissions. The secondary air injection system consists of an air pump (normally electrically 

powered), plumbing from the pump to the exhaust manifold, an electrically controlled valve, 

control circuitry in the powertrain control module, wiring and calibration. CBI estimates 

received from vehicle manufacturers and suppliers ranged from $50 to $310. Consistent with the 

proposal, we have estimated that the final direct manufacturing cost for secondary air is $104 

(2011$) for any application that may need to add it.

We consider these incremental costs to be applicable in MY2015 with flat learning 

applied thereafter. We consider secondary air to be a low complexity technology with near term 

factors applied through 2022 and long term thereafter. The resultant costs are shown in Table 

2-10. Note that the values shown do not include penetration rates. 

We do not show costs for gasoline I4, diesel or heavy-duty vehicles since none of those 

vehicles are expected to incur new secondary air injection costs. 
2-18

Table 2-10 Secondary Air Injection Costs for Gasoline Vehicles (2011$) 

Vehicle 

category Cost 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025

PC V6

PC V8

LT V6

LT V8

DMC $104 $100 $97 $94 $92 $89 $87 $85 $84 $82 $80 

PC V6

PC V8

LT V6

LT V8

IC $22 $22 $21 $21 $21 $21 $21 $21 $18 $18 $18 

PC V6

PC V8

LT V6

LT V8

TC $125 $122 $119 $116 $113 $110 $108 $107 $102 $100 $99 

PC=passenger car; LT=light truck; DMC=direct manufacturing cost; IC=indirect cost; TC=total cost; 2015 & 2016 

costs shown because the cost basis for the technology is 2015 where the learning factor=1.0; note that the costs 

shown do not include penetration rates so these costs represent technology costs, not package costs for packages of 

technologies expected to be applied to Tier 3 vehicles.

2.3.5 Engine Calibration 

Product changes considered for engine calibration include engine control and calibration 

modifications to improve air and fuel mixtures, particularly at cold start and/or to control 

secondary air. While typically there are no direct manufacturing costs associated with the 

calibration itself, we recognize that some additional engineering efforts will be required to 

implement the changes described above. As in the proposal, we have estimated the per vehicle 

cost at $2 (2011$). For gasoline engines, we have added a new engine calibration cost to address 

GDI PM-related concerns. We have estimated these new costs for gasoline engines at an 

additional $2 (2011$) per engine. The result being a total engine calibration cost of $4 (2011$) 

per gasoline engine and $2 (2011$) per diesel engine. 

We consider these incremental costs to be applicable in MY2015 with flat learning 

applied thereafter. We consider engine calibration to be a low complexity technology with near 

term factors applied through 2022 and long term thereafter. The resultant costs are shown in 

Table 2-11. Note that the values shown do not include penetration rates. 

We do not show costs for >14,000 pound gasoline vehicles since none of those vehicles 

are expected to incur new engine calibration costs. 
2-19

Table 2-11 Engine Calibration Costs for Gasoline and Diesel Vehicles (2011$) 

Vehicle 

category Cost 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025

PC, LT,

Class 2b, 3

Gasoline

DMC $4 $4 $4 $4 $4 $4 $3 $3 $3 $3 $3 

PC, LT,

Class 2b, 3

Diesel

DMC $2 $2 $2 $2 $2 $2 $2 $2 $2 $2 $2 

PC, LT,

Class 2b, 3

Gasoline

IC $1 $1 $1 $1 $1 $1 $1 $1 $1 $1 $1 

PC, LT,

Class 2b, 3

Diesel

IC * $0 $0 $0 $0 $0 $0 $0 $0 $0 $0 $0 

PC, LT,

Class 2b, 3

Gasoline

TC $5 $5 $5 $5 $5 $4 $4 $4 $4 $4 $4 

PC, LT,

Class 2b, 3

Diesel

TC $3 $2 $2 $2 $2 $2 $2 $2 $2 $2 $2 

PC=passenger car; LT=light truck; DMC=direct manufacturing cost; IC=indirect cost; TC=total cost; 2015 & 2016 

costs shown because the cost basis for the technology is 2015 where the learning factor=1.0; note that the costs 

shown do not include penetration rates so these costs represent technology costs, not package costs for packages of 

technologies expected to be applied to Tier 3 vehicles.

*Actual values are less than 50 cents and appear here as $0 due to rounding for simplicity of presentation.

2.3.6 Hydrocarbon Adsorber 

Hydrocarbon adsorbers trap hydrocarbons during cold start and release the hydrocarbons 

after the catalyst lights off. Hydrocarbon adsorbers can be applied in two different manners: 

The first is a passive device which traps hydrocarbons at cold start and releases them as the 

temperature of the device increases. The catalyst may or may not have lit off at the time of 

desorption making a rapid catalyst temperature rise and light off critical. The second is an active 

hydrocarbon adsorber. This device controls the adsorber exposure to exhaust gases based on 

temperature and is able to trap the hydrocarbons until the catalyst has lit off. The effectiveness 

of the active hydrocarbon system is much greater than the passive system. However, the active 

system is also much more costly. In the proposal, we anticipated that manufacturers would apply 

only active systems due to a perception that passive systems were limited in their ability to 

mitigate NMOG. We estimated the cost of active hydrocarbon adsorber systems at $150 

(2009$). For the final rule, we have changed our expectations and now expect that any HC 

adsorber use will be passive rather than active. We base this on comments from MECA and 

ICCT and on CBI provided by Tier 1 suppliers after the proposal.12 We have estimated the DMC 

of a passive HC adsorber at $16 (2011$, or $15 in 2009$), and we expect their use on only a 

portion of the largest gasoline engines. 

We consider these incremental costs to be applicable in MY2015 with flat learning 

applied thereafter. We consider passive HC adsorbers to be a medium complexity technology 

with near term factors applied through 2022 and long term thereafter. The resultant costs are 

shown in Table 2-12. Note that the values shown do not include penetration rates. 
2-20

We do not show costs for I4 or V6 gasoline or for diesel vehicles since none of those 

vehicles are expected to incur new HC adsorber costs. 

Table 2-12 Passive HC Adsorber Costs for Gasoline Vehicles (2011$) 

Vehicle 

category Cost 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025

PC V8,

LT V8,

Class 2b, 3

DMC $16 $15 $15 $14 $14 $13 $13 $13 $13 $12 $12 

PC V8,

LT V8,

Class 2b, 3

IC $5 $5 $5 $5 $5 $5 $5 $5 $4 $4 $4 

PC V8,

LT V8,

Class 2b, 3

TC $21 $20 $20 $19 $19 $18 $18 $18 $16 $16 $16 

PC=passenger car; LT=light truck; DMC=direct manufacturing cost; IC=indirect cost; TC=total cost; 2015 & 2016 

costs shown because the cost basis for the technology is 2015 where the learning factor=1.0; note that the costs 

shown do not include penetration rates so these costs represent technology costs, not package costs for packages of 

technologies expected to be applied to Tier 3 vehicles.

2.4 Evaporative Emission, Canister Bleed, and Leak Controls 

2.4.1 DMCs of Technologies Expected to See Widespread Implementation 

Chapter 1 identified six different technologies EPA expected to see widespread use in 

achieving the emission reductions needed to meet the Tier 3 evaporative emission standard (hot 

soak plus diurnal, canister bleed, and leak). These technologies are in-use to varying degrees in 

the fleet today. The technologies of interest are identified in Table 1-11 of Chapter 1. That table 

is replicated here, but with different entries to address the fleet penetration and costs of the 

various technologies by vehicle category. The DMCs presented below are EPA estimates based 

on discussions with manufacturers and vendors and review of the comments on the CARB LEV 

III evaporative emissions rule. See Table 2-13. All DMC are in 2011 dollars. Each of these is 

discussed below. 
2-21

Table 2-13 Tier 3 Evaporative, Leak and OBD DMCs

Vehicle Class

nonfuel (g) 0.1 0.1 0.125 0.15 0.15 0.175 0.2 0.25

MSAT std(3d/2d)(g) 0.5/0.65 0.65/0.85 0.65/0.85 0.9/1.15 0.9/1.15 1.0/1.25 1.4/1.75 1.9/2.3

T3 std (g) 0.3 0.3 0.4 0.5 0.5 0.5 0.6 0.6

Canister bleed std (g) 0.02 0.02 0.02 0.02 0.02 0.02 0.03 0.03

MSAT Baseline(g)1 0.47 0.47 0.42 0.72 0.72 0.72 0.96 0.96

T3 Target (g)2 0.2 0.2 0.3 0.37 0.37 0.37 0.45 0.45

Red Needed(g) 0.27 0.27 0.12 0.35 0.35 0.35 0.51 0.51

Red Achieved(g) 0.39 0.39 0.39 0.39 0.39 0.39 0.55 0.52

Control Cost & Cost & Cost % Cost & Cost & Cost & Cost & Cost &

Technology DMC Efficiency %Application DMC %Application DMC %Application DMC %Application DMC %Application DMC %Application DMC %Application DMC %Application DMC

Canister 

honeycomb

$8.50 

35mmx 

75mm

90% $8.50_100% $8.50 $8.50_100% $8.50 $8.50_76% $6.46 $8.50_10% $0.85 0 0 0 0 0 0 0 0

Canister 

honeycomb

$7.50 for V8s 35mm x 

50mm

90% 0 0 0 0 $7.5_24% $1.82 $7.5_90% $6.75 $7.5_100% $7.50 $7.5_100% $7.50 $7.5_100% $7.50 $7.5_100% $7.50

AIS scrubber $6 90% $6_40% $2.40 $6_27% $1.62 $6_27% $1.62 $6_27% $1.62 $6_27% $1.62 $6_27% $1.62 0 0 $6_100% $6

PFI to GDI $0 90% 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Fuel system 

architecture

(a) reduce 

connections & 

improve seals/ orings as needed 

$2 90% $2_100% $2 $2_100% $2 $2_100% $2 $2_100% $2 $2_100% $2 $2_100% $2 $2_100% $2 $2_100% $2

(b) move parts 

into tank

$0.50 100% 0.5_$0.50 $0.25 0.5_$0.50 $0.25 0.5_$0.50 $0.25 0.5_$0.50 $0.25 0.5_$0.50 $0.25 0.5_$0.50 $0.25 0.5_$0.50 $0.25 0 0

OBD software 

upgrades

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Tota DMC $13.15 $12.37 $12.15 $11.47 $11.37 $11.37 $9.75 $15.50

0.051 0.051 0.051 0.051 0.051 0.051 0.059 0.053

1

 based on mean plus one standard deviation for 2013 MY 2-day cert results on Tier 2 fuel

2 100 mg or 25% below T3 std whichever is greater 

3

 (365 day per year)(1 gal per 5.6 lbs)(1 lb per 454g)(mg reduction/day)(1 g/1000 mg)(0.9 energy density effect); needs to be further multiplied by(15yr) (avg surv fraction for fleet)(gas price)

fuel savings gal/veh-yr3

LDV LDT1 LDT2 LDT3 LDT4 MDPV LHDGV HHDGV
2-22

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2-23

Canister honeycomb: Current evaporative canisters use high working-capacity activated 

carbon, usually with multiple compartments, to optimize vapor loading and purging behavior. 

These canisters sometimes employ carbons of different working capacities within each chamber. 

Manufacturers may adjust the shapes and sizes of internal compartments, including design 

variations to include different grades of carbon in different areas to best manage rapid purge 

following engine starting, back purge during overnight parking, vapor loading at different 

loading rates, and vapor redistribution and migration while the vehicle is not operating. The 

biggest expected change to evaporative emission canisters is the addition of a secondary canister 

element, either attached to the canister body, or integral to it, in which a carbon with very low 

working capacity is available to capture diffusion emissions (also known as bleed emissions). 

This is commonly referred to as a canister scrubber. While this carbon element can hold only a 

few grams of hydrocarbon, it back purges easily and purges readily with a short amount of 

driving, so it is always ready to capture the small amount of hydrocarbon that escapes the body 

of the evaporative canister as a result of diffusion from vapor migration within the carbon bed. 

For purposes of this analysis, we expect that all vehicles covered by the rule use a canister 

scrubber. Slightly larger scrubbers are expected on vehicles with V-4 and V-6 engines, since 

they are expected to have less available purge for the primary canister than will V-8 engines. The 

scrubbers will vary in size, but a typical unit DMC is $7.50-8.50. We expect that in most cases 

these will be built as an integral part of the current canister to avoid extra packaging costs. In 

some cases, dual tank HDGVs may employ two evaporative emission canisters. 

Engine/fuel system conversion: To the extent that manufacturers use direct injection, 

there should be very little fuel vapor coming from the intake system. Any unburned fuel coming 

from the injectors would be preserved in the cylinder or released to the exhaust system and the 

catalyst. A small amount of crankcase vapor might remain, but this would likely not be enough 

to justify adding carbon to the intake system. As projected in our final rule RIA for the 2017-

2025 GHG emissions, EPA projects a significant movement from port fuel injection (PFI) 

engines to gasoline direct injection (GDI) engines. This ranges from 60-100 percent of products 

for all categories except gasoline-powered trucks over 14,000 lbs GVWR. This reduces air 

induction systems emissions by 90 percent since the GDI uses a different fuel injection timing 

strategy than the PFI This would not involve any additional cost for control of Tier 3 

evaporative emissions.

Air intake scrubbers: Manufacturers have identified the engine’s intake system as 

another source of evaporative emissions. These result from crankcase vapors and from unburned 

fuel from injectors, or sometimes from an injection event that occurred shortly before engine 

shutdown. One way to prevent these emissions is to add a device containing activated carbon to 

the air intake downstream of the air filter, typically in the form of reticulated foam coated with 

activated carbon. This device would have only a few grams of working capacity and would be 

designed to purge easily to ensure that the vapor storage is available any time the engine shuts 

down. This carbon insert would almost completely eliminate vapor emissions from the air intake 

system. This analysis projects that vehicles/engines not converting to GDI will use the air intake 

scrubber to address this source of emissions. The percentages by vehicle category are shown in 

Table 2-13 above. The intake scrubber DMC is approximately $6.00 per vehicle. 
2-24

Fuel-system architecture: As discussed below, there may be the opportunity to reduce 

permeation emissions from some fuel lines. However, the bigger area of expected development 

with respect to fuel lines is to re-engineer whole systems to reduce the number of connections 

between fuel-system components and other fuel-line segments. While manufacturers have 

already made some changes in this direction, these systems may still involve more than the 

optimum number of connections and segments due to assembly and production considerations or 

other factors. Designing the fuel system more carefully to minimize connection points will limit 

possible paths for fuel vapors to escape. This would reduce emission rates and it should also 

improve system durability by eliminating potential failure points. A broader approach to 

addressing this source of emissions is to integrate designs and to move fuel-system components 

inside the fuel tank, which eliminates the concern for vapor emissions and permeation from those 

components and connections. Most of the costs associated with these upgrades lie in 

development and tooling. There may be some additional part costs, but the overall trend should 

ultimately allow for reduced costs from reducing the number of components and reducing 

assembly time. To the extent that fuel-system components are moved inside the fuel tank, there 

may be further cost savings since those components would no longer need to be made from lowpermeation materials. DMC for these actions is about $2.50 

Onboard Diagnostics (OBD): EPA and CARB have similar but not identical OBD 

requirements for LDVs, LDTs, MDPVs, and HDGVs up to 14,000 lbs GVWR. Within the past 

five years CARB has revised their implementation scheme and upgraded requirements to 

improve the effectiveness of their systems in addressing potential exhaust and evaporative 

system performance issues in use. EPA regulations permit manufacturers to meet CARB’s most 

recent requirements and to seek a Federal certificate based on meeting CARB’s requirements. 

Certification based on meeting CARB’s requirements and application of those OBD systems 

nationwide is common practice in the industry with only a few exceptions. EPA is adopting 

current CARB OBD certification, verification, and monitoring requirements. As part of our rule, 

we are including two new elements; (1) certification that the OBD evaporative system leak 

monitor is able to find a 0.020 inch leak and (2) a requirement that the OBD computer store 

information on when the full OBD leak monitoring protocol was last run successfully and the 

result of that assessment. Since current CARB OBD requirements are being met by 

manufacturers, additional costs are attributable to certification to the 0.020 inch leak detection 

requirement and software modification to retain information on the last successful run of the 

OBD evaporative system leak monitor. EPA estimates these two items to cost on average 

approximately $0.10 (2011$) per vehicle. These are reflected in indirect costs discussed below. 

Leak standard testing: As part of the Tier 3 evaporative emission requirements EPA is 

proposing a vapor leak emission standard. EPA expects that many of the technologies and 

approaches for reducing evaporative emissions described above will assist in addressing 

potential vapor leak problems and that in most cases no specific additional measures would be 

needed. Nevertheless, there might be two additional cost areas. First would be certification 

testing. However, EPA is allowing certification requirements for the vapor leak emission 

standard to be met by written attestation rather than by testing since the certification vehicle 

would fail the hot soak plus diurnal evaporative emissions standard if it had a 0.02 inch leak. 

Manufacturers agree this is appropriate. Second, EPA is proposing to include assessment of the 

vapor leak emission standard within the in-use verification testing program (IUVP). However, 

we have structured the program to minimize additional costs. Testing will be required on all 
2-25

vehicles otherwise procured for exhaust emissions. All vehicles tested for exhaust emissions 

must also be tested for the leak emission standard. Thus, we generally expect multiple leak test 

results per group but in no case may there be no fewer than one test group representatives for 

each evaporative/refueling/leak family. Unless there are performance problems, no additional 

vehicle procurement costs are expected. Also, we are proposing to permit the manufacturer to 

use its current evaporative system leak monitoring OBD hardware to screen vehicles from IUVP 

testing for leaks and/or to use as an option to the proposed EPA test procedure if testing is 

needed. The additional costs for leak emission testing for IUVP (approximately $0.10 (2011$) 

per vehicle) are included in the indirect costs discussed below. 

Taken together, these technologies applied to the fleet to the degree described in the 

paragraphs above result in an estimated DMC of $10-15 per vehicle in 2011 dollars. 

2.4.2 DMCs of technologies which may be optimized if necessary to achieve further reductions 

Chapter 1 of the RIA also identified four technology approaches which are in widespread 

use today but with some refinement and optimization could provide additional reductions. These 

are discussed below, but not included in the overall cost analysis. These technologies are likely 

to see limited application because in comparison to the technologies in Table 1-11 of Chapter 1 

the emission reductions available (see Table 1-12 of Chapter 1) are small relative to the costs. If 

implemented, as can be seen in Table 2-13, the five approaches discussed above would provide 

more than enough reductions to meet the emission targets for the hot soak plus diurnal and 

canister bleed standards at certification even accounting for the non-fuel hydrocarbon effects. 

Thus, we are not projecting penetration rates for these technologies. 

Upgrade canister and improve purge: Recent and projected engine design changes are 

increasing the challenge to maintain manifold vacuum for drawing purge air through the 

evaporative canister. Several different technology options would help to address this increasing 

challenge. Different grades of carbon and canister configurations can lead to a more effective 

canister purge for a given volume of air flowing over the canister. If employed, such strategies 

would cost $2-4 per vehicle. 

Improve fuel tank barrier layer thickness and reduce pinch seam gaps: Fuel tanks are 

already designed to limit permeation emissions. Fuel tanks are typically made of high-density 

polyethylene with an embedded barrier layer of ethyl vinyl alcohol (EvOH) representing about 

1.8 percent of the average wall thickness. The EvOH layer is effective for reducing permeation 

emissions. Recent developments in production processes have led to improved barrier coverage 

around the ends of the tank where the molded plastic is pinch-welded to form a closed vessel, 

which is an important step in eliminating a permeation path through the wall of the fuel tank. 

Manufacturers could increase the EvOH barrier thickness to about 3 percent of the average wall 

thickness to provide a more uniform barrier layer, to provide better protection with ethanol-based 

fuels, and to improve permeation resistance generally. The incremental material cost for this 

thicker layer of EvOH comes to about $3.50. 

Filler neck connection and materials upgrade: Another area of potential evaporative 

emissions is the connection between the fill neck and the fuel tank. The challenge is to design a 

low-cost solution that is easily assembled and works for the demanding performance needs 
2-26

related to stiffness and flexibility. The best approach is likely either to use mating parts made 

from low-permeation materials, or to use conventional materials but cover this joint with 

material that acts as a barrier layer. Final designs to address this might vary widely. Technology 

to improve the permeation resistance of the fuel filler tube and the security of the connection to 

the fuel tank would cost $4-6 per vehicle.

Fuel line permeation: Fuel lines in use today also are designed for low permeation rates. 

The biggest portion of fuel and vapor lines are made of metal, but that may still leave several feet 

of nonmetal fuel line on a vehicle. There may be development of new materials to further reduce 

permeation rates, but it is more likely that manufacturers will adjust the mix of existing types of 

plastic fuel lines, and perhaps use more metal fuel lines, to achieve the desired performance at 

the lowest possible price. This would likely vary significantly among vehicle models. As an 

industry average figure, we estimate upgrades involving $1.60 of additional cost for materials 

with greater permeation resistance. 

2.4.3 ORVR for Complete HDGVs 

Onboard Refueling Vapor Recovery (ORVR): Current EPA standards require vehiclebased control of refueling emissions for all complete LDVs and LDTs up to 10,000 lbs GVWR. 

We are extending EPA’s refueling emission standard to complete heavy-duty gasoline vehicles 

(HDGVs) up to 14,000 lbs GVWR starting with the 2018 model year. Today these HDGVs are 

produced by three OEMs. Their chassis and fuel system configurations are very similar to their 

slightly lighter GVWR LDT counterparts, which are now covered by the refueling emission 

standard. Because annual sales of these 10,001-14,000 lb GVWR HDGVs is small relative to 

their similar lighter GVWR LDT counterparts, for uniformity of production and other cost 

savings reasons, manufacturers have installed ORVR on these vehicles since about 2006. 

However, they have not been certified since there were no emission control requirements to 

certify them against. We are including refueling emission control requirements for these vehicles 

but expect no additional costs beyond current practice. Beyond, this the refueling emision 

standards apply to all complete HDGVs regardless of their GVWR by the 2022MY. There are no 

complete HDGVs above 14,000 lbs GVWR today, but there have been in the past and if a future 

product emerges, this will be a requirement for the 2022 model year. 

Table 2-14 presents the evaporative system costs discussed above along with how those 

have been weighted to arrive at evaporative system costs for the vehicle categories used 

throughout this cost analysis. 
2-27

Table 2-14 Evaporative Emission Control System DMC for Gasoline Vehicles (2011$) 

Vehicle

Type

DMC Sales

fraction

Tier 3

Cost analysis

Vehicle category

Tier 3

Cost analysis

DMC

LDV $13.15 100% Passenger car $13.15

LDT1 $12.37 17%

Light truck $12.00

LDT2 $12.15 57%

LDT3 $11.47 17%

LDT4 $11.37 8%

MDPV $11.27 1%

LHDGV $9.75 100% Class 2b & 3 $9.75

HHDGV $15.50 100% >14,000 pound GVWR $15.50

We consider these incremental costs to be applicable in MY2015 with flat learning 

applied thereafter. We consider evaporative emission controls to be a low complexity 

technology with near term factors applied through 2022 and long term thereafter. The resultant 

costs are shown in Table 2-15. Note that the values shown do not include phase-in rates. We do 

not show costs for diesel vehicles since none of those vehicles are expected to incur new 

evaporative emission control costs. 

Table 2-15 Evaporative Emission Control System Costs for Gasoline Vehicles (2011$) 

Vehicle 

category Cost 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025

PC DMC $13 $13 $12 $12 $11 $11 $11 $11 $10 $10 $10 

LT DMC $12 $11 $11 $11 $10 $10 $10 $10 $10 $9 $9 

Class 2b, 3 DMC $10 $9 $9 $9 $8 $8 $8 $8 $8 $8 $7 

>14K HD DMC $15 $15 $14 $14 $13 $13 $13 $13 $12 $12 $12 

PC IC $3 $3 $3 $3 $3 $3 $3 $3 $2 $2 $2 

LT IC $2 $2 $2 $2 $2 $2 $2 $2 $2 $2 $2 

Class 2b, 3 IC $2 $2 $2 $2 $2 $2 $2 $2 $2 $2 $2 

>14K HD IC $3 $3 $3 $3 $3 $3 $3 $3 $3 $3 $3 

PC TC $16 $15 $15 $14 $14 $14 $14 $13 $13 $13 $12 

LT TC $14 $14 $14 $13 $13 $13 $12 $12 $12 $11 $11 

Class 2b, 3 TC $12 $11 $11 $11 $10 $10 $10 $10 $9 $9 $9 

>14K HD TC $18 $18 $17 $17 $17 $16 $16 $16 $15 $15 $15 

PC=passenger car; LT=light truck; DMC=direct manufacturing cost; IC=indirect cost; TC=total cost; 2015 & 2016 

costs shown because the cost basis for the technology is 2015 where the learning factor=1.0; note that the costs 

shown do not include penetration rates so these costs represent technology costs, not package costs for packages of 

technologies expected to be applied to Tier 3 vehicles.

2.5 Vehicle Package Costs 

The total costs (TC) of a given technology are the direct manufacturing costs (DMC) plus 

the indirect costs (IC). These costs change over time due to learning effects and different levels 

of indirect costs as discussed above. Here we present our estimated application or penetration 

rates for each technology and the subsequent average technology cost estimates by year for each 
2-28

technology inclusive of those penetration rates. We then present our approach to developing 

package costs—a package being a group of individual technologies added to a given vehicle. 

As stated above, we have developed our costs with respect to a given vehicle type and the 

type of engine with which it is equipped. Although the cost of achieving the Tier 3 standards 

will increase with both the size of the vehicle and the displacement of the engine we have 

concluded that the cost by engine type is consistent. The final cost per vehicle is the result of not 

only the cost per technology but also the application rate of that technology for each vehicle 

type. For example, while the cost of secondary air injection is the same, $119 (2011$) in 

MY2017, for both a V6 and V8 application, we anticipate that a lower percentage of V6 

applications will require the technology compared to V8 applications. This technology 

penetration rate, or application rate, is the first step in developing our vehicle package costs. 

Table 2-16 presents our estimates of application rates of each enabling technology by 

engine type to meet the Tier 3 standards. These rates are identical, with two exceptions, to the 

rates used in the proposal. The changes from the proposal are to the secondary air and the 

optimized thermal management technologies. For secondary air, we have used the same starting 

rate as used in the proposal, but are now ramping that rate downward in the later years of 

implementation. The secondary air application rates are shown in Table 2-17. We are using 

these application rates because we believe, based on comments from ICCT and post-proposal 

Tier 1 suppliers, that secondary air will follow a similar implementation schedule to past uses of 

that technology. In the past, secondary air has been added in the early years of implementation 

because it is a very effective and relatively easy to employ technology. As experience is gained, 

secondary air is often removed because it is a relatively expensive technology. 

 Table 2-16 Technology Application Rates for MY2017 and later Passenger Cars 

and MY2018 and later Light Trucks and HD Vehicles 

Technology

Gasoline Diesel

I4 V6 V8 Class 2b, 

3

>14K 

HD All

Catalyst Loading 100% 100% 100% 100% 0% 0%

Optimized Close-coupled 

Catalyst 50% 60% 75% 0% 0% 0%

Hydrocarbon Adsorber 0% 0% 15% 0% 0% 0%

Evaporative Emissions 

Controls 100% 100% 100% 100% 100% 0%

Engine Calibration 100% 100% 100% 100% 0% 100%

Optimized Thermal 

Management 50% 40% 25% 25% 0% 25%

SCR Optimization 0% 0% 0% 0% 0% 100%

Note: 0% entries reflect the fact that the technology is not considered to be an enabler for compliance with 

the standards.
2-29

Table 2-17 Technology Application Rates for Secondary Air Injection on Gasoline Vehicles 

Vehicle 

category 2017 2018 2019 2020 2021 2022 2023 2024 2025

PC V6 25% 25% 25% 15% 15% 5% 5% 5% 5%

PC V8 75% 75% 75% 65% 65% 55% 55% 45% 45%

LT V6 0% 25% 25% 15% 15% 5% 5% 5% 5%

LT V8 0% 75% 75% 65% 65% 55% 55% 45% 45%

PC=passenger car; LT=light truck

MDPVs were included in the light-duty fleet as part of Tier 2. Given their current 

certification requirements for criteria pollutants, we have included the costs for MDPVs to meet 

the Tier 3 standards with the LT V8 cost estimates. We do not expect that the technologies 

required to meet the Tier 3 standards for MDPVs will be very different from those applied to LT 

V8s as in many cases there are identical powertrains and chassis between the LT and MDPV 

platforms. 

 The next step in developing vehicle package costs is to consider the phase-in rate of the 

standards. For example, the Tier 3 standards do not reach maximum stringency until the 2025 

MY, ramping down from a presumed Tier 2 Bin 5 level in MY2016 to the final levels in 

MY2025. Manufacturers will be required to start the phase-in of Tier 3 standards on passenger 

cars in MY2017 and light trucks in MY2018. Based on the declining fleet averages for cars and 

trucks, we have apportioned our estimates for full compliance across of the phase-in years as a 

percentage of the final standard. Manufacturers will be required to move from a Tier 2 Bin 5 

fleet average in MY2016 (for vehicles <6,000 lbs GVW) to the Tier 3 standards. This results in 

a significant step in stringency in MY2017. It is also important to note that manufacturers will 

have the opportunity in MYs 2015 and 2016 to earn Tier 3 credits by producing a fleet that is 

cleaner than the current Tier 2 requirements. While we expect that most manufacturers will earn 

credits, either by selling California vehicles as 50 state vehicles or by certifying existing vehicles 

to lower Tier 2 bins, we have not reflected these credits in our cost analysis. 

The ramp down in standards can also be expressed as an increasing percentage of the 

fleet meeting the Tier 3 standards, moving from 0 percent compliance in MY2016 to 100 percent 

compliance in MY2025 (see Section IV of the preamble, which presents the standards and how 

they change by MY). This changing percentage of vehicles complying is treated as being equal 

in this analysis to the percentage of costs being incurred. Table 2-18 shows the percentage of 

vehicles complying with the new standards. Note that Table 2-18 is identical in content to the 

ramp down in standards used in the proposal. 
2-30

Table 2-18 Percentage of Vehicles Phasing-in Compliance with the Tier 3 Standards 

Vehicle

Category Standards 2017 2018 2019 2020 2021 2022 2023 2024 2025

PC Exhaust 57% 62% 68% 73% 78% 84% 89% 95% 100%

LT Exhaust 0% 52% 59% 66% 73% 80% 87% 94% 100%

Class 2b Exhaust 0% 54% 65% 77% 88% 100% 100% 100% 100%

Class 3 Exhaust 0% 47% 60% 73% 87% 100% 100% 100% 100%

PC Evap 40% 60% 60% 80% 80% 100% 100% 100% 100%

LT Evap 0% 60% 60% 80% 80% 100% 100% 100% 100%

HD Evap 0% 60% 60% 80% 80% 100% 100% 100% 100%

PC=passenger car; LT=light truck; HD=Class 2b and 3 vehicles, and >14,000 pound gasoline vehicles.

The third step, and new for the final rule, is to consider the compliance rate in the 

reference case fleet—i.e., if some vehicles already comply with the Tier 3 standards, we do not 

need to add technology and costs to those vehicles. To estimate the reference case compliance 

rate, we looked at MY2013 compliance (the most recent full set of compliance data). Filtering 

these data to include only those certifications for federal Tier 2 compliance, and combining their 

certified NMOG and NOx emissions—Tier 2 vehicles are certified to separate NMOG and NOx 

standards, but we combined them as though they were combined standards as are the Tier 3 

standards—we were able to determine that 14% of MY2013 passenger car and light truck 

certifications had combined NMOG+NOx emissions below the 30 mg level (i.e., the Tier 3 Bin 

30 level). That percentage included 33% of passenger car I4 gasoline vehicles and 10% of 

passenger car V6 gasoline vehicles. These results are shown in Table 2-19. 

Table 2-19 Percentage of MY2013 Certifications with Certified NMOG+NOx Emissions at 

the Indicated Tier 3 Levels 

Vehicle

Category Fuel Bin20 Bin30 Bin50 Bin70 Bin125 Bin160 >Bin160 % belowBin30

PC I4 gasoline 25% 7% 22% 37% 8% 0% 0% 33%

PC V6 gasoline 5% 4% 22% 46% 22% 0% 0% 10%

PC V8 gasoline 2% 2% 26% 41% 26% 3% 0% 3%

PC I4 Diesel 0% 0% 0% 100% 0% 0% 0% 0%

PC V6 Diesel 0% 0% 100% 0% 0% 0% 0% 0%

PC V8 Diesel 0% 0% 0% 0% 0% 0% 0% 0%

LT I4 gasoline 4% 4% 18% 36% 39% 0% 0% 7%

LT V6 gasoline 3% 4% 38% 31% 24% 0% 0% 7%

LT V8 gasoline 0% 1% 23% 34% 16% 18% 7% 1%

LT I4 Diesel 0% 0% 0% 100% 0% 0% 0% 0%

LT V6 Diesel 0% 0% 33% 67% 0% 0% 0% 0%

LT V8 Diesel 0% 0% 0% 0% 0% 0% 0% 0%

Total 10% 4% 25% 38% 17% 4% 2% 14%

Importantly, the percentages shown in Table 2-19 represent certified engine families, not 

vehicle sales, and they represent certified emission levels absent any compliance margin. We 

have chosen to address these two issues in the following ways. As regards the absence of 
2-31

compliance margin—the amount below the standard to which vehicles are typically designed and 

certified as insurance against failing the standards in-use—we went the next step and considered 

only those certifications that met 70% of the Tier 3 Bin 30 combined NMOG+NOx levels. 

Doing this resulted in a total of 11% of the certifications with emissions below 70% of the Bin 

30 levels.F This change also resulted in a reduction to 28% of passenger car I4 families and 6% 

of passenger car V6 families at 70% of the Bin 30 levels. 

As for reconciling certified families with actual sales, we had no way of matching these 

certifications to actual sales since the full MY2013 sales were not yet available. We could 

simply assume that the percentage of engine families equates to the percentage of sales but, in an 

effort to be conservative in our cost estimates, we have chosen instead to assume only a 50% 

relationship. In other words, to be conservative, we have chosen to estimate that sales are 

represented by only half of the certified engine families. So, the 28% of passenger car I4 

families with certified emissions below 70% of the Bin 30 level is taken to represent 14% of 

actual passenger car I4 sales. The resultant reference case sales percentages estimated to already 

comply with the Tier 3 Bin 30 average are shown in Table 2-20. Note that we have assumed that 

no HD vehicles are already at compliant emission levels in the reference case. 

Table 2-20 Reference Case Engine Families and Estimated Sales at or below 70% of the 

Bin 30 Standard 

Vehicle

Category Fuel

% of certified 

families 

below

Bin30

% of certified 

families 

below

70% of Bin30

Estimated % 

of sales below 

70% of Bin30

PC I4 gasoline 33% 28% 14%

PC V6 gasoline 10% 6% 3%

PC V8 gasoline 3% 2% 1%

PC I4 diesel 0% 0% 0%

PC V6 diesel 0% 0% 0%

PC V8 diesel 0% 0% 0%

LT I4 gasoline 7% 4% 2%

LT V6 gasoline 7% 3% 1%

LT V8 gasoline 1% 0% 0%

LT I4 diesel 0% 0% 0%

LT V6 diesel 0% 0% 0%

LT V8 diesel 0% 0% 0%

Total 14% 11% 5%

With each of these percentages—the technology application rate percentage; the phase-in 

rate of the standard; and the reference case sales percentage meeting Bin 30—we can then 

 

F

 A compliance margin of just 70% of the actual standard could be considered too high by traditional measures 

where each criteria pollutant has a unique standard level. However, the combined nature of the Tier 3 NMOG+NOx 

standard makes traditional compliance margin goals too large and, some have argued, that even 70% in the context 

of Tier 3 may be too large. We prefer to be conservative and use 70% of the standard. 
2-32

determine the contribution of each individual technology to the resultant package cost for each 

vehicle category. This is done by multiplying the total cost of each individual technology in a 

given year by it technology application rate for that year, then multiplying this product by the 

phase-in rate less reference case sales percentage. An example calculation is shown in Table 

2-21 for optimized close coupled catalyst costs on I4 gasoline passenger cars. 

Table 2-21 Example Calculation: Contribution of Optimized Close Coupled Catalyst to the 

Package Cost for I4 Gasoline Passenger Car (dollar values in 2011$) 

Item Value Source

Optimized close coupled catalyst Total Cost (TC) 

for MY2017 $24 Table 2-8

Application rate to meet Tier 3 50% Table 2-16

Standard phase-in percentage for MY2017 57% Table 2-18

Reference case sales in compliance 14% Table 2-20

Contribution to package cost $5

= ($24)(50%)(57%-14%) Table 2-22

Table 2-22 through Table 2-30 use this calculation approach to present the contribution 

of each technology cost to the resultant package cost. Table 2-31 and Table 2-32 present the 

final package costs for gasoline and diesel vehicles, respectively, which simply sum the 

appropriate costs shown in Table 2-22 through Table 2-30.
2-33

Table 2-22 Contribution of Individual Technologies to Vehicle Package Costs – Gasoline 

Passenger Cars (2011$) 

Technology Engine 2017 2018 2019 2020 2021 2022 2023 2024 2025

Catalyst Loading I4 $18 $20 $22 $23 $25 $27 $27 $29 $30

Optimized Close-coupled 

Catalyst I4 $5 $6 $6 $7 $7 $7 $8 $8 $8

Secondary Air Injection I4 $0 $0 $0 $0 $0 $0 $0 $0 $0

Hydrocarbon Adsorber I4 $0 $0 $0 $0 $0 $0 $0 $0 $0

Evaporative Emissions 

Controls I4 $4 $7 $6 $9 $9 $11 $11 $11 $11

Engine Calibration I4 $2 $2 $2 $3 $3 $3 $3 $3 $3

Optimized Thermal 

Management I4 $8 $8 $9 $10 $10 $11 $11 $12 $13

Catalyst Loading V6 $37 $39 $42 $44 $47 $49 $50 $52 $55

Optimized Close-coupled 

Catalyst V6 $15 $16 $18 $19 $20 $21 $21 $22 $23

Secondary Air Injection V6 $16 $17 $18 $12 $12 $4 $4 $5 $5

Hydrocarbon Adsorber V6 $0 $0 $0 $0 $0 $0 $0 $0 $0

Evaporative Emissions 

Controls V6 $5 $8 $8 $11 $10 $13 $12 $12 $12

Engine Calibration V6 $3 $3 $3 $3 $3 $3 $4 $4 $4

Optimized Thermal 

Management V6 $8 $8 $9 $9 $10 $10 $11 $11 $11

Catalyst Loading V8 $57 $61 $64 $68 $72 $75 $77 $80 $83

Optimized Close-coupled 

Catalyst V8 $30 $32 $34 $36 $38 $40 $41 $42 $44

Secondary Air Injection V8 $50 $53 $57 $52 $55 $49 $50 $42 $44

Hydrocarbon Adsorber V8 $2 $2 $2 $2 $2 $2 $2 $2 $2

Evaporative Emissions 

Controls V8 $6 $9 $8 $11 $11 $13 $13 $12 $12

Engine Calibration V8 $3 $3 $3 $3 $3 $4 $4 $4 $4

Optimized Thermal 

Management V8 $5 $5 $6 $6 $6 $7 $7 $7 $7

Note: $0 entries denote zero costs due to a 0 percent application rate (see Table 2-16) and/or compliance rate (see

Table 2-18). 
2-34

Table 2-23 Contribution of Individual Technologies to Vehicle Package Costs – Gasoline 

Light-duty Trucks (2011$) 

Technology Engine 2017 2018 2019 2020 2021 2022 2023 2024 2025

Catalyst Loading I4 $0 $25 $28 $30 $33 $35 $37 $39 $41

Optimized Close-coupled 

Catalyst I4 $0 $6 $6 $7 $8 $8 $9 $9 $10

Secondary Air Injection I4 $0 $0 $0 $0 $0 $0 $0 $0 $0

Hydrocarbon Adsorber I4 $0 $0 $0 $0 $0 $0 $0 $0 $0

Evaporative Emissions 

Controls I4 $0 $8 $7 $10 $10 $12 $11 $11 $11

Engine Calibration I4 $0 $2 $3 $3 $3 $3 $3 $4 $4

Optimized Thermal 

Management I4 $0 $9 $10 $11 $12 $13 $13 $14 $15

Catalyst Loading V6 $0 $37 $41 $45 $49 $53 $55 $58 $61

Optimized Close-coupled 

Catalyst V6 $0 $14 $16 $17 $19 $20 $21 $22 $23

Secondary Air Injection V6 $0 $15 $16 $11 $12 $4 $4 $5 $5

Hydrocarbon Adsorber V6 $0 $0 $0 $0 $0 $0 $0 $0 $0

Evaporative Emissions 

Controls V6 $0 $8 $8 $10 $10 $12 $11 $11 $11

Engine Calibration V6 $0 $2 $3 $3 $3 $3 $3 $4 $4

Optimized Thermal 

Management V6 $0 $7 $8 $9 $9 $10 $10 $11 $12

Catalyst Loading V8 $0 $55 $61 $66 $72 $78 $81 $86 $90

Optimized Close-coupled 

Catalyst V8 $0 $27 $30 $33 $36 $38 $40 $42 $44

Secondary Air Injection V8 $0 $45 $50 $47 $52 $47 $49 $42 $44

Hydrocarbon Adsorber V8 $0 $2 $2 $2 $2 $2 $2 $2 $2

Evaporative Emissions 

Controls V8 $0 $8 $8 $10 $10 $12 $12 $11 $11

Engine Calibration V8 $0 $2 $3 $3 $3 $3 $4 $4 $4

Optimized Thermal 

Management V8 $0 $5 $5 $5 $6 $6 $7 $7 $7

Note: $0 entries denote zero costs due to a 0 percent application rate (see Table 2-16) and/or compliance rate (see

Table 2-18).

Table 2-24 Contribution of Individual Technologies to Vehicle Package Costs – Gasoline 

Heavy-duty Class 2b Trucks (2011$) 

Technology Engine 2017 2018 2019 2020 2021 2022 2023 2024 2025

Catalyst Loading All $0 $31 $37 $42 $48 $53 $51 $50 $49

Optimized Close-coupled 

Catalyst All $0 $0 $0 $0 $0 $0 $0 $0 $0

Secondary Air Injection All $0 $0 $0 $0 $0 $0 $0 $0 $0

Hydrocarbon Adsorber All $0 $0 $0 $0 $0 $0 $0 $0 $0

Evaporative Emissions 

Controls All $0 $6 $6 $8 $8 $10 $9 $9 $9

Engine Calibration All $0 $2 $3 $3 $4 $4 $4 $4 $4

Optimized Thermal 

Management All $0 $5 $6 $6 $7 $8 $8 $8 $7

Note: $0 entries denote zero costs due to a 0 percent application rate (see Table 2-16) and/or compliance rate (see

Table 2-18).
2-35

Table 2-25 Contribution of Individual Technologies to Vehicle Package Costs – Gasoline 

Heavy-duty Class 3 Trucks (2011$) 

Technology Engine 2017 2018 2019 2020 2021 2022 2023 2024 2025

Catalyst Loading All $0 $27 $34 $40 $47 $53 $51 $50 $49

Optimized Close-coupled Catalyst All $0 $0 $0 $0 $0 $0 $0 $0 $0

Secondary Air Injection All $0 $0 $0 $0 $0 $0 $0 $0 $0

Hydrocarbon Adsorber All $0 $0 $0 $0 $0 $0 $0 $0 $0

Evaporative Emissions Controls All $0 $6 $6 $8 $8 $10 $9 $9 $9

Engine Calibration All $0 $2 $3 $3 $4 $4 $4 $4 $4

Optimized Thermal Management All $0 $4 $5 $6 $7 $8 $8 $8 $7

Note: $0 entries denote zero costs due to a 0 percent application rate (see Table 2-16) and/or compliance rate (see 

Table 2-18). 

Table 2-26 Contribution of Individual Technologies to Vehicle Package Costs – >14,000 

Pound HD Gasoline Trucks (2011$) 

Technology Engine 2017 2018 2019 2020 2021 2022 2023 2024 2025

Catalyst Loading All $0 $0 $0 $0 $0 $0 $0 $0 $0

Optimized Close-coupled 

Catalyst All $0 $0 $0 $0 $0 $0 $0 $0 $0

Secondary Air Injection All $0 $0 $0 $0 $0 $0 $0 $0 $0

Hydrocarbon Adsorber All $0 $0 $0 $0 $0 $0 $0 $0 $0

Evaporative Emissions 

Controls All $0 $10 $10 $13 $13 $16 $15 $15 $15

Engine Calibration All $0 $0 $0 $0 $0 $0 $0 $0 $0

Optimized Thermal 

Management All $0 $0 $0 $0 $0 $0 $0 $0 $0

Note: $0 entries denote zero costs due to a 0 percent application rate (see Table 2-16) and/or compliance rate (see

Table 2-18). 

Table 2-27 Contribution of Individual Technologies to Vehicle Package Costs – Diesel 

Passenger Cars (2011$) 

Technology Engine 2017 2018 2019 2020 2021 2022 2023 2024 2025

Engine Calibration All $1 $1 $2 $2 $2 $2 $2 $2 $2

Optimized Thermal Management All $5 $5 $6 $6 $6 $7 $7 $7 $7

SCR Optimization All $34 $36 $38 $40 $43 $45 $45 $47 $49

Table 2-28 Contribution of Individual Technologies to Vehicle Package Costs– Diesel 

Light-duty Trucks (2011$) 

Technology Engine 2017 2018 2019 2020 2021 2022 2023 2024 2025

Engine Calibration All $0 $1 $1 $1 $2 $2 $2 $2 $2

Optimized Thermal Management All $0 $5 $5 $5 $6 $6 $7 $7 $7

SCR Optimization All $0 $30 $33 $36 $40 $43 $44 $47 $49

Note: $0 entries denote zero costs due to a 0 percent application rate (see Table 2-16) and/or compliance rate 

(see Table 2-18). 
2-36

Table 2-29 Contribution of Individual Technologies to Vehicle Package Costs– Diesel 

Heavy-duty Class 2b Trucks (2011$) 

Technology Engine 2017 2018 2019 2020 2021 2022 2023 2024 2025

Engine Calibration All $0 $1 $1 $2 $2 $2 $2 $2 $2

Optimized Thermal Management All $0 $5 $6 $6 $7 $8 $8 $8 $7

SCR Optimization All $0 $31 $37 $42 $48 $53 $51 $50 $49

Note: $0 entries denote zero costs due to a 0 percent application rate (see Table 2-16) and/or compliance rate 

(see Table 2-18). 

Table 2-30 Contribution of Individual Technologies to Vehicle Package Costs– Diesel 

Heavy-duty Class 3 Trucks (2011$) 

Technology Engine 2017 2018 2019 2020 2021 2022 2023 2024 2025

Engine Calibration All $0 $1 $1 $2 $2 $2 $2 $2 $2

Optimized Thermal Management All $0 $4 $5 $6 $7 $8 $8 $8 $7

SCR Optimization All $0 $27 $34 $40 $47 $53 $51 $50 $49

Note: $0 entries denote zero costs due to a 0 percent application rate (see Table 2-16) and/or compliance rate 

(see Table 2-18). 

The final package costs are simply the sum of the costs shown in each of Table 2-22

through Table 2-30. These results are shown in Table 2-31 for gasoline vehicles and Table 2-32

for diesel vehicles. 

Table 2-31 Vehicle Package Costs by Year for All Gasoline Vehicles (2011$) 

Vehicle category Engine 2017 2018 2019 2020 2021 2022 2023 2024 2025

Passenger car I4 $37 $43 $46 $51 $54 $60 $60 $63 $65

Passenger car V6 $84 $92 $97 $97 $102 $101 $102 $106 $110

Passenger car V8 $152 $165 $174 $177 $187 $189 $192 $190 $197

Light-duty truck I4 $0 $50 $54 $61 $65 $72 $73 $77 $80

Light-duty truck V6 $0 $83 $91 $94 $101 $102 $105 $111 $116

Light-duty truck V8 $0 $144 $158 $167 $180 $187 $193 $195 $203

Class 2b $0 $45 $52 $60 $67 $75 $72 $71 $70

Class 3 $0 $40 $48 $58 $66 $75 $72 $71 $70

>14,000 pound HD $0 $10 $10 $13 $13 $16 $15 $15 $15

Note: $0 entries denote zero costs due to a 0 percent application rate (see Table 2-16) and/or compliance rate (see

Table 2-18). 

Table 2-32 Vehicle Package Costs by Year for All Diesel Vehicles (2011$) 

Vehicle category Engine 2017 2018 2019 2020 2021 2022 2023 2024 2025

Passenger car I4 $40 $43 $46 $48 $51 $53 $54 $56 $59

Passenger car V6 $40 $43 $46 $48 $51 $53 $54 $56 $59

Passenger car V8 $40 $43 $46 $48 $51 $53 $54 $56 $59

Light-duty truck I4 $0 $36 $40 $43 $47 $51 $53 $56 $59

Light-duty truck V6 $0 $36 $40 $43 $47 $51 $53 $56 $59

Light-duty truck V8 $0 $36 $40 $43 $47 $51 $53 $56 $59

Class 2b V8 $0 $37 $44 $50 $57 $63 $61 $60 $59

Class 3 V8 $0 $32 $40 $48 $56 $63 $61 $60 $59

Note: $0 entries denote zero costs due to a 0 percent application rate (see Table 2-16) and/or compliance rate (see

Table 2-18). 
2-37

2.6 Operating Costs 

New for the final rule are estimates of operating costs (fuel savings) associated with the 

new evaporative emission standards. The fuel that would have evaporated absent the new 

standards will ultimately be used to propel the vehicle, thus providing a savings to the consumer. 

This savings is very small but nonetheless real. We also considered other operating costs, such 

as maintenance costs and repair costs, but concluded that the nature of the Tier 3 compliance 

technologies will not result in any increases or decreases in existing operating costs. 

In Chapter 1, we discussed at the length the new evaporative standards and the estimated 

reductions; hydrocarbon reductions achieved are converted to the fuel saved by each vehicle 

category using the equation in footnote 3 of Table 2-13. Those fuel savings in 

gallons/vehicle/year are shown in Table 2-33. 

Table 2-33 Fuel Savings per Vehicle per Year Associated with the New Evaporative 

Emission Standards 

Vehicle

type

Gallons 

saved/vehicle/year

Sales

fraction Vehicle category

Tier 3 Cost analysis

Gallons 

saved/vehicle/year

LDV 0.051 n/a Passenger car 0.051

LDT1 0.051 17%

Light truck 0.050

LDT2 0.049 57%

LDT3 0.051 17%

LDT4 0.051 8%

MDPV 0.051 1%

LHDGV 0.059 n/a Class 2b & 3 0.059

HHDGV 0.053 n/a >14,000 pound 

GVWR 0.053

Tier 3 compliant vehicles will be expected to realize these fuel savings throughout their 

lifetimes. To estimate the lifetime fuel savings, we used the survival fractions shown in Table 

2-34, the fuel prices shown in Table 2-35, and the evaporative emission standard phase-in rates 

shown in Table 2-18. 
2-38

Table 2-34 Vehicle Survival Fractions used in Operating Cost Estimates 

Vehicle 

age

PC LT HD

1 1.000 1.000 1.000

2 0.988 0.978 0.978

3 0.977 0.963 0.963

4 0.961 0.943 0.943

5 0.945 0.931 0.931

6 0.930 0.915 0.915

7 0.911 0.893 0.893

8 0.891 0.870 0.870

9 0.869 0.841 0.841

10 0.840 0.796 0.796

11 0.800 0.742 0.742

12 0.756 0.692 0.692

13 0.706 0.641 0.641

14 0.653 0.583 0.583

15 0.595 0.535 0.535

16 0.531 0.486 0.486

17 0.458 0.442 0.442

18 0.383 0.398 0.398

19 0.308 0.352 0.352

20 0.241 0.309 0.309

21 0.183 0.267 0.267

22 0.139 0.228 0.228

23 0.107 0.202 0.202

24 0.082 0.175 0.175

25 0.063 0.158 0.158

26 0.051 0.145 0.145

27 0.042 0.139 0.139

28 0.034 0.125 0.125

29 0.028 0.111 0.111

30 0.024 0.103 0.103

31 0.000 0.093 0.093

32 0.000 0.083 0.083

33 0.000 0.073 0.073

34 0.000 0.062 0.062

35 0.000 0.050 0.050

36 0.000 0.038 0.038

37 0.000 0.027 0.027

38 0.000 0.000 0.000

39 0.000 0.000 0.000

40 0.000 0.000 0.000

PC=passenger car; LT=light truck; 

HD=all Heavy-duty, including >14K 

pounds

Source: EPA’s MOVES model . For 

more information regarding the 

MOVES model, see Chapter 7 of this 

RIA.
2-39

Table 2-35 Gasoline Prices (2011$) 

Calendar

Year

Taxed price

($/gal)

Untaxed price

($/gal)

2017 $3.15 $2.74

2018 $3.19 $2.79

2019 $3.25 $2.85

2020 $3.32 $2.92

2021 $3.38 $2.98

2022 $3.43 $3.03

2023 $3.45 $3.06

2024 $3.48 $3.09

2025 $3.49 $3.10

2026 $3.52 $3.14

2027 $3.55 $3.17

2028 $3.58 $3.20

2029 $3.63 $3.25

2030 $3.67 $3.29

2031 $3.71 $3.33

2032 $3.75 $3.38

2033 $3.82 $3.44

2034 $3.87 $3.50

2035 $3.94 $3.57

2036 $4.01 $3.64

2037 $4.08 $3.71

2038 $4.15 $3.79

2039 $4.23 $3.87

2040 $4.32 $3.96

Source: Energy Information Administration, Annual Energy Outlook 2013, Table 59.

Note that the 2040 prices were used for years beyond 2040 in the analysis.

Looking first at the gallons saved during the lifetime of Tier 3 vehicles, the results are 

shown in Table 2-36. Clearly, the fuel savings are small on a per vehicle basis, approaching 1 

gallon per vehicle during the entire lifetime. Note that the fuel savings reach their maximum in 

MY2022 when the phase-in hits 100% and they remain at those levels thereafter. Importantly, 

the maximum lifetime savings would actually be realized by any vehicle meeting the new Tier 3 

evaporative standards. The lower savings shown in the early years of implementation are the 

result of the phase-in. In other words, 40% of the MY2017 passenger cars would realize 0.783 

gallons saved during their lifetimes while the remaining 60% would realize none since they 

would not be compliant with the new evaporative standards. The resultant savings for the 

average MY2017 passenger car would then be (40%)(0.783)+(60%)(0.0)=0.313 gallons. 

Nonetheless, while the savings per vehicle are small, they are real and when realized by millions 

of vehicles the total gallons saved becomes more meaningful. 
2-40

Table 2-36 Gallons of Gasoline Saved during the Lifetimes of Gasoline Vehicles sold in the 

indicated MY 

Vehicle

category

MY

2017

MY

2018

MY

2019

MY

2020

MY

2021

MY

2022

MY

2023

MY

2024

MY

2025

PC 0.313 0.470 0.470 0.626 0.626 0.783 0.783 0.783 0.783

LT 0.000 0.491 0.491 0.655 0.655 0.819 0.819 0.819 0.819

Class 2b 0.000 0.585 0.585 0.779 0.779 0.974 0.974 0.974 0.974

Class 3 0.000 0.585 0.585 0.779 0.779 0.974 0.974 0.974 0.974

>14K HD 0.000 0.524 0.524 0.698 0.698 0.873 0.873 0.873 0.873

PC=passenger car; LT=light truck; HD=heavy-duty.

We can also look at these gasoline savings on a calendar year basis where, in calendar 

year 2017 only the MY2017 vehicles meeting the new evaporative standards will realize any fuel 

savings. As shown in Table 2-18 and Table 2-33, this means that only 40% of passenger cars 

will realize 0.051 gallons of fuel saved in the 2017 calendar year. But, with gasoline passenger 

car sales estimated at 6,184,804 in MY2017, the total gallons saved becomes a more meaningful 

number. These results are shown in Table 2-37. 

Table 2-37 Annual Gallons of Gasoline Saved 

Calendar

Year PC LT Class 2b Class 3 >14K HD Total

2017 124,985 0 0 0 0 124,985

2018 310,678 107,820 14,663 324 1,679 435,164

2019 498,358 213,383 29,055 642 3,341 744,779

2020 751,009 352,549 48,038 1,062 5,557 1,158,215

2021 1,002,378 487,226 66,546 1,471 7,728 1,565,350

2022 1,315,316 652,291 89,471 1,978 10,430 2,069,486

2023 1,625,192 812,105 112,044 2,478 13,089 2,564,908

2024 1,933,324 967,512 134,426 2,972 15,719 3,053,954

2025 2,239,897 1,118,389 156,504 3,461 18,318 3,536,569

2030 3,661,158 1,800,289 255,597 5,652 30,125 5,752,821

PC=passenger car; LT=light truck; HD=heavy-duty.

Using the gasoline prices shown in Table 2-35, we can determine the monetary savings 

associated with these fuel savings. These results are shown in Table 2-38 (using a 3% discount 

rate) and in Table 2-39 (using a 7% discount rate) for the lifetimes of all vehicles sold in each 

model year. Table 2-40 presents the annual monetized fuel savings. 

Table 2-38 Monetized Lifetime Fuel Savings of all Vehicles Sold in Each Model Year, 

Discounted at 3% to the 1st year of the Model Year (Millions of 2011$) 

Vehicle

category

MY

2017

MY

2018

MY

2019

MY

2020

MY

2021

MY

2022

MY

2023

MY

2024

MY

2025 Sum

PC $4.66 $7.09 $7.35 $10.1 $10.3 $13.1 $13.3 $13.7 $14.0 $93.6

LT $0 $4.22 $4.29 $5.76 $5.77 $7.17 $7.16 $7.19 $7.24 $48.8

Class 2b $0 $0.574 $0.584 $0.786 $0.793 $0.99 $1.01 $1.03 $1.05 $6.82

Class 3 $0 $0.013 $0.013 $0.017 $0.018 $0.022 $0.022 $0.023 $0.023 $0.151

>14K HD $0 $0.066 $0.068 $0.092 $0.093 $0.117 $0.119 $0.121 $0.124 $0.799

Sum $4.66 $12.0 $12.3 $16.8 $17.0 $21.4 $21.6 $22.1 $22.4 $150 

Fuel savings calculated with untaxed gasoline prices; PC=passenger car; LT=light truck; HD=heavy-duty.
2-41

Table 2-39 Monetized Lifetime Fuel Savings of all Vehicles Sold in Each Model Year, 

Discounted at 7% to the 1st year of the Model Year (Millions of 2011$) 

Vehicle

category

MY

2017

MY

2018

MY

2019

MY

2020

MY

2021

MY

2022

MY

2023

MY

2024

MY

2025 Sum

PC $3.47 $5.27 $5.47 $7.51 $7.69 $9.73 $9.9 $10.2 $10.4 $69.7

LT $0.000 $3.05 $3.10 $4.17 $4.17 $5.18 $5.18 $5.20 $5.24 $35.3

Class 2b $0.000 $0.415 $0.422 $0.568 $0.573 $0.719 $0.730 $0.747 $0.763 $4.94

Class 3 $0.000 $0.009 $0.009 $0.013 $0.013 $0.016 $0.016 $0.017 $0.017 $0.109

>14K HD $0.000 $0.048 $0.049 $0.066 $0.067 $0.085 $0.086 $0.088 $0.090 $0.578

Sum $3.47 $8.79 $9.05 $12.3 $12.5 $15.7 $15.9 $16.3 $16.5 $111 

Fuel savings calculated with untaxed gasoline prices; PC=passenger car; LT=light truck; HD=heavy-duty.

Table 2-40 Annual Monetized Fuel Savings (Millions of 2011$) 

Calendar

Year PC LT Class 2b Class 3 >14K HD Total

2017 $0.342 $0.000 $0.000 $0.000 $0.000 $0.342

2018 $0.866 $0.301 $0.041 $0.001 $0.005 $1.21

2019 $1.42 $0.608 $0.083 $0.002 $0.010 $2.12

2020 $2.19 $1.030 $0.140 $0.003 $0.016 $3.38

2021 $2.99 $1.45 $0.198 $0.004 $0.023 $4.67

2022 $3.99 $1.98 $0.271 $0.006 $0.032 $6.28

2023 $4.97 $2.48 $0.343 $0.008 $0.040 $7.84

2024 $5.97 $2.99 $0.415 $0.009 $0.049 $9.43

2025 $6.95 $3.47 $0.486 $0.011 $0.057 $11.0

2030 $12.0 $5.92 $0.841 $0.019 $0.099 $18.9

Fuel savings calculated with untaxed gasoline prices; PC=passenger 

car; LT=light truck; HD=heavy-duty.

2.7 Vehicle Program Costs 

With the package costs presented in Table 2-31 and Table 2-32 and the operating costs 

presented in Table 2-40, we can begin to develop vehicle program costs associated with the new 

Tier 3 standards. The vehicle program costs multiply package costs by appropriate vehicle sales 

per year to estimate the annual technology costs of the program. We then subtract from those 

annual technology costs the annual operating savings associated with the evaporative standards. 

We also include the annual PM facility costs as discussed below. 

The first step to this is determining the projected sales of each vehicle category, or 

package, as presented in Table 2-31 and Table 2-32. To do this, we have started with the latest 

sales projections from our MOVES database which provides projected sales by passenger car, 

light truck, etc., and gasoline versus diesel. However, MOVES does not provide sales 

projections to the I4 versus V6 versus V8 level of granularity which we need for Tier 3 vehicle 

program costs. 
2-42

For a fleet mix breakout at the level needed, we are using the fleet mix projections 

stemming from OMEGA runs done in support of our recent GHG final rulemakings.13 We began 

with the baseline database developed in support of the MY 2017-2025 GHG final rule.14 That 

baseline database provides the fleet sales mix in the years 2017-2025 for each of the vehicle 

category/engine/fuel combinations listed in Table 2-31 and Table 2-32. However, that baseline 

database is not reflective of the MY 2012 to 2016 or the MY 2017-2025 GHG final rules which 

are expected to have an impact on the sales mix of the vehicle category/engine/fuel combinations 

largely due to an expectation that engines will be turbocharged and downsized to achieve better 

GHG performance while also maintaining vehicle performance and utility. This downsizing is 

expected to provide downward effects on overall Tier 3 costs since vehicles with smaller engines 

are expected to incur lower costs than vehicles with larger engines. Therefore, using the baseline 

database and the technology penetration rates expected from the MY 2017-2025 GHG final rule, 

we have developed a Tier 3 reference case fleet. This reference fleet is the fleet we have used in 

developing Tier 3 vehicle program costs. Note that the Tier 3 control case fleet and the reference 

case fleet are, in effect, one in the same since Tier 3 itself is not expected to have any impact on 

the car/truck fleet mix or the I4/V6/V8 fleet mix. 

Note that this reference case fleet differs considerably from the reference case fleet used 

in the proposal. The proposal used a fleet mix representing a future fleet meeting the MY2016 

GHG standards. That fleet mix had considerably less turbocharging and downsizing of engines 

since the MY2016 GHG standards were less stringent than the MY 2017-2025 standards 

represented in the final rule’s reference case fleet. 

Table 2-41 shows the baseline fleet mix—representing the best estimates of the future 

fleet absent any GHG rules—and Table 2-42 shows the Tier 3 reference fleet—representing the 

future fleet in the presence of the MY 2012-2016 and MY 2017-2025 GHG final rules. Table 

2-43 shows projected sales of light-duty and heavy-duty vehicles excluding sales in California 

and other states that have adopted LEVIII.G

 

G

 Vehicle sales in California and other states that have adopted LEVIII are estimated at 36% of the nationwide total. 
2-43

Table 2-41 Baseline Light-Duty Fleet Mix 

Vehicle

category

Engine

Fuel

2017 2018 2019 2020 2021 2022 2023 2024 2025

PC

I4 G 37.8% 38.1% 38.4% 38.7% 38.9% 39.2% 39.7% 40.0% 40.4%

I4 D 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%

V6 G 21.4% 21.7% 21.8% 22.0% 22.4% 22.3% 22.3% 22.5% 22.7%

V6 D 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%

V8 G 3.2% 3.1% 3.2% 3.2% 3.2% 3.2% 3.1% 3.1% 3.2%

V8 D 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%

LT

I4 G 4.4% 4.0% 3.9% 3.7% 3.6% 3.6% 3.6% 3.5% 3.5%

I4 D 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%

V6 G 22.1% 23.4% 23.4% 23.4% 23.0% 23.2% 23.1% 23.0% 22.7%

V6 D 0.1% 0.1% 0.1% 0.1% 0.1% 0.1% 0.1% 0.1% 0.1%

V8 G 10.7% 9.3% 9.0% 8.6% 8.5% 8.2% 8.0% 7.5% 7.2%

V8 D 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%

EV 0.2% 0.2% 0.2% 0.2% 0.2% 0.2% 0.2% 0.2% 0.2%

PC All All 62.6% 63.2% 63.6% 64.2% 64.7% 64.9% 65.3% 65.9% 66.5%

LT All All 37.4% 36.8% 36.4% 35.8% 35.3% 35.1% 34.7% 34.1% 33.5%

PC=passenger car; LT=light truck; EV=electric vehicle; G=gasoline; D=diesel.

Table 2-42 Tier 3 Reference Case Light-Duty Fleet Mix 

Vehicle

category

Engine

Fuel

2017 2018 2019 2020 2021 2022 2023 2024 2025

PC

I4 G 49.8% 51.9% 53.9% 56.0% 58.0% 60.1% 60.8% 61.5% 62.2%

I4 D 0.3% 0.2% 0.2% 0.1% 0.1% 0.0% 0.0% 0.0% 0.0%

V6 G 9.1% 7.7% 6.2% 4.8% 3.4% 1.9% 1.8% 1.6% 1.5%

V6 D 0.8% 0.6% 0.5% 0.3% 0.2% 0.0% 0.0% 0.0% 0.0%

V8 G 2.3% 2.2% 2.1% 2.1% 2.0% 1.9% 1.6% 1.3% 0.9%

V8 D 0.2% 0.1% 0.1% 0.1% 0.0% 0.0% 0.0% 0.0% 0.0%

LT

I4 G 19.1% 20.3% 21.4% 22.6% 23.7% 24.9% 26.0% 27.0% 28.1%

I4 D 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%

V6 G 11.1% 10.0% 8.9% 7.7% 6.6% 5.5% 4.9% 4.3% 3.7%

V6 D 0.1% 0.1% 0.1% 0.1% 0.1% 0.1% 0.1% 0.1% 0.1%

V8 G 6.9% 6.4% 6.0% 5.5% 5.1% 4.7% 3.7% 2.7% 1.7%

V8 D 0.1% 0.1% 0.1% 0.1% 0.0% 0.0% 0.0% 0.0% 0.0%

EV 0.2% 0.3% 0.5% 0.6% 0.8% 0.9% 1.2% 1.5% 1.8%

PC All All 62.6% 63.1% 63.5% 64.0% 64.4% 64.9% 65.4% 65.9% 66.4%

LT All All 37.4% 36.9% 36.5% 36.0% 35.6% 35.1% 34.6% 34.1% 33.5%

PC=passenger car; LT=light truck; EV=electric vehicle; G=gasoline; D=diesel.

One very important piece of information shown in the above tables is the gasoline I4 

share of the fleet mix—that share being 63% for passenger cars and 29% for light trucks. So, 

OMEGA projects that fully 92% of the light-duty fleet will be gasoline I4 by MY2025. With the 

exception of electric vehicles, gasoline I4 engines are the least costly of the vehicle categories at 
2-44

achieving Tier 3 emission levels. This helps, in part, to explain the large reduction in program 

costs (presented below) in this final rule analysis relative to the proposal. 

For heavy-duty Class 2b and 3, we expect no downsizing of engines or other changes to 

engines that might influence Tier 3 costs as a result of the MY 2014-2018 Heavy-duty GHG rule. 

Therefore, we are using the baseline fleet as the reference fleet for this analysis. However, we 

have updated the HD baseline fleet relative to the proposal using more recent MOVES data. 

Table 2-43 Projected Tier 3 Sales by Yeara

Vehicle

Category

Fuel

2017 2018 2019 2020 2021 2022 2023 2024 2025

PC I4 G 5,195,481 5,345,425 5,621,877 5,863,693 6,078,373 6,127,715 6,217,541 6,341,466 6,481,560

PC I4 D 22,542 16,732 11,301 5,685 0 0 0 0 0

PC V6 G 767,432 617,934 482,618 341,259 197,189 181,270 166,561 152,573 138,652

PC V6 D 65,042 48,787 33,640 17,961 2,080 1,852 1,637 1,427 1,217

PC V8 G 221,891 212,696 208,494 202,729 195,923 161,634 128,438 95,552 62,251

PC V8 D 14,440 10,718 7,239 3,642 0 0 0 0 0

LT I4 G 2,030,320 2,124,486 2,269,022 2,400,216 2,520,536 2,618,264 2,733,236 2,864,048 3,003,581

LT I4 D 0 0 0 0 0 0 0 0 0

LT V6 G 1,003,041 879,974 777,339 667,197 552,966 492,601 435,536 380,146 324,535

LT V6 D 11,155 9,982 9,041 8,017 6,947 6,342 5,779 5,241 4,705

LT V8 G 644,502 594,005 557,387 516,100 471,969 368,953 268,449 168,242 66,502

LT V8 D 11,102 8,301 5,688 2,985 247 223 202 181 160

EV 32,163 46,553 62,080 77,465 92,581 120,496 149,188 178,997 209,761

PC All 6,318,991 6,298,846 6,427,249 6,512,434 6,566,146 6,595,482 6,668,409 6,777,644 6,903,720

LT All 3,700,120 3,616,747 3,618,477 3,594,515 3,552,665 3,486,383 3,443,202 3,417,858 3,399,482

Lightduty All 10,019,111 9,915,593 10,045,726 10,106,949 10,118,811 10,081,865 10,111,611 10,195,502 10,303,202

Class 

2b G 413,426 411,174 412,765 410,660 409,218 405,730 407,101 411,430 415,032

Class 

2b D 28,228 27,710 27,572 27,320 27,253 27,018 26,979 27,101 27,219

Class 3 G 9,142 9,092 9,127 9,081 9,049 8,972 9,002 9,098 9,177

Class 3 D 97,119 95,336 94,863 93,995 93,764 92,955 92,821 93,243 93,649

Class 

2b G 441,654 438,884 440,337 437,980 436,470 432,747 434,080 438,532 442,252

Class 3 D 106,261 104,428 103,990 103,076 102,812 101,926 101,823 102,341 102,826

>14K 

HD G 53,101 52,557 53,216 53,508 53,558 53,349 53,505 53,952 54,514

Heavyduty All 601,015 595,869 597,544 594,563 592,841 588,023 589,408 594,824 599,592

LD + 

HD All 10,620,126 10,511,462 10,643,270 10,701,513 10,711,652 10,669,888 10,701,019 10,790,326 10,902,793

PC=passenger car; LT=light truck; EV=electric vehicle; LD=light-duty; HD=heavy-duty; G=gasoline; D=diesel. 

a Sales exclude vehicle sales in California and other states that have adopted LEVIII, or roughly 36% of the nationwide total; sales 

continue beyond 2025 but are not presented here.
2-45

Using these projected sales, we can calculate the annual costs of the Tier 3 vehicle 

program for each vehicle category/engine/fuel combination. We can then add the passenger car 

and light-duty truck results to get the costs for light-duty and add the Class 2b, 3 and >14,000 

pound HD costs to get the costs for heavy-duty. We have done this separately for the exhaust 

and evaporative standards and then the combined standards. The results are shown in Table 

2-45. 

In addition to considering the costs associated with improving the emission control 

systems on vehicles, we also expect that manufacturers will be required to improve their 

capability to measure particulate matter (PM) at the levels being required. For additional 

information on the test procedure changes, see Section IV.H of the preamble.

We are using the same PM facility upgrade cost inputs as used in the proposal, except 

that we have updated those costs to 2011 dollars. To determine the appropriate costs for 

upgrading test facilities for PM measurement we used two sources of information: The first was 

the cost that the EPA incurred in upgrading its own PM measurement equipment, and the second 

was information provided by vehicle manufacturers reflecting estimates for upgrading their 

internal facilities. The cost estimates ranged from $250,000 to $500,000 per PM test site (both in 

2010$). We recognize that the number of sites that a manufacturer will require is dependent on 

the number of vehicle models it expects to develop and certify in a given model year. As stated 

in Section IV.A, we have limited the number of certifications required per model year to 25 

percent of the represented durability groups, thereby potentially reducing the number of test sites 

that require upgrade. In addition, costs will vary by manufacturer depending on the state of their 

current test facilities. 

Our estimated costs for each manufacturer are show in Table 2-44. With a certification 

responsibility of 25 percent of its given model year durability groups we believe that 

manufacturers with annual sales of 1 million units or less will require 2 facility upgrades at an 

average cost of $375,000 (in 2010$, or $383,000 in 2011$). For manufacturers with greater than 

1 million units per year annual sales we believe that 4 facility upgrades may be required to meet 

the Tier 3 requirements. 

Table 2-44: PM Facility Costs Imposed by Tier 3 (2011$) 

Annual 

Sales 

Volume

# of PM 

Sites to be 

upgraded

Cost per site

Weigh 

Room 

Costs

Facility 

Cost/Manufacturer

# of 

Manufacturers

Total Costs

</= 1 

million 2

$383,000 $766,000 18 $13,800,000

> 1 million 4 $1,530,000 5 $7,66,000

Fleet 23 $21,400,000

Note that the number of manufacturers in the </= 1 million range has been reduced from 20 in the proposal to 18 in 

the final rule. This is because Chrysler, Fiat and Maserati are now treated as one manufacturer in the >1 million 

range rather than two in the </=1 million range (Fiat and Maserati) and one in the >1 million range (Chrysler).

We also anticipate that each manufacturer would hire a new full time employee to cover 

additional PM measurement-related work. We have estimated this employee to cost each 

manufacturer $153,000 (2011$) per year. With 23 manufacturers, the total cost would be 
2-46

$3,520,000 per year every year going forward. In contrast, the PM facility costs shown in Table 

2-44 represent one-time costs we expect to be incurred in the year prior to implementation of the 

standards. These costs are shown in Table 2-45. 

Table 2-45 Undiscounted Annual Costs of the Tier 3 Vehicle Program (Millions of 2011$) 

Exhaust Evaporative Operating Facility

& staff Total LD HD All LD HD All LD HD All

2016 $0 $0 $0 $0 $0 $0 $0 $0 $0 $21.4 $21.4

2017 $268 $0 $268 $25.5 $0 $25.5 $0 $0 $0 $3.52 $297

2018 $519 $20.2 $539 $70.2 $3.24 $73.4 -$1.17 -$0.047 -$1.22 $3.52 $615

2019 $555 $24.2 $579 $69.2 $3.18 $72.4 -$2.03 -$0.094 -$2.12 $3.52 $653

2020 $571 $27.8 $599 $94.3 $4.12 $98.4 -$3.22 -$0.160 -$3.38 $3.52 $697

2021 $598 $31.5 $630 $92.8 $4.04 $96.8 -$4.44 -$0.226 -$4.67 $3.52 $725

2022 $605 $34.8 $640 $116 $4.93 $121 -$5.96 -$0.309 -$6.27 $3.52 $758

2023 $606 $33.3 $639 $111 $4.73 $116 -$7.45 -$0.390 -$7.84 $3.52 $751

2024 $620 $33.1 $653 $109 $4.70 $114 -$8.95 -$0.472 -$9.42 $3.52 $761

2025 $635 $32.8 $668 $108 $4.66 $113 -$10.4 -$0.553 -$11.0 $3.52 $773

2030 $632 $31.8 $664 $108 $4.56 $113 -$18.0 -$0.959 -$19.0 $3.52 $761

Note: Costs shown include costs for the Tier 3 standards on vehicles sold outside California and other states that 

have adopted LEVIII; operating savings use untaxed gasoline prices.

 

By then sales weighting the exhaust and evaporative results by sales in each of the 

vehicle category/engine/fuel combinations, we can calculate the annual technology costs for 

passenger cars, light-duty trucks and heavy-duty trucks. We show these cost per vehicle results 

for the exhaust standards in Table 2-46, for the evaporative standards in Table 2-47and for the 

combined exhaust and evaporative standards in Table 2-48. The costs shown in these three 

tables include all direct and indirect costs for new vehicle hardware (they exclude operating 

savings and PM facility costs). They also include the effects of learning, and the expected 

penetration rates and phase-ins of the Tier 3 standards. 

Table 2-46 Cost per Vehicle for the Tier 3 Exhaust Emission Standards (2011$) 

2017 2018 2019 2020 2021 2022 2023 2024 2025

Passenger car $42 $45 $47 $48 $50 $52 $52 $54 $55

Light-duty truck $0 $65 $70 $72 $76 $76 $75 $75 $75

All light-duty $27 $52 $55 $56 $59 $60 $60 $61 $62

Class 2b $0 $38 $45 $52 $59 $65 $63 $62 $60

Class 3 $0 $32 $41 $48 $56 $64 $61 $60 $59

>14K HD $0 $0 $0 $0 $0 $0 $0 $0 $0

All heavy-duty $0 $34 $40 $47 $53 $59 $57 $56 $55

All LD and HD $25 $51 $54 $56 $59 $60 $60 $61 $61

Note: Costs shown include costs for the Tier 3 standards on vehicles sold outside California and other states that 

have adopted LEVIII.

 
2-47

Table 2-47 Cost per Vehicle for the Tier 3 Evaporative Emission Standards (2011$) 

2017 2018 2019 2020 2021 2022 2023 2024 2025

Passenger car $4 $7 $7 $9 $9 $11 $11 $11 $10

Light-duty truck $0 $8 $8 $10 $10 $12 $11 $11 $11

All light-duty $3 $7 $7 $9 $9 $12 $11 $11 $11

Class 2b $0 $6 $6 $8 $8 $9 $9 $9 $9

Class 3 $0 $1 $1 $1 $1 $1 $1 $1 $1

>14K HD $0 $10 $10 $13 $13 $16 $15 $15 $15

All heavy-duty $0 $5 $5 $7 $7 $8 $8 $8 $8

All LD and HD $2 $7 $7 $9 $9 $11 $11 $11 $10

Note: Costs shown include costs for the Tier 3 standards on vehicles sold outside California and other states that 

have adopted LEVIII.

 

Table 2-48 Cost per Vehicle for the Combined Tier 3 Exhaust and Evaporative Emission 

Standards (2011$) 

2017 2018 2019 2020 2021 2022 2023 2024 2025

Passenger car $46 $51 $53 $57 $59 $63 $63 $64 $65

Light-duty truck $0 $73 $78 $82 $86 $88 $87 $87 $86

All light-duty $29 $59 $62 $66 $68 $72 $71 $72 $72

Class 2b $0 $44 $51 $60 $66 $75 $71 $70 $69

Class 3 $0 $33 $41 $49 $57 $65 $62 $61 $60

>14K HD $0 $10 $10 $13 $13 $16 $15 $15 $15

All heavy-duty $0 $39 $46 $54 $60 $68 $65 $64 $62

All LD and HD $28 $58 $61 $65 $68 $71 $71 $71 $72

Note: Costs shown include costs for the Tier 3 standards on vehicles sold outside California and other states that 

have adopted LEVIII.

 
2-48

References 

1

 ICCT Comments in Response to the Tier 3 Proposed Rulemaking, Docket ID No. EPA-HQ-OAR-2011-0135-

4304; Posada, Francisco, et. al., “Estimated Cost of Emission Control Technologies for Light-Duty Vehicles Part 1 – 

Gasoline,” SAE 2013-01-0534, 4/8/2013. 

2

 California Air Resources Board Initial Statement of Reasons, Public Hearing to Consider LEV III , December 7, 

2011, Workshop Document (http://www.arb.ca.gov/regact/2012/leviiighg2012/leviiighg2012.htm), Document ID# 

EPA-HQ-OAR-2011-0135-0438. 

3

 “The Effects of Fuel Sulfur Level on Emissions from Tier 2 Vehicles in the In-Use Fleet,” EPA-420-D-13-003. 

Available in docket number EPA-HQ-OAR-2011-0135. 

4

 The 2012-2016 GHG final rule can be found at 75 FR 25374; the 2017-2025 GHG final rule can be found at 77 FR 

62624. 

5

 RTI International. Automobile Industry Retail Price Equivalent and Indirect Cost Multipliers. February 2009. 

http://www.epa.gov/otaq/ld-hwy/420r09003.pdf ; Rogozhin, A.,et al., “Using indirect cost multipliers to estimate the 

total cost of adding new technology in the automobile industry,” International Journal of Production Economics 

(2009), doi:10.1016/j.ijpe.2009.11.031. The peer review for the RTI report is at http://www.epa.gov/otaq/ldhwy/420r09004.pdf . 

6

 “Joint Technical Support Document: Final Rulemaking for 2017-2025 Light-Duty Vehicle Greenhouse Gas 

Emission Standards and Corporate Average Fuel Economy Standards,” EPA-420-R-12-901, August 2012, 

Document ID# EPA-HQ-OAR-2011-0135-4948.

7

 75 FR 25324, 76 FR 57106, 77 FR 62624, 78 FR 29816. 

8

 Posada, Francisco, et. al., “Estimated Cost of Emission Control Technologies for Light-Duty Vehicles Part 1 – 

Gasoline,” SAE 2013-01-0534, 4/8/2013. 

9

 “Regulatory Impact Analysis: Heavy-Duty Engine and Vehicle Standards and Highway Diesel Fuel Sulfur Control 

Requirements,” EPA420-R-00-026, December 2000; “Final Regulatory Analysis: Control of Emissions from 

Nonroad Diesel Engines,” EPA420-R-04-007, May 2004; “Regulatory Impact Analysis: Control of Emissions of 

Air Pollution from Locomotive Engines and Marine Compression Ignition Engines Less than 30 Liters Per 

Cylinder,” EPA420-R-08-001, March 2008. 

10 Ball, Douglas and David Moser, “Cold Start Calibration of Current PZEV Vehicles and the Impact of LEV-III 

Emission Regulations,” SAE 2012-01-1245, 4/16/2012. 

11 See ICCT, Docket ID No. EPA-HQ-OAR-2011-0135-4304, at page 4 of 21; see MECA, Docket ID No. EPA-HQOAR-2011-0135-4675, at page 3 of 7; see CARB, Docket ID No. EPA-HQ-OAR-2011-0135-4621, at page 23. 

12 See ICCT, Docket ID No. EPA-HQ-OAR-2011-0135-4304, at page 11 of 21; see MECA, Docket ID No. EPAHQ-OAR-2011-0135-4675, at page 3 of 7. 

13 OMEGA is the Optimization Model for reducing Emissions of Greenhouse gases from Automobiles. Information 

about OMEGA can be found at http://www.epa.gov/otaq/climate/models.htm. 
2-49

14 See Chapter 1 of “Regulatory Impact Analysis: Final Rulemaking for 2017-2025 Light-Duty Vehicle Greenhouse 

Gas Emission Standards and Corporate Average Fuel Economy Standards,” EPA-420-R-12-016, August 2012. 
3-1

Chapter 3 Establishing New Emission Test Fuel Parameters 

In-use gasoline has changed considerably since EPA’s emission test gasoline 

specifications were first set and last revised. Sulfur and benzene content have been reduced and, 

perhaps most visibly to consumers, gasoline containing 10 percent ethanol by volume (E10) has 

replaced non-oxygenated gasoline (E0) across the country. The relationship between emissions 

certification test fuel and in-use fuel is important in recognition of the fact that fuel properties 

can affect emission levels. Therefore, in revising specifications for emission test gasoline, it is 

important to have a thorough assessment of fuel available to the public. 

We primarily used two sources of fuel property information to determine appropriate 

specifications for emissions test fuel. One was the Reformulated Gasoline and Anti-Dumping 

Batch Report data submitted to EPA (referred to in this section as batch data). Producers and 

importers of gasoline and related blendstocks must submit data to EPA for each batch of gasoline 

produced or imported. These data include batch volume as well as physical and chemical 

properties that can be used to determine whether the fuel is compliant with applicable standards 

and regulations. These reports are considered Confidential Business Information and thus only 

aggregated data is presented here. 

The second data source was the Alliance of Automobile Manufacturers (AAM) North 

American Fuel Survey. Each summer and winter, the AAM collects over 300 gasoline samples 

from retail stations in 29 major metropolitan areas in 23 states plus the District of Columbia. 

Areas currently sampled include: Albuquerque, NM; Atlanta, GA; Billings, MT; Boston, MA; 

Chicago, IL; Cleveland, OH; Dallas, Houston, and San Antonio, TX; Denver, CO; Detroit, MI; 

Fairbanks, AK; Kansas City and St. Louis, MO; Las Vegas, NV; Los Angeles and San Francisco, 

CA; Memphis, TN; Miami, FL; Minneapolis/St. Paul, MN; New Orleans, LA; New York, NY; 

Philadelphia and Pittsburgh, PA; Phoenix, AZ; Salt Lake City, UT; Seattle, WA; Washington, 

D.C.; and Watertown, SD. Although the AAM North American Fuel Survey does not represent 

all U.S. gasoline, it is designed to have good coverage of the U.S. market. 

Note that this assessment focuses on fuel properties for summertime, regular grade, E10 

gasoline since this is most relevant to the certification testing conditions and fuel specifications. 

3.1 Assessment of Current Gasoline Properties 

3.1.1 Ethanol Content 

According to the Energy Information Administration (EIA), ethanol is now blended into 

almost every gallon of U.S. gasoline, bringing the average gasoline ethanol content to 9.7 percent 

denatured ethanol by volume (vol%) as shown in Figure 3-1. Denaturant, generally a 

hydrocarbon blendstock such as natural gas liquids or low-octane gasoline components, is added 

at a rate of approximately 2 volume percent by the ethanol producer before shipping it to fuel 

terminals. (This is required to differentiate the product from beverage alcohol.) 
3-2

Figure 3-1. Denatured Ethanol Content in U.S. Gasoline Over Time1

The plot shows a rapid increase in ethanol content starting around 2002 and leveling out 

after 2010 as it approaches 10 percent volume (this average figure also includes a small amount 

of E85 use in Flex Fuel vehicles). While EPA has approved use of E15 in gasoline vehicles of 

model year 2001 and later, its use has not yet become widespread.A

Figure 3-2 shows the distribution of ethanol levels across 404 regular grade summer E10 

gasoline samples collected by AAM in 2010 and 2011. These data suggest the range of ethanol 

blending in E10 is relatively narrow, with most samples falling between 9.3 and 10.0 volume 

percent (excluding denaturant). Higher and lower values in the data are likely due to test method 

uncertainty. Based on this information, an emission test fuel target of 9.8 volume percent 

ethanol (excluding denaturant) is appropriate. 

 

A

 The E15 approval decision was published in 76 FR 4662 (January 26, 2011). 
3-3

0 %

5 %

10%

15%

20%

8.5 8.7 8.9 9.1 9.3 9.5 9.7 9.9 10.1 10.3 10.5

Percent of Samples

Volume Percent Ethanol (ASTM D5599)

Figure 3-2. Range of Ethanol in E10 Gasoline in 2010-11 AAM Summer Surveys 

3.1.2 Octane 

U.S. gasoline must meet a minimum octane rating (also known as (R+M)/2 or anti-knock 

index, AKI) of 87 for regular grade in most parts of the country. Denatured fuel ethanol has a 

typical octane rating of 115 AKI, making it a high-octane blendstock. However, finished 

gasoline has not experienced an increase in octane due to increased ethanol blending. Given this 

situation, along with data presented in the next subsection, it is evident that many refiners have 

backed off on octane production at the refinery by reducing levels of aromatics and olefins. 

Producing these high-octane components at the refinery represents a significant cost to refiners, 

so they are able to reduce costs by taking advantage of ethanol’s octane value. We estimate that 

many refiners are currently producing 84-85 AKI blendstocks for 87 octane regular-grade 

gasoline and 88-89 AKI blendstocks for 91 octane premium-grade gasoline, such that the final 

E10 blends meet minimum octane requirements. 

According to AAM summer fuel surveys, the average octane of finished regular grade 

gasoline has remained constant between 87-88 AKI over the past decade (refer to Figure 3-3) 

despite the increasing blend level of ethanol. According to EIA’s Petroleum Marketing Annual, 

regular grade gasoline represents over 85 percent of U.S. sales.2 Accordingly, we believe the 

updated 87-88.4 (R+M)/2 test fuel specification is representative of regular grade in-use 

gasoline. 
3-4

87.1 86.9 87.0 86.9 87.0 87.2 87.2 87.4 88.1 87.4 87.8 87.4

1.3 1.3 1.5

2.1

2.5

2.9

3.9

4.8

7.0

8.0

9.3

9.6

0

2

4

6

8

1 0

1 2

1 4

0

10

20

30

40

50

60

70

80

90

100

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 Gasoline Ethanol Concentration (vol%) Gasoline Octane (R+M/2)

Avg. Octane (AAM) Avg. EtOH (EIA)

Figure 3-3. Average Summer Regular Grade Octane and Ethanol Levels Over Time 

3.1.3 Total Aromatics and Total Olefins 

The term olefin describes a hydrocarbon compound containing at least one unsaturated or 

double bond. Aromatics are a specific class of olefins that contain the benzene ring. When 

crude oil is distilled into various fractions according to boiling range, the fraction going into the 

gasoline pool, called straight run naphtha, contains primarily saturated hydrocarbons. Both 

olefins and aromatics have higher AKI values relative to saturates, and therefore increasing their 

proportions in the finished gasoline is an important method refiners use to meet required AKI 

targets. 

Ethanol also has a high AKI value, and as it has become more ubiquitous as a blendstock, 

refiners are relying on it to an increasing extent to meet octane targets. The average aromatics, 

olefin, and ethanol levels by year for all summer gasoline are shown in Figure 3-4. Here we can 

see a general trend of aromatic and olefin levels declining as fuel ethanol content increased. 

Using 2010-11 AAM survey data, the average aromatics content of conventional regular grade 

E10 gasoline (172 samples) was 24.3 vol% and the average olefins content was 7.3 vol%. When 

interpreting these aromatics results as a basis for updating test fuel specifications, we considered 
3-5

the fact that ASTM D1319 (used for the AAM surveys) gives a numerical value between 1-2 

vol% higher than ASTM D5769 (specified for test fuel analysis) for the same fuel sample.B

26.6

27.1

26.0

26.5

27.3

26.4

25.6

25.1

23.5 23.6

22.6

24.5

9.1

8.4

7.2 7.4

8.1 8.4

7.5 7.3

8.2

6.9 7.3 7.1

1.3 1.3 1.5

2.1

2.5 2.9

3.9

4.8

7.0

8.0

9.3

9.6

0

5

10

15

20

25

30

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 Proportoin in Gasoline (vol%)

Avg. Corrected Aromatics (AAM)

Avg. Corrected Olefins (AAM)

Avg. EtOH (EIA)

Figure 3-4. Average Summer Gasoline Aromatics, Olefin and Ethanol Levels Over Time 

Although total aromatics and olefins have been reduced over the past decade, there 

continues to be variation on a batch-by-batch and geographic basis. Our refinery batch data for 

summer 2011 shows a range of gasoline aromatics levels from approximately 5 to 50 vol% with 

an average concentration of 24 vol% (Figure 3-5), and a range of olefin levels from 0 to 25 vol% 

with an average concentration of 11 vol% (Figure 3-6). The 2011 batch data shown in Figures 3-

5 and 3-6 only reflects the effect of ethanol in reformulated gasoline that is match blended to 

account for it. It does not account for ethanol that may be blended into conventional gasoline 

after it leaves the refinery since existing gasoline regulations do not readily allow refiners to take 

advantage of ethanol properties in most compliance calculations. As a result, AAM and other 

gasoline surveys may show lower aromatics and olefins than what is suggested by the batch data. 

 

B

 Information based on analysis of several recent ASTM cross-check datasets. 
3-6

0 %

10%

20%

30%

40%

50%

60%

0 % 20% 40% 60% 80% 100%

Total Aromatics (volume %)

Cumulative Gasoline Volume (% Total)

Figure 3-5. Gasoline Aromatics Distribution Based on Summer 2011 Refinery Batch Data 

0 %

5 %

10%

15%

20%

25%

30%

35%

40%

0 % 20% 40% 60% 80% 100%

Olefins (volume %)

Cumulative Gasoline Volume (% Total)

Figure 3-6. Gasoline Olefins Distribution Based on Summer 2011 Refinery Batch Data 

In the summer of 2010, according to the AAM North American Fuel Survey, measured 

in-use aromatics levels ranged from 3 to 47 vol% (Figure 3-7) while olefin levels ranged from 
3-7

0.6 to 17 vol% (Figure 3-8). California tends to have lower, tighter in-use levels of aromatics 

and olefins as a result of their more stringent fuel regulations. As shown below, gasoline 

samples taken from Los Angeles and San Francisco had aromatics levels ranging from 10 to 30 

vol% and olefin levels ranging from 1 to 8 vol%. Nevertheless, our updated emission test fuel 

specifications for aromatics and olefins still overlap with those established by the California Air 

Resources Board (CARB) for LEV III test fuel.C

 

Figure 3-7. Range of Total Aromatics by AAM City Surveyed, Summer 2010 

 

C

 California LEV III emission test procedures, including fuel specifications, are available at 13 CCR 1961.2. 
3-8

0

2

4

6

8

1 0

1 2

1 4

1 6

1 8 Corrected Olefins, vol%

Cities Sampled, Summer 2010

Figure 3-8. Range of Olefins by AAM City Surveyed, Summer 2010 

3.1.4 Aromatics Species 

Gasoline speciation data performed by EPA and others shows a wide range of aromatic 

molecule configurations from benzene (C6, meaning it contains six carbon atoms), and toluene 

(C7), to larger more complicated C10+ aromatics. Between 2007 and 2011, EPA performed 

aromatic speciation analyses on 52 fuel samples from various locations throughout the country. 

Approximately 60 percent were RFG oversight samples (supplied by refiners as part of the RFG 

program) and the remainder were audit samples collected mostly from retail outlets as part of the 

City Surveys provision in the RFG program. Total aromatics ranged from 6 to 39 percent of 

gasoline by volume, but the relative proportions of molecular species by carbon number were 

relatively consistent across the samples (Figure 3-9). 
3-9

0 %

10%

20%

30%

40%

50%

60%

70%

80%

90%

100% Conroe, TX Ponder, TX Arlington, TX North Billerica, MA River Edge, NJ Olympa Fields, IL Brick Township, NJ Essington, PA Essington, PA Linden, NJ Deer Park, TX Romeoville, IL Bayonne, NJ St. Rose, LA Deer Park, TX Linden, NJ Newport News, VA Bayonne, NJ Essington, PA Carteret, NJ Linden, NJ West Bend, WI Watertown, MA Montgomery, NY Houston, TX Linden, NJ Houston, TX Bayonne, NJ Deer Park, TX Deer Park, TX Essington, PA Deer Park, TX Linden, NJ St. Rose, LA Essington, PA St. Rose, LA New Haven, CT Deer Park, TX Essington, PA Linden, NJ Linden, NJ Deer Park, TX Carteret, NJ Homewood, IL Union City, NJ Stewartsville, NJ Bayonne, NJ Milwaukee, WI Roslyn Heights, NY Fort Worth, TX Franklin, NJ Fisherville, KY Proportion of Total Aromatics 

C10+

C9

C8

C7

C6

Figure 3-9. Proportions of Aromatic Species by Carbon Number and Sample Location, 

Based on EPA Samples Taken Over 2007-2011

The relative proportion of aromatics of varying molecular size is of interest in light of a 

growing number of studies showing the influence of higher-boiling aromatic compounds on 

particulate matter (PM) emissions from gasoline vehicles. A study published by the Japan 

Petroleum Energy Center (JPEC) found that PM mass emissions from a light-duty gasoline 

vehicle increased with increasing carbon number of aromatics in the gasoline.3 Honda has 

published a “PM Index” that correlates PM emissions to the double bond equivalent (DBE) and 

vapor pressure (V.P) of the fuel components.4The PM index is a function of all the gasoline 

components (i) and their respective weight percent (Wti) as shown in Equation 1. DBE is an 

indication of the number of double bonds and rings present in the molecule. For example, 

benzene (C6H6) would have a DBE of four (three double bonds plus one ring) while naphthalene 

(C10H8), would have a DBE of seven (five double bonds plus two rings). According to this 

model, gasoline containing a large fraction of low-volatility compounds with high DBE values is 

expected to produce greater PM emissions. 

Equation 1. Particulate Matter Index Calculation 
3-10

Since aromatics do not appear to be created equally in terms of the potential impact on 

vehicle PM emissions, we believe it is prudent that both the amount and distribution of aromatics 

in the updated emissions test fuel is representative of in-use fuel. Figure 3-10 shows averages 

and ranges of EPA aromatics speciation data with test fuel specification ranges shown in blue. 

0.6

5.2

6.5

5.9

4.7

0

1

2

3

4

5

6

7

8

9

C6 (Q) C7 (Q) C8 (Q) C9 (Q,J) C10+ (Q,G,H,J)

Groups Included:

Q = Mono-aromatics

G = Naphthalenes

H = Napthleneo/OlefinoBenzenes

J = Indenes 5.2-6.4% 4.4-5.6%

Proportions adjusted to total aromatics of 23.0 vol%

0.5-0.7%

Figure 3-10. Mean and Standard Deviation of Aromatics Speciation Data with Test Fuel 

Specification Ranges Shown in Blue

3.1.5 Distillation Temperatures 

As shown below in Figure 3-11, AAM survey data suggests there has not been a large 

change in gasoline volatility curves for summer gasoline over the past decade as ethanol 

blending has increased. The T50 and T90 temperatures are treated in more detail in subsections 

below. 
3-11

136 136 138 138 137 139 137 137 136 135 134 133

208 207 210 210 211 210 212 210 204 207 205 202

329 324 328 329 329 325 325 326

317

326 322 319

405 401 407 409 411 408 406 410

397

411 407 402

0

100

200

300

400

500

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 Gasoline Distillation (°F)

Avg. T10 (AAM) Avg. T50 (AAM) Avg. T90 (AAM) Avg. FBP (AAM)

Figure 3-11. Summer Gasoline Distillation Temperatures Over Time From AAM Surveys 

3.1.5.1 T50 analysis 

Splash-blending 10 percent ethanol in an E0 base typically lowers T50 by several degrees 

relative to the base gasoline. Given that much of the refinery batch data for conventional 

gasoline in 2011 did not capture the property changes resulting from ethanol blending, we would 

expect the curve in Figure 3-12 to be shifted downward, putting it in closer agreement with the 

AAM survey data average of around 202°F as shown in Figure 3-11. The AAM survey data in 

Figure 3-13 shows that T50 varies widely in in-use fuel, from around 150°F to 220°F. Plotting 

T50 by RVP reveals that T50 values span a higher and narrower range in reformulated and 

volatility-control-area fuels (on the left, below about 8.5 psi) compared to conventional gasoline 

(above about 9 psi). Adopting a wide specification for test fuel to cover this whole range may 

have undesirable effects on consistency of vehicle test results between facilities and over time. 

Therefore, we have chosen a range of 190-210°F to represent both fuel types and maintain some 

overlap with CARB’s specification of 205-215°F. 
3-12

140

160

180

200

220

240

260

0 % 20% 40% 60% 80% 100%

T50 (F)

Cumulative Gasoline Volime (% Total)

Figure 3-12. Gasoline T50 Range Based on Summer 2011 Refinery Batch Data 

140

150

160

170

180

190

200

210

220

230

240

7 8 9 1 0 1 1

T50 (deg.F)

RVP (psi)

Figure 3-13. T50 Range in 2010-11 Summer Gasoline as Reported in AAM Surveys 
3-13

3.1.5.2 T90 Analysis 

To develop an understanding of the variation of T90 over the pool of gasoline produced 

or imported during the 2011 averaging period, we plotted T90 versus cumulative gasoline 

volume. Approximately 90% of the T90 data is linearly distributed along the center portion of 

the plot. The remaining 10% of the T90 data is comprised of outliers, with the lower and upper 

end of the temperature spectrum tailing off slightly. The volume-weighted average T90 was 

325F (see Figure 3-14). T90 is relatively insensitive to ethanol blending at the 10 percent level, 

and therefore we see good agreement between the batch and AAM datasets on average value. 

Figure 3-15 shows AAM T90 data plotted by RVP, where there appears to be much less 

influence difference between reformulated and conventional fuel pools. Based on this 

information, we set the test fuel specification range at 315-335°F. 

260

280

300

320

340

360

380

400

0 % 20% 40% 60% 80% 100%

T90 (F)

Cumulative Gasoline Volime (% Total)

Figure 3-14. Gasoline T90 Range Based on Summer 2011 Refinery Batch Data 
3-14

270

280

290

300

310

320

330

340

350

360

370

7 8 9 1 0 1 1

T90 (deg.F)

RVP (psi)

Figure 3-15. T90 Range in 2010-11 Summer Gasoline as Reported in AAM Surveys 

3.1.6 Sulfur and Benzene 

Gasoline sulfur levels have declined significantly over the past decade under the Tier 2 

gasoline program.D

 The phase-in period of those standards began in 2004 and continued until 

2011, when all geographic and small refiner relief provisions ended. According to AAM 

summer fuel surveys, average gasoline sulfur has gone from over 150 ppm in 2000 to less than 

30 ppm (the Tier 2 average standard) in 2012 (refer to Figure 3-16). Refinery batch reports for 

2011 (refer to Figure 3-17) depict a volume-weighted average gasoline sulfur just below 30 ppm. 

Again, given that refinery certification data does not include all ethanol blended into 

conventional gasoline, the average sulfur content in-use is expected to be slightly lower, which is 

consistent with the AAM data. 

After the phase-in of the Tier 3 sulfur limits, gasoline sulfur levels are required to fall to 

10 ppm. Sulfur naturally occurs in crude oil and most refineries must spend money to install and 

operate units that remove it from gasoline. This sulfur byproduct of refining has little market 

value itself, so significant overcompliance with this standard is not expected. Accordingly, the 

updated test fuel sulfur specification is being set to a range of 8-11 ppm. 

 

D

 The Tier 2 final rulemaking was published in 65 FR 6698 (February 10, 2000). 
3-15

Gasoline benzene levels have also fallen in recent years primarily due to the MSAT2 

program, which enacted an annual average standard of 0.62 volume percent benzene across all 

gasoline effective January, 1, 2011.E According to AAM summer fuel surveys, average gasoline 

benzene content has declined from almost 1 vol% in 2006 to less than 0.7 vol% in 2011 (refer to

Figure 3-16). This is in general agreement with refinery batch reports where volume-weighted 

average benzene was less than 0.6 vol% in summer 2011 (refer to Figure 3-18). Again, given 

that refinery certification data does not include all ethanol blended into conventional gasoline, it 

is reasonable that the average benzene content shown in the AAM data is a bit lower than 

suggested by the batch reports. 

Some benzene naturally occurs in crude oil, but the majority that ends up in finished 

gasoline is produced during refinery operations intended to increase the total aromatics content 

to meet octane requirements. Therefore most refineries must spend money to install and operate 

units that remove benzene from certain blendstock streams before the finished gasoline is made. 

In some areas of the country (such as the Gulf Coast), benzene has significant value as a 

chemical feedstock and may be extracted from gasoline at a rate that is greater than would 

otherwise be required to meet fuel regulations. In most areas of the country, however, meeting 

the gasoline benzene limits is the sole driver of any reduction process, and therefore due to the 

averaging, banking, and trading provisions in the regulations we don’t expect significant 

overcompliance on a nationwide basis. Therefore we believe an emissions test fuel benzene 

specification of 0.5-0.7 vol% is representative of in-use gasoline now and going forward. These 

benzene and sulfur specifications are consistent with CARB’s LEV III specifications. 

 

E

 The MSAT 2 final rulemaking was published in 72 FR 8428 (February 26, 2007). 
3-16

152 156

148

135

7 9

7 6

4 5

3 3 3 2

2 7 2 8 2 4

0.95 0.94

0.85

0.87

0.90

0.95 0.97 0.96

0.89

0.80 0.79

0.68

0.0

0.2

0.4

0.6

0.8

1.0

1.2

0

20

40

60

80

100

120

140

160

180

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 Gasoline Benzene Concentration (vol%) Gasoline Sulfur Concentration (ppm)

Avg. Sulfur (AAM) Avg. Benzene (AAM)

Figure 3-16. Average Summer Sulfur and Benzene Levels Over Time from AAM Surveys 
3-17

0

1 0

2 0

3 0

4 0

5 0

6 0

7 0

8 0

0 % 20% 40% 60% 80% 100%

Sulfur (ppm)

Cumulative Gasoline Volime (% Total)

Figure 3-17. Gasoline Sulfur Based on Summer 2011 Refinery Batch Data 

0 %

1 %

2 %

3 %

4 %

5 %

0 % 20% 40% 60% 80% 100%

Benzene (vol%)

Cumulative Gasoline Volume (% Total)

Figure 3-18. Gasoline Benzene Based on 2011 Refinery Batch Data 
3-18

3.2 Gasoline Emission Test Fuel Specifications 

As explained in Section IV.F of the preamble, we are updating federal emission test fuel 

specifications to better match in-use fuel. The revised test fuel specifications apply for exhaust 

emissions testing, fuel economy/greenhouse gas testing, and emissions testing for non-exhaust 

emissions (evaporative, refueling, and leak detection testing). The revised gasoline 

specifications, found at §1065.710 and shown here in Table 3-1, apply to emissions testing of 

light-duty cars and trucks as well as heavy-duty gasoline vehicles certified on the chassis test, 

those subject to the Tier 3 standards. For information on how we arrived at the revised ASTM 

test procedures, refer to Section 3.3. Commercial gasoline or “street fuel” would continue to be 

used for service accumulation (durability fuel). This is consistent with CARB’s LEV III 

approach and should help limit the total number of test fuels that automakers need to manage. 
3-19

Table 3-1. Gasoline Emission Test Fuel Specifications 

Property Unit

SPECIFICATION

Reference 

Procedure1

General 

Testing

LowTemperature 

Testing

High Altitude 

Testing

Antiknock Index 

(R+M)/2 - 87.0 - 88.42

87.0 Minimum ASTM D2699 and 

D2700

Sensitivity (R-M) - 7.5 Minimum ASTM D2699 and 

D2700

Dry Vapor Pressure 

Equivalent (DVPE)

3,4 kPa (psi) 60.0-63.4 

(8.7-9.2)

77.2-81.4

(11.2-11.8)

52.4-55.2 

(7.6-8.0) ASTM D5191

Distillation4

10% evaporated °C (°F) 49-60(120-140)

43-54 

(110-130)

49-60

(120-140)

ASTM D86

50% evaporated °C (°F) 88-99 (190-210)

90% evaporated °C (°F) 157-168 (315-335)

Evaporated final 

boiling point °C (°F) 193-216 (380-420)

Residue milliliter 2.0 Maximum

Total Aromatic 

Hydrocarbons volume % 21.0-25.0

ASTM D5769

C6 Aromatics 

(benzene) volume % 0.5-0.7

C7 Aromatics 

(toluene) volume % 5.2-6.4

C8 Aromatics volume % 5.2-6.4

C9 Aromatics volume % 5.2-6.4

C10+ Aromatics volume % 4.4-5.6

Olefins5 mass % 4.0-10.0 ASTM D6550

Ethanol blended volume % 9.6-10.0 See 

§1065.710(b)(3)

Ethanol confirmatory6volume % 9.4-10.2 ASTM D4815 or 

D5599

Total Content of 

Oxygenates Other than 

Ethanol6

volume % 0.1 Maximum ASTM D4815 or 

D5599

Sulfur mg/kg 8.0-11.0 ASTM D2622, 

D5453 or D7039

Lead g/liter 0.0026 Maximum ASTM D3237

Phosphorus g/liter 0.0013 Maximum ASTM D3231

Copper Corrosion - No. 1 Maximum ASTM D130

Solvent-Washed Gum 

Content

mg/100 

milliliter 3.0 Maximum ASTM D381

Oxidation Stability minute 1000 Minimum ASTM D525

1ASTM procedures are incorporated by reference in §1065.1010. See §1065.701(d) for other allowed procedures.

2Octane specifications apply only for testing related to exhaust emissions. For engines or vehicles that require the 

use of premium fuel, as described in paragraph (d) of this section, the adjusted specification for antiknock index is a 

minimum value of 91.0; no maximum value applies. All other specifications apply for this high-octane fuel.

3Calculate dry vapor pressure equivalent, DVPE, based on the measured total vapor pressure, pT, using the following 

equation: DVPE (kPa) = 0.956∙pT - 2.39 (or DVPE (psi) = 0.956∙pT – 0.347. DVPE is intended to be equivalent to 

Reid Vapor Pressure using a different test method.

4

Parenthetical values are shown for informational purposes only. 
3-20

5The reference procedure prescribes measurement of olefin concentration in mass %. Multiply this result by 0.857 

and round to the first decimal place to determine the olefin concentration in volume %. 

6The reference procedure prescribes concentration measurements for ethanol and other oxygenates in mass %. 

Convert results to volume % as specified in Section 14.3 of ASTM D4815.

Along with updated emission test fuel parameters, we are adding specifications for 

distillation residue, total content of oxygenates other than ethanol, copper corrosion, solventwashed gum content, and oxidation stability. These parameters, summarized in Table 3-1, are 

consistent with ASTM D-4814 gasoline specifications and CARB’s LEV III test fuel 

requirements. 

3.3 Changes to ASTM Test Methods 

Many of the test methods specified in 40 CFR 86.113 for gasoline used in exhaust and 

evaporative emission testing have been retained in 40 CFR 1065.710 test fuel specification for 

ethanol-blended gasoline. However, some test methods have been replaced with methods 

deemed more appropriate, easier to use, or more precise. The following paragraphs highlight the 

new reference methods. 

ASTM D323 “Standard Test Method for Vapor Pressure of Petroleum Products (Reid 

Method)” is not applicable to ethanol-blended gasoline. It is being replaced with an automated 

ASTM D5191 “Standard Test Method for Vapor Pressure of Petroleum Products (Mini 

Method),” which is appropriate for ethanol-blended gasoline. 

ASTM D1319 “Standard Test Method for Hydrocarbon Types in Liquid Petroleum 

Products by Fluorescent Indicator Adsorption” is required by 40 CFR 86.113 for use in the 

measurement of aromatics and olefins. It is being replaced with ASTM D5769 “Standard Test 

Method for Determination of Benzene, Toluene, and Total Aromatics in Finished Gasolines by 

Gas Chromatography/Mass Spectrometry” and ASTM D6550 “Standard Test Method for 

Determination of Olefin Content of Gasolines by Supercritical-Fluid Chromatography.” Method 

D5769 enables simultaneous determination of the total aromatic hydrocarbon content, carbon 

number-specific content, and benzene content and is already being used in reformulated gasoline 

applications. ASTM D1319 does not identify aromatics by carbon number, which is now 

required for the Tier 3 test fuel in 40 CFR 1065.710. In addition, ASTM D5769 and D6550 are 

more precise and less labor-intensive than ASTM D1319. 

Measurement of oxygenates, including ethanol, is being updated to allow two methods 

that produce equivalent results: ASTM D4815, “Standard Test Method for Determination of 

MTBE, ETBE, TAME, DIPE, tertiary-Amyl Alcohol and C1 to C4 Alcohols in Gasoline by Gas 

Chromatography” and ASTM D5599, “Standard Test Method for Determination of Oxygenates 

in Gasoline by Gas Chromatography and Oxygen Selective Flame Ionization Detection”.

For sulfur measurements, ASTM D1266 “Standard Test Method for Sulfur in Petroleum 

Products (Lamp Method)” is being replaced with three automated methods: ASTM D2622 

“Standard Test Method for Sulfur in Petroleum Products by Wavelength Dispersive X-ray 

Fluorescence Spectrometry”, ASTM D5453 “Standard Test Method for Determination of Total 
3-21

Sulfur in Light Hydrocarbons, Spark Ignition Engine Fuel, Diesel Engine Fuel, and Engine Oil 

by Ultraviolet Fluorescence” and ASTM D7039 “Standard Test Method for Sulfur in Gasoline 

and Diesel Fuel by Monochromatic Wavelength Dispersive X-ray Fluorescence Spectrometry.” 

These three new methods are significantly less labor-intensive than ASTM D1266 and are 

widely used in the measurement of sulfur content in petroleum products. 
3-22

References 

1

 EIA, January 2012 Monthly Energy Review, Table 3.7a, Petroleum Consumption: Residential and Commercial 

Sectors; Table 3.7b, Petroleum Consumption: Industrial Sector; Table 3.7c, Petroleum Consumption: Transportation 

Sector, and Table 10.3, Fuel Ethanol Overview. 

2

 EIA, Petroleum Marketing Annual 2009, Table 45, Prime Supplier Sales Volume of Motor Gasoline by Grade, 

Formulation, PAD District and State. 

3

 Iizuka, Masashi, Advanced Technology and Research Institute (ATRI) and Japan Petroleum Energy Center 

(JPEC), Effect of Fuel Properties on Emissions from Direct Injection Gasoline Vehicle. 

4

 Jetter, Jeff, Honda R&D America Inc., Development of a Predictive Model for Gasoline Vehicle Particulate Matter 

Emissions, SAE 2010-01-2115.
4-1

Chapter 4 Fuel Program Feasibility 

4.1 Overview of Refining Operations 

Figure 4-1 shows a process flow diagram for a typical complex refinery, capable of 

making a wide product slate (shown on the right side of the figure) from crude oil (input on the 

left). Following the figure is a brief description of key units and streams focusing more on the 

gasoline producing units.1

 It’s important to note that not all refineries have all of these units, 

which is a key factor in both the variation in their baseline sulfur levels as well as their cost of 

sulfur control. 

Gasoline

Kerosene

Low Sulfur Diesel

Jet Fuel

Off-road Diesel

Resid

Hwy Diesel 

Hydrotreater

Fluidized Cat 

Vacuum Tower Cracker

Hydrocracker

Reformer

Crude 

Tower

Naphtha 

Splitter

Gas Plant

Aromatics 

Extraction

Naphtha Hydrotreater

Isomerization

H2

H2

H2

H2

H2

Hydrogen Plant

Fuel Gas

LPG

Crude 

Oil

Natural 

Gas

Aromatics

Polymerization

Alkylation

A B

Coke

Coker

Heating Oil

C

D

Crude 

Stabilizer

To Naphtha Hydrotreater

From Coker

Figure 4-1 Process Flow Diagram for a Typical Complex Refinery 

Crude Tower 

The purpose of the crude tower is to perform a distillation separation of crude oil into 

different streams for additional processing in the refinery and for the production of specific 

products. Crude oil is shipped to the refinery via pipeline, ship, barge, rail, or truck, whereupon 

it is sampled, tested, and approved for processing. The crude oil is heated to between 650 °F and 

700 °F and fed to crude distillation tower. Crude components vaporize and flow upward through 

the tower. Draw trays are installed at specific locations up the tower from which desired side 

cuts or fractions are withdrawn. The first side-cut above the flash zone is usually atmospheric 

gasoil (AGO), then diesel and kerosene/jet fuel are the next side-cuts, in that order. The lightest 
4-2

components, referred to here as straight run naphtha, remain in the vapor phase until they exit the 

tower overhead, following which they are condensed and cooled and sent to the naphtha splitter. 

Naphtha Splitter 

The purpose of the naphtha splitter is to perform a distillation separation of straight run 

naphtha into light straight run naphtha and heavy straight run naphtha. The feed can be split 

between the C5’s and C6’s in order to assure the C6’s and heavier are fed to the reformer. 

Naphtha Hydrotreater 

The purpose of the naphtha hydrotreater is to reduce the sulfur of light and heavy straight 

run streams before those streams are refined further by the isomerization and reformer units. 

Isomerization Unit 

The purpose of the isomerization unit is to convert the light naphtha from straight chain 

hydrocarbons to branched chain hydrocarbons, increasing the octane of this stream. The 

isomerate is sent to gasoline blending. 

Reformer 

The purpose of the reformer unit is to convert heavy straight run (C6 to C8 or C9 

hydrocarbons) into aromatic and other higher octane compounds (benzene is one of the aromatic 

compounds produced), typically necessary to produce gasoline with sufficient octane. To protect 

the very expensive, precious metal catalyst used in reformers, heavy straight run naphtha must be 

hydrotreated first before it is fed to the reformer. As the reformer converts the feed 

hydrocarbons to aromatics, hydrogen and light gases are produced as byproducts. The liquid 

product, known as reformate, is sent directly to gasoline blending, or to aromatics extraction. 

Aromatics Extraction Unit 

The purpose of aromatics extraction is to separate the aromatic compounds from the rest 

of the hydrocarbons in reformate using chemical extraction with a solvent to concentrate the 

individual aromatic compounds, (mainly xylene and benzene) for sale to the chemicals market. 

Vacuum Tower 

The purpose of the vacuum distillation tower unit is to enable a refinery to produce more 

gasoline and diesel fuel out of a barrel of crude oil. It separates the vacuum gasoil (VGO), which 

is fed to the FCC unit, from the vacuum tower bottoms (VTB) which is sent to the coker, or in 

other refineries is made into asphalt. Because most sulfur contained in crude oil is contained in 

the heaviest part of crude oil, the VGO and VTB are very high in sulfur. 

Fluidized Catalytic Cracker 

The purpose of the fluidized catalytic cracker is to convert heavy hydrocarbons, which 

have very low value, to higher value lighter hydrocarbons. AGO and VGO are the usual feeds to 
4-3

a fluid catalytic cracker (FCC). The full boiling range cracked product leaves the reactor and is 

sent to a fractionator. The overhead includes propane, propylene, butane, butylene, fuel gas and 

FCC naphtha, which contains a significant amount of sulfur. There are two heavy streams; light 

cycle oil (LCO), which can be hydrotreated and blended into diesel fuel or hydrocracked into 

gasoline; and heavy cycle oil, sometimes called slurry oil, which can be used for refinery fuel. 

Very simple refineries do not have FCC units, and therefore, produce gasoline with very low in 

sulfur. 

FCC Feed Hydrotreater or Mild Hydrocracker “A” 

FCC feed hydrotreaters and mild hydrocrackers hydrotreat or mildly hydrocrack the feed 

to the FCC unit which provides two distinct benefits. First, by increasing the amount of 

hydrogen in the feed to the FCC unit, the FCC unit increases the conversion of the feed to high 

value light products, particularly FCC naphtha which increases the gasoline yield. Second, 

hydrotreating the feed removes some contaminants in the feed such as nitrogen and sulfur. 

Nitrogen in the feed negatively affects the FCC catalyst. Removing the sulfur in the feed helps 

in two ways. Some of the sulfur in the feed is released by the cracking process and results in 

high SOX emissions that would otherwise have to be controlled by scrubbers – the FCC feed 

hydrotreaters may prevent the need to add a scrubber. Also, FCC feed hydrotreaters remove 

sulfur which can allow a refinery to comply with gasoline sulfur standards. 

FCC Postreat Hydtrotreater “B” 

Postreat hydrotreaters solely hydrotreat the naphtha that is produced by the FCC unit to 

reduce its sulfur level which enables compliance with gasoline sulfur standards. The FCC 

naphtha is high in olefins, which can be saturated by postreat hydrotreaters, resulting in lower 

octane of the FCC naphtha. Vendor companies have developed postreat hydrotreating 

technologies that minimize this octane loss. 

Distillate Hydrotreater 

The purpose of the distillate hydrotreater is to reduce the sulfur of distillate, which is also 

called diesel fuel. 

Gas Plant 

The purpose of the gas plant is to use a series of distillation towers to separate various 

light hydrocarbons for further processing in the alkylation or polymerization units or for sale. 

Alkylation Unit 

The purpose of the alkylation unit is to chemically react light hydrocarbons together to 

produce a high quality, heavy gasoline product. Alkylation uses sulfuric or hydrofluoric acid as 

catalysts to react butylene or propylene together with isobutane. Following the main reaction 

and product separation, the finished alkylate is sent to gasoline blending. Alkylate is low in 

RVP. 
4-4

Polymerization Unit 

The purpose of the polymerization unit is to react light hydrocarbons together to form a 

gasoline blendstock. A polymerization unit, often referred to as a “cat poly” is somewhat similar 

to an alkylation unit, in that both use light olefins to produce gasoline blendstocks. The feed is 

generally propylene and/or butylene from the gas plant. The product, called polygas is sent to 

gasoline blending. 

Coker Unit 

The purpose of the coker unit is to process vacuum tower bottoms (VTB) to coke and to 

crack a portion to various lighter hydrocarbons. The hydrocarbons produced by the coker 

include cracked gases, coker naphtha, coker distillate and gas oil. The gas is fed to the gas plant, 

the naphtha to the naphtha hydrotreater after which the heavy coker naphtha is typically fed to 

the reformer, and the distillate either to distillate hydrotreating or to the hydrocracker. 

Hydrocracker 

The purpose of the hydrocracker is to crack and “upgrade” the feedstock into higher 

value products. The feedstock to the hydrocracker is usually light cycle oil (LCO) and coker 

distillate, poor quality distillate blendstocks, which are upgraded to diesel fuel, or cracked to 

gasoline. Heavier hydrocarbons such as AGO and HVGO can be feedstocks as well. 

A more complete description for naphtha hydrotreating is contained in Section 4.2.

4.2 Feasibility of Removing Sulfur from Gasoline 

The case that it is feasible to comply with the 10 ppm gasoline sulfur standard can be 

made in two ways. First, feasibility can be demonstrated because there are available 

technologies that are currently available to achieve significant reductions in gasoline sulfur. A 

discussion of these currently available technologies is contained below. Second, refiners in 

California are already meeting a 10 ppm average, and certain countries or other regions are 

currently complying with a 10 ppm gasoline sulfur cap standard. These two cases will be made 

below, but first we will review the source of sulfur in gasoline to understand how sulfur levels 

can be further reduced. 

4.2.1 Source of Gasoline Sulfur 

Sulfur is in gasoline because it naturally occurs in crude oil. Crude oil contains anywhere 

from fractions of a percent of sulfur, such as less than 500 ppm (0.05 weight percent) to as much 

as 30,000 ppm (3 percent). The average amount of sulfur in crude oil refined in the U.S. is about 

14,000 ppm. Most of the sulfur in crude oil is in the heaviest part, or in the heaviest petroleum 

compounds, of the crude oil (outside of the gasoline boiling range). In the process of refining 

crude oil into finished products, such as gasoline, some of the heavy compounds are broken up, 

or cracked, into smaller compounds and the embedded sulfur can end up in gasoline. Thus, the 
4-5

refinery units which convert the heavy parts of crude oil into gasoline are the units most 

responsible for putting sulfur into gasoline. 

The fluidized catalytic cracker (FCC) unit is a refinery processing unit that creates FCC 

naptha, which is a high sulfur content gasoline blendstock. FCC naphtha contains from hundreds 

to several thousand parts per million of sulfur. The FCC unit cracks large carbon molecules into 

smaller ones and produces anywhere from 25 to 50 percent of the gasoline in those refineries 

with FCC units. Because the FCC unit makes a gasoline blendstock out of the heavier, higher 

sulfur-containing compounds, more than 95 percent of sulfur in gasoline blendstocks comes from 

streams produced in that unit. For compliance with the 30 ppm Tier 2 gasoline sulfur standard 

refiners reduced the sulfur content of the FCC naphtha. The impact of this action is described 

below in subsection 4.2.2. 

Straight run naphtha is a gasoline blendstock which contains a moderate amount of 

sulfur. Straight run naphtha is the part of crude oil, which after distillation in the atmospheric 

crude oil tower, falls in the gasoline boiling range. The heaviest portion of straight run, which 

would have more sulfur, is normally desulfurized and reformed in the reformer (to improve its 

octane), so its contribution to the gasoline pool is virtually nil.A The light straight run naphtha, 

which contains the five-carbon hydrocarbons, contains on the order of 100 ppm sulfur and if this 

material is not hydrotreated and processed in an isomerization unit, it is blended directly into 

gasoline. 

Another refinery unit which produces naphtha with a significant amount of sulfur is the 

coker unit. These units produce coke from the heaviest part of the crude oil. In the process of 

producing coke, a naphtha is produced that contains more than 3,000 ppm sulfur and many very 

unstable olefins. Because this stream is highly olefinic and unstable, refiners tend to hydrotreat 

coker naphtha. Coker naphtha is normally split into two different streams. The six- to ninecarbon hydrocarbons are hydrotreated along with the rest of the heavy naphtha and fed to the 

reformer. The five-carbon hydrocarbon part of coker naphtha is called light coker naphtha and 

usually contains on the order of several hundred parts per million sulfur. Light coker naphtha is 

usually hydrotreated along with the light straight run, and refined further in an isomerization unit 

if the refinery has one. 

Other gasoline blendstocks contain little or no sulfur. Alkylate, which is produced from 

isobutene and butylenes that contain a small amount of sulfur, can end up with a small amount of 

sulfur. Most refineries have less than 15 ppm sulfur in this pool, however, some refineries which 

feed coker naphtha to the alkylate plant can have much more. On average, alkylate probably has 

about 10 ppm sulfur. One more gasoline blendstock with either very low or no sulfur is 

hydrocrackate, which is the naphtha produced by hydrocrackers. It is low in sulfur because the 

hydrocracking process removes the sulfur. Ethanol, which is eventually blended into gasoline 

usually has very little or no sulfur. However, the hydrocarbon used as a denaturant and blended 

with ethanol at 2 percent is usually natural gasoline, a C5 to C7 naphtha from natural gas 

 

A

 Sulfur interferes in the function of the precious metal catalyst used in the reforming process. As a result, refiners 

historically have desulfurized the heavy straight run naphtha feed to the reformer from several hundred ppm sulfur 

down to less than 1 ppm. 
4-6

processing, and it contains anywhere from a few parts per million to a couple hundred parts per 

million sulfur. After the denaturant is blended in, the denatured ethanol contains somewhere 

between 0 and 10 ppm sulfur. To meet current pipeline and California specifications, denatured 

ethanol must contain less than 10 ppm sulfur. 

4.2.2 Complying with the Current Tier 2 Gasoline Sulfur Standard 

It is important to understand the steps that refiners took to comply with the 30 ppm Tier 2 

gasoline sulfur standard because those capital investments and operational changes will play a 

major role in determining the steps that refiners take to comply with a more stringent gasoline 

sulfur standard. 

The Tier 2 sulfur standard was promulgated February 10, 2000.2 The sulfur standard 

requires that refiners reduce their annual average gasoline sulfur levels down to 30 ppm and each 

gallon of gasoline cannot exceed a per-gallon standard of 80 ppm. The sulfur standards were 

phased in from 2004 to 2006. The compliance deadline for western refiners (GPA) and small 

refiners were delayed until 2008. Some small refiners also had their gasoline sulfur deadlines 

extended through 2010 if they met the compliance deadline for the highway diesel fuel sulfur 

rule. As of January 1, 2011, all refineries are complying with the Tier 2 30 ppm sulfur standard. 

 A refinery’s previous average gasoline sulfur level is an important factor which 

determined whether a refiner would need to make a substantial capital investment to meet the 

Tier 2 gasoline sulfur standards. We believe that refiners with low gasoline sulfur levels to begin 

with (i.e., gasoline sulfur levels lower than about 50 ppm) probably did not invest in expensive 

capital. These refineries have very low sulfur levels due to one or more of a number of possible 

reasons. For example, some of these refiners may not have certain refining units, such as either a 

FCC unit or a coker, which convert heavy boiling stocks to gasoline. As described above, these 

units push more sulfur into gasoline and their absence means much less sulfur in gasoline. 

Alternatively, these refiners may either use a very low sulfur (sweet) crude oil which can result 

in a low sulfur gasoline, or have already installed an FCC feed hydrotreater, which uses a 

heavier, higher sulfur (more sour) crude oil, to improve the operations of their refinery. As 

described above, this unit removes much of the sulfur from the heaviest portion of the heavy gas 

oil before it is converted into gasoline. 

Of the refiners that already had low sulfur levels prior to Tier 2, the refineries with 

average sulfur levels below 30 ppm may not have had to do anything to meet the Tier 2 

standards. On the other hand, refineries with sulfur levels above 30 ppm but below about 50 

ppm, probably are meeting the 30 ppm sulfur standard by employing operational changes only 

and avoided making capital investments. Most refineries with gasoline sulfur levels below 50 

ppm prior to the Tier 2 investments either do not have a FCC unit, or if they do, probably also 

have an FCC feed hydrotreating unit. 

The vast majority of gasoline that was being produced prior to the inception of the Tier 2 

program was by refineries with higher sulfur levels. These refiners had to either adapt some 

existing hydrotreating unit or install new capital equipment in these refineries to meet the Tier 2 

gasoline sulfur standards. As stated above, the FCC unit is responsible for most of the sulfur in 

gasoline. Thus, investments for desulfurizing gasoline involved the FCC unit to maximize the 

sulfur reduction, and to minimize the cost of compliance with Tier 2. These desulfurization units 
4-7

were installed for treatment of either the gas oil feed to the FCC unit, or the gasoline blendstock 

that is produced by the FCC unit. Each method has advantages and disadvantages. 

4.2.2.1 Using FCC Feed Pretreat Hydrotreating to Comply with Tier 2 

Some refiners installed FCC feed hydrotreaters (also known as pretreaters) at their 

refineries to comply with the Tier 2 gasoline sulfur standards. FCC pretreaters treat the vacuum 

gas oil, heavy coker gas oil and, in some cases, atmospheric residual feed to the FCC unit using a 

hydrotreater or a mild hydrocracker. These units are designed to operate at high pressures and 

temperatures to treat a number of contaminants in the feed. Besides sulfur, FCC pretreaters also 

reduce nitrogen and certain metals such as vanadium and nickel. These nonsulfur contaminants 

adversely affect the FCC catalyst, so the addition of this unit would improve the functioning of 

the unit. Also, because hydrotreating which occurs in the FCC pretreater reacts hydrogen in the 

feedstock, it increases the yield of the FCC unit, increasing the production of high profit-making 

products, such as gasoline and light olefins.3

 While FCC pretreaters provide yield benefits that 

offset the capital costs of adding this type of desulfurization, the costs are still high enough that 

many refiners would have a hard time justifying the installation of this sort of unit. For a 

medium to large refinery (i.e., 150,000-200,000 BPCD), the capital costs may exceed $250 

million. Because of the higher temperatures and pressures involved, utility costs are expensive 

relative to postreat hydrotreating as explained below. Using FCC feed pretreating also allows 

refiners to switch to a heavier, more sour crude oil. These crude oils are less expensive perbarrel and can offset the increased utility cost of the FCC pretreater, providing that the 

combination of reduced crude oil costs and higher product revenues justify the switch. Another 

benefit for using FCC pretreaters is that the portion of the distillate pool that comes from the 

FCC unit would be partially hydrotreated as well. This distillate blendstock, termed light cycle 

oil, comprises a relatively small portion of the total distillate produced in the refinery (about 20 

percent of on-road diesel comes from light cycle oil), and like FCC naphtha, light cycle oil 

contributes a larger portion of the total sulfur which ends up in distillate. Thus, FCC pretreaters 

would also help a refiner meet the 15 ppm highway and nonroad diesel fuel standards. 

In terms of desulfurization capability, FCC pretreaters have different abilities to remove 

sulfur from the gas oil feed depending on the unit pressure. FCC pretreaters can be subdivided 

into high pressure units (1400 psi and above), medium pressure units (900 to 1400 psi), and low 

pressure units (under 900 psi). High pressure FCC pretreaters typically remove about 90 percent 

of the sulfur contained in the gas oil feedstock to the FCC unit, while low and medium pressure 

units typically remove 65 to 80 percent of the feed sulfur.4

 We are aware of at least 5 refineries 

in the U.S. that use high pressure FCC pretreaters. Because there is no postreating at many of 

the refineries with FCC pretreaters, control of the feed to these units is a critical determining 

factor for how well the FCC pretreater will function as desulfurizers. If the feed becomes too 

heavy (due to a higher temperature endpoint), there would be a higher concentration of sulfur 

and other contaminants in the feed. To maintain the same sulfur level in the FCC naphtha, the 

FCC pretreater unit would have to be operated at a higher temperature which causes the catalyst 

to lose its effectiveness more quickly.5

FCC pretreaters improve desulfurization indirectly by improving the desulfurization 

performance of the FCC unit itself. When FCC units crack the vacuum gas oil into naphtha, 

about 90 percent of the sulfur is typically cracked out of the hydrocarbons converted to FCC 
4-8

naphtha (or the FCC naphtha contains only about 10 percent of the sulfur present in the feed) and 

is removed as hydrogen sulfide. When FCC pretreaters are used, the amount of sulfur in the 

feed, which ends up in the FCC naphtha, is only about 5 percent. This means that about 95 

percent of the sulfur in the feed is removed from the FCC feed when it is cracked into FCC 

naphtha. This is due to the additional hydrogen in the pretreater, which reacts with the feed 

hydrocarbons. With more hydrogen molecules available in the feedstock after hydrotreatment, 

the FCC cracking reactions can react more hydrogen with the sulfur contained in the feed to 

produce more hydrogen sulfide. 

For complying with Tier 2, refiners with existing pretreaters or those that installed high 

pressure FCC pretreaters were able to comply with the 30 ppm sulfur standard without the need 

to install a FCC naphtha hydrotreater. Refineries that had either a low pressure, or medium 

pressure FCC feed hydrotreater were generally less able to comply with the 30 ppm gasoline 

sulfur standard with the FCC hydrotreater by itself, and were more likely to also install an FCC 

postreater. 

4.2.2.2 Using FCC Naphtha Postreat Hydrotreating to Comply with Tier 2 

A less capital intensive alternative for reducing FCC naphtha sulfur levels to comply with 

Tier 2 is FCC naphtha hydrotreating (also known as postreaters). FCC postreaters only treat the 

gasoline blendstock produced by the FCC unit. This unit is much smaller than an FCC pretreater 

because only about 50 to 60 percent of the feed to the FCC unit ends up as FCC naphtha, a 

gasoline blendstock. The unit is sometimes smaller still because some refiners which choose to 

use a fixed bed hydrotreater may only treat the heavier, higher sulfur portion of that stream with 

hydrotreating, and then treat the lighter fraction with another lower desulfurization cost 

technology. FCC postreaters operate at lower temperatures and pressures than FCC pretreaters, 

which further reduces the capital and operating costs associated with this type of desulfurization 

equipment. Furthermore, because feed to the FCC unit has corrosive properties, FCC pretreaters 

use more corrosion-expensive metallurgy, which is not needed for postreaters.6 For a medium to 

large-sized refinery, the capital costs are on the order of $70 million for a conventional FCC 

postreater – about a third the cost of an FCC pretreater. 

One disadvantage of this desulfurization method is that the octane value and/or some of 

the gasoline yield may be lost depending on the process used for desulfurization. Octane loss 

occurs by the saturation of high octane olefins which are produced by the FCC unit. Most of the 

olefins are contained in the lighter fraction of FCC naphtha.7

 Increased olefin saturation usually 

means higher hydrogen consumption. There can also be a loss in the gasoline yield caused by 

mild cracking that breaks some of the gasoline components into smaller fractions which are too 

light for blending into gasoline. If there is octane loss, the octane loss can be made up by 

increasing the feed to or the severity of the reformer, the aromatics production unit of the 

refinery, producing more alkylate, or purchasing high octane gasoline blendstocks (such as 

reformate) which is routinely trading between refineries. Sometimes vendors of FCC pretreater 

technologies design octane increasing capability into their designs, which is discussed below in 

the section about the individual postreater technologies. 

The loss of octane and gasoline yield caused by FCC postreating is lower with 

technologies that were developed prior to the implementation of the Tier 2 program.8

These 
4-9

processes are termed selective because they achieve the lower sulfur while preserving much of 

the octane and gasoline yield (they were designed specifically for treating FCC naphtha). Octane 

is preserved because the hydrotreating units and their catalysts are specially designed to avoid 

saturating olefins. These selective processes, or parts of these processes, usually operate at less 

severe conditions and result in less cracking and thus, preserve yield compared to conventional 

hydrotreating processes. The less severe conditions also lower the capital and operating costs for 

this process. The lower operating costs arise out of the reduced utility requirements (e.g., lower 

pressure). For example, because these processes are less severe, there is less saturation of 

olefins, which means that there is less hydrogen used. Less olefin saturation also translates into 

less octane loss, which would otherwise have to be made up by octane boosting processing units 

in the refinery. The lower capital and operating costs of these newer FCC postreaters are 

important incentives for refiners to choose this desulfurization methodology over FCC 

pretreaters. For this reason, refiners chose to use the more recently developed FCC postreaters 

technologies for meeting the 30 ppm Tier 2 gasoline sulfur standard. 

Not saturating the olefins to preserve octane and limit hydrogen consumption provides a 

different challenge. During desulfurization, when the hydrogen sulfide is formed and there is a 

significant concentration of olefins present, the hydrogen sulfide compounds tend to react with 

the olefinic hydrocarbon compounds forming mercaptan sulfur compounds. This reaction is 

called “recombination” because the removed sulfur recombines with the olefinic hydrocarbons 

contained in the naphtha.9

This is particularly a problem if the light cat naphtha is present in the 

hydrotreater because the highest concentration of olefins is in the light cat naphtha. The 

recombination reactions occur more readily if the hydrotreater is operated more severely (at a 

higher temperature) to increase the sulfur removal, and the feed to the hydrotreater is high in 

sulfur. However, while operating this type of hydrotreater more severely can result in the further 

removal of the original sulfur present in the hydrocarbons, it also can result in the formation of 

more recombination mercaptans that results in a “floor” reached for the amount of sulfur that can 

be removed from the hydrocarbons. This cycle of increased sulfur removal and simultaneous 

increase in recombination results in the saturation of more olefins and increases the consumption 

of hydrogen. There are a number of different vendor-specific technologies that each vendor may 

use to avoid or address recombination reactions as discussed below. It is important to note that 

the technologies employed to reduce recombination may require the addition of some capital 

costs which offsets some or perhaps all the capital cost savings due to the milder operating 

conditions of these selective hydrotreater technologies compared to nonselective hydrotreating. 

One means to achieve high levels of desulfurization while avoiding much of the problem 

with recombination reactions is by using a two-stage hydrodesulfurization methodology. A twostage unit has two desulfurization reactors, but instead of just adding additional reactor volume, 

the hydrocarbons exiting the first reactor are stripped of gaseous compounds (most importantly, 

the hydrogen sulfide is removed), injected with fresh hydrogen, and then hydrodesulfurized 

again in the second stage. Both reactors undergo modest desulfurization and hydrogen sulfide 

concentrations remain sufficiently low to avoid recombination reactions. The disadvantage of 

this approach is that the second stage incurs greater capital costs compared to single-stage 

configurations. Because Tier 2 was not too constraining, we believe that refiners installed few, if 

any, two-stage desulfurization units to comply with those gasoline sulfur standards. 
4-10

Whatever strategy chosen by the refiner to comply with Tier 2, a critical criterion was 

that the postreater be capable of cycle lengths that match that of the FCC unit, which typically is 

4 years. If the postreater were to require a catalyst changeout before the FCC unit requires a 

shutdown, the refiner would either have to shutdown the FCC unit early to mirror that of the 

postreater, or store the high sulfur FCC naphtha (this stream would be too high in sulfur to blend 

directly to gasoline under the Tier 2 80 ppm cap standard) until the postreater was started up 

again and is able to hydrotreat the stored up high sulfur FCC naphtha. 

We know of six FCC postreater technologies that refiners used to comply with the Tier 2 

gasoline sulfur standards. These are Axens (was IFP) Prime G and Prime G+, Exxon Scanfining, 

CDTech’s CDHydro and HDS, Sinopec’s (was Phillips)S-Zorb and UOP’s ISAL and 

Selectfining. 

Axens Prime G+, Exxon Scanfining and UOP’s ISAL and Selectfining are all fixed bed 

desulfurization technologies. These processes are called fixed bed because the catalyst resides in 

a fixed bed reactor.10 The high sulfur gasoline blendstock is heated to a high temperature (on the 

order of 600 degrees Fahrenheit) and pumped to a high pressure to maintain the stream as a 

liquid. It is then combined with hydrogen before it enters the reactor. The reactions occur 

within the bed of the catalyst. While the petroleum is in contact with the catalyst in the reaction 

vessel, the sulfur reacts with hydrogen and is converted to hydrogen sulfide. Also, depending on 

the process, some of the olefin compounds that are present in the cracked stream are saturated 

which increases the amount of octane lost and hydrogen consumed. After the reactor, the 

gaseous compounds, which include unreacted hydrogen, hydrogen sulfide, and any light end 

petroleum compounds which may have been produced in the reactor by cracking reactions, are 

separated from the liquid compounds by a gas/liquid separator. The hydrogen sulfide must be 

stripped out from the other compounds and then converted to elemental sulfur in a separate 

sulfur recovery unit. The recovered sulfur is then sold. If enough hydrogen is present, and it is 

economical to recover, it is separated from the remaining hydrocarbon stream and recycled. 

Otherwise, it is burned with light hydrocarbons as fuel gas. 

Each of these fixed bed desulfurization technologies is somewhat different. Axens Prime 

G+ desulfurization process largely preserves olefins as its strategy for diminishing octane 

loss.11,12 13 The Axens process employs a selective hydrogenation unit (SHU) as a first step. The 

role of this unit is to saturate the unstable diolefin hydrocarbons in a hydrogen rich environment, 

and react the light mercaptan and sulfide hydrocarbons together. The SRU also converts exterior 

olefins to interior olefins, which results in a small increase in octane. The mild operating 

conditions of the SHU tend to avoid the saturation of monoolefins. After exiting the SRU, the 

FCC naphtha is sent to a distillation column which separates the light FCC naphtha (typically 

comprising about one fourth of the total cat naphtha) from the heavy naphtha. Because the light 

sulfur compounds were reacted together and those compounds no longer fall within the light cat 

naphtha boiling range, the light cat naphtha is low in sulfur and can be blended directly into 

gasoline. The heavy cat naphtha which is naturally high in sulfur and which also contains the 

self-reacted light mercaptans and sulfides from the SHU, is sent to a fixed bed hydrotreater. The 

fixed bed hydrotreater contains both cobalt-molybdenum and nickel-molybdenum catalyst. An 

important way that Axens avoids recombination reactions is by separating the light sulfur 

compounds from the light naphtha and keeping the light naphtha out of the fixed bed 

hydrotreater. The desulfurized heavy cat naphtha is blended into the gasoline pool. 
4-11

If the feed to the Axens Prime G unit is very low in sulfur, a low capital investment 

option was available to the refiner by feeding the entire FCC naphtha stream to the hydrotreating 

reactor avoiding the SHU and splitter. This option trades lower capital cost with somewhat 

higher octane loss and hydrogen consumption. Because of the low severity of the hydrotreating 

reactor (low severity is possible because the lower amount of desulfurization that is occurring), 

the amount of octane loss and hydrogen consumption is modest. There are more than 180 Prime 

G+ units operating worldwide, and approximately 40 in the U.S. 

The first step in Exxon’s fixed bed Scanfining process is to mildly heat the full FCC 

naphtha and pass it through a small reaction vessel which reacts the diolefins to monoolefins.14 15

16 17 18 19

 The full FCC naphtha is then heated further, injected with hydrogen gas and sent to the 

fixed bed hydrotreating reactor, which is packed with a catalyst developed jointly between 

Exxon and Akzo Nobel (now Albermele). If the degree of desulfurization is relatively modest, 

the amount of recombination is low and the FCC naphtha is sent to gasoline blending. If, 

however, the degree of desulfurization is higher (due to FCC naphtha with a higher sulfur 

content), then there likely would be an excessive number of recombination reactions. In this 

case, Exxon recommends either one of two different technologies to address the recombination 

reactions. One technology is Zeromer. Zeromer is a fixed bed reactor vessel installed after the 

main fixed bed hydrotreater reactor that specifically designed to hydrodesulfurize the mercaptan 

sulfur from the FCC naphtha without saturating olefins.20 Another technology Exxon developed, 

in conjunction with Merichem, is an extractive mercaptan removal technology named Exomer. 

The Exomer technology differs from other sulfur extraction technologies in that it is capable of 

extracting mercaptans from the entire FCC naphtha pool.21 Like Zeromer, the Exomer 

technology would be an add-on technology installed after the Scanfining fixed bed reactor. 

There are 16 Scanfining units operating in the U.S. 

UOP has licensed two FCC naphtha hydrotreating technologies. When Tier 2 was being 

phased-in, UOP was licensing a technology named ISAL developed by INTEVEP S.A.22 23 The 

ISAL process is different from the other FCC naphtha hydrotreaters because instead of avoiding 

the saturation of olefins as sulfur is being hydrotreated out of FCC naphtha, the ISAL process 

completely saturates the olefins. To avoid a large octane loss, the ISAL process separates the 

olefin-rich, light cat naphtha from the heavy cat naphtha. The light cat naphtha is treated by an 

extractive desulfurization technology such as Merox which does not saturate olefins. Only the 

heavy cat naphtha is sent to the ISAL reactor. To offset the octane loss caused by the saturation 

of the olefins in the heavy cat naphtha as it is being desulfurized, the ISAL catalyst isomerizes 

and conducts some mild cracking and reforming of the heavy cat naphtha. One downside of the 

ISAL process is that, due to the complete saturation of olefins, the hydrogen consumption is 

higher relative to the selective hydrodesulfurization technologies that avoid saturating olefins. 

UOP has since developed and licensed a FCC naphtha desulfurization technology called 

SelectFining.24 SelectFining is a selective hydrodesulfurization technology that seeks to 

minimize olefin saturation to minimize both octane loss and hydrogen consumption. 

SelectFining treats the full FCC naphtha. The full range FCC naphtha is first sent to a diolefin 

saturating reactor before being sent to the SelectFining reactor. SelectFining relies on its catalyst 

design to selectively remove sulfur and prevent recombination reactions. UOP recommends a 

two-stage reactor setup for high levels of desulfurization. 
4-12

The next two FCC naphtha desulfurization technologies, CDTech and S-Zorb do not use 

fixed bed reactors, but very different technologies which are also very different from each other. 

Each will be discussed separately. 

The CDTech process still uses the same type of catalyst used in fixed bed reactors. 

However, it also utilizes catalytic distillation.25,26,27 Catalytic distillation is a technology which 

has been applied for a number of different purposes. CDTech is currently licensing the 

technology to produce MTBE and selective hydrogenation processes, including FCC naphtha 

desulfurization and benzene saturation. As the name implies, distillation and desulfurization, via 

catalyst, take place in the same vessel. This design feature saves the need to add a separate 

distillation column sometimes used with fixed bed hydrotreating. All refineries have a 

distillation column after the FCC unit (called the main fractionation column) that separates the 

FCC naphtha from the most volatile components (such as liquid petroleum gases), the distillate 

or diesel (light cycle oil), and the heavy ends or residual oil. However, if a refiner only wishes to 

treat a portion of the FCC naphtha, then a second distillation column would need to be added 

after the main FCC fractionation column to separate out the portion of the FCC naphtha that he 

wishes not to treat. With the CDTech process, the refiner can choose to treat either the entire 

pool or a portion of the pool, but choosing to treat a part of the pool, thus negating any need for 

an additional distillation column. 

The most important portion of the CDTech desulfurization process is a set of two 

distillation columns loaded with desulfurization catalyst in a packed structure. The first vessel, 

called CDHydro, treats the lighter compounds of FCC gasoline and separates the heavier portion 

of the FCC naphtha for treatment in the second column. The second column, called CDHDS, 

removes the sulfur from the heavier compounds of FCC naphtha. All of the FCC naphtha is fed 

to the CDHydro column. The five- and six-carbon petroleum compounds boil off and head up 

through the catalyst mounted in the column, along with hydrogen which is also injected in the 

bottom of the column. The reactions in this column are unique in that the sulfur in the column is 

not hydrotreated to hydrogen sulfide, but they instead are reacted with dienes in the feed to form 

thioethers. Their higher boiling temperature causes the thioethers to fall to the bottom of the 

column. They join the heavier petroleum compounds at the bottom of the column and are sent to 

the CDHDS column. Because the pressure and temperature of the first column is much lower 

than conventional hydrotreating, saturation of olefins is reduced to very low levels. The olefin 

saturation which does occur is necessary to eliminate diolefins. Thus, little excess hydrogen is 

consumed. CDTech offers an option to refiners to put in an additional catalyst section in the 

CDHydro column to increase octane. This octane enhancing catalyst isomerizes some of the 

olefins, which increases the octane of this stream by about three octane numbers, and few of the 

olefins are saturated to degrade this octane gain. The seven-carbon and heavier petroleum 

compounds leave the bottom of the CDHydro unit and are fed into the CDHDS column. There, 

the heavier compounds head down the column and the lighter compounds head up. Both 

sections of the CDHDS column have catalyst loaded into them, which serve as hydrotreating 

reaction zones. Similar to how hydrogen is fed to the CDHydro column, hydrogen is fed to the 

bottom of the CDHDS column. 

The temperature and pressure of the CDTech process columns are lower than fixed bed 

hydrotreating processes, particularly in the upper section of the distillation column, which is 

where most of the olefins end up. These operating conditions minimize yield and octane loss. 
4-13

While the CDTech process is very different from conventional hydrotreating, the catalyst used 

for removing the sulfur compounds is the same. One important difference between the CDTech 

process and conventional hydrotreating is that CDTech mounts its catalyst in a unique support 

system, while conventional catalyst is usually dumped into the fixed bed reactor. CDTech has 

13 CDHydro/CDHDS desulfurization units in operation in the U.S. 

Phillips Petroleum Co. commercialized and licensed an adsorption desulfurization 

technology called S-Zorb, which it sold to SINOPEC in 2007.28 29 S-Zorb uses a chemical 

adsorption process, instead of hydrotreating, as the principal methodology for the removal of 

sulfur from FCC naphtha. Adsorption has the benefit of operating at much lower pressure and 

temperatures, which lowers operating costs. S-Zorb, uses two separate columns and is constantly 

moving an adsorption catalyst from the reactor vessel to the regeneration column, and back 

again.30 The untreated FCC naphtha and hydrogen are fed to the reaction vessel where the sulfur 

is catalytically removed the sulfur from the petroleum compound and facilitated by the hydrogen 

present in the reactor. The catalyst, which begins to accumulate the removed sulfur, is 

transferred over to the regeneration column on a continual basis where the sulfur is removed 

from the catalyst using hydrogen as the scavenging compound. Then the hydrogen disulfude is 

converted to sulfur dioxide and sent to the sulfur recovery unit. Because the process still relies 

upon catalytic processing in the presence of hydrogen, there is some saturation of olefins, with a 

commensurate reduction in octane. Through a literature search, we believe that 7 S-Zorb 

desulfurization units were originally licensed for Tier 2. Other sources indicated that only 4 

units are actually operating today. 

We also conducted a literature search and asked both refiners and vendors to identify the 

FCC naphtha desulfurization technology that was installed at each refinery to enable compliance 

with Tier 2. A summary of the total number of units by vendor and technology type is 

summarized in Table 4-1.

Table 4-1 Estimated Number of FCC Desulfurization Technologies Installed to comply 

with Tier 2 by Vendor Company or Technology 

Axens 

Prime G

Exxon

Scanfining

CDTech Sinopec SZorbUOP ISAL 

UOP Selectfining

FCC Feed 

HT

No FCC 

Unit

40 16 15 4 2 17 14

4.2.3 Meeting a 10 ppm Gasoline Sulfur Standard 

To meet a 10 ppm average gasoline sulfur standard, we believe that the primary strategy 

that refiners would adopt would be to further reduce the sulfur level of FCC naphtha. There are 

three primary reasons why we believe this will be the primary strategy and therefore, used it for 

analyzing the compliance costs for Tier 3. The first reason is that FCC naphtha is by far the 

largest contributor of sulfur to the gasoline pool, by virtue of both its volume and sulfur content, 

even after refiner’s use of hydrotreating to reduce the sulfur in the FCC naphtha to comply with 

Tier 2. Table 4-2 below summarizes the estimated average volumes and average sulfur levels for 

the primary blendstocks typically blended into gasoline for the current Tier 2 standards. By 

using the refinery-by-refinery model to model today’s situation for the typical refinery, we 

estimate that the FCC naphtha contains about 75 ppm for the typical refinery complying with the 
4-14

30 ppm Tier 2 sulfur standard and that gasoline blendstock typically contributes to about 34 

percent of a refiner’s gasoline pool. Table 4-2 also summarizes the changes in gasoline 

blendstock sulfur levels we believe would occur when complying with the 10 ppm gasoline 

sulfur standard. Using the refinery-by-refinery model, we project that a 10 ppm gasoline sulfur 

standard can be met by a typical refinery by reducing the sulfur level of FCC naphtha from about 

75 ppm to 25 ppm. We believe that virtually all refineries that have an FCC unit would not be 

able to comply with the proposed 10 ppm gasoline sulfur standard without further desulfurizing 

the FCC naphtha. The second reason is that both vendors and refiners have told us that this is the 

gasoline blendstock stream that they intend to address. Both vendors and refiners have explained 

to us that, for most refineries, existing FCC naphtha hydrotreaters can be retrofitted with only a 

modest capital cost to realize the sulfur reduction needed. Third, further reducing the sulfur of 

the FCC naphtha as the means to comply with Tier 3 is supported by other cost studies. When 

these studies assessed the costs for further reducing the sulfur levels of gasoline, they also 

focused further reducing the sulfur levels of the FCC naphtha. See the subsection at the end of 

Chapter 5 discussing these other cost studies. 

Table 4-2 Estimated Typical Gasoline Blendstock Volumes and Sulfur Levels after Tier 2 

and Complying with a 10 ppm Sulfur Standard 

Gasoline 

Blendstock

30 ppm Tier 2 Gasoline Sulfur 

Standard

10 ppm Gasoline Sulfur Standard

Volume 

(Percent)

Sulfur (ppm) Volume 

(Percent)

Sulfur (ppm)

FCC Naphtha 37 75 36 25

Reformate 23 0.5 22 0.5

Alkylate 13 10 13 10

Isomerate 3 0.5 3 0.5

Butane 4 5 4 5

Light Straight Run 

Naphtha and 

Natural Gas Liquids

5 15 5 5

Hydrocrackate 3 8 3 8

Ethanol 10 5 12.5 5

Coker Naphtha 2 1 2 1

Other Gasoline 

Blendstocks

1 10 1 1

Total/Sulfur 

Average

100 30 100 10

 Reducing FCC naphtha from 75 ppm to 25 ppm would likely be accomplished in 

different ways depending on the desulfurizing technology and configuration used for Tier 2, and 

whether the current capital employed for lowering gasoline sulfur is severely taxed or not severely 

taxed. For purposes of this discussion, we will discuss the likely steps taken to comply with Tier 

3 based on whether a refiner solely used an FCC pretreater or FCC postreater to comply with Tier 

2. While we provided an example for a typical refinery needing to reduce its FCC naphtha from 

75 ppm to 25 ppm to enable compliance with Tier 2, refineries that are not typical would have 

starting and ending sulfur levels that are different from this example. Despite these differences, 
4-15

we believe that every refinery can physically comply with a 10 ppm gasoline sulfur standard. 

This is because there are no technical difficulties removing sulfur from gasoline - the challenge is 

to comply while minimizing the cost of doing so, such as by minimizing the associated octane 

loss and by taking advantage of the flexibilities provided to comply. The cost analysis, reflecting 

the ability for refineries to comply though the use of the averaging banking and trading provisions 

is discussed in Chapter 5 of this RIA. Section 4.2.3.5 below also discusses the importance of the 

averaging, banking and trading program. 

 The one exception is the case where a refinery does not have an FCC unit. Refineries in 

this situation would likely already be producing gasoline which is 10 ppm or below. If such a 

refinery’s gasoline is above 10 ppm, then the refiner would need to address one or more of 

several different gasoline blendstocks, including light straight run and natural gas liquids. Our 

discussion on treatment of other gasoline streams can be found in Section 4.2.3.3. 

4.2.3.1 Meeting 10 ppm if Refiners Used an FCC Feed Pretreater to Comply with 

Tier 2 

 Refiners that relied on an FCC pretreater to comply with Tier 2 at a refinery would likely 

only be able to achieve 10 ppm sulfur gasoline if its FCC pretreater is a high pressure unit.31 32 

This is because most refineries that have FCC pretreaters process sour crude oils and if the unit is 

a mid or low-pressure unit, the unit pressure would likely be too low to sufficiently desulfurize 

the FCC feed. This may be true even if the refiner added reactor volume to its existing low or 

medium pressure FCC pretreater, which does cause additional desulfurization. Mid and low 

pressure FCC pretreaters just cannot remove enough of the sulfur in the gas oil feed to the FCC 

unit to achieve adequately low sulfur levels in the FCC naphtha. If a refinery processes 

moderate to low sulfur crude oil and has a low to mid-pressure FCC pretreater, however, it may 

be able to achieve an adequate degree of desulfurization in the FCC naphtha to enable the refiner 

to reduce its gasoline sulfur down to 10 ppm. If a refinery cannot achieve a sufficient level of 

desulfurization with its current or revamped FCC pretreater to comply with a 10 ppm gasoline 

sulfur standard, then the refiner will have to install a grassroots FCC postreater. Alternatively, 

refiners in this situation would be in the best situation to take advantage of the averaging, 

banking and trading program (ABT). Using the ABT provisions to its advantage, the refiner 

would achieve the most desulfurization that it can with its existing FCC pretreater (perhaps 20 

ppm sulfur gasoline), and then would purchase credits to demonstrate the remainder of its 

compliance with the 10 ppm gasoline sulfur standard. Such a refiner would then avoid the need 

to install an expensive grassroots FCC postreater. 

While they are expensive to install, FCC pretreaters provide important operating cost 

advantages over postreaters. An important advantage of FCC pretreating is that it occurs 

upstream of the FCC unit and therefore, does not jeopardize the octane value of the olefins 

produced in the FCC unit. Another advantage of the FCC pretreater is that it tends to increase 

the yield of naphtha from the FCC unit, which improves operating margins for the refinery with 

such a unit. Thus, refiners that are able to use FCC pretreaters to comply with the Tier 3 sulfur 

standard would likely yield a further return on any investment made, and offset some if not all of 

the increased operating costs incurred. 
4-16

A downside to solely relying on FCC pretreating to comply with Tier 3 is that a refinery 

has less operational flexibility. An FCC feed hydrotreater must be shutdown every one to three 

years to change out the catalyst, which is usually more often than when the FCC unit is 

shutdown. During the shutdown of the FCC pretreater, if the FCC unit remains operational a 

refiner has to figure out what to do with its high sulfur FCC naphtha (the refiner could blend up 

gasoline without FCC naphtha). For this reason, refiners that are complying with Tier 2 by 

solely relying on an FCC pretreater may choose to either install a grassroots postreater instead to 

comply with Tier 3, or purchase credits. 

The refiners most likely to rely on FCC pretreater to comply with Tier 3 are those with 

high pressure FCC pretreaters. As noted earlier, there are likely only 5 refineries have high 

pressure FCC pretreaters in the U.S. More refiners with FCC pretreaters may be able to comply 

with the Tier 3 standards using just their FCC pretreater, however, if they undercut the FCC 

naphtha into the diesel pool. The sulfur reduction in the FCC naphtha caused by undercutting 

would enable refiners to rely on lower pressure FCC pretreaters to comply with Tier 3, while 

also increasing diesel supply. 

4.2.3.2 Meeting 10 ppm if Refiners Used an FCC Postreater to Comply with Tier 2 

If a refiner installed an FCC postreater to comply with the Tier 2 gasoline sulfur standard, 

there are several considerations about the current configuration of the postreater which would 

affect how a refiner would use this unit to comply with a 10 ppm gasoline sulfur standard. EPA 

considered the issue of the degree of desulfurization the postreater is currently facing. In doing 

so, EPA analyzed several examples to understand the types of revamps and associated 

investments that might occur for such refiners. 

For the first example, if the refinery is refining a very sour (high sulfur) crude oil and the 

sulfur of the FCC naphtha exiting the FCC unit is 2,400 ppm, the postreater is currently 

removing almost 97 percent of the feed sulfur. This assumes that the sulfur level of the FCC 

naphtha exiting the postreater is 75 ppm, which is a very high level of desulfurization. When 

attempting to achieve further sulfur reduction in the FCC naphtha, the refiner must be concerned 

about the increased occurrence of recombination reactions and the potential for much more 

octane loss and hydrogen consumption. This refiner would strongly consider adding a second 

stage, which may actually reduce the level of recombination reactions and the octane loss 

currently experienced by the postreater. Most of the vendors offer a second stage option. In the 

case of CDTech, they call the second reactor, added as part of its second stage, a polishing 

reactor. We contacted the desulfurization engineer at Sinopec who explained that these units 

could be turned up and that no additional capital investments would be needed (though there are 

additional operating costs). A Conoco-Phillips hydrotreating specialist we spoke to confirmed 

that this would be the strategy for their S-Zorb units. We also considered an additional option of 

the refiner is interested in improving its operating margins such as increased gasoline production, 

and has ample capital dollars to spend. Such a refiner could add an FCC feed hydrotreater to 

increase its yield of FCC naphtha, or a mild hydrocracker to increase its production of low sulfur 

distillate. 

In contrast, if a refiner is processing a very sweet (low sulfur) crude oil, the sulfur level 

exiting the FCC unit may be as low as 300 ppm, and under Tier 2, the level of desulfurization 
4-17

necessary to bring that stream down to 70 ppm is about 81 percent which is a very modest level 

of desulfurization. Similarly, a refinery processing a moderately sour crude oil with a medium 

pressure FCC feed hydrotreater could be in a similar situation. The refineries in this situation 

could have a lot more capacity in their existing postreaters to achieve lower sulfur without 

additional capital cost investments. However, many refiners in this situation which invested in 

an FCC postreater for Tier 2 may have minimized their capital investments. For example, a 

refiner may have avoided the capital and operating cost of a splitter with its postreater by 

hydrotreating the full range FCC naphtha. Therefore, the increased severity of the postreater 

needed to achieve 20 ppm in the FCC naphtha to meet a 10 ppm gasoline sulfur standard might 

create a larger octane loss and higher hydrogen consumption than what the refinery could easily 

provide without a significant additional capital investment. In this case, the refiner can invest 

some capital in the postreater to minimize the increase in octane loss and hydrogen consumption. 

For example a refiner with an Axens unit in this situation could add the SHU and a splitter. A 

refiner with a Scanfining unit in this situation wishing to minimize the octane loss and hydrogen 

consumption could add a Zeromer or an Exomer unit. Alternatively, if the refiner is processing a 

moderately sour crude oil and has a moderate pressure FCC feed hydrotreater, the refinery may 

choose instead to revamp the FCC feed hydrotreater for its operational benefits rather than 

revamp the postreater. 

We also considered a third example where a refiner with a postreater has FCC gasoline 

exiting the FCC unit at 800 ppm. This is probably most typical of a refinery processing either 

crude oil containing an average amount of sulfur, or, perhaps a refinery refining a very sour 

crude oil but treating the vacuum gas oil with a low pressure FCC feed hydrotreater. The current 

FCC naphtha hydrotreater would be achieving about 90 percent desulfurization when producing 

FCC naphtha with 80 ppm sulfur. In looking to reduce the FCC naphtha down to 20 ppm to 

comply with a 10 ppm sulfur standard, such a refiner would not likely consider adding a second 

stage reactor. This is because avoiding both increased octane loss and hydrogen consumption for 

the additional increment of sulfur reduction would probably not justify the capital costs 

associated with a second stage reactor. Instead of a second stage reactor, a refiner could revamp 

the existing FCC postreater with additional reactor volume, or add capital for addressing 

recombination reactions, both likely to be a lot less capital intensive than a second stage. A no 

investment option is possible for refiners in this situation, although the increase in octane loss 

and hydrogen consumption is likely to be significant. 

The most important part of an FCC hydrotreater is likely the catalyst used in the unit. 

Due to continuing research, catalysts are constantly being developed which are more active, thus 

achieving greater desulfurization at a lower temperature, and minimizing octane loss and 

hydrogen consumption due to lower olefin saturation. When the Tier 2 naphtha desulfurizers 

were being put into service the most recent catalysts were likely used in those units. These 

catalysts can be changed when a postreater is undergoing regular maintenance, and new and 

improved catalysts can be used to improve the desulfurization capacity of the unit. If refiners 

need to reduce their gasoline sulfur levels to 10 ppm gasoline, they would be expected to 

upgrade to the most recent catalyst to minimize their costs. Using the most active catalyst 

available would reduce the capital cost that would need to be incurred and reduce the hydrogen 

consumption and octane loss that would otherwise occur. We are aware of newer lines of more 

active catalysts being marketed by Axens and UOP. It is likely that since the time catalysts were 
4-18

loaded into FCC postreaters to comply with Tier 2 all vendors are now offering improved 

hydrotreating catalysts. 

4.2.3.3 Desulfurizing Other Blendstocks 

A more stringent gasoline sulfur standard could require refiners to address other gasoline 

streams with high enough in sulfur content to be a concern to the refiners when complying with 

Tier 3. This is because without addressing such gasoline streams, the refiner would have to 

reduce their FCC naphtha even lower in sulfur resulting in high per gallon costs at the lower 

sulfur levels. The gasoline streams that we have identified that could require additional 

desulfurization include light straight run naphtha and natural gas liquids. 

Light straight run naphtha (LSR) is naturally occurring in the crude oil and is 

desulfurized at many refineries before it is sent to an isomerization unit. However, a number of 

refineries do not have isomerization units and therefore, some or perhaps many of these 

refineries may not be treating this stream today. Natural gas liquids (also termed pentanes plus) 

are naphtha streams sourced from natural gas wells, which are purchased by refiners, and 

blended into the gasoline pool. Depending on the source of the specific naphtha stream being 

purchased, these streams could vary widely in gasoline sulfur, ranging from a few ppm sulfur up 

to several hundred ppm sulfur. 

Refiners have multiple options for addressing the sulfur levels of these various streams. 

The LSR and natural gas liquids can be hydrotreated in either the FCC postreaters or the naphtha 

hydrotreaters. Because these naphtha streams do not have any olefins, there is essentially no 

octane loss and, therefore, hydrogen consumption is lower compared to hydrotreating FCC 

naphtha. Another way of treating these streams would be to use caustic extraction to extract the 

mercaptan sulfur from these streams. Since only the mercaptans are removed with the extraction 

technology, the final sulfur level would not be as low compared to desulfurization using 

hydrotreating. If the crude oil that is being refined by a particular refinery is low in sulfur, the 

refiner would likely only need to use extractive desulfurization to ensure that the sulfur in the 

LSR is adequately low under Tier 3. Finally, the refiner could choose to simply not purchase the 

natural gas liquids and sell the LSR on the open market as opposed to treating these streams. If a 

refiner decides to not treat the LSR or natural gas liquids, other refiners with excess capacity in 

their FCC postreaters or naphtha hydrotreaters could purchase that volume, treat these streams 

and blend the volume into their gasoline pool. 

For the NPRM, we did not know whether butane being blended by refiners still has high 

sulfur content and if refiners would need to treat it under Tier 3. We therefore assumed that 

some refiners might have to treat butane using extractive desulfurization licensed by UOP 

(Merox) or Merichem. A vendor we spoke to explained that almost all butane is being treated 

today using extractive desulfurization and the final sulfur level is under 5 ppm. 

In summary, to comply with a 10 ppm gasoline sulfur standard, refiners have a range of 

options available to them that mostly involve reducing the sulfur content of the FCC naphtha. If 

a refinery has a high pressure FCC pretreater, the refiner may be able to turn up the hydrotreating 

severity of that unit. If a refinery has a low or medium pressure FCC pretreater and no 

postreater, the refinery would likely need to either install a grassroots FCC postreater to comply 
4-19

with a 10 ppm gasoline sulfur standard, or reduce sulfur as much as possible with its current 

capital and rely on the ABT program for the remainder. Refiners with FCC postreaters have 

multiple options. If a refinery is short on octane and hydrogen, the refiner is likely to invest in 

capital (e.g., a second stage reactor) to avoid as much octane loss and hydrogen consumption as 

possible. However, if the refiner has a lot of excess octane and hydrogen, the refiner may choose 

to avoid any capital cost investments or only make small capital investments and tolerate the 

higher octane loss and hydrogen consumption by simply turning up the severity of its current 

FCC postreater. Refineries with postreaters could always invest in an FCC pretreater 

(hydrotreater or mild hydrocracker) to improve margins or produce more low sulfur diesel fuel. 

Finally, in blending up their gasoline, some refiners may still be blending in some produced or 

purchased gasoline blendstocks with high enough sulfur levels to be of concern when faced with 

the Tier 3 sulfur standard. Several options exist for addressing the sulfur in these gasoline 

blendstocks. 

It should be noted that the preceding is EPA’s best assessment of the steps refiners would 

have to take to comply with Tier 3. Refiners may choose to pursue alternative strategies that 

further other business objectives and also enable compliance with Tier 3 (e.g., installation of 

hydrocrackers, conversion of FCC feed hydrotreaters to mild hydrocrackers). It is not possible 

for EPA to project such alternative strategies on a refinery-by-refinery basis. While such 

alternative strategies may be triggered by or timed with actions to comply with Tier 3, they are 

not, and should not be, considered to be Tier 3 compliance actions. 

4.2.3.4 Demonstrated Compliance with a 10 ppm Gasoline Sulfur Standard 

Currently, there are multiple cases of refiners complying with 10 ppm or lower gasoline 

sulfur programs. The State of California requires gasoline sold in the State to meet a 15 ppm 

gasoline sulfur standard on average and a 20 ppm cap (California gasoline’s per-gallon sulfur cap 

dropped to 20 ppm on January 1, 2012). Furthermore, refiners can produce gasoline which 

varies in composition, provided that the California Predictive Emissions Model (which, like 

EPA’s Complex Model, estimates vehicle emissions from fuels of varying composition) 

confirms that the proposed fuel formulation meets or exceeds the emissions reduction that would 

occur based on the default fuel requirements. California refineries are using the flexibility 

provided by the Predictive Model to surpass the prescriptive standards for gasoline sulfur and are 

producing gasoline which contains around 10 ppm sulfur on average. They are making this very 

low sulfur gasoline despite using Californian and Alaskan crude oils which are heavier and more 

sour than most other crude oils being used in the U.S. today. Thus, the experience in California 

demonstrates that commercial technologies already exist to permit refiners to produce very low 

sulfur gasoline. 

Japan currently has a 10 ppm gasoline sulfur cap that took effect January 2008. Europe 

also has a 10 ppm sulfur cap that has been adopted by the 30 Member States that comprise the 

European Union (EU) and the European Free Trade Association (EFTA) as well as Albania and 

Bosnia-Herzegovina. Under a 10 ppm cap standard, the gasoline sulfur level likely averages 

about 5 ppm. Although gasoline in Japan and Europe is made from different crude oil sources 

and much of the heavier ends are cut into diesel fuel, these international fuel programs (along 

with California) provide evidence that advanced gasoline desulfurization technologies have been 

deployed and are readily available enable compliance with the proposed Tier 3 fuel program. 
4-20

4.2.3.5 Improved Feasibility with the ABT Provisions 

The averaging, banking and trading (ABT) and small refiner and small volume refinery 

aspects of the proposed Tier 3 gasoline sulfur program would ease the feasibility of compliance 

with the program. In the absence of the small refiner and small volume refinery provisions, all 

refineries would have to comply with the 10 ppm gasoline sulfur standard by January 1, 2017. 

Most refiners would have to make capital investments in their refineries to enable compliance 

with the 10 ppm gasoline sulfur standard by this date. These investments include revamped FCC 

pretreaters and postreaters, and the installation of grassroots FCC postreaters. As described 

above, reaching 10 ppm sulfur in the gasoline pool is feasible by each refinery. However, 

refiners assess the economic feasibility of their refineries differently depending on past and 

expected future economic performance. They therefore have different tolerances for making 

capital investments and absorbing increased operating costs. This is particularly true when 

gasoline demand is projected to be flat and renewable fuel blending is expected to increase. 

Refiners who own small refineries are concerned about the higher per-barrel costs for the capital 

installed at those small refineries. 

The small refiner and small volume refinery provisions will delay compliance for these 

entities until January 1, 2020. Small refiners need more time because they have smaller 

engineering staffs that they can dedicate to oversee the necessary refinery changes, thus they are 

more likely to complete the necessary changes to their refineries later than large refiners. The 

banking provisions of the ABT program effectively phase in the sulfur standard over six years 

starting in 2014 through the end of 2019. The phase-in allows refiners to stagger their 

investments to their economic advantage. Refineries that are expected to incur the lowest costs 

for achieving lower gasoline sulfur levels can comply early and earn sulfur credits. These credits 

can then be used to demonstrate compliance starting in 2017 by refineries that are expected to 

incur higher costs for reducing their gasoline sulfur levels allowing those refineries to delay 

investments for lowering their gasoline sulfur. This phase-in of the gasoline sulfur standard will 

help spread out the various aspects of the construction process by the US refining industry 

complying with the sulfur standard including: the preliminary design demands on the vendor 

companies that license the desulfurization technology to refiners, the detailed design demands on 

the engineering companies that provide that service to refiners, the permitting demands on the 

states that must provide environmental permits to refiners, and the demands on the fabrication 

shops that construct the reactors and other major hardware which must be installed at refineries 

to realize the gasoline sulfur reductions. For more on how the proposed ABT provisions are 

expected to help with lead time, refer to Section 4.3.

Finally, the averaging provisions of the ABT program will provide additional flexibility 

and help to reduce the costs of the gasoline sulfur program. The averaging provisions will allow 

refiners to reduce the gasoline sulfur levels to under 10 ppm at their lower cost refineries and 

generate credits to sell to refiners who would purchase the credits for higher cost or financially 

challenged refineries. 

4.2.3.6 Implications of an Average Gasoline Sulfur Standard Less than 10 ppm 

Although a more stringent sulfur standard than 10 ppm would increase the emission 

benefits of Tier 3, there are practical reasons for finalizing a 10 ppm annual average sulfur 
4-21

standard instead of a more stringent standard, e.g., 5 ppm or even a 10 ppm cap imposed in parts 

of Europe and in Japan. The lower the sulfur standard, the more costly it is for refiners to 

achieve the lower sulfur standard, and a 5 ppm average standard is much more costly than a 10 

ppm average standard. We identified several reasons why the costs increase so much for more 

deeply desulfurizing the gasoline pool. 

First, as desulfurization severity increases, the operating and capital costs associated with 

desulfurizing FCC naphtha also increases. FCC naphtha is very rich in high-octane olefins. As 

the severity of desulfurization increases, more olefins are saturated, further sacrificing the octane 

value of this stream and further increasing hydrogen consumption. Also, as desulfurization 

severity increases, there is an increase in the amount of the removed sulfur (in the form of 

hydrogen sulfide) which recombines with the olefins in the FCC naphtha, thus offsetting the 

principal desulfurization reactions. There are means to deal with the recombination reactions; 

however, this probably means either higher hydrogen consumption and octane loss, or greater 

capital investments. For example, the most expensive capital investment for an FCC postreater 

is a two stage desulfurization unit. A sulfur standard less than 10 ppm would likely require more 

refiners to invest in a second stage for their FCC postreater. 

Second, as shown in Table 4-2, other refinery streams contain very modest amounts of 

sulfur, yet a 5 ppm sulfur standard would likely require desulfurization of some of these streams. 

Because refineries have different sulfur levels in their non-FCC streams based on their feedstock 

sulfur levels and their configurations, those with higher sulfur levels in other refinery streams 

may have to desulfurize additional streams. Each additional individual gasoline stream that 

requires desulfurization is incrementally a lot more expensive than addressing the sulfur from the 

FCC unit because more volume has to be processed. The amount of sulfur reduction is a lot 

lower, and the capital costs are higher on a per-barrel basis for lower volume gasoline blendstock 

streams. 

Third, further desulfurization of gasoline down to 5 ppm essentially removes the 

flexibility offered by the 10 ppm gasoline sulfur standard with the ABT program. Each U.S. 

refinery is in a different position today, both technically and financially, relative to the other 

refineries. In general, they are configured to handle the different crude oils they process and turn 

their crude oil slate into a widely varying product slate to match their available markets. Those 

processing heavier, sour crudes would have a more challenging time reducing gasoline sulfur 

under the proposed Tier 3 program. Also, U.S. refineries vary greatly in size (atmospheric crude 

capacities range from less than 5,000 to more than 500,000 barrels per day) and thus have 

different economies of scale for adding capital to their refineries. As such, it is much easier for 

some refineries to get their sulfur levels below 10 ppm than for others to reach 10 ppm. This 

allows the ABT program to be used to reduce the cost of the proposed gasoline sulfur standard. 

If the gasoline sulfur standard were to be 5 ppm, the ability of refiners to average sulfur 

reductions across their refineries would likely end and thus, significantly increase the capital and 

operating costs while significantly reducing the desulfurization flexibility. 

Our cost estimates for a 5 ppm average standard as compared to a 10 ppm average sulfur 

standard bears this out. We estimate the average cost for a 10 ppm gasoline sulfur standard 

(assuming nationwide credit trading) to be 0.65 ¢/gal compared to 1.27 ¢/gal for the 5 ppm 

standard. The cost per sulfur reduction (marginal cost) for the 10 ppm average standard is 0.65 
4-22

¢/gal for the 20 ppm sulfur reduction from Tier 2, which averages 0.045 ¢/gal for each ppm of 

sulfur reduction. The marginal cost for the 5 ppm standard is 0.49 ¢/gal for the 5 ppm sulfur 

difference from the 10 ppm average standard, which averages 0.098 ¢/gal per each ppm of sulfur 

reduction, which is over 2 times higher. Therefore, we believe that an annual average standard 

of 10 ppm at the refinery gate with an ABT program is reasonable and maximizes the amount of 

sulfur reduction and the associated emission reductions before the costs begin to steeply escalate. 

We note that in most European countries and Japan, the gasoline sulfur level is capped at 

10 ppm. We, however, are not considering a 10 ppm cap for the U.S. due to the increased cost 

and increased challenges of ensuring compliance for every batch of fuel. The cost estimates 

described above for 5 ppm do not capture any additional costs refiners might need to incur to 

deal with offspec batches of fuel that get produced. Therefore, we are finalizing a 10 ppm 

average sulfur standard coupled with 80 and 95 ppm caps at the refinery gate and downstream, 

respectively, similar to what currently exists under the Tier 2 program. We believe this is the 

most prudent approach for lowering in-use sulfur while maintaining flexibility considering cost 

and other factors. These per-gallon caps are important in the context of an average sulfur 

standard to provide an upper limit on the sulfur concentration that vehicles must be designed to 

tolerate. Since there are many opportunities for sulfur to be introduced into gasoline downstream 

of the refinery, these caps also limit downstream sulfur contamination and enable the 

enforcement of the gasoline sulfur standard in-use. For more on our consideration of 

downstream caps, refer to Section 4.2.4.2. 

4.2.4 Challenges with Lowering Today’s Sulfur Caps 

4.2.4.1 Impacts of Lowering the 80 ppm Refinery Cap 

We are maintaining the existing 80 ppm refinery gate cap standard in the final Tier 3 fuel 

standard. For the NPRM, we considered lowering this cap to either 50 ppm or 20 ppm. If we 

lowered the refinery cap standard to 20 ppm, then refiners would only be able to take advantage 

of very little of the averaging aspect of the ABT program. That is because, under a 20 ppm cap 

standard, we estimate that the maximum sulfur level that refineries could average is about 14 

ppm sulfur. Thus, the compliance scenario if the cap standard were 20 ppm would essentially be 

the same as the non-ABT case we analyzed. In this case, refiners would have little of the 

flexibility offered by the ABT program. 

If the cap standard were to be lowered to 50 ppm, the final compliance scenario under the 

Tier 3 fuels program would be somewhere between the ABT scenario that we analyzed and the 

non-ABT scenario that we analyzed (probably much closer to the ABT case). Under a 50 ppm 

cap standard, we estimate that the maximum average gasoline sulfur level that refineries could 

average is 35 ppm. Although EPA batch data shows 40 refineries that averaged between 35 and 

80 ppm sulfur during 2011, our cost modeling shows only 8 of those would continue to average 

more than 35 ppm under a 10 ppm average standard and an 80 ppm cap. If the 80 ppm cap were 

to be reduced to 50 ppm, we project that those 8 refineries that averaging over 35 ppm would be 

forced to reduce their sulfur levels below 35 ppm regardless of their compliance costs. . Thus, 

the 10 ppm average standard reduced the number of refineries that average greater than 35 ppm 

sulfur from forty to eight. 
4-23

A more stringent cap would also affect refiners’ ability to process high sulfur FCC 

naphtha when there is a short term shutdown of the FCC postreater. If the FCC postreater goes 

down, the refinery would likely continue operating the FCC unit and store up the high sulfur 

FCC naphtha. Since the FCC naphtha is too high in sulfur to blend directly with gasoline, the 

refinery would have to either sell the high sulfur FCC naphtha to other refiners, or hydrotreat the 

stored up FCC naphtha along with the ongoing hydrotreating of high sulfur FCC naphtha once 

the FCC postreater was back online. If a stringent cap were in place, the refiner would have little 

room for short term production of higher sulfur gasoline if it was feeding a larger than normal 

quantity (stored and new production) of FCC naphtha to the FCC postreater. A stringent sulfur 

cap may cause refiners to oversize the FCC postreater and add additional FCC naphtha storage to 

ensure that, regardless of the higher feed volume needed to process the stored material, the FCC 

naphtha desulfurization unit could continue to desulfurize the FCC naphtha down to the required 

sulfur level to comply with the cap standard and ultimately the 10 ppm average standard. If the 

cap were to be lowered, a 50 ppm cap standard would continue to provide refiners with some 

flexibility while a 20 ppm cap would not. As shown in Section 4.4.2, refiners are currently 

taking full advantage of the flexibility offered by the 80 ppm cap standard offered under Tier 2. 

4.2.4.2 Downstream Sulfur Caps 

The feasibility of complying with a downstream sulfur cap is dependent on the 

differential between the refinery/importer gate sulfur cap and the downstream cap. This 

differential must provide sufficient flexibility for worst-case situations when the potential 

sources of sulfur addition downstream of the refinery/importer compound in a single batch of 

gasoline that was introduced into the system at the refinery/importer gate sulfur cap. 

We proposed, and are finalizing an 80 ppm refinery gate sulfur cap and 95 ppm 

downstream sulfur cap. These requirements are applicable under the current Tier 2 gasoline 

program. Therefore, under the Tier 3 program, we are maintaining the same 15 ppm differential 

between refinery gate and downstream sulfur caps that currently exists under the Tier 2 program. 

This 15 ppm differential has proven to be sufficient to accommodate the unavoidable addition of 

sulfur downstream of the refinery gate from contamination during distribution, the use of 

additives, and the disposition of transmix generated during distribution. 

The downstream sulfur cap applies at all locations downstream of the refinery or importer 

gate including the gasoline produced by transmix processors and after the use of additives. The 

potential sources of sulfur addition downstream of the refinery/importer gate and issues 

associated with the feasibility of meeting the downstream sulfur cap are discussed in the 

following subsections. 

4.2.4.2.1 Sulfur Addition Downstream of the Refinery and Importer Gate 

The sulfur content of gasoline can increase downstream of the refinery/importer due to 

contamination during distribution, the use of additives, and the disposition of transmix generated 

during distribution. 

A small amount of sulfur contamination takes place during distribution as a result of the 

shipment of gasoline over long distances by pipeline and other modes due to the sharing of the 
4-24

same distribution assets with other higher-sulfur petroleum products, e.g., jet fuel. Steps can be 

taken to limit sulfur contamination. However, it is an unavoidable feature of the efficient multiproduct distribution system in the U.S. We estimate that sulfur contamination of gasoline can be 

limited to a worst case maximum of 3 or 4 ppm in the future, even for the most involved and 

long-distance distribution pathways. Typical levels of sulfur contamination will likely be much 

lower given the removal of many sources of sulfur contamination in the fuel distribution system 

in recent years. 

There were no direct regulatory controls on the sulfur content of gasoline additives under 

the Tier 2 program. The contribution to the sulfur content of finished gasoline from gasoline 

additives is accommodated in the differential between the refinery gate and downstream sulfur 

caps. The functional components of some gasoline additives such as silver corrosion inhibitors 

and demulsifiers are inherently high in sulfur content. However, the contribution to the overall 

sulfur content of the finished fuel is very limited. For example, silver corrosion inhibitors can 

contain as much as 30 percent sulfur but because of very low treatment rates can add only 0.17 

ppm to the sulfur content of the finished fuel.33

 At seldom used highest treatment rates, the use 

of gasoline additives upstream of the consumer has the potential to add ~1 ppm to the sulfur 

content of the finished fuel. Aftermarket additives that are added directly into the vehicle fuel 

tank also have the potential to increase gasoline sulfur content. One particular aftermarket 

performance and anti-wear additive can contribute ~2 ppm sulfur to the treated fuel.B34

Transmix is a necessary byproduct of the multi-product refined product pipeline 

distribution system. Batches of different products are shipped in sequence in pipelines without 

any physical barrier between the batches. Transmix is produced when the mixture at the 

interface between two adjacent products cannot be cut into either batch. Transmix typically 

accumulates at the end of pipeline systems far from refineries. There are two methods of 

disposing of transmix. Most transmix is sent to transmix processing facilities for separation into 

saleable distillate and gasoline products through use of a simple distillation tower. 

The other means of transmix disposal is for pipeline operators to blend small quantities 

directly into batches of gasoline during shipping. This typically takes place at remote pipeline 

locations where small volumes of transmix accumulate that would be difficult to consolidate and 

ship to transmix processors. Pipeline operators that blend transmix into the gasoline in their 

systems must ensure that the resulting gasoline meets all fuel quality specifications and the 

endpoint of the blended gasoline does not exceed 437 °F.C35

 This practice currently can add as 

much as 3 to 5 ppm to the sulfur content of gasoline although we believe that the contribution is 

typically less. 

Transmix processing facilities do not handle sufficient volumes to support the installation 

of currently-available desulfurization units. Therefore, the sulfur content of the products they 

produce is predominantly governed by the sulfur content of the transmix they receive. In many 

cases, transmix contains jet fuel which can have a sulfur content as high as 3,000 ppm. Due to 

 

B

 Aftermarket additives are defined as additives sold to vehicle operators for direct addition to vehicle fuel tanks. 

C

 437 F is the maximum endpoint allowed for gasoline in the ASTM International specification for gasoline in 

ASTM D4814. 
4-25

the overlapping distillation characteristics of jet fuel and gasoline, it is unavoidable that some jet 

fuel in transmix will be present in the gasoline produced by transmix processors. 

Transmix processors produce ~0.1 percent of all gasoline consumed in the U.S. The 

small volume of transmix-derived gasoline along with the fact that such gasoline is typically 

mixed with other gasoline before delivery to the end user, substantially limits the potential 

impact on gasoline sulfur levels. Furthermore, data provided by the largest operator of transmix 

processing facilities, shown in Figure 4-2, indicates that relatively few batches of the gasoline 

they produce approach 80 ppm sulfur.36 Most batches are approximately 10 ppm above the 

current 30 ppm refinery sulfur average. We anticipate that this 10 ppm differential would likely 

continue under the 10 ppm refinery average sulfur standard. 

Figure 4-2 Kinder Morgan Transmix Gasoline Product Sulfur Levels 

4.2.4.2.2 Maintaining the Current 15 ppm Differential Between the Refinery 

/Importer Gate and Downstream Sulfur Caps 

The 80 ppm refinery gate and 95 ppm downstream sulfur caps finalized today maintains 

the current 15 ppm differential between the refinery/importer gate sulfur cap and the downstream 

sulfur cap. 
4-26

The current 15 ppm differential was established under the Tier 2 program to 

accommodate the sulfur contamination during distribution, the sulfur contribution from transmix 

blending by pipeline operators, the sulfur contribution from the use of additives, and to enable 

compliant gasoline to be produced by transmix processors. Transmix processors need to produce 

gasoline sufficiently below the downstream sulfur cap to accommodate the addition of sulfur 

from the use of additives and contamination during further distribution. Experience under the 

Tier 2 program has shown that a 15 ppm differential is sufficient for downstream parties to 

ensure compliance with the downstream sulfur cap 

Maintaining the current 95 ppm downstream sulfur cap with an 80 ppm refinery/importer 

gate sulfur cap under the Tier 3 program represents no change from current requirements. As a 

result, there will be no increased difficulty or additional costs associated with satisfying a 95 

ppm downstream sulfur cap beyond those that were already incurred under the Tier 2 program. 

Furthermore, the reduction in the refinery average sulfur standard under the Tier 3 requirements 

may make it somewhat easier to comply with the downstream sulfur cap given that most gasoline 

produced would be at or near 10 ppm sulfur. 

4.2.4.2.3 Cap on Sulfur Contribution to Gasoline from the use of a Gasoline 

Additive 

The Tier 3 rule requires that each gasoline additive may add no more than 3 ppm sulfur to 

the sulfur content of gasoline when used at the maximum recommended treatment rate. All 

current gasoline additives are currently compliant with this requirement. Therefore, 

implementing this requirement will not place an additional burden on gasoline additive 

manufactures. We are implementing this requirement to preclude the possibility that high sulfur 

blendstocks might be added to gasoline in the guise of a gasoline additive. 

4.3 Sulfur Credits 

We conducted an analysis of 2012 Tier 2 Gasoline Sulfur Credit Banking and Allotment 

Generation Reports submitted to EPA by U.S. refineries to ascertain the availability of sulfur 

credits and the fluidity of the sulfur credit trading market. These reports must be submitted by 

producers and importers of gasoline destined for sale in the United States. Such facilities submit 

Credit Banking and Allotment Generation Reports for sulfur credits it possesses or possessed 

over a given year. This data is Confidential Business Information. 

Sulfur credits must be used by the refiner that generated them or they can be transferred 

up to two times. These credits may be used at the refinery where they were generated, banked by 

a refiner for future use or use at another one of its refineries, or sold/transferred to another 

refiner. If a transferee does not use credits that they purchased, they may transfer them to 

another party; the second transferee must then use or bank the credits (i.e., they cannot be 

transferred again). Credits have a five-year life span from the year of generation. As such, 2007 

credits expired at the end of 2012. 

We performed several analyses of the data including: (a) the use of intercompany 

gasoline sulfur credit trading, (b) 2012 gasoline sulfur credit balances, (c) gasoline sulfur credit 

usage by age, and (d) the reduction of gasoline sulfur levels over time. 
4-27

The analysis revealed the number of gasoline sulfur credits banked by refiners as well as 

the extent to which gasoline sulfur credits are traded within a parent company (intra-company) 

and between competing parent companies (intercompany). These metrics, coupled with 

information on the gasoline sulfur credit usage and the reduction of gasoline sulfur levels over 

time under the current Tier 2 program, provides an indication of the ability and flexibility of 

refineries to rely on trading of credits for compliance with the Tier 3 standards being finalized 

today. 

4.3.1 Intra- and Inter-Company Trading 

Our analysis found that approximately 44% of sulfur credits transacted in 2012 were 

transferred intra-company whereas approximately 56% of gasoline sulfur credits transacted were 

transferred between competing parent companies (Figure 4-3), suggesting the existence of a 

robust and fluid gasoline sulfur trading market. 

Figure 4-3 2012 Inter- vs. Intra-company Gasoline Sulfur Credit Transfers 

4.3.2 Tier 2 Sulfur Credit Analysis 

Credits under the current Tier 2 program have a five year life, which means they could 

still be used in 2017. For the final Tier 3 program, we are allowing Tier 2 credits to be carried 

over for use in complying with Tier 3. As a result, we assessed gasoline sulfur credit availability 

for 2012. Our analysis of the number of sulfur credits generated and the number of sulfur credits 

used and transferred resulted in a difference of just under 400 billion ppm-gallon sulfur credits in 

2012. This equates to 2-3 months of compliance with the 10 ppm Tier 3 standard. If refiners 

were to simply continue to accrue at this rate until 2017 without taking any additional actions to 

comply early with Tier 3, gasoline sulfur credits generated by refineries would afford 

approximately a one-year delay in implementation of the standard. 

Of the gasoline sulfur credits transacted in 2012, 40% were generated in 2007, 30% were 

generated in 2008, 7% were generated in 2009, 9% were generated in 2010, 11% were generated 
4-28

in 2011, and 3% were generated in 2012 (Figure 4-4). Thus, a refiner’s willingness to trade 

gasoline sulfur credits varies with the time remaining until credits expire. Gasoline sulfur credits 

set to expire at the end of 2012 (i.e., credits generated in 2007) were traded thirteen times more 

often than sulfur credits generated in 2012, which expire at the end of 2017. Thus, having a 

finite credit life is helping to stimulate the robustness of the current credit trading market. 

Figure 4-4 Percentage 2012 Gasoline Sulfur Credits Transacted by Year of Generation 

4.4 Sulfur Level Analysis 

4.4.1 Volume-Weighted Gasoline Sulfur 

The analysis also revealed that volume-weighted average gasoline sulfur levels have 

decreased steadily over the period for which we analyzed data. In 2007, the volume-weighted 

gasoline average sulfur concentration was 39.8 ppm, 35.2 ppm for 2009, 31.2 ppm for 2011, and 

26.7 for 2012 (Figure 4-5). The steady decline over time was driven by the continued pressure 

of the Tier 2 standards. The last flexibilities in the program for a subset of small refiners ended 

in 2011. The additional drop in 2012, however, represents over-compliance with the Tier 2 30 

ppm average standard. 
4-29

Figure 4-5 Volume-Weighted Average Gasoline Sulfur Level by Year 

Sulfur levels by summer cumulative gasoline volume for 2011 are depicted in Figure 4-6. 

Figure 4-6 Sulfur Levels versus Summer Cumulative Gasoline Volume for 2011 

4.4.2 Batch-to-Batch Sulfur Variability 

Our analysis also revealed the extent of batch-to-batch variability of gasoline sulfur. 

While such variability is suggested when examining the aggregated sulfur levels for all gasoline 

batches produced in a year, as in Figure 4-7, the implications of this variability is not clearly 

evident until gasoline sulfur is examined at the refiner-level. 
4-30

Figure 4-7 Aggregated Sulfur Levels for All Gasoline Batches Produced in 2011 

Average gasoline sulfur varies significantly between refiners as well as between gasoline 

batches produced by the same refiner, as can be seen in Figures 4-8a-d. These figures depict 

2011 gasoline sulfur levels by batch frequency for four refineries from the analysis. In addition 

to providing insight into the volume-weighted average gasoline sulfur and the minimum and 

maximum gasoline sulfur, the figures also capture the broad distribution of sulfur levels and their 

skewness for gasoline batches produced by refiners.

For instance, the average gasoline sulfur for Refiner A (Figure 4-8a) is relatively high 

(58.6 ppm), with a broad range between minimum (8 ppm) and maximum (80 ppm). However, 

the data are negatively skewed, with most of the observations centered around 70 ppm – wellabove the volume-weighted average – and, to a lesser extent, along a shallow tail to the left (with 

lower sulfur values). These lower values offset the higher observations centered about 70 ppm. 

Figure 4-8a Sulfur Concentration Versus Batch Frequency for Refiner A 
4-31

Average sulfur for Refiner B is considerably lower than Refiner A (19.3 ppm versus 58.6 

ppm), and the data have a much smaller range (4 ppm minimum and 42 ppm maximum), with 

only a single higher observation at 63 ppm observation (Figure 4-8b). Unlike Refiner A, the 

gasoline sulfur for Refiner B is distributed bimodally about 15 and 25 ppm and is fairly 

systematical about the average of 19.3 ppm. The sulfur observations for Refiner B are not 

negatively skewed, as is the case for Refiner A. 

Figure 4-8b Sulfur Concentration Versus Batch Frequency for Refiner B 

Like Refiner A, the volume-weighted average sulfur for Refiner C is relatively high (52.7 

ppm), with a similarly broad range between minimum (20 ppm) and maximum (76 ppm) (Figure 

4-8c). However, unlike Refiner A – which is negatively skewed – these data are largely 

symetrical about the volume-weighted gasoline sulfur average. 

Figure 4-8c Sulfur Concentration Versus Batch Frequency for Refiner C 
4-32

Like Refiner B, the volume-weighted average sulfur for Refiner D is relatively low (21.5 

ppm), with a similarly broad range between 4 ppm and 51 ppm, with just a few observations 

between 70-75 ppm (Figure 4-8d). And as with Refiner B, the data for Refiner D are largely 

distributed symmetrically about the volume-weighted sulfur average. See Table 4-3 for a 

summary of these parameters. 

Figure 4-8d Sulfur Concentration Versus Batch Frequency for Refiner D 

Table 4-3 Summary of Statistics for Four Typical Refiners 

Refiner Sulfur 

Average

Sulfur 

Minimum

Sulfur 

Maximum

Sulfur 

(25th%)

Sulfur 

(75th%)

Refiner A 58.6 8.0 80.0 44.0 70.0

Refiner B 19.3 4.0 63.0 13.0 25.0

Refiner C 52.7 20.0 76.0 45.0 58.0

Refiner D 21.5 4.0 75.0 16.0 26.0

Given the significant variability in batch-to-batch gasoline sulfur, the data suggest that a 

low sulfur average with a high sulfur cap allows refiners to minimize operating costs by 

providing flexibility to those refiners producing gasoline above the average standard while 

providing incentive to those refiners producing gasoline below the average standard. 
4-33

In addition, the data demonstrate the flexibility provided by a high cap to allow normally 

low sulfur gasoline-producing refiners to still market occasional higher sulfur batches of gasoline 

during abnormal operating conditions. Finally, the data show that the combination of an average 

standard with a higher cap allows refiners considerable batch-to-batch flexibility in producing 

individual batches of gasoline while still reducing the overall sulfur level. 

4.5 Lead Time Assessment 

We received a several comments in support of and against our proposed rule regarding 

feasibility assessment and lead time. Commenters in the refining industry generally stated that 

the amount of lead time proposed was not sufficient. These commenters noted concerns that the 

short lead time proposed would drive up costs as there would be unscheduled shut-downs to 

install and/or revamp equipment to meet the Tier 3 sulfur standard, and would not provide 

enough time for the permitting process. These commenters requested at least five years of lead 

time, and noted that EPA has historically provided at least four years of lead time in previous 

fuels rulemakings. Commenters in the auto industry, as well as states and non-governmental 

organizations (NGOs), encouraged us to finalize the rule as soon as possible and to retain the 

January 1, 2017 start date to harmonize our program with California’s LEVIII program and to 

enable Tier 3 benefits as soon as possible. As discussed in more detail below, we believe the 

amount of lead time provided is sufficient, especially given the flexibilities being provided. A 

complete discussion on the comments received with regard to lead time can be found in Chapter 

5 of the Summary and Analysis of Comments document. 

While evaluating the merits of a national gasoline sulfur program to reduce emissions and 

enable future vehicle technologies, we also considered the refining industry’s ability to reduce 

sulfur to 10 ppm on average by January 1, 2017 and the associated costs (for more on fuel costs, 

refer to Chapter 5). Based on information gathered from numerous stakeholder meetings and

discussions with vendor companies that provide the gasoline desulfurization technologies both 

before and after the proposal, as well as the results from our refinery-by-refinery modeling, we 

believe it is technologically feasible at a reasonable cost for refiners to meet the sulfur standards 

in the lead time provided. A summary of our feasibility analysis is presented below. 

4.5.1 Employment Constraint Analysis 

As in prior rules, we also evaluated the capability of E&C industries to design and build 

gasoline hydrotreaters as well as performing routine maintenance. This includes an employment 

analysis. Two areas where it is important to consider the impact of the fuel sulfur standards are: 

1) refiners’ ability to procure design and construction services and 2) refiners’ ability to obtain 

the capital necessary for the construction of new equipment required to meet the new quality 

specification. We evaluated the requirement for engineering design, and construction personnel, 

in a manner consistent with the Tier 2 analysis, particularly for three types of workers: front-end 

designers, detailed designers and construction workers, needed to implement the refinery 

changes. We developed estimates of the maximum number of each of these types of workers 

needed throughout the design and construction process and compared those figures to the 

number of personnel currently employed in these areas. 
4-34

The number of person-hours necessary to design and build individual pieces of refinery 

equipment and the person-hours per piece of equipment were taken from Moncrief and 

Ragsdale37. Their paper summarizes analyses performed in support of a National Petroleum 

Council study of gasoline desulfurization, as well as other potential fuel quality changes. The 

design and construction factors for desulfurization equipment are summarized in Table 4-4. 

Table 4-4 Design and Construction Factorsa

Gasoline Refiners

Number of New Pieces of Equipment per Refinery 60

Number of Revamped Pieces of Equipment per Refinery 15

Job Hours Per Piece of New Equipmenta

Front End Design 300

Detailed Design 1,200

Direct and Indirect Construction 9,150

Note: 

a Revamped equipment estimated to require half as many hours per piece of equipment 

Refinery projects will differ in complexity and scope. Even if all refiners desired to 

complete their project by the same date, their projects would inevitably begin over a range of 

months. Thus, two projects scheduled to start up at exactly the same time are not likely to 

proceed through each step of the design and construction process at the same time. Second, the 

design and construction industries will likely provide refiners with economic incentives to avoid 

temporary peaks in the demand for personnel. 

Applying the above factors, we projected the maximum number of personnel needed in 

any given month for each type of job. The results are shown in Table 4-5. In addition to total 

personnel required, the percentage of the U.S. workforce in these areas is also shown, assuming 

that half of all projects occur in the Gulf Coast in Table 4-5. Refineries are generally expected to 

not require the full 24-month period to complete scoping studies, process design, permitting, 

detailed engineering, field construction, and start-up/shakedown for revamping an existing FCC 

postreater. 
4-35

Table 4-5 Maximum Monthly Demand for Personnel 

Front-End 

Design

Detailed 

Engineering

Construction

Tier 3 Gasoline Sulfur Program

Number of Workers 51 202 1,503

Percentage of Current Workforcea3% 2% 1%

Note: 

a Based on current employment in the U.S. Gulf Coast assuming half of all projects occur in the Gulf Coast 

To meet the Tier 3 sulfur standards, refiners are expected to invest $2.0 billion between 

2014 and 2019 and utilize approximately 250 front-end design and engineering jobs and 1,500 

construction jobs. The number of estimated jobs required is small relative to overall number 

available in the U.S. job market. As such, we believe that because of the ABT program with its 

flexibilities such as generous early credit generation period, that there is adequate lead time for 

refineries to obtain necessary permits, secure E&C resources, install new desulfurization 

equipment and make all necessary retrofits to meet the sulfur standards. 

We conducted a refinery-by-refinery analysis to determine the impacts on refinery E&C 

demand of implementing the 10 ppm standard without an ABT program. The analysis suggests 

that a greater number of refineries would need to make investments in refinery apparatus and 

upgrades without an ABT program than would be required with an ABT program. This would 

result in a greater demand on the E&C industry. Moreover, the analysis also indicated that the 

demand upon the E&C industry would be spread over a shorter period than with the ABT case. 

In particular, our refinery-by-refinery analysis indicates that without an ABT program, 72

refineries would revamp existing pre- and postreaters and 18 would install grassroots postreaters 

in order to meet the Tier 3 sulfur standards. The remaining 18 refineries are either already in 

compliance with the 10 ppm standard or expected to comply with simple process changes. This 

is compared to 66 refineries that would revamp existing pre- and postreaters and one refinery 

that would install grassroots postreaters in order to meet the Tier 3 sulfur standards under an 

ABT program. 

4.5.2 Can Refiners Meet the January 1, 2017 Start Date? 

An adequate amount of lead time is required for the implementation of any rulemaking. 

Depending on the level of effort required to comply, more or less lead time is also required. In 

the case of Tier 3, refiners need time to select the technology and the vendor that will provide the 

technology with which they will comply with the fuels standard. Next, they need time to arrange 

an engineering and construction (E & C) contractor which will design and oversee the 

construction of the refinery unit and the time needed to obtain the necessary permits and procure 

the necessary hardware. Next, refiners need time to construct the unit. Finally, the refiner needs 

time to make the necessary unit tie-ins of the unit with the rest of the refinery and then startup 

the unit. 

This section explains that when taking into account the time to revamp existing FCC 

postreater units or build grassroots postreater units, tie-in the new or revamped units with the rest 
4-36

of the refinery and considering the flexibility offered by the ABT program, refiners will be able 

to comply with the Tier 3 program within the lead time provided. 

4.5.2.1 Time Required to Install Grassroots Units and Revamp Existing Units 

The technologies for complying with Tier 3 are well known and well proven. As 

previously explained, refiners which complied with Tier 2 using FCC naphtha desulfurization 

technologies installed the following units, all of which were grassroots installations: Axens 

Prime G+, CDTech’s CDHydro and CDHDS, UOP’s ISAL, Sinopec’s S-Zorb and Exxon’s 

Scanfining. Prior to choosing a technology, refiners needed to evaluate each these different 

technologies and choose among them, all of which were largely untested at the time, which 

required us to provide more lead time for Tier 2. Since it has been 9 years since the Tier 2 sulfur 

standard began to be phased in, refiners now have direct experience with the installation and 

operation of these technologies and the vendor companies that license them and continue to 

support their installations onsite. This fact will allow refiners to reach a decision very quickly 

when complying with Tier 3, particularly, because in most cases the refiners will solely be 

revamping the units installed for Tier 2 when complying with Tier 3. 

Based on our discussions with refiners, construction companies, vendor companies and 

from published literature, we estimated the time it takes to revamp existing postreaters and install 

grassroots postreaters. Revamping an existing postreater is expected to require up to two years. 

Installing a grassroots postreater is estimated to require three years. Figure 4-6 reflects these 

project completion times showing the various major intermediate steps for completing the 

projects.D 

 

D

 The timeline shows overlap between steps which reflect actions that can be taken to set up the following step 

while the previous step is being completed. For example, refines can establish the contract for the detailed 

engineering while the process design is being completed. Refiners can begin site preparation to prepare for 

construction before the detailed design is completed. Finally, refiners can test individual pieces of equipment as 

they are installed and while construction is ongoing to find problems that would streamline unit start-up and avoid 

delays 
4-37

Figure 4.6 Estimated Project Lead Time for Revamps and Grassroots Units 

0- 3-

6

6-

9

9-

12

12-

15

15-

18

18-

21

21-

24

24-

27

27-

30

30-

33

33-

36

Revamp Pre- & Postreaters

Scoping 

Studies

Process

Design

Permitting

Detailed 

Engineering

Field 

Construction

Start-up / 

Shakedown

Grassroots Postreater

Scoping 

Studies

Process

Design

Permitting

Detailed 

Engineering

Field 

Construction

Start-up / 

Shakedown

We believe that the revamping of postreaters could take less time than what we estimate 

in Figure 4-6 because many of the Tier 3 revamps are expected to be very modest (e.g., change 

out a reboiler or heat exchanger). Since EPA held discussions with many refiners in 2011 about 

EPA’s plan to pursue additional sulfur control post-Tier 2 (Tier 3), refiners began the process of 

assessing how they would comply. The Tier 3 proposal was delayed for about a year and it is 

our understanding from recent discussions with vendor companies and some refiners that, during 

this time, many refiners began assessing how they intended to comply with Tier 3. Thus, many 

refiners likely have completed the scoping studies, which involves technology selection, and in 

the case of grassroots units, vendor selection as well (refiners with a particular postreater 

technology in most cases are expected to simply revamp the same vendor’s technology, so there 

is no need to select a vendor). If refiners have already completed their scoping studies, we 

estimate that installation of the revamps or grassroots units would be about 3 months shorter than 

the 2 and 3 years, respectively, than we estimate in Figure 4-6. 

These project timelines are reasonable in light of past industry experiences that show 

FCC postreaters being installed in refineries in less time than what we estimate. At the Motiva 

refinery in Port Arthur, TX, a grassroots CDTech postreater was designed, constructed and 

started up in less than 2 years.38

 At two refineries in Germany, two Prime G+ units were 

designed, constructed and started up – one of them in two years, and the other in 18 months.39

 
4-38

As an extreme example, the $3.6 billion dollar, 180 kbbl/day crude oil expansion at Marathon’s 

Garyville, LA refinery was designed, constructed and started up in less than 4 years.40 This 

single project involved the construction of 10 major refinery units, and permitting required only 

9 months. Since these may be best case examples, we continue to believe the projections 

provided above in Figure 4-6 are reasonable. 

4.5.2.2 Program Flexibility that Extends Lead Time 

The final Tier 3 program includes an ABT program that would significantly help refiners 

comply with the January 1, 2017 start date. There are three provisions of the ABT program 

which helps with respect to leadtime. 

The ABT program allows for ongoing intra-company and inter-company trading 

nationwide. This will allow some refineries to over-comply with the 10 ppm gasoline sulfur 

standard (in our analysis, we modeled these refineries bringing their gasoline down to 5 ppm), 

allowing other refineries that would otherwise need to install grassroots units to not invest and 

purchase credits instead. This aspect of the ABT program is very important because our analysis 

estimates that only one refinery would need to install a grassroots hydrotreater whereas without 

the ABT provisions, there could be as many as 20 grassroots units. This one aspect has 

important implications for leadtime because as discussed in the previous subsection, revamps 

require two years or less whereas grassroots FCC postreater units require approximately three 

years to install. We are convinced that this aspect of the ABT program will be utilized to the 

maximum extent possible because refineries revamping their postreaters in lieu of installing 

grassroots postreaters results in the most cost-effective mechanism for meeting the 10 ppm 

annual average standard. 

An important question is whether refiners will not invest in a grassroots unit trusting that 

the credits will be freely available. For the NPRM, we conservatively assumed that refiners 

would only rely on credits if they could generate them internal to the company. As discussed in 

Section 4.4, we assessed how the sulfur credits were being traded under Tier 2 and we found that 

over half the sulfur credits were freely traded between companies (as opposed to only being used 

within companies), and many single-refinery companies had sulfur levels above 30 ppm (singlerefinery companies must purchase credits from other companies). Because we set up the Tier 3 

credit trading program to work just like the Tier 2 credit trading program, we are confident that 

there will be widespread trading within and between refining companies which means that few 

grassroots units will be need to be built for Tier 3. 

A second aspect of the ABT program that helps with leadtime is the provision for 

generating early sulfur credits and banking them for later use. This provision allows refineries to 

reduce their gasoline sulfur to less than 30 ppm prior to January 1, 2017 and bank the credits for 

later use. Based on comments that we received on the proposed rule, we are allowing Tier 2 

credits which are generated during the years 2012 and 2013 to also be used to show compliance 

for Tier 3. This effectively extends the early credit generation period for Tier 3 to encompass the 

years 2012 to 2016, which is 5 years. Analyzing the 2012 gasoline quality data that refiners 

reported to EPA, we found that gasoline sulfur levels in the U.S. averaged 26.7 ppm. Thus, 

refiners have already begun overcomplying with Tier 2 by 3.3 ppm, and are therefore already 

generating early credits for Tier 3. If refiners do nothing more but continue to overcomply with 
4-39

Tier 2 by 3.3 ppm over the 5 years of early credit generation, refiners will have generated enough 

credits to delay the completion of their capital projects by more than one year. Furthermore 

since those credits generated in 2012 and 2013 will expire in 2017 and 2018 respectively, 

refiners will have an incentive to either use them themselves or trade them in 2017 and 2018. 

Thus refiners that may need to count on them to delay their capital investment are likely to be 

able to have access to them. 

We believe that refiners will generate a lot more early credits with their existing gasoline 

sulfur control units than the 3.3 ppm we observed in 2012. As we discussed in our cost analysis, 

to produce more diesel fuel in response to a greater demand for diesel fuel relative to gasoline, 

refiners are undercutting the swingcut portion of FCC naphtha at their refineries.E This action to 

shift what historically was blended into the gasoline pool to the diesel fuel pool, also 

dramatically reduces the sulfur content of the gasoline pool. If the entire swingcut portion of 

FCC naphtha is undercut to the diesel fuel pool, the amount of sulfur in the gasoline pool is 

reduced by about 50 percent. Our cost analysis estimates that at almost one quarter of U.S. 

refineries, refiners are fully undercutting the FCC naphtha to diesel fuel today. At many other 

refineries, our cost analysis estimates that refiners are partially undercutting their FCC naphtha. 

These refineries will be able to reduce the sulfur of their gasoline well below their current levels 

and generate a large number of early credits for Tier 3. Even for the subset of refineries where 

FCC naphtha is not being undercut, refiners can assess how much activity or catalyst life is left 

in its FCC postreater catalyst and compare this time with the time to the next turnaround when 

the FCC postreater catalyst is scheduled to be replaced. If there is spare catalyst life, the refiner 

could elect to increase the severity of their postreaters to reduce their gasoline sulfur levels to 

under 30 ppm. With this strategy, the refiner would generate early sulfur credits. Also, when the 

refiner replaces the catalyst in its Tier 2 postreater, it can elect to do so with a more active 

catalyst which would allow the refinery to produce gasoline at sulfur levels below 30 ppm and 

generate more early credits for Tier 3. 

Based on the early actions refiners are either already taking, or could take, to reduce their 

gasoline sulfur levels, we believe that refiners would be able to reduce their gasoline sulfur to as 

low as 20 ppm, on average, without making any capital investments. By averaging 20 ppm for 

2.5 years prior to 2017, refiners would be able to delay completion of all capital investments for 

Tier 3 until mid 2019. If we add the 3.3 ppm of credits during 2012, 2013 and first part of 2014, 

refiners would be able to delay completion of all capital investments in Tier 3 until 2020. Thus, 

the early credit provisions in-effect can provide nearly 6 years of leadtime for full compliance 

with the fuels program. This will allow ample time for refiners to complete their investment and 

schedule their tie-ins during normal shutdown activities. It effectively provides even more lead 

time than 5 years that the refining industry requested in their comments. The delay in the 

program implementation will also help to distribute the demand on the E & C industry over more 

years ensuring that the E & C industry would not be overwhelmed. Thus, the Tier 3 program 

with a very flexible ABT program provides ample leadtime. 

 

E

 The term swingcut means that this portion of the FCC product pool can be blended into gasoline or diesel fuel 

while still meeting the fuel quality specifications for either fuel regardless of where this swingcut is blended. 
4-40

A third aspect of the Tier 3 ABT provisions which helps with leadtime is that small 

refiners and small volume refineries (i.e., refineries processing less than or equal to 75,000 net 

barrels per day of crude oil) are exempted from complying with the 10 ppm average sulfur 

standard until 2020. This provides an estimated 36 refineries, of the total 108 refineries, nearly 

6 years of lead time; again more than the 5 years that the refining industry requested in their 

comments. As a group, we believe that these refiners and refineries are disproportionally 

impacted when it comes to their cost of compliance and ability to rationalize investment costs in 

today’s gasoline market. Giving these refiners and refineries additional lead time provides more 

time to invest in desulfurization technology, take advantage of advancements in technology, 

develop confidence in a Tier 3 credit market as a means of compliance, and avoid competition 

for capital, engineering, and construction resources with the larger refineries. The small refiner 

and small volume refinery exemption until 2020 reduces the number of refineries which will 

need to make a significant capital investment to comply with Tier 3 prior to 2020 to a total of 49 

non-small refineries (48 revamps and 1 grassroots unit), thus 15 refineries could wait to take 

action until 2020 (see Table 4-8 below). The provisions for small refiners and small volume 

refineries are discussed in more detail in Section V.E.1 of the preamble. Although the small 

refiners and small volume refineries are not required to comply with Tier 3 until 2020, they can 

still generate early credits (from January 1, 2017 through December 31, 2019) relative to 30 ppm 

for sale to other small refiners/small volume refineries, and relative to 10 ppm for sale to nonsmall refiners. Such credits generated relative to 10 ppm could provide another pool of early 

credits for Tier 3. 

In summary, the ABT program provides ample flexibility for complying with Tier 3. The 

averaging provisions will allow refiners that only need to revamp their Tier 2 postreaters to 

overcomply and generate credits which will allow refineries that otherwise need to install 

grassroots units to comply solely through the purchasing of credits. The banking provisions, 

which allow refiners to generate early credits, effectively delays investments for compliance to 

potentially as late as the year 2020. Finally, the small refiner and small refinery provisions delay 

compliance for approximately 30 refiners until 2020. The provisions also allow them to generate 

and sell credits during this period if they so choose. All these ABT provisions effectively 

address the leadtime concerns. Furthermore, were we to shift the start date back another 2 years 

as the refinery industry suggests in their comments, it would provide nearly 8 years of leadtime 

for refinery changes that require just 2 or 3 years to complete. Refiners would not have to even 

begin taking action for Tier 3 for a couple of years. Given that the lead time and associated 

programmatic flexibility we are finalizing is sufficient to allow industry to readily comply; we do 

not expect that a delay in the start date of the fuel standards would change the cost of compliance 

discussed in Chapter 5. Any further delay in the program start date would simply delay the 

actions to comply. Furthermore, delaying the start of the program would forego significant 

emissions, air quality, and health benefits. 

4.5.2.3 Impact of Turnaround Timing 

In their comments to the proposed Tier 3 rulemaking, the oil industry stated that the time 

it takes to comply with the proposed 10 ppm gasoline sulfur standard must include the time it 

takes to tie-in the revamps and grassroots units. The oil industry suggested that the leadtime for 

Tier 3 be increased to 5 years to allow for refiners to make their investments needed to comply 

with Tier 3 and tie-in those new investments. We agree that the need to make tie-ins must be 
4-41

considered when assessing the feasibility of leadtime, and even when we factor the time needed 

to do so, our analysis shows that refiners can comply with Tier 3 with the leadtime provided. 

This is true because the final rule effectively provides nearly 6 years of leadtime to complete 

capital projects, as described above, and also because the capital projects do not have to be 

completed prior to installing the necessary tie-ins for new Tier 3 units. 

When a refiner builds a grassroots unit or some sort of revamp that involves a new 

reactor or perhaps an added distillation column, the new vessels and associated equipment must 

be “tied-in” to the rest of the refinery. The tie-in usually involves connecting a pipe from the 

existing unit to the new unit installed. However, a pipe cannot simply be added while the 

refinery is operating. Instead, the refiner will add the necessary pipe for making the tie-in when 

the refinery is shutdown for regular maintenance. The revamp or grassroots unit does not have 

to be started up at that time. Instead, the connection pipe just needs to be added and blocked off 

with a sealing-type valve and a blind flange (essentially a flat piece of steel) is bolted on as a 

precaution against a leaky valve. This is a very simple process that would take several pipefitters 

a half a day of work to complete including completing all the necessary safety protocols.F Once 

this piping has been added, the refiner can restart its refinery. Then when the refiner is ready to 

complete the tie-in to the completed revamp or grassroots unit, the refiner would remove the 

blind flange and connect a pipe that connects the existing part of the refinery to the newly 

installed grassroots postreater unit or revamp postreater subunit. This last step can either occur 

when the refinery is shutdown or still operating. At that point the refiner would only need to 

open the block valve to complete the tie-in of the grassroots unit or revamp to the existing 

refinery. One refiner who owns a number of refineries informed us that it installed the tie-ins for 

a possible Tier 3 rule when it installed its Tier 2 units. 

On its webpage, the American Petroleum Institute (API) reports that the average time 

between major turnarounds is 4 years when the U.S. refineries perform maintenance on the FCC 

unit.41

 An Energy Information Administration (EIA) study makes a similar finding, which is that 

refiners target 3 – 5 years, or 4 years on average, between refinery turnarounds.42

 This means 

that on average, 25% of U.S. refineries shutdown to perform maintenance on its FCC units each 

year. Most often, refiners conduct maintenance turnarounds on their refineries during the spring 

when the demand for gasoline and diesel fuel is at their lowest. The EIA study also found that 

over 25% of the time refiners need to conduct turnarounds earlier than targeted because a 

maintenance issue forces the earlier turnaround. However, the EIA study did not estimate how 

much earlier the turnaround occurred so it was not possible to estimate an actual average 

turnaround schedule, which is likely less than 4 years. 

 

F

 Since most refiners have already completed their scoping studies with the vendor companies which license the 

desulfurization technologies, they likely already understand what steps would need to be taken to tie-in their 

revamps and grassroots units with their existing refinery. Installation of tie-ins is relatively simple refinery change 

that can be engineered and installed in a short period of time. For this reason, we believe that refiners can begin 

making their tie-ins as soon as the spring of 2014, 

G

 This analysis is focused on the projected emissions increase (step 1) and the net emissions increase calculation 

(step 2). Even if a project results in a significant emissions increase, the source may be able to demonstrate that the 

net emissions increase is insignificant and thus the project does not constitute a major modification. 
4-42

If refiners reduce their gasoline sulfur to 20 ppm immediately after the Tier 3 rule is 

finalized, as we anticipate they are capable of, then the substantial number of early credits 

generated would allow refiners to delay their unit start-ups sufficiently for refiners to not only 

make the tie-ins, but even complete their capital projects as necessary. However, we also 

conducted another analysis which assesses the ability of refiners to comply with Tier 3 if they 

generate no or few early credits. Using the estimate that turnarounds are scheduled at refineries 

every 4 years and the output from our refinery-by-refinery model, we analyzed how the need for 

refiners to tie in the new revamps and grassroots units affects the ability for refiners to comply 

with the Tier 3 program start date. Our refinery-by-refinery cost model projects how refiners 

will comply with the 10 ppm average gasoline sulfur standard at their refineries while 

minimizing the costs for doing so under the ABT program. Our modeling projects that the ABT 

program will result in a preference of revamps over grassroots units, and refiners desulfurizing 

their gasoline to 5 ppm at some refineries and generating credits that would allow refiners to not 

reduce the sulfur at other refineries requiring grassroots units. Also, small refiner and refinery 

provisions delay the Tier 3 start date for the refineries covered by these provisions until the year 

2020. Table 4-6 summarizes our estimate for the numbers of refineries which will need to 

comply in 2017 and also in 2020, when the Tier 3 gasoline sulfur program is fully phased-in. 

Table 4-6 Summary of Investment Types in 2017 and 2020 Assuming no Early Credit Use 

Grassroots 

Units

Revamps No 

Investments

Refineries 

Complying in 

2017

10 ppm 0 31 19

5 ppm 1 21

Small 

Refiners/Refineries 

Complying in 

2020

10 ppm 0 8 21

5 ppm 0 7

Total 10 ppm 0 39 40

5 ppm 1 28

Table 4-6 shows that to comply in 2017 without the use of early credits, 1 grassroots unit 

will be installed and 54 existing postreaters will be revamped to comply with the 10 ppm 

gasoline sulfur standard. Table 4-6 shows that some refineries would overcomply with the 10 

ppm gasoline sulfur standard by producing gasoline which contains 5 ppm sulfur and generate 

credits which would be purchased by refiners to show compliance because it would be more 

expensive at their refineries to reduce their gasoline sulfur to 10 ppm. Thus, 19 refineries will 
4-43

not need to reduce their gasoline sulfur to comply in 2017 because they purchase credits instead. 

Thirty six small refineries and refineries owned by small refiners will not need to invest for 2017 

because they don’t need to comply until 2020. 

With an estimate of the number of revamps and grassroots units needed for 2017, we can 

superimpose the tie-in timing that we believe would occur as refiners comply. Since the Tier 

rule was finalized by early 2014, we believe that refiners will begin to make their Tier 3 tie-ins 

starting in the spring of 2014. Thus, refiners will have the years of 2014, 2015 and 2016 to make 

their tie-ins during a regularly scheduled refinery turnaround, thus roughly three-quarters of the 

tie-ins could occur before the January 1, 2017 compliance date. The other quarter of revamped 

refineries would need to wait until the spring of 2017 to make their tie-ins. For the one 

grassroots unit, the tie in could be made anytime during the years from 2014 to 2017, but 

because we project that a grassroots unit requires three years until unit start-up, we project that 

the grassroots unit would start-up in the spring of 2017. Table 4-7 summarizes the unit startup 

timeline that accounts for the need for refiners to tie-in their revamped or grassroots units. Since 

we do not have data for when individual refineries are shutting down their FCC units and 

existing postreaters, we conducted a simple averaged analysis which assumes that each of the 

refineries is producing the same volume of gasoline and that each refinery earns credits for a year 

of compliance. To avoid confusion with how credits are generated under Tier 2, we call these 

compliance units (one compliance unit is equal to one refinery earning 20 ppm (30 minus 10 

ppm) credits or purchasing credits for one year). 

Table 4-7 Example Case of Compliance Unit Balance for Tier 3 

Revamps 

installed 2 

years after 

T3 

Published 

(April 2016)

Program 

Start Jan. 

1, 2017

Tie-ins made 

so that 

Revamps can 

start-up - 4 

Months after 

Program Start 

(April 2017)

Grassroots 

units start up 

16 Months 

after 

Program 

Start 

(April 2017)

Total 

Compliance 

Unitsa

# Revamps 39 13

# Grassroots 1

Compliance 

Unit 

Balancea

26 -4.3 -0.33 21.4

a Compliance units are a simplified representation for credits, whereas one refinery’s compliance with Tier 

3 (producing 5 or 10 ppm gasoline instead of 30 ppm gasoline) represents one compliance unit for each year of 

compliance. 

Table 4-7 shows that 39 of the total 52 revamps will have completed their tie-ins during 

the years 2014, 2015 and 2016 and will have the ability to start up immediately upon completion 

of construction of their revamped Tier 3 units. The startup of these revamps is estimated to be at 

the end of April 2016, about two years after Tier 3 is published. We believe that this is a 
4-44

conservative assumption because many revamps will not require the full two years to design, 

construct and start up. For example, we don’t discount the time required to complete these 

projects due to the fact that most refiners already completed their scoping studies before Tier 3 

was finalized. Even with this conservative set of assumptions, these refineries are estimated to 

generate 26 compliance units – 26 compliance units are generated because those 39 refineries are 

operating for two thirds of a year (May through December) before the compliance date of 

January 1, 2017. For the other 13 revamps and the one grassroots unit, they are assumed to start 

up at the end of April of 2017, which is one third of a year after the official program start date 

which would require the purchase of about 5 compliance units. The 26 compliance units 

generated greatly exceed the 5 compliance units needed to be purchased by the revamped and 

grassroots refineries estimated to start-up after January 1, 2017. It is important to point out that 

we did not assume any generation of early compliance units (early credits) in this analysis, thus 

no compliance units were created from 2012 through 2016, except for the revamps which started 

up in early 2016. 

While many refiners likely could begin to make their tie-ins in 2014, which would likely 

be before they have completed their finished design, many other refiners could also wait until 

2015 before they start to do so. We also assessed the leadtime feasibility if we assume that tieins don’t begin until the spring of 2015, thus tie-ins are made in the spring of 2015, 2016, 2017 

and 2018. Table 4-10 shows the number of refineries which would start up in the spring of each 

year based both on the time to construct the revamps and the grassroots unit and taking into 

account when the tie-ins are estimated to occur. Case 1 of Table 4-8 assumes that no early 

compliance units (early credits) are generated by refiners. Case 2 shows the compliance unit 

balance for Tier 3 if US refineries (including all the refineries not investing for 2017) average 

just 1 ppm lower sulfur starting in 2012, generating early compliance units over those 5 years. 

Case 3 shows the compliance unit balance for Tier 3 assuming that US refiners will average 3 

ppm lower sulfur starting in 2012 (data provided by refiners to EPA shows that the US refining 

industry averaged 26.7 ppm sulfur in 2012, which is greater than 3 ppm lower than what the 30 

ppm Tier 2 sulfur program requires). This analysis in Table 4-8 is really a business as usual 

case. Case 4 that we conducted assumed that all refineries average 27 ppm from 2012 until mid2014, and 20 ppm from mid-2014 until they start up, therefore generating 3 and 10 ppm worth of 

compliance units, respectively. 
4-45

Table 4-8 Example Cases of Compliance Unit Balances for Tier 3 

Early 

Compliance 

Unitsa 

2012 - 2016

Revamps 

installed 2 

years after 

T3 Published 

(April 2016)

Tie-ins made 

so that 

Revamps can 

start-up 

(April 2017)b

Grassroots 

and Revamp 

units start up 

(April 2018)b

Total 

Compliance 

Unitsa

# Revamps 26 13 13

# Grassroots 1

Case 1 

Compliance 

Unita Balance 

(no early 

credits)

17.3 -4.3 -20 -7.0

Case 2 

Compliance 

Unita Balance 

(1 ppm early 

credit)

27 16.5 -4.1 -17.7 21.7

Case 3 

Compliance 

Unita Balance 

(3 ppm early 

credits

81 14.7

-3.7

-15.9 76.1

Case 4 

Compliance 

Unita Balance 

(3/10 ppm 

early credits

175.5 8.7 -2.2 -9.3 172.7

a Compliance units are a simplified representation for credits, whereas one refinery’s compliance with Tier 

3 (producing 5 or 10 ppm gasoline instead of 30 ppm gasoline) represents one compliance unit for each year of 

compliance. 

b The reason why the values in these columns are decreasing as early credit increase is due to the fact that 

the sulfur level declines below 30 ppm reducing the number of compliance units needing to be purchased 

As shown in the upper row in Table 4-8, we conservatively assume no early compliance 

units are generated in Case 1 other than the start-up of the 26 revamps in early 2016. This case 

shows that the 17.3 early compliance units generated by the revamps which start up in April of 

2016 are insufficient to supply the 24.3 needed compliance units. To show how easy it would be 

to satisfy the demand for purchasing compliance units, Case 2 shows the compliance unit 

balance if we assume that all US refineries generate early compliance units by reducing their 
4-46

gasoline sulfur by only 1 ppm starting in 2012 (the gasoline they are producing is 29 ppm instead 

of 30 ppm). For this Case, the very modest additional compliance unit generation that occurs 

from 1 ppm of early credit generation (added to the revamps which start up in the spring of 2016) 

easily shifts the compliance units balance to a positive balance because the 43.5 early 

compliance units generated exceeds the 21.8 compliance units demanded. Case 3 assumes that 

refiners produce gasoline which averages 27 ppm sulfur, slightly higher than the level already 

being achieved in 2012. For this partial compliance case the 95.6 compliance units generated 

exceeds the 19.6 compliance units demanded by a large margin. Case 4, which assumes that 

refineries average 27 ppm until mid-2014 and 20 ppm afterwards, shows that the 184 compliance 

units generated exceed the 11.5 compliance units demanded by about a factor of seventeen. 

These analyses demonstrate that if the US refining industry generates a very modest number of 

early credits, that there is ample leadtime for refiners to comply with Tier 3. 

4.5.2.4 Hardship 

While we project that there will be plenty of credits available to allow refiners to 

complete their capital investments and tie in the new or revamped unit to the rest of their 

refinery, we provide another option to refiners as a safety valve in case there is a shortfall of 

credits. In the case where a refiner cannot complete its project by January 1, 2017 and credits are 

not available or are prohibitively expensive, the refiner may file a hardship waiver. Details about 

our hardship provisions can be found in Section 5.E.2 of the preamble. 

4.5.3 Permitting Analysis 

To meet the Tier 3 standards, it will be necessary for some U.S. refineries to install new 

equipment and/or modify existing equipment and processes resulting in increased emissions of 

some regulated air pollutants. Refinery projects designed to meet the new fuel standards could 

trigger preconstruction air permitting requirements under the Clean Air Act and the EPA’s New 

Source Review (NSR) regulations. 

EPA has updated our refinery-by-refinery assessment of the physical and operational 

changes that are likely to be needed to allow each active refinery in the U.S. to produce gasoline 

that complies with the final Tier 3 fuel specifications. We have also assessed the likely effects of 

those changes on refinery emissions. This updated assessment is described in more detail below. 

Using this updated assessment, we were able to update our understanding of the potential scope 

of the major NSR permitting requirements refiners might face under the final Tier 3 program. In 

general, our assessment indicates that only a small number of refineries will likely need to make 

modifications of a type and size that would trigger the need for a PSD or nonattainment NSR 

permit. 

In our updated analysis, we adjusted several inputs to reflect the existence of a 

nationwide average, banking, and trading (ABT) program and refined our estimates regarding the 

physical and operational changes that will be required at each refinery. The modifications at a 

given refinery could include revamps to existing FCC pre- or post-treatment unit(s) or the 

installation of a new grassroots post-treatment unit for sulfur reduction. Based on the updated 

projections of refinery-specific changes, we re-estimated the increased demand for energy (i.e., 

fuel to generate process heat, steam, and electricity), hydrogen, and sulfur recovery associated 
4-47

with meeting the final Tier 3 standards. Having received no comments suggesting that they 

should be changed, we re-applied the representative industry emission factors for NAAQS 

pollutants, their precursors, and GHGs for each emitting process and combined them with 

estimates of incremental activity to estimate the emissions changes at each equipment unit (or 

group of similar units) at each refinery. 

Resulting emissions increases were compared to pollutant-specific “major modification” 

permitting thresholds under the NSR regulations, including Prevention of Significant 

Deterioration (PSD) and Nonattainment New Source Review (NA NSR), as applicable. 

Refineries projected to trigger PSD and/or NA NSR for specific regulated NSR pollutants were 

identified. 

In summary, the permitting analysis results support the conclusion that NSR permitting 

impacts associated with the final Tier 3 fuel standards are limited, with only 3 refineries 

projected to trigger PSD and/or NA NSR for criteria pollutants and an additional 6 refineries 

projected to trigger PSD for GHGs only under the worst case impact scenario. 

In comparison, for the Tier 2 program, EPA expected the need for NAAQS-related NSR 

permits might be widespread among refineries. For the final Tier 3 gasoline sulfur standard, 

however, only about 3 refineries would need air permits that address NAAQS pollutants. 

This number could be lower if these refineries apply emission controls, such as selective 

catalytic reduction (SCR) for NOX, to reduce the emission increases below the significance level. 

For refineries that do need a major source NSR permit for NAAQS pollutants, the permitting 

process is expected to take 9 - 12 months. For an in depth assessment of stationary source 

implications, refer to Section V.K of the preamble. 

4.5.3.1 Calculation Approach 

A “major modification” is a physical change or change in the method of operation that 

results in a significant emissions increase and a significant net emissions increase.G

 In 

accordance with the major NSR applicability procedures contained in the federal regulations, the 

calculation approach for determining whether a significant emissions increase will occur depends 

upon the type of emissions units involved in the project. Three different tests can potentially 

apply: (1) the actual-to-projected-actual test for projects that involve only existing emissions 

units, (2) the actual-to-potential test for projects that only involve construction of new emissions 

unit(s) and (3) the hybrid test for projects that involve multiple types of emissions units. Under 

the hybrid test, the appropriate calculation is performed by emissions unit depending on new vs. 

existing unit status. The terms “existing emissions unit” and “new emissions unit” are defined in 

 

G

 This analysis is focused on the projected emissions increase (step 1) and the net emissions increase calculation 

(step 2). Even if a project results in a significant emissions increase, the source may be able to demonstrate that the 

net emissions increase is insignificant and thus the project does not constitute a major modification. 
4-48

the regulations. “Replacement units” meeting specified criteria are treated as existing emissions 

units for the purpose of calculating emissions increases.H

The actual-to-projected-actual test involves calculating baseline actual emissions and 

projected actual emissions for each emissions unit affected by a project and calculating the 

project emissions increase as the sum of the differences between projected actual emissions and 

baseline actual emissions for each unit. The definition of projected actual emissions provides that 

the owner or operator shall exclude, in calculating the increase from a particular emissions unit, 

that portion of the unit’s emissions following the project that the unit could have accommodated 

in the selected baseline actual emissions period and that are also unrelated to the project, 

including any increased utilization due to demand growth. The actual-to-potential test compares 

the potential to emit of a unit with the baseline actual emissions and does not provide for the 

exclusion of any emissions in calculating the increase. For new emissions units other than those 

qualifying as replacement units, baseline actual emissions are zero. 

Because individual refinery project details were not available for this analysis, EPA used 

a simplified approach to approximate the results from the application of the actual-to-projectedactual and/or or actual-to-potential tests for affected units at each source. The approach relied 

upon estimates of incremental energy, hydrogen and sulfur recovery demands associated with 

meeting the final Tier 3 fuel standards and the application of scaling factors to adjust from base 

year to projected maximum annual rates and design rates for existing and new units, respectively. 

Representative industry emission factors were identified for each affected emissions unit 

category (i.e., process heaters/boilers, hydrogen plants and sulfur recovery units) and emissions 

increases were calculated as the product of the production or activity data (e.g., MMBtu energy 

demand) and corresponding emission factors (e.g., lb/MMBtu). The activity data and emission 

factors used in the analysis are discussed in further detail below. 

Activity Data 

EPA performed a refinery-by-refinery analysis of process and equipment changes likely 

to be implemented to meet the final Tier 3 fuel standards and from this analysis generated 

refinery-specific estimates of energy demand, hydrogen demand and increased sulfur recovery 

unit (SRU) loading for 108 U.S. refineries. Energy demand includes fuel needed to generate 

process heat, steam and electricity. Hydrogen demand is associated with increased hydrotreating 

of post-fluid catalytic cracking (FCC) naphtha and light straight run (LSR) streams, which may 

involve new or revamped hydrotreater units. Increased SRU loading results from the increased 

fuel desulfurization and associated H2S generation. 

 

H

 The actual-to-projected actual test was adopted in the federal regulations as part of the 2002 NSR Reform 

rulemaking. At this time, the Reform Rule provisions are available to sources in a large majority of state/local 

jurisdictions either by delegation or adoption into state/local rules (most of which are SIP approved). There may be 

isolated cases where, at the time that Tier 3 projects are being evaluated for NSR applicability, Reform Rule 

applicability procedures are not available. For the purpose of this analysis, it was assumed that the federal NSR 

applicability procedures were available for all affected sources because: 1) this is the case for most refineries 

presently, and 2) the analysis is sufficiently conservative such that applying alternative applicability calculations is 

not expected to significantly affect the overall conclusions. 
4-49

In our updated analysis, we adjusted the analysis performed prior to the NPRM to reflect 

a nationwide average, banking, and trading (ABT) program which is being finalized and refined 

our estimates regarding the physical and operational changes that will be required at each 

refinery. To estimate the Tier 3 emissions impacts, it was first necessary to establish the 

production volumes of the units that would be affected by the standards. A “normal operating” 

case reflecting calendar year volumes was developed using refinery-specific actual base-year 

(2011) production data and production-normalized impact data (e.g., MMBtu per 1000 bbl 

gasoline production and MMscf hydrogen per 1000 bbl gasoline production). Normal operating 

production rates were then scaled up to reflect maximum annual capacity utilization rates and 

further adjusted using “overdesign” factors in certain cases as summarized below. This scaling 

was done under the assumption that, for the purpose of determining NSR applicability, each 

refinery would project emissions based on the maximum achievable production rate for existing 

units and would use design capacity to calculate potential to emit for new units. It was not tied to 

any particular assumption about overall gasoline demand. 

For refineries projected to meet Tier 3 sulfur specifications by revamping existing 

hydrotreater units, demands were scaled up to 92 percent of the refinery’s maximum 

design production. If a particular refinery ran its FCC at a utilization level above 92 

percent in the base year, it was assumed that that refinery was already operating at its 

annual capacity and no adjustment was made. 

For refineries projected to meet Tier 3 standards by installing new FCC post treatment 

units (post-treaters), the same scale-up approach documented above for revamps was 

applied, and an additional overdesign factor of 15 percent was applied to represent a 

maximum stream day capacity. 

For refineries projected to install new LSR treating units, the same approach was applied 

as documented above for new FCC post-treaters. 

For SRUs, the additional sulfur loading was calculated based on the incremental sulfur 

reduction required to meet the proposed standards and the scaled-up production estimates 

documented above for FCC revamps. 

From the scaled utility demand data, low and high impact cases were designed for 

estimating emissions increases under each scenario as follows. 

Low case: Each refiner buys its additional hydrogen, high octane blendstocks and 

electricity externally. 

High case: Each refiner generates the required additional hydrogen, high octane 

blendstocks and electricity internally. 

The low case represents external sourcing of some of the energy and chemical demand 

associated with meeting the proposed standards, meaning that emissions associated with these 

activities do not occur from the refinery itself and are not accounted for in determining NSR 

applicability. The high case represents internal production of all required energy and chemical 

demand, meaning that these impacts do occur at the refinery itself and are accounted for in 

determining NSR applicability.
4-50

Emission Factors 

The emission factors used to estimate Tier 3 projected emissions increases are 

documented in Table 4-9. 

Table 4-9 Emission Factors 

Unit Pollutant EF Units Reference

Heaters & 

Boilers

NOx 0.040 lb/MMBtu Assumed average for new/modified units equipped with ultralow NOx burners; consistent with NSPS subpart Ja for natural 

draft heaters (40 CFR 60.102a).

SO2 0.012 lb/MMBtu

Calculated based on 8 ppmv annual average SO2 limit in NSPS 

subpart Ja (40 CFR 60.102a).

CO 0.040 lb/MMBtu Recent BACT determinations – burner design and good 

combustion practices.

VOC 0.0055 lb/MMBtu AP-42 Chapter 1.4.

PM10 0.0075 lb/MMBtu AP-42 Chapter 1.4.

PM2.5 0.0075 lb/MMBtu AP-42 Chapter 1.4.

H2SO4 0.0004 lb/MMBtu Assumes 2% oxidation of SO2 to SO3 (non-SCR).

CO2e 130.6 lb/MMBtu

40 CFR 98 Tables C-1, C-2 (CO2 EF for fuel gas; CH4 & N2O 

EFs for petroleum).

H2 Plant CO2 25.0 tons/MMscf H2 Bonaquist, Dante. Analysis of CO2 Emissions, Reductions, and 

Capture for Large-Scale Hydrogen Production Plants, White 

Paper. Praxair, Oct. 2010. (Available in docket).

SRU NOx 0.271 lb/ton S Calculated industry average EF based on 2005 NEI.

SO2 3.792 lb/ton S Calculated industry average EF based on 2005 NEI.

CO 0.882 lb/ton S Calculated industry average EF based on 2005 NEI.

VOC 0.039 lb/ton S Calculated industry average EF based on 2005 NEI.

PM10 0.020 lb/ton S Calculated industry average EF based on 2005 NEI.

PM2.5 0.017 lb/ton S Calculated industry average EF based on 2005 NEI.

H2SO4 0.290 lb/ton S Calculated as 5% of SO2 EF corrected for mol. wt.

CO2 806.9 lb/ton S Technical Support Document for the Petroleum Refining 

Sector: Proposed Rule for Mandatory Reporting of Greenhouse 

Gases. EPA OAR, Sept. 8, 2008, p. 11. (Available in docket).
4-51

Pollutants Evaluated

The regulated NSR pollutants identified in the table above were determined to have some 

probability of triggering major NSR as a result of projects designed to meet the final Tier 3 fuel 

standards. Certain other regulated NSR pollutants, including total reduced sulfur (TRS), H2S and 

reduced sulfur compounds (RSC) may be emitted at very low rates from potentially affected 

refinery units, but were determined to have little or no probability of exceeding significant 

emission rate thresholds. Therefore, these pollutants were not included in the quantitative 

analysis. 

Heaters and Boilers

The emission factors selected for refinery process heaters and boilers represent 

combustion emissions from refinery fuel gas (RFG) and/or natural gas. The worst case (higher 

emitting fuel) was assumed where fuel-specific factors were available. For NOx, an emission 

factor of 0.040 lb/MMBtu was selected to represent average emissions from new and modified 

refinery process heaters and boilers. In most cases, emissions at this level are achievable using 

ultra-low NOx burners and without the addition of add-on controls such as selective catalytic 

reduction (SCR). With the use of SCR, emissions substantially below this level, on the order of 

0.01 lb/MMBtu or less are achievable. An SO2 emission factor of 0.012 lb/MMBtu was 

calculated based on the NSPS subpart Ja annual average SO2 limit of 8 ppmv for fuel gas 

combustion units. A CO emission factor of 0.040 lb/MMBtu was selected based on recent BACT 

determinations that represent burner design and good combustion practices.I VOC and PM 

emission factors are based on EPA AP-42 Chapter 1.4: Natural Gas Combustion and are 

consistent with permit precedent for refinery heaters.JFor sulfuric acid mist, it was 

conservatively assumed that 2 percent of SO2 emissions oxidize to SO3 and then condense to 

form H2SO4. A GHG emission factor of 130.6 lb/MMBtu CO2 equivalent (CO2e) was calculated 

as the sum of CO2, CH4 and N2O emission factors reported in 40 CFR 98 (EPA GHG Reporting 

Rule, Subpart C) for fuel gas multiplied by their respective global warming potentials. 

Hydrogen Plants 

In addition to emissions associated with process heat, hydrogen production by steam 

methane reforming (SMR) generates CO2 emissions as a byproduct. The selected CO2 emission 

factor of 25 lb/MMscf H2 is based on data from Praxair, a major hydrogen plant engineering and 

design firm and hydrogen supplier to the refining industry in the U.S. 

Sulfur Recovery Units

Emissions from SRUs can vary significantly depending on design and upstream 

variables, making published emission factors inappropriate in general. To account for this 

variability, EPA derived industry average emission factors for most pollutants based on total 

 

I

 Based on a review of recent BACT determinations documented in the EPA RACT/ BACT/ LAER Clearinghouse 

available at: http://cfpub.epa.gov/RBLC/index.cfm?action=Home.Home

J

 Available at: http://www.epa.gov/ttn/chief/ap42/ch01/final/c01s04.pdf
4-52

refinery SRU emissions reported in the 2005 National Emissions Inventory (NEI) database 

combined with sulfur plant production data from the U.S. Energy Information Administration 

(EIA). For sulfuric acid mist, it was conservatively assumed that 5 percent of SO2 emissions 

oxidize to SO3 and then condense to form H2SO4. For GHGs, a CO2 emission factor from the 

EPA Technical Support Document for the proposed GHG Reporting Rule for the petroleum 

refining sector was used. 

Attainment Status 

The attainment status of each refinery location for ozone and PM (PM2.5 and PM10) was 

determined using nonattainment area designation information from the EPA Green Book website 

as of November 1, 2013 supplemented by information in relevant notices for final redesignation 

actions that were not yet reflected on the website.K Based on the attainment status and 

classification (for ozone nonattainment areas), NA NSR and PSD triggers were resolved for each 

refinery. For serious and severe ozone nonattainment areas, or areas required to maintain NSR 

program requirements consistent with those designations under the prior 1-hour ozone standard 

as a result of the “anti-backsliding” policy, major modification thresholds of 25 tons per were 

assumed for the precursors NOx and VOC, versus 40 tons per year in attainment areas and areas 

classified as marginal or moderate nonattainment.L

4.5.3.2 NSR Applicability Results 

The results of the Tier 3 projected NSR applicability analysis are summarized below for 

the lowest and highest NSR impact scenario/case combinations. In total, 108 refineries 

determined to be potentially affected by the final standards were included in the analysis. 

No ABT Scenario; Low Case 

4 refineries trigger PSD and/or NA NSR 

2 of the 4 refineries trigger PSD and/or NA NSR for criteria pollutant(s) 

2 of the 4 refineries only trigger PSD for GHGs 

Primary ABT Scenario; High Case 

9 refineries trigger PSD and/or NA NSR 

3 of the 9 refineries trigger PSD and/or NA NSR for criteria pollutant(s) 

6 of the 9 refineries only trigger PSD for GHGs 

The pollutants driving major NSR applicability are GHGs and NOx. None of the other 

pollutants evaluated, including SO2, CO, VOC, PM2.5 and PM10 and H2SO4, exceeded major 

 

K

 Available at: http://www.epa.gov/oaqps001/greenbk/

L

 The significant emission rate (SER) threshold in severe ozone nonattainment areas is 25 tpy of NOx and VOC. 

While the SER in serious nonattainment areas is 40 tpy of NOx and VOC, increases in both serious and severe 

nonattainment areas are also affected by CAA §182(c)(6), which limits aggregated NOx and VOC emissions over a 

five-year period to less than 25 tpy to avoid major NSR. For the purpose of this analysis, a SER of 25 tpy for NOx

and VOC was conservatively assumed for both serious and severe ozone nonattainment areas. 
4-53

modification thresholds at any refinery. It should also be noted that in several cases, emissions 

increases shown to trigger NSR were very close to the respective thresholds, indicating that there 

would likely be opportunities to design these projects in such a way to avoid NSR applicability, 

at least for some pollutants. 

Example Calculations 

The following example calculations illustrate the approach used to determine NSR 

applicability on a refinery-by-refinery basis. The calculations are based on hypothetical Tier 3 

project impacts. 

Assumptions

Refinery located in an area designated as attainment/unclassifiable for all criteria 

pollutants (PSD area) 

Incremental demand estimates reflect “high case” assumptions, i.e., hydrogen and 

electrical power demand generated internally 

Tier 3 Incremental Refinery Demand Estimates:

Total energy demand: 1,500,000 MMBtu/yr 

Hydrogen demand: 400 MMscf/yr 

SRU production: 150 tons S/yr 

Emissions Increase - NOx:

[(1,500,000 MMBtu/yr) × (0.040 lb/MMBtu) + (150 tons S/yr) × (0.271 lb/ton)] × (1 

ton/2,000 lb) = 30.0 tons NOx/yr 

The applicable significant emission rate threshold for NOx is 40 tpy; therefore, the 

project does not trigger PSD for NOx.

Emissions Increase - PM2.5:

[(1,500,000 MMBtu/yr) × (0.0075 lb/MMBtu) + (150 tons S/yr) × (0.017 lb/ton)] × (1 

ton/2,000 lb) = 5.63 tons PM2.5/yr 

The applicable significant emission rate threshold for PM2.5 is 10 tpy; therefore, the 

project does not trigger PSD for PM2.5. 

Emissions Increase - GHGs (CO2e):

[(1,500,000 MMBtu/yr) × (130.6 lb/MMBtu) + (150 tons S/yr) × (806.9 lb/ton)] × (1 

ton/2,000 lb) + (400 MMscf H2/yr) × (25 tons/MMscf) = 108,011 tons CO2e/yr 
4-54

The applicable “subject to regulation” threshold for GHGs is 75,000 tpy CO2e and the 

applicable significant emission rate threshold is any increase on a mass basis; therefore, the 

project triggers PSD for GHGs.
4-55

References 

1

 Meyers, Robert A., Handbook of Petroleum Refining Processes, McGraw Hill, 1997. 

2

 40 CFR 80 Subpart H. 

3

 Shorey, Scott W., AM – 99-55, Exploiting the Synergy Between FCC and Feed Pretreating Units to Improve 

Refinery Margins and Produce Low-Sulfur Fuels, National Petroleum and Refiners Association’s 1999 Annual 

Meeting. 

4

 Conversation with Woody Shiflett, Advanced Refining Technologies, October 2011. 

5

 Barletta, Tony, Refiners must optimize FCC feed hydrotreating when producing low-sulfur gasoline, Oil and Gas 

Journal, October 14, 2002. 

6

 Conversation with Woody Shiflett, Advanced Refining Technologies, October 2011. 

7

 Shorey, Scott W., AM – 99-55, Exploiting the Synergy Between FCC and Feed Pretreating Units to Improve 

Refinery Margins and Produce Low-Sulfur Fuels, National Petroleum and Refiners Association’s 1999 Annual 

Meeting. 

8

 Brunet, Sylvette, On the hydrodesulfurization of FCC gasoline: a review, Applied Catalysis A: General 278 

(2005) 143 – 172. 

9

 Leonard, Laura E., Recombination: A Complicating Issue in FCC Naphtha Desulfurization, Prepared for the 

AIChE 2006 Spring National Meeting, April 26, 2006. 

10 Petroleum Refinery Process Economics, Maples, Robert E., PennWell Books, Tulsa, Oklahoma, 1993. 

11 Nocca, J.L., et al, Cost-Effective Attainment of New European Gasoline Sulfur Specifications within Existing 

Refineries, November 1998. 

12 Prime G, A Sweet Little Process for Ultra-Low Sulfur FCC Gasoline without Heavy Octane Penalty, IFP 

Industrial Division. 

13 Debuisschert, Quentin, Prime G+ Update, 12th European FCC Conference – Grace Davidson Seminar, Seville 

Spain, May 2004. 

14 Beck, J.S., Advanced Catalyst Technology and Applications for Higher Quality Fuels and Fuels, Prepr. Pap. Am 

Chem Soc., Div. Fuel Chem, 2004 49(2), 507. 

15 McGihon, Ron, Exxon Mobil, FCC Naphtha Desulfurization – New Developments, Presentation at the 2009 

Technology Conference, October 5 &6, Dubai, United Arab Emirates. 

16 Ellis, E.S., Meeting the demands of low sulfur gasoline, Petroleum Technology Quarterly Spring 2002. 

17 Successful Start-Up of New Scanfining Unit at Statoil’s Mongstad Refinery, November 19, 2003. 
4-56

18 Greeley, J.P., Zaczepinski, S., Selective Cat Naphtha Hydrofining with Minimal Octane Loss, NPRA 1999 

Annual Meeting (this document available from docket A-97-10). 

19 Halbert, Thomas R., Technology Options for Meeting Low Sulfur Mogas Targets AM-00-11, Presented at the 

2000 Annual Meeting of the National Petrochemical and Refiners Association, March 2000. 

20 McGihon, Ron, Exxon Mobil, FCC Naphtha Desulfurization – New Developments, Presentation at the 2009 

Technology Conference, October 5 &6, Dubai, United Arab Emirates. 

21 Refining Processes 2004, Hydrocarbon Processing. 

22 Upson, Lawrence L., Low-sulfur specifications cause refiners to look at hydrotreating options, Oil and Gas 

Journal, December 8, 1997. 

23 Krenzke, David L., Hydrotreating Technology Improvements for Low-Emissions Fuels AM-96-67, Presented at 

the 1996 Annual Meeting of the National Petrochemical and Refiners Association, March 1996. 

24 UOP SelectFiningTM Process – New Technology for FCC Naphtha HDS, 2009. 

25 CDTECH, FCC Gasoline Sulfur Reduction, CDTECH, Sulfur 2000, Hart’s Fuel and Technology Management, 

Summer 1998. 

26 Rock, Kerry J., Putman, Hugh, Global Gasoline Reformulation Requires New Technologies, Presented at Hart’s 

World Fuels Conference, San Francisco, March 1998. 

27 Rock, Kerry L., et al, Improvements in FCC Gasoline Desulfurization via Catalytic Distillation, Presented at the 

1998 NPRA Annual Meeting, March 1998. 

28 Greenwood, Gil J., Next Generation Sulfur Removal Technology AM-00-12, Presented at the 2000 NPRA Annual 

Meeting, March 2000. 

29 Meier, Paul F., S Zorb Gasoline Sulfur Removal Technology – Optimized Design AM-04-14, Presented at the 

2004 NPRA Annual Meeting, March 2004. 

30 Printed Literature by Phillips Petroleum Shared with EPA September 1999. 

31 Patal, Raj, Advanced FCC Feed Pretreatment Technology and Catalysts Improves FCC Profitability AM-02-58, 

Presented at the 2002 NPRA Annual Meeting, March 2002. 

32 Conversation with Woody Shiflett of Advanced Refining Technologies October 2011. 

33 Letter to Margo Oge, EPA, from Mike Ricca, Baker Hughes, July 25, 2011. 

34 Letter to Caryn Muellerleine, EPA, from Richard Kelly, Marvel Oil Company, July 13, 2011. 

35 The requirements for transmix blenders are contained in 40 CFR 80.84(d). 

36 Graphs of transmix gasoline product sulfur levels at Kinder Morgan transmix processing facilities e-mail from 

James Holland, Kinder Morgan, August 24, 2011. 
4-57

37 Moncrief, Philip and Ralph Ragsdale, “Can the U.S. E&C Industry Meet the EPA’s Low Sulfur Timetable,” 

NPRA 2000 Annual Meeting, March 26-28. 2000, Paper No. AM-00-57.

38

 Judzis Jr., Arvids, Start-up of First CDHDS Unit at Motiva’s Port Arthur, Texas Refinery AM-01-11, technical 

paper presented at the 2001 National Petrochemical and Refiners Association Annual Meeting, March 2001. 

39

 Nocca, Jean-Luc, Prime G+: From Pilot to Start-up of Worlds First Commercial 10 ppm FCC Gasoline AM-02-

12, Technical Paper presented at the 2002 National Petrochemical and Refiners Association Annual Meeting, March 

2002.

40

 Bedell, Richard, Power point presentation to the Energy Summit 2007, LSU Center for Energy Studies, October 

24, 2007. 

41

 Fact Sheet entitled “Refinery Turnarounds,” American Petroleum Institute (API) webpage: 

http://www.api.org/oil-and-natural-gas-overview/fuels-and-refining/refineries/refinery-turnarounds; downloaded 

June 21, 2013. 

42

 Energy Information Administration, Refinery Outages: Description and Potential Impact on Petroleum Product 

Prices, March 2007. 
5-1

Chapter 5 Fuel Program Costs 

5.1 Methodology 

This chapter provides a summary of the methodology used and the results obtained from 

our cost analyses of the final Tier 3 gasoline sulfur control program. We start by summarizing 

the refinery models used for our analysis. We then describe our detailed methodology for 

estimating the sulfur control costs for our proposed sulfur program followed by the results. 

Finally, we discuss and compare the results of several other cost analyses. 

5.1.1 Overview 

When we began our planning for estimating the cost of additional reductions in gasoline 

sulfur, we considered two different options. One option for estimating the costs would be to 

utilize a linear programming (LP) model, while the second option would be to develop a 

refinery-by-refinery cost model. While the LP refinery models are necessary and appropriate for 

many analyses, they also have several important limitations of relevance here. When used to 

model the cost of nationwide fuel control programs on the entire refining industry, LP models are 

usually used to model groups of refineries in geographic regions called Petroleum 

Administration for Defense Districts (PADDs). The LP refinery model averages the costs over 

the refineries represented in the PADDs; however, the technology chosen by the refinery model 

would normally be the lowest cost technology found by the refinery model. This may represent 

an unreasonable choice of technologies for individual refineries because of how refineries are 

configured and based on the sulfur control technologies installed for compliance with the Tier 2 

gasoline sulfur program. While the choice of technologies can be limited based on an 

approximate analysis of what mix of technologies would best suit the group of refineries 

modeled in each PADD, this would only provide an approximate estimate of the cost incurred. 

Based on the quality of input data to these LP models and the assumptions made for complying 

with a regulatory requirement, LP refinery models may overestimate or underestimate the 

program costs. For example, an LP refinery model would not be a sensible tool for estimating 

the credit averaging and trading between refineries. This could be partially overcome by 

iterating between PADD refinery model runs, thus estimating the number of credits traded 

between PADDs and estimating the level of sulfur control in each PADD. However, the need to 

make multiple runs per PADD for each case, coupled with the need to run multiple control cases 

for different sulfur standards, would be very time consuming, costly and still would only result in 

approximate estimates of the sulfur levels achieved and the cost incurred. 

For this reason, EPA developed a refinery-by-refinery cost model which models the 

capability for each refinery to revamp existing or install new sulfur control technologies 

available to them to reduce their gasoline sulfur levels. Rather than start from scratch, we started 

from a refinery-by-refinery cost model developed by APT (Mathpro) for EPA to estimate the 

cost of benzene control under MSAT2. However, instead of using the representations of benzene 

control technology contained in the model, we obtained information about gasoline 

desulfurization and represented the cost of this desulfurization in the refinery-by-refinery cost 

model. 
5-2

We believe the refinery-by-refinery cost model best estimates the cost of individual 

refineries, especially when considering an averaging, banking and trading (ABT) program and 

therefore is the best analysis tool for estimating nationwide costs. However, certain inputs 

necessary for estimating costs. Because some refinery-specific information is not publicly 

available, it was necessary to find another way to estimate certain inputs necessary for estimating 

costs with the refinery-by-refinery model. The inputs and outputs from LP refinery cost 

modeling provide this needed information and it was utilized in the refinery-by-refinery cost 

model. The information from LP refinery modeling used in the refinery-by-refinery cost model 

is described in Section 5.1.2, and in more detail in other Sections below. 

Since the refinery-by-refinery cost model contains confidential business information for 

each refinery, we could not publish the model or present some of the details of the model here. 

Therefore, to ensure its viability, the refinery-by-refinery cost model that we developed for the 

proposed rule was subjected to peer reviews by two refinery industry consultants (involving a 

total of three peer reviewers). Our review of most of the suggested changes recommended by the 

initial set of peer reviewers suggested that there would be little to no change in our 

desulfurization cost estimate (some of the changes would increase the estimated costs, while 

others would reduce the estimated costs). Also, after modifying the modeling to respond to this 

first round of peer review comments, we then went on to make a number of additional model 

improvements to support the final rule. This additional work was then put through a second 

round of peer review that was used to modify the modeling for this FRM. The peer review 

comments and our assessment of the peer review comments are contained in reports submitted to 

the docket. 1 2 3 4

 The refinery-by-refinery cost model focuses on reducing sulfur from the FCC naphtha 

because of its high sulfur content. To comply with the 30-ppm Tier 2 sulfur control program, 

most refiners installed FCC naphtha hydrotreaters (referred to as FCC postreaters) or FCC feed 

hydrotreaters (referred to as FCC pretreaters) to reduce that unit’s sulfur contribution to their 

gasoline pool. If refiners installed an FCC postreater under Tier 2, we modeled refiners 

revamping those units. However, if refiners relied on FCC pretreaters to comply with Tier 2, we 

assumed that grassroots FCC postreaters would have to be installed at those refineries to reduce 

its gasoline pool down to 10 ppm. However, since adding grassroots FCC postreaters is 

relatively expensive for the amount of sulfur reduction obtained, the ABT analysis we conducted 

avoided almost all of these types of investments. Refineries with both pre and postreaters today 

could achieve further gasoline sulfur reductions less than 10 ppm (we used 5 ppm) at a relatively 

low incremental cost and sell the credits to those refiners who are operating refineries which 

would otherwise be faced with grassroots postreater investments. In addition to addressing the 

sulfur in the FCC naphtha, we believe that at some refineries, refiners may need to reduce the 

sulfur in light straight run (LSR) naphtha. 

To better understand the desulfurization costs, we evaluated several alternative gasoline 

sulfur control scenarios or cases besides the primary final rule cost analysis. For a 10-ppm 

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

standard with no averaging among refineries and another with only intra-company transfers of 

sulfur credits. To provide credits for averaging and trading under the 10-ppm average standard, 

we evaluated refiners reducing their gasoline sulfur down to 5 ppm. Since we had estimated 

costs for each refinery to get to 5 ppm sulfur, we also report out the cost for a 5 ppm average 
5-3

gasoline sulfur standard assuming no averaging between refineries (at an average of 5 ppm, the 

opportunity to comply through credit transfers would be limited). Although we considered 

reducing the 80 ppm cap standard, we do not provide any cost assessment for lowering the 80 

ppm cap standard, nor do we estimate sulfur control costs which include a lower cap standard. 

These different scenarios are summarized in Table 5-1.

Table 5-1 Sulfur Control Cases Evaluated for the Final Rule 

Description Sulfur Standard ABT Credit Trading Cap Standard

Final Rule Fuels 

Program 10ppm Nationwide 80 ppm

Limited Credit 

Trading (Proposed 

rule) 

10 ppm Intra-company

80 ppm

No Credit Trading 10 ppm None 80 ppm

Stringent Sulfur 

Standard 5 ppm None 80 ppm

We made a series of improvements to the cost analysis since we completed the proposed 

rule cost analysis. Some of the improvements were made to address the comments of the peer 

reviewers. Others were conceived and incorporated to further improve the robustness of the 

refinery modeling work by incorporating more data which we believe allowed us to better model 

each individual refinery. The following describes the most important improvements that we 

made to the refinery-by-refinery cost model: 

We updated the EIA data for individual refineries in the refinery-by-refinery cost model 

from 2009 to 2011. The data that we updated included crude oil sulfur content and API gravity, 

refinery-specific throughput volumes for the atmospheric crude tower, the FCC unit, cokers and 

hydrocrackers We also incorporated new refinery-specific data into the refinery cost model 

which includes purchases and sales of pentanes plus (natural gas liquids or NGLs), and sales into 

the petrochemical market. 

Refinery blendstock volumes for the reformer, alkylation unit, isomerization unit, and the 

naphtha hydrotreater are now based on actual throughput volume data from the Office of Air 

Quality Planning and Standards (OAQPS). OAQPS requested, and the Office of Management 

and Budget (OMB) approved, the collection of refinery operations data by OAQPS from refiners 

which included throughput data for many refinery units. The data collected by OAQPS was for 

the year 2010. We obtained that data and entered it into the refinery-by-refinery model and this 

new data provides us with a much clearer picture of how these units are being utilized in 

individual refineries and provides us with a much more robust modeling tool. Previously we 

were using projected PADD-average use estimates by an LP refinery modeling run made by 

Mathpro for the MSAT2 cost analysis. A very important outcome of using this actual unit 

throughput data is that we removed the uncertainty associated with the volumes of gasoline 

blendstocks which make up each refinery’s gasoline pool. Since we better understand the 

volumes of these gasoline blendstocks, we can much better deduce certain other practaces that 

refiners may be using, such as undercutting their heavy naphtha streams into the jet and diesel 

pools which will likely have implications for complying with Tier 3. 
5-4

We attempted to better match each refinery’s gasoline production in the refinery-byrefinery cost model to actual refinery gasoline production volume as reported to EPA. In trying 

to match individual refinery gasoline volumes, we estimated if the practice of undercutting FCC 

naphtha and heavy naphtha is being practiced. Since we often had excess gasoline blendstock 

material, we also estimated hydrocracker operation (naphtha, intermediate, or diesel modes) as a 

means to match gasoline volumes. More often than not, heavy naphtha volumes tend to exceed 

reformer throughput volumes, so for those refineries that have excessive gasoline volumes we 

assume that the excessive heavy naphtha volume is sold. For refineries with insufficient gasoline 

volume, this excess volume is assumed to be blended into gasoline (but not reformed). 

We updated the refinery-by-refinery model with 2012 refinery capacity data, and 

included some 2013 and later data for announced expansions. Based on the comments of one 

peer reviewer, we focused on including the expansions of the refineries recently modified to 

process more tar sands from Canada. Because we incorporated the refinery expansions that 

involved processing more tar sands, we needed to not only process more volume, but we needed 

to adjust the quality of crude oil processed by the refinery to represent the heavier tar sands. 

The volume of light and heavy straight run naphtha are based on the API gravity of the 

crude oil slate being refined by each refinery. This replaces the previous method of relying on 

similar correlation for the average quality of crude oil refined in each PADD. 

We developed a means to adjust desulfurization costs to account for the cases when a 

refinery’s modeled desulfurization situation differed from the typical case for which the vendors 

provided us information. For example, for reducing a refinery’s gasoline sulfur from 30 ppm to 

10 ppm, the refiner would typically need to reduce its FCC naphtha from 75 to 25 ppm. 

Depending on the amount of FCC naphtha blended into its gasoline, the amount of sulfur control 

that the refiner would need to achieve in its FCC naphtha could be larger or smaller than this. 

We linearly adjusted the desulfurization cost to account for the variances from the typical case. 

However, where the level of desulfurization required exceeded 96% and 99% for single stage 

and double stage units, respectively, we assumed an exponential increase in hydrogen demand 

and octane loss. If we did not make this adjustment, we would be underestimating the cost for 

those refineries which must achieve a very steep rate of desulfurization. 

We incorporated in our refinery-by-refinery cost model refiner actions that they took for 

complying with the Mobile Source Air Toxics rulemaking to reduce the content of benzene in 

their gasoline. This affected the volume of benzene precursors sent to the reformer or the volume 

of benzene extracted from the gasoline pool. 

We obtained more information from vendors of gasoline desulfurization equipment and 

included this information in the final rule cost analysis. We increased the offsite factor for the 

vendor costs to 0.35 based on discussions with engineering companies.5

In the refinery-by-refinery cost model, we updated utility (natural gas and electricity) cost 

projections to be based on AEO 2013, the most recent projections available at the time that we 

were conducting the final rule cost analysis. 
5-5

We updated the octane costs used in the refinery-by-refinery model. To do so we 

improved, updated and reran the LP refinery model for octane costs, As part of the LP refinery 

analysis, we updated our analysis of the changes in gasoline qualities associated with gasoline 

sulfur control. The LP refinery model incorporated improvements in how the model blends up 

reformate.A

The several errors that the peer reviewers found in the version of the refinery-by-refinery 

model that was used for the proposed rule have been corrected. These errors had an insignificant 

impact on the costs of the Tier 3 program. 

Since we made a series of new modifications to the refinery-by-refinery cost model, we 

had the refinery-by-refinery cost model peer reviewed again by three peer reviewers. The 

following describes the most important improvements that we made to the refinery-by-refinery 

cost model based on the second round of peer reviews: 

Two peer reviewers commented that inside battery and outside battery limit costs that we 

estimated do not reflect extra costs which could be incurred. Such excess costs could include 

adding pilings for foundations at construction sites with poor soil, adding a control room for 

operations control, adding a storage tank, and long pipeline runs in the case that the Tier 3 unit 

needs to be placed an abnormally long distance from associated refinery units. To account for 

such cost add-ons, we applied a 20% contingency factor. 

One peer reviewer commented that some FCC feed pretreaters are too small to hydrotreat 

the entire FCC feed, yet our cost analysis assumed that that the entire FCC feed was being 

hydrotreated. We adjusted the sulfur level of the feed and the output of FCC units in the cases 

where the FCC pretreaters were relative small in throughput capacity and could only treat a part 

of the FCC feed. 

One peer reviewer commented that we only accounted for the sulfur content of vacuum 

gas oil and not very high sulfur light coker gas oil which also is fed to FCC units. For those 

refineries with cokers, we increased the sulfur content of the feed to the FCC pretreater or FCC 

unit to account for refining light coker gas oil in addition to vacuum gas oil. 

One peer reviewer commented that the volumetric yield loss from the reformer was based 

on too low of severity and that many reformers are operating at a higher severity than that which 

would cause a higher yield loss. We developed a methodology for estimating reformer severity 

which resulted in higher average reformer severity. 

One peer reviewer commented that the regression that we developed for estimating light 

straight run volume from crude oil had a poor fit. The peer reviewer provided a regression based 

on much more crude assays with a much better fit of the data and we used that regression to 

estimate light straight run volume for each refinery. 

 

A

 The refinery model now estimates reformate distillation properties, including RVP, based on actual feed qualities. 

Before the improvements, the refinery model estimated a fixed set of reformate distillation properties based on a 

typical set of feed qualities. 
5-6

We discuss how we applied these changes to our refinery-by-refinery cost model in the 

following sections and a more complete discussion of the peer review comments and our 

response to them are contained in our response document to the peer review comments. 

5.1.2 LP Refinery Modeling Methodology and Results 

Although we used the refinery-by-refinery cost model to estimate gasoline 

desulfurization costs, certain input information was needed. Without access to detailed refineryspecific information, we relied on outputs from our LP refinery modeling for some important 

inputs. Perhaps the most important input is the cost for making up the octane loss that occurs 

with desulfurization. In addition, certain refinery operations information from the LP refinery 

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

model, including the utilization factors of individual refinery units, and the percentage that 

straight run naphtha, FCC naphtha and hydrocrackate comprises of the feed volume of their 

respective units. 

 LP refinery models are detailed mathematical representations of refineries. They are 

used by individual refining companies to project how best to operate their refineries. They are 

also used by government agencies, such as EPA and DOE, as well as by refining industry 

associations and individual companies, to estimate the cost and supply impacts of fuel quality 

changes. LP refinery models have been used for these purposes for decades and a certain 

protocol has been established to conduct these studies. 

Refinery modeling output from the Haverly GRTMPS refinery model was used in the 

refinery-by-refinery cost analysis. The primary reason for using recent LP refinery modeling 

analysis was to estimate the cost of making up the octane loss associated with desulfurization as 

well as estimate how gasoline qualities would be affected by the octane recovery to feed into the 

emissions inventory impact analysis discussed in Chapter 7. The cost of octane has decreased 

due to expected increased use of ethanol under the RFS2 rulemaking, making historical octane 

cost data of limited usefulness. 

The first step in conducting an LP refinery modeling analysis was the development of a 

base case. The base case is a refinery modeling case that calibrates the refinery model based on 

actual refinery unit capacity and input and output data. The base year for this study was the year 

2004 for the Haverly model. Because much of the information available for establishing the base 

case is only available for PADDs of refineries, the LP refinery modeling was conducted on a 

PADD-wide basis. Refinery capacity information for 2012 from the Energy Information 

Administration (EIA) was aggregated by PADD and entered into the LP refinery model. The 

feedstock volumes, including crude oil and gasoline blendstocks, were obtained from the EIA 

and entered into each PADD’s model. Similarly, product volumes such as gasoline, jet fuel, and 

diesel fuel were obtained from EIA and entered into the cost model. The environmental and 

ASTM fuel quality constraints in effect in the base year were imposed on the products. This 

includes the Reformulated Gasoline program and the 500-ppm highway diesel fuel sulfur 

standard, and the first year of the Tier 2 gasoline sulfur standard. This information was input 

into the LP refinery cost model for each PADD and each PADD model was run to model the 

U.S. refinery industry for the base year. The gasoline quality for each PADD refinery model was 

then compared to the actual gasoline quality for conventional and reformulated gasoline which is 
5-7

available from the RFG database. Each model was calibrated to closely approximate the 

gasoline quality of each PADD. 

The second step in modeling is the development of a reference case. The purpose of the 

reference case is to model the refining industry operations and cost in a future year, which is the 

year that the control program is modeled to be in effect (serving as a point of reference to the 

control cases for estimating costs and other impacts). The reference years for the Haverly 

refinery modeling were 2018 and 2030 for the control cases that we ran. The reference cases 

were created by starting with the base case for each PADD and adjusting each base case to 

model the future year, accounting for the changes between the two years. 

Two different types of adjustments were made to the base case refinery models to enable 

modeling the refining industry for the reference case. First, the refinery model needed to reflect 

future product volumes and energy prices which are projected year-by-year by EIA in its Annual 

Energy Outlook (AEO). For the 2018 and 2030 Haverly LP refinery modeling cases, we relied 

on the early release of the AEO 2013 (the later actual AEO 2013 was not yet available). The 

projected U.S. refinery production was entered into the reference case version of the LP refinery 

model. The utility and crude oil and other feedstock prices which are projected by EIA for 2018 

and 2030 were also entered into the refinery model, as well as the estimated product prices which 

were based on the forecasted product prices. 

The second adjustment made to model the reference cases was the application of fuel 

quality changes. Environmental programs which have been implemented or which will largely 

be implemented by the time that the prospective fuels control program would take effect were 

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

average gasoline sulfur standard, 15-ppm caps on highway and nonroad diesel fuel and the 

MSAT2 benzene control program, in addition to the environmental programs which were already 

being modeled in the base case. This also included the fact that California gasoline was already 

averaging 10 ppm sulfur or less as a result of prior changes to their predictive model used for 

gasoline certification, well in advance of their 20 ppm cap on gasoline sulfur taking effect. As a 

result, our Tier 3 gasoline standards are not proposed to apply in California. Thus, for this 

analysis we only assumed further sulfur control on gasoline volumes produced by California 

refineries for distribution outside of California. Also, the implementation of EPAct included a de 

facto ban on MTBE by rescinding the RFG oxygenate requirement. The RFS2 renewable fuels 

volumes were modeled for 2030 based on the projections made by the Energy Information 

Administration (EIA) in its 2013 early release of the Annual Energy Outlook (AEO). For the 

2030 reference case, we modeled 14.4billion gallons of corn and cellulosic ethanol, and 8.3 

billion gallons of renewable diesel and biodiesel. As discussed below, for the 2018 case, which 

was used for modeling octane costs, we modeled all gasoline containing 10 volume percent 

ethanol and a small volume of E85. 

The third step in conducting the LP refinery modeling was to run the control cases. The 

control cases are created by applying a specific fuel control standard to each PADD reference 

case. To single out a specific cost or other impact, the sole difference between the control case 

and the reference case is the parameter change being studied. 
5-8

One control case was run to model the octane loss associated with desulfurizing gasoline 

using 2018 as the year of analysis. Since we solely wanted to identify the cost of recovering lost 

octane for the refinery-by-refinery modeling, this case was run by reducing the octane value of 

the FCC naphtha by one octane number, and this was the sole change relative to the reference 

case. The control case was run with capital costs evaluated at a 15 percent rate of return on 

investment (ROI) after taxes.B This case was run with E10 and a small volume of E85, and we 

substituted 2013 natural gas liquid prices (ethane, propane and butane) which are much lower 

compared to the historical price relationship from previous years. The lower natural gas prices 

increases the octane cost provided by the reformer since the reformer produces natural gas 

liquids as byproducts. The octane cost estimated by the LP cost model is $0.31/octane numberbarrel (0.74 c/octane number-gallon) as summarized in Table 5-39 in the appendix and the 

related tables numbered 5-41 through 5-49. Because the octane loss associated with a specific 

sulfur control technology may be lower or higher than 1 octane number, we scaled the octane 

cost based on the relative estimated octane loss on the FCC naphtha (i.e., a 1⁄2 octane loss of the 

FCC naphtha was estimated to cost $0.155/octane number-barrel. 

The oil industry and one of the peer reviewers commented that we should use the 

wholesale price difference between premium and regular gasoline grades to develop an octane 

cost. Using this method, they estimated that the cost of octane would be $1/octane numberbarrel. We believe that the premium minus regular grade pricing method for estimating octane 

cost overstates the cost of making up lost octane in the FCC naphtha pool. Premium grade 

gasoline is produced in smaller batches than regular grade and must be handled specially and 

separately to avoid compromising its octane content. For example, when shipping premium 

gasoline in pipelines, the interface between premium and regular grades of gasoline must be 

downgraded into the regular grade gasoline to ensure that premium gasoline’s high octane 

content is not compromised – this downgrading increases the production cost of premium 

gasoline. Furthermore, the pricing between regular and premium grades of gasoline tends to 

reflect higher profit margins on premium fuel. 

However, it was further analysis of our LP refinery modeling work which provided the 

most significant reason why the price differentials between premium and regular grade gasoline 

overstates the cost of octane when the octane loss is in fact occurring in the FCC naphtha. While 

the octane cost for making up octane loss in the FCC naphtha is $31/octane number-barrel from 

the LP model, the octane cost determined by the premium-regular grade differential using the LP 

model is $0.50/octane number-barrel, which is 60 percent higher (see Table 5-40). We believe 

that the LP refinery model is estimating a higher octane cost for the premium-regular grade 

differential because of the cost of producing premium gasoline, which is 6 octane numbers 

higher than the regular grade. And yet, the LP model is not capturing the additional cost 

inflating factors mentioned above such as smaller tankage, special handling and distribution and 

profit. Our conclusion from this analysis is that the premium-regular grade price differential is a 

poor indicator of the cost of making up the small amount of lost octane in FCC naphtha for 

 

B

 Normally we conduct the refinery modeling assuming an after-tax 15% ROI and adjust the costs to reflect a 

before-tax 7% ROI to report the costs. However, in this case because the new capital investments were so minimal, 

we omitted the capital cost amortization adjustment because its effect on costs was judged to be negligible. 
5-9

desulfurization and by using it would overstate the cost. Despite our confidence in the octane 

cost that we generated, we recognize the need to quantify the impacts on our costs if octane costs 

are indeed higher than what we estimated, so in Section 5.2 where we present the Tier 3 fuel 

cost, we provide a sensitivity cost estimate assuming that octane costs are $0.50/octane numberbarrel. A table in an appendix at the end of this chapter summarizes the data output from the 

refinery modeling from which we calculated the octane cost for use in the refinery-by refinery 

cost model. Other output from the LP refinery modeling are also summarized in tables contained 

in the appendix. 

Another peer reviewer also evaluated octane cost and concluded that while recent octane 

costs using premium minus regular grade price differences were in the $1/octane number barrel 

range, modeled future octane costs for 2015 and 2020 were appreciably lower. This peer 

reviewer’s estimate for future octane costs could be much lower and provided a range of $0.25 - 

$0.5/octane number-barrel. The octane cost that we are using is right in the middle of the 

projected octane cost projected by this peer reviewer and our octane cost sensitivity is at the high 

end of this range. 

We also conducted LP refinery modeling to estimate how the addition of ethanol affects 

gasoline quality which allowed us to establish a reference case for our air quality analysis. This 

refinery modeling is described, and the resultant projected changes in gasoline quality are 

summarized, in Chapter 7 in subsection 7.1.3. 

5.1.3 Summary of Refinery-by-Refinery Model Methodology 

The purpose of the refinery-by-refinery cost model is to project how each refinery would 

reduce the sulfur in its gasoline pool to 10 ppm or lower and to estimate the cost for doing so. 

To do this we created a U.S. refining industry refinery-by-refinery spreadsheet cost model using 

refinery-specific unit operations information. This spreadsheet cost model also allowed us to 

model how costs would be affected by the ABT provisions. 

The building of the refinery-by-refinery model consisted of two major steps. The first 

step was to estimate baseline operating conditions for each refinery. This involves estimating the 

volumes and sulfur levels of the gasoline blendstocks that comprise each refinery’s gasoline. We 

chose to use information from 2010 and 2011 for modeling the baseline operating conditions for 

the refineries as it was the latest years for which we had data for refiner operations and yields. 

Additionally, EIA projections indicated that gasoline demand is expected to be essentially flat 

between 2011 and when the Tier 3 sulfur control program takes effect, alleviating the need to 

adjust refinery operating throughputs and yields for future changes in gasoline demand.6 As a 

final adjustment to our estimated gasoline volumes and sulfur levels, we calibrated the model to 

actual refinery gasoline volume and sulfur levels to ensure our model’s accuracy. 

A critical step in characterizing refinery operations was to estimate the FCC naphtha 

volume, the sulfur level of the FCC naphtha, and the amount of sulfur reduction needed in FCC 

naphtha to meet a 10-ppm sulfur standard at each refinery. We also incorporated in our refineryby-refinery model the impacts that FCC pretreaters have on FCC naphtha yields and sulfur 

levels, as well as the impact of refinery-specific crude oil sulfur levels on FCC naphtha yields. 

Similarly, we also used the refinery-by-refinery cost model to estimate the volume levels of light 
5-10

straight run naphtha (LSR) and natural gas liquids (NGL) that may require additional 

hydrotreating. 

The second step involved applying the various sulfur control technologies to each 

refinery as necessary to meet the 10-ppm sulfur standard. We expect that the majority of the 

sulfur reductions necessary to comply with a 10-ppm gasoline sulfur standard will come from 

reducing the sulfur level in their FCC naphtha. We first identified the sulfur control technology 

used by refiners at each refinery for complying with Tier 2. We then obtained information from 

vendors of FCC naphtha desulfurizing equipment for revamping or adding new capital as the 

basis for complying with additional gasoline sulfur control. Furthermore, we used our refineryby-refinery model to estimate the extent that refiners will need to add additional LSR/NGL 

hydrotreating capacity at their refineries. 

This allowed us to generate a cost estimate for the sulfur control technology in each 

refinery. The capital costs for installing the sulfur control technologies in each refinery were 

evaluated based on a before-tax, 7 percent return on investment (ROI). In the following sections, 

we present the various steps that were used in this refinery-by-refinery modeling analysis. 

5.1.3.1 Estimating Individual Refinery Gasoline Blendstock Volumes 

To effectively model sulfur control costs for each refinery in our refinery-by-refinery cost 

model, it was necessary to understand the sulfur levels and volumes of the various blendstocks 

which make up each refinery’s gasoline. Each refinery blends up its gasoline pool from the 

various gasoline blendstocks that are produced from the refinery units installed at each refinery. 

However, information on the volumes and sulfur levels of each gasoline blendstock produced by 

each refinery is not publicly available, so it was necessary to seek other sources of information. 

Fortunately, instead of solely relying on refinery unit capacity data to estimate unit operations, 

we were able to obtain individual refinery unit throughput volumes for most of the refinery units. 

From the Energy Information Administration (EIA), we obtained actual year 2011 refinery 

specific throughput volumes for the crude, FCC, cokers and hydrocracking units. For other 

refinery units, including the alkylation unit, reformer isomerization unit and naphtha 

hydrotreater, we obtained throughput data from the Office of Air Quality and Standards 

(OAQPS). We used this information to estimate the extent that each refinery process unit is 

utilized, followed by a unit-specific analysis for estimating how the respective refinery unit 

produces material for blending into gasoline. After the unit-by-unit estimates were completed, 

we performed a check for each refinery by comparing our estimated gasoline volumes with 

reported gasoline volumes for each refinery, using refinery gasoline production volumes that 

refiners report to EPA and made further appropriate adjustments to our refinery-by-refinery 

model. 

5.1.3.1.1 Principal Refinery Unit Throughput Volumes 

To estimate the production volumes for each of the refinery’s gasoline blendstocks, we 

obtained average unit throughput volumes from EIA and from the Office of Air Quality Planning 

and Standards (OAQPS), a sister office at the EPA. With this information, the refinery-byrefinery model effectively models each refinery’s gasoline blendstock yields. Our use of this 

information significantly improved our model’s ability to estimate FCC naphtha, as well as other 
5-11

gasoline blendstocks that each refinery makes. The FCC, coker and hydrocracker unit 

throughputs versus actual capacity (capacity utilization) that we obtained from EIA for each 

domestic refinery are aggregated and presented on a PADD-average basis in Table 5-2. We also 

present the actual throughput volume aggregated by PADD in Table 5-3. This data is presented 

on a PADD-average basis to protect refinery confidential business information (CBI). 

Table 5-2 Process Capacity Utilizationa 

Crude 

Throughput

FCC 

Throughput

Coker 

Throughput

Hydrocracker 

Throughput

Total U.S. 0.827 0.797 0.803 0.827

PADD 1b0.722 0.750 0.474 0.434

PADD 2 0.840 0.763 0.838 0.782

PADD 3 0.847 0.821 0.813 0.860

PADDs 4/5 

excluding California

0.762 0.777 0.739 0.774

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

Table 5-3 2011 EIA Refinery Unit Throughputs (1,000 BPSD) 

Crude FCC Units Coker Hydrocracker

PADD 1 906 419 <3 a<3 a

PADD 2 3,427 998 512 239

PADD 3 7,893 2,572 1,326 985

PADDs 4/5 excluding 

California

1,362 282 124 99

a

 Since there are less than three refiners in this PADD with these units, the data was not reported to protect 

CBI information. 

In the model, we also adjusted the refinery capacity information to account for refinery 

expansions or refinery shutdowns that we were aware of and are scheduled to occur over the next 

several years. Refinery expansions include those announced for WRB Refinery in Wood River 

Illinois Motiva in Port Arthur, TX, Valero in Port Arthur, TX, Tesoro in Mandan, ND, Holly 

Frontier in Woods Cross, UT and BP in Whiting, IN. For these expansions, there is limited 

public data on which of the specific process unit capacities would be increased, though each 

expansion project has information on the crude unit capacity increase. Since the data was 

limited, we increased all of the existing individual process unit capacities by the fractional 

increase in crude oil unit capacity at each of the expanding refineries. Refineries that we believe 

are permanently shutdown in PADD 1 were removed from our analysis but, consistent with 

recent import/export trends, PADD 3 refineries or European gasoline likely would supply any 

lost capacity to PADD 1 as a result of this lost production. PADD 1 refineries that were 

presumed to be permanently shutdown are; Giant refinery located in Yorktown, Virginia, the 

Sunoco refineries in Westville, New Jersey, the Sunoco refinery in Markus Hook (was part of the 

Philadelphia complex), and the Hovensa refinery on St. Croix of the Virgin Islands 

The next step was to calculate actual unit throughput rates for the other refinery processes 

that produce gasoline blendstocks. These units include alkylation, dimerization, polymerization, 

isomerization, naphtha reforming. All of the feedstocks for these processes are primarily 
5-12

supplied by the crude and FCC Units. We used OAQPS throughput data for Alkylation and 

Isomerization units, while Poly/Dimersol units were assumed to run at full capacity. 

Additionally, there were seven refiners that did not have alkylation throughput charge rates in the 

OAPQS data. Since it is likely that refiners are using the alkylation units at these refineries, in 

response to peer reviewer comments, we assumed that the alkylation units were being used at the 

same utilization rate as the FCC unit at those refineries. Since the throughput data for alkylation 

units is for the production volume, alkylate volume was the same as the throughput volume. The 

results of the capacity utilizations of these downstream units are aggregated summarized on a 

PADD-average basis in Table 5-4. 

Table 5-4 Other Unit Process Capacity Utilizationa  

Reformer 

Throughput

Alkylation 

Throughput

Isomerization 

Throughput

Poly/Dimersol 

Throughput

PADD 1 0.499 0.597 0.960 1.000

PADD 2 0.580 0.727 0.651 1.000

PADD 3 0.599 0.800 0.443 1.000

PADDs 4/5 

excluding 

California

0.609 0.691 0.730 1.000

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

With these inputs the refinery-by-refinery model now contained estimates of the 

feedstock charge rates for all of the gasoline blendstock producing units. However, for some 

units, estimating refinery unit capacity and capacity utilization may does not translate directly 

into the gasoline blendstock volume produced by a specific refinery unit. This is because some 

refinery units may also produce products other than gasoline blendstock. Additionally, some 

processes have volume loss of feedstock due to process reactions and conversions that take place 

that increase or decrease the density and therefore the volume of products. To take this into 

account, a gasoline fraction yield factor has to be applied for some of the processes to convert the 

process charge rate into the yield of gasoline blendstocks. The crude, the FCC, the coker and 

hydrocracker units all produce some naphtha from its feed, and we needed to estimate the 

naphtha volume. We will discuss how we estimated the FCC naphtha here separate from the 

other units because the FCC naphtha is usually kept separate from the other naphtha streams 

until it is blended into the gasoline pool. We will discuss the contribution of the crude, coker and 

hydrocracker units to naphtha when we present how we estimate light naphtha and heavy 

naphtha volume below. 

5.1.3.1.2 FCC Naphtha Volume 

The FCC unit produces significant volumes of naphtha, a gasoline blendstock. The 

conversion percentage to naphtha is affected by the severity of the operation of the FCC unit. As 

shown in Table 5-5, an initial estimate was made for the portion of FCC feedstock converted to 

naphtha. This initial estimate ranged from 53 to 57 percent depending on the PADD and was 

estimated based on a year 2018 refinery modeling run output using the Haverly LP refinery 

model. 
5-13

Table 5-5 FCC Naphtha Fraction of Feed 

FCC Units Average

PADD 1 0.543

PADD 2 0.574

PADD 3 0.572

PADDs 4/5 excluding California 0.535

While having an initial estimate is useful, the range among individual refineries can be 

quite large, but we didn’t have access to refinery-specific data for this. However, we were able 

to take steps to use the data that we did have access to better estimate each refinery’s FCC 

naphtha production. There is expected to be differences in FCC naphtha production between 

refineries with and without FCC pretreaters. Thus, as the first step we took to better estimate 

FCC naphtha production from each refinery’s FCC unit, we l differentiated between refineries 

that have an FCC feedstock pretreater and those that do not. We also quantified the gasoline 

blendstock fraction yield for FCC units that have both feed pretreater and postreater units. Per 

comments from the peer review of our model, we limited the amount of FCC feedstock that 

could be pretreated at a few refineries that did not have enough capacity to pretreat all of their 

FCC feedstock. Historically, refiners have installed FCC feed pretreaters for economic reasons, 

as pretreaters increase FCC unit conversion to a high value gasoline blendstock while decreasing 

the production of low value light cycle oil and residual material. FCC feed pretreaters also have 

the benefit of reducing sulfur from the FCC feedstocks, resulting in the production of lower 

sulfur FCC naphtha and ultimately lower sulfur gasoline. In developing our refinery-by-refinery 

model, we quantified the impact that FCC feed pretreating and postreating has on FCC naphtha 

yields and sulfur levels based on our evaluation of information we received from technology 

vendors. The results of this analysis are shown in Table 5-6. 

Table 5-6 FCC Unit Gasoline Blendstock Fraction Yields 

Average of All 

FCC Units

FCC Units with 

No Pretreater

FCC Units with a 

Pretreater Only

FCC Units with a 

Pretreater and 

Postreater

PADD 1 0.543 0.532 NA 0.588

PADD 2 0.574 0.547 0.650 0.605

PADD 3 0.572 0.551 0.650 0.608

PADD 4/5 excluding 

California

0.535 0.523 0.608 0.574

The volume of FCC naphtha is affected in other ways by how refiners operate their 

refineries. One way that FCC naphtha volume is affected is if they choose to produce increased 

volumes of propylene.7 8 9 10 Propylene is a valuable feedstock chemical used for the production 

of polypropylene. All FCC units produce some propylene, however, if refiners opt to use a 

particular catalyst additive called ZSM-5, the FCC unit cracks even more heavier hydrocarbons 

(primarily C6 and C7 hydrocarbons) to light olefins and more propylene is produced. The extent 

that more olefins are produced depends on the amount of ZSM-5 which is added to the FCC unit. 

We obtained refinery-specific data from EIA for the volume of propylene sales by each refinery. 

We compared the propylene sales data to the volume of propylene expected to be produced by 
5-14

FCC units which do not use the ZSM-5 catalyst, and if the propylene sales volume exceeded the 

expected propylene production volume, we assumed that ZSM-5 catalyst is being used. The 

reason why this is important is that as the propylene production increases, the volume of FCC 

naphtha decreases, which lowers the fuel volume needing to be desulfurized. It also reduces the 

severity of desulfurization because FCC naphtha comprises a smaller percentage of the gasoline 

pool and the FCC naphtha would not need to be desulfurized to as low a level to meet the same 

gasoline sulfur target. 

The two critical criteria for implementing this propylene-related adjustment to FCC 

naphtha volume are the point at which higher propylene production fractions of the FCC naphtha 

indicates the use of ZSM-5, and the rate at which FCC naphtha production volume decreases 

relative to the rate that propylene production volume increases. For the former criterion, we used 

the recommendation made by a peer reviewer, who consulted refiners on the use of ZSM-5. The 

peer reviewer recommended that we use 8.5 percent as the point at which the propylene 

production indicated the use of ZSM-5 catalyst.11 Thus, when propylene sales by a refinery 

exceed 8.5 percent of the FCC naphtha volume, we apply an adjustment to lower the FCC 

naphtha volume. For the second criterion which estimates how much to adjust the FCC naphtha 

volume as propylene production exceeds 8.5 percent, we used information from the Jacobs data 

base which models the use of a ZSM-5 catalyst. The Jacobs database estimates that for every 1 

percent increase in propylene volume above 8.5 percent, there is a reduction of 1.4 percent in 

FCC naphtha. After implementing this adjustment, the production volume of FCC naphtha was 

reduced in 22 refineries from a range of 0 to 10 percent, and the volume weighted average was 

2.9 percent. 

Another way that refiner decisions impact FCC naphtha volume is if the refiner elects to 

undercut its FCC naphtha to the light cycle oil (diesel fuel) pool in response to relatively higher 

demand for diesel fuel. Diesel fuel demand is increasing in the US and US refiners are also 

exporting more diesel fuel. At the same time gasoline demand is decreasing in the US and US 

refiners tend not to export as much gasoline. This trend is expected to continue in the future 

based on Energy Information Administration’s (EIA’s) projections in its Annual Energy 

Outlook. Table 5-7 summarizes both the historical and projected demand in petroleum and 

renewable fuels. 
5-15

Table 5-7 Historical and Projected US Petroleum and Renewable Fuels Demand 

(billion gallons) 

2009 2012 2018 2030

Total Gasoline 132.8 134.6 130.9 112.5

Total Diesel 53.9 57.8 66.6 68.7

Total Jet 20.2 21.1 22.9 24.5

Ethanol 11 13 16 22

Biodiesel/Renewable 

Diesel 0.3 1 3.84 8.34

Refinery Gasoline 121.8 121.6 114.9 90.5

Refinery Distillate

(Jet + Diesel) 73.8 77.9 85.7 84.9

Distillate/Gasoline

Ratio 0.606 0.641 0.746 0.938

Table 5-7 summarizes historical and future total demand for gasoline, diesel and jet fuel 

including renewable fuels and that which refiners produce after renewable fuels are subtracted 

out (refineries don’t produce these fuels). Refinery gasoline production was essentially flat from 

2009 to 2012, but after 2012, it is expected to decline. Conversely, refinery distillate production 

has been increasing and it is expected to increase further in the future. Thus, the changing 

refinery production profile, when expressed as a ratio of distillate production (jet and diesel fuel) 

to gasoline production, is expected to increase from 0.61 to 0.94 during the period from 2009 to 

2030. As a point of comparison, Europe demands much more diesel fuel than gasoline, and its 

ratio of distillate to gasoline demand is currently over 2.0. 

If this trend towards lower relative gasoline demand continues, refiners will continue to 

change how they refine crude oil into gasoline and diesel fuel. One way that refiners are 

expected to respond to this trend is by undercutting the FCC naphtha to the diesel fuel pool. The 

refinery unit information that we obtained from OAQPS has allowed us to better calibrate our 

model to how refiners are operating their refineries. Despite the improved modeling of US 

refineries, we frequently found that refinery gasoline production exceeded their actual gasoline 

production volume as reported to EPA. One refiner which operates multiple refineries shared 

with us that they use FCC naphtha undercutting as a means to rebalance its gasoline and diesel 

fuel production volumes. One vendor of FCC naphtha desulfurization shared with us that 

refiners are indeed undercutting FCC naphtha into diesel fuel at many refineries, particularly in 

the wintertime. Finally, the peer reviewers shared that undercutting FCC naphtha to diesel fuel 

is a commonly used practice by refiners. As a verification that undercutting of FCC naphtha is 

occurring, we compared the T90 value of US gasoline produced in 2011 versus 2004. We found 

that the volume-weighted average T90 of US gasoline was 323F in 2011 compared to 333F in 

2004. Thus, the gasoline pool is getting lighter which supports our premise that undercutting of 

FCC naphtha is occurring. Therefore, we used undercutting of FCC naphtha in our refinery-byrefinery model as a means to help balance the modeled gasoline volume with actual gasoline 

volume. The practice of undercutting is important because if the FCC naphtha swingcut is fully 

cut into the diesel fuel pool, an estimated 16% of FCC naphtha volume, and more importantly, 

half of the FCC naphtha sulfur would be shifted to the diesel fuel pool.12 13 It is important to 

note that we do not project that this is a strategy that refiners will adopt for complying with Tier 
5-16

3, but instead refiners will pursue undercutting FCC naphtha as a means to improve its day-today refinery margins independent of Tier 3. 

We used output from the LP refinery model to guide us in assumptions for undercutting 

the heavy gasoline streams in the refinery-by-refinery model. The LP refinery model estimates 

that US refineries undercut the heavy naphtha (heavy naphtha is the feedstock for the reformer) 

swingcut by 84% in 2009 and projects that 100% will be undercut in 2018. Conversely, the LP 

model estimates that refineries undercut 22% of the FCC naphtha swingcut in 2009 and will 

undercut 68% of the FCC naphtha swingcut in 2018. This information from our LP model 

suggests that the economics favor undercutting the heavy naphtha to jet fuel over undercutting 

FCC naphtha to diesel fuel. For this reason, we chose to undercut the heavy naphtha to jet as a 

first step to match the model’s gasoline production volumes with actual gasoline volumes (to the 

extent that reformer throughput volume allows it) before we resorted to undercutting FCC 

naphtha. After applying FCC naphtha undercutting to further balance the gasoline volume in the 

refinery-by-refinery model, we ended up undercutting 34% of the FCC naphtha swingcut to 

diesel fuel. There is general agreement between the LP refinery model and our refinery-byrefinery model since the undercutting in the refinery-by-refinery model is in the range of 22% to 

68% undercutting which represents the undercutting between 2009 and 2018. While the LP 

model projects that refiners will be undercutting a larger portion of the FCC naphtha to diesel 

fuel in the future, we did not attempt to account for any cost reduction associated with further 

undercutting of FCC naphtha to diesel fuel, so we are likely being conservative with this aspect 

of our cost analysis. We present a sensitivity case for the potential savings due to full 

undercutting of the FCC naphtha in subsection 5.2.

5.1.3.1.3 Poly Gas and Alkylate 

For the polymerization and alkylation units the throughput volume from the OAQPS data 

base was used for these units for each refinery. Since this volume represents the output from 

these units, no adjustments to the volumes were necessary 

5.1.3.1.4 Heavy Naphtha and Reformate 

A series of steps were taken in the refinery-by-refinery model to effectively estimate the 

volume of heavy naphtha which, for the most part, serves as the feed to the reformer. The heavy 

naphtha volume was estimated from the volume of three components of heavy naphtha, 

including heavy straight run naphtha, heavy coker naphtha, and heavy hydrocrackate. The feed 

to the reformer was based on OAQPS throughput data, which often did not match the heavy 

naphtha volume. With the use of actual unit throughput volume, it removed a lot of uncertainty 

about how refiners are actually operating their reformers. Having good estimates of both the 

volume of heavy naphtha and feed to the reformer allowed us to better estimate the total volume 

of heavy naphtha sent to the reformer and volume of heavy naphtha which is likely blended 

straight to gasoline, instead of being sent to the reformer, or undercut to the jet and kerosene 

pool. An additional step was added to estimate the fate of benzene precursors based on refiners’ 

actions they took to comply with the Mobile Source Air Toxics (MSAT2) 0.62 volume percent 

benzene standard. The aggregated summary of refinery action on MSAT2 (we used refinery 

specific information which is confidential business information) can be found in a report entitled 
5-17

Summary and Analysis of the 2011 Gasoline Benzene Pre-Compliance Reports on EPA’s 

webpage (www.epa.gov/otaq/regs/toxics). 

Heavy straight run naphtha comes from the distillation of crude oil in the atmospheric 

crude oil tower. The heavy straight run naphtha volume was estimated for each refinery by 

applying the results of a regression analysis of API gravity versus heavy straight run naphtha 

volume based on the assays of 13 crude oils. Table 5-8 summarizes the regression equations used 

for each cut of heavy straight run naphtha, and also provides a regression based on the total 

volume of HSR naphtha. 

Table 5-8 Values from Regression Analysis Used to Estimate 

Heavy Straight Run Naphtha Volume 

x- variable Intercept r2

All HSR 0.0090 -0.106 0.88

160/220 0.0031 -0.0448 0.81

220/285 0.0035 -0.0484 0.83

285/350 0.0023 -0.0131 0.85

350/400 0.0014 0.0027 0.75

Based on a regression of crude quality (API gravity) versus crude assays, we were able to 

estimate the fraction of crude oil that is heavy straight run. The volume of heavy straight run 

naphtha ranges from about 7 to 36 percent of the crude oil input depending on crude oil quality 

processed by the refinery, and whether or not the refinery may be undercutting the heaviest part 

of this stream into the jet or diesel fuel pool. To demonstrate the results of the regression 

analysis, the volume of the various portions of heavy straight run naphtha are estimated for two 

different API gravities representing two hypothetical crude oils in Table 5-9. The two API 

gravities chosen to represent light and heavy crude oils were 20 and 35, respectively. 
5-18

Table 5-9 Estimated heavy straight run naphtha volume cuts at two API Gravities 

API Gravity

Crude Oil fraction for 

specific distillation 

cuts (Temperature F)

20 35

160/220 0.017 0.064

220/285 0.023 0.076

285/350 0.033 0.068

350/400 0.031 0.052

The information in Table 5-9 shows that lighter crude oils (API gravity 35) contain a 

larger amount of heavy naphtha than heavier crude oils. An important reason why we chose to 

conduct our regression analysis for separate heavy naphtha cutpoints was to capture how, as the 

API gravity changes, the fraction of each heavy naphtha cutpoint varies. For example, the 

350/400 swingcut cutpoint comprises about 30% of the heavy naphtha volume for the 20 API 

crude oil, but only 20% of the of the heavy naphtha volume for the 35 API crude oil. 

The volume of heavy coker naphtha was estimated based on fractions of coker unit feed 

from information in the Jacobs data base that we use with the Haverly refinery cost model. For 

the 160/220, 220/350 and 350/400 distillation cuts, the fractions of coker feed are 0.022, 0.097

and 0.033, respectively. While cokers can produce somewhat lower and higher amounts of 

naphtha depending on how the coker units are being operated, we believe that these fractions are 

about average. Because the feed volumes to the cokers are actual throughput volumes from EIA 

data, the volume of coker naphtha that we estimate at each refinery is likely to be reasonably 

accurate. 

The volume of heavy hydrocrackate was also estimated based on information in the 

Jacobs data base as well as from a peer reviewer, depending on feedstock type. We estimated 

different production profiles depending on the feed type. Standalone hydrocrackers which 

process gas oil are very flexible units capable of producing a range of gasoline and diesel fuel 

production volumes. We incorporated the range of gasoline production volumes in our refineryby-refinery model to represent this flexibility. One important reason why we included this range 

of gasoline production volume is to help balance the gasoline volume produced at each refinery. 

Our refinery-by-refinery model estimates lower and higher gasoline volumes than actual gasoline 
5-19

production, and differences in hydrocracker naphtha production volumes, based on how 

hydrocrackers are operated, is likely one reason why our model is not matching actual refinery 

gasoline production volume. We also model the heavy naphtha production volume when 

hydrocrackers are used to process residual fuel. When processing residual fuel, the naphtha 

production profile is more predictable for residual fuel hydrocrackers and the conversion to 

naphtha tends to be much lower. The last type of hydrocracker that we modeled is an FCC feed 

hydrotreater which is converted over to a mild hydrocracker. This may increasingly be an 

approach used by refiners to increase their distillate to gasoline ratio. In doing so, it would also 

aid Tier 3 sulfur control. However, since we had no data with which to estimate which refiners 

might convert their FCC feed hydrotreaters to mild hydrocrackers, we did not assume this in our 

cost analysis, but only show the potential impact in a sensitivity analysis discussed in section 5.2. 

The fraction of feed to the hydrocracker which is produced as heavy naphtha is summarized in 

the Table 5-10 for each type of hydrocracker that we modeled. 

Table 5-10 Summary of Heavy Naphtha Production by Hydrocracker Type and Operating 

Mode 

Hydrocracking of Gas Oil – Operating Modes Resid Gas Oil

Naphtha cut 

(F)

Naphtha Middle Diesel FCC Feed HT 

to Mild 

Hydrocracker

49/200* 0.42 0.23 0.06 0.03 0.02

200/285 0.21 0.15 0.08 0.04 0.03

285/400 0.16 0.23 0.17 0.09 0.07

* The naphtha cutpoint data for hydrocrackers included the light hydrocrackate cut (49/160) along with the light 

portion of the heavy naphtha cut. 

The heavy naphtha distillation cutpoints were sometimes different depending on the 

source of the heavy naphtha. For example, the heaviest naphtha cut for the hydrocracker is 

285/400, while the heaviest naphtha cut for the heavy straight run naphtha is 350/400. It was 

necessary to create a consistent set of cutpoints before we could combine the various streams 

from different units, so we normalized the cutpoints to create four distinct heavy naphtha 

volumes. The cutpoints for the heavy naphtha volumes are 160/200, 200/285, 285/340 and 

340/400. The cutpoints were either adopted from the Jacobs data base, or specified to satisfy a 

certain need. The benzene precursor fraction was established as 160/200, (changed from 

160/180 used in the NPRM) based on benzene precursor boiling point information provided by a 

peer reviewer. The swingcut was established as 340/400 (changed from 350/400 used in the 

NPRM) to capture the ability for jet fuel or kerosene to accommodate the lighter blendstocks and 

still meet the flashpoint specifications. In cases when a heavy naphtha cutpoint provided does 
5-20

not match the cutpoints we are using, we adjusted the volume using a simple reapportionment 

based on the temperature range that the cutpoint represents. Using the heaviest naphtha cut 

produced by the hydrocracker as an example, to convert 285/400 to 285/340 and 340/400, the 

volume was apportioned (340-285)/(400-285), or 48% for the lighter cut, and 52% for the 

heavier portion. 

Refiners must comply with MSAT2 benzene standard which requires refiners to reduce 

their gasoline to an average of 0.62 volume percent benzene. How refiners comply with MSAT2 

determines the fate of the 160/200 heavy naphtha volume. Depending on what happens with the 

volume, it can affect our estimated refinery gasoline volume. In their compliance report to EPA, 

refiners indicated how that they would comply with MSAT2 benzene standard listing one of 

several possible actions. These actions can be divided into two categories; those who would 

route the benzene precursors to the reformer and those who would not. A second point of 

interest is whether the benzene precursor stream or the benzene-rich reformate stream is blended 

into the refinery’s gasoline pool or not, which makes a difference in terms of matching a 

refinery’s gasoline production volume. Table 5-11 summarizes the refinery options for the 

benzene precursors or the benzene-rich reformate stream. 

Table 5-11 Summary of Refiner Actions for Complying with MSAT2 

Fate of Benzene Precursors Keep in Gasoline Pool Do not Keep in Gasoline Pool

Do not Route to Reformer 1) Send to Isom unit

2) Route around 

Reformer

3) Send to Benzene 

Saturation unit

Send Benzene Precursors to 

another Refinery

Route to Reformer 1) Reform and Extract

2) Benzene Alkylation

Send Benzene-Rich Reformate 

to another Refinery or 

Petrochemical Plant

The options for compliance with MSAT2 are: continue to reform the benzene precursor 

cut and extract the benzene, routing the benzene precursors around the reformer to a benzene 

saturation unit, route the benzene precursors around the reformer to an isomerization unit, and 

finally, exporting the 160/200 substream. In the case of exporting the 160/200 substream, it is 

not clear whether the stream would be exported before or after being reformed. So we used a 

reformer balance, as described below, to estimate whether this stream is reformed or not before 

being exported. Table 5-12 summarizes refiner plans for complying with MSAT2. 
5-21

Table 5-12 Refinery MSAT2 Compliance Plans 

MSAT2 Compliance Plans

Extraction Route 

Around 

Reformer to 

Gasoline

Isomerization Export Benzene 

Saturation

Number of 

Refineries

15 39 16 16 10

The reformate volume is based on throughput volume from data we obtained from 

OAQPS. The reformer throughput volume is the volume of heavy naphtha which is fed to the 

reformer. The OAQPS reformer throughput data shows that on average, US refiners are 

operating their reformers at 69% of capacity, with some reformers operating at full capacity 

while others are shutdown (this usually is one train of multiple reformer trains at larger 

refineries). Consistent with our LP refinery modeling results, refiners are operating their 

reformers at a much lower throughput volume than capacity due to the much increased blending 

of ethanol which is very high in octane. Furthermore, demand for premium gasoline has 

diminished in recent years, which also has reduced the demand from octane-producing units such 

as the reformer. 

The reformer throughput volume usually did not match the heavy naphtha volume that 

we estimated for each refinery, which we expected because throughput volume was so low 

relative to reformer capacity. While there was a very good match between the heavy naphtha 

volume and the reformer throughput for 22 refineries, for the rest of the refineries there was a 

discrepancy. While 13 refineries did not have sufficient heavy naphtha volume to match the 

reformer throughput volume, it was far more common for the heavy naphtha volume to exceed 

reformer throughput volume, even after accounting for refiners’ plans for complying with 

MSAT2. The most likely reason why refiners were not feeding all the heavy naphtha to the 

reformer is because refiners are undercutting the 340/400 heavy naphtha swingcut to the jet pool. 

When the heavy naphtha volume exceeded the reformer throughput volume and our model 

estimated a larger gasoline volume than actual, we assumed that the refinery is undercutting the 

heavy naphtha swingcut to the jet pool. Based on our criteria for undercutting the heavy 

naphtha, our model estimates that about one third of the heavy naphtha swingcut is being 

undercut to the jet pool. If after assuming that the refinery is undercutting the heavy naphtha 

swingcut and the refinery’s heavy naphtha volume still exceeds the reformer throughput volume, 

we assumed that the refinery is routing a portion of the heavy naphtha around the reformer and 

blending it straight to gasoline. Alternatively, we assume that the heavy naphtha stream which is 

not being reformed is being exported from the refinery if the model’s gasoline production is 

exceeding actual gasoline production. 
5-22

The volume of reformate produced by the reformer is not the same as the feed volume to 

the reformer because of the cracking and volume shrinkage which occurs due to the reforming 

reactions. Furthermore, the change in volume that occurs in the reformer is dependent on the 

severity of the reformer. Reformer severity is measured by the research octane number (RON) 

of the reformate, which can vary between 90 to 105. As the severity of the reformer increases, 

the volume of the product reformate decreases as a fraction of the feed. This relationship also 

varies depending on the type of reformer. Table 5-13 summarizes the estimated volume 

shrinkage for different reformers operating at different operating severities. 

Table 5-13 Reformate Production Fraction of Feed for Different Reformer Severities 

Severity Reformer Type and Fraction of Feed Volume that Reformate Volume 

Represents

Semi Regen Cyclic Continuous

90 0.87 0.87 0.895

95 0.845 0.845 0.87

100 0.78 0.78 0.805

The volume of reformate is clearly dependent on the severity that a refiner is operating its 

reformer. Unfortunately, there is no available data on the severity at which refinery reformers 

are operating, so we developed a means to estimate it. Our assumption is that reformer severity 

is dependent on the number of octane increasing units that a refinery has and whether the 

refinery has an aromatics plant. If a refinery has an aromatics plant (refiners would likely want 

to maximize aromatics production if they have an aromatics plant), or if the refinery does not 

have an isomerization unit nor an alkylation plant (if the sole octane producing unit in a refinery 

is a reformer, then the refiner would likely need to operate it at high severity to provide sufficient 

octane), then we assume that a refinery’s reformer is operating at 100 severity. If a refinery has 

either an alkylation plant or an isomerization unit and no aromatics plant, then we assume the 

refinery’s reformer is operating at 95 severity. However, if a refinery has both an alkylation and 

isomerization unit and no aromatics plant, then we assume that the refinery’s reformer is 

operating at 90 severity. Based on our assumptions for estimating reformer severity, the 

reformers at 14 refineries are operating at 90 severity, the reformers at 66 refineries are operating 

at 95 severity, and the reformers at 27 refineries are operating at 100 severity. Once we assigned

a severity to each refinery’s reformer and knowing the type of reformer each refinery has (based 

on information from the Oil and Gas Journal), we determined the fraction that the product 

reformate is of the throughput volume as summarized in Table 5-13. 
5-23

5.1.3.1.5 Light Naphtha 

The light straight run naphtha (LSR), light coker naphtha, light hydrocrackate and 

pentanes plus (natural gas liquids) all are light naphtha streams which are principally comprised 

of five- and six-carbon hydrocarbons which boil in the range from 49 F to 160 F. The LSR 

comes directly from crude oil and the pentanes plus (natural gas liquids or NGL) come from 

natural gas wells, while light coker naphtha and light hydrocrackate come from the coker and 

hydrocracker units, respectively. 

The volume of LSR for each refinery was based on a regression analysis of volume of 

LSR versus API gravity for the crude oil that it processes. Crude oil assays contain crude API 

gravity numbers along with the corresponding LSR yields fraction for the crude oils, which 

enables someone to develop a correlation between crude API and LSR yield. During the peer 

review of our model, one of the peer reviewers provided a regression analysis of the LSR versus 

crude oil API gravity using a large number of crude oil assays. For the final rule we adopted the 

equation recommended by the peer reviewer. The resulting equation is: LSR Yield = 2E-06 X3

– 8E-5X2+ 0.0022X + 0.0001, with X being crude API gravity number. This equation has a 

predictive R2

value of 0.8197 for estimating the percentage of LSR from Crude API gravity. By 

utilizing data obtained from EIA for each refinery’s average annual crude oil API number, we 

were then able to estimate each refiner’s LSR yield fraction. Our regression analysis estimates 

that the percentage of LSR in crude oil varies from 2 and one half percent, for heavy crude oils, 

to over 8 percent for light crude oils. 

The NGL that refiners purchase comes from natural gas wells after it has been separated 

and cleaned up at natural gas processing plants. Refiners report to EIA this volume of NGL that 

they purchase at each refinery and we obtained and entered this data into our refinery-by-refinery 

model and added this volume to the rest of the light naphtha assuming that it all boils in the 

temperature range of 49 F to 160 F. 

The volume of light naphtha produced by the coker unit is estimated based on data from 

the Jacobs data base. That data base estimates that light coker naphtha comprises 2.1 percent of 

the feed volume to the coker unit. While the coker units may produce a somewhat higher or 

lower percentage of light naphtha than what we estimated, we believe that this percentage is 

average for coker units in general. 

The volume of light naphtha from hydrocrackers is estimated based on naphtha 

production estimates for hydrocrackers operating in different modes as described above in 

Section 5.1.3.1.4. In that Section, we present the volume of lightest cut of the heavy naphtha 

produced by hydrocrackers, and that cut also contains the volume of light naphtha. To calculate 

the volume of light naphtha from that cut, we used a simple ratio of the distillation cut points. 

The light naphtha portion of the 49/200 cut is calculated to be (160-49)/(200-49), or 74 percent 

of that volume fraction provided for that cut. 

For modeling purposes, the light naphtha (LSR, light coker naphtha and light 

hydrocrackate) were split into a five carbon stream and a six carbon stream. This split was 

necessary to facilitate matching the RVP of the gasoline produced by the refinery, as described in 

subsection X that discusses matching refinery gasoline volume. These five and six carbon 
5-24

streams have several possible fates in each refinery. If a refinery has an isomerization unit, 

which converts straight chain hydrocarbons to branched chain hydrocarbons for its octane 

benefit, these streams could be fed to that unit. If a refinery does not have an isomerization unit, 

or that unit is capacity limited, the five and six carbon hydrocarbons are blended directly into 

gasoline, unless removing five carbon hydrocarbons is necessary to control RVP. 

The volume of C5 and C6 hydrocarbons fed to a refinery’s isomerization unit was based 

on its throughput volume in 2010 from OAQPS data. To ease the task of balancing RVP, the six 

carbon stream was sent to the isomerization unit first and then the five carbon stream sent to the 

isomerization unit to satisfy the throughput volume. Any leftover volume was blended straight 

to gasoline, unless some 5 carbon hydrocarbons needed to be removed to balance RVP. For the 

isomerization units in 6 refineries, the Oil and Gas Journal specifies that these are only C5 

isomerization units. For these isomerization units, we modeled that these isomerization units 

were solely being fed C5s. The volume of isomerate is estimated to be 98.5 percent of the feed 

to the isomerization unit (there is 1.5 percent volume loss in the isomerization unit). 

5.1.3.1.6 Other Purchased Blendstocks 

Some additional gasoline blendstocks are purchased and blended into the gasoline pool 

and we attempt to account for this. The gasoline blendstocks typically purchased include ethanol 

and butane. Gasoline quality data reported by refiners to us contains the percentage of ethanol 

blended into each refinery’s RFG, but does not contain the amount of ethanol that is blended into 

the conventional gasoline pool at the refinery, and it certainly does not contain the ethanol 

blended into gasoline at terminals. In the 2011 gasoline quality database, the ethanol volumes 

only averaged 3.3 percent of US refinery gasoline production, which would result in an over 

estimation of our refinery and program costs if we did not account for the rest of the ethanol. To 

capture the impact of the blended ethanol, we added ethanol into each refinery’s gasoline pool 

until the total ethanol blended into each refinery’s gasoline reached 10 percent. . 

To estimate the butane volumes in our refinery-by-refinery model we used an RVP 

balance equation. This equation states that the product of the overall RVP and volume of a 

refinery’s annual gasoline pool is equal to the sum of the product of the RVP and volumes of the 

non-butane components plus the product of the RVP and the volume of the butane blendstocks. 

We raised each of the RVP values to an exponent to capture the true impact of hydrocarbon’s 

volatility. The value of the exponent that we used is 1.15 which is the value recommended by 

vendors and consultants. This equation can be rearranged to solve for the volume of butane 

blendstocks as shown in Equation 5-1 below. 
5-25

Equation 5-1 RVP Butane Balance Equation 

Butane =D* (A1.15-B1.15)/(C1.15-A1.15) 

Where: 

Butane = Volume of Butane added in each refinery in BPSD 

A = Blended gasoline RVP average 

B = Non-butane blendstock RVP average 

C = Butane RVP 

D = Volume of gasoline produced 

The gasoline production volumes and RVP of the blended gasoline are reported to EPA 

by refiners for each refinery and were used for the A and D terms in Equation 5-1. For the 

butane stream, our LP refinery modeling shows that this stream is comprised predominantly of 

normal butane. We assumed that only normal butane would be blended into gasoline in our 

refinery modeling analysis. The non-butane blendstock RVP was estimated by multiplying each 

individual gasoline blendstock RVP times the gasoline blendstocks volume fraction of each 

refineries gasoline pool (CG and RFG) using 2011 ethanol volumes and taking the sum of all of 

these values. The RVP value for each of these streams is shown in Table 5-14 below. With this 

information we were then able to estimate the volume of butane added to the gasoline blendstock 

at each refinery. The annual volumes of butane added by refineries on a PADD level are listed 

in Table 5-15. The volume of butane blended into gasoline at each individual refinery varies 

based on the annual average gasoline RVP that the refinery produces (the RVP of CG and RFG 

gasoline are volume weighted together), as well the variance in gasoline blendstock streams that 

a particular refinery uses to produce CG and RFG gasoline. 

Table 5-14 PADD Average RVP’s of Gasoline Blendstocks 

PADD 1 PADD 2 PADD 3 PADD’s 4/5a

LSR 12.0 12.0 12.0 12.0

Heavy Naphtha 3.0 3.0 3.0 3.0

Reformate[update] 4.5 6.6 5.0 6.2

FCC Naphtha 4.6 4.6 4.6 4.6

Isomerate C5 13.0 13.0 13.0 13.0

Isomerate C6 7.2 7.2 7.2 7.2

NGL 12.6 12.6 12.6 12.6

Polymerization Gasoline 2.8 2.8 2.8 2.8

Alkylate, C4 3.2 3.2 3.2 3.2

Dimersol 5.8 5.8 5.8 5.8

Ethanolb13.5 10.713.5 10.713.5 10.713.5

a Excluding California data 

b Ethanol’s RVP was established by taking ethanol’s blending RVP of 20 to the root of 1.15 
5-26

Table 5-15 PADD Average Gasoline Data 

PADD 1 PADD 2 PADD 3 PADD’s 4/5a

Non-butane blendstock RVP (B), psi 6.4 6.3 5.7 6.3

Gasoline Pool Volume (D), BPSD 738.2 1744 3487.8 500.3

Volume Butane Added, BPSD 21.4 95.1 143.1 25.7

Blended Gasoline RVP average (A), psi 9.4 10.38 9.31 10.2

a Excluding California data 

5.1.3.1.7 Calibrating the Blendstock Volumes in the Refinery-ByRefinery Model 

As we discussed earlier, we took steps to balance each refinery’s gasoline production 

volume in the refinery-by-refinery model against actual gasoline volume production volume 

reported by refiners to EPA. We estimated each refinery’s gasoline volume by estimating the 

volume of each gasoline blendstock which comprises gasoline. Because we used individual 

refinery unit throughput volumes to estimate the gasoline blendstock volume for each refinery 

unit, we believe that we employed a robust methodology for estimating gasoline volume. 

However, the modeled gasoline volume for most refineries was higher than their actual gasoline 

volume. Thus, it was necessary to identify and make additional adjustments that would better 

match refiners’ gasoline production. 

We adjusted gasoline volume based on certain inputs and outputs that we identified. EIA 

collects data on natural gas liquid (termed pentanes plus) purchases for each refinery and we 

added the 2011 volume to each refinery. We entered the information of refinery actions for 

complying with the MSAT2 gasoline benzene standard in the refinery model. The MSAT2 

actions which involved exports from the refinery, which included extraction of benzene, or 

exports of benzene precursors or the benzene-rich reformate, and these impact gasoline volume. 

We also adjusted for gasoline exports from Gulf Coast refineries. We did not have refineryspecific data on Gulf Coast exports, so we apportioned the 428 thousand barrel per day exports 

(EIA data) from Gulf Coast refineries by each Gulf Coast refinery’s overproduction of gasoline. 

While the throughput volume fairly well defines the gasoline blendstock volumes for 

most refinery units, we needed to estimate the gasoline blendstock volume for others. 

Hydrocrackers can be operated in different modes that preferentially produce naphtha or 

distillate fuel. While we did not know which mode each refinery operates its hydrocrackers, 

when the modeled gasoline volume for a refinery with a hydrocracker was too high relative to its 

actual gasoline production, we assumed that the refinery was operating its hydrocracker in 

distillate maximization mode. Or, when the modeled gasoline volume for a refinery with a 

hydrocracker was too low, we assumed that the hydrocracker was being operated in naphtha 

mode. We also assumed a middle mode for hydrocrackers when the modeled gasoline volume 

for refinery with a hydrocracker was close to matching its actual gasoline volume. 

Another gasoline blendstock volume which we adjusted was heavy naphtha from the 

atmospheric crude distillation unit, the hydrocracker and the coker that would otherwise be feed 

to the reformer. Refiners have the option of feeding the heaviest portion of this heavy naphtha 
5-27

stream to the reformer or cutting it into the distillate pool. For any refinery, we only cut this 

heaviest portion of the heavy naphtha pool into distillate fuel if the volume of heavy naphtha 

exceeded the reformer throughput volume and the modeled gasoline volume exceeded the actual 

gasoline volume for that refinery. There were times when the heavy naphtha volume was 

insufficient compared to the reformer throughput volume, so we assumed that unfinished oils 

which are purchases that are made by refineries are 

The last refinery’s unit production volume that we adjusted is the FCC unit and we did so 

in several different ways. The production of FCC naphtha from the FCC unit is affected by 

whether the feed to the FCC unit is hydrotreated with an FCC pretreater – FCC units produce 

greater naphtha when the feed is hydrotreated. As a percentage of feed, the FCC naphtha volume 

varied from 53.5 to 65%. Another adjustment we made was to adjust for refinery use of a 

propylene increasing catalyst named ZSM-5. When maximizing propylene production, the 

ZSM-5 reduces FCC naphtha volume. We identified 21 refineries which we estimate are using 

the ZSM-5 catalyst. The last volume adjustment we made to FCC naphtha was to undercut the 

heaviest portion of the FCC naphtha, called the swingcut. This volume is called the swingcut 

because it can either be blended into the gasoline pool or the distillate pool. We only undercut 

the FCC naphtha to distillate fuel if the modeled refinery volume exceeded the actual refinery 

volume. In the refinery-by-refinery model, some or all of the FCC naphtha swingcut was being 

undercut to distillate fuel at 45 out of the total 108 refineries that we modeled. 

After having completed these steps that we took to balance the modeled gasoline volume 

against actual gasoline production volume, the modeled gasoline volume for many refineries did 

match actual gasoline production volume. However, for many refineries the modeled refinery 

gasoline volume did not match the actual gasoline production volume. We reviewed the 

modeling for the refineries whose modeled gasoline volume did not match actual gasoline 

volume and we were able to identify several reasons why there were discrepancies. First, the 

refineries which we modeled as tar sands refineries were short of gasoline relative to actual 

gasoline volume. This is because tar sands are so heavy that they contain very little naphtha. 

Another group of refineries with a volume discrepancy have aromatics extraction units and they 

tend to have insufficient heavy naphtha feed for the reformer. We believe that the volume 

discrepancy exists because these refineries purchase heavy naphtha for feeding to their reformers 

for making additional aromatics for their aromatics plants, but we do not have data for heavy 

naphtha purchase (the only category that may reflect this is unfinished oils, but the volumes did 

not match the heavy naphtha shortfall in many of these cases. To avoid improperly modeling 

refinery costs because of our inability to accurately model refinery gasoline volume, we used 

actual refinery gasoline production volume in the year 2011 for refinery gasoline volume instead 

of the modeled gasoline volume estimated by the refinery-by-refinery model. 

5.1.3.2 Refinery Blendstock Sulfur Levels 

After determining the volume of each gasoline blendstock stream, we next estimated the 

sulfur level of each of the gasoline blendstocks for our modeling analysis using information we 

collected from literature reviews and discussions with refinery consultants and technology 

providers. We also considered the blendstock sulfur levels estimated for the MSAT2 rule and 

the estimates derived from our refinery-by-refinery model to estimate the sulfur levels of the 

blendstock streams. Establishing these sulfur levels is important as this sets a baseline for the 
5-28

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

refinery. This allowed us to project what changes refiners would have to make in their refineries 

to comply with the Tier 3 standards, and project the new investments and operating costs 

associated with these changes. The following section contains further details on how the sulfur 

content of each of the blendstocks was estimated. The results of this analysis can be found in 

Table 5-9 at the end of this section. 

The first stream we considered was the butanes that are used as a gasoline blendstock. 

The butanes used as gasoline blendstock within a refinery come from a variety of sources. Much 

of the butane used as a gasoline blendstock is distilled from the crude oil or other blendstock 

streams within the refinery. Refiners remove the butanes from crude oil and sometimes gasoline 

blendstocks which contain some butane (i.e., FCC naphtha, hydrocrackate) and then blend them 

back into the gasoline up to the RVP or vapor/liquid limit applicable to the gasoline market that 

the gasoline is being sold into. During the summer months refiners usually have excess butane 

which cannot be blended into the gasoline pool because of the tighter RVP standards. Many 

refiners store the excess butanes and then blend them back into gasoline in the winter months 

when the volatility limits for gasoline are less stringent. Other sources of butanes used as 

gasoline blendstocks are natural gas processers and crude oil drilling operations. The butanes 

from these sources are produced in downstream units which separate the various hydrocarbon 

components. Some of these downstream units “sweeten” or desulfurize the butanes using an 

extractive desulfurization unit prior to shipping them in pipelines or selling them directly to 

refiners. The sweetening process reacts the hydrocarbon mercaptan compounds to disulfide 

compounds reducing their odor and corrosivity. The sweetening process, however, does not 

lower the sulfur level. If the source natural gas well is very high in sulfur, the operator may need 

to use an extractive treatment technology which actually removes the sulfur from the butane 

stream. If the purchased butanes are not treated, then refiners treat the butanes. This treatment 

generally lowers the sulfur level of the butanes to under 5ppm. Purchased butanes that are 

blended into gasoline have a sulfur limit of 30 ppm and those that are shipped through pipelines, 

regardless of their end use, have a limit of 140 ppm. Furthermore, many refiners have extractive 

desMerox units on site that are capable of removing sulfur from butanes that are either purchased 

or generated internally from refinery units. For dimersol, and poly gas blendstock streams, we 

used the same sulfur levels that we estimated for our MSAT2 rulemaking. The sulfur levels for 

these streams are inherently low due to the dynamics of process reactions in the dimersol and 

polymerization units. Furthermore, it is unlikely that refiners have altered these processes in 

their refineries since our analysis for the MSAT2 rule was completed. 

Alkylate blendstocks usually have a small amount of sulfur, usually less than 15 ppm. 

The primary source of sulfur in alkylate is the sulfuric acid that is used as a catalyst in the 

alkylation process. Finished product coalescers and knockout drums are used by refiners to 

remove impurities, including sulfuric compounds, from the alkylate product as it leaves the 

alkylation unit. This separation is imperfect, and a small quantity of the sulfuric compounds 

which remain in the alkylate account for the majority of its sulfur content. Prior to the enactment 

of the Tier 2 standards, the alkylate produced by most refineries contained 10 to 25 ppm sulfur 

which assumes that there was some carryover of sulfuric compounds into the alkylate. Based on 

our discussions with gasoline desulfurization technology vendors, however, refiners have 

installed new acid coalescers and knock out drums in recent years. These new units improved 

the removal of residual sulfuric compounds and can produce an alkylate blendstock with a 5-ppm 
5-29

sulfur level. This adjustment by refiners seems to be a low cost method for reducing the sulfur 

content of alkylate. For our refinery-by-refinery baseline analysis, we assumed that refiners have 

already installed improved acid knockout drums and are currently producing alkylate which 

averages 10 ppm sulfur. We also assumed that Hydrofluoric Acid (HF) alkylation processes had 

the same alkylate yield per feedstock throughput as a sulfuric acid alkylation unit in our refinery 

by refinery model. We assumed that the sulfur level of alkylate from an HF units also averages 

10 ppm sulfur, even though HF processing units use hydrofluoric acid as the processing catalyst, 

instead of using sulfuric acid. 

The coker unit produces a gasoline blendstock with a significant amount of sulfur. These 

units convert the heavy portion of crude oil, called residuals, into gasoline and diesel blendstocks 

through the use of heat and pressure. The gasoline blendstock produced by the coker can contain 

more than 3,000 ppm sulfur. This stream is normally split into two different streams. The 

stream which contains the six to nine carbon hydrocarbons is processed in the naphtha 

hydrotreater, which reduces the sulfur level of this blendstock to below 1 ppm. This stream is 

then routed to the reformer for octane improvement. The five and six carbon hydrocarbon 

portion of coker naphtha is called light coker naphtha and usually contains on the order of 

several hundred ppm sulfur. Because of the instability of this stream due to its high olefin 

content, it is generally processed by the naphtha hydrotreater and sent to the isomerization unit if 

the refinery has one. After being processed in the hydrotreater, the sulfur content of this stream 

is reduced to approximately 1 ppm. If a refinery does not have an isomerization unit, we assume 

that light coker naphtha is already being desulfurized due to the unstable and very high sulfur 

levels of this naphtha stream. These treating pathways were assumed for each refinery in the 

refinery-by-refinery baseline analysis. 

Straight run naphtha is a gasoline blendstock which contains a moderate amount of 

sulfur. Straight run naphtha is the product stream from the atmospheric crude oil tower with a 

boiling point that falls within the boiling range of gasoline. The heaviest portion of straight run 

naphtha is higher in sulfur relative to the lighter portion of the straight run naphtha. The heavy 

portion of straight run naphtha is normally hydrotreated in the naphtha hydrotreater before being 

reformed by the reformer in order to improve its octane before being blended into gasoline. 

After this processing, the reformate has a sulfur level of less than 1 ppm. The light straight run 

naphtha (LSR) contains the five and part of the six carbon hydrocarbons and can range from zero 

to hundreds of parts per million sulfur before any extractive desulfurization or hydrotreating. 

LSR that is routed as feedstock to isomerization units has its sulfur lowered to 1 ppm by 

hydrotreating in the naphtha hydrotreater. This hydrotreating is necessary to allow this material 

to be processed in the isomerization unit, as the catalysts in these units require low sulfur 

feedstocks to function properly. Some refiners, however, do not have isomerization units or they 

produce LSR volumes that are greater than the capacity of their isomerization units. For many of 

these cases, refiners can treat LSR using sulfur extraction which, in most cases, reduces the 

sulfur level of LSR to well under 10 ppm sulfur. Even cases where there is insufficient capacity 

in the isomerization units it may be desirable for refiners to hydrotreat as much of the LSR as 

possible since it is more cost-effective to reduce the sulfur content of the LSR than the FCC 

naphtha. Refiners can either hydrotreat this volume of LSR in the naphtha hydrotreaters or in 

FCC naphtha postreaters. After considering the volume of LSR which is already being 

hydrotreated or treated with extractive desulfurization, we assume that LSR contains 5 ppm 

sulfur. 
5-30

Natural Gas Liquids (NGL) have a composition that is similar to LSR, as it is comprised 

primarily of pentanes and hexanes. NGLs are produced from natural gas processers and crude 

oil drilling operations and the sulfur content of the NGLs can vary depending on its source, 

although we estimate that this stream ranges from zero to about 100ppm sulfur. While some of 

the NGLs are treated to remove sulfur by the NGL producers before being purchased by the 

refineries we did not have sufficient information to be able to determine the extent to which this 

treatment is occurring. At most, if not all refineries, refiners are extracting the sulfur from NGLs 

to prevent their gasoline from having odor issues due to the mercaptans which may be present in 

NGLs. Extraction is likely to reduce the total sulfur content of NGLs to low levels. For the 

control case in our refinery-by-refinery model we assumed that NGL liquids are being treated in 

a similar manner as LSR. 

We also assumed that all ethanol blended into gasoline has a sulfur content of 5 ppm. 

Ethanol produced at ethanol plants should naturally have a negligible amount of sulfur. Before 

being sold, however, a denaturant is added to the ethanol. This denaturant most commonly used 

is natural gasoline, a C5 to C7 naphtha produced during natural gas processing. Natural gasoline 

has a sulfur content that ranges anywhere from a few parts per million to a couple hundred parts 

per million sulfur. We conservatively assumed that the natural gasoline used as an ethanol 

denaturant is not hydrotreated and has an average sulfur level of 250 ppm. Ethanol contains 2 

percent denaturant, which results in denatured ethanol having a sulfur level of 5 ppm.

After determining the sulfur level for each of the gasoline blendstock streams as 

discussed above we can use this information, along with the gasoline production volumes and 

sulfur levels for the United States in 2011, to determine the sulfur level of the FCC naphtha 

stream on a national average basis. To do this we used the following equation, referred to as 

Equation 5-2 hereafter: 
5-31

FCC Naphtha Sulfur ppm = [(A*B) – (C*D+E*F+G*H+I*J+K*L+M*N+O*P+Q*R+S*T)] / Z 

Where: 

A = Refinery Total Gasoline Yield, BPSD 

B = Refinery Total Gasoline Sulfur level, ppm 

C = Butane to Gasoline, BPSD 

D = Butane Sulfur, ppm 

E = Alkylate BPSD 

F = Alkylate Sulfur, ppm 

G= Reformate BPSD 

H= Reformate Sulfur, ppm 

I = Coker Naphtha, BPSD 

J = Coker Naphtha Sulfur, ppm 

K= Hydro-crackate BPSD 

L= Hydro-crackate Sulfur, ppm 

M= Light Straight Run (LSR) and Natural Gas Liquids (NGL), BPSD 

N =LSR and NGL Sulfur, ppm 

O= Dimersol, BPSD 

P= Dimersol Sulfur, ppm 

Q= Polymerization BPSD 

R= Polymerization Sulfur, ppm 

S= Ethanol, BPSD 

T = Ethanol Sulfur, ppm 

Z= FCC Gasoline Yield, BPSD 

Equation 5-2 Calculating FCC Naphtha Sulfur Content for Refinery-By-Refinery Model 

We used this equation to assess two cases; a baseline case where the 30 ppm Tier 2 sulfur 

standards were fully implemented and a control case that reflects the 10 ppm Tier 3 sulfur 

standards. The only terms in Equation 5-2 that change between the two cases are the national 

average sulfur level and the sulfur levels of the LSR, NGL, and FCC naphtha streams. The 

national average sulfur levels for the two cases were set at the sulfur limits under the Tier 2 and 

Tier 3 programs -- 30 ppm and 10 ppm, respectively. For the baseline case we assumed that the 

sulfur level of the LSR stream is 15 ppm. This reflects our assessment of how these streams are 

currently being handled as discussed earlier in this section. We estimate that 66 percent of the 

volume of NGL and LSR are hydrotreated before being blended into gasoline and have a very 

low sulfur content of approximately 1 ppm. Another 25 percent of LSR is being treated by 

extractive desulfurization and is low in sulfur, likely in the 0 to 10 ppm range. The remaining 10 

percent is untreated and has a sulfur content of approximately 100 ppm. 

For the Tier 3 control case we assumed that all of the NGLs and LSR were either A) 

hydrotreated or treated with extractive desulfurization and therefore had an average sulfur 

content of 5 ppm, or B) the refinery would comply by purchasing credits and their LSR would 

remain at its Tier 2 levels. This information allowed us to solve Equation 5-2 for the FCC 

naphtha content. The resulting FCC naphtha sulfur numbers, along with our estimation of the 

gasoline blendstock sulfur levels and percent of total gasoline volume made up by each 

blendstock are shown in Table 5-16. 
5-32

Table 5-16 Sulfur Levels for Gasoline Blendstocks in the Refinery-By-Refinery Model 

Gasoline Blendstocks Baseline Tier 2 

Case

Proposed Tier 3 

Case Year 2017

Proposed Tier 3 

Case Year 2030

Percent 

of Total 

Volume

Sulfur 

Levels 

30 

ppm

Percent 

of Total 

Volume

Sulfur 

Levels 

10 

ppm

Percent 

of Total 

Volume

Sulfur 

Levels 

10 

ppm

FCC Naphtha 37.2 80a36.0 21

a

35.0 21

a

Reformate 22.5 0.5 21.8 0.5 21.2 0.5

Alkylate 12.7 10 12.5 10 12.1 10

Isomerate 3.2 0.5 3.1 0.5 3.1 0.5

Butane 4.0 5 4.0 5 3.8 5

Light Straight Run Naphtha (LSR) and 

Natural gas Liquids (NGL)

5.2 15 4.9 5 4.8 5

Hydrocrackate 3.0 8 2.9 8 2.8 8

Ethanol 9.9 5 12.5 5 15 5

Coker Naphtha 2.2 0.5 2.1 0.5 2.0 0.5

Other Gasoline Blendstocks 0.2 10 0.2 10 0.2 10

Total/Sulfur Average 100 30 100 10 100 10

a These values are calculated using Equation 5-2; all other sulfur levels are assumed. 

The numbers in the table above represent national averages. While this is useful 

information, it is insufficient for us to be able to model the implications of the proposed Tier 3 

standards for an individual refinery. Each refinery has a unique combination of processing units 

that will determine the cost and operational changes necessary for that refiner to comply with our 

proposed sulfur limit. While each of these processing units may impact the cost for refiners to 

lower the sulfur content of the gasoline they produce we believe these costs will be dominated by 

the units responsible for the desulfurization of the FCC naphtha, and to a lesser extent the NGLs 

and LSR. This is because these are the only streams we anticipate would see significant sulfur 

reduction under the proposed Tier 3 sulfur standards. The units that are used to desulfurize these 

streams include the FCC unit pre- and postreaters and the naphtha hydrotreaters. It is important, 

therefore, to have a good understanding of which of these units are in place in each refinery, as 

well as the type and capacity of these units, in order to allow us to most accurately estimate the 

cost of the Tier 3 sulfur standards to the refining industry. We used the above FCC naphtha 

sulfur balance information as the basis of our vendor request for refiner modifications to FCC 

postreaters under Tier 3. However, for the vendor requests, we used a preliminary model, where 

the FCC naphtha levels under Tier 2 averaged 75 ppm, while FCC naphtha levels under Tier 3 

averaged 25 ppm for 10-ppm sulfur gasoline, representing a 50 ppm sulfur reduction, close to the 
5-33

same delta presented in the table above.C The following section discusses our assessment of the 

desulfurization equipment currently being used in refineries. 

5.1.3.3 Assessment Existing Desulfurization Equipment at Refineries 

Since the desulfurization cost of the Tier 3 program is largely impacted by the cost of 

lowering sulfur in FCC gasoline, it is important to understand what refiners are already doing to 

lower the sulfur content of the FCC gasoline blendstock to meet the Tier 2 sulfur standards. This 

was important to our analysis of the cost for each individual refiner to reduce the sulfur content 

of their gasoline to meet the proposed Tier 3 sulfur standard. Refiners that already have an FCC 

pretreater or postreater can revamp these units for a lower cost than installing grass roots units. 

It was also important to determine which refineries have an FCC feed pretreater, since these units 

increase the refineries FCC conversion and production of FCC naphtha and also lower the sulfur 

level of the FCC naphtha. To compile this information we analyzed capacity information for 

FCC naphtha pretreaters and postreaters for each refinery listed in the OGJ, EIA and OAQPS 

database sets. If one of the databases showed that a refinery had FCC pretreating and/or posttreating capacity, while the other did not, we assumed that the refinery did have the units listed 

with a capacity as reported. Our OAQPS database had approximately six refiners that have FCC 

post treaters, and that were not listed in either the EIA or OGJ data sets. We assumed that these 

refiners had an existing postreater. For refineries that have FCC naphtha postreaters we next 

determined which vendor’s FCC naphtha desulfurization technology is installed in each refinery. 

To do this we conducted a public database search using OGJ, company web postings and, other 

refinery publications. To supplement this data we also had extensive discussions with many 

refiners who provided us with information on the type and capacity of the desulfurization 

technology currently installed in their refineries, as well as how their operations might be 

adjusted to meet the new Tier 3 sulfur standards. The various FCC naphtha desulfurization 

technologies that we identified as currently being used by refiners are CD Tech’s Cd Hydro and 

CDHDS, Axens Prime G and Prime G+, UOP’s ISAL and Selectfining, Exxon’s Scanfining I or 

II and Sinopec’s S-Zorb. For refineries for which we could not find or obtain information on the 

type of desulfurization they were using, Axens was chosen as the default as they have the largest 

market share of desulfurization units in the U.S. To confirm the accuracy of our work we 

reviewed our assessments with one of the main technology vendors. Our desulfurization 

technology selection assumptions were adjusted based on feedback from the vendor. The 

aggregated results of this assessment are summarized in Table 5-17. 

 

C

 Because the technology vendors provided us with cost data only for the increment of reducing FCC naphtha sulfur 

content from 75 ppm to 25 ppm and in some cases from 75 ppm to 10 ppm, we modeled all refineries, regardless of 

their current sulfur level, using the same technology costs. In reality, those with finished gasoline sulfur levels 

higher than 30 ppm would have slightly higher costs and those with finished gasoline sulfur levels lower than 30 

ppm would have slightly lower costs. We are trying to obtain additional information that would enable us to adjust 

our cost analysis to reflect actual refinery starting sulfur levels. 
5-34

Table 5-17 Postreater Technologies Used By Refineries 

CD Tech IFP/Axens Scanfining UOP ISAL S-Zorb

Refiners with Existing 

Postreater

15 38 15 2 5

The next step of our analysis was to determine which refineries use FCC feed 

hydrotreating technology (pretreaters) in addition to post-treating units. FCC feed hydrotreating 

was primarily installed at refineries not as a sulfur control technology but because of the 

economic benefits that can be obtained from hydro-treating FCC feed. Hydrotreating the FCC 

feed increases the crackability of this stream by saturating the components with hydrogen 

resulting in a higher paraffin content in the feed stream. Hydrotreating also removes FCC feed 

impurities such as nitrogen, metals, con-carbon and sulfur, which improve FCC unit catalyst 

effects. An additional benefit of FCC feed pretreating is that it reduces the sulfur content of the 

FCC feedstock by 70 to 90 percent, resulting in the production of FCC naphtha with lower sulfur 

levels than what would be produced using FCC feed that is not hydrotreated. 

Our analysis indicates that approximately 54 refiners are currently using FCC feed 

pretreaters. Of the 54 refineries with pretreaters, 35 also have FCC postreaters installed to 

comply with the Tier 2 gasoline sulfur standard. The technologies used by these 35 refineries are 

shown in Table 5-18. FCC naphtha produced from an FCC pretreater operating at standard 

severity generally produces a gasoline with a sulfur content that exceeds the Tier 2 standards. 

According to information from vendors, the average FCC naphtha sulfur level of refineries with 

an FCC feed pretreater operating at standard conditions without a postreater ranges from 200 to 

500 ppm. Further reductions in the sulfur level of the FCC naphtha are possible using only an 

FCC pretreater by operating the pretreater at a higher severity or higher pressure (if the unit is 

designed to do so). This appears to be the case for the 19 refineries using only FCC pretreaters 

to comply with the current Tier2 sulfur standard. These high pressure FCC pretreating units 

were designed to be able to run at a high severity to further increase the crackability of the FCC 

feed and therefore increase the conversion rate of the FCC unit. These more severe conditions 

also further reduce the sulfur level of the FCC naphtha. The naphtha produced from these units 

operating with high severity or high pressure has an average sulfur content ranging from 75 to 

100 ppm, allowing these refineries to produce gasoline that meets the Tier 2 sulfur standards. 

Operating FCC pretreaters at the high severities necessary to meet the Tier 2 standards, however, 

also results in increased operating cost, as the pretreater requires more frequent catalyst 

changeouts, consumes more hydrogen, and operates higher temperatures than pretreaters 

operating under standard conditions. 

Table 5-18 Technologies Used By Refiners with FCC Pre and Postreaters 

CD Tech IFP/Axens Scanfining UOP ISAL S-Zorb

Refiners with FCC Pretreater 

and Naphtha Postreater

9 17 6 1 2

Our analysis also showed that there are several refineries that have an FCC unit but have 

installed neither an FCC naphtha postreater nor an FCC feed pretreater. These are small 

refineries, or refineries that produce a refinery gate gasoline with a sulfur level below the Tier 2 

cap of 80 ppm sulfur, but above the 30-ppm average. These refiners are relying on buying or 
5-35

sharing sulfur credits from other refineries that are over-complying with Tier 2 and make 

gasoline with a sulfur level less than 30 ppm. 

Finally, some refineries do not have an FCC unit and therefore have not installed FCC 

postreaters to comply with the Tier 2 sulfur standards. These refiners primarily use reformate, 

alkylate, LSR, butanes, and pentanes to make gasoline. Since these blendstocks all have low 

sulfur content this allows refiners to produce gasoline with a low enough sulfur content to meet 

the Tier 2 sulfur standards. 

A summary of the number refineries which fall into differing categories of how they are 

complying with Tier 2 is shown in Table 5-19. 

Table 5-19 Refinery FCC Naphtha Desulfurization Unit Characterization 

5.1.3.4 Estimate of FCC Naphtha Sulfur Levels 

After we had determined the desulfurization technology in place at each refinery, we 

sought to calculate the sulfur content of the FCC naphtha, which is the feedstock for FCC 

postreaters. It is important to understand the sulfur level of FCC naphtha because it helps to 

determine the extent that existing FCC postreaters are operating at their maximum hydrotreating 

capacity and how refiners might invest to comply with Tier 3. Some refineries may have excess 

capacity in their FCC naphtha pretreater or postreaters that would allow them to produce 

gasoline that would meet the proposed Tier 3 standards without having to revamp existing units 

or add grass roots units. These refineries will have much lower cost impacts than refineries that 

have to make more significant capital investments. To estimate the sulfur of the FCC naphtha we 

must start upstream of the FCC unit and first understand the sulfur level of the crude oil which is 

the source for the vacuum gas oil that serves as the feedstock for the FCC units. 

The sulfur level of the FCC feedstock is dependent on several items; 1) the sulfur level of 

the crude oil being processed by the refinery, 2) whether or not a refinery has a coker unit and 3) 

whether or not the refinery has an FCC feed pretreater. In refineries, the crude unit directly 

supplies heavy atmospheric gas oils (HGO) and vacuum gas oils (VGO) streams, which are the 

bulk of material used as FCC feedstock in most refineries. The sulfur level of these two streams 

can be estimated using a regression correlation that is based on the actual crude unit sulfur level 

and actual VGO sulfur level from crude assays. The peer reviewers agreed that our calculations 

were adequate for estimating the FCC feed sulfur levels of HGO/VGO feedstocks based on crude 

sulfur levels. However, if a refinery has a coker unit, the FCC unit will also likely use heavy 

coker gas oil (HCGO) as a feedstock. A peer reviewer pointed out to us that the sulfur level of 

HCGO is usually much higher than HGO and VGO, since coker units use heavy residual stocks 

FCC Treatment Units Installed Number of Refineries

No FCC Unit 14

FCC Unit, No Pretreater or Postreater 4

FCC Unit With Postreater Only 42

FCC Unit With Pretreater Only 16

FCC Unit With Pretreater and Postreater 35
5-36

as feedstock. As such, the sulfur level of HCGO cannot be estimated from the same correlation 

used for HGO and VGO. As a result, for our final rule analysis we adjusted the FCC feed sulfur 

levels higher to account for the refining of higher sulfur HCGO in FCC units. 

To arrive at each refiner’s FCC feed sulfur level, we determined the blended FCC 

feedstock sulfur value based on the volumes and sulfur levels we estimate for HGO/VGO and 

HCGO, as describe below. 

The first step in determining the sulfur level of the FCC feedstock was to input the crude 

sulfur level for each refinery into our refinery-by-refinery model. For this, we obtained 

confidential business information (CBI) from EIA on the annual average crude sulfur levels that 

each refinery processed in 2011. This data, which is reported to EIA for each refinery, was used 

as the baseline crude sulfur level in our refinery-by-refinery analysis. Using this data, we then 

determined what each refiner’s HGO/VGO feed sulfur level would be, using a regression corelation we built from data on crude sulfur levels and FCC feedstock material, as discussed 

below. 

The boiling point range that we assumed for VGO also contained some residual material, 

representing FCC feed with residual content. This was done to reflect the imperfect distillation 

cuts in crude towers and that some refiners use small amounts of residual material as FCC 

feedstock. The balance of the residual material, however, was excluded from the feed to FCCs 

since this material makes a poor feedstock due to its high aromatics, metals and concarbon 

content. Each of these materials negatively affects the FCC gasoline conversion yields. Most 

refiners today do not directly use residuals as feedstock to their FCC units, but instead send them 

to be processed in coker units or use the residual material for fuel oil and asphalt production. 

The boiling point ranges that we used for HGO and VGO are listed Table 5-20.

Table 5-20 Boiling Ranges of FCC Feedstocks from the Crude Unit 

TBP Initial TBP Final

Heavy Atmospheric Gas Oil 

(HGO)

600°F 800°F

Vacuum Gas Oil (VGO)a800°F 1,000°F

a

 Contains some residual material 

For our FCC HGO/VGO feed sulfur regression, we used various crude oil assays that we 

obtained from Jacobs Engineering. We used data from five specific crude types, including West 

Texas intermediate, Bonny Light, Saudi Heavy, Alaskan North Slope, and Mayan, and three 

blended crude assays. The equation for this regression, along with the estimated FCC feed sulfur 

contents for various crude oils are shown in Equation 5-3 and Table 5-21. 

Equation 5-3 FCC HGO/VGO Feed Sulfur Content Based on Crude Sulfur Content 

FCC Feed Sulfur Weight Percent = (Crude Sulfur Weight Percent)0.8 * 1.1858 + 0.0409 
5-37

Table 5-21 FCC HGO/VGO Feedstock Sulfur For Various Crude Sulfur Levels 

Crude Sulfur Level (Weight %) FCC HGO/VGO Feed Sulfur Level 

(Weight %)

0.11% 0.24%

0.28% 0.47%

0.85% 1.08%

1.3% 1.50%

1.4% 1.59%

1.6% 1.77%

2.8% 2.74%

3.04% 2.93%

If a refiner did not have a coker unit, we used the above method to estimate the FCC 

feedstock sulfur level prior to any FCC feed pretreating. However, for refiners with a coker unit, 

we had to adjust the above numbers higher to account for the levels of sulfur from HCGO. 

For refiners with a coker unit, the HCGO yield from the coker unit was set at 25% of the 

feedstock, based on yield estimated from one of the peer reviewers. The sulfur level of HCGO 

was set to be equal to the feedstock sulfur level of vacuum residual bottoms (VTB), which is 

used as feedstock to the coker unit. The VTB sulfur level was assumed to be 2.2 times the 

refiners EIA crude sulfur level, based on correlations recommended by the peer reviewer. Using 

this approach, we estimated the HCGO volume and sulfur level that is used as FCC feedstock in 

refineries with coker units. Then, the HGO/VGO volume of feedstock was determined by 

subtracting any HCGO from the total EIA FCC feedstock volume that the refiner used as charge 

in 2011. The resulting HCGO and HGO/VGO feedstocks were then volume averaged with the 

corresponding sulfur levels to determine the final FCC feedstock sulfur level for the refiner. 

This resulted in a modest rise in FCC unit feedstock sulfur levels from our NPRM analysis 

approach. Table 5-22 shows the FCC feedstock sulfur results, using this methodology. 
5-38

Table 5-22 PADD Average Effects of HCGO on FCC feed sulfur levels 

PADD FCC Feed not adjusted for 

HCGO, wt. % sulfur

FCC Feed adjusted for 

HCGO, wt. % sulfur

1 1.15 1.21

2 1.46 1.59

3 1.52 1.70

4 & 5,

excluding California 1.30 1.35

California 1.54 1.54

National Average 1.44 1.54

With FCC feed sulfur estimated, the next step in our analysis was to consider the impact 

of pretreaters on the FCC feed sulfur levels for refineries that have these units. There are several 

factors that must be considered to determine the impact of the pretreaters on the FCC sulfur 

level, including the pressure at which the unit operates, the severity at which it is run, and 

whether or not the FCC naphtha will be postreated. 

To inform our understanding of how FCC pretreaters operate, we obtained guidance from 

technology and catalyst providers. From these discussions we learned that the capability for 

FCC pretreaters to remove sulfur from the gas oil feed varies significantly depending on the 

pressure at which the unit operates. FCC pretreaters can generally be subdivided into high 

pressure units (1400 psi and above), medium pressure units (900 to 1,400 psi), and low pressure 

units (below 900 psi). High pressure FCC pretreaters are capable of removing about 90 percent 

of the sulfur contained in the gas oil feedstock to the FCC unit, while low and medium pressure 

units are capable of removing 65 to 80 percent of the feed sulfur. Information we received from 

the vendors also indicated that refiners with both a pretreater and a postreater are typically 

producing FCC naphtha that ranges from 200 to 450 ppm before being processed by the 

postreater. Having a postreater allows these refineries to not have to operate their pretreaters at a 

high severity for compliance with the 30 ppm Tier 2 sulfur standard since the sulfur will further 

be reduced to levels necessary to meet the applicable standards in the postreater. For a subset of 

these refineries, the pretreater is undersized and not able to pretreat the entire FCC feed charge 

volume. In response to peer reviewer comments, we therefore, limited the amount of FCC feed 

that was processed for several refineries based on their unit capacity. Refineries with only a 

pretreater are making lower sulfur FCC naphtha in the 75 to 100 ppm range, according to vendor 

estimates. With this information we used our refinery-by-refinery model to estimate the 

pretreater desulfurization rates required to get FCC naphtha sulfur levels within the ranges 

specified. We estimated that FCC units with a pretreater and a naphtha postreater are operating 

their pretreaters at a severity which results in a 76 percent desulfurization of the FCC feed 

stream. This number represents the national average. While the actual severity at which the 
5-39

pretreating units are run varies on a refinery-by-refinery basis this average was used in our 

modeling for all refineries with both pretreating and postreating units due to a lack of refineryspecific information. For FCC units with a feed pretreater but no postreater we calculated the 

FCC naphtha sulfur level required to make a refinery gate gasoline that meets the Tier 2 

standard. To do this calculation we used the gasoline yields from our refinery-by-refinery model 

along with the gasoline blendstock sulfur levels discussed in subsection 5.1.3.2 and shown in 

Table 5-16. These calculations showed that refiners with FCC feed pretreating units, but no 

postreaters, need to produce FCC naphtha that averages about 85 ppm on a national level. This 

sulfur level corresponded to these refiners operating their pretreaters at a severity that results in a 

reduction of sulfur in the FCC feed stream of approximately 91-92 percent. This number is close 

to the estimate we received from the vendors for this category of refineries and therefore was 

used in our refinery-by-refinery model to determine the FCC feed sulfur level for refiners with 

pretreaters. 

After we have calculated the sulfur level of the FCC feed we had to then take into 

consideration the impact the FCC unit itself has on the sulfur level of the FCC naphtha. We 

reviewed several literature sources14,15 and found that the FCC naphtha sulfur level can be 

estimated by dividing the FCC feed sulfur level by 20 for refineries with an FCC feed pretreating 

unit. For refineries without an FCC feed pretreater, the FCC naphtha sulfur levels can be 

calculated by dividing the desulfurized FCC feed sulfur level by 10. In these cases the effect of 

the FCC unit itself on the sulfur level of the FCC naphtha is lower, as the FCC feed has already 

been through a desulfurization process. These factors, when combined with the sulfur levels of 

the FCC streams as discussed above, allow us to calculate on a refinery-by-refinery basis the 

sulfur level of the FCC naphtha before any post-treating operations. The results of this analysis 

are summarized in Table 5-23.

Table 5-23 FCC Naphtha Sulfur Levels for Various Refinery Configurations 

PADD 1 PADD 2 PADD 3 PADD 4/5

No Pretreater or Postreater N.A.

a

-<3 b-<3 b-<3 b

Pretreater Only N.A.

a

79 52 61

Postreater Only 1119 1233 556 1039

Pretreater and Postreater 45 <3 b601 293

a

 N.A. – not applicable, no units of this type in the PADD 

b

 Since there are less than three refiners in this PADD with the described configuration, the data was 

removed to protect potential CBI concerns. 

An additional adjustment to the FCC naphtha sulfur levels was made because of 

undercutting of the FCC naphtha into the diesel fuel pool. If in the refinery-by-refinery model 

we estimated that a refinery is fully undercutting its FCC naphtha to the diesel fuel pool, the 

sulfur level of the FCC naphtha was reduced to half of what it would be without undercutting. If 

the amount of FCC undercutting was somewhere between none and all of the swingcut being 

undercut to diesel fuel, we proportionally adjusted the FCC naphtha sulfur level. For example, if 

in the refinery-by-refinery model we estimated that half of the FCC naphtha swingcut was being 

undercut, we estimated that the FCC naphtha sulfur level is 75 percent of what the FCC naphtha 

sulfur level would be without undercutting. 
5-40

This information, along with the information described in previous sections (e.g., 

gasoline blendstock volumes and sulfur levels, desulfurization equipment currently in place at 

refineries, and crude oil sulfur levels) allowed us to conduct the best analysis for the baseline 

case for our refinery-by-refinery model. This baseline case reflects what we believe the current 

operating conditions are at each refinery, including any modifications they have made to meet 

the Tier 2 sulfur standards. The next step of our analysis was to project what further changes, 

either to operations, adding new equipment or revamping existing units, each refiner would have 

to make to meet the proposed Tier 3 standards. After these changes are estimated, we can then 

estimate the cost associated with each of these changes, and ultimately the cost of the program. 

5.1.3.5 Cost Inputs for the Sulfur Control Technologies 

After we determined the sulfur levels of the gasoline blendstocks for each refinery and 

the sulfur levels that these blendstocks would have to achieve to meet the Tier 3 sulfur standards, 

the next step in our refinery-by-refinery analysis was to project the changes to refinery units and 

unit operations each refinery would have to make to comply with the Tier 3 sulfur standard. One 

step refiners would take to further reduce gasoline sulfur levels would be to desulfurize the light 

straight run and natural gas liquids. The costs to reduce the sulfur content of these streams is 

relatively low and would therefore be a cost-effective way to further reduce the sulfur content of 

the finished gasoline. In addition, because ethanol tends to be a relatively low sulfur blendstock 

(assumed to be 5 ppm in our refinery-by-refinery model), increasing the amount of ethanol in the 

gasoline pool lowers the overall sulfur content of the gasoline. For the NPRM analysis, we 

projected that 50 percent of all gasoline produced by refiners in 2017 would contain 15 percent 

ethanol and that it would be almost entirely E15 by 2030. However, for our final rule analysis 

we are basing our ethanol use on AEO2013, which assumes widespread E10 use with very little 

E15 use and a small amount of E85 use. Reducing the sulfur content of the LSR and NGL

streams and taking advantage of ethanol blending, however, would fall far short in enabling 

refiners to comply with the Tier 3 gasoline sulfur standards. Refineries with an FCC unit would 

still have to reduce the sulfur content of their FCC naphtha blendstock to meet the Tier 3 

standards. 

For each refinery we considered two cases. In the first case each refinery had to meet the 

Tier 3 gasoline sulfur standard of 10 ppm. To meet this standard, as discussed in Section 5.1.3.2, 

we estimated that they would have to reduce the sulfur level of their FCC naphtha stream from 

75 to 25 ppm. We also considered a case where each refinery would reduce the sulfur level of 

their gasoline to 5 ppm. This information was used to help us determine which refineries might 

reduce the sulfur level of their gasoline below our proposed 10-ppm standard to generate credits 

for our ABT scenarios summarized in Table 5-1 and discussed in Section 5.2.1. 

Our refinery-by-refinery model assumed that reducing the sulfur content of the FCC 

naphtha to 25 ppm and 10 ppm for the two cases discussed above would require that each 

refinery that produces FCC naphtha have an FCC naphtha postreater. For companies that 

already have an FCC naphtha postreater we assumed that all that would be necessary to meet the 

Tier 3 sulfur standards was to revamp their existing FCC postreating units. We received cost 

information from several vendors for revamping FCC postreating units and assumed a revamp 

cost for each refinery in line with the cost projections quoted by the vendor of the technology 

already in place in their refinery. We assumed that refineries with FCC units that currently do 
5-41

not have an FCC postreater would have no choice other than to add a new grass roots FCC 

postreating unit. We ultimately only received cost information from one vendor for the cost of 

adding a new grass roots FCC postreating unit that fit the sulfur reduction requirements of the 

proposed Tier 3 program. We therefore assumed the cost for each refinery that would need to 

add a new FCC post-treating unit would be in line with this estimate. More details on the costs 

used in our refinery-by-refinery model for the desulfurization of LSR and NGL, ,as well as the 

new FCC post-treating units and revamps, can be found in the following sections. 

5.1.3.5.1 Cost to Revamp Existing FCC Naphtha Postreaters 

To estimate the cost for revamping existing FCC postreating units or for adding new 

postreating capacity, we contacted several technology vendors for cost estimates and reviewed 

literature, including cost information provided for the Tier 2 rulemaking. Because no two 

refineries are exactly the same, the cost for new FCC postreater units or revamps to existing units 

will vary significantly from refinery to refinery. Some of the factors that have the most 

significant impact on the cost of FCC postreaters are the technology that the refiner used to 

comply with Tier 2, the volume of FCC naphtha, the sulfur content of the FCC unit feed and the 

level of desulfurization in the existing postreater, and the location of the refinery. Based on 

feedback from vendors we considered three categories of FCC postreaters based on whether the 

FCC naphtha (the feed for the existing Tier 2 postreater) contained low (0 – 400 ppm) medium 

(400 – 1,200 ppm) or high (>1,200 ppm) levels of sulfur. 

For revamp postreaters, we asked the vendors to evaluate desulfurizing FCC naphtha 

from a Tier 2 sulfur level of 75 ppm, down to 25 and 10 ppm, for Tier 3 finished gasoline sulfur 

levels of 10 and 5 ppm, respectively. This corresponds to a delta FCC naphtha sulfur reduction 

of 50 ppm (75 ppm minus 25 ppm) for the 10 ppm standard, and 65 ppm (75-10 ppm) for the 5 

ppm level. For new standalone Tier 3 post treaters, we asked the vendors to evaluate a FCC 

naphtha sulfur reduction from a Tier 2 sulfur level of 100 pm, down to levels of 25 and 10 ppm, 

(reductions of 75 and 90 ppm), for the 10 and 5 ppm finished gasoline levels, respectively. For 

our FRM analysis, we applied the vendor cost estimates based on these sulfur ranges, to the 

sulfur reductions needed for every refinery. Since each refinery has a specific FCC naphtha 

sulfur reduction level needed for the Tier 3 standards, we adjusted the vendor cost estimates, so 

as to apply them to each refinery’s particular FCC naphtha sulfur level reduction amount that 

was needed for Tier 3. We applied the vendor cost estimates to each refiners FCC naphtha sulfur 

reduction level needed for Tier3, by assuming that the vendors estimate scale linearly for octane 

and hydrogen for sulfur reduction levels that are less than 96 percent of the FCC naphtha Tier 2 

sulfur levels. As such, the vendor cost estimates for octane and hydrogen were scaled based on 

the relative increase or decrease in a refiners FCC naphtha sulfur level, versus the 50 and 65 ppm 

sulfur delta used in the vendor estimates for a 10 and 5 ppm standard. All of the other vendor 

cost estimates, such as capital cost, steam, electricity usage etc, were assumed to not vary from 

what was supplied by the vendors. This cost adjustment was applied to all of the vendor 

estimates for new and revamp FCC Naphtha post treaters. The starting (Tier 2 ) FCC naphtha 

sulfur level for each refiner was determined based on our modeling of the volumes and sulfur 

levels of each of the gasoline blendstocks that the refinery uses to produce finished gasoline. 

We obtained information from several technology providers for the revamp costs of 

existing FCC postreaters. One of the technology providers, however, declined to provide us with 
5-42

information applicable for Tier 3 sulfur control; they merely provided us with historical 

information for controlling sulfur from pre-Tier 2 uncontrolled sulfur levels. As a result, their 

capital and operating costs were extraordinarily high relative to the rest of the cost information 

we received from the other technology providers that was specific to Tier 3. In addition, the 

information they provided did not contain sufficient detail to enable us to adjust it to be of 

relevance for Tier 3. Given the magnitude of their cost estimate, we also believe it is likely that 

their cost estimate represented not only a grass roots FCC postreater, but also significant refinery 

investment in other refinery processes such as FCC feed pretreating, coker unit expansion, etc. 

Thus, we were unable to use this information to estimate the revamp costs for FCC post treating 

for the refineries that employ that company’s technology, and our peer reviewers concurred. The 

other technology providers submitted information applicable to Tier 3, but not necessarily 

covering all of the scenarios refineries would experience. Therefore, as discussed below, we 

used and adjusted the information we were provided as necessary to apply it across all the 

refineries. Some of the submitted information only had cost information for our medium sulfur 

(400 – 1,200 ppm) FCC feed case. Another technology provider did not provide cost estimates 

for producing FCC naphtha with a sulfur level of 25 ppm, corresponding to a finished gasoline 

with 10 ppm sulfur, therefore, we needed to interpolate their cost information. Because the cost 

information provided by the technology providers was labeled CBI, this cost information cannot 

be listed individually, however we aggregated the cost information we received for FCC 

postreater revamps to meet 10 ppm and 5 ppm sulfur levels in gasoline. The aggregated 

information is summarized in 5-25 and 5-26. 

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

technology provided information for several potential FCC postreater revamp cases. The first 

case was a no capital costs case where refiners made no equipment modifications, but rather 

solely made operational changes using their existing equipment installed for Tier 2. The second 

case we requested was one where refiners would incur only minor capital costs and was intended 

to be used for analyzing program options with moderate octane costs. The third case we 

requested was one where refiners were willing to incur greater capital costs in order to minimize 

operating costs and octane loss. The majority of the vendors only supplied cost estimates for the 

third case, which included adding an additional catalyst reactor bed to the existing FCC 

postreater unit (i.e. revamping their existing FCC postreater). This addition of catalyst reactor 

bed ensures that refiners will be able to run their existing FCC postreater at 4 to 5 year catalyst 

cycle lengths, which is a critical feature for FCC unit operations. 

The costs for the FCC postreater revamps submitted by one of the vendors, however 

showed that for low (0 – 400 ppm) and medium (400 – 1,200 ppm) sulfur FCC naphtha sulfur 

levels, the second case, with low capital costs, resulted in the lowest cents per gallon costs for 

meeting the proposed 10-ppm Tier 3 standards. According to this vendor, these cases also had a 

4 to 5 year catalyst cycle length, equivalent to the higher capital cost cases even though a second 

stage reactor was not required. We therefore assumed that refineries using this vendor’s 

technology would choose the minor capital cost pathway for meeting the 10-ppm Tier 3 standard 

when they had low or medium sulfur levels in their FCC feed. The high capital cost cases for 

producing gasoline to meet a 5 ppm sulfur standard from low and medium sulfur FCC feeds were 

found to have the lowest cost on a cents per gallon basis and were therefore selected by our 

model for these cases. 
5-43

One vendor only submitted information for postreater revamp cost estimates for FCC 

naphtha in the 400 – 1,200 ppm sulfur category that produced a 5 ppm sulfur gasoline. In our 

refinery-by-refinery model, however, we had multiple refineries with FCC feed sulfur levels in 

the 0 – 400 and >1,200 ppm categories that use this vendor’s postreating technology. In order to 

apply this vendor’s cost estimate to cases of low (0 – 400 ppm) and high (>1,200 ppm) sulfur 

feed categories we adjusted this vendors 400 – 1,200 ppm postreater revamp cost based on the 

cost differentials between the three FCC naphtha sulfur levels in the other vendors’ revamp 

estimates. We similarly derived a postreater revamp cost estimate to produce a 10 ppm gasoline 

for this vendor using cost differentials between the 10 and 5 ppm cases from other vendors. For 

refineries currently employing technology by other vendors for which we had no specific cost 

information, we used an average of all of the vendors’ estimates to represent FCC postreater 

revamp costs for refiners using this particular technology in our refinery-by-refiner model. 

After we had determined cost estimates for the FCC postreater revamps based on 

information from the vendors the next step was to scale these costs based on the size of the FCC 

postreating unit present in each refinery. The vendor estimates submitted for revamp costs were 

based on various FCC postreater design volumes ranging from 10,000 BPSD to 45,000 BPSD 

depending on the base unit size used by the vendor. To determine how to apply these vendor 

costs to each refinery, we first calculated each refinery’s maximum FCC naphtha production. 

The maximum production was derived by assuming each refiner runs their FCC unit at its 

maximum nameplate throughput capacity (barrels per stream day) with the FCC naphtha yield 

rates discussed in Section 5.1.3.1.2. After sizing the FCC postreater that would be required for 

each refinery we then scaled the costs given by the vendors using the six-tenths rule as shown in 

Equation 5-4. This is a “rule of thumb” cost estimating tool commonly used for cost estimating 

by the refining and petrochemical industries for estimating the cost of a process unit based on a 

similar unit of differing size. 

Cost to Revamp an FCC Unit= A * (B/C)0.6 

Where: 

 A = Cost Estimate Received from the Vendor 

 B = Size of the FCC Unit in the Refinery 

C = Size of the FCC Unit in the Vendor’s Estimate 

Equation 5-4 Six-Tenths Rule for Estimating Capital Cost 

We also adjusted the costs submitted by the technology providers based on the location of 

each refinery. We assumed that each vendor’s estimate was based on revamping an FCC 

postreater in PADD 3 (Gulf Coast), which is the lowest cost region for installing new capital in 

refineries. The cost for refineries that are not located in PADD 3 were adjusted upwards based 

on a ratio of the cost of refinery capital projects in the PADD in which they are located relative 

to PADD 3. An additional factor was applied to account for the “offsite” costs that are incurred 

when installing new capital in refineries. When vendors provide a cost estimate for their 

technology, this estimated cost is called the inside battery limits (ISBL) cost and it is solely for 

the immediate unit of interest. However, refiners may need to install peripheral capital to 

support the new unit, such as electrical switchgear, a control room, storage for feed, intermediate 

or unit products, and longer than anticipated pipeline runs – these costs are usually considered 

Outside battery limit (OSBL) costs, or offsite costs. In some cases, OSBL costs may include 
5-44

hydrogen and sulfur plant costs, although, for our analysis, we separately estimated the cost for 

providing additional hydrogen and for processing the removed sulfur and included this cost in 

our cost analysis. Based on feedback from our peer reviewers, for the FRM analysis, we 

increased the grassroots and revamp offsite cost factors for desulfurization units significantly to 

1.35. 

To reflect the capital costs in the per-gallon costs, we amortize the capital costs over the 

volume of gasoline produced. The Office of Management and Budget (OMB) set guidelines 

how this is to be done. The capital costs are to be amortized assuming a before-tax 7 percent 

return on investment (ROI), which OMB believes reflects the societal cost of complying with 

environmental regulations. Using this criterion, we derived a capital amortization factor which is 

0.11. Thus, the aggregate capital costs are multiplied times the capital amortization factor to 

derive a yearly capital cost charge. Also in the OMB guidelines, OMB stated that the program 

costs should be estimated based on how the industry would assess costs to achieve a payback on 

capital invested. For a capital payback cost analysis, we assessed costs assuming an after-tax 10 

percent ROI. For the capital payback cost analysis, we derived a capital amortization factor 

which is 0.16. The other relevant factors we used in deriving the capital cost amortization 

factors are: a 10 year depreciation life, a 15 year economic life and 39 percent federal and tax 

rate. 

These cost factors, as well as the utility prices that we used in our refinery-by-refinery 

cost model, are shown in Table 5-24: 

Table 5-24 Cost Factors for Various PADDs 

PADD 1 PADD 2 PADD 3 PADD 4 PADD 5a

Capital Cost Factor 1.5 1.3 1.0 1.4 1.2

Natural Gas ($/MMBTU) 8.91 7.77 6.31 6.78 7.69

Electricity (¢/kW-hr) 8.66 6.17 5.87 5.36 8.83

Steam ($/1,000 lb) 20.56 17.89 14.23 17.03 17.24

Offsite Capital Cost Factor –

New Units

1.35 1.35 1.35 1.35 1.35

Offsite Capital Cost Factor –

Unit Revamps

1.35 1.35 1.35 1.35 1.35

Capital Amortization Factor 

Before Tax 7% ROI

0.11 0.11 0.11 0.11 0.11

Capital Amortization Factor

After Tax 10% ROI

0.16 0.16 0.16 0.16 0.16

a

 Excluding California 

The volume-weighted cost estimates for revamping FCC postreaters across the entire 

refining industry as calculated by our refinery-by-refinery model are shown in Table 5-25 and 

Table 5-26. These costs are aggregated cost estimates for the FCC revamp costs used in our 

refinery-by-refinery model. In our model, we paired vendor cost data with refineries that are 

already using that particular vendor’s technology for their FCC postreating units. We further 

tailored the information provided by the vendors to match the specific refinery configuration to 

the extent possible. We assumed that the data provided by the vendors includes the cost for 
5-45

complying with the applicable stationary emission standards and that any incidental costs for 

permitting, if necessary, are negligible and covered by the offsite factor. The information that 

we received from the vendors and the individual refinery capital costs, however, cannot be 

shown due to CBI concerns. 

Table 5-25 Revamp Cost for a 30,000 BPSD FCC Postreater for 10-ppm Standard 

FCC Feed Sulfur Levela0 – 400 ppm 400 – 1,200 ppm >1,200 ppm Volume Weighted 

Average b

Capital Cost ($/B ISBL) 294 214 592 334

Hydrogen (scf/bbl) 46.3 51.3 58.5 42.0

Fuel Gas (kBTU/bbl) 8.5 7.6 3.1 5.3

Electricity (kWh/bbl) 0.10 0.12 0.51 0.17

Octane Loss (R+M)/2 0.68 1.00 0.93 0.77

Olefin Decrease (vol%) 2.44 2.57 1.31 1.89

Catalyst Cost ($/B) 0.02 0.03 0.02 0.02

Steam (lb/bbl) 6.23 6.96 19.86 6.25

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

kilowatt-hours per barrel; (R+M)/2 = (research octane + motor octane)/2; vol% = volume percent; $/B = dollars per 

barrel; lb/bbl = pounds of steam per barrel of feed. 

b

 Of the refineries that are expected to revamp their FCC naphtha hydrotreater for the no ABT case, 28 have FCC 

naphtha sulfur levels in the 0 – 400 ppm range, 30 have FCC naphtha sulfur levels in the 400 – 1200 ppm range and 

17 have FCC naphtha sulfur levels greater than 1200 ppm. 

Table 5-26 Revamp Cost for a 30,000 BPSD FCC Postreater for 5 ppm Standarda

FCC Feed Sulfur Level 0 – 400 ppm 400 – 1,200 ppm >1,200 ppm Volume Weighted 

Average

Capital Cost ($/B ISBL) 470 530 652 487

Hydrogen (scf/bbl) 39.3 64.9 55.3 45.69

Fuel Gas (KBTU/bbl) 13.36 3.07 4.45 5.53

Electricity (kWh/bbl) 0.23 0.47 0.51 0.33

Octane Loss (R+M)/2 0.97 1.10 1.04 0.94

Olefin Decrease 1.45 2.46 2.12 1.82

Catalyst Cost ($/B) 0.02 0.03 0.02 0.02

Steam (lb/bbl) 29.17 6.96 19.86 12.71

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

We also found that there were 16 refineries that had an existing FCC postreaters that 

were not sized large enough to process their maximum FCC naphtha production volume. For 

these refineries we assigned additional capital costs to debottleneck the existing first stage 

reactor in order to increase the postreater capacity so that it could accommodate maximum FCC 

naphtha production. For each refinery with an existing unit that could not process more than 70 

percent of our estimate of a refiner’s maximum FCC naphtha production we added capital costs 

to revamp and expand the first stage to increase its capacity to allow the postreater to process 

100 percent of its maximum FCC naphtha rate. For the capital costs for this debottlenecking we 

used 35 percent of the cost of a new grass roots unit (discussed below) for the volume of the 

expansion. We once again used the six-tenths rule to adjust the capital cost for the volume 
5-46

expansion needed versus the cost for the 30,000 BPSD grass roots treater used for technology 

vendor estimates. 

5.1.3.5.2 Cost for Grassroots FCC Postreaters 

While all refineries that already have FCC postreaters should be able to meet the Tier 3 

standards by revamping their existing postreaters, refineries that do not currently have an FCC 

postreater would have to add a grass roots FCC postreater. To determine the cost of building 

grass roots FCC postreating units at a refinery we similarly requested cost estimates from 

vendors. Only one of the vendors that supplied FCC postreating equipment submitted 

information on the cost of a grass roots FCC postreating unit for desulfurizing FCC naphtha with 

a feed sulfur content of 100 ppm. Based on the calculation methodology shown in Equation 5-2, 

we estimate that refineries that require a grass roots postreater will already have an FCC feed 

sulfur level that averages between 85 and 100 ppm as these refineries already have FCC feed 

pretreaters. The other grassroots vendor estimate we received, as well as those we received for 

Tier 2, represented a grass roots postreater with an FCC feed sulfur content of about 800 ppm. 

These estimates were deemed to be not representative of the costs to refineries that would be 

installing grass roots postreating units as the capital, hydrogen, and other operating costs would 

be much higher for an FCC feed sulfur of 800 ppm vs. 100 ppm. We did not consider this other 

vendor’s cost estimate for a grass roots postreater and therefore relied on a single vendor’s cost 

estimate for grass roots FCC postreating units for the Tier 3 program. In our FRM analysis we 

expanded our analysis for the vendor’s cost estimate of a new standalone unit by incorporating 

additional cost information from other vendors and literature sources on new units. Based on 

this other information, the cost estimate we obtained for a new Tier 3 unit, seemed reasonable 

relative to the other cost data that we have for higher levels of desulfurization. 

The vendor estimate submitted for a grass roots postreater was based on a postreater with 

a capacity of 30,000 BPSD capable of producing an FCC naphtha with a sulfur level of 10 ppm, 

corresponding to a gasoline sulfur level of 5 ppm. To scale the cost submitted by the technology 

vendor to be applicable to a specific refinery, we used a similar methodology to that which was 

used for postreater revamps. We first determined the appropriate size for each unit based on 

each refiners maximum FCC naphtha production rate. We then used the six-tenths rule 

(Equation 5-4) to scale the cost reported by the vendor up or down as appropriate based on the 

relative volume of the grass roots unit required by the refinery and the size on which the 

vendor’s cost estimate was based. We once again assumed that the capital cost from the 

technology vendor was representative of a refinery in PADD 3 complying with the applicable 

stationary emission standards. We then adjusted the cost based on the cost of refinery capital 

projects in the PADD in which they are located relative to PADD 3. Finally, we used a new unit 

offsite adjustment factor listed in Table 5-24 to estimate the final cost of a grass roots FCC 

postreater for each refinery. The costs to produce FCC naphtha with a sulfur level of 25 ppm 

(corresponding to a 10-ppm gasoline) were estimated based on the grass roots postreater unit that 

makes FCC naphtha for the 5-ppm standard. These costs are summarized in Table 5-27 and 

Table 5-28 below. 
5-47

Table 5-27 

Cost for a 30,000 BPSD Grass Roots FCC Postreater for 10-ppm Standard 

FCC Feed Sulfur Level 100 ppm

Capital Cost ($/B ISBL) 1500

Hydrogen (scf/bbl) 94.2

Fuel Gas (KBTU/bbl) 7.5

Electricity (kWh/bbl) 1.06

Octane Loss (R+M)/2 0.83

Olefin Decrease 4.02

Catalyst Cost ($/B) 0.04

Steam (lb/bbl) 20.0

Table 5-28 

Cost for a 30,000 BPSD Grass Roots FCC Postreater for 5-ppm Standard 

FCC Feed Sulfur Level 100 ppm

Capital Cost ($/B ISBL) 1500

Hydrogen (scf/bbl) 113

Fuel Gas (kBTU/bbl) 9

Electricity (kWh/bbl) 1.06

Octane Loss (R+M)/2 1.00

Olefin Decrease 5.15

Catalyst Cost ($/B) 0.04

Steam (lb/bbl) 20.0

5.1.3.5.3 Adjustments to Vendor Costs for Atypical Levels of 

Desulfurization 

The information that we obtained from the vendors estimated the desulfurization cost for 

a typical refinery which is reducing its gasoline sulfur from 30 ppm to 10 ppm, or 5 ppm. Since 

the refiner would need to reduce the sulfur in its FCC naphtha, we estimated that for a typical 

refinery, the refiner would need to reduce its FCC naphtha by 50 ppm for 10 ppm gasoline, or 

reduce its FCC naphtha by 65 ppm for 5 ppm gasoline. However, even if every refinery were 

reducing its gasoline sulfur from 30 ppm to 10 or 5 ppm, because FCC naphtha comprises a 

different fraction of the gasoline pool, refineries would need to desulfurize their FCC naphtha 

different amounts. Added to this, under Tier 2, US refineries produce gasoline which ranges 

from well under 10 ppm and up to the cap at 80 ppm. Thus, to best model the cost for each 

refinery, we needed to develop a strategy for adjusting the desuflurization cost to capture the cost 

for desulfurizing FCC naphtha different increments than the 50 or 65 ppm that the vendor data is 

based on. 

We reviewed desulfurization curves from desulfurization vendors for desulfurizing FCC 

naphtha. The curves show that the octane loss for desulfurizing FCC naphtha is fairly linear 

when the desulfurization severity is below a certain point. Thus, if a particular vendor estimated 

a 0.5 octane number loss for a 50 ppm sulfur reduction in the FCC naphtha, we assumed that if a 

particular refinery would require a 100 ppm sulfur reduction, then the octane loss would be 1 
5-48

octane number. Similarly, if that refinery would only require a 25 ppm reduction in the FCC 

naphtha, then the octane number loss would be 0.25 octane numbers. Since hydrogen is 

consumed to saturate the olefins that leads to the octane loss, we scaled hydrogen in the same 

manner. We, however, didn’t scale utility demands, but rather assumed that the estimated utility 

demands are the same regardless of the change in sulfur required. 

Above a certain desulfurization severity point, the octane loss seems to increase in an 

exponential manner, and if we did not account for this we would be underestimating the 

desulfurization cost for some refneries. The point at which that occurs seems to depend on the 

capital investment made to hydrotreat the FCC naphtha. For example, if a refinery has a one 

stage reactor and it uses distillation to separate the light FCC naphtha, the cost curves suggest 

that the octane loss for this hydrotreater would begin to increase exponentially when the percent 

desulfurization exceeds 93 – 96%. For complying with Tier 3, we assume that many revamps 

fall into this category. Alternatively, FCC postreaters which are two stage units do not seem to 

reach the point where the octane loss begins to increase exponentially until the percent 

desulfurization is in the high 90s, such as 98% or 99%. We asked one of the 

hydrodesulfurization vendors which licenses an FCC postreating technology where to draw the 

line between linear and nonlinear octane loss, and the vendor suggested at 99% desulfurization 

and we used that value in our cost model. 

5.1.3.5.4 Light Straight Run and Natural Gas Liquids 

Desulfurization Costs 

Another action refiners may need to take to reduce the sulfur content of their gasoline is 

to desulfurize their light straight run naphtha (LSR) and natural gas liquids (NGL) blendstocks. 

While these blendstocks have lower sulfur contents than the FCC naphtha, in some cases, the 

sulfur levels may still be too high and it would be cheaper to desulfurize than FCC naphtha for 

refineries that are not already treating these streams. Many refineries have been desulfurizing 

some or all of these blendstocks using extraction desulfurization technologies, such as Merox or 

Merichem, due to the very strong odor of the mercaptans. The extraction desulfurization 

technologies can usually reduce the sulfur levels of LSR and NGL by about 2/3rds by removing 

most of the mercaptans. One third of the sulfur is not removable by these technologies either 

because the sulfur compounds are thiophenes or are heavier mercaptans, which cannot be 

extracted using these technologies. If refiners find that they need to resort to hydrotreating 

because the sulfur levels are too high, they may be able to use existing excess hydrotreating 

capacity in their naphtha hydrotreaters or FCC naphtha postreaters. Additionally, as opposed to 

hydrotreating FCC naphtha which contains olefins, the LSR and NGL blendstocks contain no 

olefins and therefore, hydrotreating them does not result in octane loss and has a lower hydrogen 

consumption. The combination of the potential for using excess capacity in existing units and 

low operating costs result in the relatively low desulfurization costs for the LSR and NGL 

blendstocks. From our discussions with refiners, several refineries indicated that they would 

install new standalone hydrotreaters for processing LSR and NGL blendstocks, though it is 

unclear which other refineries will have to add equipment to desulfurize LSR and NGL. To 

determine the cost to desulfurize the LSR and NGL blendstocks we first had to determine the 

volume of blendstock that requires desulfurization. Our determination of the quantity of LSR 

and NGL used as gasoline blendstock at each refinery is discussed in Section 5.1.3.1.5. From 

this total we then subtracted the volume of LSR processed in the isomerization unit. Because the 
5-49

isomerization units require a low sulfur feedstock we assume that refiners with isomerization 

units are treating all the light straight run naphtha in the naphtha hydrotreater. Refiners likely 

determine how they desulfurize their naphtha depending on whether they have an isomerization 

unit. If a refinery has an isomerization unit, the refiner likely hydrotreats the straight run naphtha 

before sending the stream to a splitter, after which the heavy straight run naphtha is sent to the 

reformer while the light straight run naphtha is sent to the isomerization unit. If a refinery does 

not have an isomerization unit, the refiner likely sends the straight run naphtha to the splitter and 

afterwards, the heavy straight run naphtha is sent to the naphtha hydrotreater before it is 

reformed, while the light straight run naphtha is blended directly into the gasoline pool. 

We also evaluated the likely sulfur level of LSR associated with crude sulfur level. Table 

5-29 summarizes the name of the crude oil, the total sulfur level and sulfur level of the LSR from 

a crude assay (or in the case of Bakken and Eagle Ford fracked crude oil, data was provided by a 

peer reviewer), and the expected sulfur level of the LSR after using extractive desulfurization. 
5-50

Table 5-29 Sulfur of LSR associated with Crude Sulfur Level 

Crude Oil Name Crude Oil Sulfur 

Level (wt%)

LSR Sulfur Level 

(ppm)

LSR Sulfur Level 

after Extracting Sulfur 

(ppm)

Alaskan North Slope 1.04 26 9

Kern River 1.1 330 109

Ecuador Export 1.0 10 3

Saudi Heavy 2.82 6 2

Saudi Light 1.8 200 66

Saudi Medium 2.32 108 36

West Texas 

Intermediate 0.28 0 0

Bonny Light 0.11 48 16

Bow River 2.96 65 21

Cabinda 0.1 5 2

Maya 3.04 50 17

Canadian Interprov. 0.37 0 0

West Texas Sour 1.57 1510 498

Bakken 0.15 4 1

Eagle Ford Light 0.01 1 0

Eagle Ford Heavy 0.12 10 4

Table 5-29 shows that lower sulfur crude oils tend to have very low sulfur LSR when 

extractive desulfurization is factored in. In fact, for crude oils with less than 1 percent sulfur, 

there is only one crude oil where the LSR contains more than 5 ppm sulfur after extractive 

desulfurization is accounted for, and that is Bonny Light. However, imported light crude oils 

such as Bonny Light (which is imported from Nigeria) are likely being displaced by domestically 

fracked crude oils such as Bakken or Eagle Ford, the LSR of which is very low in sulfur. Based 

on this data, we assumed that refiners would solely rely on extractive desulfurization for 
5-51

desulfurizing their LSR under Tier 3 if the crude sulfur being refined at their refineries was 

below 1 percent sulfur. 

The next step in our assessment of the desulfurization costs of the LSR and NGL 

blendstocks was to estimate the extent to which higher sulfur LSR (refineries with crude oil 

sulfur levels above 1 percent and without an isomerization unit) is already being treated at 

refineries to meet the existing Tier 2 sulfur standards. Based on our discussion with refining 

consultants, vendors and refiners, it appears that in response to the Tier 2 standards refiners have 

altered their operations to use excess capacity in their FCC naphtha postreaters and naphtha 

hydrotreaters to reduce the sulfur content of LSR and NGL blendstocks. Since information on 

the extent to which these streams are currently being hydrotreated is not publicly available we 

estimated these volumes using the capacities of the FCC postreaters and reformer feed 

hydrotreaters under normal refiner crude throughputs and yields from the refinery-by-refinery 

model. 

We evaluated each refinery’s capacity to hydrotreat LSR and NGL using existing 

equipment by first determining the volume that can be processed in their naphtha hydrotreaters. 

We compared the throughput volume of each refinery’s naphtha hydrotreater with the calendarday capacity of that unit. The difference between the two represented the available capacity of 

that unit. If a refinery had insufficient excess capacity in their naphtha hydrotreater to treat all of 

the LSR and NGL volumes we next determined if there was excess capacity in that refinery’s 

FCC postreater. We allowed LSR and NGL to be processed using excess FCC postreating 

capacity in refineries where the capacity of the FCC postreater exceeds 120 percent of that 

required to process a refinery’s maximum FCC naphtha yield as determined by the refinery-byrefinery model. Several refiners had excess FCC postreating capacity available for the treating 

of LSR or NGL feedstocks, as the capacity of most FCC postreaters was less than 120 percent of 

the maximum FCC naphtha production rate. We assumed that refiners are currently using any 

excess hydrotreating capacity in their naphtha hydrotreating and FCC postreating units to 

desulfurize LSR and NGL in response to the Tier 2 sulfur standards. 

If a refinery did not have sufficient excess hydrotreating capacity for all of the LSR and 

NGL in these units we assumed the refinery would have to either revamp their existing 

equipment or add new hydrotreating capacity. If the additional capacity needed at any given 

refinery exceeded the existing naphtha hydrotreater capacity by less than 30 percent we assumed 

the necessary capacity could be added by revamping the existing unit. If, however, the additional 

capacity required exceeded the existing reformer feed hydrotreater capacity by more than 30 

percent we assumed the refinery would install a new stand-alone hydrotreater to desulfurize the 

excess LSR and NGL. Based on available capacity in our refinery-by-refinery model and 2010 

and 2011 refinery unit throughput data, we estimated that refiners are already hydrotreating 66 

percent of the LSR and NGL that are directly blended into gasoline (excluding LSR processed in 

the isomerization units). The results of this assessment are shown in Table 5-30. 
5-52

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

New Hydrotreater 

(No FCC Unit)

New Hydrotreater 

(with FCC Unit)

Revamped 

Hydrotreater 

(No FCC Unit)

Revamped 

Hydrotreater 

(with FCC Unit)

Number of 

Refineries 4 11 1 7

We conservatively evaluated the capital cost required for hydrotreater revamps and new 

units by assuming that refiners will size their hydrotreater equipment needs to treat all production 

volumes of LSR and NGL based on each refinery’s maximum crude run rate. The operating 

costs used in our refinery-by-refinery model, however, are based on LSR and NGL blendstock 

volumes from the model’s yields based on 2011 operational crude throughputs and crude oil 

quality as discussed in Section 5.1.3.1.5. Sizing the equipment this way allows each refiner to 

have excess hydrotreater capacity utilization, which is beneficial in the event of process unit 

shutdowns and to reprocess blendstocks from abnormal operations. 

Our estimate for the cost of adding a new hydrotreater at a refinery was obtained from 

Gary and Handework’s Petroleum Refining Technology and Economics, page 182-183, Curve C, 

Table 9.1, 30,000 BSD unit. The capital cost for a grass roots hydrotreater listed by this source 

was for a hydrotreater with a capacity of 30,000 BPSD and was based on 1999 dollars. We 

multiplied this cost by 1.534 to determine the equivalent cost in 2010 dollars based on the 

relative increase in the Nelson Refining Construction index from 1999 to 2010 (listed as 1497 

and 2296 respectively). We used the six-tenths rule to scale the capital cost listed in Petroleum 

Refining Technology and Economics to those of differing capacities based on relative size of the 

desired unit. We assumed a hydrogen consumption of 40 SCF/Bbl for the processing of LSR 

and NGL blendstocks which we obtained from the Jacobs Refining LP modeling database for 

naphtha hydrotreating as this information was not presented in the literature source. For 

refineries that only required a revamp of existing units we assumed a capital cost equivalent to 

40 percent of the cost of a new hydrotreating unit of equal size. We assumed equivalent 

operating costs for new hydrotreating units and revamped units. The capital and operating costs 

for these hydrotreating units that were used in our model is shown in Table 5-31. 
5-53

Table 5-31 Capital and Operating Costs for LSR and NGL Hydrotreaters 

New Hydrotreating Units Revamped Hydrotreating Units

Capital ($/BBL ISBL) 1380 550

Hydrogen (SCF/BBL) 40 40

Fuel Gas (kBTU/BBL) 100 100

Electricity (kWh/BBL) 2.0 2.0

Octane Loss (R+M)/2 0.0 0.0

Change in Olefins (vol%) 0.0 0.0

Steam (lb/BBL) 6.0 6.0

Catalyst Cost ($/BBL) 0.03 0.03

5.1.3.5.5 Using FCC Pretreaters to Comply with Tier 3 

5.1.3.5.5.1 FCC Pretreater Sulfur Control Cost 

We also assessed the cost of utilizing an existing FCC pretreater to comply with Tier 3. 

To understand the feasibility and estimate the cost for using FCC pretreaters to comply with Tier 

3, we conducted a literature survey and spoke to vendors and refiners. In our literature search 

and conversation with vendors, we found that the feasibility and cost for using current FCC 

pretreaters for complying with Tier 3 is dependent on many factors. These factors include the 

pressure of the FCC pretreater, the current turnaround schedule of the unit, the price of natural 

gas used to produce hydrogen for the unit, the crude oil sulfur level which determines the sulfur 

level of the gas oil feed, the percent desulfurization that must be achieved to comply with Tier 3, 

the refiner’s future product marketing plans, and whether the refiner is willing to spend capital 

dollars to revamp the existing unit. Since we don’t know the response to these issues that we 

identified, we found it useful to conduct several different cost assessments to estimate the costs 

for a range of situations that different refiners may be in with their FCC pretreaters. 

FCC pretreaters hydrotreat the gas oil which boils in the range of 690F to 1000F. FCC 

pretreaters enable greater production of FCC naphtha by the FCC unit by saturating aromatic 

compounds in the gas oil. These saturated aromatic compounds can be cracked more easily 

which allows the FCC unit to produce more FCC naphtha. Even before the Tier 2 gasoline 

standards were put in place, many refiners installed FCC pretreaters to increase the production of 

FCC naphtha. To comply with Tier 2, more refiners installed FCC pretreaters, not only because 

the refinery was able to comply with Tier 2 by hydrotreating the feed to the FCC unit, but also 

because refiners were able to realize a return on investment by producing more FCC naphtha 

(increase gasoline production). FCC pretreaters also improve the quality of the light cycle oil, a 

diesel fuel blendstock, which is produced by the FCC unit. 

Some refiners who installed FCC pretreaters for Tier 2 installed repurposed reactors 

which were originally installed for other purposes and these can affect a refiner’s ability to 

comply with Tier 3. For example, refiners installed hydrotreaters to hydrotreat residual fuel, but 

found that the hydrotreating catalyst is quickly diminished by the high metal content in residual 

fuel. Refiners then reused the very high pressure (2000+ psi) reactors as their FCC pretreaters. 

Other refiners repurposed diesel fuel hydrotreaters as FCC hydrotreaters and put in higher 

pressure diesel hydrotreaters when the diesel fuel sulfur standards took effect. The repurposed 
5-54

diesel fuel hydrotreaters were likely low pressure (i.e. 600 pound per square inch (psi)) units. 

While refiners constructing a grassroots FCC pretreater would target a 3 to 4 year cycle length 

and a higher pressure unit (i.e. 1400 psi), if a refiner instead repurposed an existing reactor for its 

FCC pretreater, the cycle lengths of its FCC pretreater may be shorter, and the unit’s pressure 

could be lower pressure, than desired. As we discuss in section 4.2.3.1, refiners with low 

pressure FCC hydrotreaters are likely limited in their ability to use those units for complying 

with Tier 3. If refiners are currently experiencing short cycle lengths with their FCC pretreaters, 

the cost and inconvenience of even shorter cycle lengths would likely deter any refiner from 

using existing FCC pretreaters to comply with Tier 3 without adding additional reactor volume. 

In conducting our cost analysis, we based our cost analysis on a refinery which is solely 

using an FCC pretreater today to comply with Tier 2. We assume that this unit currently requires 

a turnaround every two years. From EIA data for that refinery, the throughput to the FCC 

pretreater is 75,000 bbl/day and the total gasoline volume is a little more than over twice that 

volume. Our refinery-by-refinery model estimates that this refinery is achieving about 92% 

desulfurization of the FCC feed, which allows the refinery to reduce its FCC naphtha to about 80 

ppm. To comply with Tier 3, the refinery would need to achieve about 98% desulfurization of 

its FCC feed to comply with Tier 3. 

We analyzed three different pathways that the refiner could take if it were to solely rely 

on its FCC pretreater to further reduce the sulfur of the feed to its FCC unit to comply with Tier 

3. In the first case (Case 1), the refiner solely increases the severity of its FCC pretreater, by 

raising the temperature of the reactor, which further reduces the sulfur of the FCC naphtha. In 

this case we assume that the unit is capable of further saturating aromatics and creating 

additional yield benefits. However, for this first case, the cycle length of the FCC pretreater 

shortens from 2 years to 1 year, so the refiner would have to replace the catalyst in the FCC 

pretreater every year instead of every two years. 

In the second case (Case 2), the refiner revamps the FCC pretreater by adding a second 

reactor, which effectively doubles the reactor volume. This allows the refinery to comply with 

Tier 3, achieve additional yield benefits and still maintain a two year cycle length with its FCC 

pretreater. 

In the third case (Case 3), we assume no additional investments (like Case 1), but in this 

case the refinery is assumed to have a lower pressure FCC pretreater and the FCC pretreter has 

reached its poly-aromatics saturation maximum. Thus, while the FCC pretreater is able to 

achieve the desired desulfurization, it does not realize additional yield benefits. 

The cost factors for increasing the severity or or revamping an existing FCC pretreater 

(for all three cases) are from a National Petrochemical and Refiners Association (NPRA) Annual 

Meeting technical report.16 The report includes yield estimates, hydrogen demands and a capital 

cost for adding additional reactor volume for 90%, 98% and 99% desulfurization. We estimate 

that the refinery we are studying is desulfurizing its FCC naphtha by 92% and we estimate that it 

must desulfurize its FCC naphtha at 98% to comply with Tier 3 (produce 10 ppm gasoline). 

Thus, we used the differences between 90% HDS and 98% HDS in our cost analysis. Table 5-32

summarizes the changes in yield, hydrogen consumption and capital costs for operating an FCC 

pretreater at a higher desulfurization level. 
5-55

Table 5-32 Yield Changes and Other Impacts of Higher Severity FCC Pretreating 

90% HDS 98% HDS Difference

H2S (wt%) 0.1 0.0 -0.1

C2 (wt%) 3.5 3.2 -0.3

C3-C4 (wt%) 17.6 18.7 1.1

Full Range FCC naphtha 

(wt%)

51.5 52.5 1.0

LCO (wt%) 15.7 15.0 -0.7

CSO (wt%) 6.6 5.9 -0.7

Coke (wt%) 5.0 4.7 -0.3

Total 100 100 -

Naphtha Sulfur (ppm) 225 55 170

LCO sulfur (ppm) 3400 900 -2500

LCO cetane index 25.7 26.4 0.7

Hydrogen Addition (wt%) 0.51 0.74 0.23

Capital Cost 61.8 70.3 8.5

To estimate the cost impacts of operating the FCC pretreater at a higher level of 

desulfurization, it was necessary to estimate the costs for the changes in yield, the increased 

hydrogen demand, the cost of additional capital. We used the component cost values for ethane, 

propane and butane, FCC naphtha, light cycle oil (LCO), and cycle slurry oil (CSO) from our LP 

refinery model for the year 2018. The value of hydrogen is from our LP model based on natural 

gas which averages $7.1 per million BTU. The hydrotreating catalyst is estimated to cost $244 

per barrel per stream day. These cost factors are summarized in Table 5-33.
5-56

Table 5-33 Economic Value of Yield Components, Hydrogen and Catalyst 

FCC Product or Reactant Value

C2 ($/bbl FCC) 9.2

C3-C4 ($/bbl FCC) 66.5

Full Range FCC naphtha ($/bbl) 115.6

LCO ($/bbl) 122

CSO ($/bbl) 87

Hydrogen ($/KSCF) based on natural gas at 7.1 

$/mmbtu

4.1

The economic value of the FCC unit yield changes for the three cases is estimated by 

converting the weight percent percentages to volume percent, multiplying each times the FCC 

unit feed, which is 75,000 bbl/day and then multiplying the resulting yield changes in barrels per 

day by the respective economic value of each hydrocarbon product in dollars per barrel. The 

hydrogen is calculated in a similar way. We estimate that the hydrogen consumption 

corresponds to about 300 standard cubic feed per barrel of feed. We multiplied this times $4.1 

per thousand standard cubic feet. The capital costs were inflated from 1999 dollars to 2011 

dollars using Nelson-Farrar inflation index, which increased the capital costs by a factor of 1.63. 

We applied a 20% contingency factor and a 35% offsite factor. Finally, the costs were scaled 

using the sixth-tenths rule to estimate the cost for the refinery unit processing 75,000 bbl/day. 

For Cases 1 and 3, we estimate that the FCC pretreater must be shutdown every year 

instead of every two years. Based on information shared to us by one vendor for a 35,000 barrel 

per day unit, the lost production due to the shutdown is estimated to cost $150,000/day for 5 

weeks, the catalyst is estimated to cost $5 million to fill the reactor, and an additional $1.5 

million cost is added to represent the maintenance cost during the shutdown. To estimate the 

cost for a 75,000 bbl/day unit these costs were scaled by a factor of 75,000 over 35,000. The 

catalyst cost is also used for Case 2 for filling the added reactor volume. 

Table 5-34 contains the results of the cost analysis for each of the three cases analyzed. 
5-57

Table 5-34 Cost for Different FCC Pretreater Scenarios for Complying with Tier 3 

Case 1

Higher Severity

Case 2

Revamp

Case 3

Higher Severity at 

Aromatics Peak 

Saturation

Yield Cost ($/bbl) -1.1 -1.1 0

Catalyst and 

Turnaround Cost 

($/bbl FCC feed)

0.47 0.23 0.47

Hydrogen Cost ($/bbl

FCC feed)

1.2 1.2 1.2

Capital Cost ($/bbl

FCC feed)

- 0.18 -

Fixed Cost ($/bbl

FCC feed)

- 0.11 -

Total Cost FCC Feed 

($/bbl)

0.59 0.64 1.7

Total Cost All 

Gasoline ($/bbl)

0.27 0.29 0.77

Total Cost All 

Gasoline (c/gal)

0.65 0.71 1.8

Our analyses of the three different cases summarized in Table 5-34 shows that achieving 

additional yield gain is an important factor for achieving further sulfur control at a low cost. For 

the cases which assume additional yield gain, we estimate a cost of about 0.3 dollars per barrel, 

or about 0.7 cents per gallon when the costs are amortized over the refinery’s entire gasoline 

pool. The estimated total capital cost for the revamp case is $44 million. For the case which 

assumes no additional yield gain, our estimated cost is about 1.8 cents per gallon. These costs 

may be overstated somewhat because we are not accounting for the further desulfurization and 

cetane improvements of the light cycle oil, which is a diesel fuel blendstock. We estimate that if 

this refinery were to install a grassroots FCC postreater for complying with Tier 3 instead of its 

FCC pretreater, the grassroots postreater is estimated to cost 1.45 c/gal and need to invest $109 

million in capital. Thus, our cost analysis estimates that if a refinery were to revamp its FCC 

pretreater or simply turn up the severity of its FCC pretreater and expect to achieve additional 

yield benefits in addition to lower FCC naphtha sulfur levels, then it would do so based on costs, 

as opposed to installing a grassroots FCC postreater. 
5-58

5.1.3.5.5.2 Would Refiners use FCC Pretreaters to 

Comply with Tier 3? 

The decision to rely solely on FCC pretreating to comply with Tier 3 is more complicated 

than simple economics. If the refinery solely relies on an FCC pretreater to comply with Tier 3, 

the refinery will not gain the operational flexibility of having both an FCC pretreater and 

postreater would provide (if one of those units suffers an emergency shutdown, the other unit 

would allow the refiner to continue to use the FCC unit to blend up its gasoline and still comply 

with the cap standard). If the refiner were to revamp its FCC pretreater, it would roughly 

maintain the operational flexibility that it currently experiences under Tier 2, although it would 

be somewhat lower due to the higher desulfurization that would have to be maintained and the 

more stringent sulfur standard that the refiner would have to comply with. If a refiner chooses to 

solely increase the severity of its FCC pretreater for complying with Tier 3, which would reduce 

the cycle length of its FCC pretreater, the refiner would have lower operational flexibility since 

the unit would need to shutdown more frequently. 

Refiners may have sacrificed some of their operational flexibility when complying with 

Tier 2 by turning up the severity of its FCC pretreater, and therefore may already be 

experiencing shorter turnaround times with its FCC pretreaters than desired. If this is the case, 

then when investing for Tier 3 the refiner may choose to add additional reactor volume when 

revamping its pretreater to lengthen the FCC pretreater turnaround times. This additional 

investment would be justified if the refiner would offset the increased capital costs by lower 

turnaround costs. This same investment strategy could occur if the refiner intends on installing a 

grassroots postreater. The refiner would design the postreater to take over some of the 

pretreater’s desulfurization duty which would allow for lengthening the turnaround times for the 

FCC pretreater. 

Another consideration of refiners contemplating relying solely on FCC pretreating to 

comply with Tier 3 is the coke make on the FCC catalyst and how it would affect the FCC unit 

operations. As shown in Table 5-32, coke make in the FCC unit decreases as the percent 

desulfurization by the FCC pretreater increases. As the amount of coke which forms on FCC 

catalyst decreases, there would be less heat created in the FCC unit regenerator. The lower heat 

generation in the FCC regenerator can apparently be addressed by increasing the catalyst flow 

between the reactor and regenerator, but if the catalyst control valve must be opened too much to 

control the FCC temperature balance, an FCC control issue can develop which potentially could 

cause operational problems that would force a shutdown of the FCC unit. To counter this, the 

refiner may have to operate their FCC pretreater at the poly aromatics saturation maximum 

temperature to preserve coke make. However, in operating in maximum poly aromatics 

saturation mode, the refinery would not realize the yield gains and would face higher 

desulfurization costs. 

One more consideration that refiners could have about relying on FCC pretreaters for 

complying with Tier 3 is the price of natural gas, which essentially determines the production 

cost for producing hydrogen. FCC pretreaters demand a lot of hydrogen and low natural gas 

prices support a desulfurization strategy that uses FCC pretreating. We are aware that several 

US liquid natural gas (LNG) export projects have been approved to export natural gas to the rest 

of the world. Although natural gas prices are projected to stay low, if refiners are concerned that 
5-59

increased exports of natural gas from the US could cause US natural gas prices to double or even 

triple, which is roughly what the rest of the world pays for natural gas, it would significantly 

increase the cost of FCC pretreating compared to FCC postreating. This could cause refiners to 

choose to add an FCC postreater instead. 

One more strategy that a refiner could pursue would be to convert the FCC pretreater to a 

mild hydrocracker. This strategy involves a lot more investment to allow for fractionating the 

product after the hydrocracking reactor. For two reasons, the potential level of hydrocracking is 

often limited. First, the FCC unit requires on the order of 50 percent of its maximum capacity to 

permit the unit to operate. If the FCC pretreater were to be converted over to a high conversion 

hydrocracker, there may not be sufficient feed for the FCC unit. Second, many FCC pretreaters 

are not sufficiently high in pressure to permit its conversion to a high conversion hydrocracker. 

We believe that the increased demand for diesel fuel will already cause refiners to convert their 

FCC pretreaters over to mild hydrocrackers, so we did not pursue this as part of a Tier 3 strategy, 

although we did include a sensitivity case for which we estimated the compliance cost to Tier 3 

assuming lower feed rates to FCC units if FCC pretreaters are converted over to mild 

hydrocrackers. 

Based on the low estimated cost for Case 1 and Case 2 that we evaluated for relying on 

FCC pretreaters to comply with Tier 3, we could have included FCC pretreater modifications in 

our cost analysis for Tier 3. For several different reasons we decided not to. First, we assessed 

the use of credits under Tier 2 and found that the sulfur credits are freely traded between refining 

companies. When we assumed nationwide credit trading, the ABT program effectively 

eliminated most of the need to install grassroots postreaters which would be installed at these 

refineries currently using FCC pretreating for Tier 2 and are thus the candidates for using FCC 

pretreaters to comply with Tier 3. Thus, even if we included options for using existing FCC 

pretreaters to comply with Tier 3, it may not actually be the most economical option available to 

these refiners given the flexibility of the ABT program. 

A second reason why we did not include in our cost estimates the revamp of existing 

FCC pretreaters for complying with Tier 3 is the uncertainty of how each pretreater is operated 

today and how it would operate when complying with Tier 3. We don’t know the current 

turnaround schedule for each refinery’s FCC pretreater, nor do we know their operating pressure, 

thus, we don’t know how these units would operate at higher severity, nor if refiners would add 

reactor volume or just increase their severity. We also don’t know what the coke-make is on the 

FCC catalyst at these refineries that rely on FCC pretreaters for Tier 2 and how a refiner would 

operate its FCC pretreater if insufficient coke-make would be an issue when operating its FCC 

unit when relying on an FCC pretreater to comply with Tier 3. Furthermore, as discussed above, 

adding a postreater would provide additional compliance flexibility. For these reasons, we did 

not include FCC pretreating as an option for complying with Tier 3 in our cost modeling. While 

we did not model any refineries revamping their existing FCC pretreaters to comply with Tier 3, 

there may nevertheless be some for whom it may be commercially advantageous. If so, this 

would tend to lower the overall costs of the Tier 3 standards compared to our cost analysis 

described in sections 5.1 and 5.2.
5-60

5.2 Estimated Tier 3 Sulfur Control Costs 

5.2.1 Final Fuel Program Cost Results 

We used the refinery-by-refinery cost model to estimate the costs of the 10 ppm average 

standard being adopted in this final rule. The Tier 3 fuels program maintains the 80 ppm cap 

sulfur control standard that was put in place under the Tier 2 sulfur program. In general, the cost 

model indicates that further desulfurizing the FCC naphtha will be the most cost-effective means 

for achieving sulfur control. We accounted for additional costs to refiners for desulfurizing their 

LSR naphtha, for those refineries where we estimate that the LSR naphtha is not being 

desulfurized today and found that it likely needs to be. In addition to analyzing the cost of the 

final Tier 3 fuels program, we also assessed the cost of other possible gasoline sulfur standards 

that we considered for the proposed rulemaking. The cost information for these other gasoline 

sulfur standards that we analyzed is summarized in subsection 5.2.2. 

As described in Section V.D of the preamble and Chapter 4, we are also adopting an ABT 

program that is designed to ease the overall burden on the industry while still achieving the 10-

ppm annual average sulfur standard for the nation as a whole. Under the ABT program, 

refineries that can reduce sulfur below 10 ppm at a relatively low cost can generate credits which 

can then be acquired by refiners for the refineries at which the cost of attaining the 10-ppm sulfur 

standard would be higher. These credits can be traded among refineries within the same 

company, or between refiners and importers nationwide. The net effect of this credit trading 

would be to reduce the overall cost of the program. The extent to which the ABT provisions 

reduce the cost of the Tier 3 program depends on the extent that the ABT program is used by 

refiners. Since we were not sure about the extent that credits were traded under Tier 2 when we 

conducted the cost analysis for the NPRM we conservatively assumed for the NPRM cost 

analysis that refiners would only volume-average sulfur levels among their refineries, and not 

trade credits between refining companies. However, for the final rule cost analysis we evaluated 

the credit trading that was occurring under Tier 2. We found that 56% of credits were in fact 

being traded between refining companies under Tier 2, with the balance being used within 

refining companies. This demonstrated that credit trading was freely occurring between refining 

companies, supporting the conclusion that credit trading would occur nationwide among 

refineries under Tier 3. We therefore assumed nationwide credit trading for our final rule. 

To estimate the impact that the ABT program could have on nationwide average fuel 

costs, we began with the refinery-by-refinery costs for sulfur reductions down to either 10 ppm 

or 5 ppm. We then determined the lowest cost option among three alternatives for each refinery: 

1. The refinery reduces its sulfur to 10 ppm. 

2. The refinery reduces its sulfur to 5 ppm and generates credits for the increment 

between 10 ppm and 5 ppm. 

3. The refinery does not lower sulfur, but instead relies on the purchase of credits to 

comply with the 10-ppm standard. 
5-61

A fourth category applied to refineries whose average gasoline sulfur levels are already 

below 10 ppm (their refineries don’t have FCC units). All such refineries were assumed to 

generate credits for the increment between 10 ppm and their current sulfur level. 

Our methodology was unable to consider a fifth category where a refinery may utilize 

less expensive capital and operational changes to reduce their sulfur levels partially below Tier 2 

levels and rely on purchasing credits only for the remainder. Such opportunities are likely to 

exist at most refineries, but such refinery specific information is not available to us. As a result, 

refineries in the third category are modeled to simply remain at Tier 2 sulfur levels and incur no 

capital or operating cost. 

To simplify the modeling of how an ABT program might operate, we focused on the 

circumstances that refineries would face in the longer term, specifically after 2020. This 

approach meant that the ABT program modeling did not consider the impact on gasoline sulfur 

levels of delayed compliance for small refiners and small volume refineries, nor did it consider 

the generation and use of any early sulfur credits. Moreover, our ABT modeling considered only 

gasoline sold for use outside of California, and only gasoline produced by domestic refineries 

(not importers). 

To model credit trading in our cost analysis, we first establish an estimated cost for each 

refinery for reducing its gasoline sulfur down to 10 ppm and to 5 ppm. Next we ranked the 

sulfur control strategies for all the refineries in order from lowest to highest sulfur control cost 

per gallon of gasoline and estimated the impact of their projected sulfur control strategies on 

refinery sulfur levels using only one cost (either 10 or 5 ppm) for any one refinery. The model 

then follows this ranking, starting with the lowest-cost refineries, and adds refineries and their 

associated control technologies one-by-one until the projected national average gasoline sulfur 

level reaches 10 ppm. This modeling strategy projects the sulfur control technology that will be 

used by each refinery, as well as identifies those refineries that are expected to generate credits 

and those that are expected to use credits in lieu of investing in sulfur control. The sum of the 

costs of the refineries expected to invest in further sulfur control provides the projected overall 

cost of the program. 

Based on the results of our cost analysis, we estimate that for the US refining industry to 

achieve a 10-ppm average level with the full benefit of nationwide credit trading, the final sulfur 

control program would cost on average 0.65 cents per gallon when it is fully phased in, assuming 

that capital investments are amortized at a seven percent return on investment before taxes and 

expressed in 2011 dollars. Refiners would be expected to make $2.025 billion in capital 

investments to achieve this sulfur reduction. These capital investments are expected to be made 

over the 6 years that the Tier 3 program is expected to be phased in, which would spread out the 

capital costs to average about $330 million per year. 

Our cost assessment is likely conservative. The capital cost estimate is based on vendor 

data which assumes that refiners are hydrotreating full range FCC naphtha. If refiners are indeed 

undercutting their FCC naphtha at many refineries (and more will be doing so in the future), 

many refiners would likely not need to make any capital changes. This is because the FCC 

postreaters were designed when refiners were maximizing their gasoline production and 

hydrotreating full range FCC naphtha. When undercutting the FCC naphtha to the diesel pool, 
5-62

refiners are cutting out about 16% of the FCC naphtha volume, but more importantly, they are 

cutting out about half of the sulfur. Thus, if a refiner was able to produce 30 ppm gasoline, after 

fully undercutting their FCC naphtha into the diesel pool, they would likely be able to produce 

15 ppm sulfur gasoline using their existing Tier 2 postreater. They could then use a more active 

catalyst which likely would enable the refinery to achieve 10 ppm gasoline without any capital 

changes to their FCC postreaters. If all refiners were undercutting their FCC naphtha and are 

able to comply with Tier 3 without any capital additions to their FCC postreaters, the cost of the 

program would decrease to about 0.4 c/gal. 

Another way that our modeling could be conservative is that refiners are slowly 

converting their FCC pretreaters over to mild hydrocrackers to produce more diesel fuel, which 

is in higher demand. We don’t know the extent that this is happening, and our current analysis 

assumes that none of the FCC pretreaters have been converted over to mild hydrocrackers. 

However, a cost sensitivity analysis that we conducted with our refinery model estimates that if 

all the FCC pretreaters were converted over to mild hydrocrackers, costs of the Tier 3 program 

would decrease to 0.55 c/gal, assuming nationwide credit trading. If we combined the cost 

reduction of undercutting with the mild hydrocracking, the Tier 3 costs would be lower than 

either of two cost sensitivities which were conducted independently. 

We also received some comments by API and two of the peer reviewers about our octane 

costs. We will not include all the discussion here about octane costs because we do so in detail 

in the response to peer review comments. While we are comfortable with the octane costs that 

we used, we did conduct a sensitivity at a higher octane cost ($0.5/per octane number barrel 

instead of $0.31/octane number-barrel that we used). At the higher octane cost of $0.5/octane 

number barrel, the Tier 3 sulfur control costs increases from 0.65 c/gal to 0.73 c/gal. 

We also estimated annual aggregate costs, including the amortized capital costs, 

associated with the new fuel standard.D When the 10-ppm gasoline sulfur standard is fully 

phased in 2020, we estimate that the sulfur standard would cost $790 million in that year. Figure 

5-1 shows the distribution of refinery costs over the accumulated gasoline volume for the fully 

phased in 10 ppm sulfur standard. 

 

D

 The aggregate annual costs is the estimated per-gallon cost multiplied by the total projected gasoline volume in 

that year. 
5-63

Figure 5-1 Tier 3 Sulfur Control Costs 

Figure 5-1 shows that for almost 20 percent of the gasoline pool, refineries will not incur 

any cost under Tier 3, either because these refineries are already very low in sulfur because they 

don’t have FCC units, or because the refineries are purchasing credits.E For another 10 percent 

of the gasoline pool, the refinery costs are in the 0 – 0.5 cent/gal range. For the next 55 percent 

of the gasoline pool, the refinery costs are in the 0.5 – 1.0 c/gal range. For the last 15 percent of 

the gasoline pool, the refinery costs range from 1.0 to 2.1 c/gal for revamps, with the exception 

of one refinery at 2.8 c/gal representing the cost for the sole grassroots unit which our modeling 

estimates would need to be installed. All other refiners that may otherwise need to install a 

grassroots hydrotreater were able to do so more cheaply through the purchase of credits. 

In addition to assessing the Tier 3 program costs on a societal cost basis which amortizes 

the capital costs on a before-tax 7 percent ROI, we also assessed the program costs based on how 

industry would assess costs to achieve a payback on the capital invested, which amortizes capital 

costs on an after-tax 10 percent ROI. When the capital costs are amortized assuming an after-tax 

10 percent ROI, the per-gallon costs of the final Tier 3 fuels program increases to 0.75 cents per 

gallon. 

Figure 5-2 summarizes our estimated US gasoline sulfur levels over the accumulated 

gasoline volume post Tier 3. 

 

E

 Refineries purchasing credits will incur a cost for the purchase of the credit, but since we don’t know what the 

price of a credit will be, we allocate all the cost for complying with Tier 3 solely on the refineries adding capital and 

incurring operating costs to comply with Tier 3. 
5-64

Figure 5-2 Estimated US Gasoline Sulfur Levels Post Tier 3 

Figure 5-2 shows that over 80 percent of the gasoline pool would predominately be either 

5 or 10 ppm representing the two sulfur levels to which we assumed that refiners would 

desulfurize their gasoline pool. For the rest of the gasoline pool, the refineries are clearly 

purchasing credits and their sulfur levels range from 10 to nearly 70 ppm. As discussed earlier, 

lacking more detailed refinery-specific information, for these refineries we assumed that they 

take no action to reduce their gasoline sulfur below their Tier 2 levels. In reality these refineries 

are likely to take some very cost-effective steps to partially reduce their gasoline sulfur and not 

rely solely on credits to demonstrate compliance with Tier 3. Were we able to model such 

refinery changes, it would only serve to further lower our projected costs. 

5.2.2 Cost of Alternative Fuel Program Standards and Alternative ABT Program 

Assumptions 

In addition to analyzing the cost of the finalized sulfur control program, we also provide 

other gasoline sulfur control cost estimates. In one case we analyzed the cost of the final rule 

program, but assumed that refiners don’t continue to trade credits as freely as they are doing 

under Tier 2, but only trade credits within companies (intracompany) instead. For other cost 

estimates we assessed the cost of 10 ppm but with no ABT program and the cost of a 5 ppm 

sulfur standard with no ABT program. In no case did we assess the cost of a more stringent cap 

standard, but continued to assume that the sulfur cap remained at 80 ppm. 

5.2.2.1 10 ppm Average Assuming Only Intracompany Credit Trading 

Based on the results of our cost analysis, we estimate that for the US refining industry to 

achieve a 10-ppm average level with only the benefit of intracompany credit trading, the final 

sulfur control program would cost on average 0.75 cents per gallon when it is fully phased in, 

assuming that capital investments are amortized at a seven percent return on investment before 
5-65

taxes and expressed in 2011 dollars. Refiners would be expected to make $2.190 billion in 

capital investments to achieve this sulfur reduction. 

We also estimated annual aggregate costs, including the amortized capital costs, 

associated with the new fuel standard. When the 10 ppm gasoline sulfur standard is fully phased 

in 2020, we estimate that the sulfur standard would cost $910 million in that year. Figure 5-3

shows the distribution of refinery costs over the accumulated gasoline volume for the fully 

phased-in 10 ppm sulfur standard which assumes that sulfur credits were solely traded within 

refining companies. 

Figure 5-3 Alternative Sulfur Control Costs - 10 ppm Average Assuming Intracompany 

Credit Trading 

Figure 5-3 shows that for about 15 percent of the gasoline pool, refineries would not 

incur any cost, either because these refineries are already very low in sulfur because they don’t 

have FCC units, or because the refineries are purchasing credits. For the next 65 percent of the 

gasoline pool, the refinery costs are in the 0 – 1.0 c/gal range. For the last 20 percent of the 

gasoline pool, the refinery costs range from 1.0 to 5 c/gal. While the average cost increased by 

just 0.1 cents per gallon compared to the cost based on nationwide trading, the upper end of this 

range is nearly twice that of the maximum cost for nationwide trading. This emphasizes the 

benefits to the program that result from nationwide trading. 

Figure 5-4 summarizes our estimated US gasoline sulfur levels over the accumulated 

gasoline volume post Tier 3. 
5-66

Figure 5-4 Alternative US Gasoline Sulfur Levels - 10 ppm Average Assuming 

Intracompany Credit Trading 

Figure 5-4 shows that for about 90 percent of the gasoline pool would predominately be 

either 5 or 10 ppm representing the two sulfur levels to which we assumed that refiners would 

desulfurize their gasoline pool. For the rest of the gasoline pool, the refineries are clearly 

purchasing credits and their sulfur levels range from 10 to nearly 70 ppm. As discussed earlier, 

lacking more detailed refinery-specific information, for these refineries we assumed that they 

take no action to reduce their gasoline sulfur below their Tier 2 levels. In reality these refineries 

would likely to take some very cost-effective steps to partially reduce their gasoline sulfur and 

not rely solely on credits to demonstrate compliance with Tier 3. 

5.2.2.2 10 ppm Average Assuming No ABT program 

Based on the results of our cost analysis, we estimate that for the US refining industry to 

achieve a 10-ppm average level but with no benefit of credit trading, the final sulfur control 

program would cost on average 0.87 cents per gallon when it is fully phased-in, and with capital 

investments at a seven percent return on investment before taxes and expressed in 2011 dollars. 

Refiners would be expected to make $2.990 billion in capital investments to achieve this sulfur 

reduction. 

We also estimated annual aggregate costs, including the amortized capital costs, 

associated with the new fuel standard. When the 10 ppm gasoline sulfur standard is fully phased 

in 2020, we estimate that the sulfur standard would cost $1060 million in that year. Figure 5-5

shows the distribution of refinery costs over the accumulated gasoline volume for the fully 

phased in 10 ppm sulfur standard. 
5-67

 

Figure 5-5 Tier 3 Sulfur Control Costs 

Figure 5-5 shows that for a small fraction of the gasoline pool, refineries would not incur 

any cost under Tier 3, because these refineries are already very low in sulfur because they don’t 

have FCC units. For about 80 percent of the gasoline pool, the refinery costs are in the 0 – 1

cent/gal range. For the next 55 percent of the gasoline pool, the refinery costs are in the 0.5 – 1.0 

c/gal range. For the last 20 percent of the gasoline pool, the refinery costs range from 1.0 to 8.5 

c/gal. All other refiners that may otherwise need to install a grassroots hydrotreater were able to 

do so more cheaply through the purchase of credits. While the average cost increased by just 

0.22 cents per gallon compared to the cost based on nationwide trading, the upper end of this 

range is about three times higher than that of the maximum cost for nationwide trading. This 

emphasizes the benefits to the program that result from nationwide trading. This cost scenario 

most closely parallels that conducted by Baker & O’Brien for API as discussed below in Section 

5.3, given the stringent per-gallon cap they assumed. This serves to emphasize the cost benefits 

provided by a flexible nationwide ABT program. 

5.2.2.3 5 ppm Average Assuming No ABT program 

Based on the results of our cost analysis, we estimate that for the US refining industry to 

achieve a 10-ppm average level with the full benefit of nationwide credit trading, the final sulfur 

control program would cost on average 1.28 cents per gallon when it is fully phased in, assuming 

that capital investments are amortized at a seven percent return on investment before taxes and 

expressed in 2011 dollars. Refiners would be expected to make $3810 million in capital 

investments to achieve this sulfur reduction. 

We also estimated annual aggregate costs, including the amortized capital costs, 

associated with the new fuel standard. When the 10-ppm gasoline sulfur standard would be 

fully phased in 2020, we estimate that the sulfur standard would cost $1555 million in that year. 
5-68

Figure 5-6 shows the distribution of refinery costs over the accumulated gasoline volume for the 

fully phased in 10 ppm sulfur standard. 

 

Figure 5-6 Alternative Sulfur Control Costs – 5 ppm Average and no ABT Program 

Figure 5-6 shows that for a small fraction of the gasoline pool, refineries would not incur 

any cost, because these refineries would already be very low in sulfur because they don’t have 

FCC units. For another 80 percent of the gasoline pool, the refinery costs are in the 0 – 1.0

cent/gal range. For the last 20 percent of the gasoline pool, the refinery costs range from 1.0 to 

13 c/gal. 

5.2.2.4 Estimated Cost of a 50 ppm Sulfur Cap Standard 

For the NPRM, we co-proposed a 50 ppm sulfur cap along with the current 80 ppm cap 

already in place under the Tier 2 regulations. In doing so, we assumed, based on feedback from 

some refiners, that a 50 ppm cap would not increase the cost of compliance with Tier 3. 

However, we received comments on this assumption from API and other commenters suggesting 

that lowering the sulfur cap might considerably increase the cost of Tier 3 gasoline sulfur 

control. To support their comments, they provided a study they commissioned by Turner, Mason 

and Company (TMC) as discussed further below. 

In response to the comments provided, for the FRM we estimated the cost of a potential 

50 ppm refinery gate sulfur cap standard relative to the current 80 ppm cap standard. We 

identified two potential cost impacts of lowering the cap standard to 50 ppm: 1) some refineries 

that could maintain their sulfur levels at higher levels under Tier 3 with a 80 ppm cap standard 

would have to reduce their gasoline sulfur levels under a 50 ppm cap, and 2) some refineries may 

need to invest in additional tankage to store high sulfur FCC naphtha if the FCC pretreater or 

postreater has operational problems or needs to shutdown. 
5-69

If the refinery gate cap standard were to be reduced from 80 ppm sulfur to 50 ppm, we 

estimate that refineries which otherwise might avoid capital investment by purchasing credits 

and continuing to produce gasoline above an average of 35 ppm under Tier 3 with an 80 ppm cap 

would need to make a capital investment to avoid having batches of gasoline exceed the 50 ppm 

cap on a regular basis. Refiners cannot produce gasoline which averages the same as the cap 

standard because of the variability in gasoline blendstock and gasoline batch-to-batch sulfur 

content (see Section 4.42). Based on our evaluation of refinery gasoline sulfur levels under the 

Tier 2 program, we found that the average sulfur level for refineries is at or below 70% of the 

cap standard, with the exception of only two refineries. This appears to be about the level 

necessary for most refineries to operate with adequate flexibility. Seventy percent of a 50 ppm 

cap would translate into a maximum average sulfur production level of 35 ppm for refineries. Of 

the 40 refineries which average greater than 35 ppm under Tier 2, our refinery modeling for Tier 

3 estimates that 8 refineries would continue to average above 35 ppm sulfur when the Tier 3 

sulfur standard is fully phased in under the 80 ppm cap standard. For the purpose of estimating 

the cost of the 50 ppm cap standard we assume that these 8 refineries would then need to make 

capital investments to reduce their gasoline sulfur levels. Because our refinery modeling could 

not model partial sulfur reductions in gasoline (i.e., reducing gasoline sulfur from 55 to 35 ppm), 

we estimated that these 8 refineries would reduce their gasoline sulfur levels to 10 ppm. To 

avoid overcomplying with Tier 3, other refineries would then not invest as much which would 

maintain the industry average of 10 ppm sulfur. After modeling these changes in our refinery 

model, we estimate that complying with Tier 3 with a more stringent cap of 50 ppm increases the 

average cost by 0.02 c/gal and increases the overall capital costs at refineries by $135MM. 

The second factor we identified that would increase refinery costs is the potential need to 

add storage at refineries to store high sulfur FCC naphtha, or other high sulfur naphtha, in the 

event that a refinery’s gasoline hydrotreater (pretreater or postreater) were to require emergency 

maintenance. This volume of storage is not intended to store all the FCC naphtha to enable a 

full turnaround of the FCC pretreater or postreater. Instead, it would: 1) provide short-term 

storage for a modest fix to either of these units, 2) permit the refiner to make arrangements for 

storing or selling the FCC naphtha elsewhere until the inoperable hydrotreating unit could be 

made operational, or 3) allow for an orderly shutdown the FCC unit. Based on data that TMC

collected on behalf of API from a survey of refiners, refiners today have on average 4.6 days 

worth of storage for unhydrotreated FCC naphtha to comply with the current Tier 2 standards (an 

average of 30 ppm and a cap of 80 ppm). The affect of a lower cap with Tier 3 would be slight. 

As we describe in Section 5.1.3.2, a Tier 3 refinery’s FCC naphtha is typically 21 ppm assuming 

that FCC naphtha comprises 35% of the refinery’s gasoline pool. However if a refinery’s FCC 

pretreater or postreater needs to be taken off line, the refinery’s FCC naphtha sulfur level could 

increase to hundreds or even thousands of ppm. Assuming that the refinery’s FCC naphtha is 

1000 ppm when the pretreater or posttreater is down, the refiner would only be able to blend less 

than 1% FCC naphtha in its gasoline under either an 80 ppm or a 50 ppm cap, so the cap should 

not fundamentally change the refinery’s situation when the cap standard is at 80 or 50 ppm. 

Either way the refiner needs to find a home for the high sulfur FCC naphtha and they are 

currently doing so with an average of 4.6 days worth of storage. Nevertheless, it is possible that 

some refineries may need to increase their storage capacity for unhydrotreated FCC naphtha in 

response to a lower sulfur cap. 
5-70

We conservatively estimated potential storage need increases with a 50 ppm cap by 

evaluating which refineries might experience lower ratio of cap to average sulfur level under Tier 

3 compared to Tier 2, and therefore have a need for increases storage capacity. To estimate 

which refineries might need more storage we used our modeling results to look at each refinery’s 

situation before and after Tier 3. For example, one refinery’s average sulfur level is 29 ppm 

under Tier 2 and our modeling assumed that this refinery would remain at 29 ppm and purchase 

credits under Tier 3. Under Tier 3 the refinery’s cap to average sulfur level would be 1.6 

(compared to 2.6 under Tier 2). This refinery could experience a greater need for storing high 

sulfur FCC naphtha batches than under Tier 2. On the other hand, if a refinery reduces its 

gasoline sulfur under Tier 3 from 30 ppm to 10 or 5 ppm, the refinery’s cap to average sulfur 

level would be higher under Tier 3 than Tier 2 (assuming a 50 ppm cap standard) and the 

refinery is less likely to need FCC naphtha storage under Tier 3 than under Tier 2. We project 

that after complying with Tier 3 and with a 50 ppm refinery gate standard, 17 refineries would be 

projected to experience lower ratio of cap to average sulfur level under Tier 3 than under Tier 2 

To estimate the potential tankage costs, we assumed that these 17 refineries have no FCC 

storage capacity today and would need to add the full 4.6 days worth. For each of the 17 

refineries, we calculated the volume of FCC naphtha that may be needed to be stored based on 

the maximum FCC naphtha volume capable of being produced (at maximum FCC throughput 

rates) with the FCC unit operating full time over those 4.6 days. We estimated the cost of 

petroleum storage to be $25/bbl for a 250,000 barrel storage tank, which is based on a cost 

estimate we obtained from the Independent Fuel Terminal Association for a gasoline storage 

tank. We applied a 20% contingency factor and a 20% offsite factor to estimate a total installed 

cost. We adjusted this cost to reflect the cost for the appropriate-sized storage tank for each 

refinery using the six-tenths rule (see equation 5-4). Based on the capital cost for adding the 

storage capacity at each of these refineries, we estimated the fixed costs assuming that they 

comprise 6.7% of the capital costs. The total of capital and fixed costs, averaged over the entire 

US gasoline production volume is 0.02 cents per gallon, and the capital costs for this storage are 

$95 million. 

Combining the above cost estimates, we estimate that reducing the cap standard from 80 

to 50 ppm could increase the total compliance cost for Tier 3 compliance cost by 0.04 cents per 

gallon, thus, increasing Tier 3 estimated costs from 0.65 to 0.69 cents per gallon. The estimated 

total capital cost increase for a 50 ppm cap standard is $230 million, thus increasing Tier 3 

estimated capital costs from $2.025 billion to $2.26 billion. 

In their comments on our proposal, the American Petroleum Institute provided a report 

which discussed the costs and other impacts that might result from a more stringent gasoline 

sulfur cap standard. The comments were in the form of a report analyzed and written by the 

Turner, Mason and Company (TMC) wherein they principally report the results of a survey of 

refiners that they conducted to ascertain their compliance approach and potential compliance 

costs with more stringent gasoline sulfur caps of 60, 40, 30, and 20 ppm as compared to the 

current 80 ppm cap. The survey was comprised of a series of multiple choice questions. While 

the TMC study did not look specifically at the implications of the proposed 50 ppm cap standard, 

one could look at the responses for the 40 and 60 ppm cap standard and interpolate to get a good 

sense of what the study would show for a 50 ppm cap standard. Apparently, 6 refiners 

responded to the survey and TMC estimated that these refiners operate 30% of the operating 
5-71

refineries and produce 44% of the gasoline produced in the U.S. Thus, the respondents were 

primarily large refining companies which own multiple refineries. TMC then extrapolated the 

results from these 6 refiners to the remaining 38 U.S. refiners to estimate the overall impact. A 

summary of the API estimated cost and other impacts is summarized in Table 5-35. We 

calculated a per-gallon cost by amortizing the capital costs over the volume of gasoline that API 

used in its cost study assuming a before tax 7% return on investment (specified by the Office of 

Management and Budget). The estimated per-gallon costs are also summarized in Table 5-35. 

Table 5-35 API Estimated Cost and Supply Impacts 

80 60 40 30 20

Capital Cost ($MM) - 1768 3390 5533 6090

Per-Gallon Cost 

(c/gal)

- 0.17 0.33 0.54 0.60

Gasoline Supply Loss 

(Kbbl/day)

12 43 63 108 129

The TMC survey results can be placed into five different categories associated with lower 

cap standards: 1) how refiners would comply with the Tier 3 average sulfur standard, 2) how 

refiners would react to an outage of a FCC naphtha desulfurization unit (FCC pretreater or 

postreater), 3) how refiners would react to a loss of low sulfur blendstocks, 4) what the projected 

increase in capital costs would be for tighter cap standards, and 5) what the loss in gasoline 

production volume would be. Many of the survey results are presented in the report as a series 

of plusses (from 1 to 4) or a single minus instead of presenting the raw survey results. 

Presumably, one plus indicates a modest tendency to undertake an action and increasing numbers 

of plusses indicates a greater tendency to undertake an action, while a single minus sign indicates 

very little or no tendency to undertake an action. 

With respect to the first survey category, when complying with the 10 ppm average 

standard, the TMC refiner survey found that as the cap standard was decreased refiners would 

rely less and less on FCC pretreating as the sole means for desulfurizing FCC naphtha, and 

therefore would rely on both combined pre and postreating (at a 20 ppm cap, the report seems to 

conclude that every refinery which solely relies on FCC pretreating today to lower its gasoline 

sulfur would install an FCC postreater). This survey result in TMC’s study for API is 

inconsistent with the cost study Baker & O’Brien performed for API. In that study, which 

assumed a 20 ppm cap standard, refiners were assumed to rely on revamped FCC pretreaters for 

complying with the 10 ppm average standard. In our cost analysis discussed in section 5.1.3.5, 

we conservatively assumed that the only option considered by refineries which are complying 

with Tier 2 by only using FCC pretreating is to put in a grassroots FCC postreater to comply with 

Tier 3. Thus, our cost analysis of the 10 ppm average and 80 ppm cap standard may already 

include some of the costs of a tighter cap standard. Furthermore, there are several California 

refineries, already governed by a 20 ppm cap standard, that solely use FCC pretreating to comply 

with the California gasoline sulfur standard. Thus, it does not appear that decreasing the cap 

would necessarily force FCC postreating versus FCC pretreating. 
5-72

With respect to the first survey category, the survey also found that refiners are more 

likely to reduce the endpoint of FCC naphtha and add treatment of other blendstocks as the cap 

standard is lowered. Reducing the endpoint of gasoline is likely an important factor driving the 

gasoline supply results from the TMC study. However, our LP refinery modeling projects that 

refineries will already be extensively undercutting FCC naphtha when the Tier 3 program is 

implemented in order to maximize distillate production and profits. Thus, we believe that this 

will be occurring in the baseline with or without Tier 3. 

With respect to the second survey category, (how refiners would react to an outage of a 

FCC naphtha desulfurization unit with lower cap standards), the refiner survey found that 

refiners would predominantly idle or significantly reduce feed rate to the FCC unit, regardless of 

the stringency of the cap standard. The second most important strategy that refiners would use 

would be to store high sulfur components, and that this strategy would increase as the cap 

tightens. Other strategies that increased as the cap was lowered included purchasing low-sulfur 

components, selling high sulfur components and/or exporting high-sulfur gasoline, reducing the 

endpoint of FCC naphtha, and reducing crude oil feed rate. One other strategy identified for that 

subset of refineries with both a pretreater and a postreater or multiple postreaters today was to 

simply operate the nonshutdown hydrotreating unit more severely. The refiner survey results 

supports the analysis that we conducted above, which is to add storage capacity to allow 

additional storing of high sulfur FCC naphtha. The refiner then has time to deal with the very 

high sulfur FCC naphtha stream through reprocessing, selling, blending, exporting, etc. 

With respect to the third survey category (loss of low sulfur blendstocks), the refiner 

survey found that refiners would take a number of actions. The most common response was to 

store high sulfur components, although idling or significantly reducing the feed rate to the FCC 

unit was also common. Other responses were to increase the severity of the FCC pre or 

postreater, sell high sulfur components or export high sulfur gasoline. We believe that this issue 

is predominantly about an emergency shutdown of the naphtha hydrotreater which facilitates the 

production of reformate, isomerate, and low-sulfur, light straight run naphtha. Both the reformer 

and isomerization units require near zero sulfur gasoline to function, and if the naphtha 

hydrotreater undergoes an emergency shutdown, then the feedstock to the reformer and 

isomerization units must be stopped and those units would need to be shutdown as well. Since 

straight-run naphtha is high in sulfur, it likely cannot be blended straight to gasoline without 

exceeding the sulfur cap standard. This is a situation that exists today, and due to the very high 

sulfur of untreated FCC naphtha, this situation is little impacted by the level of the cap. Perhaps 

in limited situations if a refinery was refining a sweet crude oil, the refinery may be able to 

blend some of the heavy straight run naphtha into its gasoline pool and still meet the sulfur cap 

without hydrotreating it if the cap was not too stringent. However, this would be further limited 

by the need to meet the octane requirements for the gasoline. Provided that the refiner put in 

emergency storage for FCC naphtha, this storage could also be used for heavy straight run 

naphtha since it is unlikely that the naphtha hydrotreater would need to be shutdown at the same 

time that an FCC pre or postreater would need to be shutdown. As a result, there should really 

be no additional impact or cost associated with this issue that isn’t already captured under survey 

category 2. 

With respect to the fourth survey category (estimated capital costs for lower caps), the 

survey results, TMC extrapolated to the industry as a whole, estimated the impact of the cap 
5-73

standards would be $1.8 billion for a 60 ppm cap standard, $3.4 billion for a 40 ppm cap 

standard, $5.5 billion for a 30 ppm cap standard, and $6.1 billion for a 20 ppm cap standard. 

Thus, for complying with a 50 ppm cap standard, the TMC refiner survey estimates a capital cost 

of about $2.5 billion, which is about one order of magnitude higher than our estimate. Because 

these values are solely responses to a survey questionnaire, and no justification or support for 

these values was provided in the report, it is difficult to identify the basis for the reported costs. 

It is difficult to reconcile these results with our own. There is no connection made in the report 

between the responses to the other survey questions discussed above, and the potential capital 

costs. As discussed above, there are several other survey results which would have an impact on 

capital costs that we believe are inappropriate to attribute to a declining cap standard, but the 

report doesn’t provide any means to assess this in the context of capital costs. Part of the 

discrepancy between the survey results and our own may simply be due to confusion with the 

refiner responses to the survey. The survey asked refiners what the costs would be for 

complying with the various hypothetical cap standards, but the survey did not specify whether 

the refiner should report their capital cost estimate on a refinery basis or company basis. Thus, it 

is possible that TMC assumed that the refiner responses for a capital cost estimate were on a 

refinery basis and multiplied the values by the number of refineries that each refiner has, when in 

fact the refiner may have responded on a company basis. No discussion is provided to help the 

reader understand how this potential confusion may have been resolved by TMC. 

The last survey category discussed in the TMC report is the potential gasoline production 

loss during turnarounds associated with tighter cap standards. The TMC report estimated that 

the 80 ppm cap standard would already be responsible for 12 thousand barrels per day (kbbl/day) 

of gasoline production loss. As the cap is lowered to 60 ppm the report estimates this gasoline 

production loss increases to 43 kbbl/day, if the cap is lowered to 40 ppm the projected loss 

increases to 63 kbbl/day, at a 30 ppm cap standard the loss increases to 108 kbbl/day and a 20 

ppm cap standard is projected to cause a loss of 129 kbbl/day of gasoline production. 

Interpolating between 60 and 40 ppm, the projected gasoline production loss for a 50 ppm cap is 

53 kbbl/day. Thus, decreasing the cap standard from 80 to 50 ppm is projected by TMC to 

increase the gasoline production loss by 41 kbbl/day. Of the 8452 kbbl/day of gasoline 

consumed in the US, this projected gasoline production loss represents 0.5%. Similar to our 

observation of estimated capital costs, there is no connection made in the report between the 

responses to the other survey questions discussed above and the potential gasoline production 

loss. Furthermore, as discussed above, there are several other survey results which would have 

an impact on gasoline production that we believe are inappropriate to attribute to a declining cap 

standard, but the report doesn’t provide any means to assess this in the context of gasoline 

production impacts. A portion of this projected gasoline production loss is a short term loss and 

once the affected units are restarted, high sulfur intermediate refinery streams (such as FCC 

naphtha) would be hydrotreated with the excess capacity available in the respective hydrotreating 

units and would eventually be blended into the gasoline pool. Thus, the projected net gasoline 

production loss would be much less than the 0.5% reported by TMC for a 50 ppm cap standard. 

5.3 Other Cost Studies 

Other cost studies were recently conducted to estimate the cost of additional reduction in 

gasoline sulfur. We evaluated each of these studies and compare them to our own cost analysis. 
5-74

5.3.1 International Council for Clean Transportation Cost Study 

The International Council for Clean Transportation (ICCT) retained Mathpro in October 

2011 to study the cost of a 10 ppm average gasoline sulfur standard as well as a 1 psi reduction 

in RVP.17

 Since the lower RVP standard was modeled as a separate step from the low sulfur 

standard, we were able to isolate the gasoline sulfur reduction costs from the low RVP costs. 

ICCT’s estimated cost for a 10 ppm average gasoline sulfur standard is 0.8 cents per 

gallon which reflects the capital costs amortized assuming a before-tax 7 percent rate of return 

on investment (to be consistent with our analysis). This cost reflects an assumption that the 

capital cost for revamps of FCC postreaters is 30 percent of the capital costs for a grassroots 

FCC postreater. Mathpro also analyzed costs assuming that the capital cost for revamps of FCC 

postreaters are 50 percent of a grassroots FCC postreaters, which is 1.1 cents per gallon. ICCT’s 

cost estimate for complying with a 10 ppm average gasoline sulfur standard is very close to ours. 

5.3.2 The Alliance Cost Study 

In 2008 The Alliance retained Mathpro to use its LP refinery cost model to estimate the 

costs of what they termed National Clean Gasoline (NCG) in PADDs 1, 2 and 3 (generally 

speaking, this is the part of the U.S. east of the Rocky Mountains).18

 Achieving NCG would 

entail reducing gasoline sulfur to 5 ppm under a 10-ppm cap standard and the reduction of 

gasoline RVP to 7 psi. For the low-RVP standard, a 1-psi waiver was allowed for conventional 

gasoline, but not for current low-RVP areas. The study also evaluated two sensitivity cases 

which increases the stringency of the distillation index (DI) from 1250 to 1200. The Alliance 

study also evaluated crude oil price as a second sensitivity case, evaluating crude oil prices at 

$51 /bbl and $125/bbl. 

The Alliance studied three different cases. The first case applied the 10 ppm sulfur cap to 

RFG. The second case applied the 10 ppm sulfur cap and the 7.0-psi low-RVP standard to RFG 

as well as 7.0- and 7.8-psi low-RVP gasoline. The third case applies the 10 ppm sulfur cap and 

7.0-psi RVP standard to all RFG and CG. Of these three cases, the first case is most relevant 

because applying the fuels changes to RFG solely applies the 10 ppm sulfur cap to RFG and does 

not involve any changes in RVP. However, the 10 ppm sulfur cap standard studied by the 

Alliance is still 5 ppm more stringent than the 10 ppm average standard that we are proposing. 

The Alliance cost estimate for Case 1 is 1.6 cents per gallon for RFG in PADDs 1, 2 and 

3. This cost estimate is based on amortizing the capital costs on a 10 percent after-tax return on 

investment (ROI). We adjusted the cost estimate to amortize the capital costs based on a before 

tax 7 percent ROI and adjusted the costs to 2010 dollars which increases the costs to 1.75 cents 

per gallon. The 1.75 ¢/gal cost estimate is based on a crude oil price of $51/bbl. The Alliance 

estimated the cost of a 10 ppm sulfur cap standard on RFG assuming that crude oil is priced at 

$125/bbl. At the $125/bbl crude oil price, the Alliance study estimates that it costs 2.50 ¢/gal to 

require that RFG comply with a 10-ppm sulfur cap standard. Adjusting the Alliance costs to 

reflect a 7 percent before tax ROI and 2010 dollars increases the Alliance costs based on a 

$125/bbl crude oil price to 2.69 ¢/gal. 
5-75

For our cost analysis we analyzed the cost of sulfur control assuming that crude oil is 

priced at $91.8/bbl. We can interpolate between the Alliance costs based on $51 and $125 per 

barrel crude oil prices, which results in a single cost which is 2.3 cents per gallon. We also 

estimated a cost for refiners lowering their gasoline sulfur to 5 ppm using the refinery-byrefinery cost model and our cost is 1.28 ¢/gal. 

5.3.3 API Cost Study 

In response to the Alliance study, API retained Baker & O’Brien (BOB) in 2010 to study 

the cost of additional gasoline sulfur control and RVP control using a refinery-by-refinery cost 

approach with BOB’s Prism model.19

 The Prism model is largely a spreadsheet cost model with 

blending optimization. The primary case analyzed by the API study is the cost of reducing 

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

waiver for blending 10 percent ethanol. The study also analyzed three other sensitivity cases: 1) 

a 5-ppm average gasoline sulfur standard with 7 psi RVP limit on conventional gasoline without 

a 1-psi waiver; 2) a 10 ppm average gasoline sulfur standard and a 7.8-psi RVP limit on 

conventional gasoline without a 1-psi waiver; and 3) a 10 ppm average gasoline sulfur standard 

with a 7.8-psi RVP limit on all conventional gasoline with a 1-psi waiver. 

In an addendum to its fuels study report released in 2011, API contracted with Baker & 

O’Brien to study a sensitivity case 4, which is a sulfur only case, using its PRISM refinery 

model. From our understanding of the study, the study parameters seemed to be about the same 

as the original study, except that API solely studied a 10 ppm average gasoline sulfur standard 

(not including any RVP control), the same sulfur standard that we are proposing. However, API 

also assumed that a 20 ppm cap standard would also be in place which would effectively not 

allow the application of an averaging, banking and trading (ABT) program to optimize refinery 

investments and minimize overall costs. 

API made a series of conclusions based on the study. Perhaps the most important 

difference with the original study is that API concluded that not a single refinery would shut 

down as a result of the proposed 10 ppm gasoline sulfur control standard, even though API did 

not study the flexibilities of an ABT program and used excessively high capital costs for a 

grassroots FCC postreater (see below). Like the original study, API did not report average costs, 

but reported only the marginal costs for the cost study. Marginal costs reflect the cost of the 

program to the refinery or refineries which would incur the highest costs, assuming that the 

highest cost refineries would set the price (or in this case, the price increase) of gasoline. The 

report concluded that marginal costs after the imposition of a 10 ppm gasoline sulfur program 

would increase the price of gasoline by 6 to 9 cents per gallon in most markets. API did not 

define how its statement “in most markets” would apply to the US gasoline supply. API also did 

not provide any justification why it assumed that the refineries that would experience the highest 

desulfurization cost under Tier 3 would also be the same refineries which set the gasoline price 

in their gasoline markets today. 

Although API did not provide an average gasoline desulfurization cost in its report, we 

could calculate an average cost based on the gasoline volume and total annual costs provided. 

The total cost reported in the report for the 10 ppm average gasoline sulfur standard is 

$2390MM/yr and the non-California gasoline volume is 7343 thousand barrels per day. This 
5-76

results in an average per-gallon desulfurization cost of $0.89/bbl or 2.12 c/gal. The difference 

between the average cost and marginal cost (price increase) that API is projecting is profit. API 

is projecting that the oil industry would profit from 10 ppm low sulfur standard by the roughly 4 

to 7 cents per gallon difference between the average cost and the two marginal price values. 

That per-gallon profit translates into $4 to $8 billion dollars per year in profit. 

The average cost of the 10 ppm average gasoline sulfur standard was calculated using 

API’s methodology for amortizing capital investments. To facilitate a fairer comparison 

between the API cost study and our cost study, we adjusted the API costs to be on a similar basis 

as our costs. We adjusted the API costs to reflect a before-tax 7 percent return on investment 

(ROI) for capital invested for the hydrotreaters and hydrogen plants instead of the after-tax 10 

percent ROI used by API. This lowered the API estimated costs from 2.12 c/gal to 1.58 c/gal. 

API’s 1.58 cents per gallon cost is still higher than our 0.89 c/gal cost with an ABT program that 

assumes intercompany trading of credits, and higher than our 0.97 c/gal for the case which 

assumes no ABT program. Thus comparing “apples-to-apples” to the to the extent possible, 

API’s 1.58 c/gal estimated cost for complying with a 10 ppm average gasoline sulfur standard 

compares very favorably with our own cost estimates, and not at all near the 25 c/gal value that 

was sometimes quoted from the first API study. The remaining cost difference between our 

estimated costs and those by API are the capital cost assumptions that API used, as discussed 

below. While little detail is provided by API about what hardware comprises their 

desulfurization units, the inside battery limits (ISBL) and total capital costs for the FCC 

postreaters and FCC pretreaters are provided in API’s report. API’s FCC pretreaters capital 

costs are consistent with the capital costs that we have used for this unit. However, the FCC 

postreater costs used by API are much higher than what we used and have been used in the past 

by others. API’s capital cost for a grassroots FCC postreater is $228 million for a 35,000 bbl/day 

unit, or $6540 per/bbl per day. API’s capital cost includes the outside battery limit (OSBL) 

costs. In contrast, the ISBL capital cost that we used for a grassroots FCC postreater is 

$1500/bbl-day for a 30,000 bbl/day grassroots unit, which increases to $2440/bbl/day when the 

offsite costs and a 20% contingency are added on. Thus, the API capital costs are more than 2 1⁄2 

times higher than the capital costs that we are using for a grassroots FCC postreater. To check 

our capital costs, we found other capital cost estimates to which we could compare our costs. 

Table 5-36 contains a cost comparison of ISBL and OSBL FCC postreater capital costs for a 

grassroots unit. 

Table 5-36 Capital Cost Comparison 

Technology EPA 

(Tier 3)

Mathpro 

(ICCT)

Jacobs API

ISBL Capital 

Cost ($/bbl/day) 1500 - 2440 -

ISBL and OSBL 

Capital Cost 

($/bbl/day)

2430 1800 3538 6540

Table 5-36 shows that, compared to the average of the rest of the capital cost estimates, 

the API capital cost for FCC postreater is about 2 1⁄2 times higher. Compared to the next highest 
5-77

cost estimate, which is the FCC postreater capital cost from the Jacobs data base in the Haverly 

refinery cost model that we use,Fthe API capital costs are almost two times higher. 

An important distinction must be made with respect to the severity of desulfurization for 

the capital cost comparison made in 5-32. For complying with the Tier 2 gasoline sulfur 

standard (Jacobs), a typical refinery would have installed an FCC postreater to desulfurize the 

FCC naphtha from about 800 ppm down to about 75 ppm, a 725 ppm, or a 91 percent sulfur 

reduction. In the case of a grassroots postreater that would be installed for Tier 3, the postreater 

would treat FCC naphtha already low in sulfur due to the pretreater installed before the FCC unit 

(these refineries are currently complying with Tier 2 using an FCC pretreater). Thus, the new 

grassroots FCC postreater would only have to reduce the FCC naphtha from 100 ppm to 25 ppm, 

a much smaller 75 ppm or 75 percent sulfur reduction. A grassroots FCC postreater installed for 

Tier 2 would typically remove 10 times more sulfur than one installed for Tier 3. This is 

important because a significant portion of the FCC postreater capital cost is devoted to avoiding 

the recombination reactions which occur when hydrogen sulfide concentrations are high and 

react with the olefins contained in the FCC naphtha. Thus, a grassroots FCC postreater installed 

for Tier 3 would be expected to be significantly lower in capital cost compared to a Tier 2 FCC 

postreater. API’s costs are based solely on Tier 2 compliance costs, which is one reason why 

their costs are so high. API obtained either estimated installation costs or actual installation costs 

(API did not specify) for FCC postreaters for installation in 5 different refineries for complying 

with the Tier 2 30 ppm gasoline sulfur standard. The postreater capital cost information which 

reflected cost information from the years 2003 to 2005 was adjusted upward to reflect mid-year 

2009 capital costs using the Nelson-Farrar index and normalized to reflect a 35 thousand barrel 

per day unit. This resulted in an average ISBL cost of $144.5 million for installing a Tier 2 

compliant FCC postreater. After discussing this capital cost estimate with several refiners who 

built several of the units in recent years, those refiners felt that the estimated capital costs that 

API had calculated were too low, and one refiner thought that the estimated capital costs should 

be doubled. Based on the information provided by that one refiner, API doubled its estimated 

capital costs for a 35K bbl/day FCC postreater to $228.8 million. 

Another way to assess the API capital cost for the FCC postreaters is to compare it to the 

FCC pretreater cost that API is using. FCC pretreaters are much higher pressure units and use 

more expensive metallurgy than FCC postreaters and, for these two reasons, are much more 

expensive than FCC postreaters on a per-barrel basis. However, API’s FCC postreater capital 

costs are about 50 percent more expensive than its FCC pretreater capital costs, which is 

inconsistent with the design requirements of the units. API acknowledged this inconsistency, but 

did not take steps to correct it. 

API’s estimated range of capital cost for revamping an FCC postreater is also higher than 

our range of capital cost for revamping an FCC postreater, when assessing the revamped costs as 

a percentage of the capital cost for a grassroots unit. API estimates that revamping an FCC 

 

F

 The installed capital cost for an FCC postreater from the Jacobs data base was adjusted to current year dollars. 

This estimated installed capital cost is several years old and may not represent Jacobs current cost estimate for a 

FCC postreater. 
5-78

postreater would cost 30 to 70 percent of the capital cost for a grassroots FCC unit. Our capital 

cost estimate for revamping FCC naphtha postreaters range from 17 to 50 percent of the capital 

cost for a grassroots FCC postreater, however, most of the revamps are estimated to cost at the 

lower end of that range. 

As discussed above, an important reason why API’s projected capital costs for complying 

with Tier 3 are so high is that API assumed a 20 ppm cap standard in addition to the 10 ppm 

average standard that it studied. The 20 ppm cap standard eliminates the possibility of realizing 

the cost savings of an ABT program. After we proposed the Tier 3 rule, API presented to EPA, 

in its comments on the proposed rulemaking, its estimate for the cost of finalizing a more 

stringent cap standard. The study, which was contracted to the Turner, Mason & Company, 

estimated that a 20 ppm cap standard would increase the capital cost of complying with a 10 ppm 

average standard by $6.1 billion. If we subtract the $6.1 billion in capital costs attributed to the 

20 ppm cap standard from the $9.8 billion in total capital costs from API’s Addendum report 

which estimated the cost of complying with Tier 3, and adjust the fixed operating costs 

accordingly, the API estimated average cost (not marginal cost) for complying with Tier 3 

decreases to 0.97 c/gal. In addition to the questionable capital costs assumed for FCC postreaters 

as discussed above, this information from API on its estimated cost of complying with a 20 ppm 

cap standard helps to answer an important question of why the API estimated average cost was 

still higher than the other studies after other cost adjustments were made. This final adjustment 

to the API costs makes the estimated API costs for complying with Tier 3 right in line with the 

other cost studies. This adjusted API cost, however, still does not include the cost saving aspects 

of credit averaging and trading since the API analysis assumed that each refinery meets the 10 

ppm average sulfur standard. Thus, to compare this most recent cost adjustment of API costs to 

our cost study, our 0.87 c/gal cost for no ABT program would be the most appropriate cost for 

comparison (see section 5.2.2 for alternative costs). The adjusted API cost and our cost are only 

0.1 c/gal different. 

5.3.4 Emissions Control Technology Association Cost Study 

The Emissions Control Technology Association (ECTA) retained personnel within 

Navigant Economics to study the costs of a 10 ppm average gasoline sulfur standard and assess 

the ICCT and API cost studies.20 The authors made a number of conclusions. After reviewing 

both the ICCT and API studies, the authors found that a primary difference in estimated costs 

between the two studies was the capital costs. The authors contacted vendor companies that 

license FCC postreater technologies and surveyed the companies to find out what the capital 

costs are for a FCC postreater. As a result of the survey, the report authors concluded that API’s 

capital costs were too high, and those used in the ICCT study were about right. The authors 

found that Baker & O’Brien has a history of exaggerating the economic impacts of EPA rules, 

citing the costs and other impacts of its analysis of the 2007 on-highway heavy-duty proposed 

rulemaking. The authors concluded that the impact of a 10 ppm gasoline sulfur standard on the 

average refining cost would likely be closer to the 1 cent per gallon estimate by the ICCT study. 

Furthermore, the report’s authors also pointed out that the marginal cost analysis conducted by 

API did not consider the proposed averaging banking and trading (ABT) program that we were 

expected to propose, which would reduce the marginal costs of the Tier 3 proposed rule. 
5-79

5.4 Projected Energy Impacts and Impacts on Permitting 

Our refinery-by-refinery model was also used to determine the impact the Tier 3 

standards would have on the energy related CO2 emissions and permitting of existing refineries. 

While the Tier 3 proposal will reduce emissions from vehicles, the addition of grass roots units 

and revamping of existing units which we project will happen as a result of the Tier 3 sulfur 

standards are likely to result in some increased emissions of regulated air pollutants at refineries. 

Refinery projects designed to meet the new fuel standards could trigger preconstruction air 

permitting requirements under the Clean Air Act and EPA’s New Source Review (NSR) 

regulations. To address this concern, we used our refinery-by-refinery model to estimate the 

likely process and equipment changes that may be required to meet the Tier 3 gasoline standards. 

This information was submitted to EPA’s Office of Air Quality Planning and Standards 

(OAQPS) to provide the inputs that are necessary for the modeling and analysis of the refinery 

emissions and permitting impacts of the Tier 3 fuel standards. 

Using our refinery-by-refinery model we generated refinery-specific estimates of the 

increased energy and hydrogen demands that we estimate will result from the proposed Tier 3 

standards. We also estimated the increase in sulfur plant recovery unit (SRU) loading/operations 

for the 110 U.S. refineries that we modeled in our analysis. Energy demand includes fuel that is 

needed to generate refinery process heat, steam and electricity. Hydrogen demand is associated 

with increased hydrotreating of Fluid Catalytic Cracking (FCC) naphtha and light straight run 

(LSR) streams. Increased SRU loading results from the increased fuel desulfurization and 

associated H2S generation. All of these incremental demands will be referred to as “demands” 

in the following sections. We used our refinery-by-refinery model to calculate the increase in 

these various demands for several scenarios where sulfur averaging, banking, and trading (ABT) 

was not allowed and each refinery had to meet the 10ppm standard, as well as scenarios that 

allowed ABT between refineries owned by the same parent company to minimize the cost of 

compliance with the Tier 3 standards. 

5.4.1 Emissions Impacts of Different Production Volumes 

In addition to considering scenarios with and without ABT we also considered the 

impacts on emissions and permitting of different gasoline production volumes for each refinery. 

In the first case, called the normal case, we considered the incremental demands for each refinery 

assuming no change in gasoline production volume. We also considered a case, called the 

maximum demand case, where each refinery maximized gasoline production based on currently 

existing refinery capacity and equipment. 

5.4.1.1 Normal Case 

The normal case was estimated using each refinery’s predicted yields of FCC naphtha 

and LSR from our refinery-by-refinery model, along with each refinery’s total gasoline 

production volume from EPA’s RFG database. For each refinery the refinery-by-refinery model 

generated specific Tier 3 demands for hydrogen, steam, fuel gas and electricity based on the 

desulfurization technology used by each refinery for any FCC postreating and LSR 

hydrotreating. To determine the FCC postreating demands the model considers each refinery’s 

volume of FCC naphtha under normal operations, the FCC naphtha sulfur level at the refinery 
5-80

prior to postreating, and the process requirements of the FCC postreater technology used by that 

refinery. The demands are calculated by multiplying the FCC naphtha volume by the demands 

from the use of the associated FCC postreating technology. Table 5-20 through Table 5-23 show 

the FCC postreater technology demand averages as applied to refineries on a national basis for 

the 5 and 10 ppm gasoline sulfur standards. Note that the demands vary significantly with the 

FCC naphtha sulfur level prior to postreating. 

Similarly, the normal case demands for any LSR blendstocks that require additional 

hydrotreating as a result of the Tier 3 standards were determined based on each refinery’s yield 

of LSR blendstock under normal operations and the demands for the additional LSR 

hydrotreating. These demands are discussed in section 5.1.3.1.2. The normal case demands for 

FCC postreating and LSR hydrotreating were then summed to determine the increase in energy 

and hydrogen demand. To determine the additional sulfur removed from gasoline we first 

calculated the difference between the current gasoline sulfur level of the gasoline produced at 

each refinery according to their compliance reports to EPA and the proposed Tier 3 standard. 

This difference was multiplied by the refinery’s gasoline production volume and divided by the 

number of days of operation to calculate the additional sulfur removal level at each refinery. 

This sulfur removal information was then used to determine the increase in SRU loading on a 

fractional basis by dividing the additional sulfur removal as a result of the Tier 3 standards (in 

tons of sulfur per day) by the refineries SRU process capacity. 

5.4.1.2 Maximum Case

We also considered a second demand case, called the maximum case, in which we 

calculated the demands that result from the Tier 3 standards if each refinery maximizes gasoline 

production based on currently existing refinery capacity. For this case we first determined each 

refiners FCC unit process capacity utilization rate in the normal case. The annual FCC unit 

feedstock charge rate for each refinery as reported in the 2011 EIA data was divided by the FCC 

unit design capacity as reported in the Oil and Gas Journal (OGJ) to calculate the capacity 

utilization rate for the normal case. These normal capacity utilization rates were then scaled up 

to reflect maximum capacity utilization rates, and further adjusted using an overdesign factor. 

For refineries projected to meet the proposed Tier 3 standards by revamping existing 

FCC postreating units we assumed that their maximum gasoline production rate was equal to the 

rate produced running the FCC unit at 92% of the refinery’s maximum FCC design capacity. 

There were several refineries that are currently operating their FCC unit greater than a 92% 

capacity utilization rate. We assumed that these refineries were already operating at their 

maximum annual capacity utilization rate. For the refinery projected to install a new FCC 

postreater, we similarly assumed that the new unit would be scaled to process the output of the 

FCC unit operating with a 92% utilization rate. For the new FCC postreater, however, we 

increased the results by 15% as an overdesign factor and adjusted the results accordingly. A 

similar sizing approach was taken for refineries we projected would revamp or add new LSR 

hydrotreating capacity to comply with the proposed Tier 3 standards. 

The results represent a “maximum” annual gasoline production case for each refinery 

under the Tier 3 standards based on each refiners FCC unit design capacity. These cases 

represent a scenario where each refinery’s emissions based on the maximum achievable annual 
5-81

production rate for their existing processing units. These cases reflect each refiner’s potential 

emissions impacts as a result of the proposed Tier 3 standards, relative to the existing Tier 2 

standards, when operating at maximum FCC rates as opposed to normal operation more 

indicative of national gasoline demand. 

5.4.2 Refinery Demand Sourcing 

After determining the increased demands for each refinery as a result of the proposed 

Tier 3 regulations we next developed cases for each refinery demand scenario that represented 

different options for sourcing these demands. Some refiners may choose to produce all of the 

required hydrogen and electricity. Others may choose to purchase some or all of the hydrogen 

and electricity that they would need to comply with the Tier 3 standards from external suppliers. 

These decisions have a significant impact on the emissions and permitting impacts of the 

proposed Tier 3 regulations. In order to bound all possible scenarios we considered both high 

and low impact cases for each refinery demand scenario. In the high impact scenarios we 

assume that each refinery produces all of the required hydrogen, and electricity needs. In the low 

impact scenarios we assume that all the necessary hydrogen and electricity are purchased from 

an external supplier. 

In both cases we assumed that fuel gas demands would increase to meet the increased 

thermal demands at the refinery. In the high impact scenarios the refinery’s fuel gas needs 

would be further increased to produce the needed hydrogen and electricity. We consulted 

literature sources to determine the conversion factors from MBTU fuel gas to 1,000 standard 

cubic feet (scf) of hydrogen21 and 1,000 pounds of steam22 that are typical for refineries. We 

also assumed a standard conversion efficiency from fuel gas to electricity for our modeling. For 

hydrogen needs, in our emissions analysis, we presumed that fuel gas used to make hydrogen 

would only generate C02 emissions, as we presumed that the conversion process was efficient. 

Fuel gas used as process energy needs in the hydrogen production process, however, we 

projected would emit the full range of emissions. All of the fuel gas demand estimates are 

shown in Table 5-37. 

Table 5-37 Fuel Gas Required to Produce Hydrotreater Utilities 

Utility Fuel Gas Required (M BTU)

Hydrogen Process 

Energy (1,000 SCF)

140

Hydrogen Process Feed 

Needs (1,000 SCF)

248

Steam (1,000 lbs) 1530

Electricity (1 kWh) 5.1

We assumed that refiners would not need any additional energy needs to make up for lost 

octane, because our LP refinery modeling estimates that the utility demands associated with 

recovering the octane debit from Tier 3 was inconsequential. Refiners are expected to use 

reformers and other high octane processes, such as alkylation units, to cover any octane debit in 

FCC naphtha, by making minor shifts in operations which apparently does not impact utility 
5-82

demands. Also, in some cases lost octane could be recovered by purchasing high octane 

blendstocks which would result in no fuel gas or electricity demand increases at the refinery. 

5.4.3 Refinery Energy Demand Impacts 

Using our refinery-by-refinery model, along with the technology vendor data for new and 

revamped FCC postreating and LSR hydrotreating data (shown in Table 5-25 through Table 5-28

and Table 5-31), we were able to calculate the increases in refinery energy demands as a result of 

our proposed Tier 3 regulations for each of the various scenarios outlined in the previous 

sections. This information is summarized in Table 5-38 below. The refineries have been 

identified by randomly assigned numbers to protect confidential business information (CBI). 

This information was submitted to our sister office, OAQPS, to serve as the basis for 

their emissions and permitting analysis of the Tier 3 regulations. Based on the updated refinery 

analysis, EPA determined that under the final Tier 3 gasoline sulfur standard, which includes 

national ABT, 9 refineries are projected to trigger New Source Review (NSR). This equates to 

approximately 8% of the 108 refineries. Of these 9 refineries, only 3 are projected to trigger 

permitting for both a NAAQS-related pollutants and GHGs while an additional 6 refineries are 

projected to require PSD permits addressing only GHG emissions. A technical memorandum 

describing the OAQPS analysis and results is in the public docket for this final rule.23
5-83

Table 5-38 Tier 3 Maximum Refinery Energy, Hydrogen and Sulfur Plant Demand 

Increases for ABT Case 

Refinery 

Number

Demand Estimates

Fuel

Gas Demands Sulfur Plant Production Hydrogen

(Million BTU/Yr) Sulfur 

Production 

Increase 

(Tons 

Sulfur/Day)

Sulfur Plant 

Capacity 

Increase 

(Percent of 

Existing 

Facility)

Hydrogen 

Demand 

Increase 

(million 

scf/year)

Low Case High Case

High Case Plus 

CO2 for 

Hydrogen

1 55,766 239,291 555,121 0.50 0.07 1529

2 494,692 579,106 690,241 0.44 0.04 462

3 0 0 0 0.00 0.00 0

4 50,404 125,517 252,794 0.04 0.08 501

5 0 0 0 0.00 0.00 0

6 125,277 344,410 561,788 0.88 No Data 867

7 140,263 215,618 345,295 0.30 0.09 524

8 1,152,149 1,403,863 1,743,848 0.86 0.12 1686

9 0 0 0 0.00 0.00 0

10 498,770 1,088,552 1,989,386 0.08 0.06 3638

11 0 0 0 0.00 0.00 0

12 512,053 618,649 766,760 0.68 0.18 595

13 32,553 113,349 210,888 0.25 0.21 394

14 181,259 259,280 370,586 0.45 0.10 450
5-84

Refinery 

Number

Demand Estimates

Fuel

Gas Demands Sulfur Plant Production Hydrogen

(Million BTU/Yr) Sulfur 

Production 

Increase 

(Tons 

Sulfur/Day)

Sulfur Plant 

Capacity 

Increase 

(Percent of 

Existing 

Facility)

Hydrogen 

Demand 

Increase 

(million 

scf/year)

15 0 0 0 0.00 0.00 0

16 184,692 279,786 443,434 0.05 0.03 661

17 0 0 0 0.00 0.00 0

18 592,842 464,226 485,068 0.27 0.50 88

19 579,988 721,733 918,750 0.26 0.26 811

20 2,169,093 2,506,050 2,863,334 0.78 0.09 1441

21 0 0 0 0.00 0.00 0

22 29,522 115,563 169,530 0.56 0.04 217

23 127,534 358,933 594,542 2.20 0.00 0

24 53,024 129,662 259,460 0.41 0.28 536

25 0 0 0 0.00 0.00 0

26 0 0 0 0.00 0.00 0

27 19,972 81,398 123,448 0.25 0.11 167

28 1,040,992 1,309,416 1,716,105 0.30 0.06 1633

29 0 0 0 0.00 0.00 0

30 0 0 0 0.00 0.00 0
5-85

Refinery 

Number

Demand Estimates

Fuel

Gas Demands Sulfur Plant Production Hydrogen

(Million BTU/Yr) Sulfur 

Production 

Increase 

(Tons 

Sulfur/Day)

Sulfur Plant 

Capacity 

Increase 

(Percent of 

Existing 

Facility)

Hydrogen 

Demand 

Increase 

(million 

scf/year)

31 0 0 0 0.00 0.00 0

32 0 0 0 0.00 0.00 0

33 0 0 0 0.00 0.00 0

34 24,527 64,717 102,608 0.10 0.06 153

35 0 0 0 0.00 0.00 0

36 0 0.00 0.00 0

37 0 0 0 0.00 0.00

38 50,152 200,906 396,393 0.88 0.41 786

39 76,080 158,367 202,974 0.28 0.07 180

40 90,268 142,703 232,938 0.12 0.09 364

41 25,536 53,123 99,593 0.01 0.05 188

42 22,695 71,902 127,645 0.27 0.22 186

43 724,372 929,979 1,225,219 0.40 0.04 1187

44 597,780 803,621 1,157,854 0.60 0.04 1307

45 0 0 0 0.00 0.00 0

46 21,128 32,402 51,803 0.07 0.69 78
5-86

Refinery 

Number

Demand Estimates

Fuel

Gas Demands Sulfur Plant Production Hydrogen

(Million BTU/Yr) Sulfur 

Production 

Increase 

(Tons 

Sulfur/Day)

Sulfur Plant 

Capacity 

Increase 

(Percent of 

Existing 

Facility)

Hydrogen 

Demand 

Increase 

(million 

scf/year)

47 1,421,831 1,530,970 1,643,335 0.47 0.12 454

48 99,075 113,173 122,179 0.56 0.19 0

49 0 0 0 0.00 0.04 0

50 43,263 81,700 146,144 0.31 0.03 249

51 0 0 0 0.00 0.00 0

52 33,128 118,783 223,948 0.31 0.09 425

53 0 0 0 0.00 0.00 0

54 0 0 0 0.00 0.00 0

55 0 0 0 0.00 0.00 0

56 1,433,373 1,661,638 1,955,563 0.77 0.04 1172

57 124,488 152,511 192,146 0.16 No Data 165

58 0 0 0 0.00 0.00 0

59 868,124 1,123,388 1,492,456 0.59 0.09 1366

60 62,323 101,795 169,723 0.14 0.70 331

61 0 0 0 0.00 0.00 0

62 634,584 760,395 933,119 0.34 0.14 605
5-87

Refinery 

Number

Demand Estimates

Fuel

Gas Demands Sulfur Plant Production Hydrogen

(Million BTU/Yr) Sulfur 

Production 

Increase 

(Tons 

Sulfur/Day)

Sulfur Plant 

Capacity 

Increase 

(Percent of 

Existing 

Facility)

Hydrogen 

Demand 

Increase 

(million 

scf/year)

63 0 0 0 0.00 0.00 0

64 177,667 249,774 359,493 0.27 0.63 443

65 666,474 766,007 891,308 0.52 0.05 502

66 0 0 0 0.00 0.00 0

67 276,071 504,649 834,842 0.37 0.09 1170

68 173,066 242,782 362,756 0.37 0.91 435

69 0 0 0 0.00 0.00 0

70 0 0 0 0.00 0.00 0

71 358,243 508,962 768,333 0.63 0.07 976

72 18,780 78,287 180,693 0.13 0.10 0

73 396,525 470,283 569,854 0.42 0.26 400

74 71,768 210,552 357,881 0.18 0.01 595

75 96,393 185,026 325,957 0.24 0.05 297

76 0 0 0 0.00 0.04 0

77 0 0 0 0.00 0.00 0

78 0 0 0 0.00 0.00 0
5-88

Refinery 

Number

Demand Estimates

Fuel

Gas Demands Sulfur Plant Production Hydrogen

(Million BTU/Yr) Sulfur 

Production 

Increase 

(Tons 

Sulfur/Day)

Sulfur Plant 

Capacity 

Increase 

(Percent of 

Existing 

Facility)

Hydrogen 

Demand 

Increase 

(million 

scf/year)

79 581,482 734,018 956,397 0.73 0.09 895

80 34,842 87,838 177,666 0.19 0.06 663

81 70,820 90,336 119,036 0.15 0.09 113

82 0 0 0 0.00 0.00 0

83 144,344 489,552 899,581 0.56 0.07 1653

84 30,605 51,089 86,339 0.11 0.90 142

85 0 0 0 0.00 0.00 0

86 48,840 109,034 210,697 0.36 0.03 381

87 0 0 0 0.00 0.00 0

88 0 0 0 0.00 0.00 0

89 454,267 689,362 1,093,938 0.23 0.06 1708

90 0 0 0 0.00 0.00 0

91 221,368 386,207 669,879 0.34 No Data 1001

92 48,475 98,562 182,847 0.18 0.02 310

93 0 0 0 0.00 0.00 0

94 60,159 130,128 248,169 0.28 0.15 476
5-89

Refinery 

Number

Demand Estimates

Fuel

Gas Demands Sulfur Plant Production Hydrogen

(Million BTU/Yr) Sulfur 

Production 

Increase 

(Tons 

Sulfur/Day)

Sulfur Plant 

Capacity 

Increase 

(Percent of 

Existing 

Facility)

Hydrogen 

Demand 

Increase 

(million 

scf/year)

95 22,121 71,369 127,917 0.14 0.22 237

96 31,063 182,172 442,216 0.39 0.73 822

97 0 0 0 0.00 0.00 0

98 0 0 0 0.00 0.00 0

99 64,964 99,342 158,505 0.09 0.05 238

100 16,472 33,132 61,154 0.08 No Data 119

101 145,657 151,780 158,099 0.16 4.32 25

102 0 0 0 0.00 0.00 0

103 0 0 0 0.00 0.00 0

104 37,609 122,658 221,067 0.17 0.13 397

105 57,350 100,794 173,298 0.15 0.01 0

106 96,148 164,991 283,464 0.17 No Data 403

107 23,486 86,923 195,167 0.19 0.16 437

108 18,721 63,065 115,508 0.10 0.21 212

a The refinery did not have published information on the capacity of the existing sulfur plant. 
5-90

5.5 Fuel Quality Requirements for Denatured Fuel Ethanol 

5.5.1 Costs for Producers and Importers of Denatured Fuel Ethanol 

The State of California’s has a long-standing 10 ppm sulfur requirement for denatured 

fuel ethanol (DFE). Do to logistical issues associated with maintaining a separate DFE pool that 

complies with California requirements, all DFE manufacturers currently produce California 

compliant DFE. Therefore, we expect that there will be only minimal additional costs to DFE 

producers as a result of the Tier 3 program associated with new recordkeeping and product 

transfer document requirements as discussed in the Information Collection Request (ICR) for the 

Tier 3 rule. 

5.5.2 Costs for Producers and Distributors of Ethanol Denaturants 

Suppliers of denaturants for use in manufacturing denatured fuel ethanol (DFE) are 

already accustomed to providing product with a sulfur content that is consistent with a 10 ppm 

sulfur cap for DFE as discussed in Chapter 5.4.1. Denaturant manufacturers will be required to 

maintain per batch test records on the denaturants they produce to demonstrate that the sulfur 

content does not exceed 200 ppm. As discussed in Section V of the preamble to the Tier 3 final 

rule, that addition of denaturant with sulfur content of 200 ppm would result in DFE with a sulfur 

content of 10 ppm when blended at 5 volume percent into neat ethanol. As is current practice 

today, we anticipate that ethanol manufacturers will negotiate what specific sulfur level they 

require from denaturant manufacturers to facilitate with compliance with the 10 ppm sulfur cap 

for DFE considering what level of compliance margin a given manufacturer feels is necessary. 

We understand that ethanol manufacturers often currently require denaturant manufacturers to 

provide a product with a sulfur content of 120 ppm or less in order to ensure that DFE that 

contains 5 volume percent denaturant can comply with California’s 10 ppm sulfur cap for DFE. 

Therefore, we expect that there will be no additional processing costs to manufacture denaturant 

for use in the manufacture of DFE meting the Tier 3 program 10 ppm sulfur cap. 

As discussed in the Information Collection Request (ICR) for the Tier 3 rule, there will 

only be minimal additional costs to ethanol denaturant producers and importers to comply with 

the Tier 3 requirements associated with the registration, maintenance of denaturant testing 

records, and generation of product transfer documents (PTDs). There will also be minimal 

additional costs for distributors of ethanol denaturants associated with maintaining ethanol 

denaturant product transfer documents. 

5.6 Gasoline Additives 

The Tier 3 rule requires that manufacturers of gasoline additives used downstream of the 

refinery at less than 1 volume percent must limit the sulfur contribution to the finished gasoline 

from the use of their additive to less than 3 ppm when the additive is used at the maximum 

recommended treatment rate. All current gasoline additives contribute less than 3 ppm to the 

sulfur content of the finished fuel when used at the maximum recommended treatment rate (with 

3 ppm being the extreme). Normal additive production quality control practices already have 

had to consider the sulfur contribution of the additive to finished gasoline as a result of the Tier 2 

gasoline sulfur program. Therefore, the Tier 3 requirements will not necessitate the 
5-91

reformulation of any gasoline additives or additional additive production quality testing. The 

maximum recommended treatment rate is already stated on product transfer document or 

packaging for the additive. Hence, no changes will be needed to the product transfer documents 

for gasoline additives. The only additional burden for additive manufacturers will be to retain 

production quality control records for 5 years and make these available to EPA upon request. 

Therefore, the Tier 3 program requirements will not result in significant additional costs to 

gasoline additive manufacturers. 

5.7 Downstream Pentane Blending 

The Tier 3 program provisions that will facilitate the blending of pentane into previously 

certified gasoline at terminals will provide additional flexibility to industry. The associated 

requirements are described in Section VI.A. of the preamble to the Tier 3 final rule. We expect 

that the cost savings in reduced gasoline costs from downstream pentane blending will 

substantially outweigh the associated compliance costs. Industry will only take advantage of the 

pentane blending provisions, and be subject to the associated compliance costs, the extent that 

there is a substantial cost motive to do so. Therefore, we are not assessing any costs associated 

with the Tier 3 pentane blending provisions. In addition, pentane blending will likely be used in 

place of the butane blending already allowed. Consequently, there would be no new increase in 

the amount of testing and recordkeeping. 
5-92

Appendix A 

Linear Program Refinery Modeling Tables 
5-93

Table 5-39 – Summary of LP Refinery Modeling Ouput Information and the Resulting 

Cost of Octane Used in the Refinery-by-Refinery Cost Model 

(Cost of Recovering 1 Octane Number Loss in FCC Naphtha, no E15 in Gasoline Pool and Low 

NGL Prices) 

US Total PADD 1 PADD 2 PADD 3 PADD 4/5

Control Case Summer 374463 32827 93577 221108 26951

FCC naphtha volume Winter 425601 53282 116134 218249 37936

(thousand bbls) Annual 800,064

Objective Function Reference Case -118884419

(thousand dollars) Control Case -118634411

Change in Obj Funct -250.008

Cost 0.312 $/octane-bbl

0.744 c/octane-gal

Table 5-40 – Summary of LP Refinery Model Estimated Regular and Premium Marginal 

Production Costs and the Calculated Cost of Octane - Not Used in Refinery Cost Analysis 

(No E15 in Gasoline Pool and Low NGL Prices) 

Octane Number Cost Difference

(R+M)/2 Premium Regular c/gal $/bbl

PADD 1 93 264.36 254.27 10.09 4.2378

PADD 2 93 261.71 253.49 8.22 3.4524

PADD 3 93 262.31 252.23 10.08 4.2336

PADD 4/5 OC 91.5 259.72 251.99 7.73 3.2466

PADD 1 93 248.17 243.06 5.11 2.1462

PADD 2 93 221.55 218.09 3.46 1.4532

PADD 3 93 249.58 244.47 5.11 2.1462

PADD 4/5 OC 91.5 243.63 240.07 3.56 1.4952

$/ON-bbl c/ON-gal

PADD 1 3.192 0.532 1.266667

PADD 2 2.4528 0.4088 0.973333

PADD 3 3.1899 0.53165 1.265833

PADD 4/5 OC 2.3709 0.526867 1.254444

US 0.495089 1.178783

Summer

Winter

Annual Average

Marginal Price
5-94

Table 5-41 – PADDs 1 and 2 – Modeled Refinery Purchase Volumes for Reference and Low 

Octane LP Refinery Modeling Cases (thousand bbl/day) 

Ref Control Dif. Ref Control Dif. Ref Control Dif. Ref Control Dif.

PADD Crude 1,058 1,022 -36 1,728 1,728 0 2,903 2,924 21 4,245 4,246 1

GTL Naphtha 0 0 0 0 0 0 0 0 0 0 0 0

GTL Diesel 0 0 0 0 0 0 0 0 0 0 0 0

VGO HS 0 0 0 0 0 0 0 0 0 0 0 0

VGO LS 115 170 54 76 76 0 90 90 0 1 1 0

HS AR (A960) 0 0 0 0 0 0 0 0 0 0 0 0

LS AR (Alg) 47 66 19 0 0 0 0 0 0 0 0 0

Normal Butane 7 3 -4 166 165 -1 23 31 8 200 200 0

Isobutane 12 12 0 16 16 0 57 53 -4 56 56 0

MTBE 0 0 0 0 0 0 0 0 0 0 0 0

Ethanol - E10 311 310 0 295 295 0 238 238 0 231 231 0

Ethanol - E15 0 0 0 0 0 0 0 0 0 0 0 0

Ethanol - E85 21 21 0 20 20 0 16 16 0 15 15 0

Reformer Feed 0 0 0 0 0 0 0 0 0 0 0 0

Methanol 0 0 0 0 0 0 0 0 0 0 0 0

Natural Gas (FOE) 73 74 1 100 99 -1 201 198 -3 219 220 2

Hydrogen (MSCF) 0 0 0 0 0 0 0 0 0 0 0 0

Pentanes Plus 0 0 0 0 0 0 238 214 -24 0 0 0

Import CBOB 10% Reg 0 4 4 0 2 2 0 6 6 0 3 3

Import CBOB 10% Prem 0 0 0 0 0 0 0 0 0 0 0 0

Import RBOB 10% Reg 0 1 1 0 2 2 0 0 0 0 0 0

Import RBOB 10% Prem 0 0 0 0 0 0 0 0 0 0 0 0

Import Alkylate 0 0 0 0 0 0 0 0 0 0 0 0

Import Raffinate 25 25 0 50 50 0 0 0 0 0 0 0

Import Reformate 0 0 0 0 0 0 0 0 0 0 0 0

Import FCC Naphtha 0 0 0 0 0 0 0 0 0 0 0 0

Import Lt Naphtha 0 0 0 0 0 0 0 0 0 0 0 0

Import Hvy Naph 81 53 -28 0 0 0 0 0 0 0 0 0

Transfer Lt Naphtha 0 22 22 0 0 0 0 22 22 0 0 0

Transfer Reformate 0 68 68 0 0 0 0 0 0 0 0 0

Transfer Alkylate 0 23 23 0 0 0 0 0 0 0 0 0

Transfer FCC Naphtha 0 0 0 0 0 0 0 29 29 0 0 0

Transfer Raffinate 0 0 0 0 0 0 0 88 88 0 0 0

Transfer CBOB 10% Reg 0 1,508 1,508 0 1,254 1,254 0 116 116 0 0 0

Transfer CBOB 10% Prem 0 197 197 0 144 144 0 0 0 0 0 0

Transfer RBOB 10% Reg 0 260 260 0 275 275 0 0 0 0 0 0

Transfer RBOB 10% Prem 0 104 104 0 87 87 0 0 0 0 0 0

Isooctane 0 0 0 0 0 0 0 0 0 0 0 0

Isooctene 0 0 0 0 0 0 0 0 0 0 0 0

PADD 1

Summer Winter

PADD 2

Summer Winter
5-95

Table 5-42 – PADDs 3, 4 and 5 non-California - Modeled Refinery Purchase Volumes for 

Reference and Low Octane LP Refinery Modeling Cases (thousand bbl/day) 

Ref Control Dif. Ref Control Dif. Ref Control Dif. Ref Control Dif. Ref Control Dif. Ref Control Dif.

PADD Crude 7,408 7,409 1 6,368 6,377 9 1,437 1,425 -12 1,452 1,441 -12 12,806 12,781 -25 13,794 13,792 -2

GTL Naphtha 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

GTL Diesel 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

VGO HS 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

VGO LS 0 0 0 0 0 0 0 0 0 0 0 0 205 260 54 77 77 0

HS AR (A960) 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

LS AR (Alg) 750 750 0 750 750 0 0 0 0 0 0 0 797 816 19 750 750 0

Normal Butane 37 34 -2 216 216 0 24 24 0 77 75 -2 90 92 2 659 656 -3

Isobutane 0 0 0 0 0 0 6 7 1 3 3 1 75 72 -3 75 75 1

MTBE 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Ethanol - E10 142 142 0 137 137 0 80 80 0 76 76 0 771 770 0 739 739 0

Ethanol - E15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Ethanol - E85 10 10 0 9 9 0 5 5 0 5 5 0 51 51 0 49 49 0

Reformer Feed 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Methanol 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Natural Gas (FOE) 627 626 -1 607 606 -1 96 95 -1 100 99 -2 996 992 -4 1026 1024 -2

Hydrogen (MSCF) 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Pentanes Plus 250 250 0 0 0 0 60 60 0 0 13 13 548 524 -24 0 13 13

Import CBOB 10% Reg 0 0 0 0 0 0 2 2 0 1 1 0 2 12 10 1 7 6

Import CBOB 10% Prem 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Import RBOB 10% Reg 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 2 2

Import RBOB 10% Prem 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Import Alkylate 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Import Raffinate 0 0 0 0 0 0 10 10 0 0 0 0 35 35 0 50 50 0

Import Reformate 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Import FCC Naphtha 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Import Lt Naphtha 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Import Hvy Naph 100 100 0 0 0 0 0 0 0 0 0 0 181 153 -28 0 0 0

Transfer Lt Naphtha 0 0 0 0 0 0 0 0 0 0 0 0 0 44 44 0 0 0

Transfer Reformate 0 0 0 0 0 0 0 0 0 0 0 0 0 68 68 0 0 0

Transfer Alkylate 0 0 0 0 0 0 0 0 0 0 0 0 0 23 23 0 0 0

Transfer FCC Naphtha 0 0 0 0 0 0 0 0 0 0 0 0 0 29 29 0 0 0

Transfer Raffinate 0 0 0 0 0 0 0 0 0 0 0 0 0 88 88 0 0 0

Transfer CBOB 10% Reg 0 0 0 0 0 0 50 60 11 0 0 0 50 1684 1634 0 1254 1254

Transfer CBOB 10% Prem 0 0 0 0 0 0 0 0 0 0 0 0 0 197 197 0 144 144

Transfer RBOB 10% Reg 0 0 0 0 0 0 0 0 0 0 0 0 0 260 260 0 275 275

Transfer RBOB 10% Prem 0 0 0 0 0 0 0 0 0 0 0 0 0 104 104 0 87 87

Isooctane 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Isooctene 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

US Total

Summer Winter

PADD 3 PADD 4/5 nonCA

Summer Winter Summer Winter
5-96

Table 5-43 – PADDs 1 and 2 – Modeled Refinery Sale Volumes for Reference and Low 

Octane Cases (thousand bbl/day) 

Ref Control Dif. Ref Control Dif. Ref Control Dif. Ref Control Dif.

Propane 13 14 2 21 22 1 49 50 1 58 58 0

Propylene 25 25 0 25 25 0 40 40 0 40 40 0

Normal Butane 0 0 0 0 0 0 0 0 0 0 0 0

Isobutane 0 0 0 0 0 0 0 0 0 0 0 0

PC Naphtha 25 25 0 16 16 0 50 50 0 40 40 0

PC Gasoil 0 0 0 0 0 0 0 0 0 1,031 1,031 0

CG Reg 0 0 0 0 0 0 0 0 0 0 0 0

CG Prem 0 0 0 0 0 0 0 0 0 0 0 0

CG E10 Reg 1,669 1,669 0 1,562 1,562 0 1,785 1,785 0 1,721 1,721 0

CG E10 Prem 219 217 -2 168 168 0 227 227 0 219 219 0

RFG E10 Reg 1,072 1,072 0 1,057 1,057 0 302 302 0 305 305 0

RFG E10 Prem 115 115 0 139 139 0 38 38 0 39 39 0

CG E15 Reg 0 0 0 0 0 0 0 0 0 0 0 0

RFG E15 Reg 0 0 0 0 0 0 0 0 0 0 0 0

E85 to CG 17 17 0 16 16 0 18 18 0 17 17 0

E85 to RFG 11 11 0 11 11 0 3 3 0 3 3 0

Transfer CBOB 10% Reg 0 0 0 0 0 0 0 0 0 0 0 0

Transfer CBOB 10% Prem 0 0 0 0 0 0 0 0 0 0 0 0

Transfer RBOB 10% Reg 0 0 0 0 0 0 0 0 0 0 0 0

Transfer RBOB 10% Prem 0 0 0 0 0 0 0 0 0 0 0 0

Export CBOB 10% Reg 0 0 0 0 0 0 0 0 0 0 0 0

Export RBOB 10% Reg 0 0 0 0 0 0 0 0 0 0 0 0

Jet/Kero A (450ppm) 70 70 0 70 70 0 189 189 0 185 185 0

X-Fer Diesel Rundown to Storage 0 0 0 0 0 0 0 0 0 0 0 0

HSD Gr 76 (0.2%) 0 0 0 0 0 0 0 0 0 0 0 0

LSD Gr 74 (.05%) 0 0 0 0 0 0 0 0 0 0 0 0

ULSD (15 ppm) 469 469 0 820 820 0 767 752 -15 680 680 0

CARB Diesel 0 0 0 0 0 0 0 0 0 0 0 0

X-Fer C5's to Storage 0 0 0 0 0 0 0 0 0 0 0 0

1% Residual Fuel 0 0 0 0 0 0 0 0 0 0 0 0

Residual Fuel 30 30 0 50 50 0 39 39 0 39 39 0

Slurry 0 0 0 40 40 0 80 78 -2 97 97 0

Asphalt & Wax 118 118 0 73 73 0 210 210 0 210 210 0

Gasoil 0 0 0 0 0 0 10 10 0 8 8 0

Lubes 19 19 0 19 19 0 8 8 0 8 8 0

Benzene 2 2 0 2 2 0 19 19 0 22 22 0

Toluene 0 0 0 0 0 0 0 0 0 0 0 0

Xylenes 0 0 0 0 0 0 0 0 0 0 0 0

Cumene 0 0 0 0 0 0 0 0 0 0 0 0

Cyclohexane 0 0 0 0 0 0 0 0 0 0 0 0

Transfer Raffinate 0 0 0 0 0 0 0 0 0 0 0 0

Transfer Alkylate 0 0 0 0 0 0 0 0 0 0 0 0

Transfer Reformate 0 0 0 0 0 0 0 0 0 0 0 0

Transfer FCC naphtha 0 0 0 0 0 0 0 0 0 0 0 0

Transfer Lt Naphtha 0 0 0 0 0 0 0 0 0 0 0 0

Transfer Blendstock 0 0 0 0 0 0 0 0 0 0 0 0

Sulfur (STons) 5 5 0 8 8 0 20 21 0 26 26 0

Coke (STon) 6 5 -1 42 42 0 41 41 -1 95 95 0

Summer Winter

PADD 1 PADD 2

Summer Winter
5-97

Table 5-44 – PADDs 3, 4 and 5 non-California – Modeled Refinery Sale Volumes for 

Reference and Low Octane Cases (thousand bbl/day) 

Ref Control Dif. Ref Control Dif. Ref Control Dif. Ref Control Dif. Ref Control Dif. Ref Control Dif.

Propane 101 103 2 69 70 1 17 17 0 17 17 0 179 184 4 164 167 2

Propylene 250 250 0 250 250 0 15 15 0 15 15 0 330 330 0 330 330 0

Normal Butane 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Isobutane 4 0 -4 0 0 0 0 0 0 0 0 0 4 0 -4 0 0 0

PC Naphtha 550 550 0 433 433 0 0 0 0 0 0 0 625 625 0 489 489 0

PC Gasoil 158 158 0 158 158 0 0 0 0 0 0 0 158 158 0 1189 1189 0

CG Reg 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

CG Prem 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

CG E10 Reg 968 968 0 930 930 0 686 686 0 650 650 0 5108 5108 0 4862 4862 0

CG E10 Prem 74 74 0 71 71 0 107 107 0 101 101 0 627 625 -2 559 559 0

RFG E10 Reg 334 334 0 325 325 0 0 0 0 0 0 0 1708 1708 0 1687 1687 0

RFG E10 Prem 33 33 0 31 32 1 0 0 0 0 0 0 187 187 0 208 210 1

CG E15 Reg 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

RFG E15 Reg 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

E85 to CG 10 10 0 9 9 0 7 7 0 6 6 0 51 51 0 49 49 0

E85 to RFG 3 3 0 3 3 0 0 0 0 0 0 0 17 17 0 17 17 0

Transfer CBOB 10% Reg 1,718 1,684 -33 1,251 1,254 4 0 0 0 0 0 0 1718 1684 -33 1251 1254 4

Transfer CBOB 10% Prem 198 197 -2 144 144 0 0 0 0 0 0 0 198 197 -2 144 144 0

Transfer RBOB 10% Reg 259 260 1 242 275 34 0 0 0 0 0 0 259 260 1 242 275 34

Transfer RBOB 10% Prem 104 104 -1 120 87 -34 0 0 0 0 0 0 104 104 -1 120 87 -34

Export CBOB 10% Reg 7 12 4 7 7 0 0 0 0 0 0 0 7 12 4 7 7 0

Export RBOB 10% Reg 1 1 0 2 2 0 0 0 0 0 0 0 1 1 0 2 2 0

Jet/Kero A (450ppm) 895 895 0 819 819 0 233 233 0 236 236 0 1387 1387 0 1310 1310 0

X-Fer Diesel Rundown to Storage 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

HSD Gr 76 (0.2%) 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

LSD Gr 74 (.05%) 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

ULSD (15 ppm) 2,119 2,135 15 2,091 2,091 0 518 517 -1 513 513 0 3874 3873 0 4104 4104 0

CARB Diesel 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

X-Fer C5's to Storage 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

1% Residual Fuel 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Residual Fuel 125 125 0 125 125 0 39 37 -1 33 32 -1 233 231 -1 247 246 -1

Slurry 157 157 0 102 102 1 20 20 0 20 20 0 257 256 -2 259 260 1

Asphalt & Wax 250 250 0 250 250 0 30 30 0 30 30 0 608 608 0 563 563 0

Gasoil 0 0 0 0 0 0 0 0 0 0 0 0 10 10 0 8 8 0

Lubes 158 158 0 158 158 0 0 0 0 0 0 0 184 184 0 184 184 0

Benzene 51 51 0 50 50 0 0 0 0 0 0 0 72 72 0 74 74 0

Toluene 34 34 0 34 35 0 0 0 0 0 0 0 34 34 0 34 35 0

Xylenes 8 8 0 8 8 0 0 0 0 0 0 0 8 8 0 8 8 0

Cumene 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Cyclohexane 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Transfer Raffinate 90 89 -1 1 1 0 0 0 0 0 0 0 90 89 -1 1 1 0

Transfer Alkylate 120 83 -37 1 1 0 0 0 0 0 0 0 120 83 -37 1 1 0

Transfer Reformate 63 68 5 0 0 0 0 0 0 0 0 0 63 68 5 0 0 0

Transfer FCC naphtha 0 29 29 0 0 0 0 0 0 0 0 0 0 29 29 0 0 0

Transfer Lt Naphtha 5 22 17 0 0 0 0 0 0 0 0 0 5 22 17 0 0 0

Transfer Blendstock 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Sulfur (STons) 64 64 0 55 55 0 10 10 0 11 11 0 99 100 1 99 99 0

Coke (STon) 237 237 0 173 174 0 44 43 0 44 43 0 328 326 -2 354 354 0

PADD 3 PADD 4/5 nonCA US Total

Summer Winter Summer Winter Summer Winter
5-98

Table 5-45 - PADD 1 Modeled Refinery Unit Throughput Volumes for Reference and Low 

Octane Cases (Thousand bbl/day)

PADD 1

Refinery Units Summer Winter Summer Winter Summer Winter

Crude Tower 1,250 1,058 1,728 1,022 1,728 -36 0

Vacuum Tower 560 454 731 442 731 -11 0

Sats Gas Plant 0 52 64 51 66 0 2

Unsats Gas Plant 0 123 151 142 151 19 0

FCC DeC5 Tower 0 0 0 0 0 0 0

FCC 494 467 550 535 550 68 0

FCC Splitter 0 257 298 296 298 39 0

Hydrocracker 44 44 49 44 49 0 0

H-Oil Unit 0 0 0 0 0 0 0

Delayed Coker 82 25 172 21 172 -4 0

Visbreaker 0 0 0 0 0 0 0

Thermal Naphtha Splitter 0 3 21 3 21 0 0

CRU Reformer 239 102 124 101 162 -1 39

SRU Reformer 0 0 0 0 0 0 0

BTX Reformer 0 11 11 11 11 0 0

C4 Isomerization 18 16 16 16 16 0 0

C5/C6 Isomerization 9 9 0 9 0 0 0

HF Alkylation 49 44 44 44 44 0 0

H2SO4 Alkylation 34 51 65 58 66 7 1

Dimersol 0 0 0 0 0 0 0

Cat Poly 6 1 6 6 6 5 0

Isooctane 0 0 0 0 0 0 0

DHT - Total 585 454 807 454 807 0 0

DHT 2nd RCT - Total 0 416 746 416 746 0 0

DHT Arom Saturation 0 0 0 0 0 0 0

NHT - Total Fd 371 175 316 170 316 -5 0

CGH - Generic 211 152 152 152 152 0 0

CGH - Olefin Sat'n 211 0 0 0 0 0 0

FCCU Fd HDT 44 40 40 40 40 0 0

LSR Splitter 0 49 87 47 87 -2 0

LSR Bz Saturator 0 0 0 0 0 0 0

Reformate Saturator 0 6 1 6 1 0 0

Reformate Splitter 0 19 3 19 3 0 0

SDA 33 5 15 5 15 0 0

MTBE 0 0 0 0 0 0 0

TAME 0 0 0 0 0 0 0

Hydrogen Plant - Total MSCF 113 493 695 519 673 25 -23

Lube Unit 58 53 53 53 53 0 0

Sulfur Plant 1 1 1 1 1 0 0

Merox Jet 0 0 0 0 0 0 0

Merox Diesel 0 0 0 0 0 0 0

BTX Reformer - Tower feed 4 4 4 4 4 0 0

BTX Reformer - Extract feed 9 9 9 9 9 0 0

Toluene Dealkyation 0 0 0 0 0 0 0

Cumene 0 0 0 0 0 0 0

Cyclohexane 0 0 0 0 0 0 0

Actual 

Capacity 

in 2012

2018 Ref case Control Case Minus 1 

ON

Control Case Relative 

to Ref Case
5-99

Table 5-46 - PADD 2 Modeled Refinery Unit Throughput Volumes for Reference and Low 

Octane Cases (Thousand bbl/day) 

PADD 2

Refinery Units Summer Winter Summer Winter Summer Winter

Crude Tower 4,005 2,903 4,245 2,924 4,246 21 1

Vacuum Tower 1,707 1,229 1,840 1,221 1,841 -8 0

Sats Gas Plant 0 138 144 141 144 3 0

Unsats Gas Plant 0 301 330 296 330 -6 0

FCC DeC5 Tower 0 0 0 0 0 0 0

FCC 1,314 1,066 1,134 1,047 1,134 -19 0

FCC Splitter 0 616 649 603 649 -12 0

Hydrocracker 307 276 276 276 276 0 0

H-Oil Unit 0 0 0 0 0 0 0

Delayed Coker 508 168 388 166 388 -3 0

Visbreaker 0 0 0 0 0 0 0

Thermal Naphtha Splitter 0 20 47 20 47 0 0

CRU Reformer 859 428 550 483 550 55 0

SRU Reformer 0 0 0 0 0 0 0

BTX Reformer 0 100 127 100 127 0 0

C4 Isomerization 28 25 25 25 25 0 0

C5/C6 Isomerization 178 153 118 156 150 2 32

HF Alkylation 175 157 150 157 157 0 7

H2SO4 Alkylation 98 104 104 97 97 -6 -6

Dimersol 3 0 3 0 3 0 0

Cat Poly 5 0 8 0 9 0 1

Isooctane 0 0 0 0 0 0 0

DHT - Total 1,526 789 633 770 634 -19 0

DHT 2nd RCT - Total 0 588 441 572 441 -16 0

DHT Arom Saturation 6 0 0 0 0 0 0

NHT - Total Fd 1,324 620 965 677 966 57 0

CGH - Generic 511 318 232 312 232 -6 0

CGH - Olefin Sat'n 511 0 0 0 0 0 0

FCCU Fd HDT 576 518 518 518 518 0 0

LSR Splitter 0 57 85 59 86 3 1

LSR Bz Saturator 0 0 0 0 0 0 0

Reformate Saturator 0 1 1 1 1 0 0

Reformate Splitter 0 3 3 3 3 0 0

SDA 54 54 54 54 54 0 0

MTBE 0 0 0 0 0 0 0

TAME 0 0 0 0 0 0 0

Hydrogen Plant - Total MSCF 956 1,170 1,171 1,108 1,176 -62 5

Lube Unit 25 23 23 23 23 0 0

Sulfur Plant 8 4 5 4 5 0 0

Merox Jet 0 0 0 0 0 0 0

Merox Diesel 0 0 0 0 0 0 0

BTX Reformer - Tower feed 43 37 43 37 43 0 0

BTX Reformer - Extract feed 80 80 80 80 80 0 0

Toluene Dealkyation 0 0 0 0 0 0 0

Cumene 0 0 0 0 0 0 0

Cyclohexane 0 0 0 0 0 0 0

Actual 

Capacity 

in 2012

2018 Ref case Control Case Minus 1 

ON

Control Case Relative 

to Ref Case
5-100

Table 5-47 - PADD 3 Modeled Throughput Volumes for Refinery Units for Reference and 

Low Octane Cases (Thousand bbl/day)

PADD 3

Refinery Units Summer Winter Summer Winter Summer Winter

Crude Tower 9,567 7,408 6,368 7,409 6,377 1 9

Vacuum Tower 4,778 3,382 2,882 3,383 2,885 1 4

Sats Gas Plant 0 424 366 428 369 4 3

Unsats Gas Plant 0 843 736 848 738 5 3

FCC DeC5 Tower 0 0 0 0 0 0 0

FCC 3,120 2,736 2,089 2,736 2,097 0 9

FCC Splitter 0 1,515 1,109 1,511 1,114 -4 4

Hydrocracker 1,029 1,037 1,037 1,037 1,037 0 0

H-Oil Unit 0 110 110 110 110 0 0

Delayed Coker 1,604 859 629 859 631 0 2

Visbreaker 51 46 46 46 46 0 0

Thermal Naphtha Splitter 0 104 77 104 77 0 0

CRU Reformer 1,665 909 725 945 750 36 25

SRU Reformer 0 0 0 0 0 0 0

BTX Reformer 0 256 256 256 256 0 0

C4 Isomerization 95 86 70 86 71 0 1

C5/C6 Isomerization 323 0 0 13 0 13 0

HF Alkylation 297 267 190 267 186 0 -4

H2SO4 Alkylation 311 280 280 287 287 7 7

Dimersol 19 0 0 0 0 0 0

Cat Poly 22 0 0 0 0 0 0

Isooctane 0 0 0 0 0 0 0

DHT - Total 4,339 2,230 2,107 2,246 2,106 17 0

DHT 2nd RCT - Total 0 1,643 1,643 1,659 1,643 16 0

DHT Arom Saturation 4 0 0 0 0 0 0

NHT - Total Fd 2,677 1,078 888 1,080 909 2 20

CGH - Generic 1,613 690 396 673 398 -18 1

CGH - Olefin Sat'n 1,613 0 0 0 0 0 0

FCCU Fd HDT 1,822 1,640 1,640 1,640 1,640 0 0

LSR Splitter 0 1 1 1 1 0 0

LSR Bz Saturator 0 0 0 0 0 0 0

Reformate Saturator 0 10 1 10 1 0 0

Reformate Splitter 0 30 3 30 3 0 0

SDA 433 389 389 389 389 0 0

MTBE 28 0 0 0 0 0 0

TAME 3 0 0 0 0 0 0

Hydrogen Plant - Total MSCF 2,004 4,287 4,301 4,282 4,286 -5 -15

Lube Unit 530 440 440 440 440 0 0

Sulfur Plant 27 13 11 13 11 0 0

Merox Jet 0 0 0 0 0 0 0

Merox Diesel 0 0 0 0 0 0 0

BTX Reformer - Tower feed 93 93 93 93 93 0 0

BTX Reformer - Extract feed 204 204 204 204 204 0 0

Toluene Dealkyation 0 0 0 0 0 0 0

Cumene 0 0 0 0 0 0 0

Cyclohexane 0 0 0 0 0 0 0

Actual 

Capacity 

in 2012

2018 Ref case Control Case Minus 1 

ON

Control Case Relative 

to Ref Case
5-101

Table 5-48 - PADD 4 and 5 non-California Modeled Throughput Volumes for Refinery 

Units for Reference and Low Octane Cases (Thousand bbl/day)

PADD 4 and 5 nonCA

Refinery Units Summer Winter Summer Winter Summer Winter

Crude Tower 1,791 1,437 1,452 1,425 1,441 -12 -12

Vacuum Tower 637 647 650 642 645 -5 -5

Sats Gas Plant 0 64 68 62 67 -1 -1

Unsats Gas Plant 0 104 105 103 104 -1 -1

FCC DeC5 Tower 0 0 0 0 0 0 0

FCC 368 376 376 374 374 -3 -3

FCC Splitter 0 146 147 143 145 -2 -2

Hydrocracker 128 130 146 130 146 0 0

H-Oil Unit 0 0 0 0 0 0 0

Delayed Coker 173 154 155 152 153 -2 -2

Visbreaker 56 0 0 0 0 0 0

Thermal Naphtha Splitter 0 18 18 18 18 0 0

CRU Reformer 0 92 95 98 106 6 11

SRU Reformer 273 0 0 0 0 0 0

BTX Reformer 0 0 0 0 0 0 0

C4 Isomerization 26 23 23 23 23 0 0

C5/C6 Isomerization 45 41 0 41 0 0 0

HF Alkylation 39 39 39 39 39 0 0

H2SO4 Alkylation 47 48 48 47 47 -1 -1

Dimersol 1 0 0 0 0 0 0

Cat Poly 10 0 0 0 0 0 0

Isooctane 0 0 0 0 0 0 0

DHT - Total 584 557 559 551 553 -6 -6

DHT 2nd RCT - Total 0 404 404 398 398 -6 -6

DHT Arom Saturation 0 0 0 0 0 0 0

NHT - Total Fd 391 297 300 295 297 -3 -3

CGH - Generic 132 107 107 107 107 0 0

CGH - Olefin Sat'n 132 0 0 0 0 0 0

FCCU Fd HDT 121 109 109 109 109 0 0

LSR Splitter 0 100 100 100 100 0 0

LSR Bz Saturator 0 0 0 0 0 0 0

Reformate Saturator 0 1 10 1 8 0 -2

Reformate Splitter 0 3 30 3 24 0 -6

SDA 58 58 58 58 58 0 0

MTBE 0 0 0 0 0 0 0

TAME 0 0 0 0 0 0 0

Hydrogen Plant - Total MSCF 518 679 722 665 704 -14 -17

Lube Unit 0 0 0 0 0 0 0

Sulfur Plant 2 2 2 2 2 0 0

Merox Jet 0 0 0 0 0 0 0

Merox Diesel 0 0 0 0 0 0 0

BTX Reformer - Tower feed 0 0 0 0 0 0 0

BTX Reformer - Extract feed 0 0 0 0 0 0 0

Toluene Dealkyation 0 0 0 0 0 0 0

Cumene 0 0 0 0 0 0 0

Cyclohexane 0 0 0 0 0 0 0

Control Case Minus 1 

ON

Control Case Relative 

to Ref Case

Actual 

Capacity 

in 2012

2018 Ref case
5-102

Table 5-49 – PADDs 1-4 and 5 non-California Modeled Throughput Volumes for Refinery 

Units for Reference and Low Octane Cases (Thousand bbl/day)

PADDs 1 -4 and 5 nonCA

Refinery Units Summer Winter Summer Winter Summer Winter

Crude Tower 16,613 12,806 13,794 12,781 13,792 -25 -2

Vacuum Tower 7,683 5,712 6,103 5,688 6,102 -24 -1

Sats Gas Plant 0 677 642 682 647 5 4

Unsats Gas Plant 0 1,371 1,321 1,389 1,323 18 2

FCC DeC5 Tower 0 0 0 0 0 0 0

FCC 5,296 4,646 4,149 4,692 4,155 46 6

FCC Splitter 0 2,533 2,203 2,554 2,206 21 2

Hydrocracker 1,508 1,488 1,508 1,488 1,508 0 0

H-Oil Unit 0 110 110 110 110 0 0

Delayed Coker 2,366 1,207 1,344 1,198 1,344 -9 0

Visbreaker 107 46 46 46 46 0 0

Thermal Naphtha Splitter 0 145 162 144 162 -1 0

CRU Reformer 2,763 1,532 1,494 1,627 1,568 95 75

SRU Reformer 273 0 0 0 0 0 0

BTX Reformer 0 367 394 368 394 0 0

C4 Isomerization 168 151 135 151 136 0 1

C5/C6 Isomerization 556 203 118 218 150 15 32

HF Alkylation 560 508 424 508 426 0 3

H2SO4 Alkylation 490 483 497 490 498 7 0

Dimersol 23 0 4 0 4 0 0

Cat Poly 43 2 14 6 15 5 1

Isooctane 0 0 0 0 0 0 0

DHT - Total 7,034 4,030 4,106 4,021 4,100 -9 -6

DHT 2nd RCT - Total 0 3,052 3,234 3,045 3,228 -6 -6

DHT Arom Saturation 10 0 0 0 0 0 0

NHT - Total Fd 4,763 2,170 2,469 2,222 2,487 52 18

CGH - Generic 2,467 1,267 887 1,244 888 -24 2

CGH - Olefin Sat'n 2,467 0 0 0 0 0 0

FCCU Fd HDT 2,564 2,308 2,308 2,308 2,308 0 0

LSR Splitter 0 206 273 207 274 1 1

LSR Bz Saturator 0 0 0 0 0 0 0

Reformate Saturator 0 18 13 18 11 0 -2

Reformate Splitter 0 55 39 55 33 0 -6

SDA 577 506 516 506 516 0 0

MTBE 28 0 0 0 0 0 0

TAME 3 0 0 0 0 0 0

Hydrogen Plant - Total MSCF 3,591 6,630 6,889 6,574 6,839 -56 -50

Lube Unit 614 515 515 515 515 0 0

Sulfur Plant 38 20 20 20 20 0 0

Merox Jet 0 0 0 0 0 0 0

Merox Diesel 0 0 0 0 0 0 0

BTX Reformer - Tower feed 140 135 140 135 140 0 0

BTX Reformer - Extract feed 293 293 293 293 293 0 0

Toluene Dealkyation 0 0 0 0 0 0 0

Cumene 0 0 0 0 0 0 0

Cyclohexane 0 0 0 0 0 0 0

Actual 

Capacity 

in 2012

2018 Ref case Control Case Minus 1 

ON

Control Case Relative 

to Ref Case
5-103

Table 5-50 - PADD 1 - Gasoline Qualities Estimated by LP Refinery Modeling for 

Reference and Octane Recovery Cases 

PADD 1

CG RFG Pool CG RFG Pool CG RFG Pool CG RFG Pool

Energy (MMBTU/bbl) 5.00 5.00 5.00 4.92 4.87 4.90 5.01 4.99 5.00 4.92 4.87 4.90

Density (lb/bbl) 259 261 260 255 254 255 260 261 260 255 254 255

Sulfur (ppm) 26 26 26 15 18 16 25 25 25 15 18 16

% at 200 57 54 56 60 62 61 56 54 56 60 62 61

% at 300 83 86 84 87 90 88 83 86 84 87 90 88

RVP (psi) 9.1 7.0 8.3 13.0 13.0 13.0 9.1 7.0 8.3 13.0 13.0 13.0

T10 (F) 125 139 131 100 101 101 125 139 131 100 101 101

T50 (F) 186 192 188 179 176 178 187 191 189 179 176 178

T90 (F) 328 316 323 310 300 306 329 316 324 310 300 306

Driveability 1067 1093 1077 991 974 984 1072 1092 1080 991 974 984

Vapor Lock 132 144 137 110 110 110 132 144 137 110 110 110

Aromatics (vol%) 21.8 18.7 20.6 17.6 16.1 17.0 23.2 18.9 21.5 17.6 16.1 17.0

Benzene (vol%) 0.61 0.59 0.60 0.61 0.63 0.62 0.61 0.61 0.61 0.61 0.63 0.62

Olefins (vol%) 10.8 8.7 9.9 10.7 9.6 10.2 10.1 8.9 9.6 10.7 9.6 10.2

Alcohol (vol%) 11.5 11.6 11.5 11.5 11.5 11.5 11.5 11.6 11.5 11.5 11.5 11.5

Oxygen (wt%) 4.27 4.29 4.28 4.34 4.35 4.34 4.27 4.29 4.28 4.34 4.35 4.34

Volume (Kbbl/day) 1,864,595 1,241,809 3,106,404 1,745,324 1,181,174 2,926,498 1,864,595 1,241,809 3,106,404 1,745,324 1,181,174 2,926,498

2018 Reference Case 2018 minus 1ON in FCC naphtha

Summer Winter Summer Winter

Table 5-51 - PADD 2 - Gasoline Qualities Estimated by LP Refinery Modeling for 

Reference and Octane Recovery Cases 

PADD 2

CG RFG Pool CG RFG Pool CG RFG Pool CG RFG Pool

Energy (MMBTU/bbl) 4.93 4.99 4.94 4.86 4.87 4.86 4.93 4.99 4.94 4.86 4.87 4.86

Density (lb/bbl) 259 260 259 257 257 257 259 259 259 257 257 257

Sulfur (ppm) 26 14 24 23 26 23 26 12 24 23 26 23

% at 200 60 57 60 62 62 62 61 57 60 62 62 62

% at 300 86 85 86 87 88 87 86 85 86 87 88 87

RVP (psi) 9.2 7.0 8.9 12.7 12.7 12.7 9.2 7.0 8.9 12.7 12.7 12.7

T10 (F) 125 139 127 103 102 103 125 139 127 103 102 103

T50 (F) 178 186 180 176 175 176 178 186 179 176 175 176

T90 (F) 317 321 318 311 309 311 317 321 318 311 309 311

Driveability 1033 1081 1040 986 982 985 1032 1079 1039 986 982 985

Vapor Lock 130 143 132 110 110 110 130 143 132 110 110 110

Aromatics (vol%) 21.5 20.6 21.4 19.9 18.7 19.8 21.6 20.3 21.4 19.9 18.7 19.8

Benzene (vol%) 0.64 0.68 0.64 0.55 0.67 0.57 0.61 0.67 0.62 0.55 0.67 0.57

Olefins (vol%) 8.1 4.8 7.6 9.2 10.6 9.4 8.5 4.9 7.9 9.2 10.6 9.4

Alcohol (vol%) 11.6 11.6 11.6 11.6 11.6 11.6 11.6 11.6 11.6 11.6 11.6 11.6

Oxygen (wt%) 4.33 4.31 4.32 4.35 4.35 4.35 4.33 4.32 4.33 4.35 4.35 4.35

Volume (Kbbl/day) 2,068,931 349,978 2,418,909 1,959,358 346,825 2,306,183 2,068,931 349,978 2,418,909 1,959,358 346,825 2,306,183

2018 Reference Case 2018 minus 1ON in FCC naphtha

Summer Winter Summer Winter
5-104

Table 5-52 - PADD 3 - Gasoline Qualities Estimated by LP Refinery Modeling for 

Reference and Octane Recovery Cases 

PADD 3

CG RFG Pool CG RFG Pool CG RFG Pool CG RFG Pool

Energy (MMBTU/bbl) 5.01 5.07 5.02 4.98 5.05 5.00 5.02 5.03 5.02 4.98 5.05 5.00

Density (lb/bbl) 259 260 260 257 257 257 260 260 260 257 257 257

Sulfur (ppm) 26 11 22 15 9 14 25 20 24 15 9 14

% at 200 58 55 57 59 52 57 58 57 58 59 52 57

% at 300 83 83 83 85 80 84 83 84 83 85 80 84

RVP (psi) 9.0 7.0 8.5 11.1 11.2 11.1 9.0 7.0 8.5 11.1 11.2 11.1

T10 (F) 125 139 129 112 112 112 126 139 129 112 112 112

T50 (F) 183 190 185 181 195 185 184 186 184 181 195 185

T90 (F) 330 330 330 318 341 324 331 326 330 318 341 324

Driveability 1061 1100 1072 1025 1087 1041 1065 1086 1071 1025 1087 1041

Vapor Lock 132 143 135 120 121 120 132 143 135 120 121 120

Aromatics (vol%) 22.2 19.3 21.5 19.0 18.0 18.7 23.5 19.8 22.5 19.0 18.0 18.7

Benzene (vol%) 0.61 0.51 0.59 0.62 0.36 0.55 0.62 0.67 0.63 0.62 0.36 0.55

Olefins (vol%) 10.8 4.4 9.1 11.2 1.7 8.7 10.2 6.6 9.2 11.2 1.7 8.7

Alcohol (vol%) 11.5 11.6 11.5 11.5 11.5 11.5 11.5 11.6 11.5 11.5 11.5 11.5

Oxygen (wt%) 4.27 4.32 4.28 4.30 4.31 4.30 4.26 4.32 4.27 4.30 4.31 4.30

Volume (Kbbl/day) 1,051,761 378,078 1,429,839 1,010,516 352,882 1,363,398 1,051,761 378,078 1,429,839 1,010,516 352,882 1,363,398

2018 Reference Case 2018 minus 1ON in FCC naphtha

Summer Winter Summer Winter

Table 5-53 - PADD 4 and 5 non-California - Gasoline Qualities Estimated by LP Refinery 

Modeling for Reference and Octane Recovery Cases 

PADD 4/5 nonCA

CG RFG Pool CG RFG Pool CG RFG Pool CG RFG Pool

Energy (MMBTU/bbl) 4.90 0.00 4.90 4.87 0.00 4.87 4.90 0.00 4.90 4.87 0.00 4.87

Density (lb/bbl) 259 0 259 256 0 256 259 0 259 256 0 256

Sulfur (ppm) 22 0 22 28 0 28 20 0 20 28 0 28

% at 200 65 0 65 67 0 67 65 0 65 67 0 67

% at 300 93 0 93 93 0 93 93 0 93 93 0 93

RVP (psi) 9.3 0.0 9.3 12.6 0.0 12.6 9.3 0.0 9.3 12.6 0.0 12.6

T10 (F) 124 0 124 102 0 102 123 0 123 102 0 102

T50 (F) 170 0 170 165 0 165 170 0 170 165 0 165

T90 (F) 286 0 286 282 0 282 286 0 286 282 0 282

Driveability 978 0 978 926 0 926 978 0 978 926 0 926

Vapor Lock 129 0 129 110 0 110 129 0 129 110 0 110

Aromatics (vol%) 16.1 0.0 16.1 14.4 0.0 14.4 15.9 0.0 15.9 14.4 0.0 14.4

Benzene (vol%) 1.16 0.00 1.16 0.43 0.00 0.43 1.11 0.00 1.11 0.43 0.00 0.43

Olefins (vol%) 7.5 0.0 7.5 7.7 0.0 7.7 7.6 0.0 7.6 7.7 0.0 7.7

Alcohol (vol%) 11.6 0.0 11.6 11.6 0.0 11.6 11.6 0.0 11.6 11.6 0.0 11.6

Oxygen (wt%) 4.33 0.00 4.33 4.37 0.00 4.37 4.33 0.00 4.33 4.37 0.00 4.37

Volume (Kbbl/day) 801,247 0 801,247 758,461 0 758,461 801,247 0 801,247 758,461 0 758,461

2018 Reference Case 2018 minus 1ON in FCC naphtha

Summer Winter Summer Winter
5-105

Table 5-54 - PADD 1 Gasoline Qualities Estimated by LP Refinery Modeling for Reference, 

E10 and E15 Cases 

CG RFG Pool CG RFG Pool CG RFG Pool CG RFG Pool CG RFG Pool CG RFG

Energy (MMBTU/bbl) 4.90 5.06 5.10 4.99 4.96 5.02 5.07 5.05 5.06 5.02 4.94 4.98 4.99 4.92 4.96 4.92 4.89

Density (lb/bbl) 252.86 260.41 259.87 253.26 255.50 255.32 258.49 261.05 259.52 255.89 256.26 256.05 260.93 259.32 260.27 256.64 255.49

Sulfur (ppm) 28.00 23.67 23.47 2.91 14.71 14.35 10.57 23.33 15.71 2.49 15.98 8.24 20.99 27.59 23.71 25.86 25.40

% at 200 62.51 53.59 48.71 45.27 61.47 54.10 56.09 54.08 55.28 55.40 62.22 58.30 63.01 62.44 62.77 64.96 65.14

% at 300 95.61 85.52 84.11 80.77 88.89 85.91 85.30 86.18 85.65 83.29 89.53 85.94 86.70 87.83 87.17 86.82 87.94

RVP (psi) 8.40 7.00 7.76 13.95 12.96 12.38 9.40 7.00 8.43 13.17 12.96 13.08 8.40 7.00 7.82 12.68 12.85

T10 (F) 128.15 139.22 134.25 98.33 101.74 105.33 123.48 138.75 129.63 99.94 101.49 100.60 129.78 138.64 133.43 102.09 102.18

T50 (F) 174.28 192.49 202.45 209.47 176.41 191.45 187.38 191.49 189.04 188.80 174.87 182.86 173.26 174.42 173.73 169.28 168.91

T90 (F) 272.12 317.99 324.41 339.58 302.70 316.22 318.99 315.01 317.39 328.14 299.79 316.06 312.62 307.52 310.52 312.10 307.01

Driveability 987.19 1097.88 1126.11 1104.02 977.92 1041.25 1059.49 1092.27 1072.69 1036.80 970.86 1008.71 1020.79 1034.48 1026.43 968.09 962.01

Vapor Lock 135.42 144.26 141.40 109.71 109.71 114.91 129.82 144.30 135.65 109.71 109.71 109.71 133.09 141.91 136.72 109.71 109.71

Aromatics (vol%) 10.11 18.99 23.77 24.31 18.93 22.55 20.75 18.79 19.96 20.23 19.34 19.85 20.25 14.09 17.71 17.13 14.46

Benzene (vol%) 0.72 0.58 0.67 0.92 0.59 0.65 0.52 0.58 0.54 0.54 0.59 0.56 0.76 0.90 0.81 0.50 0.45

Olefins (vol%) 19.67 8.00 14.36 4.67 10.28 13.74 10.02 11.98 10.81 7.51 14.52 10.50 11.33 6.33 9.27 10.23 5.57

Alcohol (vol%) 0.00 10.00 4.16 0.00 10.00 4.36 10.00 10.00 10.00 10.00 10.00 10.00 15.00 15.00 15.00 15.00 15.00

Oxygen (wt%) 0.00 3.70 1.54 0.00 3.77 1.64 3.73 3.69 3.71 3.77 3.76 3.76 5.54 5.58 5.56 5.63 5.66

Volumes (kbbl/day) 21,942 1,111,857 2,671,322 160,860 1,121,901 2,574,564 1,681,574 1,134,711 2,816,285 1,504,982 1,116,727 2,621,709 1,754,900 1,229,826 2,984,726 1,570,606 1,165,422

Gasoline Qualities and 

Volume for PADD 1

2005 in 2030 E10 E15

Summer Winter Summer Winter Summer Winter
5-106

Table 5-55 - PADD 2 Gasoline Qualities Estimated by LP Refinery Modeling for Reference, 

E10 and E15 Cases 

CG RFG Pool CG RFG Pool CG RFG Pool CG RFG Pool CG RFG Pool CG RFG

Energy (MMBTU/bbl) 4.91 5.02 4.93 5.02 4.75 4.97 4.92 5.02 4.94 4.89 4.85 4.89 4.92 4.91 4.92 4.87 4.77

Density (lb/bbl) 256.73 260.54 257.33 256.45 252.44 255.79 257.04 260.49 257.61 258.44 256.94 258.19 259.31 259.23 259.30 260.25 256.17

Sulfur (ppm) 25.00 19.56 24.15 25.31 24.84 25.24 24.87 21.47 24.31 23.87 22.21 23.60 28.00 28.00 28.00 28.00 25.11

% at 200 60.99 54.39 59.95 49.26 71.10 52.81 60.45 54.40 59.45 57.80 60.38 58.22 64.60 64.60 64.60 63.37 70.07

% at 300 89.09 85.63 88.54 82.83 94.01 84.65 88.51 85.71 88.05 85.60 87.22 85.86 87.92 89.19 88.12 84.75 89.69

RVP (psi) 9.45 7.00 9.07 13.31 12.27 13.14 9.49 7.00 9.08 12.92 12.79 12.89 8.60 7.00 8.35 12.54 12.28

T10 (F) 122.71 138.63 125.21 99.77 104.71 100.57 122.52 138.57 125.18 101.33 102.02 101.44 128.27 138.10 129.81 103.86 104.79

T50 (F) 177.38 190.84 179.49 201.32 156.74 194.08 178.48 190.82 180.52 183.88 178.63 183.03 170.00 170.00 170.00 172.52 158.84

T90 (F) 301.79 317.48 304.25 330.22 279.39 321.97 304.39 317.12 306.50 317.64 310.25 316.44 307.11 301.30 306.20 321.48 299.07

Driveability 1012.88 1091.45 1025.20 1073.68 902.57 1045.90 1018.23 1091.08 1030.28 1014.05 992.49 1010.55 1003.99 1014.21 1005.59 987.23 927.90

Vapor Lock 128.45 143.42 130.80 110.29 110.29 110.29 128.34 143.45 130.84 110.29 110.29 110.29 131.67 140.71 133.09 110.29 110.29

Aromatics (vol%) 17.74 20.00 18.09 27.75 14.77 25.65 18.28 20.00 18.56 21.33 19.82 21.08 18.08 15.28 17.64 22.09 16.01

Benzene (vol%) 0.54 0.58 0.55 0.51 0.58 0.52 0.52 0.58 0.53 0.51 0.55 0.51 0.55 0.75 0.58 0.64 0.77

Olefins (vol%) 8.92 7.09 8.63 11.80 9.37 11.40 8.89 7.39 8.64 11.07 10.30 10.94 8.37 7.31 8.20 11.03 11.17

Alcohol (vol%) 9.59 10.00 9.65 0.00 10.00 1.62 10.00 10.00 10.00 10.00 10.00 10.00 15.00 15.00 15.00 15.00 15.00

Oxygen (wt%) 3.60 3.70 3.62 0.00 3.82 0.62 3.75 3.70 3.74 3.73 3.75 3.73 5.58 5.58 5.58 5.56 5.64

Volumes (kbbl/day) 1,396,446 259,727 1,656,173 1,327,820 257,387 1,585,207 1,357,780 269,081 1,626,861 1,375,643 266,657 1,642,300 1,509,824 280,814 1,790,638 1,435,628 278,286

Gasoline Qualities and 

Volume for PADD 2

2005 in 2030 E10 E15

Summer Winter Summer Winter Summer Winter
5-107

Table 5-56 - PADD 3 Gasoline Qualities Estimated by LP Refinery Modeling for Reference, 

E10 and E15 Cases 

CG RFG Pool CG RFG Pool CG RFG Pool CG RFG Pool CG RFG Pool CG RFG

Energy (MMBTU/bbl) 5.11 5.11 5.09 5.09 5.14 5.10 5.08 5.08 5.08 5.07 5.03 5.06 5.00 5.06 5.02 4.98 4.96

Density (lb/bbl) 258.93 259.59 258.38 255.87 256.01 255.89 258.77 260.62 259.30 257.06 256.33 256.88 261.39 260.17 261.06 258.99 257.57

Sulfur (ppm) 16.95 15.87 9.56 10.97 3.52 9.93 10.43 22.45 13.92 2.76 3.63 2.98 19.78 2.97 15.21 26.77 23.50

% at 200 49.43 50.15 54.62 49.84 54.67 50.51 55.79 51.98 54.68 53.98 57.96 54.99 61.63 58.43 60.76 61.19 58.11

% at 300 83.78 82.02 84.24 83.31 83.96 83.40 85.08 83.50 84.62 83.18 86.25 83.96 85.50 84.06 85.11 84.40 82.11

RVP (psi) 8.69 7.00 8.66 11.56 11.26 11.52 9.30 7.00 8.63 11.32 11.20 11.29 8.30 7.00 7.95 10.93 11.02

T10 (F) 128.38 139.25 128.72 110.21 112.14 110.48 124.17 138.64 128.37 111.20 111.55 111.29 130.62 139.16 132.94 113.41 113.18

T50 (F) 200.97 199.51 190.37 200.14 190.27 198.76 188.00 195.78 190.25 191.68 183.56 189.61 176.08 182.61 177.85 176.97 183.26

T90 (F) 325.92 333.93 323.80 328.03 325.07 327.61 320.01 327.19 322.09 328.64 314.67 325.08 318.09 324.65 319.87 323.09 333.51

Driveability 1113.37 1132.80 1079.32 1085.66 1056.08 1081.53 1063.17 1115.94 1078.47 1063.44 1027.57 1054.32 1035.20 1073.07 1045.49 1018.21 1045.60

Vapor Lock 135.62 144.29 133.75 120.07 120.07 120.07 130.38 144.24 134.40 120.07 120.07 120.07 133.83 141.55 135.93 120.07 120.07

Aromatics (vol%) 25.49 20.00 21.81 24.00 18.98 23.30 21.19 19.79 20.78 19.75 18.28 19.38 21.42 18.70 20.68 19.00 17.29

Benzene (vol%) 0.65 0.47 0.51 0.61 0.44 0.58 0.53 0.58 0.54 0.48 0.58 0.50 0.77 0.56 0.71 0.53 0.52

Olefins (vol%) 13.68 1.02 4.34 12.32 2.95 11.01 9.94 8.68 9.58 7.88 11.95 8.91 10.15 1.52 7.81 10.03 1.29

Alcohol (vol%) 3.92 10.00 10.00 3.18 10.00 4.13 10.00 10.00 10.00 10.00 10.00 10.00 15.00 15.00 15.00 15.00 15.00

Oxygen (wt%) 1.46 3.71 3.72 1.20 3.77 1.56 3.73 3.70 3.72 3.75 3.76 3.75 5.53 5.56 5.54 5.58 5.61

Volumes (kbbl/day) 2,528,524 378,805 1,369,806 2,378,941 385,854 1,472,992 960,985 392,446 1,353,431 1,126,292 384,074 1,510,366 1,097,387 409,559 1,506,946 1,175,404 400,822

Gasoline Qualities and 

Volume for PADD 3

2005 in 2030 E10 E15

Summer Winter Summer Winter Summer Winter
5-108

Table 5-57 - PADD 4 and 5 non-California - Gasoline Qualities Estimated by LP Refinery 

Modeling for Reference, E10 and E15 Cases 

CG RFG Pool CG RFG Pool CG RFG Pool CG RFG Pool CG RFG Pool CG RFG

Energy (MMBTU/bbl) 5.14 0.00 5.14 5.01 0.00 5.01 5.03 0.00 5.03 4.92 0.00 4.92 4.95 0.00 4.95 4.85 0.00

Density (lb/bbl) 256.88 0.00 256.88 253.37 0.00 253.37 258.60 0.00 258.60 255.69 0.00 255.69 260.83 0.00 260.83 256.55 0.00

Sulfur (ppm) 9.72 0.00 9.72 10.69 0.00 10.69 9.89 0.00 9.89 7.91 0.00 7.91 22.12 0.00 22.12 24.71 0.00

% at 200 57.05 0.00 57.05 59.49 0.00 59.49 62.45 0.00 62.45 66.88 0.00 66.88 64.60 0.00 64.60 72.87 0.00

% at 300 95.31 0.00 95.31 95.16 0.00 95.16 93.21 0.00 93.21 95.94 0.00 95.94 90.13 0.00 90.13 96.24 0.00

RVP (psi) 8.60 0.00 8.60 12.79 0.00 12.79 9.49 0.00 9.49 12.49 0.00 12.49 8.60 0.00 8.60 12.22 0.00

T10 (F) 130.48 0.00 130.48 102.91 0.00 102.91 122.47 0.00 122.47 103.82 0.00 103.82 127.64 0.00 127.64 104.41 0.00

T50 (F) 185.42 0.00 185.42 180.44 0.00 180.44 174.40 0.00 174.40 165.36 0.00 165.36 170.00 0.00 170.00 153.13 0.00

T90 (F) 273.51 0.00 273.51 274.16 0.00 274.16 283.04 0.00 283.04 270.62 0.00 270.62 297.06 0.00 297.06 269.29 0.00

Driveability 1015.94 0.00 1015.94 961.79 0.00 961.79 985.09 0.00 985.09 917.05 0.00 917.05 994.89 0.00 994.89 882.72 0.00

Vapor Lock 133.90 0.00 133.90 110.58 0.00 110.58 127.89 0.00 127.89 110.29 0.00 110.29 132.21 0.00 132.21 110.29 0.00

Aromatics (vol%) 22.25 0.00 22.25 20.98 0.00 20.98 18.78 0.00 18.78 16.27 0.00 16.27 17.63 0.00 17.63 13.40 0.00

Benzene (vol%) 1.30 0.00 1.30 0.94 0.00 0.94 0.34 0.00 0.34 0.65 0.00 0.65 0.42 0.00 0.42 0.27 0.00

Olefins (vol%) 7.90 0.00 7.90 7.88 0.00 7.88 6.36 0.00 6.36 6.72 0.00 6.72 6.41 0.00 6.41 6.26 0.00

Alcohol (vol%) 0.00 0.00 0.00 0.00 0.00 0.00 10.00 0.00 10.00 10.00 0.00 10.00 15.00 0.00 15.00 15.00 0.00

Oxygen (wt%) 0.00 0.00 0.00 0.00 0.00 0.00 3.73 0.00 3.73 3.77 0.00 3.77 5.54 0.00 5.54 5.64 0.00

Volumes (kbbl/day) 544,754 0 544,754 578,168 0 578,168 529,671 0 529,671 598,991 0 598,991 552,767 0 552,767 625,110 0

Gasoline Qualities and 

Volume for PADDs 4 & 

5 nonCA

2005 in 2030 E10 E15

Summer Winter Summer Winter Summer Winter
5-109

References 

1

 Ahrens, James, Stancil and Company, Peer Review of Refining Industry Cost Model, September 27, 2013. 

2

 Lappinen, Mauri and Higgins, Terry, Hart Energy, Review of EPA Proposed Tier 3 Motor Gasoline Refinery Cost 

Model, September 2013. 

3

 Freyman, David, Peer Review of EPA Refinery Tier 3 Cost Model, September 2013. 

4

 Memorandum from Lester Wyborny to Docket EPA-HQ-OAR-2011-0135, Refinery-by-Refinery Gasoline Sulfur 

Cost Model – Response to Peer Review comments for the Final Tier 3 Rulemaking. 

5

 Conversations with representatives of Foster Wheeler and Bechtel at the American Fuel and Petrochemical 

Manufacturers Annual Meeting; March 2012 and March 2013. 

6

 Annual Energy Outlook 2006, Energy Information Administration, Department of Energy. 

7

 Lesemann, M, et al, Grace Davison, Increasing FCC Propylene, PTQ Q1 2006. 

8

 Wagner, Kristen, Grace Davison, Applying ZSM-5 Additives to Meet FCC Propylene and Octane Objectives, 

Refinery Operations Vol 3 ISS 02, January 18, 2012. 

9

 Amalraj, Stephen, Albermarle, Albemarle’s AFX Lifts Propylene to new Levels, MEDW 2011. 

10 Miller, Rik, KBR and Bhore, Nazeer, Mobil Technology Company, et at, Maxofin: A Novel FCC Process for 

Maximizing Light Olefins using a New Generation ZSM-5 Additive, technical paper AM-98-18 presented at the 

1998 National Petrochemical and Refiners Association Annual Meeting, March 1998. 

11

 Peer Review of Refining Industry Cost Model, Stancil and Co., September 27, 2013. 

12 Stratiev, D, Lukoil Neftochim, Investigate processing near-zero-sulfur gasoline, Hydrocarbon Processing, 

September 2011. 

13 Rock, Kerry, CDTech, Long Term Reliability, Hydrocarbon Engineering, September 2004. 

14 The Challenges & Opportunities of 10 ppm Sulfur Gasoline. Jay Ross, Delphine Largeteau, Marc Laborde, Larry 

Wisdom. NPRA Annual Meeting, AM-11-57, March, 2011, page 6. 

15 The Benefits of Cat Feed Hydrotreating and the Impact of Feed Nitrogen on Catalyst Stability. Brian Moyse at 

Haldor Topso. NPRA Annual Meeting, AM-10-167, March 2010, Page 2. 

16

 Shorey, Scott et al, UOP; Exploiting Synergy between FCC and Feed Pretreating Units to Improve Refinery 

Margins and Produce Low-Sulfur Fuels; National Petrochemical and Refiners Association Annual Meeting technical 

paper AM-99-55, March 1999. 

17 Refining Economics of a National Low Sulfur, Low RVP Gasoline Standard, Performed for The International 

Council for Clean Transportation by Mathpro, October 25, 2011. 

18 Refining Economics of a National Clean Gasoline Standard for PADDs 1-3; for The Alliance of Automobile 

Manufacturers by Mathpro, June 27, 2008. 

19 Potential Supply and Cost Impacts of Lower Sulfur, Lower RVP Gasoline; prepared for The American Petroleum 

Institute by Baker and O’Brien; July 2011. 
5-110

20 Schink, George R., Singer, Hal J., Economic Analysis of the Implications of Implementing EPA’s Tier 3 Rules, 

prepared for the Emissions Control Technology Association, June 14, 2012. 

21 Gary, J., & Handewerk, G. (2001). Petroleum Refining: Technology and Economics. (4th ed.). CRC Press. p 256. 

22 Gary, J., & Handewerk, G. (2001). Petroleum Refining: Technology and Economics. (4th ed.). CRC Press. p 337. 

23 Keller, P. (2013, February). New Source Review Permitting Impact Analysis for Proposed Tier 3 Gasoline 

Program. Memorandum to the docket. 
6-1

Chapter 6 Health and Environmental Effects Associated with 

Exposure to Criteria and Toxic Pollutants 

6.1 Health Effects of Criteria and Toxic Pollutants 

Motor vehicles emit pollutants that contribute to ambient concentrations of ozone, PM, 

NO2, SO2, CO, and air toxics. A discussion of the health effects of these pollutants is included in 

this section of the RIA. Children may be more vulnerable to air pollution and other 

environmental exposures than adults because their bodily systems are still developing, they 

breathe more in proportion to their body size than adults and their behavior can expose them 

more to chemicals than adults. Early lifestages (e.g., children) are thought to be more 

susceptible to tumor development than adults when exposed to carcinogenic chemicals that act 

through a mutagenic mode of action.1

6.1.1 Particulate Matter 

6.1.1.1 Background 

Particulate matter (PM) is a highly complex mixture of solid particles and liquid droplets 

distributed among numerous atmospheric gases which interact with solid and liquid phases. 

Particles range in size from those smaller than 1 nanometer (10-9 meter) to over 100 micrometer 

(μm, or 10-6 meter) in diameter (for reference, a typical strand of human hair is 70 μm in 

diameter and a grain of salt is about 100 μm). Atmospheric particles can be grouped into several 

classes according to their aerodynamic and physical sizes, including ultrafine particles (<0.1 

μm), accumulation mode or ‘fine’ particles (< 1 to 3 μm), and coarse particles (>1 to 3 μm). For 

regulatory purposes, fine particles are measured as PM2.5 and inhalable or thoracic coarse 

particles are measured as PM10-2.5, corresponding to their size (diameter) range in micrometers. 

The EPA currently has standards that measure PM2.5 and PM10.

2

Particles span many sizes and shapes and may consist of hundreds of different chemicals. 

Particles are emitted directly from sources and are also formed through atmospheric chemical 

reactions; the former are often referred to as “primary” particles, and the latter as “secondary” 

particles. Particle concentration and composition varies by time of year and location, and in 

addition to differences in source emissions, is affected by several weather-related factors, such as 

temperature, clouds, humidity, and wind. A further layer of complexity comes from particles’ 

ability to shift between solid/liquid and gaseous phases, which is influenced by concentration and 

meteorology, especially temperature. 

Fine particles are produced primarily by combustion processes and by transformations of 

gaseous emissions (e.g., sulfur oxides (SOX), nitrogen oxides (NOX) and volatile organic 

compounds (VOCs)) in the atmosphere. The chemical and physical properties of PM2.5 may vary 

greatly with time, region, meteorology and source category. Thus, PM2.5 may include a complex 

mixture of different components including sulfates, nitrates, organic compounds, elemental 

carbon and metal compounds. These particles can remain in the atmosphere for days to weeks 

and travel through the atmosphere hundreds to thousands of kilometers.3 
6-2

6.1.1.2 Health Effects of PM 

Scientific studies show ambient PM is associated with a broad range of health effects. 

These health effects are discussed in detail in the December 2009 Integrated Science Assessment 

for Particulate Matter (PM ISA).4 The PM ISA summarizes health effects evidence associated 

with both short- and long-term exposures to PM2.5, PM10-2.5, and ultrafine particles. The PM ISA 

concludes that human exposures to ambient PM2.5 concentrations are associated with a number 

of adverse health effects and characterizes the weight of evidence for these health outcomes.5 

The discussion below highlights the PM ISA’s conclusions pertaining to health effects associated 

with both short- and long-term PM exposures. Further discussion of health effects associated 

with PM2.5 can also be found in the rulemaking documents for the most recent review of the PM 

NAAQS completed in 2012.6,7

The EPA concludes that a causal relationship exists between both long- and short-term 

exposures to PM2.5 and premature mortality and cardiovascular effects and a likely causal 

relationship exists between long- and short-term PM2.5 exposures and respiratory effects. 

Further, there is evidence suggestive of a causal relationship between long-term PM2.5 exposures 

and other health effects, including developmental and reproductive effects (e.g., low birth 

weight, infant mortality) and carcinogenic, mutagenic, and genotoxic effects (e.g., lung cancer 

mortality).8

As summarized in the Final PM NAAQS rule, and discussed extensively in the 2009 PM 

ISA, the scientific evidence available since the completion of the 2006 PM NAAQS review 

significantly strengthens the link between long- and short-term exposure to PM2.5 and premature 

mortality, while providing indications that the magnitude of the PM2.5- mortality association with 

long-term exposures may be larger than previously estimated.9,10

 The strongest evidence comes 

from recent studies investigating long-term exposure to PM2.5 and cardiovascular-related 

mortality. The evidence supporting a causal relationship between long-term PM2.5 exposure and 

mortality also includes consideration of new studies that demonstrated an improvement in 

community health following reductions in ambient fine particles.11

Several studies evaluated in the 2009 PM ISA have examined the association between 

cardiovascular effects and long-term PM2.5 exposures in multi-city studies conducted in the U.S. 

and Europe. While studies were not available in the 2006 PM NAAQS review with regard to 

long-term exposure and cardiovascular-related morbidity, studies published since then have 

provided new evidence linking long-term exposure to PM2.5 with an array of cardiovascular 

effects such as heart attacks, congestive heart failure, stroke, and mortality. This evidence is 

coherent with studies of short-term exposure to PM2.5 that have observed associations with a 

continuum of effects ranging from subtle changes in indicators of cardiovascular health to 

serious clinical events, such as increased hospitalizations and emergency department visits due to 

cardiovascular disease and cardiovascular mortality.12

As detailed in the 2009 PM ISA, extended analyses of studies available in the 2006 PM 

NAAQS review as well as epidemiological studies conducted in the U.S. and abroad published 

since then provide stronger evidence of respiratory-related morbidity effects associated with 

long-term PM2.5 exposure. The strongest evidence for respiratory-related effects is from studies 

that evaluated decrements in lung function growth (in children), increased respiratory symptoms, 
6-3

and asthma development. The strongest evidence from short-term PM2.5 exposure studies has 

been observed for increased respiratory-related emergency department visits and hospital 

admissions for chronic obstructive pulmonary disease (COPD) and respiratory infections.13

The body of scientific evidence detailed in the 2009 PM ISA is still limited with respect 

to associations between long-term PM2.5 exposures and developmental and reproductive effects 

as well as cancer, mutagenic, and genotoxic effects, but is somewhat expanded from the 2006 

review The strongest evidence for an association between PM2.5 and developmental and 

reproductive effects comes from epidemiological studies of low birth weight and infant 

mortality, especially due to respiratory causes during the post-neonatal period (i.e., 1 month to 12 

months of age). With regard to cancer effects, ‘‘[m]ultiple epidemiologic studies have shown a 

consistent positive association between PM2.5 and lung cancer mortality, but studies have 

generally not reported associations between PM2.5 and lung cancer incidence.’’14,15

Specific groups within the general population are at increased risk for experiencing 

adverse health effects related to PM exposures.16,17,18,19 The evidence detailed in the 2009 PM 

ISA expands our understanding of previously identified at-risk populations and lifestages (i.e., 

children, older adults, and individuals with pre-existing heart and lung disease) and supports the 

identification of additional at-risk populations (e.g., persons with lower socioeconomic status, 

genetic differences). Additionally, there is emerging, though still limited, evidence for additional 

potentially at-risk populations and lifestages, such as those with diabetes, people who are obese, 

pregnant women, and the developing fetus.20

For PM10-2.5, the 2009 PM ISA concluded that available evidence was suggestive of a 

causal relationship between short-term exposures to PM10-2.5 and cardiovascular effects (e.g., 

hospital admissions and ED visits, changes in cardiovascular function), respiratory effects (e.g, 

ED visits and hospital admissions, increase in markers of pulmonary inflammation), and 

premature mortality. Data were inadequate to draw conclusions regarding the relationships 

between long-term exposure to PM10-2.5 and various health effects. 21,22,23

For ultrafine particles, the 2009 PM ISA concluded that the evidence was suggestive of a 

causal relationship between short-term exposures and cardiovascular effects, including changes 

in heart rhythm and vasomotor function (the ability of blood vessels to expand and contract). It 

also concluded that there was evidence suggestive of a causal relationship between short-term 

exposure to ultrafine particles and respiratory effects, including lung function and pulmonary 

inflammation, with limited and inconsistent evidence for increases in ED visits and hospital 

admissions. Data were inadequate to draw conclusions regarding the relationship between shortterm exposure to ultrafine particle and additional health effects including premature mortality as 

well as long-term exposure to ultrafine particles and all health outcomes evaluated.24,25

6.1.2 Ozone 

6.1.2.1 Background 

Ground-level ozone pollution is typically formed through reactions involving VOCs and 

NOX in the lower atmosphere in the presence of sunlight. These pollutants, often referred to as 

ozone precursors, are emitted by many types of pollution sources such as highway and nonroad 
6-4

motor vehicles and engines, power plants, chemical plants, refineries, makers of consumer and 

commercial products, industrial facilities, and smaller area sources. 

The science of ozone formation, transport, and accumulation is complex. Ground-level 

ozone is produced and destroyed in a cyclical set of chemical reactions, many of which are 

sensitive to temperature and sunlight. When ambient temperatures and sunlight levels remain 

high for several days and the air is relatively stagnant, ozone and its precursors can build up and 

result in more ozone than typically occurs on a single high-temperature day. Ozone and its 

precursors can be transported hundreds of miles downwind of precursor emissions, resulting in 

elevated ozone levels even in areas with low VOC or NOX emissions. 

The highest levels of ozone are produced when both VOC and NOX emissions are present 

in significant quantities on clear summer days. Relatively small amounts of NOX enable ozone 

to form rapidly when VOC levels are relatively high, but ozone production is quickly limited by 

removal of the NOX. Under these conditions NOX reductions are highly effective in reducing 

ozone while VOC reductions have little effect. Such conditions are called “NOX-limited.” 

Because the contribution of VOC emissions from biogenic (natural) sources to local ambient 

ozone concentrations can be significant, even some areas where man-made VOC emissions are 

relatively low can be NOX-limited.

Ozone concentrations in an area also can be lowered by the reaction of nitric oxide (NO) 

with ozone, forming nitrogen dioxide (NO2). As the air moves downwind and the cycle 

continues, the NO2 forms additional ozone. The importance of this reaction depends, in part, on 

the relative concentrations of NOX, VOC, and ozone, all of which change with time and location. 

When NOX levels are relatively high and VOC levels relatively low, NOX forms inorganic 

nitrates (i.e., particles) but relatively little ozone. Such conditions are called “VOC-limited.” 

Under these conditions, VOC reductions are effective in reducing ozone, but NOX reductions can 

actually increase local ozone under certain circumstances. Even in VOC-limited urban areas, 

NOX reductions are not expected to increase ozone levels if the NOX reductions are sufficiently 

large. Rural areas are usually NOX-limited, due to the relatively large amounts of biogenic VOC 

emissions in such areas. Urban areas can be either VOC- or NOX-limited, or a mixture of both, 

in which ozone levels exhibit moderate sensitivity to changes in either pollutant. 

6.1.2.2 Health Effects of Ozone 

This section provides a summary of the health effects associated with exposure to 

ambient concentrations of ozone.26 The information in this section is based on the information 

and conclusions in the February 2013 Integrated Science Assessment for Ozone (Ozone ISA) 

prepared by EPA’s Office of Research and Development (ORD).27 The Ozone ISA concludes 

that human exposures to ambient concentrations of ozone are associated with a number of 

adverse health effects and characterizes the weight of evidence for these health effects. 28

 The 

discussion below highlights the Ozone ISA’s conclusions pertaining to health effects associated 

with both short-term and long-term periods of exposure to ozone. 

For short-term exposure to ozone, the Ozone ISA concludes that respiratory effects, 

including lung function decrements, pulmonary inflammation, exacerbation of asthma, 

respiratory-related hospital admissions, and mortality, are causally associated with ozone 
6-5

exposure. It also concludes that cardiovascular effects, including decreased cardiac function and 

increased vascular disease, and total mortality are likely to be causally associated with short-term 

exposure to ozone and that evidence is suggestive of a causal relationship between central 

nervous system effects and short-term exposure to ozone. 

For long-term exposure to ozone, the Ozone ISA concludes that respiratory effects, 

including new onset asthma, pulmonary inflammation and injury, are likely to be a causally 

related with ozone exposure. The Ozone ISA characterizes the evidence as suggestive of a 

causal relationship for associations between long-term ozone exposure and cardiovascular 

effects, reproductive and developmental effects, central nervous system effects and total 

mortality. The evidence is inadequate to infer a causal relationship between chronic ozone 

exposure and increased risk of lung cancer. 

Finally, interindividual variation in human responses to ozone exposure can result in 

some groups being at increased risk for detrimental effects in response to exposure. The Ozone 

ISA identified several groups that are at increased risk for ozone-related health effects. These 

groups are people with asthma, children and older adults, individuals with reduced intake of 

certain nutrients (i.e., Vitamins C and E), outdoor workers, and individuals having certain 

genetic variants related to oxidative metabolism or inflammation. Ozone exposure during 

childhood can have lasting effects through adulthood. Such effects include altered function of 

the respiratory and immune systems. Children absorb higher doses (normalized to lung surface 

area) of ambient ozone, compared to adults, due to their increased time spent outdoors, higher 

ventilation rates relative to body size, and a tendency to breathe a greater fraction of air through 

the mouth. Children also have a higher asthma prevalence compared to adults. Additional 

children’s vulnerability and susceptibility factors are listed in Section XII.G of the preamble. 

6.1.3 Nitrogen Oxides and Sulfur Oxides 

6.1.3.1 Background 

Sulfur dioxide (SO2), a member of the sulfur oxide (SOX) family of gases, is formed from 

burning fuels containing sulfur (e.g., coal or oil), extracting gasoline from oil, or extracting 

metals from ore. Nitrogen dioxide (NO2) is a member of the nitrogen oxide (NOX) family of 

gases. Most NO2 is formed in the air through the oxidation of nitric oxide (NO) emitted when 

fuel is burned at a high temperature. SO2 andNO2 and their gas phase oxidation products can 

dissolve in water droplets and further oxidize to form sulfuric and nitric acid which react with 

ammonia to form sulfates and nitrates, both of which are important components of ambient PM. 

The health effects of ambient PM are discussed in Section 6.1.1.2. NOX along with VOCs are 

the two major precursors of ozone. The health effects of ozone are covered in Section 6.1.2.2.

6.1.3.2 Health Effects of Sulfur Oxides 

This section provides an overview of the health effects associated with SO2. Additional 

information on the health effects of SO2 can be found in the 2008 Integrated Science Assessment 

for Sulfur Oxides (SO2 ISA).29 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. The immediate 
6-6

effect of SO2 on the respiratory system in humans is bronchoconstriction. Asthmatics are more 

sensitive to the effects of SO2 likely resulting from preexisting inflammation associated with this 

disease. In addition to those with asthma (both children and adults), potentially sensitive groups 

include all children and the elderly. In laboratory studies involving controlled human exposures 

to SO2, respiratory effects have consistently been observed following 5-10 min exposures at SO2

concentrations ≥ 0.4 ppm in asthmatics engaged in moderate to heavy levels of exercise, with 

more limited evidence of respiratory effects among exercising asthmatics exposed to 

concentrations as low as 0.2-0.3 ppm. A clear concentration-response relationship has been 

demonstrated in these studies following exposures to SO2 at concentrations between 0.2 and 1.0 

ppm, both in terms of increasing severity of respiratory symptoms and decrements in lung 

function, as well as the percentage of asthmatics adversely affected. 

In epidemiologic studies, respiratory effects have been observed in areas where the mean 

24-hour SO2 levels range from 1 to 30 ppb, with maximum 1 to 24-hour average SO2 values 

ranging from 12 to 75 ppb. Important new multicity studies and several other studies have found 

an association between 24-hour average ambient SO2 concentrations and respiratory symptoms 

in children, particularly those with asthma. Generally consistent associations also have been 

observed between ambient SO2 concentrations and emergency department visits and 

hospitalizations for all respiratory causes, particularly among children and older adults (≥ 65 

years), and for asthma. A limited subset of epidemiologic studies has examined potential 

confounding by copollutants using multipollutant regression models. These analyses indicate 

that although copollutant adjustment has varying degrees of influence on the SO2 effect 

estimates, the effect of SO2 on respiratory health outcomes appears to be generally robust and 

independent of the effects of gaseous and particulate copollutants, suggesting that the observed 

effects of SO2 on respiratory endpoints occur independent of the effects of other ambient air 

pollutants. 

Consistent associations between short-term exposure to SO2 and mortality have been 

observed in epidemiologic studies, with larger effect estimates reported for respiratory mortality 

than for cardiovascular mortality. While this finding is consistent with the demonstrated effects 

of SO2 on respiratory morbidity, uncertainty remains with respect to the interpretation of these 

associations due to potential confounding by various copollutants. The U.S. EPA has therefore 

concluded that the overall evidence is suggestive of a causal relationship between short-term 

exposure to SO2 and mortality. Significant associations between short-term exposure to SO2 and 

emergency department visits and hospital admissions for cardiovascular diseases have also been 

reported. However, these findings have been inconsistent across studies and do not provide 

adequate evidence to infer a causal relationship between SO2 exposure and cardiovascular 

morbidity. 

6.1.3.3 Health Effects of Nitrogen Oxides 

The most recent review of the health effects of oxides of nitrogen completed by the EPA 

can be found in the 2008 Integrated Science Assessment for Nitrogen Oxides (NOX ISA).30 The 

EPA concluded that the findings of epidemiologic, controlled human exposure, and animal 

toxicological studies provide evidence that is sufficient to infer a likely causal relationship 

between respiratory effects and short-term NO2 exposure. The 2008 NOX ISA concluded that the 

strongest evidence for such a relationship comes from epidemiologic studies of respiratory 
6-7

effects including increased respiratory symptoms, emergency department visits, and hospital 

admissions. Based on both short- and long-term exposure studies, the 2008 NOX ISA concluded 

that individuals with preexisting pulmonary conditions (e.g., asthma or COPD), children, and 

older adults are potentially at greater risk of NO2-related respiratory effects. Based on findings 

from controlled human exposure studies, the 2008 NOX ISA also drew two broad conclusions 

regarding airway responsiveness following NO2 exposure. First, the NOX ISA concluded that 

NO2 exposure may enhance the sensitivity to allergen-induced decrements in lung function and 

increase the allergen-induced airway inflammatory response following 30-minute exposures of 

asthmatic adults to NO2 concentrations as low as 260 ppb. Second, exposure to NO2 has been 

found to enhance the inherent responsiveness of the airway to subsequent nonspecific challenges 

in controlled human exposure studies of healthy and asthmatic adults. Small but statistically 

significant increases in nonspecific airway hyperresponsiveness were reported for asthmatic 

adults following 30-minute exposures to 200-300 ppb NO2 and following 1-hour exposures of 

asthmatics to 100 ppb NO2. Enhanced airway responsiveness could have important clinical 

implications for asthmatics since transient increases in airway responsiveness following NO2

exposure have the potential to increase symptoms and worsen asthma control. Together, the 

epidemiologic and experimental data sets form a plausible, consistent, and coherent description 

of a relationship between NO2 exposures and an array of adverse health effects that range from 

the onset of respiratory symptoms to hospital admission. 

In evaluating a broader range of health effects, the 2008 NOX ISA concluded evidence 

was “suggestive but not sufficient to infer a causal relationship” between short-term NO2

exposure and premature mortality and between long-term NO2 exposure and respiratory effects. 

The latter was based largely on associations observed between long-term NO2 exposure and 

decreases in lung function growth in children. Furthermore, the 2008 NOX ISA concluded that 

evidence was “inadequate to infer the presence or absence of a causal relationship” between 

short-term NO2 exposure and cardiovascular effects as well as between long-term NO2 exposure 

and cardiovascular effects, reproductive and developmental effects, premature mortality, and 

cancer.31 The conclusions for these health effect categories were informed by uncertainties in the 

evidence base such as the independent effects of NO2 exposure within the broader mixture of 

traffic-related pollutants, limited evidence from experimental studies, and/or an overall limited 

literature base. 

6.1.4 Health Effects of Carbon Monoxide 

Information on the health effects of carbon monoxide (CO) can be found in the January 

2010 Integrated Science Assessment for Carbon Monoxide (CO ISA).32 The CO ISA concludes 

that ambient concentrations of CO are associated with a number of adverse health effects.33 This 

section provides a summary of the health effects associated with exposure to ambient 

concentrations of CO.

34

 

Controlled human exposure studies of subjects with coronary artery disease show a 

decrease in the time to onset of exercise-induced angina (chest pain) and electrocardiogram 

changes following CO exposure. In addition, epidemiologic studies show associations between 

short-term CO exposure and cardiovascular morbidity, particularly increased emergency room 

visits and hospital admissions for coronary heart disease (including ischemic heart disease, 

myocardial infarction, and angina). Some epidemiologic evidence is also available for increased 
6-8

hospital admissions and emergency room visits for congestive heart failure and cardiovascular 

disease as a whole. The CO ISA concludes that a causal relationship is likely to exist between 

short-term exposures to CO and cardiovascular morbidity. It also concludes that available data 

are inadequate to conclude that a causal relationship exists between long-term exposures to CO 

and cardiovascular morbidity. 

Animal studies show various neurological effects with in-utero CO exposure. Controlled 

human exposure studies report central nervous system and behavioral effects following low-level 

CO exposures, although the findings have not been consistent across all studies. The CO ISA 

concludes the evidence is suggestive of a causal relationship with both short- and long-term 

exposure to CO and central nervous system effects. 

A number of studies cited in the CO ISA have evaluated the role of CO exposure in birth 

outcomes such as preterm birth or cardiac birth defects. The epidemiologic studies provide 

limited evidence of a CO-induced effect on preterm births and birth defects, with weak evidence 

for a decrease in birth weight. Animal toxicological studies have found perinatal CO exposure to 

affect birth weight, as well as other developmental outcomes. The CO ISA concludes the 

evidence is suggestive of a causal relationship between long-term exposures to CO and 

developmental effects and birth outcomes. 

Epidemiologic studies provide evidence of associations between ambient CO 

concentrations and respiratory morbidity such as changes in pulmonary function, respiratory 

symptoms, and hospital admissions. A limited number of epidemiologic studies considered 

copollutants such as ozone, SO2, and PM in two-pollutant models and found that CO risk 

estimates were generally robust, although this limited evidence makes it difficult to disentangle 

effects attributed to CO itself from those of the larger complex air pollution mixture. Controlled 

human exposure studies have not extensively evaluated the effect of CO on respiratory 

morbidity. Animal studies at levels of 50-100 ppm CO show preliminary evidence of altered 

pulmonary vascular remodeling and oxidative injury. The CO ISA concludes that the evidence 

is suggestive of a causal relationship between short-term CO exposure and respiratory morbidity, 

and inadequate to conclude that a causal relationship exists between long-term exposure and 

respiratory morbidity. 

Finally, the CO ISA concludes that the epidemiologic evidence is suggestive of a causal 

relationship between short-term concentrations of CO and mortality. Epidemiologic studies 

provide evidence of an association between short-term exposure to CO and mortality, but limited 

evidence is available to evaluate cause-specific mortality outcomes associated with CO exposure. 

In addition, the attenuation of CO risk estimates which was often observed in copollutant models 

contributes to the uncertainty as to whether CO is acting alone or as an indicator for other 

combustion-related pollutants. The CO ISA also concludes that there is not likely to be a causal 

relationship between relevant long-term exposures to CO and mortality. 
6-9

6.1.5 Health Effects of Air Toxics 

6.1.5.1 Benzene 

The EPA’s IRIS database lists benzene as a known human carcinogen (causing leukemia) 

by all routes of exposure, and concludes that exposure is associated with additional health 

effects, including genetic changes in both humans and animals and increased proliferation of 

bone marrow cells in mice.35,36,37

 EPA states in its IRIS database that data indicate a causal 

relationship between benzene exposure and acute lymphocytic leukemia and suggest a 

relationship between benzene exposure and chronic non-lymphocytic leukemia and chronic 

lymphocytic leukemia. EPA’s IRIS documentation for benzene also lists a range of 2.2 x 10-6 to 

7.8 x 10-6 as the unit risk estimate (URE) for benzene.38,39 The International Agency for 

Research on Carcinogens (IARC) has determined that benzene is a human carcinogen and the 

U.S. Department of Health and Human Services (DHHS) has characterized benzene as a known 

human carcinogen.40,41

A number of adverse noncancer health effects including blood disorders, such as 

preleukemia and aplastic anemia, have also been associated with long-term exposure to 

benzene.42,43

 The most sensitive noncancer effect observed in humans, based on current data, is 

the depression of the absolute lymphocyte count in blood.44,45

 EPA’s inhalation reference 

concentration (RfC) for benzene is 30 μg/m3. The RfC is based on suppressed absolute 

lymphocyte counts seen in humans under occupational exposure conditions. In addition, recent 

work, including studies sponsored by the Health Effects Institute (HEI), provides evidence that 

biochemical responses are occurring at lower levels of benzene exposure than previously 

known.46,47,48,49 EPA’s IRIS program has not yet evaluated these new data. EPA does not 

currently have an acute reference concentration for benzene. The Agency for Toxic Substances 

and Disease Registry (ATSDR) Minimal Risk Level (MRL) for acute exposure to benzene is 29 

μg/m3

for 1-14 days exposure.50,51

6.1.5.2 1,3-Butadiene 

EPA has characterized 1,3-butadiene as carcinogenic to humans by inhalation.52,53 The 

IARC has determined that 1,3-butadiene is a human carcinogen and the U.S. DHHS has 

characterized 1,3-butadiene as a known human carcinogen.54,55,56

 There are numerous studies 

consistently demonstrating that 1,3-butadiene is metabolized into genotoxic metabolites by 

experimental animals and humans. The specific mechanisms of 1,3-butadiene-induced 

carcinogenesis are unknown; however, the scientific evidence strongly suggests that the 

carcinogenic effects are mediated by genotoxic metabolites. Animal data suggest that females 

may be more sensitive than males for cancer effects associated with 1,3-butadiene exposure; 

there are insufficient data in humans from which to draw conclusions about sensitive 

subpopulations. The URE for 1,3-butadiene is 3 × 10-5 per μg/m3.

57 1,3-butadiene also causes a 

variety of reproductive and developmental effects in mice; no human data on these effects are 

available. The most sensitive effect was ovarian atrophy observed in a lifetime bioassay of 

female mice.58

 Based on this critical effect and the benchmark concentration methodology, an 

RfC for chronic health effects was calculated at 0.9 ppb (approximately 2 μg/m3).
6-10

6.1.5.3 Ethanol 

EPA is planning to develop an assessment of the health effects of exposure to ethanol, a 

compound which is not currently listed on EPA’s IRIS database. Extensive health effects data 

are available for ingestion of ethanol, while data on inhalation exposure effects are sparse. In 

developing the assessment, EPA is evaluating pharmacokinetic models as a means of 

extrapolating across species (animal to human) and across exposure routes (oral to inhalation) to 

better characterize the health hazards and dose-response relationships for low levels of ethanol 

exposure in the environment. 

6.1.5.4 Formaldehyde 

In 1991, EPA concluded that formaldehyde is a carcinogen based on nasal tumors in 

animal bioassays.59 An Inhalation Unit Risk for cancer and a Reference Dose for oral noncancer 

effects were developed by the Agency and posted on the Integrated Risk Information System 

(IRIS) database. Since that time, the National Toxicology Program (NTP) and International 

Agency for Research on Cancer (IARC) have concluded that formaldehyde is a known human 

carcinogen.60,61,62

The conclusions by IARC and NTP reflect the results of epidemiologic research 

published since 1991 in combination with previous animal, human and mechanistic evidence. 

Research conducted by the National Cancer Institute reported an increased risk of 

nasopharyngeal cancer and specific lymphohematopoietic malignancies among workers exposed 

to formaldehyde.63,64,65 A National Institute of Occupational Safety and Health study of garment 

workers also reported increased risk of death due to leukemia among workers exposed to 

formaldehyde.66 Extended follow-up of a cohort of British chemical workers did not report 

evidence of an increase in nasopharyngeal or lymphohematopoietic cancers, but a continuing 

statistically significant excess in lung cancers was reported.67

 Finally, a study of embalmers 

reported formaldehyde exposures to be associated with an increased risk of myeloid leukemia 

but not brain cancer.68

 Health effects of formaldehyde in addition to cancer were reviewed by the Agency for 

Toxics Substances and Disease Registry in 199969 and supplemented in 2010,70 and by the World 

Health Organization.71 These organizations reviewed the literature concerning effects on the 

eyes and respiratory system, the primary point of contact for inhaled formaldehyde, including 

sensory irritation of eyes and respiratory tract, pulmonary function, nasal histopathology, and 

immune system effects. In addition, research on reproductive and developmental effects and 

neurological effects were discussed. 

 EPA released a draft Toxicological Review of Formaldehyde – Inhalation Assessment 

through the IRIS program for peer review by the National Research Council (NRC) and public 

comment in June 2010.72 The draft assessment reviewed more recent research from animal and 

human studies on cancer and other health effects. The NRC released their review report in April 

201173 (http://www.nap.edu/catalog.php?record_id=13142). The EPA is currently revising the 

draft assessment in response to this review. 
6-11

6.1.5.5 Acetaldehyde 

Acetaldehyde is classified in EPA’s IRIS database as a probable human carcinogen, 

based on nasal tumors in rats, and is considered toxic by the inhalation, oral, and intravenous 

routes.74 The URE in IRIS for acetaldehyde is 2.2 × 10-6 per μg/m3.

75

 Acetaldehyde is 

reasonably anticipated to be a human carcinogen by the U.S. DHHS in the 12th Report on 

Carcinogens and is classified as possibly carcinogenic to humans (Group 2B) by the IARC.76,77

 

EPA is currently conducting a reassessment of cancer risk from inhalation exposure to 

acetaldehyde. 

The primary noncancer effects of exposure to acetaldehyde vapors include irritation of 

the eyes, skin, and respiratory tract.78 In short-term (4 week) rat studies, degeneration of 

olfactory epithelium was observed at various concentration levels of acetaldehyde exposure.79,80

 

Data from these studies were used by EPA to develop an inhalation reference concentration of 9 

μg/m3. Some asthmatics have been shown to be a sensitive subpopulation to decrements in 

functional expiratory volume (FEV1 test) and bronchoconstriction upon acetaldehyde 

inhalation.81

 The agency is currently conducting a reassessment of the health hazards from 

inhalation exposure to acetaldehyde. 

6.1.5.6 Acrolein 

EPA most recently evaluated the toxicological and health effects literature related to 

acrolein in 2003 and concluded that the human carcinogenic potential of acrolein could not be 

determined because the available data were inadequate. No information was available on the 

carcinogenic effects of acrolein in humans and the animal data provided inadequate evidence of 

carcinogenicity.82 The IARC determined in 1995 that acrolein was not classifiable as to its 

carcinogenicity in humans.83 

Lesions to the lungs and upper respiratory tract of rats, rabbits, and hamsters have been 

observed after subchronic exposure to acrolein.84

 The Agency has developed an RfC for acrolein 

of 0.02 μg/m3 and an RfD of 0.5 μg/kg-day.85 EPA is considering updating the acrolein 

assessment with data that have become available since the 2003 assessment was completed. 

Acrolein is extremely acrid and irritating to humans when inhaled, with acute exposure 

resulting in upper respiratory tract irritation, mucus hypersecretion and congestion. The intense 

irritancy of this carbonyl has been demonstrated during controlled tests in human subjects, who 

suffer intolerable eye and nasal mucosal sensory reactions within minutes of exposure.86

 These 

data and additional studies regarding acute effects of human exposure to acrolein are 

summarized in EPA’s 2003 IRIS Human Health Assessment for acrolein.87 Studies in humans 

indicate that levels as low as 0.09 ppm (0.21 mg/m3) for five minutes may elicit subjective 

complaints of eye irritation with increasing concentrations leading to more extensive eye, nose 

and respiratory symptoms. Acute exposures in animal studies report bronchial hyperresponsiveness. Based on animal data (more pronounced respiratory irritancy in mice with 

allergic airway disease in comparison to non-diseased mice88) and demonstration of similar 

effects in humans (e.g., reduction in respiratory rate), individuals with compromised respiratory 

function (e.g., emphysema, asthma) are expected to be at increased risk of developing adverse 

responses to strong respiratory irritants such as acrolein. EPA does not currently have an acute 
6-12

reference concentration for acrolein. The available health effect reference values for acrolein 

have been summarized by EPA and include an ATSDR MRL for acute exposure to acrolein of 

7 μg/m3for 1-14 days exposure; and Reference Exposure Level (REL) values from the 

California Office of Environmental Health Hazard Assessment (OEHHA) for one-hour and 8-

hour exposures of 2.5 μg/m3and 0.7 μg/m3, respectively.89 

6.1.5.7 PAN 

PAN (peroxy acetyl nitrate) has not been evaluated by EPA’s IRIS program. Information 

regarding the potential carcinogenicity of PAN is limited. As noted in the EPA air quality 

criteria document for ozone and related photochemical oxidants, cytogenetic studies indicate that 

PAN is not a potent mutagen, clastogen (a compound that can cause breaks in chromosomes), or 

DNA-damaging agent in mammalian cells either in vivo or in vitro. Some studies suggest that 

PAN may be a weak bacterial mutagen at concentrations much higher than exist in present urban 

atmospheres.90

Effects of ground-level smog causing intense eye irritation have been attributed to 

photochemical oxidants, including PAN.91

 Animal toxicological information on the inhalation 

effects of the non-ozone oxidants has been limited to a few studies on PAN. Acute exposure to 

levels of PAN can cause changes in lung morphology, behavioral modifications, weight loss, and 

susceptibility to pulmonary infections. Human exposure studies indicate minor pulmonary 

function effects at high PAN concentrations, but large inter-individual variability precludes 

definitive conclusions.92

6.1.5.8 Polycyclic Organic Matter 

The term polycyclic organic matter (POM) defines a broad class of compounds that 

includes the polycyclic aromatic hydrocarbon compounds (PAHs). One of these compounds, 

naphthalene, is discussed separately below. POM compounds are formed primarily from 

combustion and are present in the atmosphere in gas and particulate form. Cancer is the major 

concern from exposure to POM. Epidemiologic studies have reported an increase in lung cancer 

in humans exposed to diesel exhaust, coke oven emissions, roofing tar emissions, and cigarette 

smoke; all of these mixtures contain POM compounds.9394

 Animal studies have reported 

respiratory tract tumors from inhalation exposure to benzo[a]pyrene and alimentary tract and 

liver tumors from oral exposure to benzo[a]pyrene.95 In 1997 EPA classified seven PAHs 

(benzo[a]pyrene, benz[a]anthracene, chrysene, benzo[b]fluoranthene, benzo[k]fluoranthene, 

dibenz[a,h]anthracene, and indeno[1,2,3-cd]pyrene) as Group B2, probable human carcinogens.96

 

Since that time, studies have found that maternal exposures to PAHs in a population of pregnant 

women were associated with several adverse birth outcomes, including low birth weight and 

reduced length at birth, as well as impaired cognitive development in preschool children (3 years 

of age).97,98 These and similar studies are being evaluated as a part of the ongoing IRIS 

assessment of health effects associated with exposure to benzo[a]pyrene. 

6.1.5.9 Naphthalene 

Naphthalene is found in small quantities in gasoline and diesel fuels. Naphthalene 

emissions have been measured in larger quantities in both gasoline and diesel exhaust compared 
6-13

with evaporative emissions from mobile sources, indicating it is primarily a product of 

combustion. Acute (short-term) exposure of humans to naphthalene by inhalation, ingestion, or 

dermal contact is associated with hemolytic anemia and damage to the liver and the nervous 

system.99 Chronic (long term) exposure of workers and rodents to naphthalene has been reported 

to cause cataracts and retinal damage.100 EPA released an external review draft of a 

reassessment of the inhalation carcinogenicity of naphthalene based on a number of recent 

animal carcinogenicity studies.101

 The draft reassessment completed external peer review.102 

Based on external peer review comments received, a revised draft assessment that considers all 

routes of exposure, as well as cancer and noncancer effects, is under development. The external 

review draft does not represent official agency opinion and was released solely for the purposes 

of external peer review and public comment. The National Toxicology Program listed 

naphthalene as "reasonably anticipated to be a human carcinogen" in 2004 on the basis of 

bioassays reporting clear evidence of carcinogenicity in rats and some evidence of 

carcinogenicity in mice.103 California EPA has released a new risk assessment for naphthalene, 

and the IARC has reevaluated naphthalene and re-classified it as Group 2B: possibly 

carcinogenic to humans.104 

Naphthalene also causes a number of chronic non-cancer effects in animals, including 

abnormal cell changes and growth in respiratory and nasal tissues.105 The current EPA IRIS 

assessment includes noncancer data on hyperplasia and metaplasia in nasal tissue that form the 

basis of the inhalation RfC of 3 μg/m3

.

106

 The ATSDR MRL for acute exposure to naphthalene 

is 0.6 mg/kg/day. 

6.1.5.10 Other Air Toxics 

In addition to the compounds described above, other compounds in gaseous hydrocarbon 

and PM emissions from vehicles will be affected by this proposal. Mobile source air toxic 

compounds that would potentially be impacted include ethylbenzene, propionaldehyde, toluene, 

and xylene. Information regarding the health effects of these compounds can be found in EPA’s 

IRIS database.107

6.1.6 Traffic-associated health effects 

In addition to health concerns resulting from specific air pollutants, a large number of 

studies have examined the health status of populations near major roadways. These studies 

frequently have employed exposure metrics that are not specific to individual pollutants, but 

rather reflect the large number of different pollutants found in elevation near major roads. 

In this section of the RIA, information on health effects associated with air quality near 

major roads or traffic in general is summarized. Generally, the section makes use of publications 

that systematically review literature on a given health topic. In particular, this section makes 

frequent reference of a report of by the Health Effects Institute (HEI) Panel on the Health Effects 

of Traffic-Related Air Pollution, published in 2010 as a review of relevant studies.108,109

 Other 

systematic reviews of relevant literature are cited were appropriate. 
6-14

6.1.6.1 Populations near major roads 

Numerous studies have estimated the size and demographics of populations that live near 

major roads. Other studies have estimated the number of schools near major roads, and the 

populations of students in such schools. 

Every two years, the U.S. Census Bureau’s American Housing Survey (AHS) has 

reported whether housing units are within 300 feet of an “airport, railroad, or highway with four 

or more lanes.” The 2009 survey reports that over 22 million homes, or 17 percent of all housing 

units in the U.S., were located in such areas. Assuming that populations and housing units are in 

the same locations, this corresponds to a population of more than 50 million U.S. residents in 

close proximity to high-traffic roadways or other transportation sources. According to the 

Central Intelligence Agency’s World Factbook, in 2010, the United States had 6,506,204 km or 

roadways, 224,792 km of railways, and 15,079 airports. As such, highways represent the 

overwhelming majority of transportation facilities described by this factor in the AHS. 

The AHS reports are published every two years, and until 2011 recorded whether homes 

were located near highways with four or more lanes, railroads, or airports. As such, trends in the 

AHS can be reported to describe whether a greater or lesser proportion of homes are located near 

major roads over time. Figure 6-1 depicts trends in the number and proportion of homes located 

near major transportation sources, which generally indicate large roadways. As the figure 

indicates, since 2005, there has been a substantial increase in the number and percentage of 

homes located near major transportation sources. As such, the population in close proximity to 

these sources, which may be affected by near-road air quality and health concerns, appears to 

have increased over time. 
6-15

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

14.0%

16.0%

18.0%

1 0

1 2

1 4

1 6

1 8

2 0

2 2

2 4

1997 1999 2001 2003 2005 2007 2009 Percent Near Infrastructure Million Homes

Year of American Housing Survey

Million Housing Units

Near 4+ Lane Highway, 

Railroad, or Airport

Figure 6-1 Trends in Populations Near Large Highways, Railroads, and Airports 

Furthermore, according to data from the 2008 American Time Use Survey (ATUS), 

conducted by the Bureau of Labor Statistics (BTS), Americans spend more than an hour 

traveling each day, on average.110

 Although the ATUS does not indicate their mode of travel, the 

majority of trips undertaken nationally is by motor vehicle.111 As such, daily travel activity 

brings nearly all residents into a high-exposure microenvironment for part of the day. 

6.1.6.2 Premature mortality 

The HEI panel report concluded that evidence linking traffic-associated air pollution with 

premature mortality from all causes was “suggestive but not sufficient” to infer a causal 

relationship. This conclusion was based largely on several long-term studies that “qualitatively” 

examined whether or not someone was exposed to traffic-associated air pollution. In addition, 

based on several short-term studies of exposure, the panel concluded that there was evidence that 

there was “suggestive but not sufficient” evidence to infer a causal relation between trafficrelated exposure and cardiovascular mortality. 

6.1.6.3 Cardiovascular effects 

6.1.6.3.1 Cardiac physiology 

Exposure to traffic-associated pollutants has been associated with changes in cardiac 

physiology, including cardiac function. One common measure of cardiac function is heart rate 
6-16

variability (HRV), an indicator of the heart’s ability to respond to variations in stress, reflecting 

the nervous system’s ability to regulate the heart.112 Reduced HRV is associated with adverse 

cardiovascular events, such as myocardial infarction, in heart disease patients. The HEI panel 

concluded that available evidence provides evidence for a causal association between exposure 

to traffic-related pollutants and reduced control of HRV by the nervous system. Overall, the 

panel concluded that the evidence was “suggestive but not sufficient” to infer a causal relation 

between traffic-related pollutants and cardiac function. Studies suggest that the HRV changes 

from traffic-related air pollution result in changes to heart rhythms, which can lead to 

arrhythmia.113,114

6.1.6.3.2 Heart attack and atherosclerosis 

The HEI panel concluded that epidemiologic evidence of the association between trafficrelated pollutants and heart attacks and atherosclerosis was “suggestive but not sufficient” to 

infer a causal association. In addition, the panel concluded that the toxicology studies they 

reviewed provided “suggestive evidence that exposure to traffic emissions, including ambient 

and laboratory-generated [PM] and diesel- and gasoline-engine exhaust, alters cardiovascular 

function.” The panel noted there are few studies of human volunteers exposed to real-world 

traffic mixture, which were not entirely consistent. The panel notes that the studies provide 

consistent evidence for exposure to PM and impaired cardiovascular responses. In addition to 

the HEI study, several other reviews of available evidence conclude that there is evidence 

supporting a causal association between traffic-related air pollution and cardiovascular 

disease.115

A number of mechanisms for cardiovascular disease are highlighted in the HEI and AHA 

report, including modified blood vessel endothelial function (e.g., the ability to dilate), 

atherosclerosis, and oxidative stress. The HEI review cites “two well executed studies” in which 

hospitalization for acute myocardial infarction (i.e., heart attack) were associated with traffic 

exposures and a prospective study finding higher rates of arterial hardening and coronary heart 

disease near traffic. 

6.1.6.4 Respiratory effects 

6.1.6.4.1 Asthma 

Pediatric asthma and asthma symptoms are the effects that have been evaluated by the 

largest number of studies in the epidemiologic literature on the topic. In general, studies 

consistently show effects of residential or school exposure to traffic and asthma symptoms, and 

the effects are frequently statistically significant. Studies have employed both short-term and 

long-term exposure metrics, and a range of different respiratory measures. HEI Special Report 

17 (HEI Panel on the Health Effects of Traffic-Related Air Pollution, 2010) concluded that there 

is sufficient evidence for a causal association between exposure to traffic-related air pollution 

and exacerbation of asthma symptoms in children. 

While there is general consistency in studies examining asthma incidence in children, the 

available studies employ different definitions of asthma (e.g., self-reported vs. hospital records), 

methods of exposure assessment, and population age ranges. As such, the overall evidence, 
6-17

while supportive of an association between traffic exposure and new onset asthma, are less 

consistent than for asthma symptoms. The HEI report determined that there is “sufficient” or 

“suggestive” evidence of a causal relationship between exposure to traffic-related air pollution 

and incident (new onset) asthma in children (HEI Panel on the Health Effects of Traffic-Related 

Air Pollution, 2010). A recent meta-analysis of studies on incident asthma and air pollution in 

general, based on studies dominated by traffic-linked exposure metrics, also concluded that 

available evidence that exposures is consistent with a effect of exposure on asthma incidence 

(Anderson et al., 2011). The study reported excess main risk estimates for different pollutants 

ranging from 7-16 percent per 10 g/m3

of long-term exposure (random effects models). Other 

qualitative reviews (Salam et al., 2008; Braback and Forsberg, 2009) conclude that available 

evidence is consistent with the hypothesis that traffic-associated air pollutants are associated with 

incident asthma. 

6.1.6.4.2 Chronic obstructive pulmonary disease (COPD) 

The HEI panel reviewed available studies examining COPD in the context of trafficassociated air pollution. Because of how the panel selected studies for inclusion in review, there 

were only two studies that they used to review the available evidence. Both studies reported 

some positive associations, but not for all traffic metrics. The small number of studies and lack 

of consistency across traffic metrics led the panel to conclude that there is insufficient evidence 

for traffic-associated air pollution causing COPD.

6.1.6.4.3 Allergy 

There are numerous human and animal experimental studies that provides strongly 

suggestive evidence that traffic-related air pollutants can enhance allergic responses to common 

allergens.116,117,118 However, in its review of 16 epidemiologic studies that address traffic-related 

air pollution’s effect on allergies, the HEI expert panel (HEI, 2010) reported that only two such 

studies showed consistently positive associations. As a result, despite the strong experimental 

evidence, the panel concluded that there is “inadequate/insufficient” evidence of an association 

between allergy and traffic-associated air pollution. As noted above, the HEI panel considered 

toxicological evidence only based on whether or not they provide mechanistic support for 

observations and inferences derived from epidemiology. 

6.1.6.4.4 Lung function 

There are numerous measurements of breathing (spirometry) that indicate the presence or 

degree of airway disease, such as asthma and chronic obstructive pulmonary disease (COPD). 

Forced vital capacity (FVC) is measured when a patient maximally fills their lungs and then 

blows their hardest in completely exhaling. The peak expiratory flow (PEF) is the maximum air 

flow achievable during exhalation. The forced expiratory volume in the first second of 

exhalation is referred to as FEV1. FEV1 and PEF reflect the function of the large airways. FVC 

and FEV1, along with their ratio (FVC/FEV1) are used to classify airway obstruction in asthma 

and COPD. Measurements of air flow at various times during forced exhalation, such as 25 

percent, 50 percent, and 75 percent, are also used. The flow at 75 percent of forced exhalation 

(FEF75) reflects the status of small airways, which asthma and COPD affect. 
6-18

The HEI panel concluded that the available literature suggests that long-term exposure to 

traffic-related air pollution is associated with reduced lung function in adolescents and young 

adults and that lung function is lower in populations in areas with high traffic-related air 

pollutant levels. However, the panel noted the difficulty of disentangling traffic-specific 

exposures from urban air pollution in general. The studies reviewed that were more specifically 

oriented toward traffic were not consistent in their findings. As a result, the panel found that the 

evidence linking lung function and traffic exposure is “inadequate and insufficient” to infer a 

causal relationship. 

6.1.6.5 Reproductive and developmental effects 

Several studies have reported associations between traffic-related air pollution and 

adverse birth outcomes, such as preterm birth and low birth weight. At the time of the HEI 

review, the panel concluded that evidence for adverse birth outcomes being causally associated 

with traffic-related exposures was “inadequate and insufficient.” Only four studies met the 

panel’s inclusion criteria, and had limited geographic coverage. One study provided evidence of 

small but consistently increased risks using multiple exposure metrics. No studies were at the 

time available that examined traffic-specific exposures and congenital abnormalities. Since then, 

several studies investigating birth outcomes have been published, but no new systematic reviews. 

One new meta-analysis of air pollution and congenital abnormalities has been published, though 

none of the reviewed studies includes traffic-specific exposure information. 

The HEI panel also reviewed toxicological studies of traffic-related air pollutants and 

fertility. While numerous studies examining animal or human exposure and sperm count have 

been published, the panel concluded that the generally high exposure concentrations employed in 

the studies limited the applicability to typical ambient concentrations. Because there was no 

overlap in the effects studied by epidemiology and toxicology studies, no synthesis review of the 

combined literature was undertaken. 

Since the HEI panel’s publication, a systematic review and meta-analysis of air pollution 

and congenital abnormalities was published.119 In that review, only one study directly included 

nearby traffic in its exposure analysis. As such, there are so systematic reviews that specifically 

address traffic’s impact on congenital abnormalities. 

6.1.6.6 Cancer 

6.1.6.6.1 Childhood cancer 

A number of studies examining various types of childhood cancer have been published 

with mixed results. The HEI panel concluded that the available epidemiologic evidence was 

“inadequate and insufficient” to infer a causal relationship between traffic-related air pollution 

and childhood cancer. An earlier review article on the topic noted that studies reporting positive 

effects tended to be small, while those with null effects tended to be larger, suggesting the 

potential for publication bias in the available literature.120
6-19

6.1.6.6.2 Adult cancer 

Several studies have examined the risk of adult lung cancers in relation to exposure to 

traffic-related air pollutants. The HEI panel evaluated four such studies, and rated the available 

evidence as “inadequate and insufficient” to infer a causal relation for non-occupational lung 

cancer. 

6.1.6.7 Neurological effects 

The HEI panel found that current toxicologic and epidemiologic literature on the 

neurotoxicity of traffic-related air pollution was inadequate for their evaluation. The panel noted 

that there were a number of toxicologic studies of traffic-associated pollutants, but found them to 

have diverse exposure protocols, animal models, and endpoints, making them unsuitable for 

systematic evaluation. 

6.2 Environmental Effects of Criteria and Toxic Pollutants 

6.2.1 Visibility Degradation 

Visibility can be defined as the degree to which the atmosphere is transparent to visible 

light.121

 Visibility impairment is caused by light scattering and absorption by suspended 

particles and gases. Visibility is important because it has direct significance to people’s 

enjoyment of daily activities in all parts of the country. Individuals value good visibility for the 

well-being it provides them directly, where they live and work, and in places where they enjoy 

recreational opportunities. Visibility is also highly valued in significant natural areas, such as 

national parks and wilderness areas, and special emphasis is given to protecting visibility in these 

areas. For more information on visibility see the final 2009 PM ISA.122

EPA is working to address visibility impairment. In 1999, EPA finalized the regional 

haze program (64 FR 35714) to protect the visibility in Mandatory Class I Federal areas. There 

are 156 national parks, forests and wilderness areas categorized as Mandatory Class I Federal 

areas (62 FR 38680-38681, July 18, 1997). These areas are defined in CAA section 162 as those 

national parks exceeding 6,000 acres, wilderness areas and memorial parks exceeding 5,000 

acres, and all international parks which were in existence on August 7, 1977. Figure 6-2 shows 

the location of the 156 Mandatory Class I Federal areas. 
6-20

Figure 6-2 Mandatory Class I Federal Areas in the U.S. 

EPA has also concluded that PM2.5 causes adverse effects on visibility in other areas that 

are not protected by the Regional Haze Rule, depending on PM2.5 concentrations and other 

factors that control their visibility impact effectiveness such as dry chemical composition and 

relative humidity (i.e., an indicator of the water composition of the particles). EPA revised the 

PM2.5 standards in December 2012 and established a target level of protection that is expected to 

be met through attainment of the existing secondary standards for PM2.5. 

6.2.1.1 Visibility Monitoring 

In conjunction with the U.S. National Park Service, the U.S. Forest Service, other Federal 

land managers, and State organizations in the U.S., the U.S. EPA has supported visibility 

monitoring in national parks and wilderness areas since 1988. The monitoring network was 

originally established at 20 sites, but it has now been expanded to 110 sites that represent all but 

one of the 156 Mandatory Federal Class I areas across the country (see Figure 6-2). This longterm visibility monitoring network is known as IMPROVE (Interagency Monitoring of Protected 

Visual Environments).

IMPROVE provides direct measurement of fine particles that contribute to visibility 

impairment. The IMPROVE network employs aerosol measurements at all sites, and optical and 

scene measurements at some of the sites. Aerosol measurements are taken for PM10 and PM2.5

mass, and for key constituents of PM2.5, such as sulfate, nitrate, organic and elemental carbon 

OC and EC), soil dust, and several other elements. Measurements for specific aerosol 

constituents are used to calculate "reconstructed" aerosol light extinction by multiplying the mass 

for each constituent by its empirically-derived scattering and/or absorption efficiency, with 

adjustment for the relative humidity. Knowledge of the main constituents of a site's light 

extinction "budget" is critical for source apportionment and control strategy development. In 
6-21

addition to this indirect method of assessing light extinction, there are optical measurements 

which directly measure light extinction or its components. Such measurements are made 

principally with either a nephelometer to measure light scattering, some sites also include an 

aethalometer for light absorption, or at a few sites using a transmissometer, which measures total 

light extinction. Scene characteristics are typically recorded using digital or video photography 

and are used to determine the quality of visibility conditions (such as effects on color and 

contrast) associated with specific levels of light extinction as measured under both direct and 

aerosol-related methods. Directly measured light extinction is used under the IMPROVE 

protocol to cross check that the aerosol-derived light extinction levels are reasonable in 

establishing current visibility conditions. Aerosol-derived light extinction is used to document 

spatial and temporal trends and to determine how changes in atmospheric constituents would 

affect future visibility conditions.

Annual average visibility conditions (reflecting light extinction due to both anthropogenic 

and non-anthropogenic sources) vary regionally across the U.S. Visibility is typically worse in 

the summer months and the rural East generally has higher levels of impairment than remote 

sites in the West. Figures 9-9 through 9-11 in the PM ISA detail the percent contributions to 

particulate light extinction for ammonium nitrate and sulfate, EC and OC, and coarse mass and 

fine soil, by season.123

6.2.2 Particulate Matter Deposition 

Particulate matter contributes to adverse effects on vegetation and ecosystems, and to 

soiling and materials damage. These welfare effects result predominately from exposure to 

excess amounts of specific chemical species, regardless of their source or predominant form 

(particle, gas or liquid). The following characterizations of the nature of these environmental 

effects are based on information contained in the 2009 PM ISA and the 2005 PM Staff Paper as 

well as the 2008 Integrated Science Assessment for Oxides of Nitrogen and Sulfur- Ecological 

Criteria (secondary NOX/SOX ISA).124,125,126

6.2.2.1 Deposition of Nitrogen and Sulfur 

Nitrogen and sulfur interactions in the environment are highly complex. Both nitrogen 

and sulfur are essential, and sometimes limiting, nutrients needed for growth and productivity of 

ecosystem components (e.g. algae, plants). In terrestrial and aquatic ecosystems excesses of 

nitrogen or sulfur can lead to acidification and nutrient enrichment.127 

The process of acidification affects both freshwater aquatic and terrestrial ecosystems. 

Acid deposition causes acidification of sensitive surface waters. The effects of acid deposition 

on aquatic systems depend largely upon the ability of the ecosystem to neutralize the additional 

acid. As acidity increases, aluminum leached from soils, flows into lakes and streams and can be 

toxic to both terrestrial and aquatic biota. The lower pH concentrations and higher aluminum 

levels resulting from acidification make it difficult for some fish and other aquatic organisms to 

survive, grow, and reproduce. Research on effects of acid deposition on forest ecosystems has 

come to focus increasingly on the biogeochemical processes that affect uptake, retention, and 

cycling of nutrients within these ecosystems. Decreases in available base cations from soils are 

at least partly attributable to acid deposition. Base cation depletion is a cause for concern 
6-22

because of the role these ions play in acid neutralization, and because calcium, magnesium and 

potassium are essential nutrients for plant growth and physiology. Changes in the relative 

proportions of these nutrients, especially in comparison with aluminum concentrations, have 

been associated with declining forest health. 

At current ambient levels, risks to vegetation from short-term exposures to dry deposited 

particulate nitrate or sulfate are low. However, when found in acid or acidifying deposition, such 

particles do have the potential to cause direct leaf injury. Specifically, the responses of forest 

trees to acid precipitation (rain, snow) include accelerated weathering of leaf cuticular surfaces, 

increased permeability of leaf surfaces to toxic materials, water, and disease agents; increased 

leaching of nutrients from foliage; and altered reproductive processes—all which serve to 

weaken trees so that they are more susceptible to other stresses (e.g., extreme weather, pests, 

pathogens). Acid deposition with levels of acidity associated with the leaf effects described 

above are currently found in some locations in the eastern U.S.128

 Even higher concentrations of 

acidity can be present in occult depositions (e.g., fog, mist or clouds) which more frequently 

impacts higher elevations. Thus, the risk of leaf injury occurring from acid deposition in some 

areas of the eastern U.S. is high. Nitrogen deposition has also been shown to impact ecosystems 

in the western U.S. For example, a study conducted in the Columbia River Gorge National 

Scenic Area (CRGNSA), located along a portion of the Oregon/Washington border, indicates 

that lichen communities in the CRGNSA have shifted to a higher proportion of nitrophilous 

species and the nitrogen content of lichen tissue is elevated.129 Lichens are sensitive indicators 

of nitrogen deposition effects to terrestrial ecosystems and the lichen studies in the Columbia 

River Gorge clearly show that ecological effects from air pollution are occurring. 

Some of the most significant detrimental effects associated with excess nitrogen 

deposition are those associated with a condition known as nitrogen saturation. Nitrogen 

saturation is the condition in which nitrogen inputs from atmospheric deposition and other 

sources exceed the biological requirements of the ecosystem. The effects associated with 

nitrogen saturation include: (1) decreased productivity, increased mortality, and/or shifts in plant 

community composition, often leading to decreased biodiversity in many natural habitats 

wherever atmospheric reactive nitrogen deposition increases significantly above background and 

critical thresholds are exceeded; (2) leaching of excess nitrate and associated base cations from 

soils into streams, lakes, and rivers, and mobilization of soil aluminum; and (3) fluctuation of 

ecosystem processes such as nutrient and energy cycles through changes in the functioning and 

species composition of beneficial soil organisms.130

In the U.S. numerous forests now show severe symptoms of nitrogen saturation. These 

forests include: the northern hardwoods and mixed conifer forests in the Adirondack and 

Catskill Mountains of New York; the red spruce forests at Whitetop Mountain, Virginia, and 

Great Smoky Mountains National Park, North Carolina; mixed hardwood watersheds at Fernow 

Experimental Forest in West Virginia; American beech forests in Great Smoky Mountains 

National Park, Tennessee; mixed conifer forests and chaparral watersheds in southern California 

and the southwestern Sierra Nevada in Central California; the alpine tundra/subalpine conifer 

forests of the Colorado Front Range; and red alder forests in the Cascade Mountains in 

Washington. 
6-23

Excess nutrient inputs into aquatic ecosystems (i.e. streams, rivers, lakes, estuaries or 

oceans) either from direct atmospheric deposition, surface runoff, or leaching from nitrogen 

saturated soils into ground or surface waters can contribute to conditions of severe water oxygen 

depletion; eutrophication and algae blooms; altered fish distributions, catches, and physiological 

states; loss of biodiversity; habitat degradation; and increases in the incidence of disease. 

Atmospheric deposition of nitrogen is a significant source of total nitrogen to many 

estuaries in the United States. The amount of nitrogen entering estuaries that is ultimately 

attributable to atmospheric deposition is not well-defined. On an annual basis, atmospheric 

nitrogen deposition may contribute significantly to the total nitrogen load, depending on the size 

and location of the watershed. In addition, episodic nitrogen inputs, which may be ecologically 

important, may play a more important role than indicated by the annual average concentrations. 

Estuaries in the U.S. that suffer from nitrogen enrichment often experience a condition known as 

eutrophication. Symptoms of eutrophication include changes in the dominant species of 

phytoplankton, low levels of oxygen in the water column, fish and shellfish kills, outbreaks of 

toxic alga, and other population changes which can cascade throughout the food web. In 

addition, increased phytoplankton growth in the water column and on surfaces can attenuate light 

causing declines in submerged aquatic vegetation, which serves as an important habitat for many 

estuarine fish and shellfish species.

Severe and persistent eutrophication often directly impacts human activities. For 

example, losses in the nation’s fishery resources may be directly caused by fish kills associated 

with low dissolved oxygen and toxic blooms. Declines in tourism occur when low dissolved 

oxygen causes noxious smells and floating mats of algal blooms create unfavorable aesthetic 

conditions. Risks to human health increase when the toxins from algal blooms accumulate in 

edible fish and shellfish, and when toxins become airborne, causing respiratory problems due to 

inhalation. According to a National Oceanic and Atmospheric Administration report, more than 

half of the nation’s estuaries have moderate to high expressions of at least one of these symptoms 

– an indication that eutrophication is well developed in more than half of U.S. estuaries.131

6.2.2.2 Deposition of Heavy Metals 

Heavy metals, including cadmium, copper, lead, chromium, mercury, nickel and zinc, 

have the greatest potential for impacting forest growth.132 Investigation of trace metals near 

roadways and industrial facilities indicate that a substantial load of heavy metals can accumulate 

on vegetative surfaces. Copper, zinc, and nickel have been documented to cause direct toxicity 

to vegetation under field conditions. Trace metals are associated with ambient PM, however 

little research has been conducted on the effects associated with mixtures of contaminants. 

While metals typically exhibit low solubility, limiting their bioavailability and direct toxicity, 

chemical transformations of metal compounds occur in the environment, particularly in the 

presence of acidic or other oxidizing species. These chemical changes influence the mobility 

and toxicity of metals in the environment. Once taken up into plant tissue, a metal compound 

can undergo chemical changes, exert toxic effects on the plant itself, accumulate and be passed 

along to herbivores or can re-enter the soil and further cycle in the environment. Although there 

has been no direct evidence of a physiological association between tree injury and heavy metal 

exposures, heavy metals have been implicated because of similarities between metal deposition 

patterns and forest decline. This hypothesized relationship/correlation was further explored in 
6-24

high elevation forests in the northeastern U.S. These studies measured levels of a group of 

intracellular compounds found in plants that bind with metals and are produced by plants as a 

response to sublethal concentrations of heavy metals. These studies indicated a systematic and 

significant increase in concentrations of these compounds associated with the extent of tree 

injury. These data strongly imply that metal stress causes tree injury and contributes to forest 

decline in the northeastern United States.133 Contamination of plant leaves by heavy metals can 

lead to elevated soil levels. Trace metals absorbed into the plant frequently bind to the leaf 

tissue, and then are lost when the leaf drops. As the fallen leaves decompose, the heavy metals 

are transferred into the soil.134,135 Upon entering the soil environment, PM pollutants can alter 

ecological processes of energy flow and nutrient cycling, inhibit nutrient uptake, change 

ecosystem structure, and affect ecosystem biodiversity. Many of the most important effects 

occur in the soil. The soil environment is one of the most dynamic sites of biological interaction 

in nature. It is inhabited by microbial communities of bacteria, fungi, and actinomycetes. These 

organisms are essential participants in the nutrient cycles that make elements available for plant 

uptake. Changes in the soil environment that influence the role of the bacteria and fungi in 

nutrient cycling determine plant and ultimately ecosystem response.136

The environmental sources and cycling of mercury are currently of particular concern due 

to the bioaccumulation and biomagnification of this metal in aquatic ecosystems and the potent 

toxic nature of mercury in the forms in which is it ingested by people and other animals. 

Mercury is unusual compared with other metals in that it largely partitions into the gas phase (in 

elemental form), and therefore has a longer residence time in the atmosphere than a metal found 

predominantly in the particle phase. This property enables mercury to travel far from the 

primary source before being deposited and accumulating in the aquatic ecosystem. The major 

source of mercury in the Great Lakes is from atmospheric deposition, accounting for 

approximately eighty percent of the mercury in Lake Michigan.137,138 Over fifty percent of the 

mercury in the Chesapeake Bay has been attributed to atmospheric deposition.139 Overall, the 

National Science and Technology Council identifies atmospheric deposition as the primary 

source of mercury to aquatic systems.140 Forty-four states have issued health advisories for the 

consumption of fish contaminated by mercury; however, most of these advisories are issued in 

areas without a mercury point source. 

Elevated levels of zinc and lead have been identified in streambed sediments, and these 

elevated levels have been correlated with population density and motor vehicle use.141,142,143

 

Zinc and nickel have also been identified in urban water and soils. In addition, platinum, 

palladium, and rhodium, metals found in the catalysts of modern motor vehicles, have been 

measured at elevated levels along roadsides.144

 Plant uptake of platinum has been observed at 

these locations. 

6.2.2.3 Deposition of Polycyclic Organic Matter 

Polycyclic organic matter (POM) is a byproduct of incomplete combustion and consists 

of organic compounds with more than one benzene ring and a boiling point greater than or equal 

to 100 degrees centigrade.145

 Polycyclic aromatic hydrocarbons (PAHs) are a class of POM that 

contains compounds which are known or suspected carcinogens. 
6-25

Major sources of PAHs include mobile sources. PAHs in the environment may be 

present as a gas or adsorbed onto airborne particulate matter. Since the majority of PAHs are 

adsorbed onto particles less than 1.0 μm in diameter, long range transport is possible. However, 

studies have shown that PAH compounds adsorbed onto diesel exhaust particulate and exposed 

to ozone have half lives of 0.5 to 1.0 hours.146 

Since PAHs are insoluble, the compounds generally are particle reactive and accumulate 

in sediments. Atmospheric deposition of particles is believed to be the major source of PAHs to 

the sediments of Lake Michigan.147,148 Analyses of PAH deposition in Chesapeake and 

Galveston Bay indicate that dry deposition and gas exchange from the atmosphere to the surface 

water predominate.149,150 Sediment concentrations of PAHs are high enough in some segments 

of Tampa Bay to pose an environmental health threat. EPA funded a study to better characterize 

the sources and loading rates for PAHs into Tampa Bay.151

 PAHs that enter a water body 

through gas exchange likely partition into organic rich particles and can be biologically recycled, 

while dry deposition of aerosols containing PAHs tend to be more resistant to biological 

recycling.152

 Thus, dry deposition is likely the main pathway for PAH concentrations in 

sediments while gas/water exchange at the surface may lead to PAH distribution into the food 

web, leading to increased health risk concerns. 

Trends in PAH deposition levels are difficult to discern because of highly variable 

ambient air concentrations, lack of consistency in monitoring methods, and the significant 

influence of local sources on deposition levels.153

 Van Metre et al. noted PAH concentrations in 

urban reservoir sediments have increased by 200-300 percent over the last forty years and 

correlate with increases in automobile use.154

 

Cousins et al. estimate that more than ninety percent of semi-volatile organic compound 

(SVOC) emissions in the United Kingdom deposit on soil.155 An analysis of PAH concentrations 

near a Czechoslovakian roadway indicated that concentrations were thirty times greater than 

background.156

6.2.2.4 Materials Damage and Soiling 

The effects of the deposition of atmospheric pollution, including ambient PM, on 

materials are related to both physical damage and impaired aesthetic qualities. The deposition of 

PM (especially sulfates and nitrates) can physically affect materials, adding to the effects of 

natural weathering processes, by potentially promoting or accelerating the corrosion of metals, 

by degrading paints, and by deteriorating building materials such as concrete and limestone. 

Only chemically active fine particles or hygroscopic coarse particles contribute to these physical 

effects. In addition, the deposition of ambient PM can reduce the aesthetic appeal of buildings 

and culturally important articles through soiling. Particles consisting primarily of carbonaceous 

compounds cause soiling of commonly used building materials and culturally important items 

such as statues and works of art. 

6.2.3 Plant and Ecosystem Effects of Ozone 

The welfare effects of ozone can be observed across a variety of scales, i.e., subcellular, 

cellular, leaf, whole plant, population and ecosystem. Ozone effects that begin at small spatial 
6-26

scales, such as the leaf of an individual plant, when they occur at sufficient magnitudes (or to a 

sufficient degree) can result in effects being propagated along a continuum to larger and larger 

spatial scales. For example, effects at the individual plant level, such as altered rates of leaf gas 

exchange, growth and reproduction can, when widespread, result in broad changes in 

ecosystems, such as productivity, carbon storage, water cycling, nutrient cycling, and community 

composition. 

Ozone can produce both acute and chronic injury in sensitive species depending on the 

concentration level and the duration of the exposure.157 In those sensitive species158, effects from 

repeated exposure to ozone throughout the growing season of the plant tend to accumulate, so 

that even low concentrations experienced for a longer duration have the potential to create 

chronic stress on vegetation.159 Ozone damage to sensitive species includes impaired 

photosynthesis and visible injury to leaves. The impairment of photosynthesis, the process by 

which the plant makes carbohydrates (its source of energy and food), can lead to reduced crop 

yields, timber production, and plant productivity and growth. Impaired photosynthesis can also 

lead to a reduction in root growth and carbohydrate storage below ground, resulting in other, 

more subtle plant and ecosystems impacts.160 These latter impacts include increased 

susceptibility of plants to insect attack, disease, harsh weather, interspecies competition and 

overall decreased plant vigor. The adverse effects of ozone on areas with sensitive species could 

potentially lead to species shifts and loss from the affected ecosystems161, resulting in a loss or 

reduction in associated ecosystem goods and services. Additionally, visible ozone injury to 

leaves can result in a loss of aesthetic value in areas of special scenic significance like national 

parks and wilderness areas and reduced use of sensitive ornamentals in landscaping.162

 

The Integrated Science Assessment (ISA) for Ozone presents more detailed information 

on how ozone effects vegetation and ecosystems.163 The ISA concludes that ambient 

concentrations of ozone are associated with a number of adverse welfare effects and 

characterizes the weight of evidence for different effects associated with ozone.164 The ISA 

concludes that visible foliar injury effects on vegetation, reduced vegetation growth, reduced 

productivity in terrestrial ecosystems, reduced yield and quality of agricultural crops, and 

alteration of below-ground biogeochemical cycles are causally associated with exposure to 

ozone. It also concludes that reduced carbon sequestration in terrestrial ecosystems, alteration of 

terrestrial ecosystem water cycling, and alteration of terrestrial community composition are 

likely to be causally associated with exposure to ozone. 

6.2.4 Environmental Effects of Air Toxics 

Emissions from producing, transporting and combusting fuel contribute to ambient levels 

of pollutants that contribute to adverse effects on vegetation. Volatile organic compounds 

(VOCs), some of which are considered air toxics, have long been suspected to play a role in 

vegetation damage.165 In laboratory experiments, a wide range of tolerance to VOCs has been 

observed.166 Decreases in harvested seed pod weight have been reported for the more sensitive 

plants, and some studies have reported effects on seed germination, flowering and fruit ripening. 

Effects of individual VOCs or their role in conjunction with other stressors (e.g., acidification, 

drought, temperature extremes) have not been well studied. In a recent study of a mixture of 

VOCs including ethanol and toluene on herbaceous plants, significant effects on seed production, 

leaf water content and photosynthetic efficiency were reported for some plant species.167
6-27

Research suggests an adverse impact of vehicle exhaust on plants, which has in some 

cases been attributed to aromatic compounds and in other cases to nitrogen oxides.168,169,170 The 

impacts of VOCs on plant reproduction may have long-term implications for biodiversity and 

survival of native species near major roadways. Most of the studies of the impacts of VOCs on 

vegetation have focused on short-term exposure and few studies have focused on long-term 

effects of VOCs on vegetation and the potential for metabolites of these compounds to affect 

herbivores or insects. 
6-28

References 

1

 U.S. Environmental Protection Agency. (2005). Supplemental guidance for assessing susceptibility 

from early-life exposure to carcinogens. Washington, DC: Risk Assessment Forum. EPA/630/ 

R-03/003F. http://www.epa.gov/raf/publications/pdfs/childrens_supplement_final.pdf. 

2

 Regulatory definitions of PM size fractions, and information on reference and equivalent methods for measuring 

PM in ambient air, are provided in 40 CFR Parts 50, 53, and 58. With regard to national ambient air quality 

standards (NAAQS) which provide protection against health and welfare effects, the 24-hour PM10 standard 

provides protection against effects associated with short-term exposure to thoracic coarse particles (i.e., PM10-2.5).

3 U.S. EPA (2009). Integrated Science Assessment for Particulate Matter (Final Report). U.S. Environmental 

Protection Agency, Washington, DC, EPA/600/R-08/139F, 2009. 

4

 U.S. EPA. (2009). Integrated Science Assessment for Particulate Matter (Final Report). U.S. Environmental 

Protection Agency, Washington, DC, EPA/600/R-08/139F. 

5

 The causal framework draws upon the assessment and integration of evidence from across epidemiological, 

controlled human exposure, and toxicological studies, and the related uncertainties that ultimately influence our 

understanding of the evidence. This framework employs a five-level hierarchy that classifies the overall weight of 

evidence and causality using the following categorizations: causal relationship, likely to be causal relationship, 

suggestive of a causal relationship, inadequate to infer a causal relationship, and not likely to be a causal relationship 

(U.S. EPA. (2009). Integrated Science Assessment for Particulate Matter (Final Report). U.S. Environmental 

Protection Agency, Washington, DC, EPA/600/R-08/139F, Table 1–3). 

6

78 FR 3086 (January 15, 2013) pages 3103-3104.

7

 77 FR 38890 (June 29, 2012) pages 38906-38911.

8

 These causal inferences are based not only on the more expansive epidemiological evidence available in this 

review but also reflect consideration of important progress that has been made to advance our understanding of a 

number of potential biologic modes of action or pathways for PM-related cardiovascular and respiratory effects 

(U.S. EPA. (2009). Integrated Science Assessment for Particulate Matter (Final Report). U.S. Environmental 

Protection Agency, Washington, DC, EPA/600/R-08/139F, chapter 5). 

9

 78 FR 3086 (January 15, 2013) pages 3103-3104. 

10 U.S. EPA. (2009). Integrated Science Assessment for Particulate Matter (Final Report). U.S. Environmental 

Protection Agency, Washington, DC, EPA/600/R-08/139F, chapter 6 (section 6.5) and chapter 7 (Section 7.6). 

11 78 FR 3103 (January 15, 2013). 

12 78 FR 3103 (January 15, 2013). 

13 78 FR 3103-3104 (January 15, 2013). 

14 78 FR 3104 (January 15, 2013). 

15 U.S. EPA. (2009). Integrated Science Assessment for Particulate Matter (Final Report). U.S. Environmental 

Protection Agency, Washington, DC, EPA/600/R-08/139F. pg 2-13.

16 U.S. EPA. (2009). Integrated Science Assessment for Particulate Matter (Final Report). U.S. Environmental 

Protection Agency, Washington, DC, EPA/600/R-08/139F. Chapter 8 and Chapter 2. 

17 77 FR 38890,(June 29, 2012) page 38910. 

18 78 FR 3086 (January 15, 2013) page 3104. 

19 U.S. EPA. (2011). Policy Assessment for the Review of the PM NAAQS. U.S. Environmental Protection 

Agency, Washington, DC, EPA/452/R-11-003. section 2.2.1. 

20 U.S. EPA. (2009). Integrated Science Assessment for Particulate Matter (Final Report). U.S. Environmental 

Protection Agency, Washington, DC, EPA/600/R-08/139F. Chapter 8 and Chapter 2 (Section 2.4.1). 
6-29

21 U.S. EPA. (2009). Integrated Science Assessment for Particulate Matter (Final Report). U.S. Environmental 

Protection Agency, Washington, DC, EPA/600/R-08/139F. Section 2.3.4 and Table 2-6.

22 78 FR 3167-8 (January 15, 2013). 

23 77 FR 38947-51 (June 29, 2012). 

24 U.S. EPA. (2009). Integrated Science Assessment for Particulate Matter (Final Report). U.S. Environmental 

Protection Agency, Washington, DC, EPA/600/R-08/139F. Section 2.3.5 and Table 2-6.

25 78 FR 3121 (January 15, 2013). 

26

 Human exposure to ozone varies over time due to changes in ambient ozone concentration and because people 

move between locations which have notable different ozone concentrations. Also, the amount of ozone delivered to 

the lung is not only influenced by the ambient concentrations but also by the individuals breathing route and rate. 

27

 U.S. EPA. Integrated Science Assessment of Ozone and Related Photochemical Oxidants (Final Report). U.S. 

Environmental Protection Agency, Washington, DC, EPA/600/R-10/076F, 2013. The ISA is available at 

http://cfpub.epa.gov/ncea/isa/recordisplay.cfm?deid=247492#Download. 

28 The ISA evaluates evidence and draws conclusions on the causal relationship between relevant pollutant 

exposures and health effects, assigning one of five “weight of evidence” determinations: causal relationship, likely 

to be a causal relationship, suggestive of a causal relationship, inadequate to infer a causal relationship, and not 

likely to be a causal relationship. For more information on these levels of evidence, please refer to Table II in the 

Preamble of the ISA. 

29 U.S. EPA (2008). Integrated Science Assessment (ISA) for Sulfur Oxides – Health Criteria (Final Report). 

EPA/600/R-08/047F. Washington, DC,: U.S.EPA. Retrieved on March 19, 2009 from 

http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=198843. 

30 U.S. EPA (2008). Integrated Science Assessment for Oxides of Nitrogen – Health Criteria (Final Report).

EPA/600/R-08/071. Washington, DC,: U.S.EPA. Retrieved on March 19, 2009 from 

http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=194645. 

31 U.S. EPA (2008). Integrated Science Assessment for Oxides of Nitrogen – Health Criteria (Final Report).

EPA/600/R-08/071. Washington, DC: U.S.EPA. 

32 U.S. EPA, (2010). Integrated Science Assessment for Carbon Monoxide (Final Report). U.S. Environmental 

Protection Agency, Washington, DC, EPA/600/R-09/019F, 2010. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=218686. 

33

 The ISA evaluates the health evidence associated with different health effects, assigning one of five “weight of 

evidence” determinations: causal relationship, likely to be a causal relationship, suggestive of a causal relationship, 

inadequate to infer a causal relationship, and not likely to be a causal relationship. For definitions of these levels of 

evidence, please refer to Section 1.6 of the ISA. 

34

 Personal exposure includes contributions from many sources, and in many different environments. Total 

personal exposure to CO includes both ambient and nonambient components; and both components may contribute 

to adverse health effects. 

35 U.S. EPA. (2000). Integrated Risk Information System File for Benzene. This material is available electronically 

at: http://www.epa.gov/iris/subst/0276.htm. 

36 International Agency for Research on Cancer. (1982). IARC monographs on the evaluation of carcinogenic risk of 

chemicals to humans, Volume 29, Some industrial chemicals and dyestuffs, International Agency for Research on 

Cancer, World Health Organization, Lyon, France 1982. 

37 Irons, R.D.; Stillman, W.S.; Colagiovanni, D.B.; Henry, V.A. (1992). Synergistic action of the benzene metabolite 

hydroquinone on myelopoietic stimulating activity of granulocyte/macrophage colony-stimulating factor in vitro, 

Proc. Natl. Acad. Sci. 89:3691-3695. 

38 A unit risk estimate is defined as the increase in the lifetime risk of an individual who is exposed for a lifetime to 

1 μg/m3 benzene in air. 
6-30

39 U.S. EPA. (2000). Integrated Risk Information System File for Benzene. This material is available electronically 

at: http://www.epa.gov/iris/subst/0276.htm. 

40 International Agency for Research on Cancer (IARC). 1987. Monographs on the evaluation of carcinogenic risk 

of chemicals to humans, Volume 29, Supplement 7, Some industrial chemicals and dyestuffs, World Health 

Organization, Lyon, France. 

41 U.S. Department of Health and Human Services National Toxicology Program. (2011). 12th Report on 

Carcinogens available at: http://ntp.niehs.nih.gov/?objectid=03C9AF75-E1BF-FF40-DBA9EC0928DF8B15. 

42 Aksoy, M. (1989). Hematotoxicity and carcinogenicity of benzene. Environ. Health Perspect. 82: 193-197. 

EPA-HQ-OAR-2011-0135. 

43 Goldstein, B.D. (1988). Benzene toxicity. Occupational medicine. State of the Art Reviews. 3: 541-554. 

44 Rothman, N., G.L. Li, M. Dosemeci, W.E. Bechtold, G.E. Marti, Y.Z. Wang, M. Linet, L.Q. Xi, W. Lu, M.T. 

Smith, N. Titenko-Holland, L.P. Zhang, W. Blot, S.N. Yin, and R.B. Hayes. (1996). Hematotoxicity among Chinese 

workers heavily exposed to benzene. Am. J. Ind. Med. 29: 236-246.

45 U.S. EPA (2002). Toxicological Review of Benzene (Noncancer Effects). Environmental Protection Agency, 

Integrated Risk Information System (IRIS), Research and Development, National Center for Environmental 

Assessment, Washington DC. This material is available electronically at http://www.epa.gov/iris/subst/0276.htm. 

46 Qu, O.; Shore, R.; Li, G.; Jin, X.; Chen, C.L.; Cohen, B.; Melikian, A.; Eastmond, D.; Rappaport, S.; Li, H.; Rupa, 

D.; Suramaya, R.; Songnian, W.; Huifant, Y.; Meng, M.; Winnik, M.; Kwok, E.; Li, Y.; Mu, R.; Xu, B.; Zhang, 

X.; Li, K. (2003). HEI Report 115, Validation & Evaluation of Biomarkers in Workers Exposed to Benzene in 

China.

47 Qu, Q., R. Shore, G. Li, X. Jin, L.C. Chen, B. Cohen, et al. (2002). Hematological changes among Chinese 

workers with a broad range of benzene exposures. Am. J. Industr. Med. 42: 275-285.

48 Lan, Qing, Zhang, L., Li, G., Vermeulen, R., et al. (2004). Hematotoxically in Workers Exposed to Low Levels of 

Benzene. Science 306: 1774-1776.

49 Turtletaub, K.W. and Mani, C. (2003). Benzene metabolism in rodents at doses relevant to human exposure from 

Urban Air. Research Reports Health Effect Inst. Report No.113. 

50 U.S. Agency for Toxic Substances and Disease Registry (ATSDR). (2007). Toxicological profile for benzene. 

Atlanta, GA: U.S. Department of Health and Human Services, Public Health Service. 

http://www.atsdr.cdc.gov/ToxProfiles/tp3.pdf. 

51 A minimal risk level (MRL) is defined as an estimate of the daily human exposure to a hazardous substance that is 

likely to be without appreciable risk of adverse noncancer health effects over a specified duration of exposure. 

52 U.S. EPA. (2002). Health Assessment of 1,3-Butadiene. Office of Research and Development, National Center 

for Environmental Assessment, Washington Office, Washington, DC. Report No. EPA600-P-98-001F. This 

document is available electronically at http://www.epa.gov/iris/supdocs/buta-sup.pdf. 

53 U.S. EPA. (2002) “Full IRIS Summary for 1,3-butadiene (CASRN 106-99-0)” Environmental Protection Agency, 

Integrated Risk Information System (IRIS), Research and Development, National Center for Environmental 

Assessment, Washington, DC http://www.epa.gov/iris/subst/0139.htm. 

54 International Agency for Research on Cancer (IARC). (1999). Monographs on the evaluation of carcinogenic risk 

of chemicals to humans, Volume 71, Re-evaluation of some organic chemicals, hydrazine and hydrogen peroxide 

and Volume 97 (in preparation), World Health Organization, Lyon, France.

55 International Agency for Research on Cancer (IARC). (2008). Monographs on the evaluation of carcinogenic risk 

of chemicals to humans, 1,3-Butadiene, Ethylene Oxide and Vinyl Halides (Vinyl Fluoride, Vinyl Chloride and 

Vinyl Bromide) Volume 97, World Health Organization, Lyon, France. 

56 NTP. (2011). Report on Carcinogens, Twelfth Edition. Research Triangle Park, NC: U.S. Department of Health 

and Human Services, Public Health Service, National Toxicology Program. 499 pp. 
6-31

57 U.S. EPA. (2002). “Full IRIS Summary for 1,3-butadiene (CASRN 106-99-0)” Environmental Protection Agency, 

Integrated Risk Information System (IRIS), Research and Development, National Center for Environmental 

Assessment, Washington, DC http://www.epa.gov/iris/subst/0139.htm. 

58 Bevan, C.; Stadler, J.C.; Elliot, G.S.; et al. (1996). Subchronic toxicity of 4-vinylcyclohexene in rats and mice by 

inhalation. Fundam. Appl. Toxicol. 32:1-10.

59 EPA. Integrated Risk Information System. Formaldehyde (CASRN 50-00-0) 

http://www.epa.gov/iris/subst/0419/htm. 

60 National Toxicology Program, U.S. Department of Health and Human Services (HHS), 12th Report on 

Carcinogens, June 10, 2011. 

61 IARC Monographs on the Evaluation of Carcinogenic Risks to Humans Volume 88 (2006): Formaldehyde, 2-

Butoxyethanol and 1-tert-Butoxypropan-2-ol. 

62 IARC Mongraphs on the Evaluation of Carcinogenic Risks to Humans Volume 100F (2012): Formaldehyde. 

63 Hauptmann, M..; Lubin, J. H.; Stewart, P. A.; Hayes, R. B.; Blair, A. 2003. Mortality from lymphohematopoetic 

malignancies among workers in formaldehyde industries. Journal of the National Cancer Institute 95: 1615-1623. 

64 Hauptmann, M..; Lubin, J. H.; Stewart, P. A.; Hayes, R. B.; Blair, A. 2004. Mortality from solid cancers among 

workers in formaldehyde industries. American Journal of Epidemiology 159: 1117-1130. 

65 Beane Freeman, L. E.; Blair, A.; Lubin, J. H.; Stewart, P. A.; Hayes, R. B.; Hoover, R. N.; Hauptmann, M. 2009. 

Mortality from lymphohematopoietic malignancies among workers in formaldehyde industries: The National Cancer 

Institute cohort. J. National Cancer Inst. 101: 751-761. 

66 Pinkerton, L. E. 2004. Mortality among a cohort of garment workers exposed to formaldehyde: an update. 

Occup. Environ. Med. 61: 193-200.

67 Coggon, D, EC Harris, J Poole, KT Palmer. 2003. Extended follow-up of a cohort of British chemical workers 

exposed to formaldehyde. J National Cancer Inst. 95:1608-1615. 

68 Hauptmann, M,; Stewart P. A.; Lubin J. H.; Beane Freeman, L. E.; Hornung, R. W.; Herrick, R. F.; Hoover, R. N.; 

Fraumeni, J. F.; Hayes, R. B. 2009. Mortality from lymphohematopoietic malignancies and brain cancer among 

embalmers exposed to formaldehyde. Journal of the National Cancer Institute 101:1696-1708. 

69 ATSDR. 1999. Toxicological Profile for Formaldehyde, U.S. Department of Health and Human Services (HHS), 

July 1999. 

70 ATSDR. 2010. Addendum to theToxicological Profile for Formaldehyde. U.S. Department of Health and Human 

Services (HHS), October 2010. 

71 IPCS. 2002. Concise International Chemical Assessment Document 40. Formaldehyde. World Health 

Organization.

72 EPA (U.S. Environmental Protection Agency). 2010. Toxicological Review of Formaldehyde (CAS No. 50-00-0) 

– Inhalation Assessment: In Support of Summary Information on the Integrated Risk Information System (IRIS). 

External Review Draft. EPA/635/R-10/002A. U.S. Environmental Protection Agency, Washington DC [online]. 

Available: http://cfpub.epa.gov/ncea/irs_drats/recordisplay.cfm?deid=223614. 

73 NRC (National Research Council). 2011. Review of the Environmental Protection Agency’s Draft IRIS 

Assessment of Formaldehyde. Washington DC: National Academies Press. 

http://books.nap.edu/openbook.php?record_id=13142. 

74 U.S. EPA (1991). Integrated Risk Information System File of Acetaldehyde. Research and Development, 

National Center for Environmental Assessment, Washington, DC. This material is available electronically at 

http://www.epa.gov/iris/subst/0290.htm. 

75 U.S. EPA (1991). Integrated Risk Information System File of Acetaldehyde. This material is available 

electronically at http://www.epa.gov/iris/subst/0290.htm. 
6-32

76 NTP. (2011). Report on Carcinogens, Twelfth Edition. Research Triangle Park, NC: U.S. Department of Health 

and Human Services, Public Health Service, National Toxicology Program. 499 pp. 

77 International Agency for Research on Cancer (IARC). (1999). Re-evaluation of some organic chemicals, 

hydrazine, and hydrogen peroxide. IARC Monographs on the Evaluation of Carcinogenic Risk of Chemical to 

Humans, Vol 71. Lyon, France. 

78 U.S. EPA (1991). Integrated Risk Information System File of Acetaldehyde. This material is available 

electronically at http://www.epa.gov/iris/subst/0290.htm. 

79 U.S. EPA. (2003). Integrated Risk Information System File of Acrolein. Research and Development, National 

Center for Environmental Assessment, Washington, DC. This material is available electronically at 

http://www.epa.gov/iris/subst/0364.htm. 

80 Appleman, L.M., R.A. Woutersen, and V.J. Feron. (1982). Inhalation toxicity of acetaldehyde in rats. I. Acute and 

subacute studies. Toxicology. 23: 293-297.

81 Myou, S.; Fujimura, M.; Nishi K.; Ohka, T.; and Matsuda, T. (1993). Aerosolized acetaldehyde induces 

histamine-mediated bronchoconstriction in asthmatics. Am. Rev. Respir.Dis.148(4 Pt 1): 940-943.

82 U.S. EPA. (2003). Integrated Risk Information System File of Acrolein. Research and Development, National 

Center for Environmental Assessment, Washington, DC. This material is available at 

http://www.epa.gov/iris/subst/0364.htm. 

83 International Agency for Research on Cancer (IARC). (1995). Monographs on the evaluation of carcinogenic risk 

of chemicals to humans, Volume 63. Dry cleaning, some chlorinated solvents and other industrial chemicals, World 

Health Organization, Lyon, France. 

84 U.S. EPA. (2003). Integrated Risk Information System File of Acrolein. Office of Research and Development, 

National Center for Environmental Assessment, Washington, DC. This material is available at 

http://www.epa.gov/iris/subst/0364.htm. 

85 U.S. EPA. (2003). Integrated Risk Information System File of Acrolein. Office of Research and Development, 

National Center for Environmental Assessment, Washington, DC. This material is available at 

http://www.epa.gov/iris/subst/0364.htm. 

86 U.S. EPA. (2003). Toxicological review of acrolein in support of summary information on Integrated Risk 

Information System (IRIS) National Center for Environmental Assessment, Washington, DC. EPA/635/R-03/003. p. 

10. Available online at: http://www.epa.gov/ncea/iris/toxreviews/0364tr.pdf. 

87 U.S. EPA. (2003). Toxicological review of acrolein in support of summary information on Integrated Risk 

Information System (IRIS) National Center for Environmental Assessment, Washington, DC. EPA/635/R-03/003. 

Available online at: http://www.epa.gov/ncea/iris/toxreviews/0364tr.pdf. 

88 Morris JB, Symanowicz PT, Olsen JE, et al. (2003). Immediate sensory nerve-mediated respiratory responses to 

irritants in healthy and allergic airway-diseased mice. J Appl Physiol 94(4):1563-1571.

89 U.S. EPA. (2009). Graphical Arrays of Chemical-Specific Health Effect Reference Values for Inhalation 

Exposures (Final Report). U.S. Environmental Protection Agency, Washington, DC, EPA/600/R-09/061, 2009. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=211003. 

90 U.S. EPA. (2006). Air quality criteria for ozone and related photochemical oxidants (Ozone CD). Research 

Triangle Park, NC: National Center for Environmental Assessment; report no. EPA/600/R-05/004aF-cF.3v. page 5-

78 Available at http://cfpub.epa.gov/ncea/. 

91 U.S. EPA Air Quality Criteria for Ozone and Related Photochemical Oxidants (Final). U.S. Environmental 

Protection Agency, Washington, D.C., EPA 600/R-05/004aF-cF, 2006. page 5-63. This document is available in . 

This document may be accessed electronically at: http://www.epa.gov/ttn/naaqs/standards/ozone/s_o3_cr_cd.html. 

92 U.S. EPA Air Quality Criteria for Ozone and Related Photochemical Oxidants (Final). U.S. Environmental 

Protection Agency, Washington, D.C., EPA 600/R-05/004aF-cF, 2006. page 5-78. This document is available in . 

This document may be accessed electronically at: http://www.epa.gov/ttn/naaqs/standards/ozone/s_o3_cr_cd.html. 
6-33

93 Agency for Toxic Substances and Disease Registry (ATSDR). (1995). Toxicological profile for Polycyclic 

Aromatic Hydrocarbons (PAHs). Atlanta, GA: U.S. Department of Health and Human Services, Public Health 

Service. Available electronically at http://www.atsdr.cdc.gov/ToxProfiles/TP.asp?id=122&tid=25. 

94 U.S. EPA (2002). Health Assessment Document for Diesel Engine Exhaust. EPA/600/8-90/057F Office of 

Research and Development, Washington DC. http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=29060. 

95 International Agency for Research on Cancer (IARC). (2012). Monographs on the Evaluation of the 

Carcinogenic Risk of Chemicals for Humans, Chemical Agents and Related Occupations. Vol. 100F. Lyon, France. 

96 U.S. EPA (1997). Integrated Risk Information System File of indeno(1,2,3-cd)pyrene. Research and Development, 

National Center for Environmental Assessment, Washington, DC. This material is available electronically at 

http://www.epa.gov/ncea/iris/subst/0457.htm. 

97 Perera, F.P.; Rauh, V.; Tsai, W-Y.; et al. (2002). Effect of transplacental exposure to environmental pollutants on 

birth outcomes in a multiethnic population. Environ Health Perspect. 111: 201-205.

98 Perera, F.P.; Rauh, V.; Whyatt, R.M.; Tsai, W.Y.; Tang, D.; Diaz, D.; Hoepner, L.; Barr, D.; Tu, Y.H.; Camann, 

D.; Kinney, P. (2006). Effect of prenatal exposure to airborne polycyclic aromatic hydrocarbons on 

neurodevelopment in the first 3 years of life among inner-city children. Environ Health Perspect 114: 1287-1292. 

99 U. S. EPA. 1998. Toxicological Review of Naphthalene (Reassessment of the Inhalation Cancer Risk), 

Environmental Protection Agency, Integrated Risk Information System, Research and Development, National 

Center for Environmental Assessment, Washington, DC. This material is available electronically at 

http://www.epa.gov/iris/subst/0436.htm. 

100 U. S. EPA. 1998. Toxicological Review of Naphthalene (Reassessment of the Inhalation Cancer Risk), 

Environmental Protection Agency, Integrated Risk Information System, Research and Development, National 

Center for Environmental Assessment, Washington, DC. This material is available electronically at 

http://www.epa.gov/iris/subst/0436.htm. 

101 U. S. EPA. (1998). Toxicological Review of Naphthalene (Reassessment of the Inhalation Cancer Risk), 

Environmental Protection Agency, Integrated Risk Information System, Research and Development, National 

Center for Environmental Assessment, Washington, DC. This material is available electronically at 

http://www.epa.gov/iris/subst/0436.htm. 

102 Oak Ridge Institute for Science and Education. (2004). External Peer Review for the IRIS Reassessment of the 

Inhalation Carcinogenicity of Naphthalene. August 2004. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=84403. 

103 NTP. (2011). Report on Carcinogens, Twelfth Edition. Research Triangle Park, NC: U.S. Department of Health 

and Human Services, Public Health Service, National Toxicology Program. 499 pp. 

104 International Agency for Research on Cancer (IARC). (2002). Monographs on the Evaluation of the 

Carcinogenic Risk of Chemicals for Humans. Vol. 82. Lyon, France. 

105 U. S. EPA. (1998). Toxicological Review of Naphthalene, Environmental Protection Agency, Integrated Risk 

Information System, Research and Development, National Center for Environmental Assessment, Washington, DC. 

This material is available electronically at http://www.epa.gov/iris/subst/0436.htm. 

106 U.S. EPA. (1998). Toxicological Review of Naphthalene. Environmental Protection Agency, Integrated Risk 

Information System (IRIS), Research and Development, National Center for Environmental Assessment, 

Washington, DC http://www.epa.gov/iris/subst/0436.htm. 

107 U.S. EPA Integrated Risk Information System (IRIS) database is available at: www.epa.gov/iris. 

108 It should be noted that there are no peer reviewed EPA-authored reviews of traffic-related health studies. The 

HEI panel primarily used epidemiology studies for inferring whether there was sufficient evidence of a causal 

association exists between a particular health effect and traffic-related air pollution, In its weight-of-evidence 

determinations, the panel also placed “considerable weight” on controlled human exposure studies. However, it 

restricted consideration of other toxicological studies to whether or not the studies provided “general mechanistic 

support” for the inferences of causality made on the basis of epidemiology. 
6-34

109 Health Effects Institute Panel on the Health Effects of Traffic-Related Air Pollution. (2010). Traffic-related air 

pollution: a critical review of the literature on emissions, exposure, and health effects. HEI Special Report 17. 

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110 Bureau of Labor Statistics. (2009). American Time Use Survey. [Online at http://www.bls.gov/tus]. 

111 Bureau of Transportation Statistics. (2003). Highlights of the 2001 National Household Travel Survey. Report 

BTS03-05. [Online at http://www.bts.gov]. 

112 The autonomic nervous system (ANS) consists of sympathetic and parasympathetic components. The 

sympathetic ANS signals body systems to “fight or flight.” The parasympathetic ANS signals the body to “rest and 

digest.” In general, HRV is indicative of parasympathetic control of the heart. 

113 Baja, E.S.; Schwartz, J.D.; Wellenius, G.A.; Coull, B.A.; Zanobetti, A.; Vokonas, P.S.; Suh, H.H. (2010). 

Traffic-related air pollution and QT interval: modification by diabetes, obesity, and oxidate stress gene 

polymorphisms in the Normative Aging Study. Environ Health Perspect 118: 840-846. doi:10.1289/ehp.0901396. 

114 Zanobettia, A.; Stone, P.H.; Speizer, F.E.; Schwarz, J.D.; Coull, B.A.; Suh, H.H.; Nearing, B.D.; Mittleman, 

M.A.; Verrier, R.L.; Gold, D.R. (2009). T-wave alterans, air pollution and traffic in high-risk subjects. Am J 

Cardiol 104: 665-670. doi:10.1016/j.amjcard.2009.04.046. 

115 Brook, R.D.; Rajagopalan, S.; Pope, C.A.; Brook, J.R.; Bhatnagar, A.; Diez-Rouz, A.V.; Holguin, F.; Hong, Y.; 

Luepker, R.V.; et la. (2010). Particulate matter air pollution and cardiovascular disease: an update to the scientific 

statement from the American Heart Association. Circulation 121: 2331-2378. 

doi:10.1161/CIR.0b013e3181dbece1. 

116 Bastain, T.M.; Gilliland, F.D.; Li, Y.; Saxon, A.; Diaz-Sanchez, D. (2003) Intraindividual reproducibility of nazal 

allergic responses to diesel exhaust particles indicates a susceptible phenotype. Clinical Immunol 109: 130-136.

117 Gilliland, F.D.; Li, Y.; Diaz-Sanchez, D. (2004) Effect of glutathione-S-transferase M1 and P1 genotypes on 

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118 Svartengren, M., Strand, V.; Bylin, G. Järup, L.; Pershagen, G. (2000) Short-term exposure to air pollution in a 

road tunnel enhances the asthmatic response to allergen. Eur Respir J 15: 716-724.

119 Vrijheid, M.; Martinez, D.; Manzanares, S.; Dadvand, P.; Schembari, A.; Rankin, F.; Nieuwenhuijsen, M. (2011). 

Ambient air pollution and risk of congenital anomalies: a systematic review and meta-analysis. Environ Health 

Perspect 119: 598-606. doi:10.1289/ehp.1002946. 

120 Raaschou-Nielson, O.; Reynolds, P. (2006). Air pollution and childhood cancer: a review of the epidemiological 

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123 U.S. EPA (2009). Integrated Science Assessment for Particulate Matter (Final Report). U.S. Environmental 

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124 U.S. EPA (2009). Integrated Science Assessment for Particulate Matter (Final Report). U.S. Environmental 

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125 U.S. EPA. (2005). Review of the National Ambient Air Quality Standard for Particulate Matter: Policy 

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126 U.S. EPA. (2008). Integrated Science Assessment for Oxides of Nitrogen and Sulfur- Ecological Criteria (Final). 

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127 U.S. EPA. (2008). Integrated Science Assessment for Oxides of Nitrogen and Sulfur- Ecological Criteria (Final). 

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128 Environmental Protection Agency (2003). Response Of Surface Water Chemistry to the Clean Air Act 

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129 Fenn, M.E. and Blubaugh, T.J. (2005). Winter Deposition of Nitrogen and Sulfur in the Eastern Columbia River 

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130 Galloway, J. N.; Cowling, E. B. (2002). Reactive nitrogen and the world: 200 years of change. Ambio 31: 64–71. 

131 Bricker, Suzanne B., et al., (1999). National Estuarine Eutrophication Assessment, Effects of Nutrient 

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132 Smith, W.H. (1991). “Air pollution and Forest Damage.” Chemical Engineering News, 69(45): 30-43. 

133 Gawel, J.E.; Ahner, B.A.; Friedland, A.J.; and Morel, F.M.M. (1996). “Role for heavy metals in forest decline 

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134 Cotrufo, M.F.; DeSanto, A.V.; Alfani, A.; et al. (1995). “Effects of urban heavy metal pollution on organic matter 

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135 Niklinska, M.; Laskowski, R.; Maryanski, M. (1998). “Effect of heavy metals and storage time on two types of 

forest litter: basal respiration rate and exchangeable metals.” Ecotoxicological Environmental Safety, 41: 8-18. 

136 U.S. EPA (2009). Integrated Science Assessment for Particulate Matter (Final Report). U.S. Environmental 

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137 Mason, R.P. and Sullivan, K.A. (1997). “Mercury in Lake Michigan.” Environmental Science & Technology, 31: 

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138 Landis, M.S. and Keeler, G.J. (2002). “Atmospheric mercury deposition to Lake Michigan during the Lake 

Michigan Mass Balance Study.” Environmental Science & Technology, 21: 4518-24. 

139 U.S. EPA. (2000). EPA453/R-00-005, “Deposition of Air Pollutants to the Great Waters: Third Report to 

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140 National Science and Technology Council (NSTC) (1999). “The Role of Monitoring Networks in the 

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141 Callender, E. and Rice, K.C. (2000). “The Urban Environmental Gradient: Anthropogenic Influences on the 

Spatial and Temporal Distributions of Lead and Zinc in Sediments.” Environmental Science & Technology, 34: 232-

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142 Rice, K.C. (1999). “Trace Element Concentrations in Streambed Sediment Across the Conterminous United 

States.” Environmental Science & Technology, 33: 2499-2504. 

143 U.S. EPA. (2013) Integrated Science Assessment for Lead (Final Report). U.S. Environmental Protection 

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144 Ely, JC; Neal, CR; Kulpa, CF; et al. (2001). “Implications of Platinum-Group Element Accumulation along U.S. 

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145 U.S. EPA. (1998). EPA454/R-98-014, “Locating and Estimating Air Emissions from Sources of Polycyclic 

Organic Matter,” Office of Air Quality Planning and Standards, Research Triangle Park, North Carolina. 

146 U.S. EPA. (1998). EPA454/R-98-014, “Locating and Estimating Air Emissions from Sources of Polycyclic 

Organic Matter,” Office of Air Quality Planning and Standards, Research Triangle Park, North Carolina. 

147 Simcik, M.F.; Eisenreich, S.J.; Golden, K.A.; et al. (1996). “Atmospheric Loading of Polycyclic Aromatic 

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148 Simcik, M.F.; Eisenreich, S.J.; and Lioy, P.J. (1999). “Source apportionment and source/sink relationship of 

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149 Arzayus, K.M.; Dickhut, R.M.; and Canuel, E.A. (2001). “Fate of Atmospherically Deposited Polycyclic 

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150 Park, J.S.; Wade, T.L.; and Sweet, S. (2001). “Atmospheric distribution of polycyclic aromatic hydrocarbons and 

deposition to Galveston Bay, Texas, USA.” Atmospheric Environment, 35: 3241-3249. 

151 Poor, N.; Tremblay, R.; Kay, H.; et al. (2002). “Atmospheric concentrations and dry deposition rates of 

polycyclic aromatic hydrocarbons (PAHs) for Tampa Bay, Florida, USA.” Atmospheric Environment 38: 6005-

6015. 

152 Arzayus, K.M.; Dickhut, R.M.; and Canuel, E.A. (2001). “Fate of Atmospherically Deposited Polycyclic 

Aromatic Hydrocarbons (PAHs) in Chesapeake Bay.” Environmental Science & Technology, 35, 2178-2183. 

153 U.S. EPA. (2000). EPA453/R-00-005, “Deposition of Air Pollutants to the Great Waters: Third Report to 

Congress,” Office of Air Quality Planning and Standards, Research Triangle Park, North Carolina. 

154 Van Metre, P.C.; Mahler, B.J.; and Furlong, E.T. (2000). “Urban Sprawl Leaves its PAH Signature.” 

Environmental Science & Technology, 34: 4064-4070. 

155 Cousins, I.T.; Beck, A.J.; and Jones, K.C. (1999). “A review of the processes involved in the exchange of semivolatile organic compounds across the air-soil interface.” The Science of the Total Environment, 228: 5-24. 

156 Tuhackova, J. et al. (2001). Hydrocarbon deposition and soil microflora as affected by highway traffic. 

Environmental Pollution, 113: 255-262. 

157 73 FR 16486 (March 27, 2008).

158 73 FR 16491 (March 27, 2008). Only a small percentage of all the plant species growing within the U.S. (over 

43,000 species have been catalogued in the USDA PLANTS database) have been studied with respect to ozone 

sensitivity. 

159 The concentration at which ozone levels overwhelm a plant’s ability to detoxify or compensate for oxidant 

exposure varies. Thus, whether a plant is classified as sensitive or tolerant depends in part on the exposure levels 

being considered. Chapter 9, section 9.3.4 of U.S. EPA, 2013 Integrated Science Assessment for Ozone and 

Related Photochemical Oxidants. Office of Research and Development/National Center for Environmental 

Assessment. U.S. Environmental Protection Agency. EPA 600/R-10/076F. 

160 73 FR 16492 (March 27, 2008).

161 73 FR 16493-16494 ( March 27, 2008). Per footnote 2 above, ozone impacts could be occurring in areas where 

plant species sensitive to ozone have not yet been studied or identified.. 

162 73 FR 16490/ 16497 (March 27, 2008). 

163 U.S. EPA. Integrated Science Assessment of Ozone and Related Photochemical Oxidants (Final Report). U.S. 

Environmental Protection Agency, Washington, DC, EPA/600/R-10/076F, 2013. The ISA is available at 

http://cfpub.epa.gov/ncea/isa/recordisplay.cfm?deid=247492#Download. 

164 The Ozone ISA evaluates the evidence associated with different ozone related health and welfare effects, 

assigning one of five “weight of evidence” determinations: causal relationship, likely to be a causal relationship, 

suggestive of a causal relationship, inadequate to infer a causal relationship, and not likely to be a causal 

relationship. For more information on these levels of evidence, please refer to Table II of the ISA. 

165 U.S. EPA. (1991). Effects of organic chemicals in the atmosphere on terrestrial plants. EPA/600/3-91/001. 

166 Cape JN, ID Leith, J Binnie, J Content, M Donkin, M Skewes, DN Price AR Brown, AD Sharpe. (2003). Effects 

of VOCs on herbaceous plants in an open-top chamber experiment. Environ. Pollut. 124:341-343.

167 Cape JN, ID Leith, J Binnie, J Content, M Donkin, M Skewes, DN Price AR Brown, AD Sharpe. (2003). Effects 

of VOCs on herbaceous plants in an open-top chamber experiment. Environ. Pollut. 124:341-343.
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168 Viskari E-L. (2000). Epicuticular wax of Norway spruce needles as indicator of traffic pollutant deposition. 

Water, Air, and Soil Pollut. 121:327-337. 

169 Ugrekhelidze D, F Korte, G Kvesitadze. (1997). Uptake and transformation of benzene and toluene by plant 

leaves. Ecotox. Environ. Safety 37:24-29.

170 Kammerbauer H, H Selinger, R Rommelt, A Ziegler-Jons, D Knoppik, B Hock. (1987). Toxic components of 

motor vehicle emissions for the spruce Picea abies. Environ. Pollut. 48:235-243.
7-1

Chapter 7 Impacts of the Rule on Emissions and Air Quality 

This chapter presents the overall emissions and air quality impacts of the Tier 3 

standards. Section 7.1 describes the national impacts on criteria and toxic emissions resulting 

from the Tier 3 program. Section 7.2 describes the air quality effects of the emission reductions. 

Because the air quality analysis requires emission inventories with greater geographical 

resolution than the national average inventories, the emission inventories described in the two 

sections were developed separately, as described in each portion of this chapter. Section 7.3

discusses the impact of the program on greenhouse gas emissions. 

7.1 Criteria and Toxic Pollutant Emission Impacts 

7.1.1 Overview 

This section presents the projected national emission impacts of Tier 3 standards on

criteria and toxic air pollutants for selected calendar years, and the methodology used to estimate 

these reductions. The Tier 3 fuel and vehicle standards will directly reduce emissions of nitrogen 

oxides (NOX) (including nitrogen dioxide (NO2)), volatile organic compounds (VOC), carbon 

monoxide (CO), particulate matter (PM2.5), air toxics, and sulfur dioxide (SO2). The 

implementation of lower sulfur gasoline will reduce criteria and air toxic emissions from the 

existing gasoline-powered vehicle fleet, and cause some reductions in SO2 emissions from the 

nonroad gasoline sector. The largest reductions come immediately following the implementation 

of the fuel standard, as a significant share of overall emissions are produced by Tier 2 and older 

vehicles. To reflect these early reductions, we present the emission reductions in calendar year 

2018, near the beginning of the fuel program. 

The vehicle standards will reduce emissions as the cleaner cars and trucks begin to enter 

the fleet in model year 2017 and model year 2018, respectively. The magnitude of reduction will 

grow as the contribution of these vehicles to fleet emissions becomes more prominent – to reflect 

this, we are also presenting emission reductions in calendar year 2030, when 70 percent of the 

miles travelled are from vehicles that meet the fully phased-in Tier 3 standards. Furthermore, 

2030 is a standard out-year for evaluation; it is used for air quality modeling in this rule as well 

as recent EPA rules. However, the full impact of the vehicle program will be realized after 2030. 

For this reason, we are also presenting emissions reductions in calendar year 2050, when the 

fleet will have fully turned over to the vehicles meeting the fully phased-in Tier 3 standards. As 

explained in Section 7.2, air quality modeling was done only for 2018 and 2030. 

Emission impacts presented in this section are estimated on an annual basis, for all 50 

U.S. states plus the District of Columbia, Puerto Rico and the U.S. Virgin Islands. The 

reductions from onroad sources were estimated using an updated version of EPA’s Motor 

Vehicle Emission Simulator (MOVES) model, as described in detail in Section 7.1.3; and the 

NONROAD model for offroad sources. Reductions were estimated compared to a reference case 

that assumed an average gasoline sulfur level of 30 ppm (10 ppm in California) and continuation 
7-2

of the Tier 2 vehicle program indefinitely, with the exception of California and Section 177 

states that have adopted the LEV III program. For those states, adoption of LEV III was 

included in the reference case.A

The emission inventory methodology applied to generate these national estimates does 

differ from the methodology used to generate the finely resolved emission inventories needed for 

the air quality modeling, leading to some differences in absolute estimates of tons reduced 

between the two analyses. These differences are discussed in Section 7.2.1.1. 

7.1.2 Scenarios Modeled 

We analyzed emission impacts of the Tier 3 vehicle emissions and fuel standards by 

comparing projected emissions for future years without the Tier 3 rule (reference scenario) to 

projected emissions for future years with the Tier 3 standards in place (control scenario). Table 

7-1 below presents an overview of the reference and control scenarios for calendar years 2018 

and 2030. Both scenarios reflect the renewable fuel volumes and market fractions projected by 

the Annual Energy Outlook 2013 Report.1 We thus refer to this renewable fuel level as “AEO 

2013”. 

 

A

 These states include Connecticut, Delaware, Maryland, Maine, Massachusetts, New Jersey, New York, Oregon, 

Pennsylvania, Rhode Island, Washington, and Vermont. 
7-3

Table 7-1 Overview of Reference and Control Scenarios 

Reference Scenario Control Scenario

2018

Renewable Fuels: AEO 2013a

 17.5 B gallons renewable fuels 

 (18.3 B ethanol-equivalent gallons):

16.0 B gallons ethanol: E10 b, E15c, 

E85d

Fuel Sulfur Level: 

 30 ppm (10 ppm California)

Fleet: e

96 percent Tier 2 and older vehicles

 4 percent LEV III vehicles

Renewable Fuels: AEO 2013a

 17.5 B gallons renewable fuels 

 (18.3 B ethanol-equivalent gallons):

16.0 B gallons ethanol: E10 b, E15c, 

E85d

Fuel Sulfur Level: 

 10 ppm

Fleet: e

 86 percent Tier 2 and older vehicles

 14 percent Tier 3/LEV III vehicles 

2030

Renewable Fuels: AEO 2013a

 17.6 B gallons renewable fuels 

 (18.6 B ethanol-equivalent gallons):

15.3 B gallons ethanol: E10 b, E15c, 

E85d

Fuel Sulfur Level: 

 30 ppm (10 ppm California)

Fleet: e

76 percent Tier 2 and older vehicles

 24 percent LEV III vehicles

Renewable Fuels: AEO 2013a

 17.6 B gallons renewable fuels 

 (18.6 B ethanol-equivalent gallons):

15.3 B gallons ethanol: E10 b, E15c, 

E85d

Fuel Sulfur Level: 

 10 ppm

Fleet: e

 21 percent Tier 2 and older vehicles

 79 percent Tier 3/LEV III vehicles

a U.S. Energy Information Administration, Annual Energy Outlook 2013 (April 15, 2013) 

b Gasoline containing 10 percent ethanol by volume 

c

 Gasoline containing 15 percent ethanol by volume 

d

 Gasoline containing up to 85 percent ethanol by volume (74 percent nominal used in this analysis) 

e

 Fraction of the vehicle population 

Our reference scenarios assumed an average fuel sulfur level of 30 ppm in accordance 

with the Tier 2 gasoline sulfur standards. Under the Tier 3 program, federal gasoline will contain 

no more than 10 ppm sulfur on an annual average basis by January 1, 2017 (Section V of the 

preamble), and we therefore assumed a nationwide fuel sulfur level of 10 ppm for both future 

year control cases. A more detailed description of our fuel inputs and assumptions for this 

analysis can be found in Section 7.1.3.2.

We assumed a continuation of the existing Tier 2 standards for model years 2017 and 

later in modeling emissions for our reference scenario, with the exception of California and 

Section 177 states that have adopted the LEV III program. Our Tier 3 control scenario modeled

the suite of exhaust and evaporative emission standards for light-duty vehicles (LDVs), light 

duty trucks (LDTs: 1-4), medium passenger vehicles (MDPVs) and large pick-ups and vans 

(Class 2b and 3 trucks) described in Section IV of the preamble, including: 
7-4

Fleet average Federal Test Procedure (FTP) NMOG+NOX standards of 30 

mg/mi for LDVs, LDTs and MDPVs, phasing in from MYs 2017 to 2025 for 

the light-duty fleet under 6,000 lbs. GVWR and phasing in from MYs 2018 to 

2025 for the light-duty fleet over 6,000 lbs. GVWR, and MDPVs 

Fleet average Supplemental Federal Test Procedure (SFTP) NMOG+NOX

standards of 50 mg/mi for LDVs, LDTs and MDPVs, phasing in from MYs 

2017 to 2025 for the light-duty fleet under 6,000 lbs. GVWR and phasing in 

from MYs 2018 to 2025 for the light-duty fleet over 6,000 lbs. GVWR, and 

MDPVs

Per-vehicle FTP PM standard of 3 mg/mi for LDVs, LDTs and MDPVs, 

phasing in from MYs 2017 to 2022 for the light-duty fleet under 6,000 lbs. 

GVWR and phasing in from MYs 2018 to 2022 for the light-duty fleet over 

6,000 lbs. GVWR, and MDPVs 

Per-vehicle US06-only PM standard of 10 mg/mi for LDVs, LDTs and 

MDPVs through MY2021 and of 6 mg/mi for MY2022 and later model years 

New standards for Class 2b and 3 trucks phasing in by MY 2022 including 

NMOG+NOX declining fleet average, and more stringent PM standards 

More stringent evaporative emission standards for diurnal plus hot soak 

emissions, a new canister bleed test and emission standard, and new 

requirements addressing evaporative leaks on in-use vehicles. 

New refueling emission control requirements for all complete HDGVs equal 

to or less than 14,000 lbs GVWR (i.e., Class 2b/3 HDGVs), starting in the 

2018 model year, and for all larger HDGVs by the 2022 model year 

The Tier 3 standards will reduce onroad criteria and toxic emissions, and to a much 

smaller extent, nonroad SO2 emissions, but will not affect upstream, refueling or portable fuel 

container criteria or toxic emissions. The methodology for estimating emission impacts and the 

results for onroad and nonroad emissions are described in Section 7.1.3 and Section 7.1.4, 

respectively. 

Implementation of the Tier 3 standards is aligned with the model year 2017-2025 LightDuty GHG standards2

to achieve significant criteria pollutant and GHG emissions reductions 

while providing regulatory certainty and compliance efficiency to the auto and oil industries. 

Accordingly, the analyses for the Tier 3 rule include the final LD GHG standards in both the 

reference and control scenarios, and thus account for their impacts on the future vehicle fleet and 

future fuel consumption. 

The analysis described here accounts for the following national onroad rules: 

Tier 2 Motor Vehicle Emissions Standards and Gasoline Sulfur Control 

Requirements (65 FR 6698, February 10, 2000) 
7-5

Heavy-Duty Engine and Vehicle Standards and Highway Diesel Fuel Sulfur 

Control Requirements (66 FR 5002, January 18, 2001) 

Mobile Source Air Toxics Rule (72 FR 8428, February 26, 2007) 

Regulation of Fuels and Fuel Additives: Changes to Renewable Fuel Standard 

Program (75 FR 14670, March 26, 2010) 

Light-Duty Vehicle Greenhouse Gas Emission Standards and Corporate Average 

Fuel Economy Standards for 2012-2016 (75 FR 25324, May 7, 2010) 

Greenhouse Gas Emissions Standards and Fuel Efficiency Standards for 

Medium- and Heavy-Duty Engines and Vehicles (76 FR 57106, September 15, 

2011) 

2017 and Later Model Year Light-Duty Vehicle Greenhouse Gas Emissions and 

Corporate Average Fuel Economy Standards (77 FR 62623, October 15, 2012) 

In addition, the modeling accounts for state and local rules including local fuel standards, 

Inspection/Maintenance programs, Stage II refueling controls, the National Low Emission 

Vehicle Program (NLEV), and the Ozone Transport Commission (OTC) LEV Program. 

Furthermore, the Tier 3 emissions modeling for both the national inventory and air quality 

analysis includes California’s LEV III program and its associated emission reductions from both 

California and the states that adopted the LEV III program, in the baseline scenario. See the Tier 

3 emissions modeling TSD for more detail. 

7.1.3 Onroad Emissions 

7.1.3.1 Methodology Overview 

EPA’s official model for use in estimating mobile source emissions is known as the 

Motor Vehicle Emission Simulator (MOVES), with the most recent version approved for use in 

State Implementation Plan (SIP) and transportation conformity analyses being MOVES2010b.3 

A version of MOVES2010b, updated specifically for this analysis, was used to estimate 

emissions of criteria and air toxic emissions from on-road gasoline and diesel vehicles for the 

entire U.S. for the reference and control scenarios described in Section 7.1.2 above, for calendar 

years 2018, 2030, and 2050.B

 

 

B

The MOVES updates are reflected in a version of the MOVES model code (October 2, 2012 Version F) and 

concurrently updated versions of the MOVES default database; October 2, 2012 Version K_truncatedGFRE for the 

inventory runs for the air quality modeling and October 2, 2012 Version L_truncatedGFREIM for the national 

inventory runs (see Section 7.2.1.1 for details). Both the code and the databases are available in the Tier 3 docket. 

As these updates are still draft, these code and/or databases are not approved for official use in SIP and conformity 

analyses.
7-6

The MOVES model updates affecting reference and control case emissions were 

extensive, and are documented in a separate memorandum to the Tier 3 docket.4 Updates made 

to MOVES2010b for this analysis primarily incorporated major new research in four areas. The 

first involves fuel effects on exhaust emissions from Tier 2 vehicles. The second involves 

improvements in estimation of evaporative emissions from all vehicles, including Tier 2 

vehicles. The third involves accounting for the effects of fuel sulfur level on exhaust emissions. 

The fourth involves estimating the exhaust emissions from vehicles using E85 fuel (gasoline 

containing up to 85 percent ethanol by volume). Other than sulfur, these changes had more 

bearing on updating the reference case emissions than on the projected reductions from the Tier 

3 standards. 

The effects of changes in fuel properties on exhaust emissions of Tier 2 vehicles, which 

comprise the majority of the fleet by 2018, were assessed through the results of the EPAct Phase3 Program.5

 Specific fuel properties addressed include ethanol level, aromatics, distillation 

properties, and volatility (Reid Vapor Pressure, or RVP). Methods used to account for the 

effects of these properties in inventory modeling are described in a separate memorandum to the 

docket.6

 Improvements in estimating and projecting evaporative emissions are described in this 

document (see Section 7.1.3.3.7). Finally, because the updates to fuel sulfur effects are critical 

for estimating the reductions from the Tier 3 program, they are also presented in detail in Section 

7.1.3.4. 

In addition to fuel effects, we also improved emission estimates in other areas. The 

sulfate, sulfur dioxide, organic carbon and elemental carbon emission rates for 2007-and-later 

heavy-duty diesel vehicles were updated to include information from a recent study that 

examined the composition of particulate emissions from advanced diesel engines.7 HC, CO and 

NOX start and running emission rates for light heavy-duty gasoline vehicles were updated to fix 

an error in these rates for 2007-and-later emissions, and we repaired errors in the MOVES2010b 

emission rates for NH3, NO and NO2.

C,8

The MOVES version used for this analysis also includes an added capability to model 

many hazardous air pollutants. And, additional changes were made to the MOVES2010b model 

to facilitate the large number of parallel runs that needed to be done to complete the Tier 3 air 

quality modeling inventories. These changes are also detailed in the docket memo for the 

proposed rule addressing MOVES updates9. 

In addition to the model updates needed to incorporate new research, a set of custom 

inputs were developed to allow MOVES to model the reference and control scenarios. Some of 

these inputs were required to reflect regional variations in fuels for both the reference and control 

scenarios, as discussed in detail in Section 7.1.3.2. Other inputs were required to model the 

vehicle program for exhaust and evaporative emissions, discussed in Section 7.1.3.3. 

The national emission inventories presented in this section were developed with a simpler 

and quicker method than we used for the air quality modeling. The abbreviated approach makes 

 

C

 The changes to the NO and NO2 rates did not impact the total NOX emissions, but facilitated the output of separate 

results for nitric oxide and nitrogen dioxide. 
7-7

the analysis easier for stakeholders and other commenters to replicate. National emission 

inventories were developed using the pre-aggregation feature of MOVES at the state level. For 

all pollutants, the default pre-aggregation level of ‘hour’ was selected, which condenses the 

county-level temperatures into a single state average temperature by hour of the day. While the 

model and many of the inputs are identical for the emission inventory modeling performed for 

the air quality analysis, the pre-aggregation approach is coarser than the approach described in 

Section 7.2 used to develop the gridded/hourly emission inventories needed for air quality 

modeling. In addition to the difference in temperature resolution (state average vs. gridded 

hourly temperature), the national emission inventory analysis also used information contained in 

the MOVES2010b default database for fleet age distributions, activity inputs (e.g., speeds), 

temperatures, emission standards, and inspection/maintenance programs. In contrast, as 

discussed in Section 7.2, the air quality modeling inventory methodology used the data supplied 

by state and regional modelers for many of these inputs, and employed hourly meteorological 

data. Both the national emission inventories and the air quality modeling inventory accounted

for the state adoption of California LEV III standards, as well as previous LEV programs, in the 

modeling baseline. The future year projections of vehicle population and vehicle miles travelled 

were updated to reflect the latest estimates from the Department of Energy’s Annual Energy 

Outlook (AEO2013). 

To assure that adequate temperature resolution was incorporated into the national 

emission inventory processes, MOVES was run separately for January and July, and annual 

emissions were extrapolated (for all pollutants except PM) by scaling up each month by a factor 

of 5.88. For PM, to offset the disproportionate effect of the colder temperature January results, a 

scaling factor of 4.3 was applied to January and 7.5 to July; these factors were determined based 

on analysis of annual PM emissions during modeling for the RFS2 rule.10 The updated MOVES 

version, and all inputs and outputs that produced the results presented in Section 7.1.5 of this 

Chapter, are contained in the Tier 3 rulemaking docket. 

7.1.3.2 Fuel Inputs 

Estimating national emission inventories required translation of the reference and control 

fuel scenarios presented in Table 7-1 into a discrete set of fuels (defined by RVP, sulfur content, 

ethanol level, aromatics content, olefin content, T50 and T90), and the market share of these 

fuels, by month and county. These data were converted into “fuel supply” database tables used 

by MOVES to estimate emission inventories. Even for the state-level emission inventories 

calculated at a pre-aggregated level, these county-level fuel supply tables are retained to develop 

composite emissions that reflect the market share of the entire set of fuels that define the U.S. 

fuel pool. The crux of estimating emission impacts for the Tier 3 fuel program was the 

development of fuel supply database tables that reflected the difference between the reference 

and control scenarios, discussed in the following sections. 

In order to further simplify the final analysis, provide more consistent results for future 

efforts, and create additional data for renewable volume sensitivity, we elected to use projections 

found in the Annual Energy Outlook 2013 report1for our primary case. This report provided the 

basis for our analysis with conventional fuel volumes, as well as renewable fuel volumes and 

flex fuel vehicle usage year by year. In some years, the volume and usage differ significantly 

from the analysis found in the proposal (based on the RFS2 “mid-ethanol” full compliance case). 
7-8

Comparisons between our final analysis and the analysis completed in the proposal can be found 

in the following subsection below.

7.1.3.2.1 AEO Fuel Volume Analysis 

The Annual Energy Outlook 2013 report provided the basis for the fuel volumes used in 

this analysis. The AEO2013 report contains updated effects on fuel volumes from programs not 

included in the analysis for the proposal, most notably the latest light duty greenhouse gas 

standards2. The inclusion of that rulemaking significantly reduces the overall volume of fuel used 

as compared to the volume found in the proposal. The AEO2013 projections also show a lower 

volume of renewable fuel used, and coupled with the reduced fuel volumes, show an increasing 

fraction at which renewable fuel would have to be blended into the supply as compared to 

volumes found in the RFS2 rulemaking as well as the NPRM modeling. A comparison between 

the volumes used for the final analysis and the proposal can be found in Table 7-2, below:

Table 7-2 Comparison of NPRM Fuel Volume with FRM Fuel Volume 

(Million gallons) NPRM 2017 FRM 2018 NPRM 2030 FRM 2030

Total Fuel Volume 144.9 129.6 148.3 113.5

Ethanol Volume 21.6 15.2 30.5 14.6

E10 Volume 84.5 100.7 1.7 68.4

E15 Volume 60.0 27.5 146.6 43.4

E85 (as E74) Volume 0.4

a

1.4 0.0 1.7

a

 This small volume of E85 fuel was not modeled in the NPRM 2017 version 

The AEO2013 report shows that due to the increase in renewable fuel blending levels, 

E85 must be included in the fuel supply for the final analysis as compared to the NPRM. E85 

fueling rates were derived from the AEO2013 report on flex fuel vehicle sales and E85 fuel 

volume, and can be found in Table 7-3, below. This table describes the fraction of the gasoline 

vehicle population that is flex-fuel capable, the fraction of E85 in the overall gasoline fuel pool, 

and finally the fraction of refueling events where flex-fuel capable vehicles fill with E85 fuel.

Table 7-3 FFV Population, E85 Fuel Volume and Overall FFV E85 Usage Rates 

2018 2030

FFV Pop. % (of gasoline vehicles) 6.9% 8.1%

E85 Vol % (of gasoline fuel volume) 1.0% 1.5%

Overall E85 Usage by FFVs % 15.3% 18.9%

Updates in modeling technique have allowed us to vary ethanol blending penetration by 

region, with data provided by the AEO2013 report. These regional rates vary between 63% - 

83% for E10 penetration and 17% - 37% for E15 penetration in 2018 and between 45% - 78% 

for E10 penetration and 22% - 55% for E15 penetration in 2030. The remainder of fuel was E85, 

with no E0 included in the on-road fuel supply. The non-road/off-road fuel supply was assumed 

to be 100 percent E10. For more information regarding non-road modeling, please see Section 
7-9

7.1.4. A breakdown of ethanol penetration by region can be found in subsection 7.1.3.2.7, Table 

7-7.

7.1.3.2.2 Baseline and Reference Case 

Since the platform for air quality modeling is based on 2007, a baseline fuel supply was 

needed for that year. The regional fuel supply approach was applied using Alliance fuel survey 

data as well as the EPA refinery compliance data for the year 2007, as described in the 

subsection 7.1.3.2.4. 

Reference cases in the years 2018 and 2030 were required for the final analysis. These 

reference cases were also created following the regional fuel supply approach using Alliance fuel 

survey data as well as the EPA refinery compliance data from the years 2011 and 2012 as the 

most up-to-date surrogate for fuel properties in those years. Additionally, these fuel supplies 

were further corrected to provide consistent results region to region when compared to the 

control cases. These corrections are as follows below: 

Benzene and sulfur levels for all counties were corrected to properly reflect the 

introduction of the Control of Hazardous Air Pollutants from Mobile Sources (MSAT2) (2007) 

rule and the Tier 2 Motor Vehicle Emissions Standards and Gasoline Sulfur Control 

Requirements (1999). Benzene corrections were made by Petroleum Administration Defense 

Districts (PADD) following results from the MSAT2 analysis of downstream benzene levels. No 

other fuel property changes were found to change significantly with a change in benzene levels. 

Benzene levels by PADD follow in Table 7-4 below: 

Table 7-4 MSAT2 Downstream Fuel Benzene Levels 

PADD CG RFG

1 0.61 0.54

2 0.63 0.60

3 0.63 0.54

4 0.86 N/A

5 0.65 0.61

CA N/A 0.62

Sulfur corrections were made to all counties based on the default sulfur level found in the 

2007 baseline fuel supply. Counties with a sulfur level higher than 30 ppm were reduced to 30 

ppm to reflect the gasoline sulfur standards of the Tier 2 rule (counties subjected to lower fuel 

sulfur standards, such as in California, were not changed). Refinery modeling showed that there 

is an effect on aromatics level when sulfur is reduced. Corrections to the aromatics level based 

on refinery modeling for counties with reduced sulfur level were made as follows: 
7-10

1) A “high sulfur” aromatics level was determined using the following equation: 

Equation 7-1 Aromatics Level from Initial Sulfur Concentration 

2) A “low sulfur” aromatics level was determined using the same equation, substituting 

30ppm for the initial sulfur level of the county 

3) An aromatics delta was calculated by subtracting the “low sulfur” aromatics level from 

the “high sulfur” aromatics level 

4) This aromatics delta was applied as a correction for sulfur reduction to the original 

aromatics level for the county as appearing in the 2007 fuel supply 

Diesel fuel sulfur levels were also adjusted to 15ppm to reflect low sulfur diesel levels. 

There were no other changes to the 2018 and 2030 reference cases. For detailed fuel property 

information by region for the reference case, please refer to the subsection 7.1.3.2.7, Table 7-9. 

7.1.3.2.3 Control Case 

The Tier 3 control fuel scenarios for the years 2018 and 2030 used the fuel supplies 

constructed for the 2018 and 2030 reference cases described in the previous section as a 

foundation. To develop the control scenario fuel supplies, we modified the reference case fuel 

supplies to reflect the sulfur program in the Tier 3 control case by reducing sulfur from 30 ppm 

to 10 ppm for all gasoline. Changes in other fuel properties resulting from sulfur control were 

determined by refinery modeling and reflected in the control case, such as an increase in 

aromatics and decrease in olefins and distillation properties, as shown in Table 7-13. These 

changes were made to every county with fuel exceeding a sulfur level of 10ppm. Please note, the 

impacts to other fuel properties due to sulfur reduction are significantly lower in the final 

analysis than what was used for the proposal. Updated refinery modeling results have reduced 

the impact on these other fuel properties, which is properly reflected in the final analysis fuel 

supplies. For more information regarding refinery modeling adjustments, please refer to 

subsection 7.1.3.2.9. 

The result of this effort was two additional alternate fuel supply databases tables for use 

in MOVES, reflecting the control case fuel supplies in 2018 and 2030; these tables were used for 

the development of the final national emissions inventory as well as the inventory used for air 

quality modeling. 

7.1.3.2.4 Regional Fuel Supply 

In addition to simplifying the fuel volumes, we also made an effort to simplify the 

county-level fuel properties within the MOVES fuel supply for the final analysis. Many counties 

in the previous analysis contained unique fuel properties not associated with neighboring 
7-11

counties or pipeline locations based on fuel survey data performed in those individual counties. 

We did not feel that it was appropriate to continue this approach for the final analysis, and 

developed new fuel properties based on averages of these survey data as well as data provided to 

us at the refinery gate as part of EPA fuel compliance. We believe this average data by region 

provides a more consistent and maintainable basis for this final analysis as well as future 

analyses. Details regarding this regional fuels approach can be found in the following 

subsections, 7.1.3.2.5 – 7.1.3.2.6. 

7.1.3.2.5 Rationale for Updating MOVES Fuel Supply County Level Properties 

The fuel supplies used in the proposal analysis as well as the default version of MOVES 

are based on single-point county data on a small number of cities. Fuel survey data has tended to 

include large deviation depending on when fuel was sampled, which batch of fuel the sample 

was pulled from, which blend of fuel was being sampled, and/or when the station was refueled. 

Depending on which batch of fuel was at a station during sampling and testing, properties could 

dramatically impact the result in one city versus another. Updating this data would also result in 

potentially wide swings in assumed fuel properties for that area, when in reality the average fuel 

for that location had not changed. As a result, the single point county data are not very useful for 

creating national fuel supplies. Refer to Figure 7-1 below, for an example of deviation in fuel 

batch parameters for E200 through a one year period. Note while there is an overall trend in fuel 

property variation throughout the year, which is expected, there is also a deviation of up to 50% 

in some cases. 

Figure 7-1 Fuel Property Batch Variation Throughout One Year 

As a result, the use of this survey data city-by-city has lead to a fuel supply contained in 

the default version of MOVES, as well as the proposal analysis, that includes many variations of 

fuel properties in a non-contiguous fashion, often with little application to fuel distribution or 

overall properties. Without aggregation of the data, the fuel supply became very large, and less 
7-12

representative of our actual knowledge of fuel property variation overall. For example, the fuel 

supply used in the proposal analysis contained approximately 425 various fuel formulations, 

spread over the county in a way not representative of distribution networks, natural borders, and 

state/regional programs. Please see Figure 7-2, below, for a detailed layout of the proposal fuel 

supply: 

Figure 7-2 National Map of Unique Fuel Properties Used in Proposal 

With a new method aggregating fuel survey data, as well as incorporating refinery batchby-batch fuel compliance data, a more representative fuel supply was created for the final 

analysis. This new version of the fuel supply better accounts for fuel production and distribution 

networks, natural borders, and regional/state/local variations in fuel policy. Reducing the number 

of fuel formulations in the supply also increased our confidence that the fuels in a particular 

region represent fuel being used in that region; rather than being based on samples taken in a 

particular city or small set of cities. The new regional fuel supply method created approximately 

45 fuel formulations. Please see Figure 7-3, below, for a detailed layout of the regional fuel 

supply used in the final analysis: 

Figure 7-3 National Map of Unique Fuel Properties Using Regional Fuels Approach 
7-13

7.1.3.2.6 Fuel Regions 

There are eleven general fuel regions used in the new regional fuel supply approach. 

Table 7-5 identifies and briefly describes each region as used in the MOVES fuel supply 

database. Please see Figure 7-3, above, for an illustration of these fuel regions on a national map. 

Table 7-5 Description of Fuel Regions 

Region ID# Region Name Description

1 East Coast East coast states up to Appalachians, Florida, and gulf 

coast region

2 Midwest Midwest states up to Appalachians (not including 

Wisconsin), Tennessee, Kentucky

3 South Southern states not including gulf coast, Nebraska, 

Iowa

4 North North and South Dakota, Minnesota, Wisconsin

5 Rocky Mts Pacific northwest, Rocky mountain states, Utah

6 CA/NV/AR California, Nevada, Arizona NOT using RFG

11 East Coast RFG East coast states and regions using RFG fuel or under a 

controlled fuel program

12 MD/VA Maryland and Virginia regions using RFG fuel or 

under a controlled fuel program

13 Texas RFG Texas regions using RFG fuel or under a controlled 

fuel program

14 Midwest RFG Midwest regions using RFG fuel or under a controlled 

fuel program

15 California California using California fuel, Nevada and Arizona 

regions using California Fuel 

7.1.3.2.7 Fuel Properties by Region 

The following subsection contains tables detailing fuel properties by region for the final 

analysis 2007 baseline, 2018 and 2030 reference cases, and the 2018 and 2030 control cases. 
7-14

Fuel properties in Table 7-8, Table 7-9 and Table 7-10 below are for conventional gasoline only. 

To derive E10 and E15 properties, please refer to Table 7-6, below, for the adjustment factors 

used. 

Table 7-6 Ethanol Blending Adjustments for Conventional Gasoline Properties Within 

Fuel Regions 

ETHANOL ADJUSTMENT FACTORS (from E0 to EXX)

FUEL DESCRIPTION RVP SULF AROM OLEF BENZ E200 E300 T50 T90

E10 S E10 Summer Fuel 1.00 -2.02 -0.46 3.11 0.39 -6.34 -1.77

E10 W E10 Winter Fuel 1.00 -3.65 -2.07 4.88 0.54 -9.96 -2.45

E15 S E15 Summer Fuel -3.36 -1.64 9.24 0.91 -18.86 -4.14

E15 W E15 Winter Fuel -5.69 -3.27 11.11 1.01 -22.67 -4.59

Table 7-7 Non - Flex Fuel Ethanol Fuel Blending Levels by Region1

REGION 2018 2030

E10 E15 E10 E15

1 East Coast 0.834 0.166 0.628 0.372

2 Midwest 0.722 0.278 0.592 0.408

3 South 0.746 0.254 0.447 0.553

4 North 0.632 0.368 0.544 0.456

5 Rocky Mts 0.817 0.183 0.686 0.314

6 CA/NV/AR 0.822 0.178 0.780 0.220

11 East Coast RFG 0.834 0.166 0.628 0.372

12 MD / VA RFG 0.834 0.166 0.628 0.372

13 Texas RFG 0.746 0.254 0.447 0.553

14 Midwest RFG 0.722 0.278 0.592 0.408

15 California 0.000 1.000 0.000 1.000

1

 This table does not include the contribution of fuel blending due to flex fuel (E85) usage. For flex fuel blending 

levels, please refer to Table 7-3
7-15

Table 7-8 2007 Baseline Case Fuel Properties by Region 

REGION SUMMER WINTER

RVP SULF AROM OLEF BENZ E200 E300 T50 T90 RVP SULF AROM OLEF BENZ E200 E300 T50 T90

1 East Coast 8.70 34.66 27.60 12.78 1.004 44.06 80.22 214.9 337.6 11.31 34.27 24.68 12.71 0.915 48.52 82.52 202.4 330.8

2 Midwest 8.70 42.00 28.52 9.95 1.540 47.87 81.24 211.5 339.6 11.84 35.77 25.51 9.36 1.495 52.03 84.02 198.7 239.2

3 South 8.70 78.88 28.55 9.02 1.689 45.56 84.71 211.3 318.2 10.85 80.44 26.47 8.55 1.661 48.78 86.80 205.3 312.5

4 North 8.70 37.92 24.53 8.65 1.211 49.17 82.23 201.2 333.7 12.55 32.90 21.67 8.67 1.081 52.49 85.06 195.2 322.3

5 Rocky Mts 8.70 65.06 28.17 9.67 1.765 46.03 85.26 207.9 318.3 11.75 57.50 25.76 9.50 1.737 50.41 86.84 199.5 311.4

6 CA/NV/AR 8.70 78.88 28.55 9.02 1.689 45.56 84.71 211.3 318.2 10.85 80.44 26.47 8.55 1.661 48.78 86.80 205.3 312.5

11 East Coast RFG 6.90 33.12 21.69 11.61 0.641 50.26 84.97 196.2 322.7 11.31 33.12 21.69 11.61 0.641 55.82 87.18 184.9 312.7

12 MD / VA RFG 6.91 35.10 20.11 11.76 0.626 50.35 83.84 195.4 331.1 11.31 35.10 20.11 11.76 0.626 55.89 86.04 184.1 321.1

13 Texas RFG 6.92 30.12 16.65 11.12 0.533 50.58 85.05 196.1 329.0 10.85 30.12 16.65 11.12 0.533 55.53 87.02 186.0 320.1

14 Midwest RFG 7.06 32.12 17.13 7.85 0.774 50.98 85.24 193.2 326.7 11.84 32.12 17.13 7.85 0.774 57.00 87.63 180.9 315.8

15 California 7.06 9.00 21.98 4.44 0.530 44.52 88.81 211.0 303.0 11.84 9.00 21.98 4.44 0.530 50.54 91.20 198.5 292.0

Table 7-9 Reference Case Fuel Properties by Region 

REGION SUMMER WINTER

RVP SULF AROM OLEF BENZ E200 E300 T50 T90 RVP SULF AROM OLEF BENZ E200 E300 T50 T90

1 East Coast 8.70 30.00 22.89 13.19 0.610 45.78 80.81 208.4 339.4 10.82 30.00 21.19 12.36 0.610 50.32 83.58 199.2 326.8

2 Midwest 8.70 30.00 25.40 7.13 0.630 47.65 82.32 204.6 332.5 11.96 30.00 22.40 7.12 0.630 52.93 85.12 193.8 319.8

3 South 8.70 30.00 26.82 10.75 0.630 45.34 84.65 209.3 321.9 10.36 30.00 24.92 9.69 0.630 48.93 86.92 202.0 311.6

4 North 8.70 30.00 24.28 8.18 0.860 47.20 81.13 205.5 337.9 12.92 30.00 20.79 8.42 0.860 51.33 83.74 197.1 326.0

5 Rocky Mts 8.70 30.00 27.41 8.13 0.650 45.24 84.64 209.5 322.0 11.61 30.00 25.12 8.00 0.650 49.73 86.46 200.4 313.7

6 CA/NV/AR 8.70 30.00 26.82 10.75 0.650 45.34 84.65 209.3 321.9 10.36 30.00 24.92 9.69 0.650 48.93 86.92 202.0 311.6

11 East Coast RFG 6.90 30.00 21.69 11.61 0.540 50.26 84.97 199.3 320.5 11.31 30.00 21.69 11.61 0.540 55.82 87.18 187.9 310.4

12 MD / VA RFG 6.90 30.00 20.11 11.76 0.540 50.35 83.84 199.1 325.6 11.31 30.00 20.11 11.76 0.540 55.89 86.04 187.8 315.6

13 Texas RFG 6.90 30.00 16.65 11.12 0.540 50.58 85.05 198.6 320.1 10.85 30.00 16.65 11.12 0.540 55.53 87.02 188.5 311.2

14 Midwest RFG 6.90 30.00 17.13 7.85 0.600 50.98 85.24 197.8 319.2 11.84 30.00 17.13 7.85 0.600 57.00 87.63 185.5 308.4

15 California 6.90 9.00 21.98 4.44 0.530 44.52 88.81 211.0 303.0 11.84 9.00 21.98 4.44 0.530 50.54 91.20 198.5 292.0
7-16

Table 7-10 Control Case Fuel Properties by Region 

REGION SUMMER WINTER

RVP SULF AROM OLEF BENZ E200 E300 T50 T90 RVP SULF AROM OLEF BENZ E200 E300 T50 T90

1 East Coast 8.70 10.00 22.91 12.39 0.610 45.78 80.78 208.4 339.5 10.82 10.00 21.28 11.40 0.610 50.23 83.50 199.3 327.1

2 Midwest 8.70 10.00 25.42 7.13 0.630 47.65 82.29 204.6 332.6 11.96 10.00 22.49 6.16 0.630 52.84 85.04 194.0 320.1

3 South 8.70 10.00 26.84 10.75 0.630 45.34 84.62 209.3 322.0 10.36 10.00 25.01 8.73 0.630 48.84 86.84 202.2 312.0

4 North 8.70 10.00 24.30 8.18 0.860 47.20 81.10 205.5 338.0 12.92 10.00 20.88 7.46 0.860 51.24 83.66 197.3 326.4

5 Rocky Mts 8.70 10.00 27.43 8.13 0.650 45.24 84.61 209.5 322.1 11.61 10.00 25.21 7.04 0.650 49.64 86.38 200.6 314.0

6 CA/NV/AR 8.70 10.00 26.84 10.75 0.650 45.34 84.62 209.3 322.0 10.36 10.00 25.01 8.73 0.650 48.84 86.84 202.2 312.0

11 East Coast RFG 6.90 10.00 21.71 11.61 0.540 50.26 84.94 199.3 320.6 11.31 10.00 21.78 10.65 0.540 55.73 87.10 188.1 310.8

12 MD / VA RFG 6.90 10.00 20.13 11.76 0.540 50.35 83.81 199.1 325.7 11.31 10.00 20.20 10.80 0.540 55.80 85.96 188.0 316.0

13 Texas RFG 6.90 10.00 16.67 11.12 0.540 50.58 85.02 198.6 320.2 10.85 10.00 16.74 10.16 0.540 55.44 86.94 188.7 311.5

14 Midwest RFG 6.90 10.00 17.15 7.85 0.600 50.98 85.21 197.8 319.4 11.84 10.00 17.22 6.89 0.600 56.91 87.55 185.7 308.7

15 California 6.90 9.00 21.98 4.44 0.530 44.52 88.81 211.0 303.0 11.84 9.00 21.98 4.44 0.530 50.54 91.20 198.5 292.0

7.1.3.2.8 Boutique Fuels 

The new regional fuel supply used for the final analysis also contains fuel formulations 

for counties or regions using local fuel controls, also referred to as “boutique fuels”. These fuel 

controls are usually expressed in additional control on RVP and/or ethanol blending levels. Table 

7-11 presents the fuel property adjustments due to RVP control used in the final analysis. 

Table 7-11 RVP Adjustment Factors for Boutique Fuel Areas Within Fuel Regions 

RVP ADJUSTMENT FACTORS (per PSI)

FUEL DESCRIPTION RVP SULF AROM OLEF BENZ E200 E300 T50 T90

per PSI boutique fuel adj -1.00 -1.26 -0.50 2.57 2.27

In addition to the properties listed above, a small change in aromatics and olefins was 

found to be associated with changes to RVP in boutique fuel areas. After additional refinery 

modeling, effects to these properties were not found to be significant and were excluded from the 

analysis. 

7.1.3.2.9 Application of Refinery Modeling 

It was necessary to estimate the gasoline qualities and changes in gasoline quality to 

estimate the emissions impact of the Tier 3 program. This was conducted in two separate steps –

the first step estimated the impact of blending in more ethanol, the second step for estimating 

desulfurization on gasoline qualities. 

For estimating ethanol’s impact on gasoline qualities, it was necessary to establish a base 

case for refinery modeling, for which we chose the year 2005. However, we revised the base 

case from what actually occurred in 2005, by replacing the content of MTBE blended into 
7-17

gasoline in 2005 with 5.55 billion gallons of ethanol. Next, we established a reference case and 

the sole differences that we modeled between the 2005 revised base case and the 2030 reference 

case were the gasoline and other refinery product volumes (which change with changing 

demand), and product pricing (which changes based on forecasted changes in crude oil prices). 

Finally, we then modeled two control cases which reflect different ethanol volumes, one with 

100 percent E10 and the other with 100 percent E15.D This allowed us to estimate the impacts of 

the two different amounts of ethanol on gasoline qualities. These two ethanol control cases were 

also modeled in 2030. The changes in gasoline quality are summarized in Table 7-12. For 

estimating how ethanol affects gasoline quality, we solely used the national average change in 

gasoline qualities and applied those changes for all E10 or E15 gasoline. 

 

D

 Because E85 is blended up with the same gasoline blendstock which comprises E10 or E15, there was no need to 

estimate separate gasoline qualities for the gasoline blendstock which is used for E85. 
7-18

Table 7-12 Difference in Gasoline Qualities between the 2030 E10 and E15 Control Cases 

with the 2030 Reference Case 

2030 (E10) 2030 (E15)

Refinery 

Modeling

Refinery 

Modeling

Summer Winter Summer Winter

PADD 1 E200 6.57 4.21 PADD 1 E200 14.07 10.94

E300 1.54 0.03 E300 3.06 1.38

RVP 0.67 0.70 RVP 0.06 0.37

Aromatics -3.81 -2.70 Aromatics -6.06 -6.55

Olefins -3.55 -3.24 Olefins -5.09 -5.49

PADD 2 E200 -0.50 5.41 PADD 2 E200 4.65 11.65

E300 -0.49 1.22 E300 -0.43 0.91

RVP 0.01 -0.24 RVP -0.72 -0.65

Aromatics 0.47 -4.56 Aromatics -0.45 -4.54

Olefins 0.01 -0.46 Olefins -0.43 -0.35

PADD 3 E200 0.06 4.48 PADD 3 E200 6.13 9.89

E300 0.37 0.56 E300 0.86 0.41

RVP -0.03 -0.23 RVP -0.72 -0.57

Aromatics -1.03 -3.92 Aromatics -1.13 -4.73

Olefins 5.23 -2.09 Olefins 3.47 -3.20

PADD 

4/5

E200 5.40 7.39 PADD 

4/5

E200 7.55 13.38

E300 -2.10 0.78 E300 -5.18 1.07

RVP 0.89 -0.30 RVP 0.00 -0.58

Aromatics -3.48 -4.71 Aromatics -4.62 -7.58

Olefins -1.54 -1.17 Olefins -1.49 -1.62

US avg 

minus CA

E200 3.11 4.88 US avg 

minus CA

E200 9.24 11.11

E300 0.39 0.54 E300 0.91 1.01

RVP 0.35 0.15 RVP -0.33 -0.20

Aromatics -2.02 -3.65 Aromatics -3.36 -5.69

Olefins -0.46 -2.07 Olefins -1.64 -3.27

The second step for estimating gasoline qualities was to model the impact of 

desulfurization on gasoline qualities. The total impact of desulfurization on gasoline qualities is 

comprised of the reduction in gasoline sulfur, the associated reduction in olefins and the impacts 

of recovering the lost octane. The sulfur reduction is fixed by the standard and the olefins 

reduction is a function of the selectivity of the desulfurization technologies. We reviewed the 

information that we had obtained for the gasoline desulfurization technologies and estimated that 

desulfurizing gasoline from 30 ppm to 10 ppm would result in a 1 percent reduction in olefin 

level. Since we estimated the cost of making up lost octane using the LP refinery model, we 

used that case for estimating the impact of octane recovery on gasoline qualities. The gasoline 
7-19

qualities for the reference case and the control case that we developed reflect a 1 octane number 

loss in the FCC naphtha pool. However, we estimate that the gasoline desulfurization equipment 

that refiners will use to comply with Tier 3 will only cause about a one half octane number 

reduction in the gasoline pool, so we reduce the gasoline quality changes by half. The difference 

in gasoline qualities between the reference and control cases reflecting a one half reduction in 

octane number is summarized in Table 7-13. Because of the tendency for the LP refinery model 

to shift gasoline blendstocks around resulting in odd gasoline quality changes in individual 

PADDs, we solely used the national average change in gasoline qualities and applied those 

changes for all gasoline for the emissions analysis. 

Table 7-13 Differences in Gasoline Qualities between the Control and Reference Cases 

Change in Gasoline Quality for1/2 Octane 

Number Decrease

Summer Winter

PADD 1 E200 -0.11 -0.04

E300 -0.12 -0.09

RVP 0.00 0.00

Aromatics 0.02 0.18

Olefins 0.20 0.11

PADD 2 E200 -0.10 -0.10

E300 -0.10 -0.03

RVP 0.00 0.01

Aromatics 0.01 -0.03

Olefins 0.17 -0.01

PADD 3 E200 0.38 -0.22

E300 0.29 -0.16

RVP 0.00 0.01

Aromatics -0.02 0.11

Olefins 0.36 -0.03

PADD 4/5 E200 0.00 -0.02

E300 -0.02 -0.06

RVP 0.00 0.00

Aromatics 0.11 0.10

Olefins 0.01 0.00

US avg 

minus CA

E200 0.00 -0.09

E300 -0.03 -0.08

RVP 0.00 0.01

Aromatics 0.02 0.09

Olefins 0.20 0.04
7-20

7.1.3.3 Vehicle Program Inputs 

Modeling the controls introduced by the Tier 3 vehicle program required the development 

of a set of alternate MOVES database tables to reflect each aspect of the Tier 3 program. These 

database tables included: 

Gaseous exhaust emission rates (HC/CO/NOX) for light-duty cars, trucks, and 

light-heavy trucks (gas and diesel) to reflect the Tier 3 FTP and US06 standards 

and their phase-in.

Elemental carbon (EC) and organic carbon (OC) exhaust emission rates for lightduty cars, trucks, and light-heavy-duty trucks (gas and diesel) to reflect the Tier 3 

FTP and US06 PM standards and phase-in. 

Evaporative hydrocarbon emission rates for the permeation process to reflect the 

diurnal test standard, certification fuel, and phase-in. 

 Leak prevalence rates for tank vapor and liquid leaks to reflect requirements for 

evaporative leak detection. 

The development of these alternative inputs is discussed below by pollutant, fuel and 

vehicle regulatory class. 

7.1.3.3.1 Gasoline Light-Duty HC/CO/NOX Exhaust 

Emission rates for gaseous pollutants (HC/CO/NOx) in MOVES are contained in a 

database table (EmissionRateByAge). Rates are expressed in terms of mass per time (g/hr), 

distinguished by emission process (start and running), fuel type (gas and diesel), vehicle 

regulatory class (LDV, LDT, Light HD, etc.), model year, age, and operating mode (power/speed 

for running, engine soak time for start). Developing these rates for Tier 3 vehicles required 

accounting for expected changes in each of these dimensions. 

The development of emission rates representing implementation of the Tier 3 standards 

followed the same procedures used to develop rates for the National LEV (NLEV, covering 

model years 2001-2003) and Tier 2 standards (covering model years 2004 and later) in the 

default MOVES database, as described in the documentation for light-duty exhaust emission 

rates for MOVES2010 (known as the “MOVES Light-Duty report”).11 However, specific 

modifications were made to represent the introduction of Tier 3 standards, summarized below. 

Where no modifications to methods were made, we will refer the reader to the appropriate 

section of the MOVES2010 report. In particular, see Section 1.3.4. 

MOVES emission rates are estimated by standard level, model year, age, and vehicle 

regulatory class. There are separate rates for areas with Inspection/Maintenance programs (I/M) 

and those without. Developing the rates involves six steps, listed below. 

1. Project average Federal Test Procedure (FTP) results by standard level and vehicle 

regulatory class. As in the development of the default MOVES2010 database (outlined in the 
7-21

Light Duty Report), we made use of data measured on the FTP cycle in the course of EPA’s Inuse Verification Program (IUVP) to project emissions under the standards. For Tier 3, we 

developed estimates of FTP results for Tier 3 vehicles based on IUVP data from vehicles 

certified to Tier 2 Bin 2 and 3 standards, including cycle composites, “cold-start” emissions” 

(Bag1 minus Bag3) and “hot-running” emissions (FTP Bag 2 and US06). 

2. Develop phase-in assumptions for model years (MY) 2017 – 2031, by standard level, 

vehicle class and model year, including phase-in assumptions representing the introduction of 

Tier 3 standards. Note that for purposes of inventory modeling for the FRM, the onset of the 

Tier 3 phase-in was delayed from 2017 to 2018 for truck classes with gross vehicle weight 

ratings > 6,000 lb (LDT3 and LDT4). For LDV, LDT1 and LDT2, the phase-in begins in 2017, 

as in the inventory modeling for the NPRM. 

3. Merge FTP results and Phase-in assumptions. For running emissions, calculate 

weighted ratios of FTP and US06 emissions in each model year relative to those for cars (LDV) 

in MY2000, which represent Tier 1 LDV. 

4. Estimate Emissions by Operating Mode. Calculate emissions by operating mode in 

each model year by multiplying the MY2000 emission rates by the weighted ratio for each model 

year. We assume that the emissions control at high power (outside ranges of speed and 

acceleration covered by Bag 2 of the FTP) is not as effective as at lower power (within the range 

of speed and acceleration covered by Bag 2). 

5. Apply Deterioration to estimate emissions for three additional age groups (4-5, 6-7 

and 8-9). We assume that Tier 3 vehicles will deteriorate similarly to other vehicles, when 

viewed in logarithmic terms, but we modified deterioration to represent a useful life of 150,000 

miles, as opposed to a useful life of 120,000 miles, which was assumed for Tier 2 and NLEV 

vehicles. This is the outcome of applying ln-linear deterioration to the rates developed in steps 

1-4. For the remaining three groups (10-14, 15-19 and 20+), emissions are assumed to stabilize 

as described in the MOVES2010 report. 

6. Estimate non-I/M reference rates. The rates in steps 1-6 represent rates under a 

reference inspection/maintenance (I/M) program. Corresponding non-I/M rates are calculated by 

applying the ratios applied to the Tier 1 and pre-Tier 1rates. 

Each of these six steps is described in more detail below. Addition information is 

available in a separate memo available in the docket.12

7.1.3.3.1.1 Average FTP Results (Step 1) (Standard) 

Our projected emissions for Tier 3 vehicles are driven by the NMOG+NOX standard, set 

at 30 mg/mi. However, because MOVES models NOX and THC emissions separately, we 

apportioned the aggregate standard into NMOG and NOX components, which we will refer to as 

the “effective standards” for each pollutant. For purposes of apportionment, we assumed that 

NMOG control would pose a greater technical challenge than NOX control. Accordingly, we 

assumed “effective standards” for NMOG and NOX would be 20 mg/mi and 10 mg/mi, 

respectively. To implement this assumption, we further assumed that for NOX, vehicles would be 
7-22

effectively brought into Bin 2, and that for NMOG, vehicles would be brought to a level between 

Bin 2 and Bin 3, but closer to Bin 2. 

In addition, MOVES models start and running processes separately. It is therefore 

necessary to translate the composite standard into start and running components. One 

component represents a “cold start” on the FTP cycle, represented as “Bag1 minus Bag3” 

emissions. A second component represents “hot-running” emissions, represented by the hotrunning phase of the FTP (Bag 2). A third component represents emissions on the US06 cycle, 

representing emissions at high speed and power. 

Estimated FTP and US06 emissions levels for hydrocarbons (NMOG and NMHC) are 

shown in Table 7-14, for several Tier 2 Bins and for Tier 3. Values for all standards except Tier 

3 are identical to those used to develop rates in the default database. The values for Tier 3 are 

calculated as a weighted average of those for Bins 2 and 3, using Equation 7-2.

 .03T 775 .02B 225 3B

Equation 7-2

Table 7-14 Hydrocarbons (HC): Useful-Life FTP Standards and Associated Cold-Start 

and Hot-Running Results on the FTP and US06 Cycles. 

Bin Useful-life Standard

(mg/mi)

FTP Compositea

(mg/mi)

FTP Cold Starta

(mg)

FTP hot Runninga

(Bag 2)

(mg/mi)

US06b

(mg/mi)

8 125 41.3 591 3.56 35.8

5 90 35.5 534 2.63 35.8

4 70 24.8 383 2.28 35.8

3 55 21.5 329 1.74 35.8

2 10 5.6 87 0.42 2.6

Tier 3c20 9.2 142 0.7 10.0

a

 Values represent “non-methane organic gases” (NMOG). 

b

 Values represent “non-methane hydrocarbons” (NMHC). 

c

 Values for Tier 3 calculated using Equation 7-2. 

Under a general assumption that CO standards are not forcing, but that CO emissions 

tend to track NMOG emissions, corresponding values for CO were calculated in the same 

manner, and are presented in Table 7-15. 
7-23

Table 7-15 CO: Useful-Life FTP Standards and Associated Cold-Start and Hot-Running 

Results on the FTP and US06 Cycles. 

Bin Useful-life Standard

(mg/mi)

FTP Composite

(mg/mi)

Cold Start

(mg)

FTP hot Running

(Bag 2)

(mg/mi)

US06

(mg/mi)

8 4,200 861 6,680 451 2,895

5 4,200 606 5,510 238 2,895

4 4,200 537 5,500 201 2,895

3 2,100 463 3,470 119 2,895

2 2,100 235 1,620 70 948

Tier 3a2,100 286 2,040 81 1,390

a

 Values for Tier 3 calculated using Equation 7-2. 

Corresponding results for NOX are presented in Table 7-16. In contrast to HC and CO, 

the values for Tier 2 Bin 2 were adopted for Tier 3, as the FTP composite of 5.5 mg/mi suggests 

that Bin 2 vehicles can meet the “effective standard” of 10 mg/mi with a reasonable compliance 

margin. 

Table 7-16 NOX: Useful-Life FTP Standards and Associated Cold-Start and Hot-Running 

Results on the FTP and US06 Cycles. 

Bin Useful-life Standard

(mg/mi)

FTP Composite

(mg/mi)

Cold Start

(mg)

FTP hot Running

(Bag 2)

(mg/mi)

US06

(mg/mi)

8 200 64.2 418 35.1 61.3

5 70 21.2 165 8.2 45.9

4 40 8.7 90 4.7 30.6

3 30 5.7 71 3.8 30.6

2 20 5.5 67 0.4 18.4

Tier 3 10 5.5 67 0.4 18.4

7.1.3.3.1.2 Develop Phase-In Assumptions (Step 2) 

We designed phase-in assumptions so as to project compliance with the Tier 3 fleet 

average NMOG+NOX requirements. The requirements are illustrated in Figure 7-4. The phasein begins in model year 2017 and ends in model year 2025. Note the sharp drop in emissions at 

the outset of the Tier 3 phase-in, also that the truck standards (LDT2,3,4) are slightly higher than 

the lighter vehicles’ (LDV-T1). After 2017, the reduction in the fleet average is linear. The fleet 

averages for cars and trucks no longer differ at the completion of the phase-in. 
7-24

0.000

0.020

0.040

0.060

0.080

0.100

0.120

0.140

0.160

0.180

201520162017201820192020202120222023202420252026

FTP Composite Standard (g/mi)

Model Year

LDV/LDT1

LDT234

Figure 7-4 NMOG+NOX FTP Fleet Average Requirements during Phase-In of the Tier 3 

Exhaust Emissions Standards for Light-Duty Vehicles. 

7.1.3.3.1.3 Merge Cycle Results and Phase-In Assumptions (Step 3) 

The goal of this step is to calculate weighted averages of the FTP (cold-start and hotrunning) results for all standards in each model year, with the emissions results weighted by 

applicable phase-in fractions. We do this step for each vehicle class separately, then weight the 

four truck classes together using a set of fractions also derived from the weighted sales estimates. 

Start and running emissions in each model year are simply calculated as weighted 

averages of the emissions estimates and the phase-in fractions. The resulting weighted start 

estimates are used directly to represent cold-start emissions for young vehicles in each model 

year (ages 0-3). For running emissions, however, the averages are not used directly; rather, each 

is expressed as a ratio to the corresponding Tier 1 value. 

7.1.3.3.1.4 Estimate Emissions by Operating Mode (Step 4) 

To project emissions for the 2016-and-later vehicles, we divided the operating modes for 

running exhaust into two groups. These groups represent the ranges of speed and power covered 

by the hot-running phase (Bag 2) of the FTP cycle (< ~20 kW/Mg), and the ranges covered by 

the SFTP standards (primarily the US06 cycle). For convenience, we refer to these two regions 

as “the hot-running FTP region” and “US06 region,” respectively (See Figure 7-5). 

To estimate emissions by operating mode, the approach was to multiply the emission 

rates for MY 2000, representing Tier 1, by a specific ratio for each model year from 2017 to 

2025, to represent emissions for that model year. 

To estimate rates for the US06 modes, we followed a procedure similar to that for the 

“FTP” modes, but using the “US06” columns in Table 7-14 through Table 7-16. For HC and 

CO, we used Equation 7-2, as before. For NOX, we applied the Bin-2 values. Figure 7-6 and 
7-25

Figure 7-7 show application of the ratios to the FTP and US06 operating modes in model years 

2010, 2017, and 2025, representing fully phased-in Tier 2 standards, an interim year during the 

Tier 3 phase–in, and the fully phased-in Tier 3 standards, respectively. Figure 7-6 displays the 

information on linear scale, highlighting the differences at the higher operating modes, while 

Figure 7-7 shows the same information on a logarithmic scale, illustrating the patterns for the 

lower operating modes. 

 

Figure 7-5 Operating modes for running Exhaust Emissions, divided broadly into “hotrunning FTP” and “US06” regions. 
7-26

0

100

200

300

400

500

600

700

800

900

1,000

-5 0 5 10 15 20 25 30 35 40

Emission Rate (g/hr)

Vehicle Specific Power (kW/Mg)

2010

2017

2025

0

1

2

3

4

5

6

7

-5 0 5 10 15 20 25 30 35 40

Emission Rate (g/hr)

Vehicle Specific Power (kW/Mg)

2010

2017

2025

0

2

4

6

8

10

12

14

16

18

-5 0 5 10 15 20 25 30 35 40

Emission Rate (g/hr)

Vehicle Specific Power (kW/Mg)

2010

2017

2025

(b) THC

(c) NOx

(a) CO

Figure 7-6 Projected Emission Rates for Cars in Operating modes 21-30, vs. VSP, in 

ageGroup 0-3 years, for three model years, for (a) CO, (b) THC and (c) NOX (LINEAR 

SCALE). 
7-27

opMode

21

22

23

24

25

27

28

29

30

0.01

0.10

1.00

10.00

100.00

-10 0 10 20 30 40

Emission Rate (g/hr)

Vehicle Specific Power (kW/Mg)

2000

2010

2017

2025

0.001

0.010

0.100

1.000

10.000

100.000

1,000.000

-5 0 5 10 15 20 25 30 35 40

Emission Rate (g/hr)

Vehicle Specific Power (kW/Mg)

2000

2010

2017

2025

(c) NOx

1

10

100

1,000

10,000

-10 0 10 20 30 40

Emission Rate (g/hr)

Vehicle Specific Power (kW/Mg)

2000

2010

2017

2025

(a) CO

(b) THC

Figure 7-7 Projected Emission Rates for Cars in Operating modes 21-30, vs. VSP, in 

ageGroup 0-3 years, for Four Model Years, for (a) CO, (b) THC and (c) NOX

(LOGARITHMIC SCALE). 
7-28

7.1.3.3.1.5 Apply Deterioration (Step 5) 

Based on our extensive emissions analysis during MOVES2010 development, we 

assumed that deterioration for different technologies was best represented by a multiplicative 

model, in which different technologies, represented by successive model-year groups, showed

similar deterioration in relative terms but markedly different deterioration in absolute terms. We 

implemented this approach by translating emissions for the 0-3 age group, as calculated above, 

into natural logarithms and applying uniform logarithmic age trends to all model-year groups. 

We derived logarithmic deterioration slopes for Tier 1 vehicles (MY 1996-98) and applied them 

to Tier 2 vehicles. In this process we applied the same logarithmic slope to each operating mode, 

which is an extension of the multiplicative deterioration assumption. 

For vehicles manufactured after the onset of the Tier 3 phase-in, the deterioration 

assumptions were modified to represent an extension of the full useful life (FUL) from 120,000 

mi to 150,000 mi. Thus, the inventory modeling assumes a standard of 30 mg/mi NMOG+NOx 

and a 150,000 mi useful life. However, under the final rule, manufacturers will retain the option 

of certifying some engine test groups to a somewhat lower standard with a 120,000 mi useful 

life. Over the useful life of vehicles, we assume that the two options (higher standard with longer 

useful life, lower standard with shorter useful life) will yield approximately equivalent 

deterioration trends. Therefore, no attempt was made to represent both options in the inventory 

modeling. 

Note that we did not extrapolate the logarithmic deterioration trend beyond the 8-9 year 

age group, as we know that emissions tend to stabilize beyond this age, while the ln-linear 

emissions model would project an increasingly steep and unrealistic exponential emissions trend. 

For the 10-14, 15-19 and 20+ age groups, the “stabilization of emissions with age” was estimated 

as for MOVES2010 (MOVES Light Duty report, section 1.3.3.7). 

7.1.3.3.1.6 Estimate Non-I/M References (Step 6) 

Completion of the preceding steps provided a set of rates representing I/M reference rates 

for MY 2016-2025. As a final step, we estimated non-I/M reference rates by applying the same 

ratios used in MOVES2010 (section 1.3.3.6).

7.1.3.3.1.7 Start Emissions 

The values for “Cold Start” shown in Tables 8-4 through 6 above were used to represent 

cold-start emissions for the various standard levels. These are designated as opModeID=108 in 

the emissionRateByAge table; emission rates for starts following shorter soak periods were 

developed by applying standard soak curves (found in the MOVES Light Duty report) to the 

updated cold start rates. Deterioration was applied to start emissions, using the same approach as 

used for developing MOVES2010 base rates discussed in the MOVES Light Duty report. Start 

deterioration is expressed relative to deterioration for running emissions. 
7-29

7.1.3.3.1.8 Final Estimates of Composite FTP and US06 

In producing emission inventory estimates, MOVES combines emission rates with 

activity patterns derived from surveys of in-use vehicles. These emissions do not necessarily 

correlate directly with the test procedures used for compliance; for example, in-use activity 

shows that more miles are driven per start event than assumed on the FTP. Likewise, the US06 

cycle is focused on compliance, and represents a relatively small portion of in-use driving. 

However, to give a relative sense of the changes projected by the Tier 3 standards, emissions can 

be constructed for FTP composite and US06 from MOVES emission rates for the Tier 2 (labeled 

as MY2010) and Tier 3 (labeled as MY 2025) cases. These are shown in Figures 7-5 through 7-

8 below. Note that the Tier 3 rates shown below are for the MOVES base fuel of 30 ppm. In 

modeling the control scenarios on 10 ppm, these emission rates were further lowered by the 

sulfur reductions outlined in Section 7.1.3.4.1. 

Figure 7-8 FTP Composite NOX emissions for reference (2010) and Tier 3 (2025) 

constructed from MOVES rates 
7-30

Figure 7-6 FTP Composite THC emissions constructed from MOVES rates 

Figure 7-7 US06 NOX emissions constructed from MOVES rates 
7-31

Figure 7-8 US06 THC emissions constructed from MOVES rates 

7.1.3.3.2 Diesel LD HC/CO/NOX Exhaust 

Emission rates representing light-duty diesel vehicles under Tier 3 standards were 

calculated identically to those representing gasoline vehicles, with the exception that the 

“effective standards” were set differently. Again, diesel vehicles are projected to meet the same 

NMOG+NOX standard as gasoline vehicles (30 mg/mi). However, for diesel vehicles, we 

assumed that light-duty vehicles would meet Bin-2 standards following completion of the phase 

in. Accordingly, the “effective standards” for NMOG and NOX were set at 10 and 20 mg/mi, 

respectively. As mentioned, all remaining steps were conducted as described in Section 7.1.3.3.1 

above. As a result of the different effective standards, however, the ratios and other numeric 

results specific to diesel vehicles vary slightly from their counterparts for gasoline vehicles. 

7.1.3.3.3 Gasoline Medium-duty HC/CO/NOX

The Tier 3 program will affect not only light-duty vehicles (below 8,500 pounds 

GVWR), but also chassis-certified vehicles between 8,500 and 14,000 pounds GVWR. This 

class of vehicles is referred to “light-heavy-duty” or “medium-duty” vehicles. In MOVES, these 

vehicles are designated as regulatory class 41. This regulatory class comprises several types of 

vehicles, including engine-certified trucks, Class 2b and Class 3 heavy trucks, and medium-duty 

passenger vehicles (MDPV), which are not regulated under the medium-duty standards 

considered here. As described in the reference-case medium-duty updates to MOVES,13 we 

assumed that during this timeframe, engine-certified vehicles and medium-duty passenger 

vehicles (MDPV) comprise five percent and fifteen percent of the regulatory class, respectively, 

with the remainder composed of Class 2b and 3 trucks. 
7-32

Table 7-17 Population Percentage 

Category Fraction of RegClass 41

(%)

Engine-certified 5.0

MDPV 15

Class 2b 60

Class 3 20

The Class 2b and Class 3 vehicle program was modeled to begin in model year 2018 and 

fully phase in during the 2022 model year (Figure 7-9). This projection yields an aggregate 

standard of 0.178 g/mile NMOG+NOX for Class 2b vehicles and 0.247 gram/mile for Class 3 

vehicles in 2022. 

Figure 7-9 Class 2B and 3 Standard Phase-in

To represent mean emissions on the FTP for this regulatory class, we combined the Tier 3 

phase-in for Class 2b and 3 vehicles with the existing emission standards for MDPV and enginecertified vehicles that comprise MOVES regulatory class 41. For this analysis, we assumed that 

MDPVs met the Tier 3 SULEV 30 standard, and that engine certified vehicles would perform at 

1.2 times their standard on the chassis FTP.14

 Calculated using the fractions in Table 7-17, the 

weighted average of the Class 2b, Class 3, MDPV, and engine standards is 0.181 for model year 

2022. 

To account for the real-world performance of these vehicles, we related this average to 

that for Tier 2 light-duty vehicles, for which we have a substantial volume of data from EPA’s 

in-use verification program. Using the same approaches used for developing the Tier 2 and Tier 

3 light duty emission rates (see Section 7.1.3.3.1), we modeled MOVES Regulatory Class 41 in 
7-33

2022 as 90 percent Bin 5 and 10 percent Bin 8 vehicles.E For the phase-in years 2017-2021, we 

calculated interim emission rates for each year as a weighted average of the Tier 3 rates and the 

existing MOVES rates for regulatory class 41 (in MY 2016), such that the appropriate weighted 

composite was calculated each year as shown in Table 7-18. 

Table 7-18 Phase-in of MD Tier 3 Rates 

Model Year Tier 3 Rate Current Rate 

(MY2016)

Composite Standard 

(g/mile)

2017 34% 66% 0.33

2018 49% 51% 0.29

2019 62% 38% 0.26

2020 75% 25% 0.24

2021 87% 13% 0.21

2022 100% 0% 0.18

The CO standards for MD vehicles are less stringent than those for Tier 2 Bin 5 and Bin 8 

vehicles. For Bin 5 and Bin 8 vehicles, the CO standard is 4.2 g/mile. For engine certified 

vehicles, the standard is approximately 17.3 grams per mile (14.4 g/hp-hr multiplied by 1.2), 15

and for the Tier 3 MD vehicles, the standard ranges from 4.2 to 7.3 g/mile. Using the same 

phase-in fractions as for NMOG+NOx, we calculated an aggregate CO standard of 4.4 

grams/mile in 2022, which is 5.5 percent higher than the Tier 2 Bin 5/8 standards. To 

compensate for the lower CO emissions in the Tier 2 vehicles that were used to develop the Tier 

3 MD emission rates, we multiplied the running CO rates by 1.1 and the start CO rates by 1.05. 

As for light-duty vehicles, deterioration was modeled to represent a 150,000 mile useful 

life. The same methodology was used for light-duty and medium-duty vehicles. 

7.1.3.3.4 Diesel Medium-Duty HC/CO/NOX 

For medium-duty (MD) diesel vehicles, the emission rates currently in MOVES imply 

levels on the FTP substantially below the Tier 3 HC and CO standards. When MOVES is used 

to generate a simulated FTP estimate for NMHC, the model calculates a rate of approximately 

0.05 grams per mile, while the simulated FTP estimate for CO is less than 1 gram/mile. 

Consequently, we assumed no HC and CO emission benefits from Tier 3 standards on MD diesel 

vehicles. 

By contrast, we estimate that the Tier 3 NOX standard will produce a reduction in diesel 

Class 2b and Class 3 NOX emissions. Because data on current NOX emissions are limited, as 

there is little in-use data on MY 2010 and 2011 vehicles which use selective catalytic reduction 

as a NOX control strategy, we used a proportional approach to estimate the Tier 3 effect, 

reducing NOX in proportion to the change in the emission standard. Because emission standards 

 

E

 By basing the data on light duty vehicles, it is possible that we are misstating the emission profile of these larger 

vehicles, but as emissions decrease, it is also possible that the emission profile for the larger vehicles will more 

closely resemble that of light duty vehicles. 
7-34

tend to impact start and running emissions differently, we applied a greater portion of the 

reduction to running emissions and a smaller reduction to start emissions. These reductions were 

phased-in over the same schedule as for gasoline vehicles, as detailed in Table 7-19. Also, to 

account for the change in “useful life”, we duplicated the Tier 3 age 0-3 NOX rates to the 4-5 

year age-group. 

Table 7-19 Phase-in of MD Diesel Tier 3 NOX Rates 

Model Year Tier 3 Phase In

Reduction in NOX

Running Emission 

Rate

Reduction in NOX

Start Emission Rate

2017 20% 12% 5%

2018 38% 23% 9%

2019 54% 33% 12%

2020 69% 42% 16%

2021 85% 52% 19%

2022 100% 61% 23%

7.1.3.3.5 Gasoline Particulate Matter (PM 2.5) 

Tier 3 will introduce standards for emissions of primary particulate matter (PM) for lightduty vehicles. For the Federal Test Procedure (FTP), a full-useful life (FUL) standard of 3.0 

mg/mi will apply. Additionally, for the US06, a standard of 10.0 mg/mi during the PM phase-in 

and a final standard of 6.0 mg/mileF will apply to vehicles with GVWR up to 8,500 lbs, as well 

as medium-duty passenger vehicles (MDPV). Additionally, the full useful life (FUL) for most 

vehicles will be increased from 120,000 to 150,000 miles under the Tier 3 rule. These standards 

are targeting several processes that contribute to particulate matter in light-duty gasoline 

vehicles: cold starts, high-power and high load operation, and deterioration of engine and 

emission control technology over the life of the vehicle. 

As mentioned in the preamble, most current new light-duty vehicles are effectively in 

compliance with the 3.0 mg/mile standard (Section 1.5.1.1). The MOVES model includes strong 

deterioration of light-duty gasoline emissions based on data collected in the Kansas City Vehicle 

Emissions Study16, which causes predictions of fleet-average Tier 2 light-duty gasoline vehicles 

to exceed the proposed 3 mg/mile standard after only 3-4 years of operation. We anticipate that 

the Tier 3 PM standards will force continual improvement on fleet-wide PM emissions in several 

ways. First, the rule will require reductions in emissions from the light-duty vehicles that 

currently exceed the Tier 3 standard. Second, we expect that vehicle manufacturers will decrease 

PM emissions in order to increase their compliance margin, which will help vehicles meet the 

increased durability requirements for those test groups certified to the extended useful life of 

150,000 miles. Third, we expect that manufacturers will lower US06 PM emissions in a similar 

fashion in order to meet the respective standards. And finally, the Tier 3 standards will prevent 

 

F

 The US06 PM standard will be 10 mg/mi starting and MY 2017 through MY 2021. After MY 2021, the US06 PM 

standard will drop to 6 mg/mi. 
7-35

the backsliding of PM emissions from new vehicles with new technologies. The technologies 

and techniques that manufacturers require to meet these standards are described in Chapter 1 of 

this RIA. 

To reflect the above projections, the emission rates in MOVES were modified in the 

following ways. The light-duty PM2.5emission rates were reduced such that future vehicles 

(when new) will meet the Tier 3 standards with a compliance margin of approximately 50 

percent. MOVES estimates that current vehicles, within the first 3 years of use, emit PM2.5 on 

the FTP at 2.72 mg/mile (cars), and 3.08 mg/mile (light trucks). To achieve a 50 percent 

compliance margin with the fully-phased in Tier 3 rule, we estimated a reduction of 50 percent to 

the Tier 3 standards. The reductions are applied: 

Uniformly to cars and trucks, 

Uniformly across start and running processes, 

Uniformly across all operating modes (including the ones that cover US06 type 

driving) 

The reductions in the PM2.5 emissions over the model years reflect the phase-in of the Tier 3 

PM2.5 standards. The phase-in begins in 2017 for cars, and in 2018 for light trucks. By 2021, the 

emission rates (described above) are fully phased-in for light-duty vehicles. Table 7-20 includes 

the estimated FTP and US06 PM2.5 for new (undeteriorated) vehicles, by model year. As shown 

in the table, the reductions in PM2.5 yield compliance margins of more than 45 percent for both 

the FTP and US06 standards. 
7-36

Table 7-20 Trends in PM2.5 Emissions on the FTP and US06 Cycles, by Model Year, 

Reflecting the Phase-in of the Tier 3 Standards 

Model 

Year Tier 3 phase-in FTP (mg/mile) US06 (mg/mile)

Car Truck Car Truck Car Truck

2011 0% 0% 2.72 3.08 2.94 4.85

2012 0% 0% 2.72 3.08 2.94 4.85

2013 0% 0% 2.72 3.08 2.94 4.85

2014 0% 0% 2.72 3.08 2.94 4.85

2015 0% 0% 2.72 3.08 2.94 4.85

2016 0% 0% 2.72 3.08 2.94 4.85

2017 10% 0% 2.59 3.08 2.79 4.85

2018 20% 20% 2.45 2.77 2.64 4.36

2019 40% 40% 2.18 2.46 2.35 3.88

2020 70% 70% 1.77 2.00 1.91 3.15

2021 100% 100% 1.36 1.54 1.47 2.42

2022 100% 100% 1.36 1.54 1.47 2.42

2023 100% 100% 1.36 1.54 1.47 2.42

2024 100% 100% 1.36 1.54 1.47 2.42

2025 100% 100% 1.36 1.54 1.47 2.42

PM2.5 emissions of the vehicle fleet deteriorate with age, due to wear and failure of 

engine and emission control systems on some vehicles. The deterioration of the fleet-average 

PM2.5 emission rates increase logarithmically with age as documented in the MOVES report10.

The emissions trend reflecting the durability associated with a FUL of 120,000 mi is shown in 

Figure 7-10. The deterioration is applied multiplicatively to rates for “young” vehicles in the 0-3 

yr ageGroup. 

For vehicles manufactured after the onset of the Tier 3, the deterioration assumptions 

were modified to represent an extension of the full useful life (FUL) from 120,000 mi to 150,000 

mi. To model this assumption, we adjusted the deterioration trend such that emissions levels 

were shifted to a point in age (or miles) that is 25% later (the value of 1.25 was calculated as the 

ratio of the extended FUL to the previous FUL, or 150/120). For example, under the 120K 

assumption, the fleet-average PM2.5 emission rate reaches 10 mg/mile after 14 years. Under the 

150K scenario, the fleet-average PM2.5 emission rate does not reach 10 mg/mile until after 

14*1.25 = 17.5 years. 

Thus, the inventory modeling assumes a standard of 3.0 mg/mi and a 150,000 mi useful 

life. However, under the final rule, manufacturers will retain the option of certifying some engine 

test groups to a somewhat lower standard with a 120,000 mi useful life. Over the useful life of 

vehicles, we assume that the two options (higher standard with longer useful life, lower standard 

with shorter useful life) will yield approximately equivalent emissions trends over the life of the 

vehicles. Therefore, no attempt was made to represent both options in the inventory modeling. 
7-37

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00

9.00

0 5 10 15 20 25

FTP Composite (mg/mi)

Vehicle Age (years)

150K mi FUL

120K mi FUL 

Figure 7-10 Deterioration Trends for PM2.5, for Full Useful Lives of 120,000 and 150,000 

miles 

 The discussion to this point has concerned total particulate (PM2.5). It is important to note 

that the rates stored in the emissionRateByAge table in MOVES do not represent PM2.5 but 

rather organic and elemental carbon components, OC2.5 and EC2.5, respectively. In the table, 

these components are identified as pollutantID = 111 and 112 respectively. Starting with OC and 

EC rates in the default database for MY 2016, the reductions described in Table 7-20 are applied 

equally to OC and EC rates to generate corresponding rates under the Tier 3 standards. 

7.1.3.3.6 Diesel PM 

The Tier 3 controls were modeled as having no impact on light-duty diesel PM 

emissions. Although light-duty diesels are subject to the same Tier 3 PM standards as light-duty 

gasoline vehicles, all light-duty diesels are equipped with diesel particulate filters (DPF). The 

application of a DPF results in diesel PM emissions being very close to the cleanest gasoline 

vehicles in operation today. As a result the application of the Tier 3 PM standards to diesel 

vehicles will not result in a change in diesel PM emissions. 

7.1.3.3.7 Evaporative Emissions 

The Tier 3 evaporative program requires lower emissions on the hot soak plus diurnal test 

procedure on 9 RVP E10 certification fuel and strengthens in-use performance through a new 

leak standard and OBD requirements for detection of vapor leaks. The new standards are 

projected to result in significant reductions in evaporative hydrocarbon emissions. For this 

analysis, tighter evaporative emission standards in conjunction with 9 RVP E10 certification fuel 

are expected to reduce evaporative permeation emissions and fuel system venting, since the Tier 

3 evaporative emission standards are aimed at not allowing any vented vapor emissions during 
7-38

the test. Moreover, the new requirements addressing leaks are expected to reduce the prevalence 

(frequency rate) of fuel system vapor and liquid leaks.G The discussion below focuses on 

reducing evaporative emissions by improving the permeation resistance of fuel tanks and vapor 

lines and improved fuel system designs to reduce leaks. However, as mentioned above, and 

discussed in Chapter 1, there are a variety of technologies manufacturers could use to achieve the 

required reductions (including those which address vapor venting, permeation and leaks) and 

manufacturers are likely to use the technologies they expect to get the largest reductions for the 

lowest cost whether they be from reductions in fuel venting emissions, permeation, or leaks. 

Furthermore, some technologies will be effective in achieving emission reductions against more 

than one standard. For example, the canister honeycomb will help to meet the canister bleed and 

Tier 3 hot soak plus diurnal standards and any measure to reduce leaks will help to meet the leak 

standard and the hot soak plus diurnal standard. The technology choice is up to the manufacturer, 

but we expect that the technologies used will to varying degrees address all three basic emission 

types. 

7.1.3.3.7.1 Permeation Improvements 

Permeation emissions include fuel vapors that escape from a vehicle through micro pores 

in the various fuel system components and materials. Tier 3 will reduce the allowable emissions 

from this process. Light duty vehicles will see a reduction of about 50 percent from Tier 2 levels. 

The Tier 2 permeation rate in MOVES is 0.0102 g/hour on E0 fuel. Analysis of the 

impact of ethanol on permeation emissions conducted as part of the RFS2 final rule, and 

included in MOVES2010, suggests that the use of E10 as Tier 3 certification test fuel will 

effectively double permeation emissions over the test procedure. Therefore, the combination of 

lowering the vehicle standard and certifying on a fuel with higher propensity to permeate must 

be accounted for in Tier 3 permeation rates. 

The Tier 3 emission rate in MOVES is developed by estimating permeation emissions 

over one day of diurnal activity (65F-105F) on an ethanol-containing fuel and applying 

reductions in the base rate over time. The total permeation emissions for the day should equal 

about 75 percent of the standard (~0.225g) as the other 25 percent of the standard can be 

attributed to the Hot Soak portion of the certification test. The result is a Tier 3 permeation rate 

of 0.0026g/hour (a 75 percent reduction from the Tier 2 rate). 

 

G

 One of the updates to MOVES for this analysis was to enable direct input of the leak prevalence rates. 
7-39

Table 7-21 Tier 3 Permeation Rates 

Model Year Tier 3 

Phase-in

Permeation 

(g/hr)

Tier 2 0% 0.0102

2016_2017 40% 0.0072

2018_2019 60% 0.0056

2020_2021 80% 0.0041

2022 100% 0.0026

7.1.3.3.7.2 Reduced frequency of vapor leaks 

EPA, in conjunction with the state of Colorado and the Coordinating Research Council, 

undertook multiple research programs to help quantify the prevalence of evaporative system 

leaks in the real world, and the emissions they cause.17,18,19

 The evaporative leak provisions 

grew from this work, informing the emission inventory contribution of evaporative leaks, and the 

level of reductions possible from an in-use program focused on reducing the incidence of these 

leaks. To establish the reference case, the frequency of evaporative system leaks were estimated 

from the prevalence of high evaporative emission vehicles in the Colorado field study. 

The impact of the Tier 3 evaporative emissions standards are quantified from MOVES, 

which has been updated based on the new data collected. We expect that emissions reductions 

will come from the reduction in the incidence rate of vapor leaks. 

The vapor leak frequency estimates are generated from the high evaporative emissions 

field study in Colorado during the summer of 2009.17 In that study, it was found that, compared 

to the 1981-1995 model years pre-enhanced evaporative emissions vehicles, the vapor leak 

frequency dropped significantly with the onset of the enhanced evaporative emissions standards 

in 1996. The new standards did not explicitly require the measurement of vapor leaks through 

OBD leak detection, but the standards encouraged changes in the materials and connections in 

the fuel systems resulting in approximately 70 percent less vapor leaks. The upgraded materials 

and connections for the following Tier 2 standards are estimated to have reduced vapor leak rates 

another 33 percent. 

We expect that manufacturers will again respond to the Tier 3 standards by making 

further improvements, such as changes in materials and connections in order to reduce the 

amount of fuel permeation and vapor leaks and will address canister bleed emissions. These 

changes plus design enhancements (see Chapter 1, Section 1.6.1 “Tier 3 Evaporative 

Emissions/Leak Control Technology Approaches” for more details) can be expected to further 

reduce the amount of vapor leaks by one third, similar to the effect of Tier 2. 

Tier 3 also includes provisions for an in-use measurement program that will explicitly 

detect the remaining vapor leaks. The in-use leak standard will be enforced in the In-Use Vehicle 

Program (IUVP) at different points in the vehicle’s useful life. Tier 3 also imposes more 

stringent requirements for evaporative on-board diagnostics (OBD) including a change in the 

vapor leak check from a 0.040” equivalent diameter orifice in the current federal leak detection 
7-40

requirement to 0.020”, as well as other more stringent readiness requirements which are already 

in place for implementation in the State of California. 

The analysis from the high evaporative emission field studies in Colorado (2008-2010) 

found that evaporative OBD was only 30-50 percent effective in detecting vapor leaks.20 The 

improvements to evaporative OBD in the Tier 3 rule are estimated to increase OBD vapor leak 

detection to 80 percent effectiveness. 

Based on the analysis as described above, the leak standard is therefore estimated to 

result in an additional one third less evaporative vapor leaks. The prediction of an overall two 

thirds reduction in vapor leaks is not unreasonable, considering the observed impact of the 1996 

enhanced evap rule. Modeling details can be found in a separate memo to the docket.21

The leak prevalence rates in MOVES utilize observations that the State of Colorado 

found in a follow-up study in 2010. Leaking vehicles were recruited in the Denver area to the 

Colorado Tech Center and Laboratory to determine pre and post repair emissions. In this study 

they found that approximately 70 percent of the evaporative leaks detected were due to the 

deterioration of the evaporative and/or fuel system e.g. problems like corroded fuel lines, filler 

neck, cracked hoses, etc. that could be repaired or improved with design and materials. The other 

30 percent were due to issues beyond the manufacturers’ control, such as improper maintenance 

or missing gas caps. 

Figure 7-10 Vapor Leak Control Assumed for 100 Leaking Vehicles 

The Reference case in Figure 7-10 assumes 40 percent OBD effectiveness with 95 

percent OBD readiness, resulting in 38 out of 100 MILs due to leaks turned on (the red portion 

of first bar in above figure). This 40 percent OBD effectiveness is based on the analysis 

comparing the evaporative system leak OBD DTCs to the portable SHED hot soak emissions in 

the high evaporative emissions field studies in Denver (2008-2010), 30-50 percent of the time. 

For the LEV III case (the overall nationwide situation without Tier 3), it is assumed that 33 

percent (the one third discussed as Tier 3 permeation benefit, similar to Tier 2 benefit) of 70 

Reference
7-41

percent (≈23 percent) are prevented with the reduction in SHED test standard (white portion of 

middle). It is assumed that 80 percent of the remaining leaks will have a light on (red portion in 

middle bar). The blue portion of the middle bar is the leaks remaining undetected in the LEV III 

case. 

Based on Tier 3 control, we assume 66 percent or two thirds (one third for Tier 3 

permeation benefit in previous paragraph plus one third discussed earlier as leak standard 

benefit, equals two thirds emissions benefit for Tier 3) of the 70 percent durability related leaks 

(≈46 percent) are prevented (white portion in third bar).The modeling then assumes that 80 

percent of the remaining leaks will have an evaporative system leak OBD light on as in the LEV 

III case (the red portion of the third bar). The remaining without lights is 11 out of 100, in the 

blue portion of the third bar in the figure above. 

7.1.3.3.7.3 Reduced frequency of liquid leaks 

Similar to vapor leaks, we expect a reduction in the occurrence of liquid leaks due to 

improved system design and integrity. We believe that remaining liquid leaks occurring in 

advanced evaporative systems will be primarily caused by tampering and mal-maintenance. 

Therefore we have reduced the frequency rate for leaks for vehicles less than 15 years of age, 

and expect vehicles older than 15 to have the same rate of leak occurrence as current 

technologies. 

Table 7-22 Reductions of Liquid Leaks in Tier 3

Age Operating Hot Soak Cold Soak

0-9 45% 45% 45%

10-14 30% 30% 30%

15-19 0% 0% 0%

20+ 0% 0% 0%

7.1.3.4 Updates to MOVES Sulfur Effects 

In order to evaluate the emission impacts of the sulfur standards, the version of MOVES 

used for this analysis made significant updates to the effect of fuel sulfur levels below 30 ppm on 

exhaust emissions. In MOVES2010b, these effects were based on extrapolation of data on sulfur 

levels above 30 ppm.22

 The updates made for this analysis were based on significant new data 

generated from EPA research conducted in 2010-11, summarized below. A final report on this 

research is available in the docket.23

7.1.3.4.1 EPA Testing of Gasoline Sulfur Effects on Tier 2 Vehicles and the In-Use 

Fleet 

Fuel sulfur content has long been understood to affect the performance of emission 

aftertreatment catalysts in light duty vehicles, where the sulfur and/or its oxides adsorb to the 

active precious metal sites, reducing the catalyst’s efficiency in destroying harmful pollutants. 
7-42

This can severely impair the effectiveness of the catalyst to convert the products of combustion, 

leading to increases in these emissions relative to a “clean” catalyst. The quantity of sulfur 

present on the catalyst at any given time is a function of its temperature and the fuel sulfur level, 

with elevated catalyst temperatures and lower fuel sulfur concentration both reducing sulfur 

loading. Numerous studies have shown the direct impact of fuel sulfur levels above 30 ppm on 

emissions; these formed the basis of the Tier 2 rulemaking, which considered the impact of 

sulfur in terms of immediate impact, and irreversible impact due to permanent catalyst damage.24

With the advent of the Tier 2 sulfur standards, new research has focused on the emission 

reduction potential of lowering sulfur levels below 30 ppm, particularly on Tier 2 technology 

vehicles, under the hypothesis that increased reliance on the catalytic convertor would result in a 

higher sensitivity to sulfur accumulation. A study conducted by EPA and the auto industry on 

nine Tier 2 vehicles in support of the Mobile Source Air Toxics (MSAT) rule, found significant 

reductions in NOX, CO and total HC when the vehicles were tested on low sulfur fuel, relative to 

32 ppm fuel.25 In particular, the study found a nearly 50 percent increase in NOX when sulfur 

was increased from 6 ppm to 32 ppm. Given the preparatory procedures related to catalyst 

clean-out and loading used by these studies, these results may represent a “best case” scenario 

relative to what will be expected under more typical driving conditions. Nonetheless, these data 

suggested the effect of in-use sulfur loading was largely reversible for Tier 2 vehicles, and that 

there were likely to be significant emission reductions possible with further reductions in 

gasoline sulfur level. Another recent study by Umicore showed reductions of 41 percent for 

NOX and 17 percent for HC on a PZEV operating on fuel with 33 ppm and 3 ppm sulfur.26 Both 

of these studies conducted testing on high and low sulfur after running the test vehicles through 

test cycles meant to clean the catalyst from the effects of prior sulfur exposure. 

Both of these studies showed the emission reduction potential of lower sulfur fuel on Tier 

2 and later technology vehicles over the FTP cycle. However, assessing the potential for 

reduction on the in-use fleet requires understanding how sulfur exposure over time impacts 

emissions, and what the state of catalyst sulfur loading is for the typical vehicle in the field. In 

response to these data needs, EPA conducted a new study to assess the emission reductions 

expected from the in-use Tier 2 fleet with a reduction in fuel sulfur level from current levels. It 

was designed to take into consideration what was known from prior studies on sulfur build-up in 

catalysts over time and the effect of periodic regeneration events that may result from higher 

speed and load operation over the course of day-to-day driving. 

The study sample described in this analysis consisted of 93 cars and light trucks recruited 

from owners in southeast Michigan, covering model years 2007-9 with approximately 20,000-

40,000 odometer miles.H

 The makes and models targeted for recruitment were chosen to be 

representative of high sales vehicles covering a range of types and sizes. Test fuels were two 

non-ethanol gasolines with properties typical of certification test fuel, one at a sulfur level of 5 

 

H

 The NPRM modeling was based on analysis of 81 passenger cars and trucks. Since the NPRM, twelve additional 

Tier 2 vehicles were tested and included in the statistical analysis described in the docketed final report, examining 

the effect of sulfur on emissions from Tier 2 vehicles. The analysis based on the complete set of 93 Tier 2 vehicles 

is reflected in the results presented in this section and the emissions modeling for FRM. 
7-43

ppm and the other at 28 ppm. All emissions data was collected using the FTP cycle at a nominal 

temperature of 75°F. 

Using the 28 ppm test fuel, emissions data were collected from vehicles in their asreceived state as well as following a high-speed/load “clean-out” procedure consisting of two 

back-to-back US06 cycles intended to reduce sulfur loading in the catalyst. A statistical analysis 

of this data showed highly significant reductions in several pollutants including NOX and 

hydrocarbons, demonstrating that sulfur loadings have a large effect on exhaust catalyst 

performance, and that Tier 2 vehicles can achieve significant reductions based on removing, at 

least in part, the negative impact of the sulfur loading on catalyst efficiency (Table 7-23). For 

example, Bag 2 NOX emissions dropped 31 percent between the pre- and post-cleanout tests on 

28 ppm fuel. 

Table 7-23 Percent Reduction in In-Use Emissions after the Clean-out 

Using 28 ppm Test Fuel 

NOx

(p-value)

THC

(p-value)

CO

(p-value)

NMHC

(p-value)

CH4

(p-value)

PM

(p-value)

Bag 1 – – 6.0% 

(0.0151)

– – 15.4%

(< 0.0001)

Bag 2 31.4% 

(0.0003)

14.9% 

(0.0118)

– 18.7% 

(0.0131)

14.4% 

(0.0019)

–

Bag 3 35.4% 

(<0.0001)

20.4% 

(<0.0001)

21.5% 

(0.0001)

27.7% 

(<0.0001)

10.3% 

(<0.0001)

24.5% 

(<0.0001)

FTP Composite 11.4% 

(0.0002)

3.8% 

(0.0249)

6.8% 

(0.0107)

3.5% 

(0.0498)

6.0% 

(0.0011)

13.7% 

(<0.0001)

Bag 1 – Bag 3 – – 7.2%

(0.0656)

– – –

The clean-out effect is not significant at α = 0.10, when no reduction estimate is provided.
7-44

To assess the impact of lower sulfur fuel on in-use emissions, further testing was 

conducted on a representative subset of vehicles on 28 ppm and 5 ppm fuel with accumulated 

mileage. A first step in this portion of the study was to assess the differences in the effectiveness 

of the clean-out procedure under different fuel sulfur levels. Table 7-24 presents a comparison 

of emissions immediately following (<50 miles) the clean-out procedures at the low vs. high 

sulfur level. These results show significant emission reductions for the 5 ppm fuel relative to the 

28 ppm fuel immediately after this clean-out; for example, Bag 2 NOX emissions were 34 

percent lower on the 5 ppm fuel vs. the 28 ppm fuel. This indicates that the catalyst is not fully 

desulfurized, even after a clean out procedure, as long as there is sulfur in the fuel. This further 

indicates that current sulfur levels in gasoline continue to have a long-term, adverse effect on 

exhaust emissions control that is not fully removed by intermittent clean-out procedures that can 

occur in day-to-day operation of a vehicle and demonstrates that lowering sulfur levels to 10 

ppm on average will significantly reduce the effects of sulfur impairment on emissions control 

technology. 

Table 7-24 Percent Reduction in Exhaust Emissions When Going from 28 ppm to 5 ppm 

Sulfur Gasoline for the First Three Repeat FTP Tests Immediately Following Clean-out 

NOx

(p-value)

THC

(p-value)

CO

(p-value)

NMHC

(p-value)

CH4

(p-value)

PM‡

Bag 1 5.3%

(0.0513)

6.8%

(0.0053)

6.2%

(0.0083)

5.7%

(0.0276)

14.0%

(<0.0001)

–

Bag 2 34.4%

(0.0036)

33.9%

(<0.0001)

–

‡

26.4%

(0.0420)

49.4%

(<0.0001)

–

Bag 3 42.5%

(<0.0001)

36.9%

(<0.0001)

14.7%

(0.0041)

51.7%

(<0.0001)

28.5%

(<0.0001)

–

FTP 

Composite

15.0%

(0.0002)

13.3%

(<0.0001)

8.5%

(0.0050)

10.9%

(0.0012)

23.6%

(<0.0001)

–

Bag 1 – Bag 3 –

‡

–

‡

–

‡

–

‡

–

‡

–

‡ The effectiveness of clean-out cycle is not significant at α = 0.10. 

To assess the overall in-use reduction between high and low sulfur fuel, a mixed model 

analysis of all data as a function of fuel sulfur level and miles driven after cleanout was 

performed. This analysis found highly significant reductions for several pollutants, as shown in 

Table 7-25. Reductions for Bag 2 NOX were particularly high, estimated at 52 percent between 

28 ppm and 5 ppm overall. For all pollutants, the model fitting did not find a significant milesby-sulfur interaction, suggesting the relative differences were not dependent on miles driven 

after clean-out. 
7-45

Table 7-25 Percent Reduction in Emissions from 28 ppm to 5 ppm Fuel Sulfur 

on In-use Tier 2 Vehicles 

NOX

(p-value)

THC

(p-value)

CO

(p-value)

NMHC

(p-value)

CH4

(p-value)

NMOG+NOx

(p-value)

PM

†

Bag 1 7.1%

(0.0216)

9.2%

(0.0002)

6.7%

(0.0131)

8.1%

(0.0017)

16.6%

(< 0.0001) N/A –

Bag 2 51.9%

(< 0.0001)

43.3%

(< 0.0001) –

† 42.7%

(0.0003)

51.8%

(< 0.0001) N/A –

Bag 3 47.8%

(< 0.0001)

40.2%

(< 0.0001)

15.9%

(0.0003)

54.7%

(< 0.0001)

29.2%

(< 0.0001) N/A –

FTP 

Composite

14.1%

(0.0008)

15.3%

(< 0.0001)

9.5%

(< 0.0001)

12.4%

(< 0.0001)

29.3%

(< 0.0001)

14.4%

(< 0.0001)

–

Bag 1 –

Bag 3 –

† 5.9%

(0.0074) –

†

–

‡

–

‡ N/A –

† Sulfur level not significant at α = 0.10. 

‡ Inconclusive because the mixed model did not converge. 

 

Major findings from this study include: 

Largely reversible sulfur loading is occurring in the in-use fleet of Tier 2 vehicles 

and has a measureable effect on emissions of NOX, hydrocarbons, and other 

pollutants of interest. 

The effectiveness of high speed/load procedures in restoring catalyst efficiency is 

limited when operating on higher sulfur fuel. 

Reducing fuel sulfur levels from current levels to levels in the range of the 

gasoline sulfur standards will be expected to achieve significant reductions in 

emissions of NOX, hydrocarbons, and other pollutants of interest in the current inuse fleet. 

Assuming that the emissions impacts vs. gasoline sulfur content are 

approximately linear, changing gasoline sulfur content from 30 ppm to 10 ppm 

would result in NMOG+NOx emissions decreasing from 52 mg/mi to 45 mg/mi, 

respectively (a 13% decrease), and NOx emissions decreasing from 19 mg/mi to 

16 mg/mi, respectively (a 16% decrease), for the vehicles in the study. 

To evaluate the robustness of the statistical analyses assessing the overall in-use 

emissions reduction between operation on high and low sulfur fuel (Table 7-25), a series of 

sensitivity analyses were performed to assess the impacts on study results of measurements from 

low-emitting vehicles and influential vehicles, as documented in detail in the report.27 The 

sensitivity analyses showed that the magnitude and the statistical significance of the results were 

not impacted and thus demonstrated that the results are statistically robust. We also subjected the 

design of the experiment and data analysis to a contractor-led independent peer-review process 

in accordance with EPA’s peer review guidance. The results of the peer review28,29 largely 

supported the study design, statistical analyses, and the conclusions from the program and raised 
7-46

only minor concerns that have not changed the overall conclusions and have subsequently been 

addressed in the final version of the report.30 

Overall, the reductions found in this study are in agreement with other low sulfur studies 

conducted on Tier 2 vehicles, namely MSAT and Umicore studies mentioned above, in terms of 

the magnitude of NOX and HC reductions when switching from 28 ppm to 5 ppm fuel.31,32

 For 

additional details on the impact of gasoline sulfur control on exhaust emissions, see Section 

IV.A.6 of the preamble. 

7.1.3.4.2 Implementation in MOVES 

The fuel sulfur effect applies multiplicatively in conjunction with other gasoline fuel 

effects in MOVES. The results shown in Table 7-25 were applied in MOVES for model year 

2001 and later gasoline vehicles to estimate the sulfur effects at or below 30 ppm. For sulfur 

levels above 30 ppm, and for all pre-2001 model year vehicles, the sulfur effect originally 

implemented in MOVES2010b remains in place. 

Equation 7-3 shows the generic form of the low sulfur model applied to model year 2001 

and later gasoline vehicles. 

0.1 S Ssulfur adjustment AS base xS

Equation 7-3 Low Sulfur Model 

The sulfur coefficients (βS) were developed by linearly interpolating between emission 

levels at 28 to 5 ppm, corresponding to the reductions in emissions shown in Table 7-25, and 

standardizing to sulfur level of 30 ppm. The sulfur coefficient simply represents the slope of the 

interpolated line. The emission reductions from FTP bag 2 and FTP bag1-bag3 were used to 

calculate the sulfur coefficients for running exhaust and start exhaust, respectively. Table 7-26

shows the resulting sulfur coefficients applied in MOVES by pollutant, process, and vehicle 

type. 

Table 7-26 Low Sulfur Coefficients by Vehicle Type, Process and Pollutant 

Vehicle Type THC CO NOX PM

Starts Running Starts Running Starts Running Starts Running

Motorcycle 0 0 0 0 0 0 0 0

Passenger Car, 

Passenger Truck & 

Light Commercial Truck

0.00257 0.01813 0 0 0 0.02158 0 0

All other Vehicle Types 0 0.015488 0 0.009436 0 0.027266 0 0

The sulfur base (Sbase) in the low sulfur model varies as a function of the scenario being 

modeled and the model year group (see Table 7-27). For most states, the sulfur base is 30 ppm 

except for 2017 and later model years for the control scenario. For California, the sulfur base is 

10 ppm for all model years and scenarios. For the Section 177 states that have adopted the LEV 
7-47

III program, the sulfur base of 30 ppm and 10 ppm is used for the model years 2001 to 2016 and 

model years 2017 and later, respectively. 

Table 7-27 Sulfur Base in Low Sulfur Model 

Reference Control

MYG 2001-2016 MYG 2017+ MYG 2001-2016 MYG 2017+

Most States 30 ppm 30 ppm 30 ppm 10 ppm

California 10 ppm 10 ppm 10 ppm 10 ppm

Section-177 

States 30 ppm 10 ppm 30 ppm 10 ppm

These equations were then used to populate the database table that stores fuel effect 

equations in the MOVES database (“GeneralFuelRatioExpression”). This table allows the 

MOVES model to compute fuel effects based on the properties of any fuel contained in the 

“FuelSupply” and “FuelFormulation” database tables. Additional details are documented in the 

docket memo addressing MOVES updates. 

7.1.4 Nonroad Emissions 

The nonroad sector includes a wide range of mobile emission sources ranging from 

locomotives and construction equipment to hand-held lawn tools. In the nonroad sector, the only 

emissions that are directly affected by the Tier 3 regulation are the emissions from gasolinepowered equipment such as lawn-mowers, recreational boats and all-terrain vehicles. Their SO2

emissions are reduced with the decrease in gasoline sulfur levels. As with onroad, reference and 

control case emissions were generated using the fuel supply inputs reflecting the projected fuel 

volumes from AEO2013. 

Gasoline and land-based diesel nonroad emissions were estimated using EPA’s 

NONROAD2008 model, as run by the EPA’s consolidated modeling system known as the 

National Mobile Inventory Model (NMIM).33 The fuels in the NMIM database, NCD2010201a,

were developed from the reference and control fuels used for onroad vehicles, as described in 

Section 7.1.3.2. Onroad and nonroad gasoline formulations are assumed to be identical for all 

years. In 2018 and 2030, nonroad equipment is assumed to use E10 only. For all years, the 

reference case included the higher sulfur reference gasoline and the control case met the sulfur 

limits. 

Since aircraft, locomotive and commercial marine emission sources do not burn gasoline, 

their emission factors are unaffected by the sulfur changes in gasoline fuels that were developed 

for this rule. Hence, their emissions are the same for both the reference and control cases. The 

emissions from these sources used for this rule are the same as the ones estimated for the HeavyDuty Greenhouse Gas Rule (2011).34

 Estimation of emissions from locomotives and C1/C2 

commercial marine used the same procedures developed for the Locomotive Marine Rule 

(2008), detailed in the RIA for that rule.35

 The procedures used for calculating C3 commercial 

marine emissions are those developed in the recent C3 Rule (2010).36
7-48

7.1.5 Criteria and Toxic Emission Impact Results 

The Tier 3 rule will reduce NOX (including NO2), VOC, and SO2 from all gasolinepowered on road vehicles immediately upon implementation of lower sulfur fuel, and will further 

reduce these emissions as well as PM2.5 and CO from cars, light trucks and light heavy-duty 

trucks (gas and diesel) as tighter emission standards from these vehicles phase in. There also 

will be reductions in SO2 emissions from the nonroad gasoline fleet as a result of sulfur 

standards. The reductions are summarized in this section for each pollutant. 

NOX reductions are shown in Table 7-28 for calendar years 2018 and 2030. We project 

significant reductions immediately upon implementation of the program, growing to a nearly 25 

percent reduction in onroad emissions by 2030. We project a nearly 33 percent reduction in 

onroad emissions in 2050, when the fleet will have fully turned over to vehicles meeting the fully 

phased in Tier 3 standards. 

Table 7-28 Tier 3 NOX Reductions by Calendar Year (Annual U.S. Short Tons) 

Year

Onroad 

mobile 

reference

Onroad 

mobile 

with 

control

Reduction

Percent

reduction 

in onroad

2018 2,753,732 2,489,364 264,369 9.6%

2030 1,331,788 1,003,279 328.509 24.7%

Table 7-29 shows the reduction in NOX emissions, in annual short tons, projected in 

calendar years 2018 and 2030. The reductions are split into those attributable to the introduction 

of low sulfur fuel in the pre-Tier 3 fleet (defined for this analysis as model years prior to 2017); 

and reductions attributable to vehicle standards enabled by low sulfur fuel (model year 2017 and 

later). As shown, in 2018 over 90 percent of the program reductions are coming from lower 

sulfur gasoline on the fleet already on the road. By 2030, over 80 percent of the reduction is 

coming from 2017 and later model year vehicles, with remaining reduction coming from lower 

sulfur fuel on pre-Tier 3 vehicles.I

 

Table 7-29 Projected NOX Reductions from Tier 3 Program (Annual U.S. Short Tons) 

2018 2030

Total reduction 264,369 328,509

Reduction from pre-Tier 3 

fleet due to sulfur standard 242,434 56,324

Reduction from Tier 3 fleet

due to vehicle and sulfur 

standards

21,934 272,185

 

I

 This is an approximate breakdown, as there will be some NOX emission reduction from heavy-duty gasoline 

vehicles greater than 14,000 pounds beyond the 2017 model year that are counted in the “Tier 3 fleet” here 
7-49

VOC reductions are shown in Table 7-30 for calendar years 2018 and 2030. We project 

reductions of over 40,000 tons (3 percent of the onroad fleet emissions) immediately upon 

implementation of the program, growing to a 16 percent reduction in onroad emissions by 2030. 

We project a 28 percent reduction in onroad emissions in 2050, when the fleet will have fully 

turned over to vehicles meeting the fully phased in Tier 3 standards. 

Table 7-30 Tier 3 VOC Reductions by Calendar Year (Annual U.S. Short Tons) 

CY

Onroad 

mobile 

reference

Onroad 

mobile with 

control

Reduction

Percent 

reduction in 

onroad

2018 1,703,902 1,656,399 47,504 2.8%

2030 1,078,892 911,301 167,591 15.5%

Table 7-31 shows the VOC reductions in 2018 and 2030 split into those attributable to 

the pre-Tier 3 fleet, and the Tier 3 fleet. The Tier 3 fleet reductions are further subdivided into 

the contribution of the exhaust and evaporative standards. In 2018, over 80 percent of the 

program reductions are coming from lower sulfur gasoline on the fleet already on the road. By 

2030, over 90 percent of the reduction is coming from 2017 and later model year vehicles, with 

remaining reduction coming from lower sulfur fuel on pre-Tier 3 vehicles. The evaporative 

standards account for close to 40 percent reduction in VOC in 2030. 

Table 7-31 Projected VOC Reductions from Tier 3 Program (Annual U.S. Short Tons) 

2018 2030

Total reduction 47,504 167,591

Reduction from pre-Tier 3 

fleet due to sulfur standard 38,786 11,249

Reduction from Tier 3 fleet 

due to vehicle and sulfur 

standards

8,718 156,343

Exhaust 43,009 105,253

Evaporative 4,495 62,339

CO reductions are shown in Table 7-32 for calendar years 2018 and 2030. We project 

significant reductions immediately upon implementation of the program, growing to a 24 percent 

reduction in onroad emissions by 2030. We project a 38 percent reduction in onroad emissions 

in 2050, when the fleet will have fully turned over to vehicles meeting the fully phased-in Tier 3 

standards. 

Table 7-32 Tier 3 CO Reductions by Calendar Year (Annual U.S. Short Tons) 

CY

Onroad 

mobile 

reference

Onroad 

mobile with 

control

Reduction

Percent 

reduction 

in onroad

2018 17,517,356 17,238,477 278,879 1.6%

2030 14,663,722 11,205,680 3,458,041 23.6%
7-50

Table 7-33 shows the reductions for CO, broken down by pre- and post-Tier 3 in the 

manner described for NOX and VOC above. The immediate reductions in the onroad fleet from 

sulfur control comprise only about 40 percent of total reductions in 2018. By 2030, the Tier 3 

fleet is accounting for 99 percent of program reductions. Of the Tier 3 vehicle standard 

reductions in 2030, we estimate that about 5 percent are contributed by the heavy-duty tailpipe 

standards. 

Table 7-33 CO Reductions from Tier 3 Program (Annual U.S. Short Tons) 

2018 2030

Total reduction 278,879 3,458,041

Reduction from pre-Tier 3 

fleet due to sulfur standard 122,171 17,734

Reduction from Tier 3 fleet

due to vehicle and sulfur 

standards

156,708 3,440,307

Direct PM2.5 impacts are shown in Table 7-34 for calendar years 2018 and 2030. For 

direct PM, the impact shown is solely from the tailpipe standards. Thus, unlike other pollutants, 

reductions do not become significant until the fleet has turned over to cleaner vehicles. By 2030, 

we project a reduction of about 7,900 tons annually, which represents approximately 10 percent 

of the onroad direct PM2.5 inventory. The relative reduction in onroad emissions is projected to 

grow to 28 percent in 2050, when the fleet will have fully turned over to vehicles meeting the 

fully phased-in Tier 3 standards. 

Table 7-34 Tier 3 PM2.5 Reductions by Calendar Year (Annual U.S. Short Tons) 

CY

Onroad mobile 

reference

Onroad mobile 

with control Reduction

Percent

reduction in 

onroad

2018 115,560 115,430 130 0.1%

2030 78,320 70,428 7,892 10.1%

Emissions of air toxics also will be reduced by the sulfur, exhaust and evaporative 

standards. Air toxics are generally a subset of compounds making up VOC, so the reduction 

trends tend to track the VOC reductions presented above. Table 7-35 presents reductions for 

certain gaseous air toxics and polycyclic aromatic hydrocarbons (PAHs)J, reflecting reductions 

of a few percent in 2018, and 10 to 30 percent of onroad emissions, depending on the individual 

pollutant, in 2030. 

 

J

 PAHs represents the sum of the following 15 PAH compounds: acenaphthene, acenaphthalene, anthracene, 

benz(a)anthracene, benzo(a)pyrene, benzo(b)fluoranthene, benze(g,h,i)perylene, benzo(k)fluoranthene, chrysene, 

dibenzo(a,h)anthracene, fluoranthene, fluorine, indeno(1,2,3,cd)pyrene, phenanthrene, and pyrene. These PAHs are 

included in EPA’s national emissions inventory (NEI). 
7-51

Table 7-35 Reductions for Certain Individual Compounds (Annual U.S. Short Tons) 

2018 

Reduction 

Percent reduction 

in onroad

2030 Reduction Percent reduction 

in onroad

Acetaldehyde 600 3.4% 2,067 20.6%

Formaldehyde 513 2.3% 1,277 9.9%

Acrolein 40 2.6% 127 15.0%

1,3-Butadiene 257 5.2% 677 29.3%

Benzene 1,916 5.8% 4,762 26.4%

Naphthalene 99 3.0% 269 15.2%

Ethanol 2,704 1.7% 19,950 15.8%

2,2,4-

Trimethylpentane

806 1.9% 3,827 11.9%

Ethyl Benzene 761 2.8% 2,451 14.3%

Hexane 1,112 3.2% 4,132 19.0%

Propionaldehyde 27 2.7% 63 16.9%

Styrene 71 5.1% 242 29.5%

Toluene 3,772 2.2% 15,261 12.9%

Xylene 2,894 2.9% 9,396 15.1%

PAHs 10 1.2% 58 18.1%

The totals shown in Table 7-36 represent the sum of all toxic species listed in Table 7A-1 

of the Appendix, including the species in Table 7-35. As shown, in 2030, the overall onroad 

inventory of total toxics will be reduced by about 15 percent, with nearly one half of the 

reductions coming from the evaporative standards. 

Table 7-36 Reductions in Total Mobile Source Air Toxics (Annual U.S. Short Tons) 

2018 2030

Total reduction 15,583 64,558

Reduction from pre-Tier 3 fleet due to 

sulfur standard 11,981 3,517

Reduction from Tier 3 fleet due to 

vehicle and sulfur standards 3,602 61,041

Exhaust 13,340 34,595

Evaporative 2,243 29,963

SO2 emissions from mobile sources are a direct function of sulfur in the fuel, and 

reducing sulfur in gasoline would result in immediate reductions in SO2 from the on and off-road 

fleet. The reductions, shown in Table 7-37, represent over 50 percent reduction in onroad SO2

emissions. The breakdown of the relative contribution of onroad vehicles and off-road 

equipment is shown; the contribution of off-road sources is a function of off-road gasoline 

consumption accounting for approximately 5 percent of overall gasoline use.37
7-52

Table 7-37 Projected SO2 Reductions from Tier 3 Program (Annual U.S. Short Tons) 

2018 2030

Total reduction 15,565 13,261

Reduction from onroad 

vehicles due to sulfur 

standard

14,813 12,399

Reduction from off-road 

equipment due to sulfur 

standard

752 862

Percent reduction in 

onroad SO2 emissions 56% 56%

7.2 Criteria and Toxic Pollutant Air Quality Impacts 

7.2.1 Emission Inventories for Air Quality Modeling 

To estimate the benefits of the Tier 3 rule, we performed air quality modeling for the 

years 2018 and 2030. As noted in Section 7.1, emission inventories for air quality modeling were 

required for the entire U.S. by 12 km grid cell and hour of the day for each day of the year, 

requiring a methodology with much greater detail than the national emission inventories 

presented above. While most of the modeling tools and inputs used for estimating national 

emission inventories were also used in developing inputs for air quality modeling, the application 

of these tools (particularly MOVES) to produce the gridded / hourly emissions was quite 

different, and in essence a separate analysis. As explained in Section 7.2.1.1, the different 

analyses generated different onroad inventory totals, but the relative reduction from reference to 

control scenarios was consistent. The summary of the methodology for each sector is contained 

in the following sections; for brevity, details of the process for developing air-quality ready 

emission inventories are available in a separate technical support document.38

7.2.1.1 Onroad Emissions 

For the onroad vehicle emissions inputs to our air quality modeling, we used an emission 

inventory approach that provided more temporal and geographical resolution than the approach 

used for the national inventories described above. This additional detail is needed when 

generating inputs to air quality models because it allows us much more precision in accounting 

for local ambient temperatures and local fuel properties in our air quality modeling. For this 

purpose, we used county-specific inputs and tools that integrated the MOVES model of onroad 

emissions with the Sparse Matrix Operator Kernel Emissions tool (SMOKE) emission inventory 

model to take advantage of the gridded hourly temperature information used in air quality 

modeling. 

In particular, we used an automated process to run MOVES to produce emission factors 

by temperature and speed for the fleet mix, fuels, and I/M program for more than 100 

“representing counties,” to which every other county could be mapped. The emission factors 

then were multiplied by activity at the grid-cell-hour level to produce gridded hourly emissions 
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for the entire continental U.S. These emissions were input into the Community Multiscale Air 

Quality Modeling System (CMAQ). We summarize this approach in the sections below. 

Because of the differences in methodology between the national inventories and air 

quality inventories, particularly the treatment of local variables such as vehicle speed 

distributions and the handling of non-linear temperature effects in MOVES, the more detailed 

approach used for the air quality inventory produced different emission estimates than those 

described in the national inventory section above. This is pronounced, especially, in pollutants 

with strong temperature sensitivities in MOVES, such as PM2.5, where the finer temperature 

resolution in the air quality approach produced significantly higher emissions than the aggregate 

national inventory approach. 

In addition to the methodological differences, because this modeling methodology with 

added precision is time consuming and resource intensive, the inventories for the air quality 

modeling had to begin months before the national inventory modeling and used a slightly older 

version of the MOVES model. The model and the input differences between the national 

inventory and the inventories developed for air quality modeling are described below. 

Phase-in Assumptions for LDT3 and LDT4 

As described in Section 7.1.3.3.1, for the national inventory, the onset of the Tier 3 

phase-in for gaseous pollutants (HC, CO, NOx) starts in 2018 for truck classes with gross vehicle 

weight ratings greater than 6,000 lbs. (LDT3 and LDT4), in contrast to LDV, LDT1, and LDT2, 

which begin phasing-in in 2017. However, for the air quality modeling, the phase-in was 

modeled uniformly in 2017 for all light-duty fleet, resulting in slight overestimation of the Tier 3 

emission reductions in calendar year 2018. 

E200/E300 to T50/T90 Conversion 

While the primary impact of gasoline sulfur control is the changes in sulfur content of the 

fuel, we do expect slight changes in other fuel properties, including fuel distillation, as discussed 

in Section 7.1.3.2. Fuel distillation is one of a number of fuel properties that have been found to 

impact vehicle emissions. Specific fuel properties in question are the T50 and T90 of the 

gasoline (the temperature at which 50 percent and 90 percent of the fuel is evaporated, 

respectively), which are often discussed instead in terms of E200 and E300 (the percent of the 

fuel evaporated at 200°F and 300°F, respectively). Both T50 and T90 are among the fuel 

properties modeled in MOVES that have impacts on emissions. Thus, estimating the overall 

impact of Tier 3 sulfur control on emissions requires the characterization of the changes in fuel 

distillation resulting from changes in gasoline sulfur. 

Both T50/T90 and E200/E300 data is available from the fuel compliance database. For 

the reference case, the values for T50 and T90 were derived directly from the fuel compliance 

database. However, the changes for the control case were modeled using a refinery model which 

only provides changes in the form of E200 and E300. Therefore, we applied changes in 

E200/E300 from the refinery modeling to E200 and E300 values derived from the fuel 

compliance database, and then converted into T50 and T90 values using characteristic 

transformation equations. 
7-54

Typically, E200/E300 and T50/T90 values are well correlated using the transformation 

equations. However, if the distillation properties vary in a non-typical way, these 

transformations can provide inaccurate results compared to tested values of E200/E300 and 

T50/T90. For the 2012 fuel compliance data, fuels in all regions except the West and Pacific 

Northwest behave in a typical way regarding distillation properties and characteristic 

transformations between those properties. However, in the West and Pacific Northwest, when 

the transformation equation was used, E200/E300 did not correlate with T50/T90 as was 

expected. 

The choice to start with T50/T90 data from the fuels compliance database for the 

reference case and E200/E300 data from the same database for the control case resulted in 

unexpected differences in fuel properties between the two scenarios, and in turn, affected the 

emissions inventory in the West and Pacific Northwest. These effects on the emissions 

inventory are not real effects; they are simply an artifact of our methodology. In summary, for 

air quality modeling inputs in the West and Pacific Northwest, there is up to a 5 percent increase 

in T50 and T90 values in the control case compared to the reference case that is caused by 

improper translation from E200/E300 and not caused by a real change in these data. This error 

was corrected for the inputs used in the national inventory modeling. 

Evaporative Emissions 

Overall, the updates made to the evaporative emissions for the national inventory resulted 

in reduced evaporative emissions inventory by 10 to 20 percent. Most of the differences between 

the national inventory and the inventories for air quality modeling results from a change in the 

vapor venting leak prevalence rates. The distribution of leak sizes shifted towards smaller leaks 

causing a reduction in emissions from leaks. An error was also corrected in the temperature 

adjustment coefficients for running loss emissions, resulting in lower running loss emissions. 

There was another update to correct an error in the database for the LEV III/Section 177 States’ 

I/M versus non-I/M rates, which was very minor. Additional details are provided in the docket 

memo documenting the MOVES updates. 

Modeling of I/M Programs 

For states that have I/M programs and submitted county databasesK, the inventories for 

air quality modeling did not properly account for the I/M program, resulting in overestimation of 

the inventory for both the reference and the control cases. However, the emission reductions 

from Tier 3 are not affected. 

Modeling of Section 177 States 

The sulfur base (see Table 7-27) for the three Non-Section 177 states (VA, NH, and DC) 

were inadvertently modeled as Section 177 states in the inventories for air quality modeling. For 

these states, the emission reductions from Tier 3 were underestimated. 

 

K

 A total of 411 counties were affected. For additional detail, please refer to the docket memo describing MOVES 

updates. 
7-55

The updates and the fixes to the above described issues were included only in the national 

inventories. However, the fundamental MOVES updates incorporating new research, the custom 

inputs developed for the reference and control scenarios, and the modeling of LEV III programs, 

described in detail in Section 7.1.3, were also included in the inventories for the air quality 

modeling. 

The two sets of results are compared in Table 7-38 below. 

Table 7-38 Comparison of Calendar Year 2030 Onroad Emission National Inventories and 

Inventories Used for Air Quality Modeling [U.S. Short tons] 

Pollutant

Reference Control

National 

Inventory

Air Quality 

Inventory

Difference

AQ vs. NI

National

Inventory

Air Quality 

Inventory

Difference

AQ vs. NI

NOX 1,317,412 1,367,429 4% 993,724 1,018,962 3%

VOC 1,065,457 1,260,883 18% 900,680 1,079,042 20%

CO 14,480,459 14,434,283 0% 11,085,515 10,780,871 3%

PM2.5 77,838 82,138 6% 70,048 73,620 5%

Benzene 17,772 18,742 6% 13,092 13,603 4%

Ethanol 124,933 150,592 21% 105,324 129,002 23%

Acrolein 839 852 2% 714 717 1%

1,3-Butadiene 2,285 2,288 0% 1,619 1,572 3%

Formaldehyde 12,846 13,454 5% 11,588 12,092 4%

Acetaldehyde 9,946 10,143 2% 7,909 7,957 1%

SO2 21,973 22,310 2% 9,734 10,040 3%

Because the reference and control case emissions rate inputs were the same for the 

national inventory and air quality inventory runs, the percent reductions due to the Tier 3 rule are 

very similar, considering the differences described earlier, as shown in Table 7-39. 
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Table 7-39 Comparison of Emission Reductions from Reference to Control Case in 

“National” and “Air Quality” Onroad Inventories 

2018 2030

Pollutant

National 

Inventory 

Reduction

Air Quality 

Inventory 

Reduction

National Inventory 

Reduction

Air Quality 

Inventory 

Reduction

NOX -9.6% -9.9% -24.6% -25.5%

VOC -2.8% -2.4% -15.5% -14.4%

CO -1.6% -1.6% -23.4% -25.3%

PM2.5 -0.1% -0.4% -10.0% -10.4%

Benzene -5.8% -6.4% -26.3% -27.4%

Ethanol -1.7% -1.3% -15.7% -14.3%

Acrolein -2.6% -2.8% -14.9% -15.8%

1,3-Butadiene -5.2% -5.7% -29.2% -31.3%

Formaldehyde -2.3% -2.3% -9.8% -10.1%

Acetaldehyde -3.3% -3.5% -20.5% -21.5%

SO2 -56.3% -55.9% -55.7% -55.0%

The following sections summarize the analysis done to generate the air quality 

inventories. 

7.2.1.1.1 Representing Counties 

Air quality modeling requires emission inventories for nearly all of the more than 3,000 

counties in the United States. Although EPA compiles county-specific databases for all counties 

in the nation, actual county-specific data is not available for all counties. Instead, much of our 

“county” data is based on state-wide estimates or national defaults. For this proposal, rather than 

explicitly model every county in the nation, we have grouped counties together with counties 

with similar characteristics to generate emission rates that can be used in all of the counties in the 

grouping. 

We explicitly model only one county in the group (the "representing" county) to 

determine emission rates. These rates are then used in combination with county specific activity 

and meteorology data, to generate inventories for all of the counties in the group. This approach 

dramatically reduces the number of modeling runs required to generate inventories and still takes 

into account differences between counties. 

The representing counties are chosen so that they can be used to compute rates, such as 

g/mi factors, that will be representative across the group of counties. To assure this, the counties 

are grouped based on vehicle age, fuel parameters, emission standards, I/M programs and 

altitude. However, representative counties are not meant to represent VMT. VMT is estimated 

for every Continental U.S. county. As explained in Section 7.2.1.1.3, the SMOKE model 

calculates emissions by multiplying the county-specific VMT by the county-group specific g/mi 

emission rates produced in the MOVES run. The characteristics used to group the counties are 

summarized in Table 7-40 below.
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Table 7-40 Characteristics for Representing County Groupings 

County Grouping Characteristic Description

State Counties in each group must be in the same state as the 

representing county.

Fuel Parameters Average gasoline fuel properties for January and July 

2005, including RVP, sulfur level, ethanol fraction and 

percent benzene

Emission Standards Some states have adopted California highway vehicle 

emission standards or plan to adopt them. Since 

implementation of the standards varies, each state with 

California standards is treated separately.

Inspection/Maintenance Programs Counties were grouped within a state according to whether 

or not they had an I/M program. All I/M programs within 

a state were considered as a single program, even though 

each county may be administered separately and have a 

different program design.

Altitude Counties were categorized as high or low altitude based 

on the criteria set forth by EPA certification procedures 

(4,000 feet above sea level).

Vehicle Age The average age of passenger vehicles is calculated for 

each county. The counties in each group must be in the 

same average age category as the representing county.

The result is a set of 146 county groups with similar ages, fuel, emission standards, 

altitude and I/M programs in each state. For each group, the county with the highest VMT was 

chosen as the representing county. Only these 146 counties were needed to model the 48 states 

included in the air quality analysis inventory. 

For each county group, SMOKE-MOVES generated a set of rates that varied by vehicle 

type, speed and temperature, thus we did not need to consider the fleet mix, speed or temperature 

range in our grouping characteristics. This greatly increases the number of counties that can be 

in each grouping, and reduces the number of MOVES runs required. 

More detail on the process for selecting representative counties and a list of all of the 

3,322 counties in the nation and the counties selected to represent is provided in the emission 

inventory technical support document.39

7.2.1.1.2 SMOKE-MOVES 

The official EPA highway vehicle emissions model (MOVES) was updated as described 

in Section 7.1.3 for national emission inventory development, but in order to take advantage of 

the gridded hourly temperature information used in air quality modeling, MOVES and SMOKE 

have been integrated into an inventory generation system called SMOKE-MOVES.40

 MOVES 

can be run in “inventory mode” to calculate the mass of pollutant emissions, as was done for the 

national inventories, or in “emission rate” mode, in which it calculates emissions in grams per 
7-58

mile (for running emissions) or grams per vehicle (for start and evaporative emissions). For our 

air quality runs, we used the rates approach. This creates a set of “lookup tables” with emission 

rates by temperature, speed, pollutant, and vehicle class (Source Classification Code (SCC)). 

SMOKE then transforms these rates into emission inventories for the air quality modeling by 

multiplying these emission factors by activity specific to each grid cell hour.41 

The SMOKE-MOVES process generates MOVES run specification files to produce the 

emission rate lookup tables (in MOVES, there are three per run to cover all emission processes: 

Rate Per Distance, Rate Per Vehicle, and Rate Per Profile) covering the range of temperatures 

needed, across each combination of fuel and I/M program in the nation. A series of postprocessing scripts was developed to take the MOVES emission rate tables and translate them into 

the emission rates tables needed by SMOKE to produce mass emissions by 12 km grid and hour 

of the day for an entire year. For expediency, MOVES lookup tables were generated for July 

and January to get the full range of temperatures needed for an entire year’s worth of 

meteorology data. This efficiency step introduces uncertainty because it does not account for 

fuel “shoulder” seasons in the fall and spring, where the actual fuel pool is a blend of winter and 

summer fuel. This is mainly an issue for fuel RVP, which is not changing between the reference 

and control scenarios. 

7.2.1.1.3 Inputs to MOVES 

The county-level fuel-property inputs for the air quality runs were the same as for the 

national inventories described in Section 7.1.3. However, for the air quality runs, we were able 

to use grid-level temperatures. We also needed county-specific information on vehicle 

populations, VMT, age distributions, and inspection-maintenance programs for each of the 

representing counties. The source data for each of these inputs is described below. 

7.2.1.1.3.1 Temperature and Humidity 

Ambient temperature can have a large impact on emissions. Low temperatures are 

associated with high start emissions for many pollutants. High temperatures are associated with 

greater running emissions due to the higher engine load of air conditioning. High temperatures 

also are associated with higher evaporative emissions. 

The 12-km gridded meteorological input data for the entire year of 2007 covering the 

continental United States were derived from simulations of version 3.1 of the Weather Research 

and Forecasting Model42, Advanced Research WRF43 core. The WRF Model is a mesoscale 

numerical weather prediction system developed for both operational forecasting and atmospheric 

research applications. The Meteorology-Chemistry Interface Processor (MCIP)44 version 3.6

was used as the software for maintaining dynamic consistency between the meteorological 

model, the emissions model, and air quality chemistry model. 

EPA applied the SMOKE-MOVES tool, Met4moves, to the gridded, hourly 

meteorological data (output from MCIP) to generate a list of the maximum temperature ranges, 

average relative humidity, and temperature profiles that are needed for MOVES to create the 

emission-factor lookup tables. “Temperature profiles” are arrays of 24 temperatures that 

describe how temperatures change over a day, and they are used by MOVES to estimate vapor 
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venting emissions. The hourly gridded meteorological data (output from MCIP) was also used 

directly by SMOKE. 

The temperature lists were organized based on the representative counties and fuel 

months as described in Sections 4.6.4.1 and 4.6.4.2, respectively in the documentation for the 

2008 National Emission Inventory.45

 Temperatures were analyzed for all of the counties that are 

mapped to the representative counties, i.e., for the county groups, and for all the months that 

were mapped to the fuel months. EPA used Met4moves to determine the minimum and 

maximum temperatures in a county group for the January fuel month and for the July fuel month, 

and the minimum and maximum temperatures for each hour of the day. Met4moves also 

generated idealized temperature profiles using the minimum and maximum temperatures and 10 

degree intervals. In addition to the meteorological data, the representative counties and the fuel 

months, Met4moves uses spatial surrogates to determine which grid cells from the 

meteorological data to collect temperature and relative humidity statistics. For example, if a 

county had a mountainous area with no roads, this would be excluded from the meteorological 

statistics. The output for the daily mode is one temperature range per county per day and is a 

more detailed approach for modeling the vapor venting emissions. EPA ran Met4moves in daily 

mode for 2007 base year. 

The treatment of humidity was simpler. The humidity values that correspond to each 

temperature value in each temperature bin are averaged and used as the humidity for calculations 

for that temperature bin. Each set of temperature bins for a grouping of counties will have its 

own set of corresponding humidity values. Humidity affects the formation of oxides of nitrogen 

(NOx) during combustion and the calculation of air conditioning load effects. 

2007 calendar year temperatures and humidity values described above were used for the 

2018 and 2030 projection years as well. 

7.2.1.1.3.2 Required Vehicle Population and VMT Inputs 

Vehicle population and vehicle miles traveled (VMT) data are required input for MOVES 

when modeling on a county basis. Using the technical guidance provided to states by EPA, a 

contractor generated appropriate national estimates for vehicle populations and VMT for use in 

the MOVES databases using the county specific VMT and national average ratios of vehicle 

populations versus vehicle VMT from the MOVES application. This method is described in 

Section 3.3 of the document, "Technical Guidance on the Use of MOVES2010 for Emission 

Inventory Preparation in State Implementation Plans and Transportation Conformity."46

7.2.1.1.3.3 Other Local Inputs 

In addition to temperature, vehicle population and fuels, we also needed inputs such as 

age distribution and Inspection/Maintenance program descriptions for each of the representing 

counties. These inputs are required for the model to run at the county level and provided an 

opportunity to assure that the model was properly accounting for the most recent available local 

data. These county inputs were derived from the inputs used for the National Emissions 

Inventory (NEI). This inventory covers the 50 United States (U.S.), Washington DC, Puerto 

Rico and U.S. Virgin Islands. The NEI was created by the U.S. Environmental Protection 
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Agency's (EPA's) Emission Inventory Group (EIG) in Research Triangle Park, North Carolina, 

in cooperation with the Office of Transportation and Air Quality in Ann Arbor, Michigan. The 

inputs for the NEI are stored in the National Mobile Inventory Model (NMIM) county database 

(NCD). Details of how the NCD was developed are documented for the 2008 NEI. These inputs 

were then converted to a format consistent with MOVES. 

7.2.1.1.4 VMT, Population, and Speed 

In addition to the lookup tables, SMOKE requires county VMT, population, and average 

speed by road type to calculate the necessary emissions for air quality modeling. 

The annual vehicle miles traveled (VMT) values calculated for calendar year 2007 are 

estimated using VMT estimates from the Federal Highways Administration (FHWA) for 2007 

and 2008, combined with the state supplied VMT estimates submitted for the 2008 calendar year. 

The FHWA estimates, found in the Vehicle-miles of travel by functional system table (VM-2) 

can be obtained from the web at: 

http://www.fhwa.dot.gov/policyinformation/statistics/2007/ 

http://www.fhwa.dot.gov/policyinformation/statistics/2008/ 

The VMT data from the VM2 tables are broken out by state and HPMS road type. The 

VMT values from both 2007 and 2008 are placed into a single table (matched on state and road 

type) and an adjustment factor (2007 VMT / 2008 VMT) is calculated for each state and road 

type. 

The VMT used for the 2008 NEI is obtained from the FF10 format file (by county and 

SCC) used with SMOKE for Version 3 of the 2008 NEI 

(VMT_NEI_2008_updated2_18jan2012_v3.csv). The development of the 2008 VMT estimates 

using state supplied data and FHWA estimates is described in the technical support document for 

2008 NEI.47

 

The 2007 VMT values were calculated by applying the adjustment factors calculated 

from the FHWA tables to the appropriate rows in the 2008 VMT data, matching on state and 

HPMS road type. The same adjustment was used for all counties in a state and that all Source 

Classification Code (SCC) vehicle types used the same adjustment for each road type. 

The 2018 and 2030 VMT was created by multiplying the base year 2007 platform VMT 

by growth adjustment factors. The adjustment factors are at the state level by the 12 SCC 

vehicle types. The resulting total VMT values by SCC in 2018 are normalized to match the total 

VMT by SCC from MOVES runs using VMT projections from the “early release” of the 2013 

AEO. Adjustment factors by state were derived using the National Mobile Inventory Model 

(NMIM) County Database (NCD) growth from 2007 to 2018 and 2018 to 2030 to account for the 

relative growth among states. The NCD20080522 database contains the most recent county 

specific VMT projections available. So, while the AEO projections are used to calculate national 

totals, the relative growth among states is derived from the NCD. 
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Once the annual VMT by county has been estimated, the population can be determined 

by assigning a fixed average VMT to each vehicle. The VMT for each SCC is calculated from 

the MOVES runs used to generate VMT from the AEO estimates. These MOVES runs also 

generated population estimates using MOVES default growth and scrappage algorithms. A ratio 

of the VMT per vehicle by SCC vehicle type is calculated using the VMT values and the 

corresponding population estimates. Using this VMT/population ratio, the vehicle population for 

each county by SCC can be calculated from the VMT estimates by SCC. 

The average speeds provided to SMOKE for each county were derived from the default 

national average speed distributions found in the default MOVES2010b database 

AvgSpeedDistribution table. These average speeds are the average speeds originally developed 

for the previous EPA highway vehicle emission factor model, MOBILE6.48 In MOVES, there is 

a distribution of average speeds for each hour of the day for each road type. The average speeds 

in these distributions were used to calculate an overall average speed for each hour of the day. 

These hourly average speeds were weighted together using the default national average hourly 

vehicle miles traveled (VMT) distribution found in the MOVES default database 

HourlyVMTFraction table, to calculate an average speed for each road type. This average speed 

by road type was provided to SMOKE for each county. 

7.2.1.2 Nonroad Emissions 

The “primary” nonroad emissions used in air quality modeling are identical to those used 

for national inventories as presented in Section 7.1.4 above. The NMIM model was run to 

generate county-month inventories by SCC, which were processed to gridded-hourly emissions 

by SMOKE. For more details on SMOKE processing of nonroad emissions, see the emissions 

modeling technical support document.49 Table 7-41 shows that the only effect of the rule 

captured by the NONROAD model is a decrease in SO2 due to a drop in fuel sulfur. Not 

modeled are a probable decrease in sulfate PM and possible decreases in other pollutants due to 

improved catalyst performance in new equipment that may be equipped with catalysts. Both of 

these un-modeled effects would be due to that decreases in gasoline fuel sulfur that are part of 

this rule. 

Table 7-41 National Nonroad Emissions for Calendar Year 2018 and 2030 

Pollutant

2018 2030

Reference Control Difference Reference Control Difference

NOX 1,076,370 1,076,370 0% 729,721 729,721 0%

VOC 1,436,324 1,436,324 0% 1,225,104 1,225,104 0%

CO 13,566,942 13,566,942 0% 14,935,644 14,935,644 0%

PM2.5 105,409 105,409 0% 68,308 68,308 0%

Benzene 26,124 26,124 0% 24,146 24,146 0%

Acrolein 613 613 0% 541 541 0%

1,3-Butadiene 3,298 3,298 0% 3,215 3,215 0%

Formaldehyde 16,225 16,225 0% 13,940 13,940 0%

Acetaldehyde 8,094 8,094 0% 6,902 6,902 0%

SO2 2,729 1,977 -28% 3,113 2,251 -28%
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7.2.1.3 Heavy-Duty Extended Idle 

7.2.1.3.1 Methodology 

A non-negligible amount of heavy duty vehicles emissions occur during long idling of 

heavy duty diesel trucks engaged in long distance hauling during federally required “down” time. 

These “extended idle” emissions are accounted for in our MOVES model. However, the amount 

of extended idle that occurs in counties varies significantly, depending on the presence of 

interstate highways, freight routes and the presence of truck stops. 

We have developed a method to generate an extended idle adjustment using the county 

specific extended idle activity and county specific combination truck vehicle populations. These 

adjustments are applied in SMOKE to adjust the representing county extended idle emission 

rates produced by MOVES (in units of grams per vehicle) to reflect the different amount of 

extended idle activity in the represented counties. 

RPVc = RPV * (POPn * EIAllocFactor)/POPc 

Where: 

RPVc : Rate per vehicle for the county. 

RPV: Rate per vehicle of the representing county. 

POPn: National vehicle population. 

POPc: Vehicle population of the county. 

EIAllocFactor: Emission rate (grams per vehicle). 

7.2.1.4 Portable Fuel Container and Upstream Emissions 

The Tier 3 rule has no impact on portable fuel container (PFC) emissions. The standards 

are also not expected to impact upstream emissions associated with fuel transport/distribution. 

For fuel production, the results of our refinery permitting analysis described in Section V.B. of 

the preamble and Chapter 4 of the RIA project minor emissions increases at some refineries due 

to the reductions in fuel sulfur content that would be required by the Tier 3 standards. We did not 

include these emission impacts in our modeling because the projected increases are small and 

may be even less than projected if refineries apply emissions controls to reduce emissions 

increases. 

Although there is no modeled impact of the Tier 3 standards on upstream or PFC 

emissions a significant number of modifications were made to the 2007 v.5 platform inventory 

reflecting the renewable fuel volumes projected by AEO2013 in the reference case air quality 

inventory. These modifications are described in detail in a memorandum to the docket.50 

Modifications to point and nonpoint inventories include adjustments to agricultural emissions, 
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increases in emissions associated with production of corn ethanol, cellulosic ethanol, cellulosic 

diesel, and biodiesel, decreases in petroleum refinery emissions to account for gasoline 

displacement, and changes in vapor loss emissions from transport of ethanol and 

gasoline/ethanol fuel blends. Modifications to mobile source inventories include increases in 

combustion emissions from water, rail and truck transport of biofuels. PFC emissions were 

adjusted to account for impacts of RVP changes associated with use of gasoline/ethanol blends. 

7.2.1.5 Hydrocarbon Speciation Profiles and SMOKE 

We used the Community Multi-scale Air Quality (CMAQ) model, described in detail in 

the following section, to conduct air quality modeling for this analysis. The SMOKE tool is used 

to process emission inventories for air quality modeling.L

 Specifically, SMOKE converts our air 

quality emissions inventories into CMAQ-ready inputs by transforming the emission inventories 

based on the temporal allocation, chemical speciation, and spatial allocation requirements of 

CMAQ. In processing our Tier 3 emissions inventories for CMAQ, SMOKE uses hydrocarbon 

speciation profiles to break total hydrocarbons down into individual constituent compounds and 

create the needed chemical speciation inputs required for CMAQ. Given the complexity of the 

atmospheric chemistry, the hydrocarbon speciation can have an important influence on the air 

quality modeling results. The EPA maintains a database of VOC and particulate matter (PM) 

speciation profiles for various emission sources including mobile sources. This database, called 

SPECIATE, maintains the record of each profile including its referenced source, testing 

methods, a subjective rating of the quality of the data, and other detailed data that allow 

researchers to decide which profile is most suitable for model input.M Mobile source 

hydrocarbon speciation profiles used in this analysis are from EPA’s SPECIATE database 

(version 4.4), and additional information on the use of these profiles in air quality modeling, such 

as applicable source categories, can be found in the Emissions Inventory TSD. 

7.2.2 Air Quality Modeling Methodology 

Air quality models use mathematical and numerical techniques to simulate the physical 

and chemical processes that affect air pollutants as they disperse and react in the atmosphere. 

Based on inputs of meteorological data and source information, these models are designed to 

characterize primary pollutants that are emitted directly into the atmosphere and secondary 

pollutants that are formed as a result of complex chemical reactions within the atmosphere. 

Photochemical air quality models have become widely recognized and routinely utilized tools for 

regulatory analysis by assessing the effectiveness of control strategies. These models are applied 

at multiple spatial scales - local, regional, national, and global. This section provides detailed 

information on the photochemical model used for our air quality analysis (the Community Multiscale Air Quality (CMAQ) model), atmospheric reactions and the role of chemical mechanisms 

in modeling, and model uncertainties and limitations. Further discussion of the modeling 

methodology is included in the Air Quality Modeling Technical Support Document (AQM TSD) 

 

L

 For more information, please see the website for SMOKE: http://www.smoke-model.org/index.cfm. 

M

 For more information, please see the website for SPECIATE: 

http://www.epa.gov/ttn/chief/software/speciate/index.html. 
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found in the docket for this rule. Results of the air quality modeling are presented in Section 

7.2.4.

7.2.2.1 Modeling Methodology 

A national-scale air quality modeling analysis was performed to estimate future year 8-

hour ozone concentrations, annual PM2.5 concentrations, 24-hour PM2.5 concentrations, annual 

NO2 concentrations, air toxics concentrations, visibility levels and nitrogen and sulfur deposition 

levels for 2018 and 2030. The 2007-based CMAQ modeling platform was used as the basis for 

the air quality modeling for this rule. This platform represents a structured system of connected 

modeling-related tools and data that provide a consistent and transparent basis for assessing the 

air quality response to projected changes in emissions. The base year of data used to construct 

this platform includes emissions and meteorology for 2007. The platform was developed by the 

U.S. EPA’s Office of Air Quality Planning and Standards in collaboration with the Office of 

Research and Development and is intended to support a variety of regulatory and research model 

applications and analyses. 

The CMAQ modeling system is a non-proprietary, publicly available, peer-reviewed, 

state-of-the-science, three-dimensional, grid-based Eulerian air quality model designed to 

estimate the formation and fate of oxidant precursors, primary and secondary PM concentrations, 

acid deposition, and air toxics, over regional and urban spatial scales for given input sets of 

meteorological conditions and emissions.51,52,53 The CMAQ model version 5.0 was most 

recently peer-reviewed in September of 2011 for the U.S. EPA.54 The CMAQ model is a wellknown and well-respected tool and has been used in numerous national and international 

applications.55,56,57 This 2007 multi-pollutant modeling platform used the most recent multipollutant CMAQ code available at the time of air quality modeling (CMAQ version 5.0.1N

). 

CMAQ includes many science modules that simulate the emission, production, decay, 

deposition and transport of organic and inorganic gas-phase and particle-phase pollutants in the 

atmosphere. We used CMAQ v5.0.1 which reflects updates to version 4.7 to improve the 

underlying science. Section 7.2.3 of this RIA discusses the chemical mechanism and SOA 

formation. 

7.2.2.2 Model Domain and Configuration 

The CMAQ modeling domain encompasses all of the lower 48 States and portions of 

Canada and Mexico. The modeling domain is made up of a large continental U.S. 36 kilometer 

(km) grid and a 12 km grid as shown in Figure 7-11. The modeling domain contains 25 vertical 

layers with the top of the modeling domain at about 17,600 meters, or 50 millibars (mb) of 

atmospheric pressure. 

 

N

 CMAQ version 5.0.1 was released on October 19, 2011. It is available from the Community Modeling and 

Analysis System (CMAS) as well as previous peer-review reports at: http://www.cmascenter.org. 
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Figure 7-11 Map of the CMAQ Modeling Domain 

7.2.2.3 Model Inputs 

The key inputs to the CMAQ model include emissions from anthropogenic and biogenic 

sources, meteorological data, and initial and boundary conditions. The CMAQ meteorological 

input files were derived from simulations of the Weather Research and Forecasting Model 

(WRF) version 3.3, Advanced Research WRF (ARW) core 58 for the entire year of 2007 over 

model domains that are slightly larger than those shown in Figure 7-11. Previous CMAQ annual 

simulations have typically utilized meteorology provided by the 5th Generation Mesoscale 

Model (MM5).59 The WRF Model is a next-generation mesoscale numerical weather prediction 

system developed for both operational forecasting and atmospheric research applications 

(http://wrf-model.org). The meteorology for the national 36 km grid and 12 km grid were 

developed by EPA and are described in more detail within the AQM TSD. The meteorological 

outputs from WRF were processed to create model-ready inputs for CMAQ using the 

Meteorology-Chemistry Interface Processor (MCIP) version 4.1.2. Outputs include: horizontal 

wind components (i.e., speed and direction), temperature, moisture, vertical diffusion rates, and 

rainfall rates for each grid cell in each vertical layer.60

The lateral boundary and initial species concentrations are provided by a threedimensional global atmospheric chemistry model, the GEOS-CHEM model (standard version 8-

03-02 with version 8-02-03 chemistry).61 The global GEOS-CHEM model simulates 

atmospheric chemical and physical processes driven by assimilated meteorological observations 

from the NASA’s Goddard Earth Observing System (GEOS). This model was run for 2007 with 

a grid resolution of 2 degree x 2.5 degree (latitude-longitude) and 46 vertical layers up to 0.01 

hPa. The predictions were used to provide one-way dynamic boundary conditions at three-hour 

intervals and an initial concentration field for the 36 km CMAQ simulations. The future base 
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conditions from the 36 km coarse grid modeling were used as the initial/boundary state for all 

subsequent 12 km finer grid modeling. 

The emissions inputs used for the 2007 base year and each of the future year base cases 

and control scenarios analyzed for this rule are summarized in Section 7.1.2 of this RIA. 

7.2.2.4 CMAQ Evaluation 

An operational model performance evaluation for ozone, PM2.5 and its related speciated 

components (e.g., sulfate, nitrate, elemental carbon, organic carbon, etc.), nitrate and sulfate 

deposition, and specific air toxics (formaldehyde, acetaldehyde, benzene, 1,3-butadiene, and 

acrolein) was conducted using 2007 state/local monitoring data in order to estimate the ability of 

the CMAQ modeling system to replicate base year concentrations. Model performance statistics 

were calculated for observed/predicted pairs of daily/monthly/seasonal/annual concentrations. 

Statistics were generated for five large subregions:O Midwest, Northeast, Southeast, Central, and 

West U.S. The “acceptability” of model performance was judged by comparing our results to 

those found in recent regional PM2.5 model applications for other, non-EPA studies.P Overall, 

the performance for the 2007 modeling platform is within the range or close to that of these other 

applications. The model was able to reproduce historical concentrations of ozone and PM2.5 over 

land with low bias and error results. Model predictions of annual formaldehyde, acetaldehyde 

and benzene showed relatively small bias and error results when compared to observations. The 

model yielded larger bias and error results for 1,3 butadiene and acrolein based on limited 

monitoring sites. A more detailed summary of the 2007 CMAQ model performance evaluation 

is available within the AQM TSD found in the docket of this rule. 

7.2.2.5 Model Simulation Scenarios 

As part of our analysis for this rulemaking, the CMAQ modeling system was used to 

calculate 8-hour ozone concentrations, daily and annual PM2.5 concentrations, annual NO2

concentrations, annual and seasonal (summer and winter) air toxics concentrations, visibility 

levels and annual nitrogen and sulfur deposition total levels for each of the following emissions 

scenarios: 

- 2007 base year 

- 2018 Tier 3 reference case 

- 2018 Tier 3 control case 

- 2030 Tier 3 reference case 

 

O

 The subregions are defined by States where: Midwest is IL, IN, MI, OH, and WI; Northeast is CT, DE, 

MA, MD, ME, NH, NJ, NY, PA, RI, and VT; Southeast is AL, FL, GA, KY, MS, NC, SC, TN, VA, and 

WV; Central is AR, IA, KS, LA, MN, MO, NE, OK, and TX; West is AK, CA, OR, WA, AZ, NM, CO, UT, WY, 

SD, ND, MT, ID, and NV. 

P These other modeling studies represent a wide range of modeling analyses which cover various models, model 

configurations, domains, years and/or episodes, chemical mechanisms, and aerosol modules. 
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- 2030 Tier 3 control case 

The emission inventories used in the air quality and benefits modeling are different from 

the rule inventories due to the considerable length of time required to conduct the modeling. As 

noted above, emission inventories for air quality modeling were required for the entire U.S. by 

12 km grid cell and hour of the day for each day of the year, requiring a methodology of much 

greater detail than the national emission inventories presented in Section 7.1. While most of the 

modeling tools and inputs used for estimating national emission inventories were also used in 

developing inputs for air quality modeling as well, the application of these tools (particularly 

MOVES) to produce the gridded / hourly emissions was quite different, and in essence a separate 

analysis. As explained in Section 7.2.1.1, the different analyses generated different onroad 

inventory totals, but the reduction from reference to control scenarios was consistent. The 

emission inventories used for air quality modeling are discussed in Section 7.2.1 of this RIA. 

The emissions modeling TSD, found in the docket for this rule (EPA-HQ-OAR-2011-0135),

contains a detailed discussion of the emissions inputs used in our air quality modeling. 

We use the predictions from the model in a relative sense by combining the 2007 baseyear predictions with predictions from each future-year scenario and applying these modeled 

ratios to ambient air quality observations to estimate 8-hour ozone concentrations, daily and 

annual PM2.5 concentrations, annual NO2 concentrations and visibility impairment for each of the 

2018 and 2030 scenarios. The ambient air quality observations are average conditions, on a siteby-site basis, for a period centered around the model base year (i.e., 2005-2009). 

The projected daily and annual PM2.5 design values were calculated using the Speciated 

Modeled Attainment Test (SMAT) approach. The SMAT uses a Federal Reference Method 

(FRM) mass construction methodology that results in reduced nitrates (relative to the amount 

measured by routine speciation networks), higher mass associated with sulfates (reflecting water 

included in FRM measurements), and a measure of organic carbonaceous mass that is derived 

from the difference between measured PM2.5 and its non-carbon components. This 

characterization of PM2.5 mass also reflects crustal material and other minor constituents. The 

resulting characterization provides a complete mass balance. It does not have any unknown 

mass that is sometimes presented as the difference between measured PM2.5 mass and the 

characterized chemical components derived from routine speciation measurements. However, 

the assumption that all mass difference is organic carbon has not been validated in many areas of 

the U.S. The SMAT methodology uses the following PM2.5 species components: sulfates, 

nitrates, ammonium, organic carbon mass, elemental carbon, crustal, water, and blank mass (a 

fixed value of 0.5 μg/m3). More complete details of the SMAT procedures can be found in the 

report "Procedures for Estimating Future PM2.5 Values for the CAIR Final Rule by Application 

of the (Revised) Speciated Modeled Attainment Test (SMAT)".62 For this latest analysis, several 

datasets and techniques were updated. These changes are fully described within the technical 

support document for the Final Transport Rule AQM TSD.63 The projected 8-hour ozone design 

values were calculated using the approach identified in EPA's guidance on air quality modeling 

attainment demonstrations.64 

Additionally, we conducted an analysis to compare the absolute and percent differences 

between the future year reference and control cases for annual and seasonal ethanol, 

formaldehyde, acetaldehyde, benzene, 1,3-butadiene, naphthalene, and acrolein, as well as 
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annual nitrate and sulfate deposition. These data were not compared in a relative sense due to 

the limited observational data available. 

7.2.3 Chemical Mechanisms in Modeling 

This rule presents inventories for NOX, VOC, CO, PM2.5, SO2, NH3, and seven air 

toxics: benzene, 1,3-butadiene, formaldehyde, acetaldehyde, ethanol, naphthalene and acrolein. 

The air toxics were added as explicit model species to the carbon bond 5 (CB05) mechanisms 

used in CMAQv5.0.1.65 Emissions of all the pollutants included in the rule inventories, except 

ethanol, were generated using the Motor Vehicle Emissions Simulator (MOVES) VOC 

emissions and toxic-to-VOC ratios calculated using EPAct data.66

 Ethanol emissions for air 

quality modeling were based on speciation of VOC using different ethanol profiles (E0, E10 and 

E85) (see Section 7.2.1.5 for more information). In addition to direct emissions, photochemical 

processes mechanisms are responsible for formation of some of these compounds in the 

atmosphere from precursor emissions. For some pollutants such as PM, formaldehyde, and 

acetaldehyde, many photochemical processes are involved. CMAQ therefore also requires 

inventories for a large number of other air toxics and precursor pollutants. Methods used to 

develop the air quality inventories can be found in Section 7.2.1.

 In the CB05 mechanism, the chemistry of thousands of different VOCs in the 

atmosphere are represented by a much smaller number of model species which characterize the 

general behavior of a subset of chemical bond types; this condensation is necessary to allow the 

use of complex photochemistry in a fully 3-D air quality model.67

Complete combustion of ethanol in fuel produces carbon dioxide (CO2) and water (H2O). 

Incomplete combustion results in the production of other air pollutants, such as acetaldehyde and 

other aldehydes, and the release of unburned ethanol. Ethanol is also present in evaporative 

emissions. In the atmosphere, ethanol from unburned fuel and evaporative emissions can 

undergo photodegradation to form aldehydes (acetaldehyde and formaldehyde) and peroxyacetyl 

nitrate (PAN), and also plays a role in ground-level ozone formation. Mechanisms for these 

reactions are included in CMAQ. Additionally, alkenes and other hydrocarbons are considered 

because any increase in acetyl peroxy radicals due to ethanol increases might be counterbalanced 

by a decrease in radicals resulting from decreases in other hydrocarbons. 

CMAQ includes 63 inorganic reactions to account for the cycling of all relevant oxidized 

nitrogen species and cycling of radicals, including the termination of NO2 and formation of nitric 

acid (HNO3) without PAN formation.Q

NO2 + ∙OH + M → HNO3 + M k = 1.19 x 10-11 cm3molecule-1s

-1

 

68

The CB05 mechanism also includes more than 90 organic reactions that include alternate 

pathways for the formation of acetyl peroxy radical, such as by reaction of ethene and other 

alkenes, alkanes, and aromatics. Alternate reactions of acetyl peroxy radical, such as oxidation 

of NO to form NO2, which again leads to ozone formation, are also included. 

 

Q

 All rate coefficients are listed at 298 K and, if applicable, 1 bar of air. 
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Atmospheric reactions and chemical mechanisms involving several key formation 

pathways are discussed in more detail in the following sections. 

7.2.3.1 Acetaldehyde 

Acetaldehyde is the main photodegradation product of ethanol, as well as other precursor 

hydrocarbons. Acetaldehyde is also a product of fuel combustion. In the atmosphere, 

acetaldehyde can react with the OH radical and O2 to form the acetyl peroxy radical 

[CH3C(O)OO∙].

R

 When NOX is present in the atmosphere this radical species can then further 

react with nitric oxide (NO), to produce formaldehyde (HCHO), or with nitrogen dioxide (NO2), 

to produce PAN [CH3C(O)OONO2]. An overview of these reactions and the corresponding 

reaction rates are provided below. S

CH3CHO + ∙OH → CH3C∙O + H2O k = 1.5 x 10-11 cm3molecule-1s

-1 69

CH3C∙O + O2 + M → CH3C(O)OO∙ + M 

CH3C(O)OO∙ + NO → CH3C(O)O∙ + NO2 k = 2.0 x 10-11 cm3molecule-1s

-1

 

70

CH3C(O)O∙ → ∙CH3 + CO2 

∙CH3 + O2 + M → CH3OO∙ + M 

CH3OO∙ + NO → CH3O∙ + NO2

CH3O∙ + O2 → HCHO + HO2

CH3C(O)OO∙ + NO2 + M → CH3C(O)OONO2 + M k = 1.0 x 10-11 cm3molecule-1s

-1

 

71

Acetaldehyde can react with the NO3 radical, ground state oxygen atom (O3P) and 

chlorine, although these reactions are much slower. Acetaldehyde can also photolyze (hν), 

which predominantly produces ∙CH3 (which reacts as shown above to form CH3OO∙) and HCO 

(which rapidly forms HO2 and CO): 

CH3CHO + hν +2 O2 → CH3OO∙ +HO2 + CO = 240-380 nm 72

As mentioned above, CH3OO∙ can react in the atmosphere to produce formaldehyde 

(HCHO). Formaldehyde is also a product of hydrocarbon combustion. In the atmosphere, the 

most important reactions of formaldehyde are photolysis and reaction with the OH, with 

atmospheric lifetimes of approximately 3 hours and 13 hours, respectively.73

 Formaldehyde can 

also react with NO3 radical, ground state oxygen atom (O3P) and chlorine, although these 

reactions are much slower. Formaldehyde is removed mainly by photolysis whereas the higher 

 

R

 Acetaldehyde is not the only source of acetyl peroxy radicals in the atmosphere. For example, dicarbonyl 

compounds (methylglyoxal, biacetyl, and others) also form acetyl radicals, which can further react to form 

peroxyacetyl nitrate (PAN). 

S

 All rate coefficients are listed at 298 K and, if applicable, 1 bar of air. 
7-70

aldehydes, those with two or more carbons such as acetaldehyde, react predominantly with OH 

radicals. The photolysis of formaldehyde is an important source of new hydroperoxy radicals 

(HO2), which can lead to ozone formation and regenerate OH radicals. 

HCHO + hν + 2 O2 → 2 HO2 + CO = 240-360 nm 74

HO2 + NO → NO2+ OH 

Photolysis of HCHO can also proceed by a competing pathway which makes only stable 

products: H2 and CO. 

CB05 mechanisms for acetaldehyde formation warrant a detailed discussion given the 

increase in vehicle and engine exhaust emissions for this pollutant and ethanol, which can form 

acetaldehyde in the air. Acetaldehyde is represented explicitly in the CB05 chemical 

mechanism75,76 by the ALD2 model species, which can be both formed from other VOCs and can 

decay via reactions with oxidants and radicals. The reaction rates for acetaldehyde, as well as for 

the inorganic reactions that produce and cycle radicals, and the representative reactions of other 

VOCs have all been updated to be consistent with recommendations in the literature.77

The decay reactions of acetaldehyde are fewer in number and can be characterized well 

because they are explicit representations. In CB05, acetaldehyde can photolyze in the presence 

of sunlight or react with molecular oxygen (O (

3

P)), hydroxyl radical (OH), or nitrate radicals. 

The reaction rates are based on expert recommendations,78 and the photolysis rate is from 

IUPAC recommendations. 

In CMAQ v5.0, the acetaldehyde that is formed from photochemical reactions is tracked 

separately from that which is due to direct emission and transport of direct emissions. In CB05, 

there are 25 different reactions that form acetaldehyde in molar yields ranging from 0.02 (ozone 

reacting with lumped products from isoprene oxidation) to 2.0 (cross reaction of acylperoxy 

radicals, CXO3). The specific parent VOCs that contribute the most to acetaldehyde 

concentrations vary spatially and temporally depending on characteristics of the ambient air, but 

alkenes in particular are found to play a large role.79 The IOLE model species, which represents 

internal carbon-carbon double bonds, has high emissions and relatively high yields of 

acetaldehyde. The OLE model species, representing terminal carbon double bonds, also plays a 

role because it has high emissions although lower acetaldehyde yields. Production from 

peroxyproprional nitrate and other peroxyacylnitrates (PANX) and aldehydes with 3 or more 

carbon atoms can in some instances increase acetaldehyde, but because they also are a sink of 

radicals, their effect is smaller. Thus, the amount of acetaldehyde (and formaldehyde as well) 

formed in the ambient air, as well as emitted in the exhaust (the latter being accounted for in 

emission inventories), is affected by changes in these precursor compounds due to the addition of 

ethanol to fuels (e.g., decreases in alkenes would cause some decrease of acetaldehyde, and to a 

larger extent, formaldehyde). 

The reaction of ethanol (CH3CH2OH) with OH is slower than some other important 

reactions but can be an important source of acetaldehyde if the emissions are large. Based on 

kinetic data for molecular reactions, the only important chemical loss process for ethanol (and 

other alcohols) is reaction with the hydroxyl radical (∙OH).80 This reaction produces 
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acetaldehyde (CH3CHO) with a 90 percent yield.81 The lifetime of ethanol in the atmosphere can 

be calculated from the rate coefficient, k, and due to reaction with the OH radical, occurs on the 

order of a day in polluted urban areas or several days in unpolluted areas. T For example, an 

atmospheric lifetime for acetaldehyde under nominal oxidant conditions, OH of 1.0 x 10-6 

cm3molecule-1s

-1, would be 3.5 days. 

In CB05, reaction of one molecule of ethanol yields 0.90 molecules of acetaldehyde. It 

assumes the majority of the reaction occurs through H-atom abstraction of the more weaklybonded methylene group, which reacts with oxygen to form acetaldehyde and hydroperoxy 

radical (HO2), and the remainder of the reaction occurs at the –CH3 and –OH groups, creating 

formaldehyde (HCHO), oxidizing NO to NO2 (represented by model species XO2) and creating 

glycoaldehyde, which is represented as ALDX: 

CH3CHOH + OH → HO2 + 0.90 CH3CHO + 0.05 ALDX + 0.10 HCHO + 0.10 XO2

7.2.3.2 Secondary Organic Aerosols (SOA) 

Secondary organic aerosol (SOA) chemistry research described below has led to 

implementation of new pathways for secondary organic aerosol (SOA) in CMAQ v5.0, based on 

recommendations of Edney et al. (2007) and Carlton et al. (2008).82, 83 In previous versions of 

CMAQ, all SOA was semivolatile and resulted from the oxidation of compounds emitted entirely 

in the gas-phase. In CMAQ v5.0, parameters in existing pathways were revised and new 

formation mechanisms were added. Some of the new pathways, such as low-NOX oxidation of 

aromatics and particle-phase oligomerization, result in nonvolatile SOA. 

Organic aerosol (OA) can be classified as either primary or secondary depending on 

whether it is emitted into the atmosphere as a particle (primary organic aerosol, POA) or formed 

in the atmosphere (SOA). SOA precursors include volatile organic compounds (VOCs) as well 

as low-volatility compounds that can react to form even lower volatility compounds. Current 

research suggests SOA contributes significantly to ambient OA concentrations, and in Southeast 

and Midwest States may make up more than 50 percent (although the contribution varies from 

area to area) of the organic fraction of PM2.5 during the summer (but less in the winter).84,85

 A 

wide range of laboratory studies conducted over the past twenty years show that anthropogenic 

aromatic hydrocarbons and long-chain alkanes, along with biogenic isoprene, monoterpenes, and 

sesquiterpenes, contribute to SOA formation.86,87,88,89,90

 Modeling studies, as well as carbon 

isotope measurements, indicate that a significant fraction of SOA results from the oxidation of 

biogenic hydrocarbons.91,92

 Based on parameters derived from laboratory chamber experiments, 

SOA chemical mechanisms have been developed and integrated into air quality models such as 

the CMAQ model and have been used to predict OA concentrations.93

 

Over the past 10 years, ambient OA concentrations have been routinely measured in the 

U.S. and some of these data have been used to determine, by employing source/receptor 

methods, the contributions of the major OA sources, including biomass burning and vehicular 

gasoline and diesel exhaust. Since mobile sources are a significant source of VOC emissions, 

 

T

 All rate coefficients are listed at 298 K and, if applicable, 1 bar of air. 
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currently accounting for almost 40 percent of anthropogenic VOC,94 mobile sources are also an 

important source of SOA, particularly in populated areas. 

Toluene is an important contributor to anthropogenic SOA.95,96 Mobile sources are the 

most significant contributor to ambient toluene concentrations as shown by analyses done for the 

2005 National Air Toxics Assessment (NATA)97 and the Mobile Source Air Toxics (MSAT) 

Rule.98 The 2005 NATA indicates that onroad and nonroad mobile sources accounted for almost 

60 percent (1.46 μg/m3) of the total average nationwide ambient concentration of toluene (2.48

μg/m3), when the contribution of the estimated “background” is apportioned among source 

sectors. 

The amount of toluene in gasoline influences the amount of toluene emitted in vehicle 

exhaust and evaporative emissions, although, like benzene, some toluene is formed in the 

combustion process. In turn, levels of toluene and other aromatics in gasoline are potentially 

influenced by the amount of ethanol blended into the fuel. Due to the high octane quality of 

ethanol, it greatly reduces the need for and levels of other high-octane components such as 

aromatics including toluene (which is the major aromatic compound in gasoline). Since toluene 

contributes to SOA and the toluene level of gasoline is decreasing, it is important to assess the 

effect of these reductions on ambient PM. 

In addition to toluene, other mobile-source hydrocarbons such as benzene, xylene, and 

alkanes form SOA. Similar to toluene, the SOA produced by benzene and xylene from low-NOX

pathways is expected to be less volatile and be produced in higher yields than SOA from highNOX conditions.99 Oxidation of alkanes with longer chains as well as cyclic alkanes form SOA 

with relatively higher yields than small straight-chain alkanes.100

It is unlikely that ethanol would form SOA directly or affect SOA formation indirectly 

through changes in the radical populations due to increasing ethanol exhaust. Nevertheless, 

scientists at the U.S. EPA’s Office of Research and Development recently directed experiments 

to investigate ethanol’s SOA forming potential.101 The experiments were conducted under 

conditions where peroxy radical reactions would dominate over reaction with NO (i.e., 

irradiations performed in the absence of NOX and OH produced from the photolysis of hydrogen 

peroxide). This was the most likely scenario under which SOA formation could occur, since a 

highly oxygenated C4 organic could form. As expected, no SOA was produced. From these 

experiments, the upper limit for the aerosol yield is less than 0.01 percent based on scanning 

mobility particle sizer (SMPS) data. Given the lack of aerosol formation found in these initial 

smog chamber experiments, these data were not published. 

In general, measurements of OA represent the sum of POA and SOA and the fraction of 

aerosol that is secondary in nature can only be estimated. One of the most widely applied method 

of estimating total ambient SOA concentrations is the EC tracer method using ambient data 

which estimates the OC/EC ratio in primary source emissions.102,103

 SOA concentrations have 

also been estimated using OM (organic mass) to OC (organic carbon) ratios, which can indicate 

that SOA formation has occurred, or by subtracting the source/receptor-based total POA from the 

measured OC concentration.104 Aerosol mass spectrometer (AMS) measurements along with 

positive matrix factorization (PMF) can also be used to identify surrogates for POA and SOA in 

ambient as well as chamber experiments. Such methods, however, may not be quantitatively 
7-73

accurate and provide no information on the contribution of individual biogenic and 

anthropogenic SOA sources, which is critical information needed to assess the impact of specific 

sources and the associated health risk. These methods assume that OM containing additional 

mass from oxidation of OC comes about largely (or solely) from SOA formation. In particular, 

the contributions of anthropogenic SOA sources, including those of aromatic precursors, are 

required to determine exposures and risks associated with replacing fossil fuels with biofuels. 

Upon release into the atmosphere, numerous VOC compounds can react with free 

radicals in the atmosphere to form SOA. While this has been investigated in the laboratory, there 

is relatively little information available on the specific chemical composition of SOA compounds 

themselves from specific VOC precursors. This absence of complete compositional data from 

the precursors has made the identification of aromatically-derived SOA in ambient samples 

challenging, which in turn has prevented observation-based measurements of individual SOA 

source contributions to ambient PM levels. 

As a first step in estimating ambient SOA concentrations, EPA has developed a tracerbased method.105,106

 The method is based on using mass fractions of SOA tracer compounds, 

measured in smog chamber-generated SOA samples, to convert ambient concentrations of SOA 

tracer compounds to ambient SOA concentrations. This method consists of irradiating the SOA 

precursor of interest in a smog chamber in the presence of NOX, collecting the SOA produced on 

filters, and then analyzing the samples for highly polar compounds using advanced analytical 

chemistry methods. Employing this method, candidate tracers have been identified for several 

VOC compounds which are emitted in significant quantities and known to produce SOA in the 

atmosphere. Some of these SOA-forming compounds include toluene, a variety of 

monoterpenes, isoprene, and β-caryophyllene, the latter three of which are emitted by vegetation 

and are more significant sources of SOA than toluene. Smog chamber work can also be used to 

investigate SOA chemical formation mechanisms.107,108,109,110

Although these concentrations are only estimates, due to the assumption that the mass 

fractions of the smog chamber SOA samples using these tracers are equal to those in the ambient 

atmosphere, there are presently no other means available for estimating the SOA concentrations 

originating from individual SOA precursors. Among the tracer compounds observed in ambient 

PM2.5 samples are two tracer compounds that have been identified in smog chamber aromatic 

SOA samples.111

 To date, these aromatic tracer compounds have been identified in the 

laboratory for toluene and m-xylene SOA. Additional work is underway by the EPA to 

determine whether these tracers are also formed by benzene and other alkylbenzenes (including 

o-xylene, p-xylene, 1,2,4-trimethylbenzene, and ethylbenzene). 

One caveat regarding this work is that a large number of VOCs emitted into the 

atmosphere, which have the potential to form SOA, have not yet been studied in environmental 

smog chambers. These unstudied compounds could produce SOA species that are being used as 

tracers for other VOCs thus overestimating the amount of SOA formed in the atmosphere by the 

VOCs studied to date. This approach may also estimate entire hydrocarbon classes (e.g., all 

methylsubstituted-monoaromatics or all monoterpenes) and not individual precursor 

hydrocarbons. Thus the tracers could be broadly representative and not indicative of individual 

precursors. This is still unknown. Also, anthropogenic precursors play a role in formation of 

atmospheric radicals and aerosol acidity, and these factors influence SOA formation from 
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biogenic hydrocarbons.112,113 This anthropogenic and biogenic interaction, important to EPA and 

others, needs further study. The issue of SOA formation from aromatic precursors is an 

important one to which EPA and others are paying significant attention. 

The aromatic tracer compounds and their mass fractions have been used to estimate 

monthly ambient aromatic SOA concentrations from March 2004 to February 2005 in five U.S. 

Midwestern cities.114 The annual tracer-based SOA concentration estimates were 0.15, 0.18, 

0.13, 0.15, and 0.19 μg carbon/m3for Bondville, IL, East St. Louis, IL, Northbrook, IL, 

Cincinnati, OH and Detroit, MI, respectively, with the highest concentrations occurring in the 

summer. On average, the aromatic SOA concentrations made up 17 percent of the total SOA 

concentration. Thus, this work suggests that we are finding ambient PM levels on an annual 

basis of about 0.15 μg/m3associated with present toluene levels in the ambient air in these 

Midwest cities. Based on preliminary analysis of recent laboratory experiments, it appears the 

toluene tracer could also be formed during photooxidation of some of the xylenes.115

Over the past decade a variety of modeling studies have been conducted to predict 

ambient SOA levels. While early studies focused on the contribution of biogenic monoterpenes, 

additional precursors, such as sesquiterpenes, isoprene, benzene, toluene, and xylene, have been 

implemented in atmospheric models such as GEOS-Chem, PMCAMx, and CMAQ.116, 117, 118, 119, 

120,121,122

 Studies have indicated that ambient OC levels may be underestimated by current model 

parameterizations.123 While the treatment of new precursors has likely reduced the 

model/measurement bias, underestimates can persist.124 In general, modeling studies focus on 

comparing the sum of the POA and SOA concentrations with ambient OC or estimated OA 

concentrations. Without a method to attribute measured OC to different sources or precursors, 

identifying causes of the underestimates in modeled OC via model/measurement comparisons 

can be challenging. Oxidation of low-volatility organic compounds as well as particle-phase 

reactions resulting from acidity have been explored as potential missing sources of OC in 

models.125,126

7.2.3.3 Ozone 

As mentioned above, the addition of ethanol to fuels has been shown to contribute to 

PAN formation and this is one way for it to contribute therefore to ground-level ozone formation 

downwind of NOX sources. PAN is a reservoir and carrier of NOX and is the product of acetyl 

radicals reacting with NO2 in the atmosphere. One source of PAN is the photooxidation of 

acetaldehyde (Section 7.2.3.1), but many VOCs have the potential for forming acetyl radicals 

and therefore PAN or a PAN-type compound.U

 PAN can undergo thermal decomposition with a 

lifetime of approximately 1 hour at 298K or 148 days at 250K. V

CH3C(O)OONO2 + M → CH3C(O)OO∙ + NO2 + M k = 3.3 x 10-4 s

-1 127

 

U

 Many aromatic hydrocarbons, particularly those present in high percentages in gasoline (toluene, m-, o-, p-xylene, 

and 1,3,5-, 1,2,4-trimethylbenzene), form methylglyoxal and biacetyl, which are also strong generators of acetyl 

radicals (Smith, D.F., T.E. Kleindienst, C.D. McIver (1999) Primary product distribution from the reaction of OH 

with m-, p-xylene and 1,2,4- and 1,3,5-Trimethylbenzene. J. Atmos. Chem., 34: 339- 364.). 

V

 All rate coefficients are listed at 298 K and, if applicable, 1 bar of air. 
7-75

The reaction above shows how NO2 is released in the thermal decomposition of PAN,

along with a peroxy radical which can oxidize NO to NO2 as previously shown in Section 

7.2.3.1. NO2 can also be formed in photochemical reactions where NO is converted to NO2 (see 

OH radical reaction of acetaldehyde in Section 7.2.3.1). In both cases, NO2 further photolyzes to 

produce ozone (O3).

NO2 + hν → NO + O(3P) = 300-800 nm 128

O(3P) + O2 + M → O3 + M 

The temperature sensitivity of PAN allows it to be stable enough at low temperatures to 

be transported long distances before decomposing to release NO2. NO2 can then participate in 

ozone formation in regions remote from the original NOX source.129 A discussion of CB05 

mechanisms for ozone formation can be found in Yarwood et al. (2005).130

Another important way that ethanol fuels contribute to ozone formation is by increasing 

the formation of new radicals through increases in formaldehyde and acetaldehyde. As shown in 

Section 7.2.3.1, the photolysis of both aldehydes results in up to two molecules of either 

hydroperoxy radical or methylperoxy radical, both of which oxidize NO to NO2 leading to ozone 

formation. 

7.2.3.4 Uncertainties Associated with Chemical Mechanisms 

A key source of uncertainty with respect to the air quality modeling results is the 

photochemical mechanisms in CMAQ v5.0. Pollutants such as ozone, PM, acetaldehyde, 

formaldehyde, and acrolein can be formed secondarily through atmospheric chemical processes. 

Since secondarily formed pollutants can result from many different reaction pathways, there are 

uncertainties associated with each pathway. Simplifications of chemistry must be made in order 

to handle reactions of thousands of chemicals in the atmosphere. Mechanisms for formation of 

ozone, PM, acetaldehyde and peroxyacetyl nitrate (PAN) are discussed in Section 7.2.3. 

For PM, there are a number of uncertainties associated with SOA formation that should 

be addressed explicitly. As mentioned in Section 7.2.3, a large number of VOCs emitted into the 

atmosphere, which have the potential to form SOA, have not yet been studied in detail. Not only 

have known VOCs not been studied in detail, but unknown (or unmeasured) VOCs can also 

produce SOA. This makes reconciling SOA from combustion sources extremely difficult. In 

addition, the amount of ambient SOA that comes from benzene is uncertain. Simplifications to 

the SOA treatment in CMAQ have also been made in order to preserve computational efficiency. 

These simplifications are described in release notes for CMAQ 4.7 on the Community Modeling 

and Analysis System (CMAS) website.131

7.2.4 Impacts of the Rule on Air Quality 

Air quality modeling performed for this rule estimates the changes in ambient 

concentrations of PM2.5, ozone and NO2, as well as changes in ambient concentrations of ethanol 

and the following air toxics: acetaldehyde, acrolein, benzene, 1,3-butadiene, naphthalene, and 
7-76

formaldehyde. The air quality modeling results also include changes in deposition of nitrogen 

and sulfur and changes in visibility levels due to this rule. 

This section describes current ambient levels of the modeled pollutants and presents the 

projected future ambient levels resulting from the rule. 

7.2.4.1 Ozone 

As described in Section 6.1.2 of this RIA, ozone causes adverse health effects, and the 

EPA has set national ambient air quality standards (NAAQS) to protect against those health 

effects. In this section, we present information on current and model-projected future ozone 

levels. 

7.2.4.1.1 Current Concentrations of Ozone 

Figure 7-12 shows a snapshot of measured ozone concentrations in 2010. The highest 

ozone concentrations were located in California. 
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Figure 7-12 Ozone Concentrations (fourth highest daily maximum 8-hour concentration) in 

ppm for 2010W

The primary and secondary NAAQS for ozone are 8-hour standards with a level of 0.075 

ppm. The most recent revision to the ozone standards was in 2008; the previous 8-hour ozone 

standards, set in 1997, had a level of 0.08 ppm. In 2004, the U.S. EPA designated nonattainment 

areas for the 1997 8-hour ozone NAAQS (69 FR 23858, April 30, 2004).X As of December 5, 

2013, there were 39 8-hour ozone nonattainment areas for the 1997 ozone NAAQS, composed of 

216 full or partial counties, with a total population of over 112 million. Nonattainment areas for 

the 1997 8-hour ozone NAAQS are pictured in Figure 7-13. Nonattainment designations for the 

2008 ozone standards were finalized on April 30, 2012 and May 31, 2012.132 As of December 5, 

2013, there were 46 ozone nonattainment areas for the 2008 ozone NAAQS, composed of 227 

full or partial counties, with a population of over 123 million. Nonattainment areas for the 2008 

 

W From U.S. EPA, 2011. Our Nation’s Air: Status and Trends through 2010. EPA-454/R-12-001. February 2012. 

Available at: http://www.epa.gov/airtrends/2011/. 

X

 A nonattainment area is defined in the Clean Air Act (CAA) as an area that is violating an ambient standard or is 

contributing to a nearby area that is violating the standard. 
7-78

ozone NAAQS are pictured in Figure 7-14. As of December 5, 2013, over 135 million people 

are living in ozone nonattainment areas.Y

Figure 7-13 1997 8-hour Ozone Nonattainment Areas 

 

Y

 The 135 million total is calculated by summing, without double counting, the 1997 and 2008 ozone nonattainment 

populations contained in the Summary Nonattainment Area Population Exposure report 

(http://www.epa.gov/oar/oaqps/greenbk/popexp.html). If there is a population associated with both the 1997 and 

2008 nonattainment areas, and they are not the same, then the larger of the two populations is included in the sum. 
7-79

Figure 7-14 2008 8-hour Ozone Nonattainment Areas 

States with ozone nonattainment areas are required to take action to bring those areas into 

attainment. The attainment date assigned to an ozone nonattainment area is based on the area’s 

classification. Most ozone nonattainment areas were required to attain the 1997 8-hour ozone 

NAAQS in the 2007 to 2013 time frame and then to maintain it thereafter.Z

 The attainment dates 

for areas designated nonattainment for the 2008 8-hour ozone NAAQS are in the 2015 to 2032 

timeframe, depending on the severity of the problem in each area. In addition, EPA is currently 

working on a review of the ozone NAAQS. If EPA revises the ozone standards pursuant to that 

review, the attainment dates associated with areas designated nonattainment for that NAAQS 

would be 5 or more years after the final rule is promulgated, depending on the severity of the 

problem in each area. 

7.2.4.1.2 Projected Concentrations of Ozone Without the Rule 

EPA has already adopted many mobile source emission control programs that are 

expected to reduce ambient ozone levels. These control programs include the Heavy-Duty 

 

Z

 The Los Angeles South Coast Air Basin 8-hour ozone nonattainment area and the San Joaquin Valley Air Basin 8-

hour ozone nonattainment area are designated as Extreme and will have to attain before June 15, 2024. The 

Sacramento, Coachella Valley, Western Mojave and Houston 8-hour ozone nonattainment areas are designated as 

Severe and will have to attain by June 15, 2019. 
7-80

Greenhouse Gas Rule (76 FR 57106, September 15, 2011), New Marine Compression-Ignition 

Engines at or Above 30 Liters per Cylinder Rule (75 FR 22895, April 30, 2010), the Marine 

Spark-Ignition and Small Spark-Ignition Engine Rule (73 FR 59034, October 8, 2008), the 

Locomotive and Marine Rule (73 FR 25098, May 6, 2008), the Clean Air Nonroad Diesel Rule 

(69 FR 38957, June 29, 2004), the Heavy-Duty Engine and Vehicle Standards and Highway 

Diesel Fuel Sulfur Control Requirements (66 FR 5002, January 18, 2001) and the Tier 2 Motor 

Vehicle Emissions Standards and Gasoline Sulfur Control Requirements (65 FR 6698, February 

10, 2000). As a result of these and other federal, state and local programs, 8-hour ozone levels 

are expected to improve in the future. However, even with the implementation of all current 

state and federal regulations, there are projected to be counties violating the ozone NAAQS well 

into the future. Thus additional federal control programs, such as Tier 3, can assist areas with 

attainment dates in 2017 and beyond in attaining the NAAQS as expeditiously as practicable and 

may relieve areas with already stringent local regulations from some of the burden associated 

with adopting additional local controls. 

The air quality modeling projects that in 2018, with all current controls in effect but 

excluding the emissions changes expected to occur as a result of this action or any other 

additional controls, at least 19 counties, with a projected population of over 37 million people,

will have projected design values above the level of the 2008 8-hour ozone standard of 75 ppb. 

Even in 2030 the modeling projects there will be 6 counties with a population of over 19 million 

people that will have projected design values above the level of the 2008 8-hour ozone standard 

of 75 ppb without additional controls. Since the emission changes from this rule go into effect 

during the period when some areas are still working to attain the ozone NAAQS, the projected 

emission changes will help state and local agencies in their effort to attain and maintain the 

ozone standard. In the following section we discuss the projected ozone reductions associated 

with the standards. 

7.2.4.1.1 Projected Concentrations of Ozone With the Rule 

This section summarizes the results of our modeling of ozone air quality impacts in the 

future with the standards. Specifically, for the years 2018 and 2030 we compare a reference 

scenario (a scenario without the standards) to a control scenario that includes the standards. Our 

modeling indicates that ozone design value concentrations will decrease dramatically in many 

areas of the country as a result of this rule rule. Additional information on the emissions 

reductions that are projected with this final action is available in Section 7.2.1 of this RIA. 

Figure 7-15 and Figure 7-16 present the changes in 8-hour ozone design value 

concentrations in 2018 and 2030 respectively. 
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Figure 7-15 Projected Change in 2018 8-hour Ozone Design Values Between the Reference 

Case and Control Case 
7-82

Figure 7-16 Projected Change in 2030 8-hour Ozone Design Values Between the Reference 

Case and Control Case 

As can be seen in Figure 7-15, the majority of the design value decreases in 2018 are 

between 0.5 and 1.0 ppb. There are also 33 counties with projected 8-hour ozone design value 

decreases of more than 1 ppb; these counties are generally in urban areas in states that have not 

adopted California LEV III standards. The maximum projected decrease in an 8-hour ozone 

design value in 2018 is 1.56 ppb in Henry County, Georgia near Atlanta. Figure 7-16 presents 

the ozone design value changes for 2030. In 2030 the ozone design value decreases are larger 

than in 2018; most decreases are projected to be between 0.5 and 1.0 ppb, but over 250 more 

counties have design values with projected decreases greater than 1.5 ppb. The maximum 

projected decrease in an 8-hour ozone design value in 2030 is 2.8 ppb in Gwinnett County, 

Georgia, the northeastern part of the Atlanta metropolitan area. 

Table 7-42 and Table 7-43 show the average change, due to this rule, in 2018 and 2030 8-

hour ozone design values for: (1) all counties with 2007 baseline design values, (2) counties with 

2007 baseline design values that exceeded the 2008 ozone standard, (3) counties with 2007

baseline design values that did not exceed the 2008 standard, but were within 10 percent of it, (4) 

counties with 2018/2030 design values that exceeded the 2008 ozone standard, and (5) counties 

with 2018/2030 design values that did not exceed the standard, but were within 10 percent of it. 

Counties within 10 percent of the standard are intended to reflect counties that although not 

violating the standards, will also be impacted by changes in ozone as they work to ensure longterm maintenance of the ozone NAAQS. All of these metrics show a decrease in 2018 and 2030, 

indicating in five different ways the overall improvement in air quality. 
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On a population-weighted basis, the average modeled future-year 8-hour ozone design 

values are projected to decrease by 0.49 ppb in 2018 and 0.98 ppb in 2030. 

Table 7-42 Average Change in Projected 8-hour Ozone Design Value in 2018

Averagea Number 

of U.S.

Counties

2020 

Population

Change in 

2018 design 

value (ppb)

All

658 234,598,095

-0.53

All, population-weighted -0.49

Counties whose 2007 base year is violating the 2008 

8-hour ozone standard

319 159,636,546

-0.60

Counties whose 2007 base year is violating the 2008 

8-hour ozone standard, population-weighted -0.51

Counties whose 2007 base year is within 10 percent 

of the 2008 8-hour ozone standard

241 52,115,093

-0.51

Counties whose 2007 base year is within 10 percent 

of the 2008 8-hour ozone standard, populationweighted -0.50

Counties whose 2018 control case is violating the 

2008 8-hour ozone standard

16 35,732,987

-0.24

Counties whose 2018 control case is violating the 

2008 8-hour ozone standard, population-weighted -0.20

Counties whose 2018 control case is within 10

percent of the 2008 8-hour ozone standard

97 55,924,864

-0.50

Counties whose 2018 control case is within 10

percent of the 2008 8-hour ozone standard, 

population-weighted -0.55

a

 Averages are over counties with 2007 modeled design values. 

b

 Population numbers based on Woods & Poole data. Woods & Poole Economics, Inc. (2011). 2012 Complete 

Economic and Demographic Data Source (CEDDS).. 

Table 7-43 Average Change in Projected 8-hour Ozone Design Value in 2030 

Averagea Number 

of U.S.

Counties

2030 

Population

Change in 

2030 design 

value (ppb)

All 658 257,693,543 -0.94

All, population-weighted -0.98

Counties whose 2007 base year is violating the 2008 

8-hour ozone standard

319 175,088,003 -1.06

Counties whose 2007 base year is violating the 2008 

8-hour ozone standard, population-weighted

-1.01

Counties whose 2007 base year is within 10 percent 

of the 2008 8-hour ozone standard

241 57,122,153 -0.90
7-84

Counties whose 2007 base year is within 10 percent 

of the 2008 8-hour ozone standard, populationweighted

-0.97

Counties whose 2030 control case is violating the 

2008 8-hour ozone standard

6 19,415,241 -0.16

Counties whose 2030 control case is violating the 

2008 8-hour ozone standard, population-weighted

-0.12

Counties whose 2030 control case is within 10

percent of the 2008 8-hour ozone standard

32 33,059,752 -0.86

Counties whose 2030 control case is within 10

percent of the 2008 8-hour ozone standard, 

population-weighted

-0.95

a

 Averages are over counties with 2007 modeled design values 

b

Population numbers based on Woods & Poole data. Woods & Poole Economics, Inc. (2011). 2012 Complete 

Economic and Demographic Data Source (CEDDS).

There are still six counties, five of them in California, that are projected to have 8-hour 

ozone design values above the 2008 NAAQS in 2030 without the standards or any other 

additional controls in place. Table 7-44 below presents the changes in design values for these 

counties. 

Table 7-44 Change in Ozone Design Values (ppb) for Counties Projected to be Above the 

2008 Ozone NAAQS in 2030 

County Name Change in 8-hour Ozone 

Design Value (ppb)

Population in 

2030a

San Bernardino, California -0.10 2,784,490

Los Angeles, California -0.10 10,742,722

Riverside, California -0.10 2,614,198

Kern, California -0.02 981,806

Westchester, New York -0.64 1,196,950

Fresno, California -0.01 1,095,075

a

 Population numbers based on Woods & Poole data. Woods & Poole Economics, Inc. (2011). 2012 

Complete Economic and Demographic Data Source (CEDDS).

In terms of modeling accuracy, the count of modeled nonattainment counties is much less 

certain than the average changes in air quality. Bearing this in mind, our modeling predicts that 

the Tier 3 standards will reduce ozone design values in some counties from above the level of the 

standard to below it. In 2018, ozone design values in three counties (Harford County in 

Maryland, Denton County in Texas and Fairfield County in Connecticut) are projected to move 

from being above the standard to below. The projected population in these three counties in 

2018 is almost 2 million people. 

As described in Section 6.1.2.1 of this RIA, the science of ozone formation, transport, 

and accumulation is complex. The air quality modeling projects ozone decreases as a result of 

emissions changes from the fuel and vehicle standards. This change in ozone results from 

interactions between photochemistry, background concentrations of ozone, VOC and NOX, local 
7-85

emissions and meteorology. There is one county in 2018 that is projected to have an increase in 

modeled ozone design value concentration (Cuyahoga County, OH, where Cleveland is located). 

When NOX levels are relatively high and VOC levels relatively low, NOX forms inorganic 

nitrates (i.e., particles) but relatively little ozone. In addition, NOx can react directly with ozone 

resulting in suppressed ozone concentrations near NOx emissions sources. Such conditions are 

called “NOX-saturated.” Under these conditions, VOC reductions are effective in reducing 

ozone, but NOX reductions can actually increase local ozone under certain circumstances. We 

believe that this is the case in Cuyahoga County in 2018. In 2030, when the fleet would be 

composed of vehicles meeting the new standards and the NOX and VOC emissions reductions 

are larger, this ozone disbenefit is eliminated, and the design values for all the modeled counties 

are decreasing. 

7.2.4.2 Particulate Matter 

As described in Section 6.1.1 of this RIA, PM causes adverse health effects, and the EPA 

has set national ambient air quality standards (NAAQS) to protect against those health effects. 

In this section we present information on current and model-projected future PM levels. 

7.2.4.2.1 Current Concentrations of PM 

Figure 7-17 and Figure 7-18 respectively show a snapshot of annual and 24-hour PM2.5

concentrations in 2010. In 2010, the highest annual average PM2.5 concentrations were in 

California, Indiana, Pennsylvania and Hawaii and the highest 24-hour PM2.5 concentrations were 

in California and Alaska. 
7-86

Figure 7-17 Annual Average PM2.5 Concentrations in μg/m3for 2010AA

 

AA From U.S. EPA, 2011. Our Nation’s Air: Status and Trends through 2010. EPA-454/R-12-001. February 2012. 

Available at: http://www.epa.gov/airtrends/2011/. 
7-87

Figure 7-18 24-hour (98th percentile 24- hour concentrations) PM2.5 Concentrations in 

μg/m3for 2010BB

There are two primary NAAQS for PM2.5: an annual standard (12.0 μg/m3) and a 24-hour 

standard (35 μg/m3), and two secondary NAAQS for PM2.5: an annual standard (15.0 μg/m3

) and 

a 24-hour standard (35 μg/m3). The initial PM2.5 standards were set in 1997 and revisions to the 

standards were finalized in 2006 and in December 2012. The December 2012 rule revised the 

level of the primary annual PM2.5 standard from 15.0 μg/m3

to 12.0 μg/m3.

133

 

In 2005 the EPA designated 39 nonattainment areas for the 1997 PM2.5 NAAQS (70 FR 

19844, April 14, 2005). As of December 5, 2013, over 68 million people lived in the 24 areas 

that are still designated as nonattainment for the 1997 annual PM2.5 NAAQS. These PM2.5

nonattainment areas are comprised of 135 full or partial counties. Nonattainment areas for the 

1997 annual PM2.5 NAAQS are pictured in Figure 7-19. EPA anticipates making initial area 

designation decisions for the 2012 primary annual PM2.5 NAAQS in December 2014, with those 

designations likely becoming effective in early 2015.134 On November 13, 2009 and February 3, 

2011, the EPA designated 32 nonattainment areas for the 2006 24-hour PM2.5 NAAQS (74 FR 

58688, November 13, 2009 and 76 FR 6056, February 3, 2011). As of December 5, 2013, 28 of 

these areas remain designated as nonattainment, and they are composed of 104 full or partial 

counties, with a population of over 65 million. Nonattainment areas for the 2006 PM2.5 NAAQS 

 

BB From U.S. EPA, 2011. Our Nation’s Air: Status and Trends through 2010. EPA-454/R-12-001. February 2012. 

Available at: http://www.epa.gov/airtrends/2011/. 
7-88

are pictured in Figure 7 20. In total, there are currently 39 PM2.5 nonattainment areas with a 

population of over 84 million people.CC 

States with PM2.5 nonattainment areas will be required to take action to bring those areas 

into attainment in the future. Designated nonattainment areas not currently attaining the 1997 

annual PM2.5 NAAQS are required to attain the NAAQS by 2015 and will be required to 

maintain the 1997 annual PM2.5 NAAQS thereafter. The 2006 24-hour PM2.5 nonattainment 

areas are required to attain the 2006 24-hour PM2.5 NAAQS in the 2015 to 2019 time frame and 

will be required to maintain the 2006 24-hour PM2.5 NAAQS thereafter. Areas to be designated 

nonattainment for the 2012 primary annual PM2.5 NAAQS will likely be required to attain the 

2012 NAAQS in the 2021 to 2025 time frame. 

 

CC Data come from Summary Nonattainment Area Population Exposure Report, current as of December 5, 2013 at: 

http://www.epa.gov/oar/oaqps/greenbk/popexp.html and contained in Docket EPA-HQ-OAR-2011-0135. The 84 

million total is calculated by summing, without double counting, the 1997 and 2006 PM2.5 nonattainment 

populations contained in the Summary Nonattainment Area Population Exposure report 

(http://www.epa.gov/oar/oaqps/greenbk/popexp.html). If there is a population associated with both the 1997 and 

2006 nonattainment areas, and they are not the same, then the larger of the two populations is included in the sum. 
7-89

Figure 7-19 1997 PM2.5 Nonattainment Areas 
7-90

Figure 7-20 2006 PM2.5 Nonattainment Areas 

As of December 5, 2013, over 11 million people live in the 40 areas that are designated 

as nonattainment for the PM10 NAAQS. There are 33 full or partial counties that make up the 

PM10 nonattainment areas. Nonattainment areas for the PM10 NAAQS are pictured in Figure 

7-21.
7-91

Figure 7-21 PM10 Nonattainment Areas 

7.2.4.2.2 Projected Concentrations of PM2.5 Without the Rule 

EPA has already adopted many mobile source emission control programs that are 

expected to reduce ambient PM levels. These control programs include the Heavy-Duty 

Greenhouse Gas Rule (76 FR 57106, September 15, 2011), the New Marine CompressionIgnition Engines at or Above 30 Liters per Cylinder Rule (75 FR 22895, April 30, 2010), the 

Marine Spark-Ignition and Small Spark-Ignition Engine Rule (73 FR 59034, October 8, 2008), 

the Locomotive and Marine Compression-Ignition Engine Rule (73 FR 25098, May 6, 2008), the 

Clean Air Nonroad Diesel (69 FR 38957, June 29, 2004), the Heavy-Duty Engine and Vehicle 

Standards and Highway Diesel Fuel Sulfur Control Requirements (66 FR 5002, January 18, 

2001) and the Tier 2 Motor Vehicle Emissions Standards and Gasoline Sulfur Control 

Requirements (65 FR 6698, February 10, 2000). As a result of these and other federal, state and 

local programs, the number of areas that fail to meet the PM2.5 NAAQS in the future is expected 

to decrease. However, even with the implementation of all current state and federal regulations, 

there are projected to be counties violating the PM2.5 NAAQS well into the future. Thus 

additional federal control programs, such as Tier 3, can assist areas with attainment dates in 2017 

and beyond in attaining the NAAQS as expeditiously as practicable and may relieve areas with 
7-92

already stringent local regulations from some of the burden associated with adopting additional 

local controls. 

The air quality modeling conducted for this rule projects that in 2030, with all current 

controls in effect but excluding the emissions changes expected to occur as a result of this rule or 

any other additional controls, at least 13 counties, with a projected population of over 21 million 

people, will have projected design values above the level of the annual standard of 12.0 μg/m3

and at least 18 counties, with a projected population of over 12 million people, will have 

projected design values above the level of the 2006 24-hour standard of 35 μg/m3. Since the 

emission changes from this action would go into effect during the period when some areas are 

still working to attain the PM2.5 NAAQS, the projected emission changes will help state and local 

agencies in their effort to attain and maintain the PM2.5 standard. In the following section we 

discuss projected PM2.5 reductions from these standards. 

7.2.4.2.3 Projected Annual Average Concentrations of PM2.5 With the Rule 

This section summarizes the results of our modeling of annual average PM2.5 air quality 

impacts in the future due to the standards in this action. Specifically, for the years 2018 and 

2030 we compare a reference scenario (a scenario without the standards) to a control scenario 

that includes the standards. Our modeling indicates that annual PM2.5 design values will 

decrease due to the Tier 3 standards. The decreases in annual PM2.5 design values are likely due 

to the projected reductions in primary PM2.5, NOX, SOX and VOC emissions. As described in 

Section 7.2.1.1, the air quality modeling used inventories that included an increase in direct 

PM2.5 emissions in the West and Pacific Northwest that is an artifact of a difference in fuel 

properties that isn’t real.DD Although in most areas this direct PM2.5 increase is outweighed by 

reductions in secondary PM2.5, the air quality modeling does predict ambient PM2.5 increases in a 

few places in the West and Pacific Northwest. These modeled increases are a result of the 

inventory issue, and we do not expect them to actually occur. Ambient PM2.5 projections are 

discussed in more detail below. Additional information on the emissions reductions that are 

projected with this action is available in Section 7.2.1 of this RIA. 

 Figure 7-22 and Figure 7-23 present the changes in annual PM2.5 design values in 2018

and 2030 respectively.EE 

 

DD The issue is with the way that some of the fuel property data, specifically E200/E300 and T50/T90, matched up 

in the fuel compliance database in the West and Pacific Northwest, see Section 7.2.1.1 for additional information. 

EE An annual PM2.5 design value is the concentration that determines whether a monitoring site meets the annual 

NAAQS for PM2.5. The full details involved in calculating an annual PM2.5 design value are given in appendix N of 

40 CFR part 50. 
7-93

Figure 7-22 Projected Change in 2018 Annual PM2.5 Design Values Between the Reference 

Case and Control Case 
7-94

Figure 7-23 Projected Change in 2030 Annual PM2.5 Design Values Between the Reference 

Case and Control Case 

As shown in Figure 7-22, we project that in 2018 over 200 counties will have design 

value decreases of between 0.01 μg/m3 and 0.05 μg/m3. These counties tend to be in urban areas 

in states that have not adopted California LEV III standards. The maximum projected decrease 

in a 2018 annual PM2.5 design value is 0.04 μg/m3in Waukesha County, Wisconsin and Cook 

County, Illinois. There are two counties with very small projected increases in their annual 

PM2.5 design values in 2018: Lewis & Clark County, Montana, and Gallatin County, Montana. 

These projected increases are a result of the issue with the air quality modeling inventories 

discussed in Section 7.2.1.1, and we do not expect these increases will occur. 

Figure 7-23 presents the annual PM2.5 design value changes in 2030. The annual PM2.5

design value decreases in 2030 are larger than the decreases in 2018; most design values are 

projected to decrease between 0.01 and 0.05 μg/m3and over 140 additional counties have 

projected design value decreases greater than 0.05 μg/m3. The maximum projected decrease in 

an annual PM2.5 design value in 2030 is 0.15 μg/m3in Milwaukee County, Wisconsin. 

Table 7-45 and Table 7-46 show the average change in 2018 and 2030 annual PM2.5

design values for: (1) all counties with 2007 baseline design values, (2) counties with 2007 

baseline design values that exceeded the 2012 annual PM2.5 standard, (3) counties with 2007

baseline design values that did not exceed the 2012 standard, but were within 10 percent of it, (4) 

counties with 2018/2030 design values that exceeded the 2012 annual PM2.5 standard, and (5) 
7-95

counties with 2018/2030 design values that did not exceed the standard, but were within 10 

percent of it. Counties within 10 percent of the standard are intended to reflect counties that

although not violating the standards, will also be impacted by changes in PM2.5 as they work to 

ensure long-term maintenance of the annual PM2.5 NAAQS. All of these metrics show either no 

change or a small decrease in 2018 and 2030. On a population-weighted basis, there is a 0.01

μg/m3reduction in the average modeled future-year annual PM2.5 design values in 2018 and a 

0.04 μg/m3decrease in 2030. 

Table 7-45 Average Change in 2018 Annual PM2.5 Design Value as a Result of the Rule 

AVERAGE Number of U.S.

Counties

2020 

Population

Change in 2018

design value 

(μg/m3)

All 573 230,583,259 -0.01

All, population-weighted -0.01

Counties whose 2007 base year is 

violating the annual PM2.5 standard

231 111,371,097 -0.02

Counties whose 2007 base year is 

violating the annual PM2.5 standard, 

population-weighted

-0.02

Counties whose 2007 base year is 

within 10 percent of the annual PM2.5 

standard

123 45,480,691 -0.01

Counties whose 2007 base year is 

within 10 percent of the annual PM2.5 

standard, population-weighted

-0.01

Counties whose 2018 control case is 

violating the annual PM2.5 standard

13 19,690,375 -0.01

Counties whose 2018 control case is 

violating the annual PM2.5 standard, 

population-weighted

0.00

Counties whose 2018 control case is 

within 10 percent of the annual PM2.5 

standard

28 29,073,863 -0.02

Counties whose 2018 control case is 

within 10 percent of the annual PM2.5 

standard, population-weighted

-0.02

a

 Averages are over counties with 2007 modeled design values 

b

 Population numbers based on Woods & Poole data. Woods & Poole Economics, Inc. (2011). 2012 Complete 

Economic and Demographic Data Source (CEDDS). 
7-96

Table 7-46 Average Change in 2030 Annual PM2.5 Design Value as a Result of the Rule 

AVERAGE Number of U.S.

Counties

2030 

Population

Change in 2030

design value 

(μg/m3)

All 573 252,063,937 -0.04

All, population-weighted -0.04

Counties whose 2007 base year is 

violating the annual PM2.5 standard

231 119,932,361 -0.05

Counties whose 2007 base year is 

violating the annual PM2.5 standard, 

population-weighted

-0.05

Counties whose 2007 base year is 

within 10 percent of the annual PM2.5 

standard

123 50,009,709 -0.04

Counties whose 2007 base year is 

within 10 percent of the annual PM2.5 

standard, population-weighted

-0.05

Counties whose 2030 control case is 

violating the annual PM2.5 standard

13 21,376,437 -0.01

Counties whose 2030 control case is 

violating the annual PM2.5 standard, 

population-weighted

-0.01

Counties whose 2030 control case is 

within 10 percent of the annual PM2.5 

standard

20 22,244,541 -0.07

Counties whose 2030 control case is 

within 10 percent of the annual PM2.5 

standard, population-weighted

-0.09

a

 Averages are over counties with 2007 modeled design values 

b

 Population numbers based on Woods & Poole data. Woods & Poole Economics, Inc. (2011). 2012 Complete 

Economic and Demographic Data Source (CEDDS).

There are 13 counties, mostly in California, that are projected to have annual PM2.5

design values above the NAAQS in 2030 without the standards or any other additional standards 

in place. Table 7-47 below presents the changes in design values for these counties. 
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Table 7-47 Change in Annual PM2.5 Design Values (μg/m3) for Counties Projected to be 

Above the Annual PM2.5 NAAQS in 2030 

County Name Change in 

Annual 

PM2.5

Design 

Value 

(μg/m3)

Population 

in 2030a

Kern County, California -0.01 981,806 

Imperial County, California -0.01 174,175 

Tulare County, California -0.01 528,662 

Riverside County, California -0.01 2,614,198 

Fresno County, California 0 1,196,949 

San Bernardino County, California -0.01 2,784,489 

Santa Cruz County, Arizona -0.03 55,393 

Kings County, California 0 195,067 

Lincoln County, Montana -0.02 20,454 

El Paso County, Texas -0.06 1,080,944 

Merced County, California 0 313,333 

Stanislaus County, California 0 688,245 

Los Angeles County, California 0 10,742,722 

a

 Population numbers based on Woods & Poole data. Woods & Poole Economics, Inc. (2011). 

2012 Complete Economic and Demographic Data Source (CEDDS). 

In terms of modeling accuracy, the count of modeled nonattainment counties is much less 

certain than the average changes in air quality. Bearing this in mind, in 2018 our modeling 

predicts that the Tier 3 standards will reduce annual PM2.5 design values in Allegheny County, 

PA from above the level of the standard to below it. The projected population in Allegheny 

County in 2018 is over one million people. 

7.2.4.2.4 Projected 24-hour Average Concentrations of PM2.5 With the Rule 

This section summarizes the results of our modeling of 24-hour PM2.5 air quality impacts 

in the future due to the rule. Specifically, for the years 2018 and 2030 we compare a reference 

scenario (a scenario without the standards) to a control scenario that includes the standards. Our 

modeling indicates that 24-hour PM2.5 design values will decrease due to the Tier 3 standards. 

The decreases in 24-hour PM2.5 design values are likely due to the projected reductions in 

primary PM2.5, NOX, SOX and VOCs. As described in Section 7.2.1.1, the air quality modeling 

used inventories that include an increase in direct PM2.5 emissions in the West and Pacific 

Northwest that is an artifact of a difference in fuel properties that isn’t real.FF Although in most 

areas this direct PM2.5 increase is outweighed by reductions in secondary PM2.5, the air quality 

 

FF The issue is with the way that some of the fuel property data, specifically E200/E300 and T50/T90, matched up in 

the fuel compliance database in the West and Pacific Northwest, see Section 7.2.1.1 for additional information. 
7-98

modeling does predict ambient PM2.5 increases in a few places in the West and Pacific 

Northwest. These modeled increases are a result of the inventory issue, and we do not expect 

them to actually occur. Ambient PM2.5 projections are discussed in more detail below. 

Additional information on the emissions reductions that are projected with this action is available 

in Section 7.2.1 of this RIA. 

Figure 7-24 and Figure 7-25 present the changes in 24-hour PM2.5 design values in 2018 

and 2030 respectively 

Figure 7-24 Projected Change in 2018 24-hour PM2.5 Design Values Between the Reference 

Case and the Control Case 
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Figure 7-25 Projected Change in 2030 24-hour PM2.5 Design Values Between the Reference 

Case and the Control Case 

As shown in Figure 7-24, in 2018 there are 16 counties with projected 24-hour PM2.5

design value decreases greater than 0.15 μg/m3

. These counties are in urban areas in states that 

have not adopted California LEV III standards. The maximum projected decrease in a 2018 24-

hour PM2.5 design value is 0.30 μg/m3in Utah County, Utah. There are three counties with 

projected increases in their 24-hour PM2.5 design values in 2018: Washington County, Oregon; 

King County, Washington; and Sheridan County, Wyoming. These projected increases are a 

result of the issue with the air quality modeling emissions inventories discussed in Section 

7.2.1.1, and we do not expect these increases will occur. 

Figure 7-25 presents the 24-hour PM2.5 design value changes in 2030. In 2030 the 24-

hour PM2.5 design value decreases are larger; most design values are projected to decrease 

between 0.05 and 0.15 μg/m3and over 50 counties have projected design value decreases greater 

than 0.25 μg/m3. The maximum projected decrease in a 24-hour PM2.5 design value in 2030 is 

0.8 μg/m3in Salt Lake County, Utah. As shown in Figure 7-25, design values in 9 counties are 

projected to decrease by more than 0.5 μg/m3

. These counties are in Utah, Idaho, Colorado and 

Wisconsin. There are two counties with projected increases in their 24-hour PM2.5 design values 

in 2030: King County, Washington, and Pierce County, Washington. These projected increases 

are a result of the issue with the air quality modeling emissions inventories discussed in Section 
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7.2.1.1 and we do not expect these increases will occur. Additional information on the emissions 

reductions that are projected with this action is available in Section 7.2.1. 

Table 7-48 and Table 7-49 show the average change in 2018/2030 24-hour PM2.5 design 

values for: (1) all counties with 2007 baseline design values, (2) counties with 2007 baseline 

design values that exceeded the 24-hour PM2.5 standard, (3) counties with 2007 baseline design 

values that did not exceed the standard, but were within 10 percent of it, (4) counties with 

2018/2030 design values that exceeded the 24-hour PM2.5 standard, and (5) counties with 

2018/2030 design values that did not exceed the standard, but were within 10 percent of it. 

Counties within 10 percent of the standard are intended to reflect counties that although not 

violating the standards, will also be impacted by changes in PM2.5 as they work to ensure longterm maintenance of the 24-hour PM2.5 NAAQS. On a population-weighted basis, the average 

modeled future-year 24-hour PM2.5 design values are projected to decrease by 0.13 μg/m3in 

2030 due to the Tier 3 standards. 

Table 7-48 Average Change in Projected 24-hour PM2.5 Design Values in 2018 

Averagea

Number 

of U.S.

Counties

2030 

Populationb

Change in 

2030 design 

value 

(μg/m3)

All 568 229,741,229 -0.04

All, population-weighted -0.05

Counties whose 2007 base year is violating the 2006 

24-hour PM2.5 standard

55 56,171,551 -0.05

Counties whose 2007 base year is violating the 2006 

24-hour PM2.5 standard, population-weighted

-0.06

Counties whose 2007 base year is within 10 percent 

of the 2006 24-hour PM2.5 standard

84 39,543,851 -0.06

Counties whose 2007 base year is within 10 percent 

of the 2006 24-hour PM2.5 standard, populationweighted

-0.06

Counties whose 2030 control case is violating the 

2006 24-hour PM2.5 standard

24 18,382,427 -0.04

Counties whose 2030 control case is violating the 

2006 24-hour PM2.5 standard, population-weighted

-0.03

Counties whose 2030 control case is within 10

percent of the 2006 24-hour PM2.5 standard

14 16,167,178 -0.07

Counties whose 2030 control case is within 10

percent of the 2006 24-hour PM2.5 standard, 

population-weighted

-0.09

Note: 

a

 Averages are over counties with 2007 modeled design values 

b

 Population numbers based on Woods & Poole data. Woods & Poole Economics, Inc. (2011). 2012 Complete 

Economic and Demographic Data Source (CEDDS). 
7-101

Table 7-49 Average Change in Projected 24-hour PM2.5 Design Values in 2030 

Averagea

Number 

of U.S.

Counties

2030 

Populationb

Change in 

2030 design 

value 

(μg/m3)

All 568 251,240,080 -0.13

All, population-weighted -0.13

Counties whose 2007 base year is violating the 2006 

24-hour PM2.5 standard

55 60,280,914 -0.17

Counties whose 2007 base year is violating the 2006 

24-hour PM2.5 standard, population-weighted

-0.13

Counties whose 2007 base year is within 10 percent 

of the 2006 24-hour PM2.5 standard

84 42,498,707 -0.18

Counties whose 2007 base year is within 10 percent 

of the 2006 24-hour PM2.5 standard, populationweighted

-0.16

Counties whose 2030 control case is violating the 

2006 24-hour PM2.5 standard

18 12,363,252 -0.11

Counties whose 2030 control case is violating the 

2006 24-hour PM2.5 standard, population-weighted

-0.14

Counties whose 2030 control case is within 10

percent of the 2006 24-hour PM2.5 standard

13 22,759,997 -0.05

Counties whose 2030 control case is within 10

percent of the 2006 24-hour PM2.5 standard, 

population-weighted 0.00

a

 Averages are over counties with 2007 modeled design values 

b

 Population numbers based on Woods & Poole data. Woods & Poole Economics, Inc. (2011). 2012 Complete 

Economic and Demographic Data Source (CEDDS). 

There are 18 counties that are projected to have 24-hour PM2.5 design values above the 

NAAQS in 2030 without the Tier 3 standards or any other additional controls in place. Table 

7-50 below presents the changes in design values for these counties. 
7-102

Table 7-50 Change in 24-hour PM2.5 Design Values (μg/m3) for Counties Projected to be 

Above the 24-hour PM2.5 NAAQS in 2030 

County Name

Change in 24-hour 

PM2.5 Design Value 

(μg/m3)

Population in 2030a

Sacramento County, California 0 1,856,970 

Butte County, California 0 287,235 

Klamath County, Oregon -0.1 77,199 

Imperial County, California -0.1 174,175 

Pierce County, Washington 0.1 1,082,578 

Stanislaus County, California 0 688,245 

Fresno County, California -0.1 1,196,949 

Merced County, California 0 313,333 

Kings County, California 0 195,067 

Kern County, California 0 981,806 

Lake County, Oregon 0 9,462 

Salt Lake County, Utah -0.8 1,431,946 

Pinal County, Arizona -0.2 348,831 

Lane County, Oregon -0.1 460,992 

Allegheny County, Pennsylvania 0 1,234,930 

San Joaquin County, California -0.1 833,417 

Utah County, Utah -0.6 661,455 

Tulare County, California 0 528,662 

a

 Population numbers based on Woods & Poole data. Woods & Poole Economics, Inc. (2011). 2012 

Complete Economic and Demographic Data Source (CEDDS).

7.2.4.3 Nitrogen Dioxide 

As described in Section 6.1.3 of this RIA, NO2 causes adverse health effects, and the 

EPA has set national ambient air quality standards (NAAQS) to protect against those health 

effects. In this section we present information on current and model-projected future NO2 levels. 

7.2.4.3.1 Current Concentrations of NO2

The EPA most recently completed a review of the primary NAAQS for NO2 in January 

2010. There are two primary NAAQS for NO2: an annual standard (53 ppb) and a 1-hour 

standard (100 ppb). The EPA promulgated area designations in the Federal Register on February 

17, 2012. In this initial round of designations, all areas of the country were designated as 

“unclassifiable/attainment” for the 2010 NO2 NAAQS based on data from the existing air quality 

monitoring network. The EPA and state agencies are working to establish an expanded network 

of NO2 monitors, expected to be deployed in the 2014-2017 time frame. Once three years of air 

quality data have been collected from the expanded network, the EPA will be able to evaluate 

NO2 air quality in additional locations.135,136
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7.2.4.3.2 Projected Concentrations of NO2 without the Rule 

EPA has already adopted many mobile source emission control programs that are 

expected to reduce ambient NO2 levels. These control programs include the Heavy-Duty 

Greenhouse Gas Rule (76 FR 57106, September 15, 2011), New Marine Compression-Ignition 

Engines at or Above 30 Liters per Cylinder Rule (75 FR 22895, April 30, 2010), the Locomotive 

and Marine Compression-Ignition Engine Rule (73 FR 25098, May 6, 2008), the Clean Air 

Nonroad Diesel (69 FR 38957, June 29, 2004), the Heavy-Duty Engine and Vehicle Standards 

and Highway Diesel Fuel Sulfur Control Requirements (66 FR 5002, January 18, 2001) and the 

Tier 2 Motor Vehicle Emissions Standards and Gasoline Sulfur Control Requirements (65 FR 

6698, February 10, 2000). As a result of these and other federal, state and local programs, 

ambient concentrations of NO2 in the future are expected to decrease. 

7.2.4.3.3 Projected Concentrations of NO2 with the Rule 

This section summarizes the results of our modeling of annual average NO2 air quality 

impacts in the future due to the final Tier 3 standards. Specifically, for the years 2018 and 2030 

we compare a reference scenario (a scenario without the standards) to a control scenario that 

includes the standards. Figure 7-26 and Figure 7-27 present the changes in annual NO2

concentrations in 2018 and 2030 respectively. 

Figure 7-26 Projected Change in 2018 Annual NO2 Concentrations Between the Reference 

Case and Control Case 
7-104

Figure 7-27 Projected Change in 2030 Annual NO2 Concentrations Between the Reference 

Case and Control Case 

As shown in Figure 7-27, our modeling indicates that by 2030 annual NO2 concentrations 

in the majority of the country would decrease less than 0.1 ppb due to this rule. However, 

decreases in annual NO2 concentrations are greater than 0.3 ppb in most urban areas. These 

emissions reductions would also likely decrease 1-hour NO2 concentrations and help any 

potential nonattainment areas to attain and maintain the standard. 

7.2.4.4 Air Toxics 

As described in Section 6.1.5 of this RIA, air toxics cause adverse health effects. In this 

section we present information on current and model-projected future levels of air toxics. 

7.2.4.4.1 Current Concentrations of Air Toxics 

The majority of Americans continue to be exposed to ambient concentrations of air toxics 

at levels which have the potential to cause adverse health effects.137

 The levels of air toxics to 

which people are exposed vary depending on where people live and work and the kinds of 

activities in which they engage, as discussed in detail in U.S. EPA’s most recent Mobile Source 

Air Toxics (MSAT) Rule.138 In order to identify and prioritize air toxics, emission source types 

and locations which are of greatest potential concern, U.S. EPA conducts the National-Scale Air 

Toxics Assessment (NATA). The most recent NATA was conducted for calendar year 2005, and 

was released in March 2011.139

 NATA for 2005 includes four steps: 
7-105

1) Compiling a national emissions inventory of air toxics emissions from outdoor 

sources 

2) Estimating ambient concentrations of air toxics across the United States 

3) Estimating population exposures across the United States 

4) Characterizing potential public health risk due to inhalation of air toxics including 

both cancer and noncancer effects 

Figure 7-28 and Figure 7-29 depict estimated tract-level carcinogenic risk and noncancer 

respiratory hazard from the assessment. The respiratory hazard is dominated by a single 

pollutant, acrolein. 

According to the NATA for 2005, mobile sources were responsible for 43 percent of 

outdoor toxic emissions and over 50 percent of the cancer risk and noncancer hazard attributable 

to direct emissions from mobile and stationary sources.GG,HH,140 Mobile sources are also large 

contributors to precursor emissions which react to form secondary concentrations of air toxics. 

Formaldehyde is the largest contributor to cancer risk of all 80 pollutants quantitatively assessed 

in the 2005 NATA, and mobile sources were responsible for over 40 percent of primary 

emissions of this pollutant in 2005, and are major contributors to formaldehyde precursor 

emissions. Benzene is also a large contributor to cancer risk, and mobile sources account for 

over 70 percent of ambient exposure. Over the years, EPA has implemented a number of mobile 

source and fuel controls which have resulted in VOC reductions, which also reduced 

formaldehyde, benzene and other air toxic emissions. 

 

GG NATA also includes estimates of risk attributable to background concentrations, which includes contributions 

from long-range transport, persistent air toxics, and natural sources; as well as secondary concentrations, where 

toxics are formed via secondary formation. Mobile sources substantially contribute to long-range transport and 

secondarily formed air toxics. 

HH NATA relies on a Guassian plume model, Assessment System for Population Exposure Nationwide (ASPEN), to 

estimate toxic air pollutant concentrations. Projected air toxics concentrations presented in this final action were 

modeled with CMAQ 4.7.1. 
7-106

Figure 7-28 Tract Level Average Carcinogenic Risk, 2005 NATA 

 

Figure 7-29 County Level Average Noncancer Hazard Index, 2005 NATA
7-107

7.2.4.4.2 Projected Concentrations of Air Toxics 

Since 2005, and in future years when this rulemaking takes effect, the contribution of 

mobile sources to overall cancer risk is likely to change as a result of the impact of controls on 

both stationary and mobile sources. Overall, EPA anticipates a substantial decrease in overall 

cancer risk from ambient sources. In the following sections, we describe results of our modeling 

of air toxics concentrations in the future with the Tier 3 standards. Although there are a large 

number of compounds which are considered air toxics, we focused on those which were 

identified as national and regional-scale cancer and noncancer risk drivers in past NATA 

assessments and were also likely to be significantly impacted by the standards. These 

compounds include benzene, 1,3-butadiene, formaldehyde, acetaldehyde, and acrolein. Impacts 

on ethanol concentrations were also included in our analyses. Information on the air quality 

modeling methodology is contained in Section 7.2.2. Additional detail can be found in the air 

quality modeling technical support document (AQM TSD) in the docket for this rule. Additional 

maps, including the seasonal concentration maps for 2030 and 2018, are included in Appendix 

7.A.

It should be noted that EPA has adopted many mobile source emission control programs 

that are expected to reduce ambient air toxics levels. These control programs include the HeavyDuty Greenhouse Gas Rule (76 FR 57106, September 15, 2011), the New Marine CompressionIgnition Engines at or Above 30 Liters per Cylinder Rule (75 FR 22895, April 30, 2010), Heavyduty Onboard Diagnostic Rule (74 FR 8310, February 24, 2009), Small SI and Marine SI Engine 

Rule (73 FR 59034, October 8, 2008), Locomotive and Commercial Marine Rule (73 FR 25098, 

May 6, 2008), Mobile Source Air Toxics Rule (72 FR 8428, February 26, 2007), Clean Air 

Nonroad Diesel Rule (69 FR 38957, June 29, 2004), Heavy-Duty Engine and Vehicle Standards 

and Highway Diesel Fuel Sulfur Control Requirements (66 FR 5002, Jan. 18, 2001) and the Tier 

2 Motor Vehicle Emissions Standards and Gasoline Sulfur Control Requirements (65 FR 6698, 

Feb. 10, 2000). As a result of these programs, the ambient concentration of air toxics in the 

future is expected to decrease. The reference case and control case scenarios include these 

controls. 

Our modeling indicates that the impacts of the standards include generally small 

decreases in ambient concentrations of air toxics, with the greatest reductions in urban areas. Air 

toxics pollutants dominated by primary emissions (or a decay product of a directly emitted 

pollutant), such as benzene and 1,3-butadiene, have the largest impacts. Air toxics that primarily 

result from photochemical transformation, such as formaldehyde and acetaldehyde, are not 

impacted as much as those dominated by direct emissions. Our modeling shows decreases in 

ambient air toxics concentrations for both 2018 and 2030. Reductions are greater in 2030, when 

Tier 3 cars and trucks would contribute nearly 90 percent of fleet-wide vehicle miles travelled, 

than in 2018. However, our 2018 modeling projects there would be small immediate reductions 

in ambient concentrations of air toxics due to the sulfur controls that take effect in 2017. 

Furthermore, the full reduction of the vehicle program would be realized after 2030, when the 

fleet has fully turned over to Tier 3 vehicles. Because overall impacts are relatively small in both 

future years, we concluded that assessing exposure to ambient concentrations and conducting a 

quantitative risk assessment of air toxic impacts was not warranted. However, we did develop 

population metrics, including the population living in areas with increases or decreases in 

concentrations of various magnitudes. 
7-108

Benzene 

Our modeling projects that the standards would have a notable impact on ambient 

benzene concentrations. In 2018, soon after the Tier 3 standards take effect, ambient benzene 

reductions are generally between 0.001 and 0.01 μg/m3, or between 1 and 2.5 percent in some 

areas (Figure 7-30). In 2030, our modeling projects that the rule will decrease ambient benzene 

concentrations across much of the country on the order of 1 to 5 percent, with reductions ranging 

from 10 to 25 percent in some urban areas (Figure 7-31). Absolute decreases in ambient 

concentrations of benzene are generally between 0.001 and 0.01 μg/m3 in rural areas and as 

much as 0.1 μg/m3 in urban areas (Figure 7-31). 
7-109

Figure 7-30 Changes in Benzene Ambient Concentrations Between the Reference Case and the 

Control Case in 2018: Percent Changes (left) and Absolute Changes in μg/m3 (right) 

Figure 7-31 Changes in Benzene Ambient Concentrations Between the Reference Case and the 

Control Case in 2030: Percent Changes (left) and Absolute Changes in μg/m3 (right) 

1,3-Butadiene 

Our modeling also shows reductions of ambient 1,3-butadiene concentrations in 2018 and 

2030. Figure 7-32 shows that in 2018, ambient concentrations of 1,3-butadiene generally 

decrease between 1 and 5 percent across parts of the country, corresponding to small decreases in 

absolute concentrations (less than 0.001 μg/m3). In 2030, reductions of 1,3-butadiene 
7-110

concentrations range between 1 and 25 percent, with decreases of at least 0.005 μg/m3 in urban 

areas (Figure 7-33). 

Figure 7-32 Changes in 1,3-Butadiene Ambient Concentrations Between the Reference Case 

and the Control Case in 2018: Percent Changes (left) and Absolute Changes in μg/m3 (right) 

Figure 7-33 Changes in 1,3-Butadiene Ambient Concentrations Between the Reference Case 

and the Control Case in 2030: Percent Changes (left) and Absolute Changes in μg/m3 (right) 
7-111

Acrolein 

Our modeling indicates the standards would reduce ambient concentrations of acrolein in 

2018 and 2030. Figure 7-34 shows decreases in ambient concentrations of acrolein generally 

between 1 and 2.5 percent in parts of the country in 2018, corresponding to small decreases in 

absolute concentrations (less than 0.001 μg/m3). Reductions of acrolein concentrations in 2030 

range between 1 and 10 percent, with decreases as high as 0.003 μg/m3 in a few urban areas. 

Figure 7-34 Changes in Acrolein Ambient Concentrations Between the Reference Case and 

the Control Case in 2018: Percent Changes (left) and Absolute Changes in μg/m3 (right) 

Figure 7-35 Changes in Acrolein Ambient Concentrations Between the Reference Case and 

the Control Case in 2030: Percent Changes (left) and Absolute Changes in μg/m3 (right) 
7-112

Ethanol 

Our modeling projects that the standards would slightly decrease ambient ethanol 

concentrations in 2018 and 2030. As shown in Figure 7-36, in 2018, annual percent changes in 

ambient concentrations of ethanol are less than 1 percent across the country, with absolute 

reductions of up to 0.1 ppb in some places. In 2030, some parts of the country, especially urban 

areas, are projected to have reductions in ethanol concentrations on the order of 1 to 10 percent 

as a result of the rule (Figure 7-37). Figure 7-37 also shows that absolute decreases in ambient 

concentrations of ethanol are generally between 0.001 and 0.1 ppb in 2030 with decreases in a 

few urban areas as high as 0.2 ppb. 

Figure 7-36 Changes in Ethanol Ambient Concentrations Between the Reference Case and 

the Control Case in 2018: Percent Changes (left) and Absolute Changes in μg/m3 (right) 
7-113

Figure 7-37 Changes in Ethanol Ambient Concentrations Between the Reference Case and the 

Control Case in 2030: Percent Changes (left) and Absolute Changes in μg/m3 (right) 

Formaldehyde 

Our modeling projects that formaldehyde concentrations would slightly decrease in parts 

of the country (mainly urban areas) as a result of the rule. As shown in Figure 7-38 and Figure 

7-39, annual percent changes in ambient concentrations of formaldehyde are less than 1 percent 

across much of the country for 2018 but are on the order of 1 to 5 percent in 2030 in some urban 

areas as a result of the rule. Figure 7-38 and Figure 7-39 also show that absolute changes in 

ambient concentrations of formaldehyde are generally between 0.001 and 0.01 μg/m3 in both 

years, with some areas as high as 0.1 μg/m3 in 2030. 
7-114

Figure 7-38 Changes in Formaldehyde Ambient Concentrations Between the Reference Case 

and the Control Case in 2018: Percent Changes (left) and Absolute Changes in μg/m3 (right) 

Figure 7-39 Changes in Formaldehyde Ambient Concentrations Between the Reference Case 

and the Control Case in 2030: Percent Changes (left) and Absolute Changes in μg/m3 (right) 
7-115

Acetaldehyde 

Our air quality modeling shows annual percent changes in ambient concentrations of 

acetaldehyde of generally less than 1 percent across the U.S., although the rule may decrease 

acetaldehyde concentrations in some urban areas by 1 to 2.5 percent in 2030 (Figure 7-40). 

Changes in ambient concentrations of acetaldehyde are generally in the range of 0.01 μg/m3 to -

0.01 μg/m3 with decreases happening in the more populated areas and increases happening in 

more rural areas (Figure 7-40). 

The complex photochemistry associated with NOX emissions and acetaldehyde formation 

appears to be the explanation for the split between increased rural concentrations and decreased 

urban concentrations. In the atmosphere, acetaldehyde precursors react with NOX to form 

peroxyacylnitrate (PAN). Reducing NOX allows acetaldehyde precursors to be available to form 

acetaldehyde instead. This phenomenon is more prevalent in rural areas where NOX is low. The 

chemistry involved is further described by a recent study done by EPA’s Office of Research and 

Development and Region 3 evaluating the complex effects of reducing multiple emissions on 

reactive air toxics and criteria pollutants.141 

Figure 7-40 Changes in Acetaldehyde Ambient Concentrations Between the Reference Case and 

the Control Case in 2018: Percent Changes (left) and Absolute Changes in μg/m3 (right) 
7-116

Figure 7-41 Changes in Acetaldehyde Ambient Concentrations Between the Reference Case and 

the Control Case in 2030: Percent Changes (left) and Absolute Changes in μg/m3 (right) 

Naphthalene 

Our modeling projects reductions in naphthalene concentrations in 2018 and 2030. As 

shown in Figure 7-42 , annual percent changes in ambient concentrations of naphthalene are 

between 1 and 2.5 percent across much of the country for 2018, with small decreases in absolute 

concentrations (less than 0.001 μg/m3). In 2030, reductions of naphthalene concentrations 

generally range between 1 and 10 percent but are as high as 25 percent in some areas of the 

Southeast, with corresponding absolute decreases in urban areas of up to 0.005 μg/m3(Figure 

7-43). 
7-117

Figure 7-42 Changes in Naphthalene Ambient Concentrations Between the Reference Case and 

the Control Case in 2018: Percent Changes (left) and Absolute Changes in μg/m3 (right) 

Figure 7-43 Changes in Naphthalene Ambient Concentrations Between the Reference Case 

and the Control Case in 2030: Percent Changes (left) and Absolute Changes in μg/m3 (right) 

Population Metrics 

Although the reductions in ambient air toxics concentrations expected from the Tier 3 

standards are generally small, they are projected to benefit the majority of the U.S. population. 

As shown in Table 7-51, over 75 percent of the total U.S. population is projected to experience a 

decrease in ambient benzene and 1,3-butadiene concentrations of at least 1 percent. Table 7-51

also shows that over 60 percent of the U.S population is projected to experience at least a 1 
7-118

percent decrease in ambient ethanol and acrolein concentrations, and over 35 percent would 

experience a similar decrease in ambient formaldehyde concentrations with the standards. 

Table 7-51 Percent of Total Population Experiencing Changes in Annual Ambient 

Concentrations of Toxic Pollutants in 2030 as a Result of the Standards 

Percent Change Benzene Acrolein 1,3-Butadiene Formaldehyde Ethanol Acetaldehyde Naphthalene

≤ -50

> -50 to ≤ -25

> -25 to ≤ -10 2.29% 0.75% 19.07% 10.74%

> -10 to ≤ -5 20.63% 12.72% 27.29% 5.39% 31.56%

> -5 to ≤ -2.5 27.50% 25.17% 15.37% 0.60% 24.08% 20.58%

> -2.5 to ≤ -1 28.60% 24.62% 18.33% 35.34% 34.10% 11.77% 14.98%

> -1 to < 1 20.97% 36.74% 19.93% 64.06% 36.43% 88.23% 22.14%

≥ 1 to < 2.5

≥ 2.5 to < 5

≥ 5 to < 10

≥ 10 to < 25

≥ 25 to < 50

≥ 50 

Of note, the rule is expected to decrease population exposure to acrolein, which is 

currently a national risk driver for noncancer respiratory health effects as described in Section 

7.2.5.4.1. Our modeling projects that acrolein concentrations would decrease to levels below the 

inhalation reference concentration for acrolein (0.02 μg/m3) for over 5 million people in 2030, 

meaning that as a result of the Tier 3 standards, 5 million fewer Americans will be exposed to 

ambient levels of acrolein high enough to present a potential for adverse health effects. The 

inhalation reference concentration for acrolein and other risk drivers is described in Section 

6.1.5.6. In addition, the decrease in population exposure to the toxic compounds in Table 7-36 

will decrease cancer risks that are described in Section 6.1.5. 

7.2.4.5 Visibility 

As described in Section 6.2.1 of this RIA, PM also causes adverse visibility effects, and 

the EPA has set national ambient air quality standards (NAAQS) and regional haze rules to 

protect against visibility impairment. In this section we present information on current and 

model-projected future visibility levels at Mandatory Class I Federal Areas. 

7.2.4.5.1 Current Visibility Levels 

Designated PM2.5 nonattainment areas indicate that, as of December 5, 2013, over 84

million people live in nonattainment areas for the PM2.5 NAAQS. Thus, at least these 

populations would likely be experiencing visibility impairment, as well as many thousands of 
7-119

individuals who travel to these areas. In addition, while visibility trends have improved in 

Mandatory Class I Federal areas, these areas continue to suffer from visibility impairment.142 

Calculated from light extinction efficiencies from Trijonis et al. (1987, 1988), annual average 

visual range under natural conditions in the East is estimated to be 150 km ± 45 km (i.e., 65 to 

120 miles) and 230 km ± 35 km (i.e., 120 to 165 miles) in the West.143,144,145 In summary, 

visibility impairment is experienced throughout the U.S., in multi-state regions, urban areas, and 

remote Mandatory Class I Federal areas. 

7.2.4.5.2 Projected Visibility Levels 

Air quality modeling conducted for the final action was used to project visibility 

conditions in 137 Mandatory Class I Federal areas across the U.S. The results show that in 2030 

all the modeled areas would continue to have annual average deciview levels above background 

and the rule would improve visibility in all these areas.II The average visibility on the 20 percent 

worst days at all modeled Mandatory Class I Federal areas is projected to improve by 0.02 

deciviews, or 0.16 percent, in 2030. The greatest improvement in visibilities will be seen in 

Craters of the Moon National Monument, where visibility is projected to improve by 0.7 percent 

(0.09 DV) in 2030 due to the standards. Table 7-52 contains the full visibility results from 2030 

for the 137 analyzed areas. 

Table 7-52 Visibility Levels (in Deciviews) for Mandatory Class I Federal Areas on the 20 

Percent Worst Days with and without this Rule 

Class 1 Area

(20% worst days) State

2007

Baseline 

Visibility

(dv)a

2018

Reference

2018

Tier 3 

Control

2030 

Reference

2030

Tier 3 

Control

Natural 

Background

Sipsey Wilderness AL 28.32 20.59 20.55 20.43 20.37 10.99

Upper Buffalo Wilderness AR 25.86 20.01 19.98 19.93 19.88 11.57

Chiricahua NM AZ 12.22 11.82 11.82 12.38 12.37 7.20

Chiricahua Wilderness AZ 12.22 11.83 11.82 12.38 12.37 7.20

Galiuro Wilderness AZ 12.22 11.99 11.98 12.41 12.40 7.20

Grand Canyon NP AZ 11.97 11.21 11.20 11.31 11.30 7.04

Mazatzal Wilderness AZ 13.40 12.65 12.65 12.88 12.85 6.68

Mount Baldy Wilderness AZ 11.79 10.98 10.98 11.24 11.22 6.24

Petrified Forest NP AZ 13.02 12.24 12.23 12.37 12.35 6.49

Pine Mountain Wilderness AZ 13.40 12.69 12.69 12.93 12.91 6.68

Saguaro NM AZ 13.63 13.02 13.00 13.04 12.99 6.46

Superstition Wilderness AZ 13.81 13.18 13.18 13.38 13.34 6.54

 

II The level of visibility impairment in an area is based on the light-extinction coefficient and a unitless visibility 

index, called a “deciview”, which is used in the valuation of visibility. The deciview metric provides a scale for 

perceived visual changes over the entire range of conditions, from clear to hazy. Under many scenic conditions, the 

average person can generally perceive a change of one deciview. The higher the deciview value, the worse the 

visibility. Thus, an improvement in visibility is a decrease in deciview value. 
7-120

Class 1 Area

(20% worst days) State

2007

Baseline 

Visibility

(dv)a

2018

Reference

2018

Tier 3 

Control

2030 

Reference

2030

Tier 3 

Control

Natural 

Background

Sycamore Canyon 

Wilderness AZ 15.18 14.94 14.94 15.03 15.02 6.65

Agua Tibia Wilderness CA 20.92 17.67 17.66 16.85 16.85 7.64

Ansel Adams Wilderness 

(Minarets) CA 15.72 14.57 14.57 14.38 14.38 7.12

Caribou Wilderness CA 15.99 15.54 15.54 15.48 15.48 7.31

Cucamonga Wilderness CA 18.03 15.37 15.36 14.91 14.90 6.99

Desolation Wilderness CA 13.62 12.89 12.89 12.76 12.75 6.05

Dome Land Wilderness CA 19.23 17.89 17.89 17.60 17.60 7.46

Emigrant Wilderness CA 16.87 15.84 15.84 15.67 15.66 7.64

Hoover Wilderness CA 12.19 11.49 11.48 11.41 11.41 7.71

John Muir Wilderness CA 15.72 14.76 14.76 14.60 14.60 7.12

Joshua Tree NM CA 17.83 15.75 15.75 15.33 15.32 7.19

Kaiser Wilderness CA 15.72 14.80 14.80 14.59 14.59 7.12

Kings Canyon NP CA 23.39 21.56 21.55 21.06 21.05 7.70

Lassen Volcanic NP CA 15.99 15.52 15.52 15.45 15.45 7.31

Lava Beds NM CA 14.17 13.78 13.78 13.68 13.67 7.85

Marble Mountain 

Wilderness CA 17.34 17.02 17.01 16.91 16.91 7.90

Mokelumne Wilderness CA 13.62 12.88 12.88 12.75 12.75 6.05

Pinnacles NM CA 18.37 16.44 16.43 16.05 16.05 7.99

Point Reyes NS CA 22.03 21.04 21.03 20.71 20.71 15.77

Redwood NP CA 19.14 18.72 18.70 18.43 18.42 13.91

San Gabriel Wilderness CA 18.03 15.71 15.71 15.31 15.30 6.99

San Gorgonio Wilderness CA 20.48 17.68 17.68 16.94 16.93 7.30

San Jacinto Wilderness CA 20.48 17.76 17.76 16.95 16.95 7.30

San Rafael Wilderness CA 19.20 17.46 17.46 17.10 17.10 7.57

Sequoia NP CA 23.39 21.28 21.28 20.74 20.73 7.70

South Warner Wilderness CA 14.17 13.60 13.60 13.49 13.49 7.85

Thousand Lakes 

Wilderness CA 15.99 15.53 15.53 15.46 15.45 7.31

Ventana Wilderness CA 18.37 16.79 16.79 16.50 16.49 7.99

Yolla Bolly Middle Eel 

Wilderness CA 17.34 17.06 17.06 16.99 16.99 7.90

Yosemite NP CA 16.87 15.98 15.98 15.85 15.84 7.64

Black Canyon of the 

Gunnison NM CO 10.04 9.21 9.20 9.26 9.24 6.21

Eagles Nest Wilderness CO 8.94 7.98 7.97 7.97 7.93 6.06

Flat Tops Wilderness CO 8.94 8.26 8.26 8.28 8.27 6.06

Great Sand Dunes NM CO 11.44 10.57 10.56 10.59 10.57 6.66
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Class 1 Area

(20% worst days) State

2007

Baseline 

Visibility

(dv)a

2018

Reference

2018

Tier 3 

Control

2030 

Reference

2030

Tier 3 

Control

Natural 

Background

La Garita Wilderness CO 10.04 9.36 9.35 9.44 9.43 6.21

Maroon Bells-Snowmass 

Wilderness CO 8.94 8.15 8.14 8.18 8.17 6.06

Mesa Verde NP CO 11.28 10.48 10.47 10.57 10.55 6.81

Mount Zirkel Wilderness CO 9.72 9.12 9.11 9.10 9.08 6.08

Rawah Wilderness CO 9.72 8.92 8.91 8.88 8.86 6.08

Rocky Mountain NP CO 12.62 11.66 11.64 11.55 11.50 7.15

Weminuche Wilderness CO 10.04 9.38 9.37 9.45 9.44 6.21

West Elk Wilderness CO 8.94 8.12 8.11 8.18 8.16 6.06

Chassahowitzka FL 23.68 18.63 18.59 18.38 18.31 11.03

Everglades NP FL 20.41 17.43 17.42 17.28 17.25 12.15

St. Marks FL 25.58 20.07 20.04 19.86 19.81 11.67

Cohutta Wilderness GA 28.01 18.77 18.73 18.59 18.52 10.78

Okefenokee GA 26.00 21.32 21.30 21.33 21.31 11.44

Wolf Island GA 26.00 20.53 20.51 20.45 20.41 11.44

Craters of the Moon NM ID 13.63 12.91 12.86 12.63 12.54 7.53

Sawtooth Wilderness ID 14.76 14.61 14.61 14.58 14.57 6.42

Mammoth Cave NP KY 30.68 21.59 21.55 21.47 21.41 11.08

Acadia NP ME 21.45 17.41 17.38 17.22 17.19 12.43

Moosehorn ME 19.92 16.23 16.21 16.14 16.12 12.01

Roosevelt Campobello 

International Park ME 19.92 16.45 16.43 16.34 16.32 12.01

Isle Royale NP MI 21.76 18.49 18.45 18.21 18.13 12.37

Seney MI 24.21 20.30 20.26 20.17 20.09 12.65

Boundary Waters Canoe 

Area MN 20.05 17.05 17.01 16.77 16.70 11.61

Voyageurs NP MN 19.78 17.60 17.57 17.35 17.29 12.06

Hercules-Glades 

Wilderness MO 26.05 20.36 20.32 20.21 20.14 11.30

Mingo MO 27.08 21.09 21.06 20.88 20.83 11.62

Bob Marshall Wilderness MT 15.32 15.13 15.13 15.06 15.05 7.73

Cabinet Mountains 

Wilderness MT 13.47 13.16 13.15 13.01 13.00 7.52

Glacier NP MT 18.70 18.39 18.38 18.23 18.21 9.18

Medicine Lake MT 18.02 16.67 16.66 16.47 16.45 7.89

Mission Mountains 

Wilderness MT 15.32 15.08 15.07 14.98 14.97 7.73

Red Rock Lakes MT 11.53 11.20 11.19 11.13 11.11 6.44

Scapegoat Wilderness MT 15.32 15.17 15.17 15.12 15.11 7.73

UL Bend MT 14.86 14.41 14.41 14.37 14.36 8.16
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Class 1 Area

(20% worst days) State

2007

Baseline 

Visibility

(dv)a

2018

Reference

2018

Tier 3 

Control

2030 

Reference

2030

Tier 3 

Control

Natural 

Background

Linville Gorge Wilderness NC 27.39 18.40 18.37 18.33 18.28 11.22

Shining Rock Wilderness NC 26.60 18.17 18.13 18.04 17.98 11.47

Lostwood ND 19.56 18.58 18.57 18.45 18.44 8.00

Great Gulf Wilderness NH 20.19 15.15 15.13 15.08 15.05 11.99

Presidential Range-Dry 

River Wilderness NH 20.19 15.05 15.03 14.97 14.94 11.99

Brigantine NJ 27.32 20.66 20.63 20.59 20.55 12.24

Bandelier NM NM 11.84 10.81 10.79 10.89 10.85 6.26

Bosque del Apache NM 13.40 12.32 12.30 12.54 12.50 6.73

Carlsbad Caverns NP NM 15.85 15.19 15.18 15.88 15.86 6.65

Gila Wilderness NM 12.49 11.94 11.94 12.40 12.39 6.66

Pecos Wilderness NM 9.13 8.19 8.18 8.34 8.32 6.08

San Pedro Parks Wilderness NM 9.89 9.06 9.05 9.28 9.27 5.72

Wheeler Peak Wilderness NM 9.13 8.13 8.13 8.25 8.23 6.08

White Mountain 

Wilderness NM 13.20 12.34 12.33 12.74 12.73 6.80

Jarbidge Wilderness NV 12.42 12.17 12.16 12.13 12.12 7.87

Wichita Mountains OK 22.97 19.63 19.60 19.52 19.45 7.53

Crater Lake NP OR 13.79 13.33 13.32 13.22 13.22 7.62

Diamond Peak Wilderness OR 13.79 13.23 13.22 13.07 13.07 7.62

Eagle Cap Wilderness OR 16.23 15.61 15.59 15.22 15.20 8.92

Gearhart Mountain 

Wilderness OR 13.79 13.35 13.35 13.27 13.27 7.62

Hells Canyon Wilderness OR 18.15 17.54 17.50 17.20 17.16 8.32

Kalmiopsis Wilderness OR 16.45 15.82 15.81 15.63 15.62 9.44

Mount Hood Wilderness OR 13.72 12.71 12.68 12.25 12.23 8.43

Mount Jefferson 

Wilderness OR 16.18 15.58 15.57 15.33 15.31 8.79

Mount Washington 

Wilderness OR 16.18 15.57 15.55 15.32 15.31 8.79

Mountain Lakes Wilderness OR 13.79 13.28 13.28 13.16 13.16 7.62

Strawberry Mountain 

Wilderness OR 16.23 15.37 15.34 15.00 14.97 8.92

Three Sisters Wilderness OR 16.18 15.63 15.61 15.45 15.44 8.79

Cape Romain SC 26.45 19.75 19.72 19.61 19.56 12.12

Badlands NP SD 16.55 15.25 15.24 15.19 15.17 8.06

Wind Cave NP SD 15.50 14.41 14.39 14.26 14.24 7.71

Great Smoky Mountains 

NP TN 28.50 19.57 19.52 19.44 19.38 11.24
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Class 1 Area

(20% worst days) State

2007

Baseline 

Visibility

(dv)a

2018

Reference

2018

Tier 3 

Control

2030 

Reference

2030

Tier 3 

Control

Natural 

Background

Joyce-Kilmer-Slickrock 

Wilderness TN 28.50 19.65 19.61 19.52 19.46 11.24

Big Bend NP TX 16.69 16.39 16.38 17.32 17.31 7.16

Guadalupe Mountains NP TX 15.85 15.23 15.22 15.94 15.92 6.65

Arches NP UT 11.02 10.33 10.32 10.30 10.27 6.43

Bryce Canyon NP UT 11.88 11.40 11.40 11.39 11.37 6.80

Canyonlands NP UT 11.02 10.50 10.48 10.57 10.55 6.43

Capitol Reef NP UT 11.30 10.73 10.72 10.74 10.72 6.03

James River Face 

Wilderness VA 27.29 19.05 19.02 18.89 18.83 11.13

Shenandoah NP VA 27.26 17.67 17.63 17.60 17.54 11.35

Lye Brook Wilderness VT 23.01 16.74 16.70 16.58 16.53 11.73

Alpine Lake Wilderness WA 16.09 14.87 14.84 14.22 14.17 8.43

Glacier Peak Wilderness WA 13.72 12.78 12.77 12.56 12.54 8.39

Goat Rocks Wilderness WA 12.66 11.92 11.90 11.66 11.64 8.35

Mount Adams Wilderness WA 12.66 12.04 12.02 11.77 11.75 8.35

Mount Rainier NP WA 16.38 15.53 15.52 15.25 15.24 8.54

North Cascades NP WA 13.72 12.87 12.86 12.71 12.70 8.01

Olympic NP WA 15.20 14.30 14.28 13.94 13.92 8.44

Pasayten Wilderness WA 14.09 13.51 13.50 13.26 13.25 8.25

Dolly Sods Wilderness WV 27.55 17.97 17.94 17.99 17.95 10.39

Otter Creek Wilderness WV 27.55 18.11 18.07 18.08 18.04 10.39

Bridger Wilderness WY 10.68 10.23 10.22 10.20 10.19 6.45

Fitzpatrick Wilderness WY 10.68 10.21 10.21 10.18 10.17 6.45

Grand Teton NP WY 11.53 11.14 11.13 11.09 11.07 6.44

Teton Wilderness WY 11.53 11.18 11.18 11.15 11.14 6.44

Yellowstone NP WY 11.53 11.26 11.26 11.23 11.22 6.44

a

 The level of visibility impairment in an area is based on the light-extinction coefficient and a unitless visibility 

index, called a “deciview”, which is used in the valuation of visibility. The deciview metric provides a scale for 

perceived visual changes over the entire range of conditions, from clear to hazy. Under many scenic conditions, the 

average person can generally perceive a change of one deciview. The higher the deciview value, the worse the 

visibility. Thus, an improvement in visibility is a decrease in deciview value. 

7.2.4.6 Deposition of Nitrogen and Sulfur 

As described in Section 6.2.2 of this RIA, deposition of nitrogen and sulfur can cause 

adverse environmental effects. In this section we present information on current and modelprojected future nitrogen and sulfur deposition levels. 
7-124

7.2.4.6.1 Current Levels of Nitrogen and Sulfur Deposition 

Over the past two decades, the EPA has undertaken numerous efforts to reduce nitrogen 

and sulfur deposition across the U.S. Analyses of long-term monitoring data for the U.S. show 

that deposition of both nitrogen and sulfur compounds has decreased over the last 17 years. The 

data show that reductions were more substantial for sulfur compounds than for nitrogen 

compounds. In the eastern U.S., where data are most abundant, total sulfur deposition decreased 

by about 44 percent between 1990 and 2007, while total nitrogen deposition decreased by 25 

percent over the same time frame.JJ These numbers are generated by the U.S. national 

monitoring network and they likely underestimate nitrogen deposition because neither ammonia 

nor organic nitrogen is measured. Although total nitrogen and sulfur deposition has decreased 

over time, many areas continue to be negatively impacted by deposition. Deposition of inorganic 

nitrogen and sulfur species routinely measured in the U.S. between 2005 and 2007 were as high 

as 9.6 kilograms of nitrogen per hectare (kg N/ha) averaged over three years and 20.8 kilograms 

of sulfur per hectare (kg S/ha) averaged over three years.KK 

 

JJ U.S. EPA. (2012). U.S. EPA’s Report on the Environment. Data accessed online February 15, 2012 at: 

http://cfpub.epa.gov/eroe/index.cfm?fuseaction=detail.viewPDF&ch=46&lShowInd=0&subtop=341&lv=list.listBy

Chapter&r=216610 and contained in Docket EPA-HQ-OAR-2011-0135. 

KK U.S. EPA. (2012). U.S. EPA's Report on the Environment. Data accessed online February 15, 2012 at: 

http://cfpub.epa.gov/eroe/index.cfm?fuseaction=detail.viewPDF&ch=46&lShowInd=0&subtop=341&lv=list.listBy

Chapter&r=216610 and contained in Docket EPA-HQ-OAR-2011-0135. 
7-125

Figure 7-44 Total Sulfur Deposition in the Contiguous U.S., 1989-1991 and 2005 -2007
7-126

Figure 7-45 Total Nitrogen Deposition in the Contiguous U.S., 1989-1991 and 2005-2007 
7-127

7.2.4.6.2 Projected Levels of Nitrogen and Sulfur Deposition 

Our air quality modeling projects decreases in both nitrogen and sulfur deposition due to 

this rule. Figure 7-46 shows that for nitrogen deposition by 2030 the standards would result in 

annual percent decreases of more than 2.5 percent in most urban areas with decreases of more 

than 5 percent in urban areas in Nevada, Florida, Georgia and Virginia. In addition, smaller 

decreases, in the 1 to 1.5 percent range, would occur over much of the rest of the country. 

Figure 7-46 Percent Change in Annual Total Nitrogen Deposition over the U.S. Modeling 

Domain as a Result of the Tier 3 Standards 

Figure 7-47 shows that for sulfur deposition the standards will result in annual percent 

decreases of more than 2 percent in some urban areas in 2030. The decreases in sulfur 

deposition are likely due to projected reductions in the sulfur level in fuel. Minimal changes in 

sulfur deposition, ranging from decreases of less than 0.5 percent to no change, are projected for 

the rest of the country. 
7-128

Figure 7-47 Percent Change in Annual Total Sulfur Deposition over the U.S. Modeling 

Domain as a Result of the Tier 3 Standards 

7.3 Greenhouse Gas Emission Impacts

Reductions in nitrous oxide (N2O) emissions and methane (CH4) emissions, both potent 

greenhouse gas emissions (with global warming potentials 298 and 25 times greater than CO2, 

respectively),LL are projected for gasoline cars and trucks due to the sulfur and tailpipe standards. 

These projections are based on studies that provide a basis for reductions in N2O and CH4

emissions due to the Tier 3 sulfur and vehicle standards. With respect to sulfur, a study 

published in 2004 by the University of California at Riverside found a 29 percent reduction in 

N2O emissions over the FTP and a 50 percent reduction over the US06 when sulfur was reduced 

from 30 to 5 ppm.146

 EPA’s sulfur study, detailed in Section 7.1.3.4.1, found close to a 30

percent reduction in CH4 emissions over the FTP when sulfur was reduced from 28 to 5 ppm (the 

EPA study did not measure N2O emissions). 

 

LL The global warming potentials (GWP) used in this rule are consistent with the 100-year time frame values in the 

2007 Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). N2O has a 100-year 

GWP of 298 and CH4 has a 100-year GWP of 25 according to the 2007 IPCC AR4.
7-129

Several studies have also established that reductions in tailpipe standards for NOX and 

HC result in reductions in N2O and CH4, respectively. N2O is unique in that it is not formed 

during combustion, but in the catalyst, during catalyst warm-up, before the catalyst reaches the 

temperatures required for full effectiveness (known as “light-off”). Improvements to catalyst 

technology required to meet lower emission standards reduce the time required for the catalyst to 

reach light-off, which reduces the window of N2O formation. Studies conducted by EPA and 

Environment Canada found that N2O emission are lower on vehicles certified to more stringent 

NOX emission standards.147,148 A study by Meffert, et al. established a strong correlation 

between improvements in NOX catalytic conversion efficiency and reductions in N2O 

emissions.149 A study published by Behrentz, et al. in 2004 examined the relationship between 

N2O and NOX from data collected by the California Air Resources Board (CARB) on 37 

passenger cars and light-duty trucks ranging from the mid-1980s through early 2000’s Low 

Emission Vehicle (LEV) technology.150 Another study by Winer, et al (2005) tested 134 lightduty vehicles, including passenger cars and light-duty trucks, as part of the CARB’s vehicle 

surveillance program, varying from Tier 0 to ULEV in emissions standards.151 These two studies 

reported N2O:NOX ratios of 0.06 and 0.095, respectively, and supported the application of 

N2O:NOX ratios to NOX emissions as a reasonable method for estimating N2O emission 

inventories. Meszler, et al. subsequently analyzed the dataset by Behrentz and found that for 

vehicles equipped with more modern controls, N2O emissions increased with vehicle mileage, 

suggesting deterioration in N2O emissions as vehicles age. 152 

The Meszler and Environment Canada studies cited above also established that vehicles 

certified to more stringent HC standards emit less CH4, even though HC standards from Tier 1 

and later do not include methane in the regulated standards. This trend is also reflected in the 

MOVES model, based on analysis of correlation between CH4 and HC emissions. MOVES

estimates methane as a function of total HC emissions, so the CH4 emission inventories account 

for effects such as deterioration, temperature, aggressive driving, and reductions in tailpipe 

emission standards. Because of this, CH4 reductions from the Tier 3 program can be estimated 

directly by MOVES, as a function of reductions in HC from the sulfur and vehicle standards 

(although this will provide a conservative estimate of reductions, as the percent reduction in CH4

from using low sulfur fuel is about double that for total HC (Table 7-25)). The estimated 

methane reductions from Tier 3, using the 100-year global warming potential of 25 according to 

the 2007 IPCC AR4, are shown in Table 7-53. 

Table 7-53 Estimated Reduction in CH4 from Tier 3 Program (MMTCO2eq) 

2018 2030

Reference case onroad 

mobile emissions 1.5 1.2

Control case onroad 

mobile emissions 1.4 0.9

Reduction 0.1 0.3

In contrast, MOVES N2O emissions are based directly on a limited sample of N2O 

emission data, rather than linking N2O emissions to NOX emissions as suggested by Winer and 

Behrentz; as a result, the model does not estimate potential N2O reduction concurrent with the 

Tier 3 program. Because of this, the MOVES-based inventories are significantly lower than 
7-130

inventories that take into account the N2O:NOX link, because they do not account for the factors 

affecting light-duty NOX emissions, such as deterioration, aggressive driving, and lower NOX

standards. 

In an effort to estimate the N2O inventory accounting for the factors that affect N2O 

emissions, we analyzed the data collected by CARB from 2000 to 2007, as a part of CARB’s 

vehicle surveillance program. The data described in Winer and Behrentz were also collected as a 

part of the same program. However, the data we analyzed, available in the docket,153 is the most 

comprehensive since it included additional tests that CARB collected since the studies by Winer 

and Behrentz. A regression analysis was performed to examine the relationship between N2O 

and NOX, and the resulting regression model correlating N2O emissions to NOX emissions is 

shown in Equation 7-4. The details of the regression analysis are documented in a separate 

memorandum to the Tier 3 docket.154

Equation 7-4 Regression Model Correlating N2O Emissions to NOX Emissions 

The N2O reductions due to Tier 3 vehicle and sulfur standards are estimated by 

employing two different methodologies, resulting in a range of reductions. The first method 

applies the relationship between N2O and NOX from the regression model in Equation 7-4 to 

NOX inventories from both Tier 3 and pre-Tier 3 vehicles. The second method applies the 

regression of N2O and NOX only to Tier 3 fleet (2017 and later model year vehicles) and applies 

the percent reduction in N2O from the UC Riverside study to MOVES inventory estimates to 

pre-Tier 3 vehicles. These two methods are outlined in Table 7-54, along with the range of 

reductions that result. 
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Table 7-54 Estimated Reduction in N2O from the Tier 3 Program 

2018 2030

Reduction from Tier 3 fleet

NOX reduction from Tier 3 fleet due to 

vehicle and sulfur standards (U.S. Short Tons)

21,934 272,185

N2O reduction based on the regression

(MMTCO2eqa)

0.3 3.5

Reduction from pre-Tier 3 fleet

Method 1

Reference case onroad gasoline NOX

emissions (U.S. Short Tons)

2,599,284 377,811

Reference case onroad gasoline N2O 

emissions based on the regression

(MMTCO2eqa)

31.6 5.0

Reduction from pre-Tier 3 fleet due to sulfur 

standard (U.S. Short Tons)

242,434 56,324

N2O reduction based on the regression

(MMTCO2eqa)

1.9 0.5

Method 2

U.S. onroad gasoline N2O emissions from 

pre-Tier 3 fleet using MOVES (MMTCO2eq)

8.9 1.5

Percent reduction in N2O going from 30 to 10 

ppm

23% b23%

N2O reduction (MMTCO2eq) 1.9 0.3

Total Range of N2O Reduction 

(MMTCO2eq)

2.2 3.8-4.0

a

 Using GWP of 298 

b 29 percent from 25ppm sulfur reduction in UC Riverside study scaled to 20 ppm reduction 

The estimated N2O reduction is 2.2 million metric tons of carbon dioxide equivalent 

(MMTCO2eq) in 2018, growing to a range between 3.8 and 4.0 MMTCO2eq in 2030. For 2018, 

there was an agreement between the two methodologies described above, resulting in a single 

estimate. Summing the results from Table 7-53 and Table 7-54, the total GHG reductions from 

the Tier 3 rule is 2.3 million metric tons of carbon dioxide equivalent (MMTCO2eq) in 2018, 

growing to a range between 4.1 and 4.3 MMTCO2eq in 2030. 

These reductions will be offset to some degree by CO2 emissions associated with higher 

energy use required in the process of removing sulfur within the refinery. As an extension of our 

refinery-by-refinery cost modeling, we calculated the CO2 emission impacts of Tier 3 gasoline 

sulfur control. We estimated refinery-specific changes in process energy and then applied 

emission factors that correspond to those changes, on a refinery-by-refinery basis. As described 

in Chapter 4.5 of the RIA, the results showed an increase of up to 1.9 MMTCO2e in 2018 and 1.6 

MMTCO2e in 2030 for all U.S. refineries complying with the lower sulfur standards assuming 

that the sulfur standards are fully phased-in. In 2018, the combined impact of CH4 and N2O 

emission reductions from the vehicles and CO2 emission increases from the refineries shows a 
7-132

slight net decrease on a CO2 equivalent basis. While still small, this net decrease grows to a 

range between 2.5 to 2.7 MMTCO2e by 2030. 

We do not expect the Tier 3 vehicle standards to result in any discernible changes in 

vehicle CO2 emissions or fuel economy. Emissions of the pollutants that are controlled by the 

Tier 3 program – NMOG, NOX, and PM – are not a function of the amount of fuel consumed, 

since manufacturers need to design their catalytic emission control systems to reduce these 

emissions regardless of their engine-out levels. 
7-133

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M Lewandowski, JH Offenberg, EO Edney (2007) Hydroxydicarboxylic acids: Markers for secondary organic 

-pinene. Environ Sci Technol 41(5): 1628-1634. 

108 Edney EO, TE Kleindienst, M Jaoui, M Lewandowski, JH Offenberg, W Wang, M Claeys (2005) Formation of 

2-methyl tetrols and 2-methylglyceric acid in secondary organic aerosol from laboratory irradiated 

isoprene/NOX/SO2/air mixtures and their detection in ambient PM2.5 samples collected in the Eastern United States. 

Atmos Environ 39: 5281-5289. 

109 Jaoui M, TE Kleindienst, M Lewandowski, JH Offenberg, EO Edney (2005) Identification and quantification of 

aerosol polar oxygenated compounds bearing carboxylic or hydroxyl groups. 2. Organic tracer compounds from 

monoterpenes. Environ Sci Technol 39: 5661-5673. 

110 Kleindienst TE, TS Conver, CD McIver, EO Edney (2004) Determination of secondary organic aerosol products 

from the photooxidation of toluene and their implications in ambient PM2.5. J Atmos Chem 47: 70-100. 

111 Kleindienst TE, TS Conver, CD McIver, EO Edney (2004) Determination of secondary organic aerosol products 

from the photooxidation of toluene and their implication in ambient PM2.5, J Atmos Chem 47: 70-100. 

112 Pye et al. 2013 ES&T Epoxide pathways improve model predictions of isoprene markers and reveal key 

role of acidity in aerosol formation, http://pubs.acs.org/doi/abs/10.1021/es402106h

113 Carlton et al. 2010 ES&T Can biogenic SOA be controlled? http://pubs.acs.org/doi/full/10.1021/es903506b

114 Lewandowski M, M Jaoui , JH Offenberg , TE Kleindienst, EO Edney, RJ Sheesley, JJ Schauer (2008) Primary 

and secondary contributions to ambient PM in the midwestern United States, Environ Sci Technol 42(9):3303-3309. 

http://pubs.acs.org/cgi-bin/article.cgi/esthag/2008/42/i09/html/es0720412.html. 

115 Kleindienst TE, M Jaoui, M Lewandowski, JH Offenberg, EO Edney (2007) Estimates of the contributions of 

biogenic and anthropogenic hydrocarbons to secondary organic aerosol at a southeastern U.S. location. Atmos 

Environ 41(37):8288-8300. 

116 Henze DK, JH Seinfeld (2006) Global secondary organic aerosol from isoprene oxidation. Geophys Res Lett 33: 

L09812. doi:10.1029/2006GL025976. 
7-139

117 Hildebrandt, L., Donahue1, N. M, Pandis1, S. N. (2009) High formation of secondary organic aerosol from the 

photo-oxidation of toluene. Atmos Chem Phys 9: 2973-2986. Docket EPA-HQ-OAR-2011-0135. 

118 Ng, N. L., Kroll, J. H., Chan, A. W. H., Chabra, P. S., Flagan, R. C., Seinfield, J. H., Secondary organic aerosol 

formation from m-xylene, toluene, and benzene, Atmospheric Chemistry and Physics Discussion, 7, 3909-3922, 

2007. Docket EPA-HQ-OAR-2011-0135. 

119 Henze, D. K., Seinfeld, J. H., Ng, N. L., Kroll, J. H., Fu, T.-M., Jacob, D. J., and Heald, C. L. (2008) Global 

modeling of secondary organic aerosol formation from aromatic hydrocarbons: high- vs. low-yield pathways, 

Atmos. Chem. Phys., 8, 2405-2420, doi:10.5194/acp-8-2405-2008. 

120 Lane, T. E., Donahue, N.M. and Pandis, S.N. (2008) Simulating secondary organic aerosol formation using the 

volatility basis-set approach in a chemical transport model, Atmos. Environ., 42, 7439-7451, doi: 

10.1016/j.atmosenv.2008.06.026. 

121 Carlton, A.G., Bhave, P.V., Napelenok, S.L., Edney, E.O., Sarwar, g., Pinder, R.W., Pouliot, G.A., Houyoux, M., 

(2010). Model Representation of Secondary Organic Aerosol in CMAQv4.7. Environ Sci Technol 44(22), 8553-

8560.

122 Parikh, H.M., Carlton, A.G., Vizuete, W., and Kamen, R.M. (2011) Modeling secondary organic aerosol using a 

dynamic partitioning approach incorporating particle aqueous-phase chemistry, Atmospheric Environment, 45, 

1126-1137. 

123 Volkamer, R., J.L. Jimenez, F. SanMartini,K.Dzepina,Q. Zhang,D. Salcedo,L. T. Molina, D. R.Worsnop, and M. 

J. Molina (2006), Secondary organic aerosol formation from anthropogenic air pollution: Rapid and higher than 

expected, Geophys. Res. Lett., 33, L17811, doi:10.1029/2006GL026899. 

124 Carlton, A.G., Bhave, P.V., Napelenok, S.L., Edney, E.O., Sarwar, g., Pinder, R.W., Pouliot, G.A., Houyoux, M., 

(2010). Model Representation of Secondary Organic Aerosol in CMAQv4.7. Environ Sci Technol 44(22), 8553-

8560.

125 Robinson, A. L.; Donahue, N. M.; Shrivastava, M.; Weitkamp, E. A.; Sage, A. M.; Grieshop, A. P.; Lane, T. E.; 

Pierce, J. R.; Pandis, S. N. (2007) Rethinking organic aerosol: Semivolatile emissions and photochemical aging. 

Science 315: 1259-1262. Docket EPA-HQ-OAR-2011-0135. 

126 Carlton, A.G., Bhave, P.V., Napelenok, S.L., Edney, E.O., Sarwar, g., Pinder, R.W., Pouliot, G.A., Houyoux, M., 

(2010). Model Representation of Secondary Organic Aerosol in CMAQv4.7. Environ Sci Technol 44(22), 8553-

8560.

127 Atkinson, R., Baulch, D.L., Cox, R.A., Crowley, J.N., Hampson, R.F. Jr., Hynes, R.G., Jenkin, M.E., Kerr, J.A., 

Rossi, M.J., Troe, J. (2005) Evaluated Kinetic and Photochemical Data for Atmospheric Chemistry - IUPAC 

Subcommittee on Gas Kinetic Data Evaluation for Atmospheric Chemistry. July 2005 web version. 

http://www.iupac-kinetic.ch.cam.ac.uk/index.html. Docket EPA-HQ-OAR-2011-0135. 

128 Sander, S.P., Friedl, R.R., Golden, D.M., Kurylo, M.J., Huie, R.E., Orkin, V.L., Moortgat, G.K., Ravishankara, 

A.R., Kolb, C.E., Molina, M.J., Finlayson-Pitts, B.J. (2003) Chemical Kinetics and Photochemical Data for use in 

Atmospheric Studies, Evaluation Number 14. NASA Jet Propulsion Laboratory. 

http://jpldataeval.jpl.nasa.gov/index.html. Docket EPA-HQ-OAR-2011-0135. 

129 Finlayson-Pitts BJ, Pitts JN Jr. (1986) Atmospheric Chemistry: Fundamentals and Experimental Techniques, 

Wiley, New York.

130 Yarwood G, Rao S, Yocke M, Whitten GZ (2005) Updates to the Carbon Bond Chemical Mechanism: CB05. 

Final Report to the U.S. EPA, RT-0400675, December 8, 2005. 

http://www.camx.com/publ/pdfs/CB05_Final_Report_120805.pdf. Docket EPA-HQ-OAR-2011-0135, 

131 http://www.cmascenter.org/help/model_docs/cmaq/4.7/RELEASE_NOTES.txt. 

132 77 FR 30088 (May 21, 2012) and 77 FR 34221 (June 11, 2012). 

133 77 FR 30088 (May 21, 2012) and 77 FR 34221 (June 11, 2012). 
7-140

133 U.S. EPA (2012). National Ambient Air Quality Standards for Particulate Matter. 

http://www.epa.gov/PM/2012/finalrule.pdf. 

134 U.S. EPA (2012). Fact Sheet: Implementing the Standards. 

http://www.epa.gov/airquality/particlepollution/2012/decfsimp.pdf. 

135 U.S. EPA. (2012). Fact Sheet – Air Quality Designations for the 2010 Primary Nitrogen Dioxide (NO2) National 

Ambient Air Quality Standards. http://www.epa.gov/airquality/nitrogenoxides/designations/pdfs/20120120FS.pdf. 

136

 U.S. Environmental Protection Agency (2013). Revision to Ambient Nitrogen Dioxide Monitoring 

Requirements. March 7, 2013. http://www.epa.gov/airquality/nitrogenoxides/pdfs/20130307fr.pdf. 

137 U.S. Environmental Protection Agency (2007). Control of Hazardous Air Pollutants from Mobile Sources; Final 

Rule. 72 FR 8434, February 26, 2007. 

138 U.S. Environmental Protection Agency (2007). Control of Hazardous Air Pollutants from Mobile Sources; Final 

Rule. 72 FR 8434, February 26, 2007. 

139 U.S. EPA. (2011) 2005 National-Scale Air Toxics Assessment. http://www.epa.gov/ttn/atw/nata2005/. Docket 

EPA-HQ-OAR-2011-0135.

140 U.S. EPA. (2011) Summary of Results for the 2005 National-Scale Assessment. 

http://www.epa.gov/ttn/atw/nata2005/05pdf/sum_results.pdf. 

141 Luecken, D,J, Clmorel, A.J. 2008. Codependencies of Reactive Air Toxic and Criteria Pollutants on Emission 

Reductions. J. Air & Waste Manage. Assoc. 58:693–701. DOI:10.3155/1047-3289.58.5.693.

142 U.S. Environmental Protection Agency (EPA). 2009. Integrated Science Assessment for Particulate Matter. U.S. 

Environmental Protection Agency. Research Triangle Park. EPA/600/R-08/139F. 

143 Trijonis, J.C. et al. 1987. Preliminary extinction budget results from the RESOLVE program, pp. 872-883. In: 

P.J. Bhardwaja, et. al. Visibility Protection Research and Policy Aspects. Air Pollution Control Assoc., Pittsburgh, 

PA.

144 Trijonis, J.C. et al. 1988. RESOLVE Project Final Report: Visibility conditions and Causes of Visibility 

Degradation in the Mojave Desert of California. NWC TP #6869. Naval Weapons Center, China Lake, CA.

145 Irving, Patricia M., e.d., 1991. Acid Deposition: State of Science and Technology, Volume III, Terrestrial, 

Materials, Health, and Visibility Effects, The U.S. National Acid Precipitation Assessment Program, Chapter 24, 

page 24–76. 

146 Huai, et al. (2004) Estimates of the emission rates of nitrous oxide from light-duty vehicles using different 

chassis dynamometer test cycles Atmospheric Environment 6621-6629. 

147 Michaels, H. (1998) Emissions of Nitrous Oxide from Highway Mobile Sources, U.S. EPA EPA420-R-98-009. 

148 Graham, L. (2006) Greenhouse Gas Emissions from 1997-2005 Model Year Light Duty Vehicles Environment 

Canada ERMD Report #04-44. 

149 Meffert, et al (2000) Analysis of Nitrous Oxide Emissions from Light Duty Passenger Cars, SAE 2000-01-1952. 

150 Behrentz, et al. (2004) Measurements of nitrous oxide emissions from light-duty motor vehicles: a pilot study 

Atmospheric Environment 4291-4303. 

151 Winer, et al. (2005) Estimates of Nitrous Oxide Emissions and the Effects of Catalyst Composition and Aging, 

State of California Air Resources Board 02-313.

152 Meszler, D. (2004) Light Duty Vehicle Methane and Nitrous Oxide Emissions: Greenhouse Gas Impacts Study 

for Northeast States Center for a Clean Air Future. 

153 Nitrous Oxide and Oxides of Nitrogen Emissions Data from California Air Resources Board’s Vehicle 

Surveillance Program. 

154 U.S. EPA, 2014, Memorandum to Docket: Regression Analysis of Nitrous Oxide and Oxides of Nitrogen from 

Motor Vehicles. 
7A-1 

7.A. Appendix to Chapter 7: Additional Air Toxics Emissions and 

Air Quality Modeling Results 

7A.1. Air Toxics Emissions 

Table 7A-1 Mobile Source Air Toxics Included in Inventory Reductions 

Pollutant ID number Pollutant Name

144 1,2,3,4,6,7,8-Heptachlorodibenzofuran

132 1,2,3,4,6,7,8-Heptachlorodibenzo-p-Dioxin

137 1,2,3,4,7,8,9-Heptachlorodibenzofuran

145 1,2,3,4,7,8-Hexachlorodibenzofuran

134 1,2,3,4,7,8-Hexachlorodibenzo-p-Dioxin

140 1,2,3,6,7,8-Hexachlorodibenzofuran

141 1,2,3,6,7,8-Hexachlorodibenzo-p-Dioxin

146 1,2,3,7,8,9-Hexachlorodibenzofuran

130 1,2,3,7,8,9-Hexachlorodibenzo-p-Dioxin

139 1,2,3,7,8-Pentachlorodibenzofuran

135 1,2,3,7,8-Pentachlorodibenzo-p-Dioxin

24 1,3-Butadiene

40 2,2,4-Trimethylpentane

143 2,3,4,6,7,8-Hexachlorodibenzofuran

138 2,3,4,7,8-Pentachlorodibenzofuran

136 2,3,7,8-Tetrachlorodibenzofuran

142 2,3,7,8-Tetrachlorodibenzo-p-Dioxin

170 Acenaphthene gas

70 Acenaphthene particle

171 Acenaphthylene gas

71 Acenaphthylene particle

26 Acetaldehyde

27 Acrolein

172 Anthracene gas

72 Anthracene particle

63 Arsenic Compounds

173 Benz(a)anthracene gas

73 Benz(a)anthracene particle

20 Benzene

174 Benzo(a)pyrene gas

74 Benzo(a)pyrene particle

175 Benzo(b)fluoranthene gas

75 Benzo(b)fluoranthene particle
7A-2 

Pollutant ID number Pollutant Name

176 Benzo(g,h,i)perylene gas

76 Benzo(g,h,i)perylene particle

177 Benzo(k)fluoranthene gas

77 Benzo(k)fluoranthene particle

64 Chromium 3+

65 Chromium 6+

178 Chrysene gas

78 Chrysene particle

168 Dibenzo(a,h)anthracene gas

68 Dibenzo(a,h)anthracene particle

21 Ethanol

41 Ethyl Benzene

169 Fluoranthene gas

69 Fluoranthene particle

181 Fluorene gas

81 Fluorene particle

25 Formaldehyde

42 Hexane

182 Indeno(1,2,3,c,d)pyrene gas

82 Indeno(1,2,3,c,d)pyrene particle

66 Manganese Compounds

61 Mercury Divalent Gaseous

60 Mercury Elemental Gaseous

62 Mercury Particulate

22 MTBE

185 Naphthalene gas

23 Naphthalene particle

67 Nickel Compounds

133 Octachlorodibenzofuran

131 Octachlorodibenzo-p-dioxin

183 Phenanthrene gas

83 Phenanthrene particle

43 Propionaldehyde

184 Pyrene gas

84 Pyrene particle

44 Styrene

45 Toluene

46 Xylene
7A-3 

7A.2. Seasonal Air Toxics Air Quality Modeling Results for 2018

The following section presents maps of seasonal changes in ambient concentrations of modeled 

air toxics in 2018. 

Benzene 

Figure 7A-1 Winter Changes in Benzene Ambient Concentrations Between the Reference Case and 

the Control Case in 2018: Percent Changes (left) and Absolute Changes in μg/m3 (right) 

Figure 7A-2 Summer Changes in Benzene Ambient Concentrations Between the Reference Case 

and the Control Case in 2018: Percent Changes (left) and Absolute Changes in μg/m3 (right) 
7A-4 

1,3-Butadiene 

Figure 7A-3 Winter Changes in 1,3-Butadiene Ambient Concentrations Between the Reference Case 

and the Control Case in 2018: Percent Changes (left) and Absolute Changes in μg/m3 (right) 

Figure 7A-4 Summer Changes in 1,3-Butadiene Ambient Concentrations Between the Reference 

Case and the Control Case in 2018: Percent Changes (left) and Absolute Changes in μg/m3 (right) 
7A-5 

Acrolein 

Figure 7A-5 Winter Changes in Acrolein Ambient Concentrations Between the Reference Case and 

the Control Case in 2018: Percent Changes (left) and Absolute Changes in μg/m3 (right) 

Figure 7A-6 Summer Changes in Acrolein Ambient Concentrations Between the Reference Case 

and the Control Case in 2018: Percent Changes (left) and Absolute Changes in μg/m3 (right) 
7A-6 

Ethanol 

Figure 7A-7 Winter Changes in Ethanol Ambient Concentrations Between the Reference Case and 

the Control Case in 2018: Percent Changes (left) and Absolute Changes in μg/m3 (right) 

Figure 7A-8 Summer Changes in Ethanol Ambient Concentrations Between the Reference Case and 

the Control Case in 2018: Percent Changes (left) and Absolute Changes in μg/m3 (right) 
7A-7 

Formaldehyde 

Figure 7A-9 Winter Changes in Formaldehyde Ambient Concentrations Between the Reference 

Case and the Control Case in 2018: Percent Changes (left) and Absolute Changes in μg/m3 (right) 

Figure 7A-10 Summer Changes in Formaldehyde Ambient Concentrations Between the Reference 

Case and the Control Case in 2018: Percent Changes (left) and Absolute Changes in μg/m3 (right) 
7A-8 

Acetaldehyde 

Figure 7A-11 Winter Changes in Acetaldehyde Ambient Concentrations Between the Reference 

Case and the Control Case in 2018: Percent Changes (left) and Absolute Changes in μg/m3 (right) 

Figure 7A-12 Summer Changes in Acetaldehyde Ambient Concentrations Between the Reference 

Case and the Control Case in 2018: Percent Changes (left) and Absolute Changes in μg/m3 (right) 
7A-9 

Naphthalene 

Figure 7A-13 Winter Changes in Naphthalene Ambient Concentrations Between the Reference Case 

and the Control Case in 2018: Percent Changes (left) and Absolute Changes in μg/m3 (right) 

Figure 7A-14 Summer Changes in Naphthalene Ambient Concentrations Between the Reference 

Case and the Control Case in 2018: Percent Changes (left) and Absolute Changes in μg/m3 (right) 
7A-10 

7A.3. Seasonal Air Toxics Air Quality Modeling Results for 2030 

The following section presents maps of seasonal changes in ambient concentrations of 

modeled air toxics in 2030. 

Benzene 

Figure 7A-15 Winter Changes in Benzene Ambient Concentrations Between the Reference Case and 

the Control Case in 2030: Percent Changes (left) and Absolute Changes in μg/m3 (right) 

Figure 7A-16 Summer Changes in Benzene Ambient Concentrations Between the Reference Case 

and the Control Case in 2030: Percent Changes (left) and Absolute Changes in μg/m3 (right) 
7A-11 

1,3-Butadiene 

Figure 7A-17 Winter Changes in 1,3-Butadiene Ambient Concentrations Between the Reference 

Case and the Control Case in 2030: Percent Changes (left) and Absolute Changes in μg/m3 (right) 

Figure 7A-18 Summer Changes in 1,3-Butadiene Ambient Concentrations Between the Reference 

Case and the Control Case in 2030: Percent Changes (left) and Absolute Changes in μg/m3 (right) 
7A-12 

Acrolein 

Figure 7A-19 Winter Changes in Acrolein Ambient Concentrations Between the Reference Case 

and the Control Case in 2030: Percent Changes (left) and Absolute Changes in μg/m3 (right) 

Figure 7A-20 Summer Changes in Acrolein Ambient Concentrations Between the Reference Case 

and the Control Case in 2030: Percent Changes (left) and Absolute Changes in μg/m3 (right) 
7A-13 

Ethanol 

Figure 7A-21 Winter Changes in Ethanol Ambient Concentrations Between the Reference Case and 

the Control Case in 2030: Percent Changes (left) and Absolute Changes in μg/m3 (right) 

Figure 7A-22 Summer Changes in Ethanol Ambient Concentrations Between the Reference Case 

and the Control Case in 2030: Percent Changes (left) and Absolute Changes in μg/m3 (right) 
7A-14 

Formaldehyde 

Figure 7A-23 Winter Changes in Formaldehyde Ambient Concentrations Between the Reference 

Case and the Control Case in 2030: Percent Changes (left) and Absolute Changes in μg/m3 (right) 

Figure 7A-24 Summer Changes in Formaldehyde Ambient Concentrations Between the Reference 

Case and the Control Case in 2030: Percent Changes (left) and Absolute Changes in μg/m3 (right) 
7A-15 

Acetaldehyde 

Figure 7A-25 Winter Changes in Acetaldehyde Ambient Concentrations Between the Reference 

Case and the Control Case in 2030: Percent Changes (left) and Absolute Changes in μg/m3 (right) 

Figure 7A-26 Summer Changes in Acetaldehyde Ambient Concentrations Between the Reference 

Case and the Control Case in 2030: Percent Changes (left) and Absolute Changes in μg/m3 (right) 
7A-16 

Naphthalene 

Figure 7A-27 Winter Changes in Naphthalene Ambient Concentrations Between the Reference Case 

and the Control Case in 2030: Percent Changes (left) and Absolute Changes in μg/m3 (right) 

Figure 7A-28 Summer Changes in Naphthalene Ambient Concentrations Between the Reference 

Case and the Control Case in 2030: Percent Changes (left) and Absolute Changes in μg/m3 (right) 
8-1

Chapter 8 Comparison of Program Costs to Program Air Quality 

Benefits 

EPA traditionally evaluates the effectiveness of a final rule in terms of net benefits. 

Section 8.1 below presents the cost-benefit analysis of the final rule. 

8.1 Cost-Benefit Analysis 

The net benefits of the final Tier 3 program are determined by the effects of the program 

on the costs to comply with the vehicle and fuel aspects of the program along with the benefits of 

improved air quality on health and the environment. 

8.1.1 Program-Wide Costs 

The costs that are incurred from our final program fall into three categories - for the Tier 

3 exhaust standards, Tier 3 evaporative standards, and reductions in sulfur content of gasoline. 

While we present these three categories of costs separately in this section, for purposes of the 

calculation of cost per ton of emissions reduced analysis we have summed them to represent the 

estimated costs of the final program. 

All costs represent the fleet-weighted average of light-duty vehicles and trucks. All costs 

are represented in 2011dollars. 

8.1.1.1 Vehicle Program Costs 

The vehicle costs include the technology costs projected to meet the final exhaust and 

evaporative standards including the facility and operating cost impacts, as detailed in RIA 

Chapter 2 and shown in Table 8-1. The fleet mix of light-duty vehicles, light duty trucks, and 

medium-duty trucks represents the MYs 2017-2025 fleet mix projected to result from the most 

recent GHG and fuel economy rules. The final vehicle costs are lower than the values projected 

in the proposal due to the items outlined in RIA Section 2.1 in addition to the exclusion of the 

vehicle sales in California and the states that have adopted the LEV III program. 

Table 8-1: Annual Vehicle Program Costs, 2011$ 

Year

Vehicle Exhaust 

Emission Control 

Costs ($Million)

Vehicle Evaporative 

Emission Control 

Costs ($Million)

Operating

Costs 

($Million)

Facility Costs 

($Million)

Total Vehicle 

Program Costs 

($Million)a

2016 $0 $0 $0 $21 $21

2017 $268 $26 $0 $4 $297

2018 $539 $73 -$1 $4 $615

2019 $579 $72 -$2 $4 $653

2020 $599 $98 -$3 $4 $697

2021 $630 $97 -$5 $4 $725

2022 $640 $121 -$6 $4 $758

2023 $639 $116 -$8 $4 $751
8-2

Year

Vehicle Exhaust 

Emission Control 

Costs ($Million)

Vehicle Evaporative 

Emission Control 

Costs ($Million)

Operating

Costs 

($Million)

Facility Costs 

($Million)

Total Vehicle 

Program Costs 

($Million)a

2024 $653 $114 -$9 $4 $761

2025 $668 $113 -$11 $4 $773

2030 $664 $113 -$19 $4 $761

a

 These estimates include costs associated with the Tier 3 vehicle standards in all states except California and states 

that have adopted the LEV III program. 

8.1.1.2 Fuel Program Costs 

The annual fuel costs of the Tier 3 program consist of the costs to the refiners to control 

sulfur on a per gallon basis and the total number of gallons consumed annually in the U.S. except 

in the state of California. 

The fuel costs associated with the additional operating and capital costs to refiners to 

meet the final sulfur average of 10 ppm, as described in detail in RIA Chapter 5, is 0.65 cents per 

gallon. The annual fuel costs of the final Tier 3 program are lower than the proposed fuel costs, 

0.89 cents, due to the reduction in cost per gallon to control sulfur. 

The fuel consumption values used in the annual fuel cost projections are based on the 

U.S. Energy Information Administration’s Annual Energy Outlook (AEO) 2013. The latest 

AEO projection used in the final rule cost projections contain lower annual fuel consumption 

than the values used in the Tier 3 proposal because AEO 2013 now reflects the light-duty GHG 

and fuel economy standards for the 2017-2025 model years. The light-duty standards are 

projected to decrease the national gasoline fuel consumption due to more efficient vehicles. 

The annual fuel consumption in AEO 2013 represents the national fuel usage in terms of 

BTU. For the fuel program cost analysis, it was necessary to convert the national BTU fuel 

consumption to millions of gallons of fuel consumed in the U.S. in all states except California. 

This conversion process is explained here using a sample year of 2017. Based on AEO 2013, the 

annual fuel consumption of motor gasoline and E85 in the transportation sector is projected to be 

15,342 trillion BTU in 2017.1

 AEO’s million BTU/barrel conversion factors for E85 and Motor 

Gasoline Average along with a conversion factor of 42 U.S. gallons of fuel per barrel were used 

to calculate the annual fuel consumption in terms of million gallons.2 Based on these 

conversions, the national fuel consumption in 2017 is projected to be 128,318 million gallons. 

Finally, the national fuel consumption values from AEO 2013 were reduced for this analysis to 

remove the fraction of gasoline sold in California. The AEO 2013 Prime Supplier Sales 

Volumes of Motor Gasoline provides the sales of motor gasoline by state.3

 Based on the average 

between 1983 and 2012, the fraction of national gasoline sales in California was 3.6 percent. 

After removing the fraction of fuel consumed in California, the annual fuel costs in 2017 are 

calculated based on a fuel consumption level of 123,689 million gallons. 

The Tier 3 fuel program provides flexibilities, including the ability for refiners to phasein the sulfur standards and earn early credits. The fuel program costs presented here assume a 

start date of 2017 and do not reflect the sulfur control program phase in. 
8-3

A comparison of the annual fuel consumption values used in the proposal and this final 

rule is shown in Figure 8-1.

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

2016 2018 2020 2022 2024 2026 2028 2030 2032 Annual Fuel Consumption (millions of gallons)

Year

Tier 3 Impacted Annual Fuel Consumption 

Notice of Proposed Rulemaking vs. Final Rule

NPRM

Final Rule

Figure 8-1: Annual Fuel Consumption Comparison between NPRM and Final Rule 

The projected annual fuel consumption and annual fuel costs of the final program are 

listed in Table 8-2. 
8-4

Table 8-2: Annual Fuel Costs, 2011$ 

Year

Annual Fuel Consumption

Impacted by Tier 3 

Program (million gallons)

Fuel Sulfur Control 

Costs

($Million)a

2016 0 $0 

2017 123,698 $804 

2018 122,962 $799 

2019 122,121 $794 

2020 121,015 $787 

2021 119,625 $778 

2022 118,190 $768 

2023 116,645 $758 

2024 115,066 $748 

2025 113,335 $737 

2030 107,065 $696 

a

 These estimates include costs associated with the Tier 3 fuel standards in all states except California. 

8.1.1.3 Total Costs 

The sum of the vehicle technology costs to control exhaust and evaporative emissions, in 

addition to the costs to control the sulfur level in the fuel, represent the total costs of the 

program, as shown in Table 8-3.

Table 8-3: Total Annual Vehicle and Fuel Control Costs, 2011$ 

Year

Total Vehicle 

Program Costs 

($Million)

Fuel Sulfur 

Control Costs

($Million)

Total Program Costs 

($Million)a

2016 $21.4 $0 $21

2017 $297 $804 $1,101

2018 $615 $799 $1,414

2019 $653 $794 $1,447

2020 $697 $787 $1,484

2021 $725 $778 $1,503

2022 $758 $768 $1,526

2023 $751 $758 $1,509

2024 $761 $748 $1,509

2025 $773 $737 $1,510

2030 $761 $696 $1,457

a

 These estimates include: (a) costs associated with the Tier 3 vehicle standards in all states except 

California and states that have adopted the LEV III program and (b) the Tier 3 fuel standards in all states 

except California. 
8-5

8.1.2 Quantified and Monetized Health and Environmental Impacts 

This section presents EPA’s analysis of the criteria pollutant-related health and 

environmental impacts that would occur as a result of the final Tier 3 standards. The vehicles 

and fuels subject to the final standards are significant sources of mobile source air pollution such 

as direct PM, NOX, SOX, VOCs and air toxics. The standards will affect exhaust and evaporative 

emissions of these pollutants from vehicles. Emissions of NOX (a precursor to ozone formation 

and secondarily-formed PM2.5), SOX (a precursor to secondarily-formed PM2.5), VOCs (a 

precursor to ozone formation and, to a lesser degree, secondarily-formed PM2.5) and directlyemitted PM2.5 contribute to ambient concentrations of PM2.5 and ozone. Exposure to ozone and 

PM2.5 is linked to adverse human health impacts such as premature deaths as well as other 

important public health and environmental effects. 

The analysis in this section aims to characterize the benefits of the final standards by 

answering two key questions: 

1. What are the health and welfare effects of changes in ambient particulate matter 

(PM2.5) and ozone air quality resulting from reductions in precursors including NOX and SO2? 

2. What is the economic value of these effects? 

For the final rulemaking, we have quantified and monetized the health and environmental 

impacts in 2030, representing projected impacts associated with a year when the program is fully 

implemented and most of the fleet is turned over. Overall, we estimate that the final standards 

will lead to a net decrease in PM2.5- and ozone-related health impacts in 2030. The estimated 

decrease in population-weighted national average PM2.5 exposure results in a net decrease in 

adverse PM-related human health impacts (the decrease in national population-weighted annual 

average PM2.5 is 0.04 μg/m3

in 2030).A The estimated decrease in population-weighted national 

average ozone exposure results in a net decrease in ozone-related health impacts (populationweighted maximum 8-hour average ozone decreases by 0.32 ppb in 2030).

Using the lower end of EPA’s range of preferred premature mortality estimates (Krewski 

et al., 2009 for PM2.5 and Bell et al., 2004 for ozone),4,5 we estimate that by 2030, 

implementation of the standards will reduce approximately 770 premature mortalities annually 

and will yield between $6.7 and $7.4 billion in total annual benefits, depending on the discount 

rate used.B The upper end of the range of avoided premature mortality estimates associated with 

the final standards (based on Lepeule et al., 2012 for PM2.5 and Levy et al., 2005 for ozone)6,7

 

A

 Note that the national, population-weighted PM2.5 and ozone air quality metrics presented in this Chapter represent 

an average for the entire, gridded U.S. CMAQ domain. These are different than the population-weighted PM2.5 and 

ozone design value metrics presented in Chapter 7, which represent the average for areas with a current air quality 

monitor. 

B

 The monetized value of PM2.5-related mortality accounts for a twenty-year segmented cessation lag. To discount 

the value of premature mortality that occurs at different points in the future, we apply both a 3 and 7 percent 

discount rate. We also use both a 3 and 7 percent discount rate to value PM-related nonfatal heart attacks 

(myocardial infarctions). Nonfatal myocardial infarctions (MI) are valued using age-specific cost-of-illness values 

that reflect lost earnings and direct medical costs over a 5-year period following a nonfatal MI. 
8-6

results in approximately 2,000 premature mortalities avoided in 2030 and will yield between $18 

and $19 billion in total benefits. Thus, even using the lower end of the range of premature 

mortality estimates, the health impacts of the final standards presented in this rule are projected 

to be substantial. 

We note that of necessity, decisions on the emissions and other elements used in the air 

quality modeling were made early in the analytical process for the final rulemaking. For this 

reason, the modeled changes in emissions used to support the air quality and benefits analyses 

are slightly different than those used to represent the final emissions impacts of the Tier 3 

standards. The magnitude of the differences is small, however, and for that reason we do not 

expect these differences to materially impact our cost-benefit conclusions. See Chapter 7.2.1.1 

for more details. 

8.1.2.1 Overview 

This analysis reflects the impacts of the final Tier 3 rule in 2030 compared to a futureyear reference scenario without the program in place. Overall, we estimate that the final rule will 

lead to a net decrease in PM2.5-related health and environmental impacts (see Section 7.2.4 for 

more information about the air quality modeling results). The estimated decrease in populationweighted national average PM2.5 exposure results in a net decrease in adverse PM-related human 

health and environmental impacts (the decrease in national population weighted annual average 

PM2.5 is 0.04 μg/m3 in 2030). 

The air quality modeling also projects decreases in ozone concentrations (see Section 

7.2.4). The overall estimated decrease in population-weighted national average ozone exposure 

results in decreases in ozone-related health and environmental impacts (population weighted 

maximum 8-hour average ozone decreases by 0.32 ppb in 2030). 

We base our analysis of the program’s impact on human health and the environment on 

peer-reviewed studies of air quality and human health effects.8,9,10

 Our benefits methods are 

consistent with the RIA that accompanied the final revisions to the National Ambient Air Quality 

Standards (NAAQS) for Particulate Matter, the 2008 final ozone NAAQS, and the 2010 ozone 

NAAQS reconsideration. To model the ozone and PM air quality impacts of the final standards, 

we used the Community Multiscale Air Quality (CMAQ) model (see Chapter 7.2.2). The 

modeled ambient air quality data serves as an input to the Environmental Benefits Mapping and 

Analysis Program version 4.065 (BenMAP).C BenMAP is a computer program developed by the 

U.S. EPA that integrates a number of the modeling elements used in previous analyses (e.g., 

interpolation functions, population projections, health impact functions, valuation functions, 

analysis and pooling methods) to translate modeled air concentration estimates into health effects 

incidence estimates and monetized benefits estimates. 

The range of total monetized ozone- and PM-related health impacts projected in 2030 is 

presented in Table 8-4. We present total benefits based on the PM- and ozone-related premature 

 

C

 Information on BenMAP, including downloads of the software, can be found at http://www.epa.gov/ttn/ecas/ 

benmodels.html. 
8-7

mortality function used. The benefits ranges therefore reflect the addition of each estimate of 

ozone-related premature mortality (each with its own row in Table 8-4) to estimates of PMrelated premature mortality. 

Table 8-4: Estimated 2030 Monetized PM-and Ozone-Related Health Benefits 

2030 Total Ozone and PM Benefits – PM Mortality Derived from American Cancer Society Analysis and 

Six-Cities Analysisa

Premature Ozone 

Mortality Function

Reference Total Benefits

(Billions, 2011$, 3% 

Discount Rate)b,c

Total Benefits

(Billions, 2011$, 7% 

Discount Rate) b,c

Multi-city analyses Bell et al., 2004 Total: $7.4 - $15

PM: $6.0 - $14

Ozone: $1.1

Total: $6.7 - $14

PM: $5.4 - $12

Ozone: $1.1

Huang et al., 2005 Total: $7.9 - $16

PM: $6.0 - $14

Ozone: $1.7

Total: $7.3 - $14

PM: $5.4 - $12

Ozone: $1.7

Schwartz, 2005 Total: $8.0 - $16

PM: $6.0 - $14

Ozone: $1.7

Total: $7.3 - $14

PM: $5.4 - $12

Ozone: $1.7

Meta-analyses Bell et al., 2005 Total: $9.8 - $18

PM: $6.0 - $14

Ozone: $3.6

Total: $9.2 - $16

PM: $5.4 - $12

Ozone: $3.6

Ito et al., 2005 Total: $11 - $19

PM: $6.0 - $14

Ozone: $4.9

Total: $11 - $18

PM: $5.4 - $12

Ozone: $4.9

Levy et al., 2005 Total: $11 - $19

PM: $6.0 - $14

Ozone: $5.0

Total: $11 - $18

PM: $5.4 - $12

Ozone: $5.0

.a Total includes premature mortality-related and morbidity-related ozone and PM2.5 estimated benefits. Range 

was developed by adding the estimate from the ozone premature mortality function to the estimate of PM2.5-

related premature mortality derived from either the ACS study (Krewski et al., 2009) or the Six-Cities study 

(Lepeule et al., 2012). Range also reflects alternative estimates of non-fatal heart attacks avoided based on either 

Peters et al. (2001) or a pooled estimate of four studies.

b

 Note that total benefits presented here do not include a number of unquantified benefits categories. A detailed 

listing of unquantified health effects is provided in Table 8-5. 

c

 Results reflect the use of both a 3 and 7 percent discount rate, as recommended by EPA’s Guidelines for 

Preparing Economic Analyses and OMB Circular A-4. Results are rounded to two significant digits for ease of 

presentation and computation. Totals may not sum due to rounding. 

The benefits analysis presented in this chapter incorporates an array of policy and 

technical changes that the Agency has adopted since the Tier 3 proposal’s draft RIA. These 

changes reflect EPA’s work to update PM-related benefits reflected in the most recent PM 

NAAQS.11 Below we note the aspects of this analysis that differ from the Tier 3 proposal’s draft 

RIA:12

 Incorporation of the newest American Cancer Society (ACS) mortality study and 

newest Harvard Six Cities mortality study. In 2012, Lepeule et al. published an 

extended analysis of the Six Cities cohort.13 Compared to the study it replaces 

(Laden et al., 2006),14 this new analysis follows the cohort for a longer time and 

includes more years of PM2.5 monitoring data. The all-cause PM2.5 mortality risk 

coefficient drawn from Lepeule et al. is roughly similar to the Laden et al. risk 
8-8

coefficient applied in the EPA’s recent analyses of long-term PM2.5 mortality and 

has narrower confidence intervals. 

In 2009, the Health Effects Institute published an extended analysis of the ACS 

cohort (Krewski et al., 2009).15 Compared to the study it replaces (Pope et al., 

2002),16 this new analysis incorporates a number of methodological 

improvements.DThe all-cause PM2.5 mortality risk estimate drawn from Krewski 

et al. (2009) is identical to the Pope et al. (2002) risk estimate applied in recent 

EPA analyses of long-term PM2.5 mortality but has narrower confidence intervals. 

 Updated health endpoints. We have removed the quantification of chronic 

bronchitis from our main analysis. This change is consistent with the findings of 

the PM Integrated Science Assessment (ISA) that the evidence for an association 

between long-term exposure to PM2.5 and respiratory effects is more tenuous.17

 Updated demographic data. We updated the population demographic data in 

BenMAP to reflect the 2010 Census and future projections based on economic 

forecasting models developed by Woods and Poole, Inc.18 These data replace the 

earlier demographic projection data from Woods and Poole (2011).19

 Incorporation of new morbidity studies. Since the publication of the 2004 Criteria 

Document for Particulate Matter,20 the publication of the more recent PM ISA,21

and the Provisional Assessment of Recent Studies on Health Effects of Particulate 

Matter Exposure (“Provisional Assessment”),22 the epidemiological literature has 

produced several new studies examining the association between short-term PM2.5 

exposure and acute myocardial infarctions, respiratory and cardiovascular 

hospitalizations, respiratory and cardiovascular emergency department visits, 

acute respiratory symptoms and exacerbation of asthma, respiratory and 

cardiovascular hospitalizations. Upon careful evaluation of this new literature, we 

added several new studies to our health impact assessment; in many cases we 

have replaced older single-city time-series studies with newer multi-city timeseries analyses. 

Updated the survival rates for non-fatal acute myocardial infarctions. Based on 

recent data from Agency for Healthcare Research and Quality’s Healthcare 

Utilization Project National Inpatient Sample database,23 we identified death rates 

for adults hospitalized with acute myocardial infarction stratified by age. These 

rates replace the survival rates from Rosamond et al. (1999).24

Updated hospital cost-of-illness (COI), including median wage data. In previous 

benefits analyses, estimates of hospital charges and lengths of hospital stays were 

based on discharge statistics provided by the Agency for Healthcare Research and 

Quality’s Healthcare Utilization Project National Inpatient Sample (NIS) database 

 

D

 Refer to the 2012 PM NAAQS RIA for more detail regarding the studies themselves. 
8-9

for 2000.25 The version of BenMAP (version 4.0.65) used in this analysis updated 

this information to use the 2007 database. The data source for the updated median 

annual income is the 2007 American Community Survey. 

The benefits in Table 8-4 include all of the estimated human health impacts we are able 

to quantify and monetize at this time. However, the full complement of human health effects 

associated with PM and ozone remain unquantified because of current limitations in methods or 

available data. We have not quantified a number of known or suspected health effects linked 

with ozone and PM for which appropriate health impact functions are not available or which do 

not provide easily interpretable outcomes (e.g., changes in heart rate variability). These are 

listed in Table 8-5. As a result, the health benefits quantified in this analysis are likely 

underestimates of the total benefits attributable to the final program. 

Table 8-5: Estimated Quantified and Unquantified Health Effects 

 

BENEFITS 

CATEGORY

SPECIFIC EFFECT EFFECT HAS 

BEEN 

QUANTIFIED

EFFECT HAS 

BEEN 

MONETIZED

MORE 

INFORMATION

Improved Human Health

Reduced 

incidence of 

premature 

mortality and 

morbidity from 

exposure to PM2.5

Adult premature mortality based on 

cohort study estimates and expert 

elicitation estimates (age >25 or age 

>30)

  PM NAAQS RIA, 

Section 5.6

Infant mortality (age <1)   PM NAAQS RIA, 

Section 5.6

Non-fatal heart attacks (age > 18)   PM NAAQS RIA, 

Section 5.6

Hospital admissions—respiratory (all 

ages)

  PM NAAQS RIA, 

Section 5.6

Hospital admissions—cardiovascular 

(age >20)

  PM NAAQS RIA, 

Section 5.6

Emergency department visits for 

asthma (all ages)

  PM NAAQS RIA, 

Section 5.6

Acute bronchitis (age 8–12)   PM NAAQS RIA, 

Section 5.6

Lower respiratory symptoms (age 7–

14)

  PM NAAQS RIA, 

Section 5.6

Upper respiratory symptoms 

(asthmatics age 9–11)

  PM NAAQS RIA, 

Section 5.6

Asthma exacerbation (asthmatics age 

6–18)

  PM NAAQS RIA, 

Section 5.6

Lost work days (age 18–65)   PM NAAQS RIA, 
8-10

BENEFITS 

CATEGORY

SPECIFIC EFFECT EFFECT HAS 

BEEN 

QUANTIFIED

EFFECT HAS 

BEEN 

MONETIZED

MORE 

INFORMATION

Section 5.6

Minor restricted-activity days (age 

18–65)

  PM NAAQS RIA, 

Section 5.6

Chronic Bronchitis (age >26) — — PM NAAQS RIA, 

Section 5.6c

Emergency department visits for 

cardiovascular effects (all ages)

— — PM NAAQS RIA, 

Section 5.6c

Strokes and cerebrovascular disease 

(age 50–79)

— — PM NAAQS RIA, 

Section 5.6c

Other cardiovascular effects (e.g., 

other ages)

— — PM ISAa

Other respiratory effects (e.g., 

pulmonary function, non-asthma ER 

visits, non-bronchitis chronic 

diseases, other ages and populations)

— — PM ISAa

Reproductive and developmental 

effects (e.g., low birth weight, preterm births, etc.)

— — PM ISAa,b

Cancer, mutagenicity, and 

genotoxicity effects

— — PM ISAa,b

Reduced 

incidence of 

premature 

mortality and 

morbidity from 

exposure to 

ozone

Premature mortality based on shortterm study estimates (all ages)  Ozone ISA

Premature mortality based on longterm study estimates (age 30–99)— — Ozone ISAc

Hospital admissions—respiratory 

causes (age > 65)

  Ozone ISA

Hospital admissions—respiratory

causes (age <2)

  Ozone ISA

Emergency department visits for 

asthma (all ages)

  Ozone ISA

Minor restricted-activity days (age 

18–65)

  Ozone ISA

School absence days (age 5–17)   Ozone ISA

Decreased outdoor worker 

productivity (age 18–65)

  Ozone ISA

Other respiratory effects (e.g., 

premature aging of lungs)

— — Ozone ISAa
8-11

BENEFITS 

CATEGORY

SPECIFIC EFFECT EFFECT HAS 

BEEN 

QUANTIFIED

EFFECT HAS 

BEEN 

MONETIZED

MORE 

INFORMATION

Cardiovascular and nervous system 

effects

— — Ozone ISAb

Reproductive and developmental 

effects

— — Ozone ISAb

Reduced 

incidence of 

morbidity from 

exposure to air

toxics

Cancer (benzene, 1,3-butadiene, 

formaldehyde, acetaldehyde)

Anemia (benzene)

Disruption of production of blood 

components (benzene)

Reduction in the number of blood 

platelets (benzene)

Excessive bone marrow formation 

(benzene)

Depression of lymphocyte counts 

(benzene)

Reproductive and developmental 

effects (1,3-butadiene)

Irritation of eyes and mucus 

membranes (formaldehyde)

Respiratory irritation (formaldehyde)

Asthma attacks in asthmatics 

(formaldehyde)

Asthma-like symptoms in nonasthmatics (formaldehyde)

Irritation of the eyes, skin, and 

respiratory tract (acetaldehyde)

Upper respiratory tract irritation and 

congestion (acrolein)

— — IRISa,b

a

 We assess these benefits qualitatively because we do not have sufficient confidence in available data or 

methods. 

b

 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. 

c We assess these benefits qualitatively due to time and resource limitations for this analysis. 

While there will be impacts associated with reductions in air toxic pollutant emissions 

that result from the final program, we do not attempt to monetize those impacts. This is 

primarily because currently available tools and methods to assess air toxics risk from mobile 

sources at the national scale are not adequate for extrapolation to incidence estimations or 

benefits assessment. The best suite of tools and methods currently available for assessment at 

the national scale are those used in the National-Scale Air Toxics Assessment (NATA). The 

EPA Science Advisory Board specifically commented in their review of the 1996 NATA that 

these tools were not yet ready for use in a national-scale benefits analysis, because they did not 

consider the full distribution of exposure and risk, or address sub-chronic health effects.26 While 

EPA has since improved these tools, there remain critical limitations for estimating incidence 

and assessing benefits of reducing mobile source air toxics. 
8-12

As part of the second prospective analysis of the benefits and costs of the Clean Air 

Act,27 EPA conducted a case study analysis of the estimated health effects associated with 

reducing exposure to benzene in Houston from implementation of the Clean Air Act. While 

reviewing the draft report, EPA’s Advisory Council on Clean Air Compliance Analysis 

concluded that “the challenges for assessing progress in health improvement as a result of 

reductions in emissions of hazardous air pollutants (HAPs) are daunting...due to a lack of 

exposure-response functions, uncertainties in emissions inventories and background levels, the 

difficulty of extrapolating risk estimates to low doses and the challenges of tracking health 

progress for diseases, such as cancer, that have long latency periods.”28 EPA continues to work 

to address these limitations; however, we did not have the methods and tools available for 

national-scale application in time for the analysis of the final program.E

 

The reduction in air pollution emissions that will result from the final program is 

projected to have “welfare” co-benefits in addition to human health benefits, including changes 

in visibility, materials damage, ecological effects from PM deposition, ecological effects from 

nitrogen and sulfur emissions, vegetation effects from ozone exposure, and climate effects.F

 

Despite our goal to quantify and monetize as many of the benefits as possible for the final 

rulemaking, the welfare co-benefits of the Tier 3 standards remain unquantified and 

nonmonetized in this RIA due to data, methodology, and resource limitations. As a result, the 

benefits quantified in this analysis are likely underestimates of the total benefits attributable to 

the final program. We refer the reader to Chapter 6 of the PM NAAQS RIA for a complete 

discussion of these welfare co-benefits. 29

8.1.2.2 Human Health Impacts 

Table 8-6 and Table 8-7 present the core estimates of annual PM2.5 and ozone health 

impacts in the 48 contiguous U.S. states associated with the final Tier 3 program. For each 

endpoint presented in Table 8-6 and Table 8-7, we provide both the point estimate and the 90 

percent confidence interval. 

Using EPA’s preferred estimates, based on the American Cancer Society (ACS) and SixCities studies and no threshold assumption in the model of mortality, we estimate that the final 

program would result in between 660 and 1,500 cases of avoided PM2.5-related premature deaths 

annually in 2030. A sensitivity analysis was conducted to understand the impact of alternative 

concentration response functions suggested by experts in the field. As shown in Table 8-8, when 

 

E

 In April, 2009, EPA hosted a workshop on estimating the benefits or reducing hazardous air pollutants. This 

workshop built upon the work accomplished in the June 2000 Science Advisory Board/EPA Workshop on the 

Benefits of Reductions in Exposure to Hazardous Air Pollutants, which generated thoughtful discussion on 

approaches to estimating human health benefits from reductions in air toxics exposure, but no consensus was 

reached on methods that could be implemented in the near term for a broad selection of air toxics. Please visit 

http://epa.gov/air/toxicair/2009workshop.html for more information about the workshop and its associated materials. 

F

 We project that the Tier 3 vehicle and fuel standards will reduce nitrous oxide (N2O) and methane (CH4) emissions 

from vehicles. The reductions in these potent greenhouse gases will be offset to some degree by the increase in CO2

emissions from refineries. The combined impact is a net decrease on a CO2-equivalent basis and would yield a net 

benefit if these reductions were monetized. 
8-13

the range of expert opinion is used, we estimate between 130 and 2,200 fewer premature 

mortalities in 2030. 

The range of ozone impacts is based on changes in risk estimated using several sources of 

ozone-related mortality effect estimates. This analysis presents six alternative estimates for the 

association based upon different functions reported in the scientific literature, derived from both 

the National Morbidity, Mortality, and Air Pollution Study (NMMAPS) 30,31,32 and from a series 

of meta-analyses. 33,34,35 This approach is not inconsistent with recommendations provided by 

the NRC in their report (NRC, 2008) on the estimation of ozone-related mortality risk reductions, 

“The committee recommends that the greatest emphasis be placed on estimates from new 

systematic multicity analyses that use national databases of air pollution and mortality, such as in 

the NMMAPS, without excluding consideration of meta-analyses of previously published 

studies.”36 For ozone-related premature mortality in 2030, we estimate a range of between 110 

to 500 fewer premature mortalities. 

Following these tables, we also provide a more comprehensive presentation of the 

distributions of incidence generated using the available information from empirical studies and 

expert elicitation. 

Table 8-8 presents the distributions of the reduction in PM2.5-related premature mortality 

based on the C-R distributions provided by each expert, as well as that from the data-derived 

health impact functions, based on the statistical error associated with the ACS study and the SixCities study. The 90 percent confidence interval for each separate estimate of PM-related 

mortality is also provided. 

In 2030, the effect estimates of nine of the twelve experts included in the elicitation panel 

fall within the empirically-derived range provided by the ACS and Six-Cities studies. Only one 

expert falls below this range, while two of the experts are above this range. Although the overall 

range across experts is summarized in these tables, the full uncertainty in the estimates is 

reflected by the results for the full set of 12 experts. The twelve experts’ judgments as to the 

likely mean effect estimate are not evenly distributed across the range illustrated by arraying the 

highest and lowest expert means. 
8-14

Table 8-6: Estimated PM2.5-Related Health Impacts 

Health Effect 2030 Annual 

Reduction in 

Incidence

(5th% - 95th%ile)

Premature Mortality – Derived from epidemiology literatureb

 Adult, age 30+, ACS Cohort Study (Krewski et al., 2009)

 Adult, age 25+, Six-Cities Study (Lepeule et al., 2012)

 Infant, age <1 year (Woodruff et al., 1997)

660

(480 – 840)

1,500

(860 – 2,100)

Non-fatal myocardial infarction (adult, age 18 and over)

 Peters et al. (2001)

 Pooled estimate of 4 studies

790

(290 – 1,300)

85

(42 – 190)

Hospital admissions - respiratory (all ages)c,e 210

(-38 – 380)

Hospital admissions - cardiovascular (adults, age >18)d250

(130 – 440)

Emergency room visits for asthma (age 18 years and younger)e340

(-58 – 660)

Acute bronchitis, (children, age 8-12)e980

(-35 – 2,000)

Lower respiratory symptoms (children, age 7-14) 13,000

(6,000 – 19,000)

Upper respiratory symptoms (asthmatic children, age 9-18) 18,000

(5,600 – 30,000)

Asthma exacerbation (asthmatic children, age 6-18) 19,000

(2,300 – 37,000)

Work loss days 81,000

(70,000 – 91,000)

Minor restricted activity days (adults age 18-65) 480,000

(400,000 – 550,000)

a Incidence is rounded to two significant digits. Estimates represent incidence within the 48 contiguous United 

States. 

b

PM-related adult mortality based upon the most recent American Cancer Society (ACS) Cohort Study 

(Krewski et al., 2009) and the most recent Six-Cities Study (Lepeule et al., 2012). Note that these are two 

alternative estimates of adult mortality and should not be summed. PM-related infant mortality based upon a 

study by Woodruff, Grillo, and Schoendorf, (1997).37

c Respiratory hospital admissions for PM include admissions for chronic obstructive pulmonary disease 

(COPD), pneumonia and asthma. 

d Cardiovascular hospital admissions for PM include total cardiovascular and subcategories for ischemic heart 

disease, dysrhythmias, and heart failure. 

e The negative estimates at the 5th percentile confidence estimates for these morbidity endpoints reflect the 

statistical power of the study used to calculate these health impacts. These results do not suggest that reducing 

air pollution results in additional health impacts. 
8-15

Table 8-7: Estimated Ozone-Related Health Impacts 

Health Effect 2030 Annual Reduction 

in Incidence

(5th% - 95th%ile)

Premature Mortality, All agesb

Multi-City Analyses 

 Bell et al. (2004) – Non-accidental

 Huang et al. (2005) – Cardiopulmonary

 Schwartz (2005) – Non-accidental

Meta-analyses:

 Bell et al. (2005) – All cause

 Ito et al. (2005) – Non-accidental

 Levy et al. (2005) – All cause

110

(46 – 170)

160

(74 – 250)

170

(68 – 270)

350

(190 – 510)

490

(320 – 660)

500

(360 – 630)

Hospital admissions- respiratory causes (adult, 65 and 

older)c

740

(87 – 1,400)

Hospital admissions -respiratory causes (children, under 2) 310

(160 – 450)

Emergency room visit for asthma (all ages)d330

(-8 – 990)

Minor restricted activity days (adults, age 18-65) 600,000

(290,000 – 910,000)

School absence days 210,000

(92,000 – 300,000)

a

 Incidence is rounded to two significant digits. Estimates represent incidence within the 48 contiguous U.S. 

b

 Estimates of ozone-related premature mortality are based upon incidence estimates derived from several 

alternative studies: Bell et al. (2004); Huang et al. (2005); Schwartz (2005) ; Bell et al. (2005); Ito et al. 

(2005); Levy et al. (2005). The estimates of ozone-related premature mortality should therefore not be 

summed.

c Respiratory hospital admissions for ozone include admissions for all respiratory causes and subcategories for 

COPD and pneumonia. 

d

 The negative estimate at the 5th percentile confidence estimate for this morbidity endpoint reflects the 

statistical power of the study used to calculate this health impact. This result does not suggest that reducing air 

pollution results in additional health impacts. 

Table 8-8: Results of Application of Expert Elicitation: Annual Reductions in Premature 

Mortality in 2030 Associated with the Final Program

Source of Mortality 

Estimate

2030 Tier 3 Control

5th Percentile Mean 95th Percentile

Krewski et al. (2009) 480 660 840

Lepeule et al. (2012) 860 1,500 2,100

Expert A 340 1,700 3,300

Expert B 88 1,400 2,900

Expert C 480 1,300 2,200

Expert D 58 950 1,500

Expert E 1,100 2,200 3,300
8-16

Source of Mortality 

Estimate

2030 Tier 3 Control

5th Percentile Mean 95th Percentile

Expert F 790 1,200 1,700

Expert G -1 790 1,400

Expert H -2 980 2,300

Expert I 110 1,300 2,300

Expert J 160 1,100 2,300

Expert K 0 130 590

Expert L 1 860 1,800

8.1.2.3 Monetized Estimates of Human Health and Environmental Impacts 

Table 8-9 presents the estimated monetary value of changes in the incidence of ozone and 

PM2.5-related health and environmental effects. Total aggregate monetized benefits are 

presented in Table 8-10. All monetized estimates are presented in 2011$. Where appropriate, 

estimates account for growth in real gross domestic product (GDP) per capita between 2000 and 

2030.G The monetized value of PM2.5-related mortality also accounts for a twenty-year 

segmented cessation lag.H To discount the value of premature mortality that occurs at different 

points in the future, we apply both a 3 and 7 percent discount rate. We also use both a 3 and 7 

percent discount rate to value PM-related nonfatal heart attacks (myocardial infarctions).I 

In addition to omitted benefits categories such as air toxics and various welfare effects, 

not all known PM2.5- and ozone-related health and welfare effects could be quantified or 

monetized. The estimate of total monetized health benefits of the final program is thus equal to 

the subset of monetized PM2.5- and ozone-related health impacts we are able to quantify plus the 

sum of the nonmonetized health and welfare benefits. Our estimate of total monetized benefits 

in 2030 for the final program, using the ACS and Six-Cities PM mortality studies and the range 

of ozone mortality assumptions, is between $7.4 and $19 billion billion, assuming a 3 percent 

 

G

 Our analysis accounts for expected growth in real income over time. Economic theory argues that WTP for most 

goods (such as environmental protection) will increase if real incomes increase. Benefits are therefore adjusted by 

multiplying the unadjusted benefits by the appropriate adjustment factor to account for income growth over time. 

For growth between 2000 and 2030, this factor is 1.23 for long-term mortality, 1.27 for chronic health impacts, and 

1.08 for minor health impacts. For a complete discussion of how these adjustment factors were derived, we refer the 

reader to the PM NAAQS regulatory impact analysis. Note that similar adjustments do not exist for cost-of-illnessbased unit values. For these, we apply the same unit value regardless of the future year of analysis. 

H

 Based in part on prior SAB advice, EPA has typically assumed that there is a time lag between changes in 

pollution exposures and the total realization of changes in health effects. Within the context of benefits analyses, 

this term is often referred to as “cessation lag”. The existence of such a lag is important for the valuation of 

premature mortality incidence because economic theory suggests that benefits occurring in the future should be 

discounted. In this analysis, we apply a twenty-year distributed lag to PM mortality reductions. This method is 

consistent with the most recent recommendation by the EPA’s Science Advisory Board. Refer to: EPA – Science 

Advisory Board, 2004. Advisory Council on Clean Air Compliance Analysis Response to Agency Request on 

Cessation Lag. Letter from the Health Effects Subcommittee to the U.S. Environmental Protection Agency 

Administrator, December. 

I

 Nonfatal myocardial infarctions (MI) are valued using age-specific cost-of-illness values that reflect lost earnings 

and direct medical costs over a 5-year period following a nonfatal MI. 
8-17

discount rate, or between $6.7 and $18 billion, assuming a 7 percent discount rate. As the results 

indicate, total benefits are driven primarily by the reduction in PM2.5- and ozone-related 

premature fatalities each year and represent the benefits of the Tier 3 program anticipated to 

occur annually when the program is fully implemented and most of the fleet turned over. 

The next largest benefit is for reductions in nonfatal heart attacks, although this value is 

more than an order of magnitude lower than for premature mortality. Hospital admissions for 

respiratory and cardiovascular causes, minor restricted activity days, and work loss days account 

for the majority of the remaining benefits. The remaining categories each account for a small 

percentage of total benefit; however, they represent a large number of avoided incidences 

affecting many individuals. A comparison of the incidence table to the monetary benefits table 

reveals that there is not always a close correspondence between the number of incidences 

avoided for a given endpoint and the monetary value associated with that endpoint. For 

example, there are many more work loss days than PM-related premature mortalities, yet work 

loss days account for only a very small fraction of total monetized benefits. This reflects the fact 

that many of the less severe health effects, while more common, are valued at a lower level than 

the more severe health effects. Also, some effects, such as hospital admissions, are valued using 

a proxy measure of willingness-to-pay (e.g., cost-of-illness). As such, the true value of these 

effects may be higher than that reported here. 

Table 8-9: Estimated Monetary Value of Changes in Incidence of Health and Welfare 

Effects (millions of 2010$)

HEALTH ENDPOINTS 2030

(5TH AND 95TH

PERCENTILE)

PM2.5-Related Health Effects

Premature Mortality – Derived 

from Epidemiology Studiesb,c

Adult, age 30+ - ACS study 

(Krewski et al., 2009)

 3% discount rate

 7% discount rate

$6,100

($910 - $14,000)

$5,500

($820 - $13,000)

Adult, age 25+ - Six-Cities study 

(Lepeule et al., 2012)

 3% discount rate

 7% discount rate

$14,000

($2,000 - $33,000)

$12,000

($1,800 - $30,000)

Infant Mortality, <1 year –

(Woodruff et al. 1997)

$13

($1.8 - $32)

Non-fatal acute myocardial infarctions 

 Peters et al., 2001

 3% discount rate

 7% discount rate

 Pooled estimate of 4 studies

 3% discount rate

 7% discount rate

$96

($21 - $230)

$93

($19 - $220)

$10

($2.6 - $27)

$10

($2.4 - $27)
8-18

Hospital admissions for respiratory causesd$5.9

(-$1.6 - $11)

Hospital admissions for cardiovascular causes $9.9

($5.0 - $17)

Emergency room visits for asthmad$0.15

(-$0.02 - $0.29)

Acute bronchitis (children, age 8–12)d$0.49

(-$0.02 - $1.2)

Lower respiratory symptoms (children, 7–14) $0.27

($0.11 - $0.51)

Upper respiratory symptoms (asthma, 9–11) $0.62

($0.18 - $1.4)

Asthma exacerbations $1.1

($0.14 - $2.7)

Work loss days $12

($11 – $14)

Minor restricted-activity days (MRADs) $34

($20 - $49)

Ozone-Related Health Effects

Premature Mortality, All ages –

Derived from Multi-city analyses

Bell et al., 2004 $1,100

($150 - $2,800)

Huang et al., 2005 $1,600

($220 - $4,100)

Schwartz, 2005 $1,700

($220 - $4,400)

Premature Mortality, All ages –

Derived from Meta-analyses

Bell et al., 2005 $3,600

($510 - $8,800)

Ito et al., 2005 $5,000

($740 - $12,000

Levy et al., 2005 $5,100

($760 - $12,000)

Hospital admissions- respiratory causes (adult, 65 and older) $21

($2.5 - $39)

Hospital admissions- respiratory causes (children, under 2) $3.7

($1.9 - $5.4)

Emergency room visit for asthma (all ages) $0.14

(-$0.003 - $0.41)

Minor restricted activity days (adults, age 18-65) $43

($19 - $73)

School absence days $21

($9.3 - $31)

a

 Monetary benefits are rounded to two significant digits for ease of presentation and computation. PM and 

ozone benefits are nationwide. 

b

 Monetary benefits adjusted to account for growth in real GDP per capita between 1990 and the analysis 

year (2030). 

c

 Valuation assumes discounting over the SAB recommended 20 year segmented lag structure. Results 

reflect the use of 3 percent and 7 percent discount rates consistent with EPA and OMB guidelines for 

preparing economic analyses. 

d The negative estimate at the 5th percentile confidence estimate for this morbidity endpoint reflects the 

statistical power of the study used to calculate this health impact. This result does not suggest that reducing 

air pollution results in additional health impacts. 
8-19

Table 8-10: Total Monetized Ozone and PM-related Benefits Associated with the Final 

Program in 2030

Total Ozone and PM Benefits (billions, 2011$) –

PM Mortality Derived from the ACS and Six-Cities Studies

3% Discount Rate 7% Discount Rate

Ozone 

Mortality 

Function

Reference Mean Total 

Benefits

Ozone 

Mortality 

Function

Reference Mean Total 

Benefits

Multi-city Bell et al., 

2004

$7.4 - $15 Multi-city Bell et al., 

2004

$6.7 - $14

Huang et al.,

2005

$7.9 - $16 Huang et al., 

2005

$7.3 - $14

Schwartz, 

2005

$8.0 - $16 Schwartz, 

2005

$7.3 - $14

Meta-analysis Bell et al., 

2005

$9.8 - $18 Meta-analysis Bell et al., 

2005

$9.2 - $16

Ito et al., 

2005

$11 - $19 Ito et al., 

2005

$11 - $18

Levy et al., 

2005

$11 - $19 Levy et al., 

2005

$11 - $18

Total Ozone and PM Benefits (billions, 2011$) –

PM Mortality Derived from Expert Elicitation (Lowest and Highest Estimate)

3% Discount Rate 7% Discount Rate

Ozone 

Mortality 

Function

Reference Mean Total 

Benefits

Ozone 

Mortality 

Function

Reference Mean Total 

Benefits

Multi-city Bell et al., 

2004

$2.4 - $22 Multi-city Bell et al., 

2004

$2.4 - $20

Huang et al., 

2005

$2.9 - $22 Huang et al., 

2005

$2.9 - $20

Schwartz, 

2005

$3.0 - $22 Schwartz, 

2005

$3.0 - $20

Meta-analysis Bell et al., 

2005

$4.9 - $24 Meta-analysis Bell et al., 

2005

$4.9 - $22

Ito et al., 

2005

$6.3 - $26 Ito et al., 

2005

$6.3 - $24

Levy et al., 

2005

$6.3 - $26 Levy et al., 

2005

$6.3 - $26

8.1.2.4 Methodology 

We follow a “damage-function” approach in calculating total benefits of the modeled 

changes in environmental quality. This approach estimates changes in individual health 

endpoints (specific effects that can be associated with changes in air quality) and assigns values 

to those changes assuming independence of the values for those individual endpoints. Total 

benefits are calculated simply as the sum of the values for all non-overlapping health endpoints. 

The “damage-function” approach is the standard method for assessing costs and benefits of 

environmental quality programs and has been used in several recent published analyses.38,39,40

To assess economic value in a damage-function framework, the changes in environmental 

quality must be translated into effects on people or on the things that people value. In some 

cases, the changes in environmental quality can be directly valued. In other cases, such as for 
8-20

changes in ozone and PM, an impact analysis must first be conducted to convert air quality 

changes into effects that can be assigned dollar values. For the purposes of this RIA, the health 

impacts analysis (HIA) includes those health effects that are directly linked to ambient levels of 

air pollution and specifically to those linked to ozone and PM2.5. 

We note at the outset that the EPA rarely has the time or resources to perform extensive 

new research to measure directly either the health outcomes or their values for regulatory 

analyses. Thus, similar to Kunzli et al. (2000)41 and other, more recent health impact analyses, 

our estimates are based on the best available methods of benefits transfer. Benefits transfer is the 

science and art of adapting primary research from similar contexts to obtain the most accurate 

measure of benefits for the environmental quality change under analysis. Adjustments are made 

for the level of environmental quality change, the socio-demographic and economic 

characteristics of the affected population, and other factors to improve the accuracy and 

robustness of benefits estimates. 

8.1.2.4.1 Human Health Impact Assessment 

The health impact assessment (HIA) quantifies the changes in the incidence of adverse 

health impacts resulting from changes in human exposure to PM2.5 and ozone air quality. HIAs 

are a well-established approach for estimating the retrospective or prospective change in adverse 

health impacts expected to result from population-level changes in exposure to pollutants. 42 PCbased tools such as the environmental Benefits Mapping and Analysis Program (BenMAP) can 

systematize health impact analyses by applying a database of key input parameters, including 

health impact functions and population projections—provided that key input data are available, 

including air quality estimates and risk coefficients.43 Analysts have applied the HIA approach to 

estimate human health impacts resulting from hypothetical changes in pollutant levels.44, 45,

46

The EPA and others have relied upon this method to predict future changes in health impacts 

expected to result from the implementation of regulations affecting air quality.47 For this 

assessment, the HIA is limited to those health effects that are directly linked to ambient ozone 

and PM2.5 concentrations. 

The HIA approach used in this analysis involves three basic steps: (1) utilizing 

projections of PM2.5 air qualityJand estimating the change in the spatial distribution of the 

ambient air quality; (2) determining the subsequent change in population-level exposure; (3) 

calculating health impacts by applying concentration-response relationships drawn from the 

epidemiological literature to this change in population exposure. 

A typical health impact function might look like: 

 0

1

x

eyy ,

where y0 is the baseline incidence (the product of the baseline incidence rate times the potentially 

affected population), β is the effect estimate, and Δx is the estimated change in the summary 

 

J

 Projections of ambient PM2.5 concentrations for this analysis were generated using the Community Multiscale Air 

Quality model (CMAQ). See Chapter 7 of this RIA for more information on the air quality modeling. 
8-21

pollutant measure. There are other functional forms, but the basic elements remain the same. 

The following subsections describe the sources for each of the first three elements: size of the 

potentially affected populations; PM2.5 and ozone effect estimates; and baseline incidence rates. 

We also describe the treatment of potential thresholds in PM-related health impact functions in 

Section 8.1.2.5.3. Section 8.1.2.4.6 describes the ozone and PM air quality inputs to the health 

impact functions. 

8.1.2.4.2 Potentially Affected Populations 

Quantified and monetized human health impacts depend on the demographic 

characteristics of the population, including age, location, and income. We use population 

projections based on economic forecasting models developed by Woods and Poole, Inc.48 The 

Woods and Poole (WP) database contains county-level projections of population by age, sex, and 

race out to 2040, relative to a baseline using the 2010 Census data. Projections in each county are 

determined simultaneously with every other county in the United States to take into account 

patterns of economic growth and migration. The sum of growth in county-level populations is 

constrained to equal a previously determined national population growth, based on Bureau of 

Census estimates.49 According to WP, linking county-level growth projections together and 

constraining to a national-level total growth avoids potential errors introduced by forecasting 

each county independently. County projections are developed in a four-stage process: 

 First, national-level variables such as income, employment, and populations are 

forecasted. 

 Second, employment projections are made for 179 economic areas defined by the 

Bureau of Economic Analysis,50 using an “export-base” approach, which relies on 

linking industrial-sector production of non-locally consumed production items, such 

as outputs from mining, agriculture, and manufacturing with the national economy. 

The export-based approach requires estimation of demand equations or calculation of 

historical growth rates for output and employment by sector. 

 Third, population is projected for each economic area based on net migration rates 

derived from employment opportunities and following a cohort-component method 

based on fertility and mortality in each area. 

 Fourth, employment and population projections are repeated for counties, using the 

economic region totals as bounds. The age, sex, and race distributions for each region 

or county are determined by aging the population by single year of age by sex and 

race for each year through 2040 based on historical rates of mortality, fertility, and 

migration. 

8.1.2.4.3 Effect Estimate Sources 

The first step in selecting effect coefficients is to identify the health endpoints to be 

quantified. We base our selection of health endpoints on consistency with the EPA’s Integrated 

Science Assessments (which replace previous Criteria Documents), with input and advice from 

the SAB-HES, a scientific review panel specifically established to provide advice on the use of 

the scientific literature in developing benefits analyses for the EPA’s Report to Congress on The 

Benefits and Costs of the Clean Air Act 1990 to 2020.

51 In addition, we have included more 
8-22

recent epidemiology studies from the PM ISA and the Provisional Assessment.52,53 In general, 

we follow a weight of evidence approach, based on the biological plausibility of effects, 

availability of concentration-response functions from well conducted peer-reviewed 

epidemiological studies, cohesiveness of results across studies, and a focus on endpoints 

reflecting public health impacts (like hospital admissions) rather than physiological responses 

(such as changes in clinical measures like Forced Expiratory Volume [FEV1]). 

There are several types of data that can support the determination of types and magnitude 

of health effects associated with air pollution exposures. These sources of data include 

toxicological studies (including animal and cellular studies), human clinical trials, and 

observational epidemiology studies. All of these data sources provide important contributions to 

the weight of evidence surrounding a particular health impact. However, only epidemiology 

studies provide direct concentration-response relationships that can be used to evaluate 

population-level impacts of reductions in ambient pollution levels in a health impact assessment. 

For the data-derived estimates, we relied on the published scientific literature to ascertain 

the relationship between PM2.5,, ozone, and adverse human health effects. We evaluated 

epidemiological studies using the selection criteria summarized in Table 8-11. These criteria 

include consideration of whether the study was peer-reviewed, the match between the pollutant 

studied and the pollutant of interest, the study design and location, and characteristics of the 

study population, among other considerations. In general, the use of concentration-response 

functions from more than a single study can provide a more representative distribution of the 

effect estimate. However, there are often differences between studies examining the same 

endpoint, making it difficult to pool the results in a consistent manner. For example, studies may 

examine different pollutants or different age groups. For this reason, we consider very carefully 

the set of studies available examining each endpoint and select a consistent subset that provides a 

good balance of population coverage and match with the pollutant of interest. In many cases, 

either because of a lack of multiple studies, consistency problems, or clear superiority in the 

quality or comprehensiveness of one study over others, a single published study is selected as the 

basis of the effect estimate. 

When several effect estimates for a pollutant and a given health endpoint have been 

selected, they are quantitatively combined or pooled to derive a more robust estimate of the 

relationship. The BenMAP Manual Technical Appendices provides details of the procedures 

used to combine multiple impact functions.54 In general, we used fixed or random effects models 

to pool estimates from different single city studies of the same endpoint. Fixed effects pooling 

simply weights each study’s estimate by the inverse variance, giving more weight to studies with 

greater statistical power (lower variance). Random effects pooling accounts for both within-study 

variance and between-study variability, due, for example, to differences in population 

susceptibility. We used the fixed effects model as our null hypothesis and then determined 

whether the data suggest that we should reject this null hypothesis, in which case we would use 

the random effects model. K

Pooled impact functions are used to estimate hospital admissions 

 

K

 EPA recently changed the algorithm BenMAP uses to calculate study variance, which is used in the pooling 

process. Prior versions of the model calculated population variance, while the version used here calculated sample 
8-23

and asthma exacerbations. When combining evidence across multi-city studies (e.g., 

cardiovascular hospital admission studies), we use equal weights pooling. The effect estimates 

drawn from each multi-city study are themselves pooled across a large number of urban areas. 

For this reason, we elected to give each study an equal weight rather than weighting by the 

inverse of the variance reported in each study. For more details on methods used to pool 

incidence estimates, see the BenMAP Manual Appendices. 

Effect estimates selected for a given health endpoint were applied consistently across all 

locations nationwide. This applies to both impact functions defined by a single effect estimate 

and those defined by a pooling of multiple effect estimates. Although the effect estimate may, in 

fact, vary from one location to another (e.g., because of differences in population susceptibilities 

or differences in the composition of PM), location-specific effect estimates are generally not 

available. 

Table 8-11: Criteria Used When Selecting C-R Functions 

Consideration Comments

Peer-Reviewed 

Research

Peer-reviewed research is preferred to research that has not undergone the peer-review 

process.

Study Type Among studies that consider chronic exposure (e.g., over a year or longer), prospective 

cohort studies are preferred over ecological studies because they control for important 

individual-level confounding variables that cannot be controlled for in ecological studies. 

Study Period Studies examining a relatively longer period of time (and therefore having more data) are 

preferred, because they have greater statistical power to detect effects. Studies that are 

more recent are also preferred because of possible changes in pollution mixes, medical 

care, and lifestyle over time. However, when there are only a few studies available, studies 

from all years will be included.

Population Attributes The most technically appropriate measures of benefits would be based on impact functions 

that cover the entire sensitive population but allow for heterogeneity across age or other 

relevant demographic factors. In the absence of effect estimates specific to age, sex, 

preexisting condition status, or other relevant factors, it may be appropriate to select effect 

estimates that cover the broadest population to match with the desired outcome of the 

analysis, which is total national-level health impacts. When available, multi-city studies 

are preferred to single city studies because they provide a more generalizable 

representation of the concentration-response function.

Study Size Studies examining a relatively large sample are preferred because they generally have 

more power to detect small magnitude effects. A large sample can be obtained in several 

ways, including through a large population or through repeated observations on a smaller 

population (e.g., through a symptom diary recorded for a panel of asthmatic children).

Study Location U.S. studies are more desirable than non-U.S. studies because of potential differences in 

pollution characteristics, exposure patterns, medical care system, population behavior, and 

lifestyle. National estimates are most appropriate when benefits are nationally distributed; 

the impact of regional differences may be important when benefits only accrue to a single 

area.

Pollutants Included in 

Model

When modeling the effects of ozone and PM (or other pollutant combinations) jointly, it is 

important to use properly specified impact functions that include both pollutants. Using

single-pollutant models in cases where both pollutants are expected to affect a health 

 

variance. This change did not affect the selection of random or fixed effects for the pooled incidence estimates 

between the proposal and final RIA. 
8-24

outcome can lead to double-counting when pollutants are correlated.

Measure of PM For this analysis, impact functions based on PM2.5 are preferred to PM10 because of the 

focus on reducing emissions of PM2.5 precursors, and because air quality modeling was 

conducted for this size fraction of PM. Where PM2.5 functions are not available, PM10

functions are used as surrogates, recognizing that there will be potential downward 

(upward) biases if the fine fraction of PM10 is more (less) toxic than the coarse fraction. 

Economically Valuable 

Health Effects

Some health effects, such as forced expiratory volume and other technical measurements 

of lung function, are difficult to value in monetary terms. These health effects are not 

quantified in this analysis.

Non-overlapping 

Endpoints

Although the benefits associated with each individual health endpoint may be analyzed 

separately, care must be exercised in selecting health endpoints to include in the overall 

benefits analysis because of the possibility of double-counting of benefits. 

It is important to note that we are unable to separately quantify all of the possible PM and 

ozone health effects that have been reported in the literature for three reasons: (1) the possibility 

of double counting (such as hospital admissions for specific respiratory diseases versus hospital 

admissions for all or a sub-set of respiratory diseases); (2) uncertainties in applying effect 

relationships that are based on clinical studies to the potentially affected population; or (3) the 

lack of an established concentration-response (CR) relationship. Table 8-12 lists the health 

endpoints included in this analysis. 

Table 8-12: Health Impact Functions Used in BenMAP to Estimate Impacts of PM2.5 and 

Ozone Reductions 

ENDPOINT POLLUTANT STUDY STUDY POPULATION

Premature Mortality

Premature mortality –

daily time series

O3 Multi-city

Bell et al (2004) (NMMAPS study)55– Nonaccidental

Huang et al (2005)56- Cardiopulmonary

Schwartz (2005)57– Non-accidental

Meta-analyses:

Bell et al (2005)58– All cause

Ito et al (2005)59– Non-accidental

Levy et al (2005)60– All cause

All ages

Premature mortality 

—cohort study, allcause

PM2.5 Krewski et al. (2009)

61

Lepeule et al. (2012)

62

>29 years

>25 years

Premature mortality, 

total exposures

PM2.5 Expert Elicitation (IEc, 2006)63 >24 years

Premature mortality 

— all-cause

PM2.5 Woodruff et al. (1997)64 Infant (<1 year)

Chronic Illness
8-25

ENDPOINT POLLUTANT STUDY STUDY POPULATION

Nonfatal heart attacks PM2.5 Peters et al. (2001)65

Pooled estimate:

 Pope et al. (2006)66

 Sullivan et al. (2005)67

 Zanobetti et al. (2009)68

 Zanobetti and Schwartz (2006)69

Adults (>18 years)

Hospital Admissions 

Respiratory

O3

Pooled estimate:

Schwartz (1995) - ICD 460-519 (all resp)70

Schwartz (1994a; 1994b) - ICD 480-486 

(pneumonia)71,72

Moolgavkar et al. (1997) - ICD 480-487 

(pneumonia)73

Schwartz (1994b) - ICD 491-492, 494-496 

(COPD)

Moolgavkar et al. (1997) – ICD 490-496 

(COPD)

>64 years

Burnett et al. (2001)74 <2 years

PM2.5 Pooled estimate:

Zanobetti et al. (2009)—ICD 460-519 (All 

respiratory)

Kloog et al. (2012)—ICD 460-519 (All 

Respiratory)

75

>64 years

PM2.5 Moolgavkar (2000)—ICD 490–496 (Chronic 

lung disease)76

18–64 years

PM2.5 Pooled estimate:

Babin et al. (2007)—ICD 493 (asthma)77

Sheppard (2003)—ICD 493 (asthma)78

<18 years

Cardiovascular PM2.5 Pooled estimate:Zanobetti et al. (2009)—ICD 

390-459 (all cardiovascular)

Peng et al. (2009)—ICD 426-427; 428; 430-

438; 410-414; 429; 440-449 (Cardio-, cerebroand peripheral vascular disease)79

Peng et al. (2008)—ICD 426-427; 428; 430-

438; 410-414; 429; 440-449 (Cardio-, cerebroand peripheral vascular disease)80

Bell et al. (2008)—ICD 426-427; 428; 430-

438; 410-414; 429; 440-449 (Cardio-, cerebroand peripheral vascular disease)81

>64 years

PM2.5 Moolgavkar (2000)—ICD 390-429 (all 

cardiovascular)

20–64 years

Asthma-related ER 

visits

O3 Pooled estimate:

Peel et al (2005)82

Wilson et al (2005)

83

All ages

All ages

Asthma-related ER 

visits (cont’d)

PM2.5 Pooled estimate:

Mar et al. (2010)84

Slaughter et al. (2005)85

Glad et al. (2012)86

All ages
8-26

ENDPOINT POLLUTANT STUDY STUDY POPULATION

Other Health Endpoints

Acute bronchitis PM2.5 Dockery et al. (1996)87 8–12 years

Upper respiratory

symptoms

PM2.5 Pope et al. (1991)88 Asthmatics, 9–11 

years

Lower respiratory 

symptoms

PM2.5 Schwartz and Neas (2000)89 7–14 years

Asthma exacerbations PM2.5 Pooled estimate:

Ostro et al. (2001)90 (cough, wheeze and 

shortness of breath)

Mar et al. (2004) (cough, shortness of breath)

6–18 yearsa

Work loss days PM2.5 Ostro (1987)91 18–65 years

School absence days

O3 

Pooled estimate:

Gilliland et al. (2001)92

Chen et al. (2000)93

5–17 yearsb

Minor Restricted 

Activity Days 

(MRADs)

O3 Ostro and Rothschild (1989)94 18–65 years

PM2.5 Ostro and Rothschild (1989) 18–65 years

Notes: 

a

 The original study populations were 8 to 13 for the Ostro et al. (2001) study and 7 to 12 for the Mar et al. (2004) 

study. Based on advice from the SAB-HES, we extended the applied population to 6-18, reflecting the common 

biological basis for the effect in children in the broader age group. See: U.S. EPA-SAB (2004) and NRC (2002). 

b

 Gilliland et al. (2001) studied children aged 9 and 10. Chen et al. (2000) studied children 6 to 11. Based on advice 

from the National Research Council and the EPA SAB-HES, we have calculated reductions in school absences for 

all school-aged children based on the biological similarity between children aged 5 to 17. 

For detailed descriptions of each of the individual studies referenced in Table 8-12, 

please refer to the RIAs that accompanied the final revisions to the National Ambient Air Quality 

Standards (NAAQS) for Particulate Matter, the 2008 final ozone NAAQS, and the 2010 ozone 

NAAQS reconsideration.95,96,97 

8.1.2.4.4 Baseline Incidence Rates 

Epidemiological studies of the association between pollution levels and adverse health 

effects generally provide a direct estimate of the relationship of air quality changes to the relative 

risk of a health effect, rather than estimating the absolute number of avoided cases. For example, 

a typical result might be that a 10 μg/m3 decrease in daily PM2.5 levels might be associated with 

a decrease in hospital admissions of 3%. The baseline incidence of the health effect is necessary 

to convert this relative change into a number of cases. A baseline incidence rate is the estimate of 

the number of cases of the health effect per year in the assessment location, as it corresponds to 

baseline pollutant levels in that location. To derive the total baseline incidence per year, this rate 

must be multiplied by the corresponding population number. For example, if the baseline 

incidence rate is the number of cases per year per million people, that number must be multiplied 

by the millions of people in the total population. 

Table 8-13 summarizes the sources of baseline incidence rates and provides average 

incidence rates for the endpoints included in the analysis. For both baseline incidence and 

prevalence data, we used age-specific rates where available. We applied concentration-response 

functions to individual age groups and then summed over the relevant age range to provide an 
8-27

estimate of total population benefits. In most cases, we used a single national incidence rate, due 

to a lack of more spatially disaggregated data. Whenever possible, the national rates used are 

national averages, because these data are most applicable to a national assessment of benefits. 

For some studies, however, the only available incidence information comes from the studies 

themselves; in these cases, incidence in the study population is assumed to represent typical 

incidence at the national level. County, state and regional incidence rates are available for 

hospital admissions, and county-level data are available for premature mortality. 

We projected mortality rates such that future mortality rates are consistent with our 

projections of population growth.98 To perform this calculation, we began first with an average 

of 2004–2006 cause-specific mortality rates. Using Census Bureau projected national-level 

annual mortality rates stratified by age range, we projected these mortality rates to 2050 in 5-year 

increments. 99,100

The baseline incidence rates for hospital admissions and emergency department visits 

reflect the revised rates first applied in the CSAPR RIA.101 In addition, we have revised the 

baseline incidence rates for acute myocardial infarction. These revised rates are more recent, 

which provides a better representation of the rates at which populations of different ages, and in 

different locations, visit the hospital and emergency department for air pollution-related 

illnesses. Also, the new baseline incidence rates are more spatially refined. For many locations 

within the U.S., these data are resolved at the county- or state-level, providing a better 

characterization of the geographic distribution of hospital and emergency department visits than 

the previous national rates. Lastly, these rates reflect unscheduled hospital admissions only, 

which represent a conservative assumption that most air pollution-related visits are likely to be 

unscheduled. If air pollution-related hospital admissions are scheduled, this assumption would 

underestimate these benefits. 

For the set of endpoints affecting the asthmatic population, in addition to baseline 

incidence rates, prevalence rates of asthma in the population are needed to define the applicable 

population. Table 8-14 lists the prevalence rates used to determine the applicable population for 

asthma symptoms. Note that these reflect current asthma prevalence and assume no change in 

prevalence rates in future years. We updated these rates in the CSAPR RIA. 

Table 8-13: Baseline Incidence Rates and Population Prevalence Rates for Use in Impact 

Functions, General Population 

Endpoint Parameter Rates

Value Source

Mortality Daily or annual mortality 

rate projected to 2020

Age-, cause-, and 

county-specific rate

CDC Wonder (2006–2008)102

U.S. Census bureau

Hospitalizations Daily hospitalization rate Age-, region-, state-, 

county- and causespecific rate

2007 HCUP data filesa,103

Asthma ER Visits Daily asthma ER visit rate Age-, region-, state-, 

county- and causespecific rate

2007 HCUP data filesa

Nonfatal Myocardial Daily nonfatal myocardial Age-, region-, state-, 2007 HCUP data files;

a

adjusted by 
8-28

Endpoint Parameter Rates

Value Source

Infarction (heart 

attacks)

infarction incidence rate 

per person, 18+

and county- specific 

rate

0.93 for probability of surviving after 

28 days (Rosamond et al., 1999)104

Asthma Exacerbations Incidence among asthmatic 

African-American children

daily wheeze

daily cough

daily shortness of breath

0.173

0.145

0.074

Ostro et al. (2001)

Acute Bronchitis Annual bronchitis 

incidence rate, children

0.043 American Lung Association (2002, 

Table 11)105

Lower Respiratory 

Symptoms

Daily lower respiratory 

symptom incidence among 

childrenb

0.0012 Schwartz et al. (1994, Table 2)

Upper Respiratory 

Symptoms

Daily upper respiratory 

symptom incidence among 

asthmatic children

0.3419 Pope et al. (1991, Table 2)

Work Loss Days Daily WLD incidence rate 

per person (18–65)

Aged 18–24

Aged 25–44

Aged 45–64

0.00540

0.00678

0.00492

1996 HIS (Adams, Hendershot, and 

Marano, 1999, Table 41);106 U.S. 

Bureau of the Census (2000)107

School Loss Days Rate per person per year, 

assuming 180 school days 

per year

9.9 National Center for Education 

Statistics (1996)108 and 1996 HIS 

(Adams et al., 1999, Table 47); 

Minor RestrictedActivity DaysDaily MRAD incidence 

rate per person

0.02137 Ostro and Rothschild (1989, p. 243)

Notes: 

a

 Healthcare Cost and Utilization Program (HCUP) database contains individual level, state and regional-level 

hospital and emergency department discharges for a variety of ICD codes. 

b

 Lower respiratory symptoms are defined as two or more of the following: cough, chest pain, phlegm, and wheeze. 

Table 8-14: Asthma Prevalence Rates Used for this Analysis 

Population Group Asthma Prevalence Rates

Value Source

All Ages 0.0780

American Lung Association (2010, Table 7)109

< 18 0.0941

5–17 0.1070

18–44 0.0719

45–64 0.0745

65+ 0.0716

African American, 5 to 17 0.1776 American Lung Association (2010, Table 9)

African American, <18 0.1553 American Lung Associationa

Notes: 

ab Calculated by ALA for U.S. EPA, based on NHIS data (CDC, 2008).110

8.1.2.4.5 Economic Values for Health Outcomes 

After quantifying the change in adverse health impacts, we estimate the economic value 

of these avoided impacts. The appropriate economic value for a change in a health effect depends 
8-29

on whether the health effect is viewed ex ante (before the effect has occurred) or ex post (after 

the effect has occurred). Reductions in ambient concentrations of air pollution generally lower 

the risk of future adverse health effects by a small amount for a large population. The appropriate 

economic measure is therefore ex ante willingness to pay (WTP) for changes in risk. 111

Epidemiological studies generally provide estimates of the relative risks of a particular health 

effect for a given increment of air pollution (often per 10 μg/m3 for PM2.5). These relative risks 

can be used to develop risk coefficients that relate a unit reduction in PM2.5 to changes in the 

incidence of a health effect. In order to value these changes in incidence, WTP for changes in 

risk need to be converted into WTP per statistical incidence. This measure is calculated by 

dividing individual WTP for a risk reduction by the related observed change in risk. For 

example, suppose a measure is able to reduce the risk of premature mortality from 2 in 10,000 to 

1 in 10,000 (a reduction of 1 in 10,000). If individual WTP for this risk reduction is $100, then 

the WTP for an avoided statistical premature mortality amounts to $1 million ($100/0.0001 

change in risk). Using this approach, the size of the affected population is automatically taken 

into account by the number of incidences predicted by epidemiological studies applied to the 

relevant population. The same type of calculation can produce values for statistical incidences of 

other health endpoints. 

For some health effects, such as hospital admissions, WTP estimates are generally not 

available. In these cases, we use the cost of treating or mitigating the effect. For example, for the 

valuation of hospital admissions we use the avoided medical costs as an estimate of the value of 

avoiding the health effects causing the admission. These cost-of-illness (COI) estimates 

generally (although not necessarily in every case) understate the true value of reductions in risk 

of a health effect. They tend to reflect the direct expenditures related to treatment but not the 

value of avoided pain and suffering from the health effect.112,113

We provide unit values for health endpoints (along with information on the distribution 

of the unit value) in Table 8-15. All values are in constant year 2011 dollars, adjusted for growth 

in real income out to 2030 using projections provided by Standard and Poor’s. Economic theory 

argues that WTP for most goods (such as environmental protection) will increase if real income 

increases. Many of the valuation studies used in this analysis were conducted in the late 1980s 

and early 1990s. Because real income has grown since the studies were conducted, people’s 

willingness to pay for reductions in the risk of premature death and disease likely has grown as 

well. We did not adjust cost of illness-based values because they are based on current costs. 

Similarly, we did not adjust the value of school absences, because that value is based on current 

wage rates. For details on valuation estimates for PM-related endpoints, see the the RIA that 

accompanied the final revisions to the National Ambient Air Quality Standards (NAAQS) for 

Particulate Matter. 114 For details on valuation estimates for ozone-related endpoints, see the 

RIAs for the 2008 Ozone NAAQS RIA and the 2010 ozone NAAQS reconsideration.115,116
8-30

Table 8-15: Unit Values for Economic Valuation of Health Endpoints (2011$) 

Health Endpoint Central Estimate of 

Value Per Statistical 

Incidence

1990

Income 

Level

2030 

Income 

Levela

Derivation of Distributions of Estimates

Premature Mortality 

(Value of a Statistical 

Life)

$8,300,000 $10,200,000 EPA currently recommends a central VSL of $6.3m (2000$, 1990 

income) based on a Weibull distribution fitted to 26 published VSL 

estimates (5 contingent valuation and 21 labor market studies). The 

underlying studies, the distribution parameters, and other useful 

information are available in Appendix B of EPA's current Guidelines 

for Preparing Economic Analyses (U.S. EPA, 2010).117 

Nonfatal Myocardial 

Infarction (heart 

attack)

3% discount rate

Age 0–24

Age 25–44

 Age 45–54

Age 55–65

Age 66 and over

7% discount rate

Age 0–24

Age 25–44

Age 45–54

Age 55–65

Age 66 and over

$100,000

$110,000

$120,000

$210,000

$100,000

$100,000

$110,000

$110,000

$200,000

$100,000

$100,000

$110,000

$120,000

$210,000

$100,000

$100,000

$110,000

$110,000

$200,000

$100,000

No distributional information available. Age-specific cost-of-illness 

values reflect lost earnings and direct medical costs over a 5-year 

period following a nonfatal MI. Lost earnings estimates are based on 

Cropper and Krupnick (1990).118 Direct medical costs are based on 

simple average of estimates from Russell et al. (1998)119 and Wittels et 

al. (1990).120

Lost earnings:

Cropper and Krupnick (1990). Present discounted value of 5 years of 

lost earnings:

age of onset: at 3% at 7%

25–44 $9,000 $8,000

45–54 $13,000 $12,000

55–65 $77,000 $69,000

Direct medical expenses: An average of:

1. Wittels et al. (1990) ($100,000—no discounting)

2. Russell et al. (1998), 5-year period ($22,000 at 3% discount rate; 

$21,000 at 7% discount rate)

Hospital Admissions

Chronic Obstructive 

Pulmonary Disease 

(COPD)

$22,000 $22,000 No distributional information available. The COI estimates (lost 

earnings plus direct medical costs) are based on ICD-9 code-level 

information (e.g., average hospital care costs, average length of 

hospital stay, and weighted share of total COPD category illnesses) 

reported in Agency for Healthcare Research and Quality (2007) 

(www.ahrq.gov).

121

Asthma Admissions $17,000 $17,000 No distributional information available. The COI estimates (lost 

earnings plus direct medical costs) are based on ICD-9 code-level 

information (e.g., average hospital care costs, average length of 

hospital stay, and weighted share of total asthma category illnesses) 

reported in Agency for Healthcare Research and Quality (2007) 

(www.ahrq.gov). 

All Cardiovascular

 Age 18-64

 Age 65-99

$43,000

$42,000

$43,000

$42,000

No distributional information available. The COI estimates (lost 

earnings plus direct medical costs) are based on ICD-9 code-level 

information (e.g., average hospital care costs, average length of 

hospital stay, and weighted share of total cardiovascular category 

illnesses) reported in Agency for Healthcare Research and Quality 

(2007) (www.ahrq.gov). 

All respiratory (ages 

65+)

$37,000 $37,000 No distributions available. The COI point estimates (lost earnings plus 

direct medical costs) are based on ICD-9 code level information (e.g., 

average hospital care costs, average length of hospital stay, and 

weighted share of total COPD category illnesses) reported in Agency 
8-31

for Healthcare Research and Quality, 2007 (www.ahrq.gov).

All respiratory (ages 

0–2)

$13,000 $13,000 No distributions available. The COI point estimates (lost earnings plus 

direct medical costs) are based on ICD-9 code level information (e.g., 

average hospital care costs, average length of hospital stay, and 

weighted share of total COPD category illnesses) reported in Agency 

for Healthcare Research and Quality, 2007 (www.ahrq.gov).

Emergency Room 

Visits for Asthma

$440 $440 No distributional information available. Simple average of two unit 

COI values:

(1) $311.55, from Smith et al. (1997)122 and

(2) $260.67, from Stanford et al. (1999).123

Respiratory Ailments Not Requiring Hospitalization

Upper Respiratory 

Symptoms (URS)

$32 $34 Combinations of the three symptoms for which WTP estimates are 

available that closely match those listed by Pope et al. result in seven 

different “symptom clusters,” each describing a “type” of URS. A 

dollar value was derived for each type of URS, using mid-range 

estimates of WTP (Neumann et al., 1994)124 to avoid each symptom in 

the cluster and assuming additivity of WTPs. In the absence of 

information surrounding the frequency with which each of the seven 

types of URS occurs within the URS symptom complex, we assumed a 

uniform distribution between $9.2 and $43 (2000$).

Lower Respiratory 

Symptoms (LRS)

$21 $22 Combinations of the four symptoms for which WTP estimates are 

available that closely match those listed by Schwartz et al. result in 11 

different “symptom clusters,” each describing a “type” of LRS. A 

dollar value was derived for each type of LRS, using mid-range 

estimates of WTP (Neumann et al., 1994) to avoid each symptom in 

the cluster and assuming additivity of WTPs. The dollar value for LRS 

is the average of the dollar values for the 11 different types of LRS. In 

the absence of information surrounding the frequency with which each 

of the 11 types of LRS occurs within the LRS symptom complex, we 

assumed a uniform distribution between $6.9 and $25 (2000$).

Asthma 

Exacerbations

$57 $59 Asthma exacerbations are valued at $45 per incidence, based on the 

mean of average WTP estimates for the four severity definitions of a 

“bad asthma day,” described in Rowe and Chestnut (1986).125 This 

study surveyed asthmatics to estimate WTP for avoidance of a “bad 

asthma day,” as defined by the subjects. For purposes of valuation, an 

asthma exacerbation is assumed to be equivalent to a day in which 

asthma is moderate or worse as reported in the Rowe and Chestnut 

(1986) study. The value is assumed have a uniform distribution 

between $16 and $71 (2000$).

Acute Bronchitis $470 $510 Assumes a 6-day episode, with the distribution of the daily value 

specified as uniform with the low and high values based on those 

recommended for related respiratory symptoms in Neumann et al. 

(1994). The low daily estimate of $10 is the sum of the mid-range 

values recommended by IEc 1994 for two symptoms believed to be 

associated with acute bronchitis: coughing and chest tightness. The 

high daily estimate was taken to be twice the value of a minor 

respiratory restricted-activity day, or $110 (2000$). 

Work Loss Days 

(WLDs)

Variable 

(U.S. 

median = 

$150)

Variable 

(U.S. 

median = 

$150)

No distribution available. Point estimate is based on county-specific 

median annual wages divided by 50 (assuming 2 weeks of vacation) 

and then by 5—to get median daily wage. U.S. Year 2000 Census, 

compiled by Geolytics, Inc. (Geolytics, 2002)126
8-32

Minor Restricted 

Activity Days 

(MRADs)

$66 $71 Median WTP estimate to avoid one MRAD from Tolley et al. 

(1986).127 Distribution is assumed to be triangular with a minimum of 

$22 and a maximum of $83, with a most likely value of $52 (2000$). 

Range is based on assumption that value should exceed WTP for a 

single mild symptom (the highest estimate for a single symptom—for 

eye irritation—is $16.00) and be less than that for a WLD. The 

triangular distribution acknowledges that the actual value is likely to be 

closer to the point estimate than either extreme.

School Absence Days $98 $98 No distribution available

Note: 

a

 Willingness-to-pay-based benefits are adjusted by multiplying the unadjusted benefits by the appropriate 

adjustment factor to account for income growth over time using projections provided by Standard and Poor’s. Due 

to a lack of reliable projections of income growth past 2024, we assume constant WTP from 2024 through 2030. 

This results in an underestimate of benefits occurring between 2024 and 2030. For growth between 2000 and 2024, 

this factor is 1.23 for long-term mortality, 1.27 for chronic health impacts, and 1.08 for minor health impacts. Note 

that similar adjustments do not exist for cost-of-illness-based unit values. For these, we apply the same unit value 

regardless of the future year of analysis. 

8.1.2.4.6 Manipulating Air Quality Modeling Data for Health 

Impacts Analysis 

In Chapter 7, we summarized the methods for and results of estimating air quality for the 

program. These air quality results are in turn associated with human populations to estimate 

changes in health effects. For the purposes of this analysis, we focus on the health effects that 

have been linked to ambient changes in ozone and PM2.5 related to emission reductions estimated 

to occur due to the implementation of the program. We estimate ambient PM2.5 and ozone 

concentrations using the Community Multiscale Air Quality model (CMAQ). This section 

describes how we converted the CMAQ modeling output into full-season profiles suitable for the 

health impacts analysis. 

General Methodology 

First, we extracted hourly, surface-layer PM and ozone concentrations for each grid cell 

from the standard CMAQ output files. For ozone, these model predictions are used in 

conjunction with the observed concentrations obtained from the Aerometric Information 

Retrieval System (AIRS) to generate ozone concentrations for the entire ozone season.L,M

 The 

predicted changes in ozone concentrations from the future-year base case to future-year control 

scenario serve as inputs to the health and welfare impact functions of the benefits analysis (i.e., 

BenMAP). 

To estimate ozone-related health effects for the contiguous United States, full-season 

ozone data are required for every BenMAP grid-cell. Given available ozone monitoring data, we 

generated full-season ozone profiles for each location in two steps: (1) we combined monitored 

 

L

 The ozone season for this analysis is defined as the 5-month period from May to September. 

M

 Based on AIRS, there were 961 ozone monitors with sufficient data (i.e., 50 percent or more days reporting at 

least nine hourly observations per day [8 am to 8 pm] during the ozone season). 
8-33

observations and modeled ozone predictions to interpolate hourly ozone concentrations to a grid 

of 12-km by 12-km population grid cells for the contiguous 48 states, and (2) we converted these 

full-season hourly ozone profiles to an ozone measure of interest, such as the daily 8-hour 

maximum.N,O

For PM2.5, we also use the model predictions in conjunction with observed monitor data. 

CMAQ generates predictions of hourly PM species concentrations for every grid. The species 

include a primary coarse fraction (corresponding to PM in the 2.5 to 10 micron size range), a 

primary fine fraction (corresponding to PM less than 2.5 microns in diameter), and several 

secondary particles (e.g., sulfates, nitrates, and organics). PM2.5 is calculated as the sum of the 

primary fine fraction and all of the secondarily formed particles. Future-year estimates of PM2.5

were calculated using relative reduction factors (RRFs) applied to 2005 ambient PM2.5 and PM2.5

species concentrations. A gridded field of PM2.5 concentrations was created by interpolating 

Federal Reference Monitor ambient data and IMPROVE ambient data. Gridded fields of PM2.5 

species concentrations were created by interpolating EPA speciation network (ESPN) ambient 

data and IMPROVE data. The ambient data were interpolated to the CMAQ 12 km grid. 

The procedures for determining the RRFs are similar to those in EPA’s draft guidance for 

modeling the PM2.5 standard (EPA, 2001).128

 The guidance recommends that model predictions 

be used in a relative sense to estimate changes expected to occur in each major PM2.5 species. 

The procedure for calculating future-year PM2.5 design values is called the “Speciated Modeled 

Attainment Test (SMAT).” EPA used this procedure to estimate the ambient impacts of the final 

program. 

Table 8-16 provides those ozone and PM2.5 metrics for grid cells in the modeled domain 

that enter the health impact functions for health benefits endpoints. The population-weighted 

average reflects the baseline levels and predicted changes for more populated areas of the nation. 

This measure better reflects the potential benefits through exposure changes to these populations. 

Table 8-16: Summary of CMAQ-Derived Population-Weighted Ozone and PM2.5 Air 

Quality Metrics for Health Benefits Endpoints Associated with the Final Tier 3 Program 

2030

Statistica Baseline Changeb

Ozone Metric: National Population-Weighted Average (ppb)c

Daily Maximum 8-Hour Average 

Concentration 

43.65 0.32

PM2.5 Metric: National Population-Weighted Average (μg/m3)

Annual Average Concentration 7.94 0.04

Notes: 

 

N

 The 12-km grid squares contain the population data used in the health benefits analysis model, BenMAP. 

O

 This approach is a generalization of planar interpolation that is technically referred to as enhanced Voronoi 

Neighbor Averaging (EVNA) spatial interpolation. See the BenMAP manual for technical details, available for 

download at http://www.epa.gov/air/benmap. 
8-34

a

 Ozone and PM2.5 metrics are calculated at the CMAQ grid-cell level for use in health effects 

estimates. Ozone metrics are calculated over relevant time periods during the daylight hours of 

the “ozone season” (i.e., May through September). Note that the national, population-weighted 

PM2.5 and ozone air quality metrics presented in this chapter represent an average for the entire, 

gridded U.S. CMAQ domain. These are different than the population-weighted PM2.5 and ozone 

design value metrics presented in Chapter 7, which represent the average for areas with a current 

air quality monitor. 

b

 The change is defined as the base-case value minus the control-case value. 

c

 Calculated by summing the product of the projected CMAQ grid-cell population and the 

estimated CMAQ grid cell seasonal ozone concentration and then dividing by the total population.

Emissions and air quality modeling decisions are made early in the analytical process. 

For this reason, the emission control scenarios used in the air quality and benefits modeling are 

slightly different than the final emission inventories estimated for the Tier 3 standards. Please 

refer to Section 7.2.1.1 for more information about the inventories used in the air quality 

modeling that supports the health impacts analysis. 

8.1.2.5 Methods for Describing Uncertainty 

In any complex analysis using estimated parameters and inputs from numerous models, 

there are likely to be many sources of uncertainty. This analysis is no exception. As outlined both 

in this and preceding chapters, this analysis includes many data sources as inputs, including 

emission inventories, air quality data from models (with their associated parameters and inputs), 

population data, population estimates, health effect estimates from epidemiology studies, 

economic data for monetizing benefits, and assumptions regarding the future state of the world 

(i.e., regulations, technology, and human behavior). Each of these inputs may be uncertain and 

would affect the benefits estimate. When the uncertainties from each stage of the analysis are 

compounded, even small uncertainties can have large effects on the total quantified benefits. 

After reviewing the EPA’s approach, the National Research Council (NRC) (2002, 2008),

129,130 which is part of the National Academies of Science, concluded that the EPA’s general 

methodology for calculating the benefits of reducing air pollution is reasonable and informative 

in spite of inherent uncertainties. The NRC also highlighted the need to conduct rigorous 

quantitative analyses of uncertainty and to present benefits estimates to decision makers in ways 

that foster an appropriate appreciation of their inherent uncertainty. Since the publication of these 

reports, the EPA has continued work to improve the characterization of uncertainty in both 

health incidence and benefits estimates. In response to these recommendations, we have 

expanded our previous analyses to incorporate additional quantitative and qualitative 

characterizations of uncertainty. Although we have not yet been able to make as much progress 

towards a full, probabilistic uncertainty assessment as envisioned by the NAS as we had hoped, 

we have added a number of additional quantitative and qualitative analyses to highlight the 

impact that uncertain assumptions may have on the benefits estimates. In addition, for some 

inputs into the benefits analysis, such as the air quality data, it is difficult to address uncertainty 

probabilistically due to the complexity of the underlying air quality models and emission inputs. 

Therefore, we decline to make up alternative assumptions simply for the purpose of probabilistic 

uncertainty characterization when there is no scientific literature to support alternate 

assumptions. 
8-35

To characterize uncertainty and variability, the 2012 PM NAAQS RIA utilized an 

approach that combined elements from two recent analyses by the EPA,131,132 and used a tiered 

approach developed by the World Health Organization (WHO) for characterizing uncertainty.133

We refer the reader to this tiered assessment as an assessment of the potential impact and 

magnitude of each aspect of uncertainty that is also present in the final Tier 3 RIA (see Appendix 

5c of the 2012 PM NAAQS RIA). 

Data limitations prevent us from treating each source of uncertainty quantitatively and 

from reaching a full-probabilistic simulation of our results, but we were able to consider the 

influence of uncertainty in the risk coefficients and economic valuation functions by 

incorporating four quantitative analyses described in more detail below: 

1. A Monte Carlo assessment that accounts for random sampling error and between 

study variability in the epidemiological and economic valuation studies; 

2. The quantification of PM-related mortality using alternative PM2.5 mortality effect 

estimates drawn from two long-term cohort studies and an expert elicitation; 

3. A concentration benchmark assessment that characterizes the distribution of 

avoided PM2.5-related deaths relative to specific concentrations in the long-term epidemiological 

studies used to estimate PM2.5-related mortality; 

4. The quantification of ozone-related mortality using alternative ozone mortality 

effect estimates drawn from six short-term studies: three multi-city studies and three metaanalyses of the existing literature; 

5. An analysis of the influence of various parameters on total monetized benefits. 

8.1.2.5.1 Monte Carlo Assessment 

Similar to other recent RIAs, we used Monte Carlo methods for characterizing random 

sampling error associated with the concentration response functions from epidemiological 

studies and random effects modeling to characterize both sampling error and variability across 

the economic valuation functions. The Monte Carlo simulation in the BenMAP software 

randomly samples from a distribution of incidence and valuation estimates to characterize the 

effects of uncertainty on output variables. Specifically, we used Monte Carlo methods to 

generate confidence intervals around the estimated health impact and monetized benefits. The 

reported standard errors in the epidemiological studies determined the distributions for individual 

effect estimates for endpoints estimated using a single study. For endpoints estimated using a 

pooled estimate of multiple studies, the confidence intervals reflect both the standard errors and 

the variance across studies. The confidence intervals around the monetized benefits incorporate 

the epidemiology standard errors as well as the distribution of the valuation function. These 

confidence intervals do not reflect other sources of uncertainty inherent within the estimates, 

such as 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 benefits estimates. 
8-36

8.1.2.5.2 Alternative Concentration-Response Functions for PM2.5-

Related Mortality 

We assign the greatest economic value to the reduction in PM2.5 related mortality risk. 

Therefore, it is particularly important to attempt to characterize the uncertainties associated with 

reductions in premature mortality. To better understand the concentration-response relationship 

between PM2.5 exposure and premature mortality, the EPA conducted an expert elicitation in 

2006.134,135 In general, the results of the expert elicitation support the conclusion that the 

benefits of PM2.5 control are very likely to be substantial. 

Alternative concentration-response functions are useful for assessing uncertainty beyond 

random statistical error, including uncertainty in the functional form of the model or alternative 

study design. Thus, we include the expert elicitation results as well as standard errors approaches 

to provide insights into the likelihood of different outcomes and about the state of knowledge 

regarding the benefits estimates. In this analysis, we present the results derived from the expert 

elicitation as indicative of the uncertainty associated with a major component of the health 

impact functions, and we provide the independent estimates derived from each of the twelve 

experts to better characterize the degree of variability in the expert responses. 

In previous RIAs, the EPA presented benefits estimates using concentration response 

functions derived from the PM2.5 Expert Elicitation as a range from the lowest expert value 

(Expert K) to the highest expert value (Expert E). However, this approach did not indicate the 

agency’s judgment on what the best estimate of PM2.5 benefits may be, and the EPA’s 

independent Science Advisory Board (SAB) recommended refinements to the way EPA 

presented the results of the elicitation.136 As a result of this recommendation, we have presented 

the ACS and Six-Cities cohort-based studies as our core premature mortality estimates, such as 

in the RIA for the final PM NAAQS. 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 of the mean PM2.5 effect on mortality fall between the two epidemiologybased estimates. Please note that the benefits estimates results presented are not the direct results 

from the studies or expert elicitation; rather, the estimates are based in part on the effect 

coefficients provided in those studies or by experts. In addition, the experts provided 

distributions around their mean PM2.5 effect estimates, which provide more information 

regarding the overall range of uncertainty, and this overall range is larger than the range of the 

mean effect estimates from each of the experts. 

Even these multiple characterizations with confidence intervals omit the contribution to 

overall uncertainty from uncertainty in air quality changes, baseline incidence rates, and 

populations exposed. Furthermore, the approach presented here does not yet include methods for 

addressing correlation between input parameters and the identification of reasonable upper and 

lower bounds for input distributions characterizing uncertainty in additional model elements. As 

a result, the reported confidence intervals and range of estimates give an incomplete picture 

about the overall uncertainty in the estimates. This information should be interpreted within the 

context of the larger uncertainty surrounding the entire analysis. 
8-37

8.1.2.5.3 Concentration Benchmark Analysis for PM2.5

In this analysis, we estimate the number of avoided PM2.5-related deaths occurring due to 

PM2.5 reductions down to various PM2.5 concentration benchmarks, including the Lowest 

Measured Level (LML) of each long-term PM2.5 mortality study. This analysis is one of several 

sensitivities that the EPA has historically performed that characterize the uncertainty associated 

with the PM-mortality relationship and the economic value of reducing the risk of premature 

death. 137,138,139

Our review of the current body of scientific literature indicates that a log-linear nothreshold model provides the best estimate of PM-related long-term mortality. The PM ISA,140

which was twice reviewed by the EPA’s Clean Air Scientific Advisory Committee, 141,142

concluded that the evidence supports the use of a no-threshold log-linear model while also 

recognizing potential uncertainty about the exact shape of the concentration-response function.P

Consistent with this finding, we estimate benefits associated with the full range of PM2.5 

exposure in conjunction with sensitivity analyses to recognize the potential uncertainty at lower 

concentrations. Specifically, we incorporated a LML assessment, a method the EPA has 

employed in several recent RIAs.143,144,145 In addition, we have incorporated an assessment using 

specific concentration benchmarks identified in the EPA’s Policy Assessment for Particulate 

Matter.

146

These two approaches summarize the distribution of avoided PM2.5-related mortality 

impacts relative to baseline (i.e., pre-rule) annual mean PM2.5 levels. The LML approach 

compares the percentage of avoided premature deaths estimated to occur above and below the 

minimum observed air quality level of each long-term cohort study we use to quantify PM. In the 

air quality benchmark approach, we summarize the impacts occurring at different points in the 

distribution of the air quality data used in these same epidemiology studies. 

Our confidence in the estimated number of premature deaths avoided (but not in the 

existence of a causal relationship between PM and premature mortality) diminishes as we 

estimate these impacts in locations where PM2.5 levels are below the LML. This interpretation is 

consistent with the Policy Assessment and advice from SAB-CASAC during their peer review.147

The Policy Assessment concludes that the range from the 25th to the 10th percentile is a 

reasonable range of the air quality distribution below which we start to have appreciably less 

confidence in the magnitude of the associations observed in the epidemiological studies. In 

general, we are more confident in the magnitude of the risks we estimate from simulated PM2.5 

concentrations that coincide with the bulk of the observed PM concentrations in the 

epidemiological studies at are used to estimate the benefits. Likewise, we are less confident in 

the risk we estimate from simulated PM2.5 concentrations that fall below the bulk of the observed 

data in these studies. However, there are uncertainties inherent in identifying any particular point 

at which our confidence in reported associations becomes appreciably less, and the scientific 

evidence provides no clear dividing line. 

 

P

 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 Concentration-Response Function for PM2.5-related Mortality (U.S. EPA, 2010f). 
8-38

For these reasons, we consider the LML as well as one standard deviation below the 

meanQair quality levels when characterizing the distribution of mortality impacts. It is important 

to emphasize that “less confidence” does not mean “no confidence.” In addition, while we may 

have less confidence in the magnitude of the risk, we still have high confidence that PM2.5 is 

causally associated with risk at those lower air quality concentrations. To clarify this concept, 

Figure 8-2graphically displays the spectrum of confidence using illustrative concentration 

benchmarks from the major epidemiology studies cited in this chapter. 

Figure 8-2: Relationship between the Size of the PM Mortality Estimates and the PM2.5

Concentration Observed in the Epidemiology Study 

Although these types of concentration benchmark analyses (e.g., LML, one standard 

deviation below the mean, etc.) provide some insight into the level of uncertainty in the 

estimated PM2.5 mortality benefits, the EPA does not view these concentration benchmarks as a 

concentration threshold below which we would not quantify health benefits of air quality 

improvements. Rather, the core benefits estimates reported in this RIA (i.e., those based on 

Krewski et al. (2009) and Lepeule et al. (2012)) are the best measures because they reflect the 

full range of modeled air quality concentrations associated with the emission reduction 

strategies. In reviewing the Policy Assessment, SAB-CASAC confirmed that “[a]lthough there is 

increasing uncertainty at lower levels, there is no evidence of a threshold (i.e., a level below 

which there is no risk for adverse health effects)”. 148 In addition, in reviewing the Costs and 

Benefits of the Clean Air Act,

149 the SAB-HES noted that “[t]his [no-threshold] decision is 

supported by the data, which are quite consistent in showing effects down to the lowest measured 

levels. Analyses of cohorts using data from more recent years, during which time PM 

concentrations have fallen, continue to report strong associations with mortality”.150 Therefore, 

 

Q

 A range of one standard deviation around the mean represents approximately 68 percent of normally distributed 

data, and, below the mean falls between the 25th and 10th percentiles. 
8-39

the best estimate of benefits includes estimates below and above these concentration benchmarks 

but uncertainty is higher in the magnitude of health benefits estimated at lower concentrations, 

with the lowest confidence below the LML. Estimated health impacts reflecting air quality 

improvements below and above these concentration benchmarks are appropriately included in 

the total benefits estimate. In other words, our higher confidence in the estimated benefits above 

these concentration benchmarks should not imply an absence of confidence in the benefits 

estimated below these concentration benchmarks. 

We estimate that most of the avoided PM-related impacts quantified in this analysis occur 

among populations exposed at or above the LML of the Lepeule et al. (2012) study, while a 

majority of the impacts occur at or above the LML of the Krewski et al. (2009) study. We show 

the estimated reduction in incidence of premature mortality above and below the LML or air 

quality benchmarks of these studies in Table 8-17, and we graphically display the distribution of 

PM2.5-related mortality impacts for the final standard in Figure 8-3 and Figure 8-4. 

Table 8-17: Estimated Reduction in Incidence of Adult Premature Mortality Occurring 

Above and Below Various Concentration Benchmarks in the Underlying Epidemiology 

Studiesa

Epidemiology 

Study

Total 

Reduced 

Mortality 

Incidence

Allocation of Reduced Mortality Incidence

Below 1 Std. 

Dev.

Below AQ 

Mean

At or 

Above 1 

Std. Dev. 

Below AQ 

Mean

Below 

LML

At or Above 

LML

Krewski et al. 

(2009) 660

620 38 37 620

(94%) (6%) (6%) (94%)

Lepeule et al. 

(2012) 1,500 N/A N/A

630 860

(42%) (58%)

a Mortality incidence estimates are rounded to whole numbers and two significant digits, so estimates may not 

sum across columns. One standard deviation below the mean is equivalent to the middle of the range between 

the 10th and 25th percentile. For Krewski, the LML is 5.8 μg/m3 and one standard deviation below the mean is 

11.0 μg/m3

. For Lepeule et al., the LML is 8 μg/m3 and we do not have the data for one standard deviation 

below the mean. It is important to emphasize that although we have lower levels of confidence in levels below 

the LML for each study, the scientific evidence does not support the existence of a level below which health 

effects from exposure to PM2.5 do not occur. 
8-40

0%

5%

10%

15%

20%

25%

30%

<1 1-2 2-3 3-4 4-5 5-6 6-7 7-8 8-9 9-10 10-11 11-12 12-13 13-14 14-15 15-16 16-17 17-18 18-19 19-20 Percentage of Avoided PM2.5Mortalities

Baseline Annual Mean PM2.5 Level (μg/m3)

LML of Lepeule et al. (2012) study

LML of Krewski et al. (2009) study

Of total PM2.5-Related deaths avoided for 12 μg/m3 : 

94% occur among populations exposed to PM2.5 levels at or above the LML of the Krewski et al. (2009) study.

58% occur among populations exposed to PM2.5 levels at or above the LML of the Lepeule et al. (2012) study. 

Figure 8-3. Number of Premature PM2.5-related Deaths Avoided for the Final Tier 3 

Standards in 2030 According to the Baseline Level of PM2.5 and the Lowest Measured Air 

Quality Levels of Each Mortality Study 
8-41

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Cumulative percentage of avoided PM Mortalities

Baseline Annual Mean PM2.5 Level (μg/m3)

Cumulative Percentage of Total PM-related Mortalities Avoided by 

Baseline Air Quality Level

LML of Krewski et al. (2009) study

LML of Lepeule et al. (2012) study

Of total PM2.5-Related deaths avoided for 12 μg/m3: 

94% occur among populations exposed to PM2.5 levels at or above the LML of the Krewski et al. (2009) study.

58% occur among populations exposed to PM2.5 levels at or above the LML of the Lepeule et al. (2012) study. 

Figure 8-4. Number of Premature PM2.5-related Deaths Avoided for the Final Tier 3 

Standards in 2030 According to the Baseline Level of PM2.5 and the Lowest Measured Air 

Quality Levels of Each Mortality Study 

While the LML of each study is important to consider when characterizing and 

interpreting the overall level of PM2.5-related benefits, as discussed earlier in this chapter, the 

EPA believes that both of the cohort-based mortality estimates are suitable for use in air 

pollution health impact analyses. When estimating PM-related premature deaths avoided using 

risk coefficients drawn from the Lepeule et al. (2012) analysis of the Harvard Six Cities and the 

Krewski et al. (2009) analysis of the ACS cohorts there are innumerable other attributes that may 

affect the size of the reported effect estimates—including differences in population 

demographics, the size of the cohort, activity patterns and particle composition among others. 

The LML assessment presented here provides a limited representation of one key difference 

between the two studies. 
8-42

8.1.2.5.4 Alternative Concentration-Response Functions for OzoneRelated Mortality 

In 2006 the EPA requested an NAS study to evaluate the extent to which the 

epidemiological literature to that point improved the understanding of ozone-related mortality. 

The NAS found that short-term ozone exposure was likely to contribute to ozone-related 

mortality151 and issued a series of recommendations to EPA, including that the Agency should 

present multiple short-term ozone mortality estimates, including those based on multi-city 

analyses such as the National Morbidity, Mortality and Air Pollution Study (NMMAPS) as well 

as meta-analytic studies. The NAS also recommended that EPA remove reference to a no-causal 

relationship between ozone exposure and premature mortality. The quantification and 

presentation of ozone-related premature mortality in this analysis is responsive to these 

recommendations. 

8.1.2.5.5 Influence Analysis – Quantitative Assessment of 

Uncertainty 

In the past few years, the EPA has initiated several projects to improve the 

characterization of uncertainty for benefits analysis. In particular, the EPA recently completed 

the first phase of a quantitative uncertainty analysis of benefits, hereafter referred to as the 

“Influence Analysis”. 152 The Influence Analysis diagramed the uncertain components of each 

step within the benefits analysis process, identified plausible ranges for a sensitivity analysis, and 

assessed the sensitivity to total benefits to changes in each component. Although this analysis 

does not quite fulfill the goal of a full probabilistic assessment, it accomplished the necessary 

first steps and identified the challenges to accomplishing that goal. Below are some of the 

preliminary observations from the first phase of the project. 

The components that contribute the most to uncertainty of the monetized benefits 

and mortality incidence (in order of importance) are the value-of-a-statistical-life 

(VSL), the concentration-response (C-R) function for mortality, and change in 

PM2.5 concentration. 

The components that contribute the least to uncertainty of the monetized benefits 

and mortality incidence are population, morbidity valuation, and income 

elasticity. 

The choice of a C-R function for mortality affects the mortality incidence and 

monetized benefits more than other sources of uncertainty within each C-R 

function. 

Alternative cessation lag structures for mortality have a moderate effect on the 

monetized benefits. 

Because the health impact function is essentially linear, the key components show 

the same sensitivity across all mortality C-R functions even if the midpoints differ 

significantly from one expert to another. 
8-43

8.1.2.5.6 Qualitative Assessment of Uncertainty and Other Analysis 

Limitations 

Although we strive to incorporate as many quantitative assessments of uncertainty as 

possible, there are several aspects we are only able to address qualitatively. These aspects are 

important factors to consider when evaluating the benefits of the final Tier 3 standards. 

The total monetized benefit estimates presented in this chapter are based on our 

interpretation of the best available scientific literature and methods and supported by the EPA’s 

independent SAB (Health Effects Subcommittee) (SAB-HES) and the National Academies of 

Science (NAS).153,154 The benefit estimates are subject to a number of assumptions and 

uncertainties. For example, the key assumptions underlying the estimates for premature 

mortality, which account for over 98% of the total monetized benefits in this analysis, include 

the following: 

1. 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 varies considerably in composition across 

sources, but the scientific evidence is not yet sufficient to allow differentiation of 

effect estimates by particle type. The 2009 PM ISA, which was twice reviewed by 

Clean Air Scientific Advisory Committee (SAB-CASAC), concluded that “many 

constituents of PM2.5 can be linked with multiple health effects, and the evidence 

is not yet sufficient to allow differentiation of those constituents or sources that 

are more closely related to specific outcomes”.155

2. We assume that the health impact function for fine particles is log-linear 

without a threshold in this analysis. Thus, the estimates include health benefits 

from reducing fine particles in areas with varied concentrations of PM2.5, 

including both areas that do not meet the fine particle standard and those areas 

that are in attainment, down to the lowest modeled concentrations. 

3. We assume that there is a “cessation” lag between the change in PM 

exposures and the total realization of changes in mortality effects. Specifically, 

we assume that some of the incidences of premature mortality related to PM2.5

exposures occur in a distributed fashion over the 20 years following exposure 

based on the advice of the SAB-HES,156 which affects the valuation of mortality 

benefits at different discount rates. 

4. To characterize the uncertainty in the relationship between PM2.5 and 

premature mortality, 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. 
8-44

This information should be interpreted within the context of the larger uncertainty 

surrounding the entire analysis. 

5. There is uncertainty in the magnitude of the association between ozone 

and premature mortality. The range of ozone benefits associated with the final 

standards is estimated based on the risk of several sources of ozone-related 

mortality effect estimates. In a report on the estimation of ozone-related 

premature mortality published by the National Research Council, a panel of 

experts and reviewers concluded that short-term exposure to ambient ozone is 

likely to contribute to premature deaths and that ozone-related mortality should be 

included in estimates of the health benefits of reducing ozone exposure.R

As previously described, we strive to monetize as many of the benefits anticipated from 

the revised and alternative standards as possible given data and resource limitations, but the 

monetized benefits estimated in this RIA inevitably only reflect a portion of the benefits. 

Specifically, only certain benefits attributable to the health impacts associated with exposure to 

ambient fine particles have been monetized in this analysis. Data and methodological limitations 

prevented the EPA from quantifying or monetizing the benefits from several important health 

benefit categories (see Table 8-5 for more information). If we could fully monetize all of the 

benefit categories, the total monetized benefits would exceed the costs by an even greater margin 

than we currently estimate. 

To more fully address these uncertainties, including those we cannot quantify, the 2012 

PM NAAQS RIA utilized a four-tiered approach using the WHO uncertainty framework,157

which provides a means for systematically linking the characterization of uncertainty to the 

sophistication of the underlying risk assessment. The EPA has applied similar approaches in 

other analyses.158,159 Using this framework, the PM NAAQS summarized the key uncertainties in 

the health benefits analysis, including our assessment of the direction of potential bias, 

magnitude of impact on the monetized benefits, degree of confidence in our analytical approach, 

and our ability to assess the source of uncertainty. We refer the reader to this tiered assessment as 

an assessment of the potential impact and magnitude of each aspect of uncertainty that is also 

present in the final Tier 3 RIA (see Appendix 5b of the 2012 PM NAAQS RIA).160

8.1.3 Comparison of Costs and Benefits 

This section presents the cost-benefit comparison related to the expected impacts of the 

final Tier 3 program. In estimating the net benefits of the program, the appropriate cost measure 

is ‘social costs.’ Social costs represent the welfare costs of a rule to society and do not consider 

transfer payments (such as taxes) that are simply redistributions of wealth. For this analysis, we 

estimate that the social costs of the program are equivalent to the estimated vehicle and fuel 

compliance costs of the program. While vehicle manufacturers and fuel producers would see 

their costs increase by the amount of those compliance costs, they are expected to pass them on 

 

R

 National Research Council (NRC), (2008). Estimating Mortality Risk Reduction and Economic Benefits from 

Controlling Ozone Air Pollution. The National Academies Press: Washington, D.C. 
8-45

in their entirety to vehicle and fuel consumers in the form of increased prices. Ultimately, these 

costs will be borne by the final consumers of these goods. The social benefits of the program are 

represented by the monetized value of health and welfare improvements experienced by the U.S. 

population. Table 8-18 contains the estimated social costs and the estimated monetized benefits 

of the program. 

The results in Table 8-18 suggest that the 2030 monetized benefits of the final standards 

are greater than the expected costs. Specifically, the annual benefits of the total program will 

range between $7.4 to $19 billion annually in 2030 using a three percent discount rate, or 

between $6.7 to $18 billion assuming a 7 percent discount rate, compared to estimated social 

costs of approximately $1.5 billion in that same year. Though there are a number of health and 

environmental effects associated with the final standards that we are unable to quantify or 

monetize (see Table 8-5), the benefits of the final standards outweigh the projected costs. 

Using a conservative benefits estimate, the 2030 benefits outweigh the costs by a factor 

of 4.5. Using the upper end of the benefits range, the benefits could outweigh the costs by a 

factor of 13. Thus, even taking the most conservative benefits assumptions, benefits of the final 

standards clearly outweigh the costs. 

Table 8-18: Summary of Annual Benefts and Costs Associated with the Final Tier 3 

Program (Billions, 2011$)a

Description 2030

Vehicle Program Costs

Fuels Program Costs

Total Estimated Costsb

$0.76

$0.70

$1.5

Total Estimated Health Benefitsc,d,e,f

 3 percent discount rate

 7 percent discount rate

$7.4 - $19

$6.7 - $18

Annual Net Benefits (Total Benefits – Total Costs)

 3 percent discount rate

 7 percent discount rate

$5.9 - $18

$5.2 - $17

Notes: 

a

 All estimates represent annual benefits and costs anticipated for the year 2030. Totals are rounded to two 

significant digits and may not sum due to rounding. 

b

 The calculation of annual costs does not require amortization of costs over time. Therefore, the estimates of annual 

cost do not include a discount rate or rate of return assumption (see Chapter 2 of the RIA for more information on 

vehicle costs, Chapter 5 for fuel costs, and Section 8.1.1 for a summary of total program costs). 

c

 Total includes ozone and PM2.5 benefits. Range was developed by adding the estimate from the Bell et al., 2004 

ozone premature mortality function to PM2.5-related premature mortality derived from the American Cancer Society 

cohort study (Krewski et al., 2009) for the low estimate and ozone premature mortality derived from the Levy et al., 

2005 study to PM2.5-related premature mortality derived from the Six-Cities (Lepeule et al., 2012) study for the high 

estimate. 

d Annual benefits analysis results reflect the use of a 3 percent and 7 percent discount rate in the valuation of 

premature mortality and nonfatal myocardial infarctions, consistent with EPA and OMB guidelines for preparing 

economic analyses. 

e Valuation of premature mortality based on long-term PM exposure assumes discounting over the SAB 

recommended 20-year segmented lag structure described in the Regulatory Impact Analysis for the 2012 PM 

National Ambient Air Quality Standards (December, 2012). 
8-46

f Not all possible benefits or disbenefits are quantified and monetized in this analysis. Potential benefit categories 

that have not been quantified and monetized are listed in Table 8-5. 

8.1.4 Illustrative Analysis of Estimated Quantified and Monetized Impacts Associated with the 

Rule in 2018

For illustrative purposes, this section presents the quantified and monetized impacts 

associated with the final standards in 2018. As presented in Section 7.1.5, the emissions impacts 

of the final standards in 2018 are primarily due to the effects of sulfur on the existing (pre-Tier 3) 

fleet. 

This analysis reflects the impacts of the final Tier 3 rule in 2018 compared to a futureyear reference scenario without the program in place. Overall, we estimate that the final rule will 

lead to a net decrease in PM2.5-related health and environmental impacts in 2018 (see Section 

7.2.4 for more information about the air quality modeling results). The decrease in populationweighted national average PM2.5 exposure results in a net decrease in adverse PM2.5-related 

human health and environmental impacts (the decrease in national population-weighted annual 

average PM2.5 is 0.012 μg/m3in 2018). The air quality modeling also projects decreases in 

ozone concentrations. The overall decrease in population-weighted national average ozone 

exposure results in decreases in ozone-related health and environmental impacts (populationweighted maximum 8-hour average ozone decreases by 0.15 ppb in 2018).

Table 8-19 and Table 8-20 present the annual PM2.5 and ozone health impacts in the 48 

contiguous U.S. states associated with the final Tier 3 program. For each endpoint presented in 

Table 8-19 and Table 8-20, we provide both the point estimate and the 90 percent confidence 

interval. Using EPA’s preferred estimates, based on the American Cancer Society (ACS) and 

Six-Cities studies and no threshold assumption in the model of mortality, we estimate that the 

final standards would result in between 180 and 400 cases of avoided PM2.5-related premature 

mortalities annually in 2018. For ozone-related premature mortality in 2018, we estimate a range 

of between 45 to 210 fewer premature mortalities. 

Table 8-21 presents the estimated monetary value of changes in the incidence of ozone 

and PM2.5-related health and environmental effects. Total aggregate monetized benefits are 

presented in Table 8-22. All monetized estimates are presented in 2011$. Where appropriate, 

estimates account for growth in real gross domestic product (GDP) per capita between 2000 and 

2018. The monetized value of PM2.5-related mortality also accounts for a twenty-year segmented 

cessation lag.S

 To discount the value of premature mortality that occurs at different points in the 

 

S

 Based in part on prior SAB advice, EPA has typically assumed that there is a time lag between changes in 

pollution exposures and the total realization of changes in health effects. Within the context of benefits analyses, 

this term is often referred to as “cessation lag”. The existence of such a lag is important for the valuation of 

premature mortality incidence because economic theory suggests that benefits occurring in the future should be 

discounted. In this analysis, we apply a twenty-year distributed lag to PM mortality reductions. This method is 

consistent with the most recent recommendation by the EPA’s Science Advisory Board. Refer to: EPA – Science 

Advisory Board, 2004. Advisory Council on Clean Air Compliance Analysis Response to Agency Request on 
8-47

future, we apply both a 3 and 7 percent discount rate. We also use both a 3 and 7 percent 

discount rate to value PM2.5-related nonfatal heart attacks (myocardial infarctions).T 

In addition to omitted benefits categories such as air toxics and various welfare effects, 

not all known PM2.5- and ozone-related health and welfare effects could be quantified or 

monetized. The estimate of total monetized health benefits of the final standards is thus equal to 

the subset of monetized PM2.5- and ozone-related health impacts we are able to quantify plus the 

sum of the nonmonetized health and welfare benefits. Our estimate of total monetized benefits 

associated with the final standards in 2018, using the ACS and Six-Cities PM mortality studies 

and the range of ozone mortality assumptions, is between $2.1 and $5.6 billion, assuming a 3 

percent discount rate, or between $1.9 and $5.3 billion, assuming a 7 percent discount rate. 

The results in Table 8-21 demonstrate that the gasoline sulfur standards provide large 

immediate benefits in the program’s first year, related to emission reductions from existing 

gasoline vehicles. The benefits increase substantially after 2018, as the vehicle standards phase 

in after 2018 and as the fleet turns over. 

Table 8-19: Estimated PM2.5-Related Health Impactsa

Health Effect 2018 Annual 

Reduction in 

Incidence

(5th% - 95th%ile)

Premature Mortality – Derived from epidemiology literatureb

 Adult, age 30+, ACS Cohort Study (Krewski et al., 2009)

 Adult, age 25+, Six-Cities Study (Lepeule et al., 2012)

 Infant, age <1 year (Woodruff et al., 1997)

180

(130 – 220)

400

(230 – 570)

0

(0 – 1)

Non-fatal myocardial infarction (adult, age 18 and over)

 Peters et al. (2001)

 Pooled estimate of 4 studies

200

(74 – 330)

22

(11 – 48)

Hospital admissions - respiratory (all ages)c,e 51

(-6 – 93)

Hospital admissions - cardiovascular (adults, age >18)d64

(33 – 110)

Emergency room visits for asthma (age 18 years and younger)e100

(-18 – 200)

Acute bronchitis, (children, age 8-12)e280

(-10 – 560)

Lower respiratory symptoms (children, age 7-14) 3,500

(1,700 – 5,300)

 

Cessation Lag. Letter from the Health Effects Subcommittee to the U.S. Environmental Protection Agency 

Administrator, December. 

T

 Nonfatal myocardial infarctions (MI) are valued using age-specific cost-of-illness values that reflect lost earnings 

and direct medical costs over a 5-year period following a nonfatal MI. 
8-48

Upper respiratory symptoms (asthmatic children, age 9-18) 5,000

(1,600 – 8,500)

Asthma exacerbation (asthmatic children, age 6-18) 5,200

(650 – 10,000)

Work loss days 23,000

(20,000 – 27,000)

Minor restricted activity days (adults age 18-65) 140,000

(120,000 – 160,000)

a Incidence is rounded to two significant digits. Estimates represent incidence within the 48 contiguous United 

States. 

b

PM-related adult mortality based upon the most recent American Cancer Society (ACS) Cohort Study 

(Krewski et al., 2009) and the most recent Six-Cities Study (Lepeule et al., 2012). Note that these are two 

alternative estimates of adult mortality and should not be summed. PM-related infant mortality based upon a 

study by Woodruff, Grillo, and Schoendorf, (1997).U

c Respiratory hospital admissions for PM include admissions for chronic obstructive pulmonary disease 

(COPD), pneumonia and asthma. 

d Cardiovascular hospital admissions for PM include total cardiovascular and subcategories for ischemic heart 

disease, dysrhythmias, and heart failure. 

e The negative estimates at the 5th percentile confidence estimates for these morbidity endpoints reflect the 

statistical power of the study used to calculate these health impacts. These results do not suggest that reducing 

air pollution results in additional health impacts.

Table 8-20: Estimated Ozone-Related Health Impactsa 

Health Effect 2018 Annual Reduction in 

Incidence (5th- 95th

percentile)

Premature Mortality, All agesb

Multi-City Analyses 

 Bell et al. (2004) – Non-accidental

 Huang et al. (2005) – Cardiopulmonary

 Schwartz (2005) – Non-accidental

Meta-analyses:

 Bell et al. (2005) – All cause

 Ito et al. (2005) – Non-accidental

 Levy et al. (2005) – All cause

45

(17 – 73)

65

(27 – 100)

69

(25 – 110)

150

(75 – 220)

200

(130 – 280)

210

(150 – 270)

Hospital admissions- respiratory causes (adult, 65 and older)c 260

(130 – 280)

Hospital admissions -respiratory causes (children, under 2) 130

(60 – 210)

Emergency room visit for asthma (all ages) 140

 

U

 Woodruff, T.J., J. Grillo, and K.C. Schoendorf. (1997). The Relationship Between Selected Causes of 

Postneonatal Infant Mortality and Particulate Air Pollution in the United States. Environmental Health Perspectives

105(6):608-612.
8-49

Health Effect 2018 Annual Reduction in 

Incidence (5th- 95th

percentile)

(-19 – 430)

Minor restricted activity days (adults, age 18-65) 270,000

(120,000 – 420,000)

School absence days 92,000

(36,000 – 140,000)

Notes: 

a

 Incidence is rounded to two significant digits. Estimates represent incidence within the 48 contiguous U.S. 

b

 Estimates of ozone-related premature mortality are based upon incidence estimates derived from several alternative 

studies: Bell et al. (2004); Huang et al. (2005); Schwartz (2005) ; Bell et al. (2005); Ito et al. (2005); Levy et al. (2005). 

The estimates of ozone-related premature mortality should therefore not be summed.

c Respiratory hospital admissions for ozone include admissions for all respiratory causes and subcategories for 

COPD and pneumonia. 

Table 8-21: Estimated Monetary Value of Changes in Incidence of Health and Welfare 

Effects (millions of 2011$) a,b

HEALTH ENDPOINTS 2018

(5TH AND 95TH

PERCENTILE)

PM2.5-Related Health Effects

Premature Mortality – Derived 

from Epidemiology Studiesb,c

Adult, age 30+ - ACS study 

(Krewski et al., 2009)

 3% discount rate

 7% discount rate

$1,600

($230 - $3,700)

$1,400

($210 - $3,300)

Adult, age 25+ - Six-Cities study 

(Lepeule et al., 2012)

 3% discount rate

 7% discount rate

$3,500

($510 - $8,600)

$3,200

($460 - $7,700)

Infant Mortality, <1 year –

(Woodruff et al. 1997)

$4.0

($0.55 - $10)

Non-fatal acute myocardial infarctions 

 Peters et al., 2001

 3% discount rate

 7% discount rate

 Pooled estimate of 4 studies

 3% discount rate

 7% discount rate

$26

($5.9 - $60)

$25

($5.5 - $59)

$2.8

($0.74 - $7.3)

$2.7

($0.68 - $7.2)

Hospital admissions for respiratory causesd$1.4

(-$0.32 - $2.7)

Hospital admissions for cardiovascular causes $2.6

($1.3 - $4.4)

Emergency room visits for asthmad$0.045

(-$0.007 - $0.087)
8-50

Acute bronchitis (children, age 8–12)d$0.14

(-$0.005 - $0.34)

Lower respiratory symptoms (children, 7–14) $0.076

($0.030 - $0.14)

Upper respiratory symptoms (asthma, 9–11) $0.17

($0.049 - $0.38)

Asthma exacerbations $0.31

($0.039 – $0.74)

Work loss days $3.5

($3.1 - $4.0)

Minor restricted-activity days (MRADs) $9.8

($5.7 - $14)

Ozone-Related Health Effects

Premature Mortality, All ages –

Derived from Multi-city analyses

Bell et al., 2004 $440

($56 – $1,100)

Huang et al., 2005 $670

($95 - $1,700)

Schwartz, 2005 $710

($96 - $1,800)

Premature Mortality, All ages –

Derived from Meta-analyses

Bell et al., 2005 $1,400

($200 - $3,600)

Ito et al., 2005 $2,000

($290 - $4,800)

Levy et al., 2005 $2,000

($300 - $4,800)

Hospital admissions- respiratory causes (adult, 65 and older) $7.5

($0.62 - $14)

Hospital admissions- respiratory causes (children, under 2) $1.6

($0.74 - $2.5)

Emergency room visit for asthma (all ages) $0.061

(-$0.008 - $0.18)

Minor restricted activity days (adults, age 18-65) $19

($7.7 - $33)

School absence days $9.4

($3.6 - $14)

a

 Monetary benefits are rounded to two significant digits for ease of presentation and computation. PM and 

ozone benefits are nationwide. 

b

 Monetary benefits adjusted to account for growth in real GDP per capita between 1990 and the analysis 

year (2018).

c

 Valuation assumes discounting over the SAB recommended 20 year segmented lag structure. Results 

reflect the use of 3 percent and 7 percent discount rates consistent with EPA and OMB guidelines for 

preparing economic analyses. 

d The negative estimate at the 5th percentile confidence estimate for this morbidity endpoint reflects the 

statistical power of the study used to calculate this health impact. This result does not suggest that reducing 

air pollution results in additional health impacts.
8-51

Table 8-22: Total Estimated Monetized Ozone and PM-related Benefits Associated with 

the Final Program in 2018 

Total Ozone and PM Benefits (billions, 2011$) –

PM Mortality Derived from the ACS and Six-Cities Studies

3% Discount Rate 7% Discount Rate

Ozone 

Mortality 

Function

Reference Mean Total 

Benefits

Ozone 

Mortality 

Function

Reference Mean Total 

Benefits

Multi-city Bell et al., 

2004

$2.1 - $4.1 Multi-city Bell et al., 

2004

$1.9 - $3.7

Huang et al., 

2005

$2.3 - $4.2 Huang et al., 

2005

$2.1 - $3.9

Schwartz, 

2005

$2.3 - $4.3 Schwartz, 

2005

$2.1 - $3.9

Meta-analysis Bell et al., 

2005

$3.1 - $5.0 Meta-analysis Bell et al., 

2005

$2.9 - $4.7

Ito et al., 

2005

$3.6 - $5.6 Ito et al., 

2005

$3.4 - $5.2

Levy et al., 

2005

$3.6 - $5.6 Levy et al., 

2005

$3.5 - $5.3
8-52

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125 Rowe, R.D., and L.G. Chestnut. 1986. “Oxidants and Asthmatics in Los Angeles: A Benefits Analysis—

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126 GeoLytics Inc. 2002. GeoLytics CensusCD® 2000 Short Form Blocks. CD-ROM Release 1.0. GeoLytics, Inc. 

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128 U.S. EPA, (2001), “Guidance for Demonstrating Attainment of Air Quality Goals for PM2.5 and Regional 

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129 National Research Council (NRC). 2002. Estimating the Public Health Benefits of Proposed Air Pollution 

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130 National Research Council (NRC). 2008. Estimating Mortality Risk Reduction and Economic Benefits from 

Controlling Ozone Air Pollution. National Academies Press. Washington, DC. 

131 U.S. Environmental Protection Agency (U.S. EPA). 2010. Quantitative Health Risk Assessment for Particulate 

Matter—Final Report. EPA-452/R-10-005. Office of Air Quality Planning and Standards, Research Triangle Park, 

NC. September. Available on the Internet at 

<http://www.epa.gov/ttnnaaqs/standards/pm/data/PM_RA_FINAL_June_2010.pdf>. 

132 U.S. Environmental Protection Agency (U.S. EPA). 2011. The Benefits and Costs of the Clean Air Act 1990 to 

2020: EPA Report to Congress. Office of Air and Radiation, Office of Policy, Washington, DC. March. Available 

on the Internet at <http://www.epa.gov/oar/sect812/feb11/fullreport.pdf>. 

133 World Health Organization (WHO). 2008. Part 1: Guidance Document on Characterizing and Communicating 

Uncertainty in Exposure Assessment, Harmonization Project Document No. 6. Published under joint sponsorship of 

the World Health Organization, the International Labour Organization and the United Nations Environment 

Programme. WHO Press: Geneva, Switzerland. Available on the Internet at 

<www.who.int/ipcs/methods/harmonization/areas/uncertainty%20.pdf>. 

134 Roman, Henry A., Katherine D. Walker, Tyra L. Walsh, Lisa Conner, Harvey M. Richmond, Bryan J. Hubbell, 

and Patrick L. Kinney. 2008. “Expert Judgment Assessment of the Mortality Impact of Changes in Ambient Fine 

Particulate Matter in the U.S.” Environ. Sci. Technol., 42(7):2268-2274. 

135 Industrial Economics, Incorporated (IEc). 2006. Expanded Expert Judgment Assessment of the ConcentrationResponse Relationship Between PM2.5 Exposure and Mortality. Prepared for: Office of Air Quality Planning and 

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Internet at <http://www.epa.gov/ttn/ecas/regdata/Uncertainty/pm_ee_tsd_expert_interview_summaries.pdf>. 

136 U.S. Environmental Protection Agency Science Advisory Board (U.S. EPA-SAB). 2008. Characterizing 

Uncertainty in Particulate Matter Benefits Using Expert Elicitation. EPA-COUNCIL-08-002. July. Available on the 
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Internet at <http://yosemite.epa.gov/sab/sabproduct.nsf/0/43B91173651AED9E85257487004EA6CB/$File/EPACOUNCIL-08-002-unsigned.pdf>. 

137 Roman, Henry A., Katherine D. Walker, Tyra L. Walsh, Lisa Conner, Harvey M. Richmond, Bryan J. Hubbell, 

and Patrick L. Kinney. 2008. “Expert Judgment Assessment of the Mortality Impact of Changes in Ambient Fine 

Particulate Matter in the U.S.” Environ. Sci. Technol., 42(7):2268-2274. 

138 U.S. Environmental Protection Agency (U.S. EPA). 2006. Regulatory Impact Analysis, 2006 National Ambient 

Air Quality Standards for Particulate Matter, Chapter 5. Office of Air Quality Planning and Standards, Research 

Triangle Park, NC. October. Available on the Internet at 

<http://www.epa.gov/ttn/ecas/regdata/RIAs/Chapter%205—Benefits.pdf>. 

139 Mansfield, Carol; Paramita Sinha; Max Henrion. 2009. Influence Analysis in Support of Characterizing 

Uncertainty in Human Health Benefits Analysis: Final Report. Prepared for U.S. EPA, Office of Air Quality 

Planning and Standards. November. Available on the internet at 

<http://www.epa.gov/ttn/ecas/regdata/Benefits/influence_analysis_final_report_psg.pdf>. 

140 U.S. Environmental Protection Agency (U.S. EPA). 2009. Integrated Science Assessment for Particulate Matter 

(Final Report). EPA-600-R-08-139F. National Center for Environmental Assessment – RTP Division. December. 

Available on the Internet at <http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=216546>. 

141 U.S. Environmental Protection Agency - Science Advisory Board (U.S. EPA-SAB). 2009. Consultation on 

EPA’s Particulate Matter National Ambient Air Quality Standards: Scope and Methods Plan for Health Risk and 

Exposure Assessment. EPA-COUNCIL-09-009. May. Available on the Internet at 

<http://yosemite.epa.gov/sab/SABPRODUCT.NSF/81e39f4c09954fcb85256ead006be86e/723FE644C5D758DF852

575BD00763A32/$File/EPA-CASAC-09-009-unsigned.pdf>. 

142 U.S. Environmental Protection Agency - Science Advisory Board (U.S. EPA-SAB). 2009. Review of EPA’s 

Integrated Science Assessment for Particulate Matter (First External Review Draft, December 2008). EPACOUNCIL-09-008. May. Available on the Internet at 

<http://yosemite.epa.gov/sab/SABPRODUCT.NSF/81e39f4c09954fcb85256ead006be86e/73ACCA834AB44A1085

2575BD0064346B/$File/EPA-CASAC-09-008-unsigned.pdf>. 

143 U.S. Environmental Protection Agency (U.S. EPA). 2010. Proposed Regulatory Impact Analysis (RIA) for the 

Transport Rule. Office of Air Quality Planning and Standards, Research Triangle Park, NC. January. Available on 

the Internet at <http://www.epa.gov/ttn/ecas/regdata/RIAs/proposaltrria_final.pdf>. 

144 U.S. Environmental Protection Agency (U.S. EPA). 2011. Regulatory Impact Analysis for the Federal 

Implementation Plans to Reduce Interstate Transport of Fine Particulate Matter and Ozone in 27 States; Correction 

of SIP Approvals for 22 States. June. Available on the Internet at 

<http://www.epa.gov/airtransport/pdfs/FinalRIA.pdf>. 

145 U.S. Environmental Protection Agency (U.S. EPA). 2011. Regulatory Impact Analysis for the Final Mercury and 

Air Toxics Standards. EPA-452/R-11-011. December. Available on the Internet at 

<http://www.epa.gov/ttn/ecas/regdata/RIAs/matsriafinal.pdf>. 

146 U.S. Environmental Protection Agency (U.S. EPA). 2011. Policy Assessment for the Review of the Particulate 

Matter National Ambient Air Quality Standards. EPA-452/D-11-003. April. Available on the Internet at 

<http://www.epa.gov/ttnnaaqs/standards/pm/s_pm_2007_pa.html>. 

147 U.S. Environmental Protection Agency Science Advisory Board (U.S. EPA-SAB). 2010. CASAC Review of 

Policy Assessment for the Review of the PM NAAQS—Second External Review Draft (June 2010). EPA-CASAC10-015. Available on the Internet at 

<http://yosemite.epa.gov/sab/sabproduct.nsf/264cb1227d55e02c85257402007446a4/CCF9F4C0500C500F8525779

D0073C593/$File/EPA-CASAC-10-015-unsigned.pdf>. 

148 U.S. Environmental Protection Agency Science Advisory Board (U.S. EPA-SAB). 2010. CASAC Review of 

Policy Assessment for the Review of the PM NAAQS—Second External Review Draft (June 2010). EPA-CASAC10-015. Available on the Internet at 

<http://yosemite.epa.gov/sab/sabproduct.nsf/264cb1227d55e02c85257402007446a4/CCF9F4C0500C500F8525779

D0073C593/$File/EPA-CASAC-10-015-unsigned.pdf>. 
8-61

149 U.S. Environmental Protection Agency (U.S. EPA). 2011a. The Benefits and Costs of the Clean Air Act 1990 to 

2020: EPA Report to Congress. Office of Air and Radiation, Office of Policy, Washington, DC. March. Available 

on the Internet at <http://www.epa.gov/oar/sect812/feb11/fullreport.pdf>. 

150 U.S. Environmental Protection Agency Science Advisory Board (U.S. EPA-SAB). 2010. Review of EPA’s 

DRAFT Health Benefits of the Second Section 812 Prospective Study of the Clean Air Act. EPA-COUNCIL-10-

001. June. Available on the Internet at 

<http://yosemite.epa.gov/sab/sabproduct.nsf/9288428b8eeea4c885257242006935a3/59e06b6c5ca66597852575e700

6c5d09!OpenDocument&TableRow=2.3#2.>. 

151 National Research Council (NRC). 2008. Estimating Mortality Risk Reduction and Economic Benefits from 

Controlling Ozone Air Pollution. National Academies Press. Washington, DC. 

152 Mansfield, Carol; Paramita Sinha; Max Henrion. 2009. Influence Analysis in Support of Characterizing 

Uncertainty in Human Health Benefits Analysis: Final Report. Prepared for U.S. EPA, Office of Air Quality 

Planning and Standards. November. Available on the internet at 

<http://www.epa.gov/ttn/ecas/regdata/Benefits/influence_analysis_final_report_psg.pdf>. 

153 U.S. Environmental Protection Agency Science Advisory Board (U.S. EPA-SAB). 2010. Review of EPA’s 

DRAFT Health Benefits of the Second Section 812 Prospective Study of the Clean Air Act. EPA-COUNCIL-10-

001. June. Available on the Internet at 

<http://yosemite.epa.gov/sab/sabproduct.nsf/9288428b8eeea4c885257242006935a3/59e06b6c5ca66597852575e700

6c5d09!OpenDocument&TableRow=2.3#2.>. 

154 National Research Council (NRC). 2002. Estimating the Public Health Benefits of Proposed Air Pollution 

Regulations. Washington, DC: The National Academies Press. Washington, DC. 

155 U.S. Environmental Protection Agency (U.S. EPA). 2009. Integrated Science Assessment for Particulate Matter 

(Final Report). EPA-600-R-08-139F. National Center for Environmental Assessment—RTP Division. December. 

Available on the Internet at <http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=216546>. 

156 U.S. Environmental Protection Agency—Science Advisory Board (U.S. EPA-SAB). 2004. Advisory Council on 

Clean Air Compliance Analysis Response to Agency Request on Cessation Lag. EPA-COUNCIL-LTR-05-001. 

December. Available on the Internet at 

<http://yosemite.epa.gov/sab/sabproduct.nsf/0/39F44B098DB49F3C85257170005293E0/$File/council_ltr_05_001.

pdf>. 

157 World Health Organization (WHO). 2008. Part 1: Guidance Document on Characterizing and Communicating 

Uncertainty in Exposure Assessment, Harmonization Project Document No. 6. Published under joint sponsorship of 

the World Health Organization, the International Labour Organization and the United Nations Environment 

Programme. WHO Press: Geneva, Switzerland. Available on the Internet at 

<www.who.int/ipcs/methods/harmonization/areas/uncertainty%20.pdf>. 

158 U.S. Environmental Protection Agency (U.S. EPA). 2010. Quantitative Health Risk Assessment for Particulate 

Matter—Final Report. EPA-452/R-10-005. Office of Air Quality Planning and Standards, Research Triangle Park, 

NC. September. Available on the Internet at 

<http://www.epa.gov/ttnnaaqs/standards/pm/data/PM_RA_FINAL_June_2010.pdf>. 

159 U.S. Environmental Protection Agency (U.S. EPA). 2011. The Benefits and Costs of the Clean Air Act 1990 to 

2020: EPA Report to Congress. Office of Air and Radiation, Office of Policy, Washington, DC. March. Available 

on the Internet at <http://www.epa.gov/oar/sect812/feb11/fullreport.pdf>. 

160 U.S. Environmental Protection Agency. (2012). Regulatory Impact Analysis for the Final Revisions to the 

National Ambient Air Quality Standards for Particulate Matter. Prepared by: Office of Air and Radiation, EPA452/R-12-005. Retrieved November 22, 2013 at http://www.epa.gov/ttn/ecas/ria.html. 
9-1

Chapter 9 Economic Impact Analysis 

9.1 Introduction 

The standards will affect two sectors directly: vehicle manufacturing and petroleum 

refining. For these two regulated sectors, the economic impact analysis discusses the market 

impacts from the standards: the changes in price and quantity sold. In addition, although 

analysis of employment impacts is not part of a benefit-cost analysis (except to the extent that 

labor costs contribute to costs), employment impacts of federal rules are of particular concern in 

the current economic climate of sizeable unemployment. Executive Order 13563, “Improving 

Regulation and Regulatory Review” (January 18, 2011), states, “Our regulatory system must 

protect public health, welfare, safety, and our environment while promoting economic growth, 

innovation, competitiveness, and job creation” (emphasis added). For this reason, we are 

examining the effects of these standards on employment in the regulated sectors. 

The employment effects of environmental regulation are difficult to disentangle from 

other economic changes and business decisions that affect employment, over time and across 

regions and industries. In light of these difficulties, economic theory provides a constructive 

framework for approaching these assessments and for better understanding the inherent 

complexities in such assessments. Neoclassical microeconomic theory describes how profitmaximizing firms adjust their use of productive inputs in response to changes in their economic 

conditions.A In this framework, labor demand impacts for regulated sectors can be decomposed 

into output and substitution effects. For the output effect, by affecting the marginal cost of 

production, regulation affects the profit-maximizing quantity of output. The substitution effect 

describes how, holding output constant, regulation affects the labor-intensity of production. 

Because the output and substitution effects may be both positive, both negative or some 

combination, standard neoclassical theory alone does not point to a definitive net effect of 

regulation on labor demand at regulated firms. 

In the labor economics literature there is an extensive body of peer-reviewed empirical 

work analyzing various aspects of labor demand, relying on the above theoretical framework.B

This work focuses primarily on the effects of employment policies, e.g. labor taxes, minimum 

wage, etc.C

 In contrast, the peer-reviewed empirical literature specifically estimating 

employment effects of environmental regulations is very limited. Several empirical studies, 

including Berman and Bui (2001)1and Morgenstern et al (2002),2suggest that net employment 

impacts may be zero or slightly positive but small even in the regulated sector. Other research 

suggests that more highly regulated counties may generate fewer jobs than less regulated ones.3

However, since these latter studies compare more regulated to less regulated counties, they 

 

A

 See Layard, P.R.G., and A. A. Walters (1978), Microeconomic Theory (McGraw-Hill, Inc.), Chapter 9 (Docket 

EPA-HQ-OAR-2011-0135), a standard microeconomic theory textbook treatment, for a discussion. 

B

 See Hamermesh (1993), Labor Demand (Princeton, NJ: Princeton University Press), Chapter 2 (Docket EPA-HQOAR-2011-0135) for a detailed treatment. 

C

 See Ehrenberg, Ronald G., and Robert S. Smith (2000), Modern Labor Economics: Theory and Public Policy 

(Addison Wesley Longman, Inc.), Chapter 4 (Docket EPA-HQ-OAR-2011-0135), for a concise overview. 
9-2

overstate the net national impact of regulation to the extent that regulation causes plants to locate 

in one area of the country rather than another. List et al. (2003)4find some evidence that this type 

of geographic relocation may be occurring. Overall, the peer-reviewed literature does not contain 

evidence that environmental regulation has a large impact on net employment (either negative or 

positive) in the long run across the whole economy. 

Analytic challenges make it very difficult to accurately produce net employment 

estimates for the whole economy that would appropriately capture the way in which costs, 

compliance spending, and environmental benefits propagate through the macro-economy. 

Quantitative estimates are further complicated by the fact that macroeconomic models often have 

very little sectoral detail and usually assume that the economy is at full employment. The EPA is 

currently in the process of seeking input from an independent expert panel on modeling 

economy-wide impacts, including employment effects. For more information, see: 

https://federalregister.gov/a/2014-02471.

9.2 Impacts on Vehicle Manufacturing Sector 

9.2.1 Vehicle Sales Impacts 

This rule takes effect from MY 2017-2025. In the intervening years, it is possible that the 

assumptions underlying a quantitative analysis, as well as market conditions, might change. For 

this reason, we present a qualitative discussion of the effects on vehicle sales of the standards at 

the aggregate market level. Light-duty vehicle manufacturers are expected to comply with the 

standards primarily through technological changes to vehicles. These changes to vehicle design 

and manufacturing are expected to increase manufacturers’ costs of vehicle production. The 

calculation is performed for an average car, an average truck and an average Class 2b/3 vehicle 

rather than for individual vehicles. The analysis conducted for this rule does not have the 

precision to examine effects on individual manufacturers or different vehicle classes. 

Section VII.A estimates the increase in vehicle costs due to the standards. These costs 

differ across years and range from $46 to $65 for cars, $73 to $88 for trucks and $33 to $75 for 

Class 2b/3 vehicles (see Section VII.A). These costs are small relative to the cost of a vehicle. 

In a fully competitive industry, these costs would be entirely passed through to consumers. 

However in an oligopolistic industry such as the automotive sector, these increases in cost may 

not fully pass through to the purchase price, and the consumers may face an increase in price that 

is less than the increased manufacturers’ costs of vehicle production.D We do not quantify the 

expected level of cost pass-through or the ultimate vehicle price increase consumers are expected 

to face, apart from noting that prices are expected to increase by an amount up to the increased 

manufacturers’ costs. 

 

D

 See, for instance, Gron, Ann, and Deborah Swenson, 2000. “Cost Pass-Through in the U.S. Automobile Market,” 

Review of Economics and Statistics 82: 316-324 (Docket EPA-HQ-OAR-2011-0135-0056), who found significantly 

less than full-cost pass-through using data from 1984-1994. Using full-cost pass-through overstates costs and thus 

contributes to lower vehicle sales than using a lower estimate. To the extent that the auto industry has become more 

competitive over time, full-cost pass-through may be more appropriate than a result based on this older study. 
9-3

This increase in price is expected to lower the quantity of vehicles sold. Given that we 

expect that vehicle prices will not change by more than the cost increase, we expect that the 

decrease in vehicle sales will be negligible. 

The effect of these standards on the use and scrappage of older vehicles will be related to 

its effects on new vehicle prices and the total sales of new vehicles. The increase in price is 

likely to cause the turnover of the vehicle fleet (i.e., the retirement of used vehicles and their 

replacement by new models) to slow slightly, thus reducing the anticipated effect of the 

standards on fleet-wide emissions. Because we do not estimate the effect of the standards on 

new vehicle price changes nor do we have a good estimate of the effect of new vehicle price 

changes on vehicle turnover, we have not attempted to estimate explicitly the effects of the 

standards on scrappage of older vehicles and the turnover of the vehicle fleet. 

9.2.2 Employment Impacts in the Auto Sector 

This chapter describes changes in employment in the auto sector due to this rule. As with 

the refinery sector, discussed below, we focus on the auto manufacturing sector because it is 

directly regulated, and because it is likely to bear a substantial share of changes in employment 

due to this rule. We include discussion of effects on the parts manufacturing sector, because the 

auto manufacturing sector can either produce parts internally or buy them from an external 

supplier, and we do not have estimates of the likely breakdown of effort between the two sectors. 

When the economy is at full employment, an environmental regulation is unlikely to have 

much impact on net overall U.S. employment; instead, labor would primarily be shifted from one 

sector to another. These shifts in employment impose an opportunity cost on society, 

approximated by the wages of the employees, as regulation diverts workers from other activities 

in the economy. In this situation, any effects on net employment are likely to be transitory as 

workers change jobs (e.g., some workers may need to be retrained or require time to search for 

new jobs, while shortages in some sectors or regions could bid up wages to attract workers). 

On the other hand, if a regulation comes into effect during a period of high 

unemployment, a change in labor demand due to regulation may affect net overall U.S. 

employment because the labor market is not in equilibrium. Schmalansee and Stavins point out 

that net positive employment effects are possible in the near term when the economy is at less 

than full employment due to the potential hiring of idle labor resources by the regulated sector to 

meet new requirements (e.g., to install new equipment) and new economic activity in sectors 

related to the regulated sector.5 In the longer run, the net effect on employment is more difficult 

to predict and will depend on the way in which the related industries respond to the regulatory 

requirements. As Schmalansee and Stavins note, it is possible that the magnitude of the effect on 

employment could vary over time, region, and sector, and positive effects on employment in 

some regions or sectors could be offset by negative effects in other regions or sectors. For this 

reason, they urge caution in reporting partial employment effects since it can “paint an inaccurate 

picture of net employment impacts if not placed in the broader economic context.” 

We follow the theoretical structure in a study by Berman and Bui 6of the impacts of 

regulation in employment in the regulated sectors. In Berman and Bui’s (2001, p. 274-75) 
9-4

theoretical model, the change in a firm’s labor demand arising from a change in regulation is 

decomposed into two main components: output and substitution effects.E

The output effect describes how, if labor-intensity of production is held constant, a 

decrease in output generally leads to a decrease in labor demand. However, as noted by 

Berman and Bui, although it is often assumed that regulation increases marginal cost, and 

thereby reduces output, it need not be the case. A regulation could induce a firm to 

upgrade to less polluting and more efficient equipment that lowers marginal production 

costs, for example. In such a case, output could theoretically increase. 

The substitution effect describes how, holding output constant, regulation affects the 

labor-intensity of production. Although increased environmental regulation generally 

results in higher utilization of production factors such as pollution control equipment and 

energy to operate that equipment, the resulting impact on labor demand is ambiguous. 

For example, equipment inspection requirements, specialized waste handling, or pollution 

technologies that are added to the production process may affect the number of workers 

necessary to produce a unit of output. Berman and Bui (2001) model the substitution 

effect as the effect of regulation on pollution control equipment and expenditures that are 

required by the regulation and the corresponding change in labor-intensity of production. 

In summary, as the output and substitution effects may be both positive, both negative or 

some combination, standard neoclassical theory alone does not point to a definitive net effect of 

regulation on labor demand at regulated firms. 

Following the Berman and Bui framework for the impacts of regulation on employment 

in the regulated sector, we consider two effects for the auto sector: the output effect and the 

substitution effect. 

9.2.2.1 The Output Effect 

The output effect depends on the effects of this rule on vehicle sales. If vehicle sales 

decrease, employment associated with these activities will decrease. As discussed in Chapter 

9.2.1, we do not make a quantitative estimate on the effect of the rule on vehicle sales, but we 

note that the decrease in vehicle sales is expected to be negligible. Thus we expect any decrease 

in employment in the auto sector through the output effect to be small as well. 

 

E

 The authors also discuss a third component, the impact of regulation on factor prices, but conclude that this effect 

is unlikely to be important for large competitive factor markets, such as labor and capital. Morgenstern, Pizer and 

Shih (2002) use a very similar model, but they break the employment effect into three parts: 1) the demand effect; 2) 

the cost effect; and 3) the factor-shift effect. See Morgenstern, Richard D., William A. Pizer, and Jhih-Shyang Shih. 

“Jobs Versus the Environment: An Industry-Level Perspective.” Journal of Environmental Economics and 

Management 43 (2002): 412-436 (Docket EPA-HQ-OAR-2011-0135-0057). 
9-5

9.2.2.2 The Substitution Effect 

The output effect, above, measures the effect due to new vehicle sales only. The 

substitution effect includes the impacts due to the changes in technologies needed for vehicles to 

meet the standards, separate from the effect on output (that is, as though holding output 

constant). This effect includes both changes in employment due to incorporation of abatement 

technologies and overall changes in the labor intensity of manufacturing. 

One way to estimate this effect, given the cost estimates for complying with the rule, is to 

use the ratio of workers to each $1 million of expenditures in that sector. The use of these ratios 

has both advantages and limitations. It is often possible to estimate these ratios for quite specific 

sectors of the economy: for instance, it is possible to estimate the average number of workers in 

the light-duty vehicle manufacturing sector per $1 million spent in the sector, rather than use the 

ratio from another, more aggregated sector, such as motor vehicle manufacturing. As a result, it 

is not necessary to extrapolate employment ratios from possibly unrelated sectors. On the other 

hand, these estimates are averages for the sectors, covering all the activities in those sectors; they 

may not be representative of the labor required when expenditures are required on specific 

activities, or when manufacturing processes change sufficiently that labor intensity changes. For 

instance, the ratio for the motor vehicle manufacturing sector represents the ratio for all vehicle 

manufacturing, not just for emissions reductions associated with compliance activities. In 

addition, these estimates do not include changes in sectors that supply these sectors, such as steel 

or electronics producers. They thus may best be viewed as the effects on employment in the auto 

sector due to the changes in expenditures in that sector, rather than as an assessment of all 

employment changes due to these changes in expenditures. In addition, this approach estimates 

the effects of increased expenditures while holding constant the labor intensity of manufacturing; 

it does not take into account changes in labor intensity due to changes in the nature of 

production. This latter effect could either increase or decrease the employment impacts 

estimated here.F

Some of the costs of this rule will be spent directly in the auto manufacturing sector, but 

it is also likely that some of the costs will be spent in the auto parts manufacturing sector. We 

separately present the ratios for both the auto manufacturing sector and the auto parts 

manufacturing sector. 

There are several public sources for estimates of employment per $1 million 

expenditures. The U.S. Bureau of Labor Statistics (BLS) provides its Employment 

Requirements Matrix (ERM),7 which provides direct estimates of the employment per $1 million 

in sales of goods in 202 sectors. The values considered here are for Motor Vehicle 

Manufacturing (NAICS 3361) and Motor Vehicle Parts Manufacturing (NAICS 3363) for 2010. 

The Census Bureau provides both the Annual Survey of Manufacturers8(ASM) and the 

Economic Census. The ASM is a subset of the Economic Census, based on a sample of 

 

F

 As noted above, Morgenstern et al. (2002) separate the effect of holding output constant into two effects: the cost 

effect, which holds labor intensity constant, and the factor shift effect, which estimates those changes in labor 

intensity. 
9-6

establishments; though the Census itself is more complete, it is conducted only every 5 years, 

while the ASM is annual. Both include more sectoral detail than the BLS ERM: for instance, 

while the ERM includes the Motor Vehicle Manufacturing sector, the ASM and Economic 

Census have detail at the 6-digit NAICS code level (e.g., light truck and utility vehicle 

manufacturing). While the ERM provides direct estimates of employees/$1 million in 

expenditures, the ASM and Economic Census separately provide number of employees and 

value of shipments; the direct employment estimates here are the ratio of those values. The 

values reported are for Motor Vehicle Manufacturing (NAICS 3361), Automobile and Light 

Duty Motor Vehicle Manufacturing (NAICS 33611), and Motor Vehicle Parts Manufacturing 

(NAICS 3363), for 2011 for the ASM, and 2007 for the Economic Census. 

The values used here are adjusted to remove the employment effects of imports through 

use of a ratio of domestic production to domestic sales of 0.667.G 

Table 9-1 provides the values, either given (BLS) or calculated (ASM, Economic Census) 

for employment per $1 million of expenditures, all based on 2011 dollars, though the underlying 

data come from different years (which may account for some of the differences). These values 

have changed from the Draft RIA to use the most recent values for the ASM, and to put them all 

in 2011$. The different data sources provide similar magnitudes for the estimates for the sectors. 

Parts manufacturing appears to be more labor-intensive than vehicle manufacturing; light-duty 

vehicle manufacturing appears to be slightly less labor-intensive than motor vehicle 

manufacturing as a whole. 

Table 9-1 Employment per $1 Million Expenditures (2011$) in the Motor Vehicle 

Manufacturing Sectora

Source Sector

Ratio of workers 

per $1 million 

expenditures

Ratio of workers per $1 

million expenditures, 

adjusted for domestic vs. 

foreign production

BLS ERM Motor Vehicle Mfg 0.754 0.503

ASM Motor Vehicle Mfg 0.633 0.422

ASM Light Duty Vehicle Mfg 0.583 0.389

Economic Census Motor Vehicle Mfg 0.651 0.434

Economic Census Light Duty Vehicle Mfg 0.590 0.393

BLS ERM Motor Vehicle Parts Mfg 2.558 1.706

ASM Motor Vehicle Parts Mfg 2.190 1.461

Economic Census Motor Vehicle Parts Mfg 2.656 1.771

Note: 

 

G

 To estimate the proportion of domestic production affected by the change in sales, we use data from Ward’s 

Automotive Group for total car and truck production in the U.S. compared to total car and truck sales in the U.S. 

For the period 2001-2010, the proportion is 66.7 percent (Docket EPA-HQ-OAR-2011-0135). 
9-7

a BLS ERM refers to the U.S. Bureau of Labor Statistics’ Employment Requirement Matrix. ASM refers to 

the U.S. Census Bureau’s Annual Survey of Manufactures. Economic Census refers to the U.S. Census 

Bureau’s Economic Census.

Over time, the amount of labor needed in the auto industry has changed: automation and 

improved methods have led to significant productivity increases. The BLS ERM, for instance, 

provided estimates that, in 1993, 1.64 workers in the Motor Vehicle Manufacturing sector were 

needed per $1 million of 2005$, but only 0.86 workers by 2010 (in 2005$).9

 Because the ERM 

is available annually for 1993-2010, we used these data to estimate productivity improvements 

over time. We regressed logged ERM values on year for both the Motor Vehicle Manufacturing 

and Motor Vehicle Parts Manufacturing sectors. We used this approach because the coefficient 

describing the relationship between time and productivity is a direct measure of the percent 

change in productivity per year. The results suggest a 3.9 percent per year productivity 

improvement in the Motor Vehicle Manufacturing Sector, and a 3.8 percent per year 

improvement in the Motor Vehicle Parts Manufacturing Sector. We then used the equation 

resulting from the regression to project the ERM through 2025. In the results presented below, 

these projected values (adjusted to 2011$) were used directly for the BLS ERM estimates. For 

the ASM, we used the ratio of the projected value in each future year to the projected value in 

2011 (the base year for the ASM) to determine how many workers will be needed per $1 million 

of 2011$; for the Economic Census estimates, we used the ratio of the projected value in the 

future years to the projected value in 2007 (the base year for that estimate). 

Section 2.7 of the RIA discusses the vehicle cost estimates developed for this rule. The 

maximum value for employment impacts per $1 million (before adjustments for changes in 

productivity, after accounting for the share of domestic production) is 1.771 in 2011$ if all the 

additional costs are in the parts sector; the minimum value is 0.389 in 2011, if all the additional 

costs are in the light-duty vehicle manufacturing sector. Increased costs of vehicles and parts 

would, by itself, and holding labor intensity constant, be expected to increase employment 

between 2017 and 2025 by some hundreds of jobs each year. 

While we estimate employment impacts, measured in job-years, beginning with program 

implementation, some of these employment gains may occur earlier as auto manufacturers and 

parts suppliers hire staff in anticipation of compliance with the standard. A job-year is a way to 

calculate the amount of work needed to complete a specific task. For example, a job-year is one 

year of work for one person. The decline in maximum employment between 2024 and 2025 is 

due to a combination of expected higher productivity and rounding, which makes an employment 

decrease from 760 to 743 job-years appear larger than it is. 

Table 9-2 Employment Effects due to Increased Costs of Vehicles and Parts, in job-years 

Year Costs (Millions 

of 2011$)

Maximum Employment Due to 

Substitution Effect (if all 

expenditures are in the Parts 

Sector)

Minimum Employment Due to 

Substitution Effect (if all 

expenditures are in the Light Duty 

Vehicle Mfg Sector)

2016 $ 21 0 0 

2017 $ 297 400 100 

2018 $ 615 800 200 

2019 $ 653 800 200 
9-8

2020 $ 697 800 200 

2021 $ 725 800 200 

2022 $ 758 800 200 

2023 $ 751 800 200 

2024 $ 761 800 200 

2025 $ 773 700 200 

9.2.2.3 Summary of Employment Effects in the Auto Sector 

The overall effect of the rule on auto sector employment depends on the relative 

magnitude of the output effect and the substitution effect. Because we do not have quantitative 

estimates of the output effect, and only a partial estimate of the substitution effect, we cannot 

reach a quantitative estimate of the overall employment effects of the rule on auto sector 

employment or even whether the total effect will be positive or negative. However, given that 

the expected increase in production costs to the auto manufacturers is relatively small, we expect 

that the magnitudes of all effects combined will be small as well. 

The standards are not expected to provide incentives for manufacturers to shift 

employment between domestic and foreign production. This is because the standards will apply 

to vehicles sold in the U.S. regardless of where they are produced. If foreign manufacturers 

already have increased expertise in satisfying the requirements of the standards, there may be 

some initial incentive for foreign production, but the opportunity for domestic manufacturers to 

sell in other markets might increase. To the extent that the requirements of this rule might lead 

to installation and use of technologies that other countries may seek now or in the future, 

developing this capacity for domestic production now may provide some additional ability to 

serve those markets. This potential benefit will not apply if other countries are not likely to have 

similar standards. 

9.3 Impacts on Petroleum Refinery Sector 

9.3.1 Refinery Sales Impacts 

The key change for refiners from the standards will be more stringent sulfur 

requirements. This change to fuels is expected to increase manufacturers’ costs of gasoline 

production by about 0.7 cents per gallon (see Section VII.B of the Preamble). 

In a perfectly competitive industry, this cost would be passed along completely to 

consumers. In an imperfectly competitive industry, as noted above, full cost pass-through is not 

necessary: firms may choose to reduce impacts on sales by not passing along full costs. In 2004, 

the Federal Trade Commission reported that “concentration for most levels of the petroleum 

industry has remained low to moderate.”10

 Thus the assumption of competitive markets has 

some foundation in this industry. We estimate that the price increase that consumers are likely to 

face should be positive and up to the increase in manufacturers’ costs of gasoline production. 

The effect of higher gasoline prices on gasoline sales is expected to be different over the 

short and long term. In the long run, in response to the increase in fuel costs, consumers can 

more easily change their driving habits, including where they live or what vehicles they use. 
9-9

Because of this, we expect that gasoline sales will decrease more in the long run compared to the 

short run as a result of the price increase due to the rule. However, because manufacturers’ costs 

are expected to increase less than one cent per gallon, we expect that the decrease in gasoline 

sales will be negligible over all time horizons. 

9.3.2 Refinery Employment Impacts 

The Berman and Bui framework of output and substitution effects can also be applied to 

the impact of the rule on employment in the refinery sector.11 Here we use a fully qualitative 

approach. A qualitative discussion allows for a wider incorporation of additional considerations, 

such as timing of impacts and the effects of the rule on imports and exports. Because the 

discussion is qualitative, we do not sum the net effects on employment. 

The output effect on refining sector employment is expected to be negative. The 

discussion in Chapter 9.3.1 above suggests that the standards will cause a small decrease in the 

quantity of gasoline demanded due to higher production costs being passed through to 

consumers. This slightly reduced level of sales will likely have a negative impact on 

employment in the refining sector. This effect will persist as long as the increase in price is in 

place. The higher long-run elasticity suggests that sales will be lower in the long run than in the 

short run, leading to a greater reduction in employment due to the output effect over time. While 

we do not quantify the level of job losses that are expected here, recall that the quantity of 

gasoline sold as a result of the standards here is expected to decrease by only a very small 

amount over any time horizon. 

The substitution effect of the rule on employment in the refining sector can be either 

positive or negative in the Berman and Bui framework; here, we expect a small, possibly positive 

impact. In order to satisfy the requirements of the rule, firms in the refining industry are 

expected to need to perform additional work that will require hiring more employees. This effect 

may be larger in the short run, when initial investments for compliance need to be made; over 

time, the increase in employment due to these investments may be reduced. Chapter 4.5.1 

discusses the expected employment needed to reduce the sulfur content of fuels; as noted there, 

to meet the Tier 3 sulfur standards, refiners are expected to invest $2 billion between 2012 and 

2019 and utilize approximately 250 front-end design and engineering jobs and 15000 

construction jobs. As the petroleum sector employed approximately 71,000 workers in 2011, 

this increase in employment is small when compared to 2011 levels. 

These standards are not expected to provide incentives to shift employment between 

domestic and foreign production. First, the standards apply to gasoline sold in the U.S. 

regardless of where it has been produced. U.S. gasoline demand is projected to continue to 

decline for the foreseeable future in response to higher gasoline prices, more stringent vehicle 

and engine greenhouse gas and fuel economy standards as well as increased use of renewable 

fuels. As a result, this analysis of incentives to shift employment between domestic and foreign 

production focuses on investments for existing capacity instead of expanding capacity.H In this 

 

H

 While refinery capacity has been increasing around the world in recent years, it has been designed primarily to 

supply foreign markets other than the U.S. (e.g., increasing demand in China and India). 
9-10

case, what is relevant is whether the necessary modifications to comply with Tier 3 would be 

significantly cheaper overseas than in the U.S. 

The main impacts on capital and operating costs to comply with Tier 3 associated with 

adding hydrotreating capacity are likely to be similar overseas as in the U.S. This is particularly 

true when analyzing likely sources of U.S. imports. The majority of gasoline imported to the 

U.S. today comes into the East Coast and is sourced out of either Europe or refineries in Canada 

or the Caribbean that exist almost solely to supply the U.S. market. 

These Canadian and Caribbean refineries, by virtue of their focus on the U.S. market, are 

very similar to U.S.-based refineries and are expected to have to incur similar capital and 

operating costs as their U.S.-based competitors meeting the 10-ppm standard. Furthermore, the 

European refineries are already producing gasoline to a 10-ppm sulfur cap for Europe. To the 

extent they have refinery streams that are more difficult to hydrotreat, the U.S. market currently 

serves as an outlet for their higher sulfur gasoline streams. As a result, they may incur capital and 

operating costs on a per gallon basis at least as high as for their U.S.-based competitors for these 

remaining higher sulfur gasoline streams. Alternatively, they may instead choose to find markets 

outside the U.S., opening the way for increased U.S.-based refinery demand. 

Finally, despite refining industry projections that previously imposed diesel rules would 

lead to greater U.S. reliance on imports through major negative impacts on domestic refining, the 

reverse has actually occurred. Over the last 8 years, imports of gasoline and diesel fuel have 

continued to be the marginal supply, and have even dropped precipitously so that the U.S. is now 

a net exporter of diesel fuel and is importing half the gasoline that it did at its peak in 2006. 

With the projected decline in future gasoline demand in the U.S. as vehicle fuel efficiency 

improves, gasoline imports are expected to continue to decline. 

Thus it is expected that for the refining sector, the output effect will lower employment, 

and the substitution effect may raise employment. As a whole then, it is not evident whether the 

rule will increase or decrease employment in the refining sector. However, given the small 

anticipated reduction in quantity sold, it appears that the standards will not have major 

employment consequences for this sector. 

The petroleum refining industry is one of the manufacturing industries studied by Berman 

and Bui (2001)7 when they looked at the effect of environmental expenditures on employment. 

They found that “Employment effects are very small, generally positive, but not statistically 

different from zero” (p. 281) [Berman and Bui, Table 3]. Berman and Bui also state that the 

estimates rule out large negative effects (p. 282). Because most of the abatement cost of the 

regulations they analyze is incurred by refineries, in their sample, they report separate 

employment effects for refineries and non-refineries “which are also all small.” (p. 282). Berman 

and Bui suggest some explanations for the zero or small estimates, particularly for oil refineries: 

they are capital-intensive industries with relatively little employment when compared to other 

manufacturing; they face relatively inelastic demand because they sell output in local markets 

and/or because there are no unregulated refineries to compete with; and, finally, regulations may 

have been associated with productivity gains in petroleum refineries. We note that the 

regulations that these estimate are derived from are not directly comparable to the current rule; it 
9-11

is based on the costs of reductions in refinery air pollution emissions instead of changing fuel 

properties, and therefore may not be applicable for the standards here. 

Section VII.B.5 of the Preamble contains some historical discussion regarding the impact 

on refineries and refining capacity of earlier rules which resulted in higher costs for refiners. 

Over the period 2003-2011, when a number of rules were being implemented, EIA data show a 

net of two refinery closures on its website. Meanwhile, over this same period the average size of 

U.S. refineries increased from 113,000 barrels per day to 123,000 barrels per day, and total U.S. 

refining capacity increased by six percent. Thus, historically during a time when rules with 

much larger expected impacts were being implemented (the 2003 ultra-low sulfur nonroad diesel 

proposal alone was expected to have a cost impact on refineries more than five times greater than 

the current rule), U.S. refining capacity increased even as the number of U.S. refineries slightly 

fell. While closing refineries has a negative effect on industry employment, it is likely that the 

increased refining capacity at many of the remaining plants had a positive effect on industry 

employment. 

The standards are also likely to have a positive impact on employment among producers 

of equipment that refiners will use to comply with the standards. Chapter 5 notes that some 

refiners are expected to revamp their current treatment units, and others will need to add 

additional treatment units. Producers of this equipment are expected to hire additional labor to 

meet this increased demand. We also note that the employment effects may be different in the 

immediate implementation phase than in the ongoing compliance phase. It is expected that the 

employment increases through the substitution effect from revamping old equipment and 

installing additional equipment should occur in the near term, when current unemployment levels 

are high, and the opportunity cost of workers is relatively low. Meanwhile, the employment 

decreases in the refining sector from the output effect will not start until 2017, when compliance 

is required, and when unemployment is expected to be reduced; in a time of full employment, 

any changes in employment levels in the regulated sector are mostly expected to be offset by 

changes in employment in other sectors. 
9-12

References 

1Berman, E. and L. T. M. Bui (2001). “Environmental Regulation and Labor Demand: Evidence from the South 

Coast Air Basin.” Journal of Public Economics 79(2): 265-295 (Docket EPA-HQ-OAR-2011-0135). 

2Morgenstern, Richard D., William A. Pizer, and Jhih-Shyang Shih. “Jobs Versus the Environment: An IndustryLevel Perspective.” Journal of Environmental Economics and Management 43 (2002): 412-436 (Docket EPA-HQOAR-2011-0135-0057). 

3

 Greenstone, M. (2002). “The Impacts of Environmental Regulations on Industrial Activity: Evidence from the 

1970 and 1977 Clean Air Act Amendments and the Census of Manufactures,” Journal of Political Economy 110(6): 

1175-1219 (Docket EPA-HQ-OAR-2011-0135); Walker, Reed. (2011).“Environmental Regulation and Labor 

Reallocation." American Economic Review: Papers and Proceedings 101(3): 442-447 (Docket EPA-HQ-OAR2011-0135). 

4List, J. A., D. L. Millimet, P. G. Fredriksson, and W. W. McHone (2003). “Effects of Environmental Regulations 

on Manufacturing Plant Births: Evidence from a Propensity Score Matching Estimator.” The Review of Economics 

and Statistics 85(4): 944-952 (Docket EPA-HQ-OAR-2011-0135). 

5

 Schmalensee, Richard, and Robert N. Stavins. “A Guide to Economic and Policy Analysis of EPA’s Transport 

Rule.” White paper commissioned by Excelon Corporation, March 2011 (Docket EPA-HQ-OAR-2011-0135-0054). 

6Berman, E. and L. T. M. Bui (2001). “Environmental Regulation and Labor Demand: Evidence from the South 

Coast Air Basin.” Journal of Public Economics 79(2): 265-295 (Docket EPA-HQ-OAR-2011-0135). 

7

 http://www.bls.gov/emp/ep_data_emp_requirements.htm. 

8

 http://www.census.gov/manufacturing/asm/index.html. 

9

 http://www.bls.gov/emp/ep_data_emp_requirements.htm; this analysis used data for sectors 88 (Motor Vehicle 

Manufacturing) and 90 (Motor Vehicle Parts Manufacturing) from “Chain-weighted (2000 dollars) real domestic 

employment requirements table. . . adjusted to remove imports.” 

10 Federal Trade Commission, Bureau of Economics. “The Petroleum Industry: Mergers, Structural Change, and 

Antitrust Enforcement.” http://www.ftc.gov/os/2004/08/040813mergersinpetrolberpt.pdf , accessed 8/16/11 (Docket 

EPA-HQ-OAR-2011-0135-0055). 

11 Berman, E. and L. T. M. Bui (2001). “Environmental Regulation and Labor Demand: Evidence from the South 

Coast Air Basin.” Journal of Public Economics 79(2): 265-295 (Docket EPA-HQ-OAR-2011-0135). 
10-1

Chapter 10 Final Regulatory Flexibility Analysis 

10.1 Introduction 

This chapter discusses our Final Regulatory Flexibility Analysis (FRFA) which evaluates 

the potential impacts of the proposed standards on small entities. The Regulatory Flexibility Act, 

as amended by the Small Business Regulatory Enforcement Fairness Act of 1996 (SBREFA), 

generally requires an agency to prepare a regulatory flexibility analysis of any rule subject to 

notice and comment rulemaking requirements 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. Prior to issuing a proposal for this rulemaking, we 

analyzed the potential impacts of these regulations on small entities. As a part of this analysis, 

we convened a Small Business Advocacy Review Panel (SBAR Panel, or ‘the Panel’). During 

the Panel process, we gathered information and recommendations from Small Entity 

Representatives (SERs) on how to reduce the impact of the rule on small entities, and those 

comments are detailed in the Final Panel Report which is located in the public record for this 

rulemaking (Docket ID Number EPA-HQ-OAR-2011-0135-0423).Pursuant to this requirement, 

we have prepared an IRFA for the proposed rule. Throughout the process of developing the 

IRFA, we conducted outreach and held meetings with representatives from the various small 

entities that could be affected by the rulemaking to gain feedback, including recommendations, 

on how to reduce the impact of the rule on these entities. The small business recommendations 

stated here reflect the comments of the small entity representatives (SERs) and members of the 

Small Business Advocacy Review Panel (SBAR Panel, or ‘the Panel’). 

10.2 Overview of the Regulatory Flexibility Act 

In accordance with section 609(b) of the Regulatory Flexibility Act, we convened an 

SBAR Panel before conducting the FRFA. A summary of the Panel’s recommendations is 

presented in the preamble to the proposed rule. Further, a detailed discussion of the Panel’s 

advice and recommendations (as well as comments from the Small Entity Representatives) can 

be found in the Final Panel Report contained in the docket for this proposed rulemaking.1 The 

regulatory alternatives that are being adopted in the final rule are described below. 

Section 609(b) of the Regulatory Flexibility Act further directs the Panel to report on the 

comments of small entity representatives and make findings on issues related to identified 

elements of the Regulatory Flexibility Analysis under section 603 of the Regulatory Flexibility 

Act. Key elements of a Regulatory Flexibility Analysis are: 

A description of and, where feasible, an estimate of the number of small entities to 

which the rule will apply; 

Projected reporting, recordkeeping, and other compliance requirements of the rule, 

including an estimate of the classes of small entities which will be subject to the 

requirements and the type of professional skills necessary for preparation of the report 

or record;
10-2

An identification to the extent practicable, of all other relevant Federal rules which 

may duplicate, overlap, or conflict with the rule; 

Any significant alternatives to the rule which accomplish the stated objectives of 

applicable statutes and which minimize any significant economic impact of the rule 

on small entities. 

The Regulatory Flexibility Act was amended by SBREFA to ensure that concerns 

regarding small entities are adequately considered during the development of new regulations 

that affect those entities. Although we are not required by the Clean Air Act to provide special 

treatment to small businesses, the Regulatory Flexibility Act requires us to carefully consider the 

economic impacts that our rules will have on small entities. The recommendations made by the 

Panel may serve to help lessen these economic impacts on small entities when consistent with 

Clean Air Act requirements. 

10.3 Need for the Rulemaking and Rulemaking Objectives 

A detailed discussion on the need for, and objectives of, this rule are located in the 

preamble to the final rule. As presented in Chapter 9 of this RIA, controlling exhaust and 

evaporative emissions from light-duty vehicles and trucks and complete heavy-duty vehicles and 

reducing sulfur levels in gasoline have important public health and welfare benefits. Further, as 

discussed in Section II of the preamble to the final rule, section 202 of the Clean Air Act 

(specifically, sections 202(a) and (k)) authorizes EPA to establish emissions standards for motor 

vehicles to address air pollution that may reasonably be anticipated to endanger public health or 

welfare. EPA also has authority to establish fuel controls to address such air pollution under 

section 211(c) of the Clean Air Act. Emissions from motor vehicles and their fuels contribute to 

pollutants for which EPA has established health-based NAAQS, and motor vehicles also emit air 

toxics and contribute to near-road air pollution. 

EPA’s current Tier 2 Vehicle and Gasoline Sulfur Program, which was finalized in 

February 2000, took a systems-based approach to motor vehicle pollution by setting standards 

for both passenger vehicles and their fuel (gasoline). The Tier 2 program set stricter tailpipe and 

evaporative emissions standards for criteria pollutants from vehicles beginning with model year 

(MY) 2004 and phasing in through 2009. The program also lowered the sulfur content of 

gasoline, to a 30 parts per million (ppm) annual refinery average, 80 ppm per-gallon cap, and 95 

ppm downstream cap; beginning in 2004 and phasing in through 2011. 

The Tier 3 rule is a comprehensive, systems-based approach to address the impact of 

motor vehicles on air quality and health, similar to the Tier 2 rule. The Tier 3 program 

establishes new standards for light-duty vehicles and trucks and complete heavy-duty vehicles 

and new fuel standards for gasoline. Such standards were assumed in the 2008 NAAQS as part 

of the strategy for reaching attainment with the NAAQS. Subsequently, a May 21, 2010 

Presidential Memorandum directed EPA to “review for adequacy” the current non-greenhouse 

gas (GHG) emissions regulations for new motor vehicles and fuels, including tailpipe emissions 

standards for NOX and air toxics, and sulfur standards for gasoline. The memo further directed 

EPA to “promulgate such regulations as part of a comprehensive approach toward regulating 

motor vehicles” if EPA determines new regulations are required. Based on our review, we have 
10-3

concluded that improved vehicle technology, combined with lower sulfur gasoline, make it 

feasible and cost-effective to reduce emissions well below the current Tier 2 levels. These 

emission reductions are necessary to reduce air pollution that is (and projected to continue to be) 

at levels that endanger public health and welfare. 

In the absence of additional controls such as Tier 3 standards, areas would have to adopt 

other measures to reduce emissions from other sources under their state or local authority. Few 

other measures exist for providing multi-pollutant reductions of the same magnitude and costeffectiveness as those expected from the Tier 3 standards. 

10.4 Definition and Description of Small Entities 

The Regulatory Flexibility Act defines small entities as including small businesses, small 

organizations, and small governmental jurisdictions. For the purposes of assessing the impacts 

of a rule on small entities, a small entity is defined as: (1) a small business that meets the 

definition for business based on the Small Business Administration’s (SBA) size standardsA

; (2) 

a small governmental jurisdiction that is a government of a city, county, town, school district or 

special district with a population of less than 50,000; and (3) a small organization that is any notfor-profit enterprise which is independently owned and operated and is not dominant in its field. 

This rulemaking is expected to affect a variety of small businesses, but will not affect any small 

governmental jurisdictions or small organizations as described above. Table 10-1 below 

provides an overview of the primary SBA small business categories potentially affected by this 

regulation. 

Table 10-1 Industry Sectors Potentially Affected by the Rule 

Industry Sector NAICS Code SBA Size Standard for Small 

Business (less than or equal to):

Gasoline fuel refiners and 

importers 324110 1,500 employees

Ethanol producers 325193 1,000 employees

Gasoline additive 

manufacturers

325199

325998

424690

1,000 employees

500 employees

100 employees

Transmix processors Varied 1,500 employees

Petroleum bulk stations & 

terminals 424710 100 employees

Other warehousing and 

storage-bulk petroleum storage 493190 $25.5 million (annual receipts)

Light-duty vehicle and lightduty truck manufacturers 336111, 336112 1,000 employees

On-highway heavy-duty engine 

& vehicle (>8,500 pounds 

333618, 336120, 336211

336312

1,000 employees

750 employees

 

A

 The SBA definitions of small business by size standards using the North American Industry Classification System 

(NAICS) can be found at 13 CFR 121.201. 
10-4

GVWR) manufacturers

Independent commercial 

importers 811111, 811112, 811198 $7 million (annual receipts)

Alternative fuel converters

335312

336312, 336322, 336399

811198

1,000 employees

750 employees

$7 million (annual receipts)

EPA used a variety of sources to identify which entities are appropriately considered 

“small” using the criteria for small entities developed by the Small Business Administration as a 

guide. Information about these entities came from sources including the Energy Information 

Administration (EIA) within the U.S. Department of Energy, oil industry literature, EPA’s motor 

vehicle certification data, and previous vehicle and fuel rulemakings that have affected these 

industries. EPA then found employment information or annual revenue information for these 

companies using the business information database Hoover’s Online (a subsidiary of Dun and 

Bradstreet). 

10.5 Summary of Small Entities to Which the Rulemaking Will Apply 

10.5.1 Fuels-related Industries 

Small entities that may be subject to the Tier 3 gasoline sulfur standards include: 

domestic gasoline refiners, importers of gasoline into the U.S., ethanol producers, gasoline 

additive manufacturers, transmix processors, and terminal operators. Based on current data, EPA 

believes that there are about 50 gasoline refiners, of these, we believe that there are currently 13 

refiners producing gasoline that meet SBA’s small business definition. Of the seven transmix 

processors that we have identified, we believe that five would be considered small entities. 

Transmix processors do not have a specific NAICS code, and thus do not have a corresponding 

SBA definition, so these parties were estimated to be small entities by using the respective size 

standard for the industry these entities had listed as their “primary” business (refining- 1,500 

employees or less). For fuel terminals, we believe that there are 1,100 companies; of the 980 

companies that we were able to find employee count and/or revenue information for, we believe 

that 900 of these companies would be considered small entities. There are approximately 204 

ethanol producers; for those companies for which we were able to find employment data, we 

believe that the majority of this sector (all but 16 ethanol producers) would be considered small 

businesses. 

It should be noted that because of the dynamics in the fuels industry (i.e., mergers and 

acquisitions), the actual number of refiners that ultimately qualify as a small business under this

program could be different from this initial estimate. 

10.5.2 Vehicle-related Industries 

The motor vehicle manufacturing industry is made up primarily of large manufacturers 

including General Motors, Ford, Toyota, and Honda. Based on EPA certification records, we 

have identified a total of 27 car and truck manufacturers which have certified vehicles for sale in 

the U.S. Of these companies, EPA has identified 4 motor vehicle manufacturers that qualify as a 

small business under SBA definitions. Two of these small entities produce either gasoline-
10-5

fueled, natural-gas fueled, or hybrid gasoline-electric vehicles. Two additional small 

manufacturers exclusively produce all-electric vehicles. 

Companies that convert motor vehicles to run on alternative fuels will be subject to the 

proposed regulations. Based on EPA certification records, we have identified 13 companies 

which convert vehicles to run on alternative fuels. Of these companies, EPA has identified 9 

alternative fuel converters that qualify as a small business under the SBA definitions. 

Another industry sector that will be subject to the proposed regulations consists of 

companies that import specialized cars and trucks into the United States (U.S.), referred to as 

Independent Commercial Importers (ICIs). ICIs work with customers to bring in cars from 

overseas either because the owners are moving to the U.S., or because the vehicle is not 

otherwise available in the U.S. (e.g., high-performance sports cars and right-hand drive postal 

vehicles). We have identified 8 ICIs that are currently importing cars and trucks into the U.S. 

All of these companies qualify as a small business under the SBA definitions. 

10.6 Related Federal Rules 

The primary federal rules that are related to this final rule are: the Tier 2 

Vehicle/Gasoline Sulfur rulemaking (65 FR 6698, February 10, 2000), the 2017 Light-duty 

Greenhouse Gas (LD GHG) rule (77 FR 62623), and the Greenhouse Gas Emissions Standards 

and Fuel Efficiency Standards for Medium- and Heavy-Duty Engines and Vehicles (HD GHG) 

rule (76 FR 57106). 

The LD GHG and HD GHG rules are coordinated efforts by EPA and the National 

Highway Traffic Safety Administration (NHTSA) taking steps to reduce GHG emissions and 

improve fuel efficiency from on-road vehicles and engines. 

10.7 Reporting, Recordkeeping, and Other Compliance Requirements 

For any fuel control program, EPA must have assurance that fuel produced, distributed, 

sold and used meets the applicable standard. The recordkeeping, reporting, and compliance 

provisions of the Tier 3 fuels program will be consistent with those currently in place for the Tier 

2 gasoline program. Further, to the program will use existing registration and reporting systems 

that parties in the fuel production and distribution industry are already familiar with. A complete 

discussion of the fuel-related compliance provisions can be found in Section V.F of the preamble 

to the final rule. 

For any motor vehicle emissions control program, EPA must have assurances that the 

regulated products will meet the standards. The final program for manufacturers subject to this 

rule will include testing, reporting, and record keeping requirements for manufacturers of 

vehicles covered by the Tier 3 regulations. Testing requirements for these manufacturers will 

include certification emissions (including deterioration factor) testing and in-use testing. 

Reporting requirements will include emissions test data and technical data on the vehicles. 

Manufacturers must keep records of this information. 
10-6

10.8 Regulatory Alternatives 

As a part of the SBREFA process, we conducted outreach to small entities and convened 

a SBREFA Panel to gain feedback and advice from these entities. Prior to convening the Panel, 

we held outreach meetings with the SERs to learn the needs of small entities and potential 

challenges that these entities may face. The feedback that we received from SERs as a result of 

these meetings was used during the Panel process to develop a wide range of regulatory 

alternatives to mitigate the impacts of the rulemaking on small businesses. It was agreed that 

EPA should consider the issues raised by the SERs (and issues raised in the course of the Panel) 

and that EPA should consider the comments on flexibility alternatives that would help to 

mitigate any negative impacts on small businesses. 

The Panel consisted of members from EPA, the Office of Management and Budget 

(OMB), and SBA’s Office of Advocacy. Following the Panel convening, a Final Panel Report 

detailing all of the alternatives that were recommended by the Panel was issued. A full 

discussion of the regulatory alternatives discussed and recommended by the Panel, all written 

comments received from SERs during the SBREFA process, and summaries of the outreach 

meetings held with the SERs can be found in the SBREFA Final Panel Report.2

 In the proposal, 

we either proposed or requested comment on the various recommendations put forth by the 

Panel. Below we discuss those flexibility options recommended in the Panel Report, our 

proposed regulatory alternatives, and those provisions which are being finalized. All of the 

flexibilities that are being finalized for small businesses, as well as those for all entities that may 

be affected by the rulemaking, are described in Sections IV and V of the preamble to the final 

rule.

10.8.1 Fuel-related Alternatives 

10.8.1.1 Delayed Standards for Small Refiners 

Panel Recommendations

The Panel recommended that EPA propose a delay option, similar to previous fuels 

rulemakings, in the Tier 3 proposed rule. The Panel recommended that EPA allow small refiners 

to postpone their compliance with the Tier 3 program for up to three years. Small refiners 

choosing this flexibility option would have from January 1, 2017 through December 31, 2019 to 

continue production of gasoline with an average sulfur level of 30 ppm (per the Tier 2 gasoline 

sulfur program), and compliance with the 10 ppm sulfur standard would begin on January 1, 

2020. Any small refiner choosing this proposed option would be allowed to continue use of their 

Tier 2 gasoline sulfur credits through December 31, 2019 to meet the refiner average 30 ppm 

sulfur standard. 

The Panel also recommended that EPA request comment on case-by-case hardship 

provisions that would provide additional relief for any refiner experiencing extreme difficulty in 

compliance with the Tier 3 requirements, as discussed below in Section 10.8.1.1.4. 
10-7

What We Proposed and Public Comments Received on the NPRM

We proposed to allow small refiners to postpone their compliance with the Tier 3 

program for up to three years—small refiners choosing this flexibility option would have from 

January 1, 2017 through December 31, 2019 to continue production of gasoline with an average 

sulfur level of 30 ppm (per the Tier 2 gasoline sulfur program). Compliance with the 10 ppm 

sulfur standard would begin on January 1, 2020. We also proposed that small refiners would be 

allowed to continue use of their Tier 2 gasoline sulfur credits through December 31, 2019 to 

meet their refinery average 30 ppm sulfur standard, but these credits could not be used for 

compliance with the proposed Tier 3 10 ppm average sulfur standard. With regard to early credit 

generation, we proposed that all refiners and importers (including small refiners) could generate 

early credits relative to the 30 ppm sulfur standard from January 1, 2014 through December 31, 

2016, and relative to the 10 ppm sulfur standard from January 1, 2017 through December 31, 

2019. We also proposed to extend the small refiner provisions to small volume refineries 

(refineries with a crude oil throughput of less than or equal to 75,000 barrels per calendar day 

(bpcd)).

Comments received on the proposed rule were generally in support of allowing an 

additional three years for small refiners (and small volume refineries) to comply with the Tier 3 

program. However, some commenters did not agree with our proposed provisions for early 

credits. Some small refiners commented that they believe small refiners should also have their 

own three-year early credit generation period, from January 1, 2017 through December 31, 2019, 

relative to the 30 ppm sulfur standard. 

What We’re Finalizing

As described in Section V.E. of the preamble to the final rule, we are finalizing a threeyear delay for approved small refiners, until January 1, 2020. With regard to the ABT program, 

as discussed in preamble Section V.D.5, we are finalizing that small refiners may generate early 

credits relative to the 30 ppm average sulfur standard from January 1, 2014 through December 

31, 2019, and these credits could be used for either Tier 2 or Tier 3 compliance. (However, 

credits generated by a small refiner from January 1, 2017 through December 31, 2019 could only 

be traded and used by other small refiners.) Further, from January 1, 2017 through December 

31, 2019, if a small refiner’s annual average sulfur level is below 10 ppm, they may elect to split 

the generation of credits between both the 10 ppm and 30 ppm standards (without doublecounting). For example, during this time, a small refiner with an annual gasoline sulfur average 

of 8 ppm could generate 20 Tier 2 credits (30 ppm-10 ppm) and 2 Tier 3 credits (10 ppm-8 ppm). 

All of the small refiner provisions are also applicable to approved small volume 

refineries. 

10.8.1.2 Provisions for Additive Manufacturers 

Panel Recommendations

During the SBREFA Panel process, different requirements than those proposed (and 

being finalized today) were discussed for additive manufacturers. Thus, the provisions 
10-8

recommended by the Panel were not applicable to the provisions proposed and now finalized for 

these parties. More information on the Panel’s recommendations for gasoline additive 

manufacturers can be found in the Final Panel Report, located in the rulemaking docket. 

What We Proposed and Public Comments Received on the NPRM

We proposed that parties introducing additives to gasoline greater than 1.0 volume 

percent would be required to satisfy all of the obligations of a fuel manufacturer, including 

demonstration that the finished blend meets the applicable sulfur specification. We also 

proposed a maximum sulfur contribution of 3 ppm from the use of a gasoline additive added 

downstream of the refinery at less than 1.0 volume percent (when added at the maximum 

recommended treatment rate). Lastly, we proposed that additive manufacturers would need to 

maintain records of their additive production quality control activities for five years. 

What We’re Finalizing

As discussed further in Section V.C., manufacturers of gasoline additives that are used 

downstream of the refinery at less than 1.0 volume percent will be required to limit the sulfur 

contribution to the finished gasoline from the use of the additive to less than 3 ppm when the 

additive is used at the maximum recommended treatment rate. For each batch of additive 

produced, the manufacturer must retain sulfur test records for 5 years, and must make these 

records available to EPA upon request. Parties that introduce additives to gasoline at over 1.0 

volume percent will be required to satisfy all of the obligations of a fuel manufacturer, including 

demonstration that the finished blend meets the applicable sulfur specification. 

10.8.1.3 Refinery Gate and Downstream Caps 

Panel Recommendations

The Panel recommended that EPA assess and request comment on retaining the current 

Tier 2 refinery gate and downstream caps of 80 and 95 ppm, respectively, to help provide 

maximum flexibility and avoid system upsets for the entire refining and distribution system. 

Further, the SBA and OMB Panel members recommended that EPA propose retaining the 80 

ppm and 95 ppm caps. 

With regard to a 20 ppm refinery gate cap, the Panel had concerns that such a standard 

could cause operational problems for small refiners during a refinery turnaround or an upset, 

because a cap of this level could result in a refiner not being able to produce gasoline (as noted in 

their comments in Section 8 of the Panel Report). The Panel likewise had concerns that a 

downstream cap of 25 ppm could cause problems for small downstream entities, such as 

transmix processors, because they may not be able to reprocess finished gasoline down to this 

level (also noted in their comments in Section 8 of the Panel Report). Thus, the Panel 

recommended that EPA request comment on additional refinery gate and downstream caps above 

20/25 ppm, but below 80/95 ppm. Additionally, the Panel recommended that EPA allow the 

current Tier 2 80 ppm sulfur refinery gate cap and 95 ppm sulfur downstream cap in Alaska to 

remain at these levels indefinitely. 
10-9

What We Proposed and Public Comments Received on the NPRM

We proposed two options for the per-gallon sulfur caps—maintaining the Tier 2 80 ppm 

refinery gate sulfur and 95 ppm downstream sulfur caps and, beginning January 1, 2020, 

lowering to 50 ppm refinery gate and 65 ppm downstream caps. In addition, we requested 

comment on lowering to a 20 ppm refinery gate cap and a 25 ppm downstream cap. Due to 

technical and economic concerns for refiners and distributors in the state of Alaska, we also 

proposed that if we were to finalize 50/65 ppm caps, Alaska would be allowed to retain the 80/95 

ppm caps. 

We received comments on both of the proposed per-gallon cap options of 80/95 ppm and 

50/65 ppm, as well as comments on finalizing lower caps of 20/25 ppm and a 20 ppm overall 

cap. Comments in support of lower refinery gate and downstream caps noted potential 

environmental benefits, greater certainty that vehicles would see lower and more uniform 

gasoline sulfur levels, and the ability to enable new vehicle technologies that require very low 

sulfur levels. Comments in support of maintaining the 80/95 ppm caps cited concerns over cost, 

flexibility during turnarounds/unplanned shut downs (due to refinery fire, natural disaster, etc.), 

and potential impacts on gasoline supply and pricing. 

What We’re Finalizing

As discussed in greater detail in Section V.C of the preamble, we are retaining the Tier 2 

per-gallon sulfur caps of 80 ppm at the refinery gate and 95 ppm downstream. We are also 

committing to monitor and further evaluate in-use sulfur levels and their impact on vehicle 

emissions, which will include: analyses of in-use fuel surveys, refinery batch data, and the sulfur 

credit market; evaluation of any implementation issues; and an ongoing evaluation of vehicle 

manufacturers’ data on Tier 3 vehicles’ in-use performance. If it is warranted, we will reassess 

the sulfur cap level and the need for potential future regulatory action. 

10.8.1.4 Hardship Provisions 

Panel Recommendations

During the Panel process, EPA stated its intent to propose hardship provisions (for all 

gasoline refiners and importers) similar to those in prior EPA fuels programs: a) the extreme 

unforeseen circumstances hardship provision, and b) the extreme hardship provision. A hardship 

based on extreme unforeseen circumstances is intended to provide short term relief due to 

unanticipated circumstances beyond the control of the refiner, such as a natural disaster or a 

refinery fire. An extreme hardship is intended to provide short-term relief based on extreme 

circumstances (e.g., extreme financial problems, extreme operational or technical problems, etc.) 

that impose extreme hardship and thus significantly affect a refiner's ability to comply with the 

program requirements by the applicable dates. In the context of the proposal, the Panel agrees 

that such relief could consider long-term relief on the sulfur cap (similar to that for Alaska) if the 

circumstances both warrant it and can be structured in a way to allow for it. The Panel agrees 

with the proposal of such provisions and recommended that EPA include them in the Tier 3 

proposed rulemaking. 
10-10

What We Proposed and Public Comments Received on the NPRM

Similar to previous EPA fuels programs, we proposed the extreme hardship and extreme 

unforeseen circumstances hardship provisions both to accommodate a refiner’s inability to 

comply with at the start of the Tier 3 program and to deal with unforeseen circumstances that 

may occur at any point during the program. We proposed that any refiner could apply for a 

hardship waiver, but relief would be granted on a case-by-case basis following a showing of 

certain requirements; primarily that compliance through the use of credits is not feasible. 

Further, we proposed that any hardship waiver granted would likely consist of short-term relief, 

and would be based on the nature and degree of the hardship and EPA’s assessment of the credit 

market at that time. 

In general, comments received agreed with the inclusion of hardship provisions in the 

Tier 3 program. While not directly related to the hardship provisions, we received comments on 

the one-year deficit carryforward provision (an individual refinery that does not meet the average 

sulfur standard in a given year may carry a credit deficit forward for 1 year). We received 

comments expressing concern that it will be more challenging for refineries to make up their 

credit deficit in one year with a 10 ppm sulfur standard, thus the commenters requested that the 

deficit carryforward allowance be extended to two or three years. One commenter suggested that 

an extension of the deficit carryforward provision could also be used as a form of hardship relief. 

What We’re Finalizing

We are finalizing both the extreme hardship and extreme unforeseen circumstances 

hardship provisions. We continue to believe that providing short-term relief to those refiners that 

need additional time due to hardship circumstances will help to facilitate the adoption of the 

overall Tier 3 program for the majority of the industry. The provisions themselves, and the 

conditions under which a refiner would receive hardship relief, are similar to those in previous 

fuels regulations, and are necessary and appropriate to ensure that any waivers granted would be 

limited in scope. Further, we expect to impose appropriate conditions to ensure that the refiner is 

making best efforts to achieve compliance offsetting any loss of emission control from the 

program. A complete discussion of the hardship provisions is located in Section V.E.2 of the 

preamble to the final rule. 

As discussed more fully in preamble Section V.D.7, while we acknowledge the increased 

hurdle to make up a deficit in the Tier 3 program, we have concerns with the enforceability 

allowing for deficit carryforward greater than one year. Further, refiners also have the 

opportunity to purchase credits from others. However, if for some reason credits are unavailable 

or are prohibitively expensive such that the refiner could not make up the deficit in one year, we 

would consider this in an evaluation of a hardship application. As such, we are finalizing that 

hardship waivers could grant relief in the form of additional deficit carryforward of up to three 

years, depending on the level of hardship and the status of the credit market. 
10-11

10.8.2 Vehicle-Related Alternatives 

10.8.2.1 Lead Time for Exhaust and Evaporative Emission Standards 

Panel Recommendations

In the types of businesses subject to the potential Tier 3 standards, small businesses have 

limited resources available for developing new designs to comply with new emission standards. 

In addition, it is often necessary for these businesses to rely on vendor companies for technology. 

Moreover, percentage phase-in requirements pose a dilemma for a small manufacturer that has a 

limited product line (e.g., the manufacturer certifies vehicles in only one or two test groups). 

Thus, similar to the flexibility provisions implemented in previous vehicle rules, the Panel 

recommended that EPA allow small businesses the following flexibility options for meeting the 

potential Tier 3 exhaust emissions standards. 

The Panel recommended that small businesses be given additional leadtime to comply 

with the potential Tier 3 exhaust standards and allow small businesses to comply with the 

standards with 100 percent of their vehicles starting in model year 2022. (This is similar to the 

Tier 2 rule where EPA allowed small manufacturers to wait until the end of the phase-in to 

comply with the Tier 2 standards.) During the Panel process, the proposed Tier 3 rule was 

expected to have several different phase-in schedules; with the final dates varying from model 

year 2021 for the new exhaust PM standards and use of the new E15 certification fuel, to model 

year 2022 for the new evaporative emission standards, to model year 2025 for the new exhaust 

gaseous pollutant standards. The Panel noted that requiring all small businesses to comply with 

the full slate of Tier 3 requirements in model year 2022 should provide sufficient lead time for 

manufacturers to plan for and implement the technology changes needed to comply with the Tier 

3 standards. 

One of the SERs recommended that EPA adopt relaxed exhaust standards for small 

manufacturers. The SER noted that the exhaust emission averaging program being proposed by 

EPA would allow large manufacturers that have many engine families to certify their small, 

niche products at levels numerically higher than the standards. Small manufacturers that 

typically do not have more than one or two emission families generally cannot use averaging to 

the same extent because of their limited product offerings. The SER’s concern was that the highperformance vehicles produced by large manufacturers which they compete against would be 

able to certify at numerically higher levels at less cost than the SER would incur. While EPA 

was planning to propose the same standards for all manufacturers, the Panel recommended that 

EPA request comment on allowing small manufacturers to meet relaxed exhaust emission 

standards. This could also be included as part of the hardship provision discussed below. The 

Panel recommended that EPA request comment on the relaxed standards recommended by the 

SER. The SER-recommended relaxed NMOG+NOX standards over the Federal Test Procedure 

(FTP) are 0.125 grams/mile in model year 2020 and 0.070 grams/mile in model year 2025. In 

addition, the Supplemental FTP standards would be the standards for the corresponding bins 

which the manufacturer selected for complying with the FTP standards. For example, if the 

manufacturer certified to the proposed Tier 3 Bin 125 standards over the FTP, the manufacturer 

would have to comply with the corresponding Tier 3 Bin 125 standards for the Supplemental 

FTP. 
10-12

The Panel recommended that small businesses comply with the Tier 3 evaporative 

emission standards, including the leak standard, with 100 percent of their vehicles starting in 

model year 2022. For evaporative emissions, where the Tier 3 standards could begin as early as 

2017 and phase-in through 2022, this provision would allow small businesses and SVMs to wait 

until the last year of the Tier 3 phase-in period for evaporative emission standards for all of their 

vehicles. This start date is consistent with the start date described above for the Tier 3 exhaust 

emission requirements being recommended by the Panel for small businesses. 

What We Proposed

We proposed that small businesses be given additional lead time to comply with the 

potential Tier 3 exhaust and evaporative emission standards and that small businesses be allowed 

to comply with the standards with 100 percent of their vehicles starting in model year 2022. 

(This is similar to the Tier 2 rule where EPA allowed small manufacturers to wait until the end of 

the phase-in to comply with the Tier 2 standards.) The proposed Tier 3 rule has several different 

phase-in schedules; with the final dates varying from model year 2021 for the new light-duty 

exhaust PM standards to model year 2025 for the new light-duty exhaust gaseous pollutant 

standards. Our assessment was that requiring all small businesses to comply with the full slate of 

Tier 3 requirements in model year 2022 would provide sufficient lead time for manufacturers to 

plan for and implement the technology changes needed to comply with the Tier 3 standards. 

Although we proposed the same standards for all manufacturers starting with model year 

2022, we also requested comment on allowing small manufacturers to meet relaxed exhaust 

emission standards. The relaxed standards could be written directly into the regulations, or 

potentially we could allow manufacturers to request relaxed exhaust standards as part of the 

hardship provision discussed below, or we could allow manufacturers to request alternative 

standards based on a comparison of vehicles with similar attributes that are certified by larger 

manufacturers. With regard to the relaxed standard, we are requested comment on the standards 

recommended by the SER. The SER-recommended relaxed NMOG+NOX standards over the 

Federal Test Procedure (FTP) are 0.125 grams/mile in model year 2020 and 0.070 grams/mile in 

model year 2025. In addition, the Supplemental FTP standards would be the standards for the 

corresponding bins which the manufacturer selected for complying with the FTP standards. For 

example, if the manufacturer certified to the proposed Tier 3 Bin 125 standards over the FTP, the 

manufacturer would have to comply with the corresponding Tier 3 Bin 125 standards for the 

Supplemental FTP. 

Public Comments Received on the NPRM and What We Are Finalizing

We did not receive comments from non-SVM small businesses subject to the Tier 3 

vehicle standards about our proposed small entity phase-in provisions. However, we received 

comments from SVMs, as well as from the Alliance of Automobile Manufacturers and the 

Association of Global Automakers, arguing that the proposed phase-in did not provide adequate 

lead time relief for SVMs, and that the long-term Tier 3 standards for light-duty vehicles are not 

technologically feasible for SVMs. They especially highlighted the ability of large 

manufacturers to offset high emissions from high-performance, luxury models by averaging with 

their low-emitting models, while competing SVM products must be designed to actually achieve 

low emissions while still meeting customers’ performance expectations. Their limited 
10-13

production can also result in emission control technology suppliers placing a lower priority on 

SVM orders than on those of larger, high-volume manufacturers. 

Because of these factors, SVMs suggested that their companies meet a slightly more 

stringent NMOG+NOX standard than what we proposed for SVMs in the early years of the 

program (125 mg/mi) and a permanently relaxed standard of 51 mg/mi beginning in MY 2022. 

Ferrari (which also raised the issue of “operational independence” as described below) suggested 

a compliance schedule for SVMs similar to the California LEV III program, with either a 

permanently relaxed standard (matching the California LEV III 70 mg/mi long-term standard) or 

a delay until MY 2030 to meet the primary 30 mg/mi Tier 3 standard (when they suggest that 

SVMs could potentially comply). CARB comments supported Tier 3 adoption of its LEV III 

provisions for SVMs, including the long-term 70 mg/mi standard beginning in MY 2025. 

After considering the comments, we agree with SVMs that their unique logistical and 

technological challenges, especially in the later years of the primary phase-in schedule, warrant a 

significant period of relaxed standards for these manufacturers. However, we see no 

fundamental reasons why, given sufficient lead time, all companies, regardless of company size 

and vehicle characteristics, will not be able to meet the Tier 3 standards. Thus, we are finalizing 

a program for SVMs, available to non-SVM small businesses as well, under which they can 

choose an alternative NMOG+NOx fleet average phase-in schedule: Meeting a standard of 125 

mg/mi for model years 2017 through 2021, meeting a standard of 51 mg/mi for model years 

2022 through 2027, and then meeting the final Tier 3 standard of 30 mg/mi thereafter. 

Because companies choosing this 3-stage compliance option are certifying to Tier 3 bin 

standards in MY 2017, we expect that other exhaust emissions standards, including SFTP and 

PM standards, would apply for their vehicles as well, to the same degree and on the same 

schedule as for other manufacturers. Application of evaporative emissions and onboard 

diagnostics (OBD) standards, on the other hand, is not affected by choice of the 3-stage 

compliance option, and small companies may separately choose to delay compliance with 

evaporative emissions and OBD standards (except as noted in Section IV.G.3) until MY 2022, as 

proposed. In addition, small companies choosing the 3-stage compliance option may also delay 

the longer useful life and new test fuel requirements for exhaust emissions standards until MY 

2022 to align these changes with the 3-stage schedule. This option would not preclude use of 

other applicable small entity flexibility provisions discussed in this subsection. 

Although we are adopting this revised implementation schedule for SVMs and small 

businesses, we believe the proposed approach of allowing postponement of Tier 3 compliance 

until MY 2022 may be useful for small companies needing more lead time to begin certifying 

Tier 3 vehicles. Therefore we are finalizing the proposed approach as an additional but separate 

option for such companies, including SVMs, ICIs, and alternative fuel vehicle converters. 

Furthermore, because the optional 3-stage SVM implementation schedule, and the record of 

comments that prompted it, are specific to the light-duty sector, we are not extending it to heavyduty vehicles and instead are finalizing only the proposed approach of allowing postponement of 

Tier 3 compliance until MY 2022 for any SVMs and small businesses in the heavy-duty sector. 

Companies that take advantage of one of the SVM and small business implementation 

schedule provisions in either the light-duty or heavy-duty sector are not allowed to generate or 
10-14

use exhaust emissions Tier 3 credits in that sector while doing so. That is, they cannot earn or 

use exhaust emissions Tier 3 credits before MY 2027 while using the light-duty SVM revised 

implementation schedule, and they also cannot do so before MY 2022 while using the postponed 

compliance schedule that we proposed. 

10.8.2.2 Assigned Deterioration Factors 

Panel Recommendations

Under EPA’s regulations, manufacturers must demonstrate that their vehicles comply 

with the emission standards throughout the “useful life” period. This is generally done by testing 

vehicles at low-mileage and then applying a deterioration factor to these emission levels. The 

deterioration factors are determined by aging new emission control systems and then testing the 

aged systems again to determine how much deterioration in emissions has occurred. In order to 

reduce the testing burden on small manufacturers, EPA suggested that small manufacturers could 

use deterioration factor values assigned by EPA instead of performing the extended testing. A 

manufacturer would apply the assigned deterioration factors to its low-mileage emission level to 

demonstrate whether it complied with the Tier 3 emission standards. EPA currently allows this 

flexibility for small manufacturers. The Panel recommended that EPA propose that small 

businesses be allowed the option to use EPA-developed assigned deterioration factors in 

demonstrating compliance with the Tier 3 exhaust and evaporative emission standards. In the 

past, EPA has relied on deterioration factor data from large manufacturers to develop the 

assigned DFs for small manufacturers. EPA would expect to follow a similar procedure to 

determine the assigned DFs for the Tier 3 standards once large manufacturers start certifying 

their Tier 3 designs. Given that larger manufacturers would begin phasing in to the Tier 3 

standards in model year 2017, EPA should have a significant set of emissions deterioration data 

upon which to base the assigned DFs for small businesses within the first few years of the Tier 3 

program. EPA recognizes that assigned DFs need to be determined well in advance of model 

year 2022 in order to provide sufficient time for small businesses to decide whether or not to use 

the assigned DFs for certification purposes. 

What We Proposed

We proposed that small businesses be allowed the option to use EPA-developed assigned 

deterioration factors in demonstrating compliance with the Tier 3 exhaust and evaporative 

emission standards. In the past, EPA has relied on deterioration factor data from large 

manufacturers to develop the assigned deterioration factors for small manufacturers. EPA would 

expect to follow a similar procedure to determine the assigned deterioration factors for the Tier 3 

standards once large manufacturers start certifying their Tier 3 designs. Given that larger 

manufacturers would begin phasing in to the Tier 3 standards in model year 2017, we expected 

that we would have a significant set of emissions deterioration data upon which to base the 

assigned deterioration factors for small businesses within the first few years of the Tier 3 

program. we recognized in the proposal that assigned deterioration factors need to be 

determined well in advance of model year 2022 in order to provide sufficient time for small 

businesses to decide whether or not to use the assigned deterioration factors for certification 

purposes. 
10-15

Public Comments Received on the NPRM and What We Are Finalizing

We are adopting the assigned deterioration factor provisions for small businesses and 

SVMs (as well as for small volume test groups), as proposed. Commenters expressed support, 

but asked that the Agency commit itself to keeping these factors up to date as durability data 

accumulates. We are committed to periodically updating and publishing these assigned 

deterioration factors. Given that SVMs will now be allowed to use the revised implementation 

schedule, starting in MY 2017, it becomes necessary to consider assigned deterioration factors in 

stages. Because there may not be a sufficient base of accumulated durability data on Tier 3 

vehicles by MY 2017, we expect that the current set of assigned factors based on Tier 2 vehicles 

may continue in place for some time, noting that the MY 2017-2021 SVM fleet average of 125 

mg/mi is not too much different from the average of today’s Tier 2 vehicle emissions. By MY 

2022, when the SVM NMOG+NOx fleet average standard drops to 51 mg/mile, we expect to 

have new assigned factors available. We note that small businesses and SVMs may also, with 

advance EPA approval, use deterioration factors developed by another manufacturer (40CFR 

86.1826-01(b)). 

10.8.2.3 Reduced Testing Burden and OBD Requirements 

Panel Recommendations

Under EPA’s regulations, manufacturers must perform in-use testing on their vehicles 

and demonstrate their in-use vehicles comply with the emission standards. The current in-use 

testing regulations provide for reduced levels of testing for small manufacturers, including no 

testing in some cases. EPA suggested that these provisions should continue for small 

manufacturers with the Tier 3 program. The Panel recommended that EPA propose that small 

businesses be allowed to have reduced burden under the in-use testing program for Tier 3 

vehicles. 

One SER requested that EPA eliminate some of the evaporative emission testing 

requirements for small businesses based on its belief that some of the tests may be duplicative. 

While EPA noted (during the Panel process) that it understood the reasons behind the 

manufacturer’s suggestion, EPA believed it may be premature to consider such an option in the 

Tier 3 rule given the impact of the CO2 emission standards on engine and fuel system 

development. Currently, it is generally understood that the 2-day diurnal test drives the purge 

characteristics of evaporative control systems, while the refueling test, and to a lesser degree the 

3-day test, drive the capacity requirement of evaporative canisters. Prospectively, due to 

expected changes in engine and fuel system designs in response to upcoming CO2 emission 

standard requirements, this may not be the case. Therefore, at the time of the Panel process, 

EPA noted its belief that it is appropriate to retain all of the evaporative test procedures. It can 

be noted that under current regulations, EPA does allow manufacturers to waive 2-day diurnal 

testing for certification purposes (see 40 CFR 86.1829-01(b)(2)(iii)) and perform only the 2-day 

diurnal test as part of the in-use testing program (see 40 CFR 86.1845-04(c)(5)(ii)). These 

provisions would continue in the Tier 3 program. In general, EPA noted that it is open to 

changes that reduce test burden while maintaining the environmental effectiveness of its 

programs and could consider changes like those suggested by the SER in the future as the 

impacts of the future regulations on engine and vehicle design become clearer. EPA also stated 
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that it intends to request comment in the Tier 3 proposal on streamlining the current test 

procedures for small businesses in ways that would still maintain the overall stringency of the 

tests. 

What We Proposed

Under EPA’s regulations, manufacturers must perform in-use testing on their vehicles 

and demonstrate their in-use vehicles comply with the emission standards. The current in-use 

testing regulations provide for reduced levels of testing for small manufacturers, including no 

testing in some cases. We proposed that small businesses be allowed to have reduced burden 

under the in-use testing program for Tier 3 vehicles. Small manufacturers that sell less than 

5,000 units per year would not be required to do any in-use testing. Small manufacturers that 

sell between 5,001 and 15,000 units per year would be required to test 2 vehicles per test group, 

but only under the high-mileage conditions specified in the program. 

Under current regulations, manufacturers may waive testing for PM emissions for lightduty vehicles and trucks, except for diesel-fueled vehicles. Manufacturers are still subject to the 

standards and must make a statement of compliance with the PM standards. With the Tier 3 

proposal, we proposed new PM standards and further proposed to require manufacturers to test 

for PM emissions for all fuels. Because PM testing requires additional test equipment and 

facilities, the costs incurred for PM testing can be substantial, especially for a company selling 

small numbers of vehicles. Therefore, we proposed to continue the waiver for PM testing in the 

Tier 3 timeframe for small businesses. Small businesses would not be required to measure PM 

emissions when they certify to the Tier 3 emission standards. In lieu of testing, small businesses 

would be required to make a statement of compliance with the Tier 3 PM standards. We would 

retain the ability to determine the PM emissions results in confirmatory or in-use testing. 

We proposed new OBD requirements for vehicles certifying to the Tier 3 standards. The 

proposed OBD requirements were the same as CARB’s existing OBD requirements. The 

proposed OBD provisions require additional amounts of testing and information that can add 

significant cost to manufacturers if they are not already meeting the CARB OBD requirements. 

Small business vehicle manufacturers tend to comply with the CARB OBD requirements 

because they want to sell in the California market. On the other hand, alternative-fuel converters 

do not generally certify with CARB because of the significant cost burden of complying with the 

CARB OBD requirements. We therefore proposed that small business alternative-fuel 

converters may continue to comply with EPA’s existing OBD requirements (see 40 CFR 

86.1806-05) when the Tier 3 standards become effective. 

Alternative-fueled vehicles, MDPVs, and FFVs do not have SFTP emissions 

requirements under the existing regulations. We proposed to apply the Tier 3 SFTP standards to 

all vehicles, including alternative-fueled vehicles, MPDVs, and FFVs. Because SFTP testing 

includes emission measurement over the SC03 test cycle, which requires additional test facilities 

beyond those needed to run the FTP, the costs incurred for SC03 testing can be substantial, 

especially for companies like alternative fuel converters that sell very low numbers of converted 

vehicles. We proposed that the categories of vehicles newly subject to the SFTP standards, 

including alternative-fuel conversions, have the option to substitute the FTP emissions levels for 

the SC03 emissions results for purposes of compliance when calculating the SFTP emissions. 
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However, we would retain the ability to determine the composite emissions using SC03 test 

results in confirmatory or in-use testing. Because the vehicles being converted to an alternative 

fuel will likely have been tested for SFTP compliance, we expressed the view that the SFTP 

emissions would be similarly low, and therefore the added SC03 testing burden is unnecessary. 

Public Comments Received on the NPRM and What We Are Finalizing

We received no adverse comments on our proposal to continue providing for reduced 

levels of in-use testing and for waiving of PM testing for SVMs and small businesses, and are 

retaining these existing provisions in Tier 3. In lieu of PM testing, these companies will be 

required to make a statement of compliance with the Tier 3 PM standards. We may however 

measure PM emissions in EPA confirmatory or in-use testing. 

VNG, a natural gas fuel network provider, objected that the proposed OBD exception 

disadvantages larger manufacturers and should be made equally available to all vehicle 

manufacturers’ small volume test groups. We expect that larger manufacturers (as well as 

SVMs) wishing to produce alternative fuel vehicles will be well familiar with CARB’s OBD 

requirements and will be well-positioned to implement these requirements in Tier 3. We note 

that larger OEMs themselves did not make an argument for extending this provision beyond 

converters. We are finalizing the exception to the Tier 3 OBD requirements as proposed. We 

further note that the optional delay in Tier 3 implementation until MY 2022 that is available to 

small businesses, discussed above, includes a delay in the Tier 3 OBD requirement to MY 2022, 

as proposed, except that vehicles already meeting this requirement in MY 2017 must continue to 

do so in subsequent years. We are also adopting this Tier 3 OBD delay to MY 2022 for small 

companies taking advantage of the revised light-duty 3-stage implementation schedule discussed 

above, even though it involves other Tier 3 requirements starting in MY 2017, in order to avoid 

overburdening these manufacturers with multiple sets of new OBD design constraints. 

10.8.2.4 Hardship Relief Provisions 

Panel Recommendations

The Panel recommended that hardship provisions be provided to small businesses for the 

Tier 3 exhaust and evaporative emission standards. Under the hardship provisions, small 

businesses would be allowed to apply for additional time to meet the 100 percent phase-in 

requirements for exhaust and evaporative emissions. All hardship requests would be subject to 

EPA review and approval. Appeals for such hardship relief would be required to be made in 

writing and submitted well before the earliest date of noncompliance. The request should 

identify how much time is being requested. It must also include evidence that the 

noncompliance would occur despite the manufacturer's best efforts to comply, and must contain 

evidence that severe economic hardship would be faced by the company if the relief is not 

granted. The above provision should effectively provide the opportunity for small businesses to 

obtain more time to comply with the new Tier 3 standards. (The existing hardship provisions 

limit the extra time that can be requested to 1 year, but such a limit may or may not be included 

in the proposed Tier 3 hardship provisions.) 
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What We Proposed

We proposed hardship relief provisions for small businesses subject to the Tier 3 exhaust 

and evaporative emission standards. Under the proposed hardship provisions, small businesses 

would be allowed to apply for additional time to meet the 100 percent phase-in requirements for 

exhaust and evaporative emissions. All hardship relief requests would be subject to EPA review 

and approval. Appeals for such hardship relief would need to be made in writing and must be 

submitted well before the earliest date of potential noncompliance. The request would need to 

identify how much time is being requested. It must also include evidence that the 

noncompliance would occur despite the manufacturer's best efforts to comply, and must contain 

evidence that severe economic hardship would be faced by the company if the relief is not 

granted. The proposed hardship relief provision would effectively provide the opportunity for 

small businesses to obtain more time to comply with the new Tier 3 standards. The existing 

hardship relief provisions limit the extra time that can be requested to 1 year, but we proposed

that such a limit is not needed as part of the Tier 3 hardship relief provisions. 

Public Comments Received on the NPRM and What We Are Finalizing

Commenters supported these proposed provisions, within the context of a revised 

approach to SVM lead time, discussed above. We are finalizing the provisions as proposed. 

10.8.2.5 Applicability of Flexibilities 

Panel Recommendations

Under EPA’s current Tier 2 regulations, EPA provides a number of flexibilities for small 

volume manufacturers. The criteria for determining if a company is a small volume 

manufacturer is based on the annual production level of vehicles and is based on whether the 

company produces less than 15,000 vehicles per year. Unlike EPA’s small volume manufacturer 

criteria noted above, SBA defines which manufacturers are small businesses (and therefore 

should be considered under the SBAR Panel process) based on the number of employees for 

vehicle manufacturers and annual revenues for ICIs and alternative fuel converters. For 

example, SBA defines small business vehicle manufacturers as those who have less than 1,000 

employees. Similarly, SBA defines small business ICIs as those who have annual revenues of 

less than $7 million per year. 

The Panel recommended that EPA propose to allow all small businesses that meet the 

SBA criteria be eligible for the flexibilities described above. In addition, in the Panel Report, 

EPA stated that it is expecting to propose that manufacturers that meet a specified sales-based 

criterion to be eligible for the flexibilities described above. It is relatively easy for a 

manufacturer to project and ultimately determine sales. Determining the annual revenues or 

number of employees is less straightforward. In the recent rule setting the first light-duty vehicle 

and truck CO2 emission standards, EPA adopted provisions for small manufacturers based on a 

sales cutoff of 5,000 vehicles per year as opposed to the 15,000 level noted earlier that is used in 

the Tier 2 program. In the Panel Report, EPA noted that it expects to propose a small volume 

manufacturer definition based on the 5,000 vehicle per year level for the Tier 3 program. EPA 

believes the 5,000 unit cut-off for small volume manufacturers would include all of the small 
10-19

business vehicle manufacturers, ICIs, and alternative fuel converters that meet the applicable 

SBA definition as well as some additional companies that have similar concerns to small 

businesses. Lastly, EPA noted in the Panel Report that it expects to propose the flexibilities 

described above to be available to any manufacturer that meets either the SBA small business 

criteria or the sales-based criteria. 

What We Proposed

Under EPA’s Tier 2 regulations, EPA provides a number of flexibilities for small volume 

manufacturers. The criteria for determining if a company is a “small volume manufacturer” is 

based on the annual production level of vehicles and is based on whether the company produces 

less than 15,000 vehicles per year. Unlike EPA’s existing small volume manufacturer criteria, 

the Small Business Administration (SBA) defines which manufacturers are small businesses 

based on the number of employees for vehicle manufacturers and annual revenues for ICIs and 

alternative fuel converters. For example, SBA defines a small business vehicle manufacturer as 

those who have less than 1,000 employees. 

We proposed that all small businesses that are subject to the Tier 3 standards and that 

meet the SBA criteria be eligible for the flexibilities described above. Unless otherwise noted, 

the proposed flexibilities would be available to all small business vehicle manufacturers, ICIs, 

and alternative fuel converters subject to the Tier 3 standards. In addition, we proposed that 

manufacturers subject to the Tier 3 standards which meet a specified sales-based criteria be 

eligible for the flexibilities described above. It is relatively easy for a manufacturer to project 

and ultimately determine sales. Determining the annual revenues or number of employees is less 

straightforward. In the recent rule setting the first light-duty vehicle and truck CO2 emission 

standards, EPA adopted provisions for small manufacturers based on a sales cutoff of 5,000 

vehicles per year as opposed to the 15,000 level noted earlier that is used in the Tier 2 program.B 

We proposed that the small volume manufacturer definition be based on the 5,000 vehicle per 

year level for the Tier 3 program. For purposes of the Tier 3 rule, the 5,000 limit would be based 

on a running three-year average of the number of light-duty vehicles, light-duty trucks, mediumduty passenger vehicles, and complete heavy-duty trucks below 14,000 pounds GVWR. We

expressed the belief that the 5,000 unit cut-off for small volume manufacturers would include all 

of the small entity vehicle manufacturers, ICIs, and alternative fuel converters that currently 

meet the applicable SBA definition, as well as a few additional companies that have similar 

concerns to small businesses. 

We requested comment on extending eligibility for the Tier 3 SVM provisions to small 

manufacturers that are owned by large manufacturers but are able to demonstrate that they are 

operationally independent. We established such a provision in the light-duty greenhouse gas 

(GHG) program, and CARB did so in LEV III as well. 

 

B

 See 75 FR 25324, May 7, 2010. 
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Public Comments Received on the NPRM and What We Are Finalizing

As proposed, we are using the federal Small Business Administration (SBA) criteria to 

define small businesses eligible for the special provisions. SBA defines small business vehicle 

manufacturers as those with less than 1,000 employees, and small business ICIs and alternative 

fuel vehicle converters are evaluated using SBA criteria based on annual revenues. See Section 

IV.H.3 for a discussion of additional provisions that apply specifically to ICIs. Also, as 

proposed, we are defining SVMs in 40 CFR 86.1838-01 for purposes of Tier 3 as companies 

with nationwide annual U.S. sales volumes at or below 5,000 vehicles, though the 15,000 vehicle 

threshold used in Tier 2 continues to apply in a few regulatory provisions that Tier 3 changes are 

not impacting. Eligibility will be evaluated using an average of 2012-2014 MY sales. For 

companies with no 2012 MY sales, projected sales may be used, but their eligibility will be reevaluated thereafter using a three-year running average. 

VNG commented that the proposed 5,000 vehicle threshold could potentially limit the 

ability (or willingness) of natural gas SVMs to scale up production by forcing a tradeoff between 

sales and regulatory burden, pointing also to the fact that 15,000 vehicles is only 0.1% of annual 

light-duty vehicle sales. We do not believe that the SVM relief provisions are so advantageous 

as to cause self-limiting of sales, except perhaps for a company very near the threshold. Even if 

this were to happen, we do not see how moving the threshold to 15,000 would prevent the same 

dynamic from happening at that sales level. Furthermore, our use of a three-year rolling average 

of sales for determining SVM eligibility protects the SVMs from being penalized for having an 

especially good year not reflective of a its long-term growth trend. See the 2017 and later lightduty GHG final rule for a discussion of our basis for adopting the 5,000 vehicle threshold (77 FR 

62793, October 15, 2012). 

Comments from CARB and Ferrari supported the extension of SVM eligibility to 

operationally independent small manufacturers. No commenters opposed it; however, Advanced 

Biofuels USA recommended caution to avoid advantaging SVMs capable of leveraging parent 

company resources to drastically increase U.S. market share within 2-3 years. Given the 

precedent established in our GHG program, and the value of this extension for harmonization 

with LEV III, we are adopting this change into Tier 3 using the same eligibility criteria as in our 

GHG program, described in 40 CFR 86.1838-01(d). We believe these criteria are sufficiently 

strict and objective to address the concerns expressed by Advanced Biofuels USA. 

10.9 Economic Effects 

The following section summarizes the economic impact on small businesses of the Tier 3 

exhaust and evaporative emission standards and the fuel requirements. As noted earlier, the 

types of companies that will be affected by the Tier 3 exhaust and evaporative emissions include 

vehicle manufacturers, ICIs, and alternative fuel converters. Similarly, the types of companies 

that will be affected by the fuel requirements include gasoline refiners and importers, ethanol 

producers, gasoline additive manufacturers, transmix processors, and terminal operators. 

To gauge the impact of the Tier 3 standards on small businesses, EPA employed a costto-sales ratio test to estimate the number of small businesses that would be impacted by less than 

one percent, between one and three percent, and above three percent. The costs used in this 
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analysis for the in-use gasoline requirements are based on the cost estimates developed in 

Chapter 5 of this RIA. The costs used in this analysis for the Tier 3 exhaust and evaporative 

emission standards are based on the cost estimates developed in Chapter 2 of this RIA, 

supplemented with additional information for alternative fuel converters. A description of the 

inputs used for the vehicle-related sectors and the methodology used to develop the estimated 

impact on small businesses in each vehicle-related sector is presented in the docket for this 

rulemaking.3

During discussions with SERs during the SBREFA Panel process, ethanol SERs 

mentioned that ethanol producers are largely already meeting a 10 ppm sulfur standard and 

terminal operator SERs indicated that effects on their industry would largely be based on 

decisions made by refiners upstream. The final Tier 3 program retains the 80 ppm refinery gate 

cap and 95 ppm downstream cap, which means that downstream parties such as transmix 

processors, gasoline additive manufacturers, and terminal operators should not incur additional 

costs as a result of this program. 

While many gasoline refiners and importers are currently meeting, or are close to, a 10 

ppm sulfur standard, there are some refiners that could incur increased costs as a result of the 

Tier 3 program. Of the 12 refiners that EPA believes would be considered small refiners for the 

Tier 3 program, it is projected that the majority of these refiners will experience costs less than 

one percent of their sales, three refiners will experience costs between one and three percent of 

their sales, and two refiners would incur costs of three percent or more of sales, as noted in Table 

10-2 below. 

For vehicle manufacturers, EPA identified four small businesses. One of the small 

businesses manufactures adaptive vehicles (vehicles with adaptive equipment for persons with 

disabilities) in both gasoline-powered and CNG-powered versions. One of small businesses 

manufactures a hybrid gasoline-electric vehicle. Both of these manufacturers purchase engines 

from large manufacturers and then use the engines in their vehicles. Both of these manufacturers 

rely on third-party testing facilities to perform emissions testing. Both of these manufacturers 

are projected to incur compliance costs of less than one percent. Finally, two additional small 

businesses identified by EPA manufacture all-electric vehicles. For the two small businesses 

manufacturing all-electric vehicles, the estimated costs for meeting the Tier 3 vehicle standards 

are zero. 

For alternative fuel converters, EPA identified nine small businesses. Of the small 

business alternative fuel converters, four are projected to incur compliance costs above three 

percent and three are projected to incur compliance costs between one and three percent. Two 

small business alternative fuel converters will be impacted by less than one percent. 

For ICIs, EPA identified eight small businesses. All eight of the small business ICIs are 

projected to incur compliance costs between one and three percent. 

Table 10-2 summarizes the impacts of the regulations on small businesses impacted by 

the Tier 3 fuel requirements and exhaust and evaporative emission standards. 
10-22

Table 10-2 Summary of Impacts on Small Businesses 

Industry Sector 0-1 Percent 1-3 Percent >3 Percent

Gasoline refiners and importers 7 3 2

Vehicle manufacturers 4 0 0

Alternative fuel converters 2 3 4

Independent commercial importers 0 8 0

Totals 13 14 6

For a complete discussion of the economic impacts of the final Tier 3 rulemaking, see 

Chapter 9, the Economic Impact Analysis chapter, of this Regulatory Impact Analysis. 
10-23

References 

1

 Final Report of the Small Business Advocacy Review Panel on EPA’s Planned Proposed Rule Control of Air 

Pollution from New Motor Vehicles: Tier 3 Emission and Fuel Standards, October 3, 2011. 

2

 Final Report of the Small Business Advocacy Review Panel on EPA’s Planned Proposed Rule Control of Air 

Pollution from New Motor Vehicles: Tier 3 Emission and Fuel Standards, October 3, 2011. 

3

 “Small Business Impact Memo, Proposed Tier 3 Motor Vehicle Emission Standards and Related Provisions,” EPA 

memorandum from Phil Carlson to EPA Docket EPA-HQ-OAR-2011-0135, December 1, 2011.