United States

Environmental Protection

Agency

Air and Radiation EPA420-R-92-009

December 1992

Procedures for Emission

Inventory Preparation

 Printed on Recycled Paper

Volume IV: Mobile Sources
EPA420-R-92-009

December 1992

Procedures for Emission Inventory Preparation

Volume IV: Mobile Sources

Emission Planning and Strategies Division

Office of Mobile Sources

and

Technical Support Division

Office of Air Quality Planning and Standards

U.S. Environmental Protection Agency

NOTICE

This technical report does not necessarily represent final EPA decisions or positions.

It is intended to present technical analysis of issues using data which are currently available.

The purpose in the release of such reports is to facilitate the exchange of

technical information and to inform the public of technical developments which

may form the basis for a final EPA decision, position, or regulatory action.
ACKNOWLEDGMENT

Several people in EPA's Emission Planning and Strategies Division have contributed to this

document. Their names and contributions are listed below.

Chapter 1 Natalie Dobie Introduction

Chapter 2 Natalie Dobie Overview

Chapter 3 Terry Newell MOBILE4. 1

Natalie Dobie Vehicle Miles Traveled

Chapter 4 Greg Janssen Nonroad Sources

Joe Somers

Chapter 5 Richard Wilcox Aircraft

Chapter 6 Peter Okurowski Locomotives
NOTICE

The Procedures For Emission Inventory Preparation consists of these five volumes:

Volume I - Emission Inventory Fundamentals

Volume II - Point Sources

Volume III - Area Sources

Volume IV - Mobile Sources

Volume V - Bibliography

Volume I is a guide to the managerial and technical aspects of the emission inventory. It outlines

the information sources available, methods of estimating emissions, data validation and quality assurance

techniques, as well as procedures to maintain and update the inventory. Also included are a detailed

analysis of the manpower and resources required to derive each component of an emission inventory and

a comprehensive glossary.

Volume II discusses point sources identification, data collection, emissions calculation, and data

presentation. It establishes standardized methods and procedures to develop a point source data base.

Volume III outlines the methods of collecting and handling emission data from sources too small

and/or too numerous to be surveyed individually. Collectively, these sources are known as area sources.

Procedures are presented to identify area source categories. Important reference material that can be used

to determine the activity levels associated with area source categories are also listed. Finally, emission

factors, emission calculations, pollutant allocation and projection techniques, and methods of data

presentation are included to assist in the preparation and maintenance of the area source emission

inventories.

Volume IV presents an overview of the mobile source category as a whole and identifies specific

methods that can be used to identify and inventory sources, estimate emissions, and establish and

maintain a useful, current mobile source emissions inventory.

Volume V presents an extensive listing of currently available reference material designed to

assist in the development of an emission inventory. A concise abstract is provided for each reference

cited, outlining the pertinent emission inventory information.

These volumes are intended to present emission inventory procedures and techniques applicable

to state and local air programs. Please forward comments and suggestions for improvement to the U.S.

Environmental Protection Agency, Monitoring And Reports Branch (MD-14), Research Triangle Park,

North Carolina 27711.
Other U.S. EPA emission inventory procedures publications include:

Emission Inventory Requirements For Ozone State Implementation Plans,

EPA-450/4-91-010, U. S. Environmental Protection Agency, Office of Air

Quality Planning and Standards, Research Triangle Park, North Carolina,

March 1991.

Procedures for the Preparation of Emission Inventories for Carbon Monoxide

and Precursors of Ozone. Volume I: General Guidance for Stationary Sources,

EPA-450/4-91-016, U. S. Environmental Protection Agency, Office of Air

Quality Planning and Standards, Research Triangle Park, North Carolina, May

1991.

Procedures for the Preparation of Emission Inventories for Carbon Monoxide

and Precursors of Ozone. Volume II: Emission Inventory Requirements for

Photochemical Air Quality Simulation Models, EPA-450/4-9-014, U.S.

Environmental Protection Agency, Office of Air Quality Planning and

Standards, Research Triangle Park, North Carolina, May 1991.

Emission Inventory Requirements for Carbon Monoxide State Implementation

Plans, EPA-450/4-91-0l1, U.S. Environmental Protection Agency, Office of Air Quality Planning

and Standards, Research Triangle Park, North Carolina, March 1991.

Example Documentation Report For 1990 Base Year Ozone and Carbon

Monoxide State Implementation Plan Emission Inventories, EPA-450/4-92-007,

U. S. Environmental Protection Agency, Office of Air Quality Plaining and

Standards, Research Triangle Park, North Carolina, March 1992.

AIRS Facility Subsystem Source Classification Codes (SCCs) and Emission

Factor Listing for Criteria Pollutants EPA-450/4-90-003, U.S. Environmental

Protection Agency, Office of Air Quality Planning and Standards, Research

Triangle Park, North Carolina, March 1990. Revised edition to be issued

Summer 1992.

Guidance for the Preparation of Quality Assurance Plans O3,/CO SIP Emission

Inventories, EPA-450/4-88-023, U.S. Environmental Protection Agency, Office

of Air Quality Planning And Standards, Research Triangle Park, North

Carolina, December 1988.

Quality' Review Guidelines For 1990 Base Year Emission Inventories, EPA450/4-91-022, U.S. Environmental Protection Agency, Office of Air Quality

Planning and Standards, Research Triangle Park, North Carolina, September

1991
SIP Air Emission Inventory Management System (SAMS) Version 4.1 and

SAMS User's Guide, U. S. Environmental Protection Agency, Office of Air

Quality Planning and Standards, Research Triangle Park, North Carolina,

September 1991.

User's Guide to MOBILE4. 1 (Mobile Source Emission Factor Model), 

EPA-AA-TEB-91 -01, U.S. Environmental Protection Agency, Office of Mobile 

Sources, Ann Arbor, Michigan, July 1991.

Procedures for Estimating and Applying Rule Effectiveness in Post-1987 Base

Year Emission Inventories for Ozone and Carbon Monoxide State

Implementation Plans, U.S. Environmental Protection Agency, Office of Air

Quality Planning and Standards, Research Triangle Park, North Carolina, June

1989.

Surface Impoundment Modeling System (SIMS) Version 2.0 User's Manual, 

EPA-450/4-90-019a, U.S. Environmental Protection Agency, Research Triangle

Park, North Carolina, September 1990.

Background Document for Surface Impoundment Modeling Svstem (SIMS)

Version 2.0, EPA-450/4-90-019b, U.S. Environmental Protection Agency,

Research Triangle Park, North Carolina, September 1990.
TABLE OF CONTENTS

 Page

1.0 INTRODUCTION 1

2.0 OVERVIEW OF THE MOBILE SOURCE CATEGORY 2

2.1 INDIVIDUAL MOBILE SOURCE CATEGORIES 2

2.1.1 Highway Vehicles 2

2.1.2 Nonroad Sources 3

2.1.3 Aircraft 3

2.1.4 Locomotives 4

3.0 EMISSIONS FROM HIGHWAY VEHICLES 5

3.1 GUIDANCE ON THE USE OF MOBILE4.1 VS MOBILE5 FOR THE

 1990 BASE YEAR INVENTORY AND OTHER INVENTORIES 5

3.2 MOBILE SOURCE EMISSION ESTIMATION PROCESS 6

3.2.1 Overview of Factors Influencing Motor Vehicle Emission

 Inventories 6

3.2.1.1 Vehicle Fleet Activity 7

3.2.1.2 Emission Factors 7

3.2.1.3 Fleet Characteristics 7

3.2.1.4 Fuel Characteristics 7

3.2.1.5 Correction Factors 8

3.2.1.6 Control Programs 8

3.2.2 Overview of MOBILE4.1 Input Requirements 8

3.2.2.1 Fleet Characteristics 9

3.2.2.1.1 VMT Mix 9

3.2.2.1.2 Annual Mileage Accumulation Rates 9

3.2.2.1.3 Registration Distributions 10

3.2.2.2 Fuel Specifications 10

3.2.2.2.1 RVP 10

3.2.2.3 Correction Factors 10

3.2.2.3.1 Speed 10

3.2.2.3.2 Temperature 10

3.2.2.3.3 Operating Modes 11

3.2.2.3.4 Minor Correction Factors 11

3.2.2.4 Tampering and Misfueling 12

3.2.2.5 Control Programs 12

3.2.2.5.1 Refueling Emissions 12

3.2.2.5.2 Inspection and Maintenance Programs 12

3.2.2.5.3 Anti-Tampering Programs (ATPs) 12

3.3 GUIDANCE ON SELECTING MOBILE4.1 INPUTS 13

3.3.1 Emission Factors 13

3.3.1.1 Region 14

3.3.1.2 Calendar Year 14
TABLE OF CONTENTS

Page

3.3.2 Fleet Characteristics 15

3.3.2.1 Vehicle Miles Traveled Mix by Vehicle Type 15

3.3.2.2 Annual Mileage Accumulation Rates and

 Registration Distributions by Vehicle Type and Age 16

3.3.2.3 Trip Length Distribution 18

3.3.2.4 Diesel Sales Fractions 20

3.3.3 RVP Determination 22

3.3.3.1 EPA-Provided 1990 RVP Estimates 26

3.3.3.2 "Period 1" RVP and "Period 2" RVP 26

3.3.3.3 Interpolation 27

3.3.3.4 Inputs for Future Year RVP 27

3.3.3.4.1 Future Summer RVP 27

3.3.3.4.2 Future Winter RVP 28

3.3.4 Oxygenated Fuels 29

3.3.5 Correction Factors 30

3.3.5.1 Speed 30

3.3.5.2 Temperature 34

3.3.5.3 Operating Modes 38

3.3.5.4 Additional Correction Factors for Light-Duty 

 Gasoline-Fueled Vehicle Types 40

3.3.6 Control Programs 43

3.3.6.1 Refueling Emissions 43

3.3.6.2 Inspection and Maintenance Programs 45

3.3.6.2.1 I/M 47

3.3.6.2.2 Start Year 47

3.3.6.2.3 Stringency 47

3.3.6.2.4 First Model Year 47

3.3.6.2.5 Last Model Year 48

3.3.6.2.6 Waiver Rates 48

3.3.6.2.7 Compliance Rate 49

3.3.6.2.8 Inspection Frequency 50

3.3.6.2.9 Vehicle Classes 51

3.3.6.2.10 I/M Test Types 51

3.3.6.2.11 Alternate I/M Credits 53

3.3.6.2.12 Centralized Programs 53

3.3.6.2.13 Decentralized Programs (Manual) 53

3.3.6.2.14 Computerized Inspection 54

3.3.6.2.15 Tech I-II and Tech IV+ 55

3.3.6.3 Anti-Tampering Programs 55

3.3.6.3.1 ATP 57

3.3.6.3.2 Tampering and Misfueling 57

3.3.6.3.3 Air Pump Inspection 57
TABLE OF CONTENTS

 Page

3.3.6.3.4 Catalyst Inspection 57

3.3.6.3.5 Fuel Inlet Restrictor Inspection 58

3.3.6.3.6 Tailpipe Lead Detection Test 58

3.3.6.3.7 EGR Inspection 59

3.3.6.3.8 Evaporative Control System 59

3.3.6.3.9 PCV Inspection 60

3.3.6.3.10 Gas Cap Inspection 60

3.3.6.3.11 Tampering Rates 60

3.4 VEHICLE MILES TRAVELED 62

3.4.1 Highway Performance Monitoring System 62

3.4.1.1 Role of the HPMS in SIP Development 62

3.4.1.2 Overview of HPMS 63

3.4.1.3 Consistency Between HPMS and SIP VMT 65

3.4.1.3.1 Expansion Factors 65

3.4.1.3.1.1 Non-Attainment Area the Same As

 the Federal Aid Urbanized Area 65

3.4.1.3.1.2 Non-Attainment Area Inside

 of the Federal Aid Urbanized Area 66

3.4.1.3.1.3 Non-Attainment Area Outside

 of the Federal Aid Urbanized Area 66

3.4.1.3.1.4 Non-Attainment Area and Federal

 Aid Urbanized Area Crossover 67

3.4.1.3.2 Local Functional System 67

3.4.1.3.3 Seasonal Adjustment 68

3.4.1.3.4 Daily Adjustment 68

3.4.1.4 Allocating VMT to Time of Day 68

3.4.1.5 Allocating VMT to Functional Systems 69

3.4.1.6 Estimating VMT in Rural and Small Urban Areas 69

3.4.1.6.1 Apportionment of Statewide 

 VMT-Recommended Method 72

3.4.1.6.2 Apportionment of Statewide 

 VMT-Alternative Methods 74

3.4.1.6.2.1 Motor Vehicle Registrations 74

3.4.1.6.2.2 Population 74

3.4.1.6.2.3 Fuel Sales 75

3.4.2 Travel Demand Network Models 78

3.4.2.1 Role of Transportation Models in SIP Development 78

3.4.2.2 Background 78

3.4.2.3 Overview of Network Models 79

3.4.2.3.1 Level of Service 81

3.4.2.3.2 Physical Attributes 83

3.4.2.3.3 Locational Link Attributes 83

3.4.2.3.4 Trip Generation 86
TABLE OF CONTENTS

Page

3.4.2.3.5 Trip Distribution 86

3.4.2.3.6 Modal Split 86

3.4.2.3.7 Traffic Assignment 86

3.4.2.3.8 Feedback 87

3.4.2.4 Consistency Between Transportation Model

 VMT and HPMS 87

3.4.2.4.1 Non-Attainment Area the Same As the

Network Model Area 88

3.4.2.4.2 Non-Attainment Area Inside of the

Network Model Area 89

3.4.2.4.3 Non-Attainment Area Outside of the

Network Model Area 89

3.4.2.4.4 Non-Attainment Area and Network 

Model Area Crossover 90

3.4.2.5 Local Functional System 90

3.4.2.6 Seasonal Adjustment 91

3.4.2.7 Daily Adjustment 91

3.4.2.8 Allocating VMT to Time of Day 91

3.4.2.9 Allocating VMT to Functional Systems 91

3.4.3 Exception to the Use of HPMS VMT 92

Appendix 3-A 94

4.0 EMISSIONS FROM NONROAD SOURCES 98

4.1 Introduction 98

4.2 Inventory Options Under This Guidance 99

4.2.1 Options for Areas With EPA Provided Inventories 99

4.2.2 Options For Areas With EPA Provided Inventories 101

4.2.3 Options For Areas Without EPA Provided Inventories 102

4.3 Explanation of EPA Provided Inventory 102

4.3.1 Derivation of AMS Inputs 103

4.3.2 AMS Inputs 105

4.4 General Methodology Used In Deriving Emission Inventories For

 33 Areas 107

4.4.1 Explanation of Methodologies to Distribute Equipment Within

Each Category Type at the County Level 108

4.4.2 Explanation of Methodologies For Distributing Equipment Within

Each Category at the Sub-County Level 112

4.4.3 Seasonal Adjustment Methodology 113

4.5 New York Non-Attainment Area Example 115

Appendix 4-A 117

Appendix 4-B 124

Appendix 4-C 132

Appendix 4-D 135
TABLE OF CONTENTS

 Page

5.0 EMISSIONS FROM AIRCRAFT 137

5.1 OVERVIEW OF THE INVENTORY METHODOLOGY 137

5.1.1 Factors Affecting Emissions 138

5.1.1.1 Aircraft Categorization 138

5.1.1.2 Pollutant Emissions 139

5.1.1.3 Aircraft Engines 140

5.1.1.4 Operating Modes 140

5.2 INVENTORY METHODOLOGY 144

5.2.1 Airport Selection 144

5.2.2 Mixing Height Determination 145

5.2.3 Activity and Emissions for Commercial Aircraft 149

5.2.4 Activity and Emissions for General Aviation and Air Taxi 

Aircraft 173

5.2.4.1 Aircraft-Specific Procedure 173

5.2.4.2 Alternative, Fleet-Average Procedure 176

5.2.5 Activity and Emissions for Military Aircraft 178

5.3 VARIATIONS TO THE INVENTORY CALCULATION 

PROCEDURE 190

5.3.1 Variability of Activity - Daily and Seasonal 190

5.3.2 Operational Activity that Affects Aircraft Emissions 191

5.3.2.1 Reduced Engine Taxiing 191

5.3.2.2 Derated Take%off 192

5.3.3 Particulate Emissions 192

5.4 OTHER EMISSION SOURCES 192

5.4.1 Auxiliary Power Units 192

5.4.2 Evaporative Emissions 197

5.5 EFFECT OF FUTURE CHANGES TO THE FLEET 197

5.6 CONVERTING FROM TOTAL HYDROCARBONS (THC) TO

 VOLATILE ORGANIC COMPOUNDS (VOC) 198

5.6.1 Commercial and Military Conversions 198

5.6.2 General Aviation and Air Taxi Conversions 199

6.0 EMISSIONS FROM LOCOMOTIVES 200

6.1 OVERVIEW OF RECOMMENDED INVENTORY

METHODOLOGY 202

6.2 RECOMMENDED METHODS 202

6.2.1 Class I Line Haul Locomotives 202

6.2.1.1 Fuel Consumption 202

6.2.1.2 Emission Factors 204

6.2.2 Class II and III Line Haul Locomotives 205

6.2.2.1 Fuel Consumption 205

6.2.2.2 Emission Factors 206

6.2.3 Yard Operations 206

6.2.3.1 Number of Yard Locomotives 206

6.2.3.2 Emissions Per Yard Locomotive 206
TABLE OF CONTENTS

 Page

6.3 TAILORING METHODS 208

6.3.1 Locomotive Roster Tailoring Method 208

6.3.1.1 Identify the locomotives in the area 208

6.3.1.2 Determine the engine type 209

6.3.1.3 Sum the total of the conversions 209

6.3.1.4 Calculate the new fleet average emission factor 210

6.3.1.5 Multiply the new emission factors by fuel 

 consumption 210

6.3.2 Duty Cycle Tailoring Method 210

6.3.3 SO2 Tailoring Method 212

6.4 ALTERNATIVE METHOD 213

6.5 RE-ENGINED LOCOMOTIVES 213

6.6 CONVERTING FROM TOTAL HYDROCARBONS (THC) TO

 VOLATILE ORGANIC COMPOUNDS (VOC) 213

Appendix 6-1 215

Appendix 6-2 216

Appendix 6-3 217

Appendix 6-4 219

Appendix 6-5 222

Appendix 6-6 223

Appendix 6-7 225

Appendix 6-8 227
1

1.0 INTRODUCTION

A fundamental requirement in the effort to control pollution in any form is to quantify the

emissions being released. This is necessary to understand the relationships between emissions

and the ambient concentrations that result, and to develop appropriate policies and methods to

ensure that ambient pollutant concentrations remain within acceptable limits. 

Specific air pollution requirements are set forth in Title 40, Code Of Federal Regulations,

Part 51.321 (40 CFR 51), and in the Clean Air Act, as amended, for the development and

maintenance of ongoing programs to inventory specific pollutant emissions. States are required

by 40 CFR 51 to prepare and submit annual reports to the U.S. Environmental Protection Agency

(EPA) regarding the emissions of particulate matter, sulfur oxides, carbon monoxide, nitrogen

oxides, and volatile organics from point sources within their boundaries. The amendments to the

Clean Air Act require the development of "...comprehensive, accurate, and current..." inventories

from all sources of each pollutant for every non-attainment area, in conjunction with the

preparation of revised State Implementation Plans (SIPs). EPA recognizes that a significant

effort will continue to be needed to develop and maintain emission inventories to meet the

requirements for both technical analysis and administrative reporting.

To assist the states in meeting the requirements for emission inventory development, a

five volume series has been prepared that describes in detail many of the technical aspects of the

inventory process. This document is the fourth volume in the series, and it focuses on mobile

sources. Specifically, this document presents specific methods that can be used to identify

sources, estimate emissions, and establish and maintain a useful, current mobile source emissions

inventory. Special attention has been given to preparing the 1990 SIP inventories. 

Following this introductory chapter, Chapter 2 gives an overview of the mobile source

category. Chapters 3 through 6 present specific methods that should be used to derive emission

estimates for each of the primary mobile source subcategories. 

Chapter 1 - Introduction

Chapter 2 - Overview

Chapter 3 - Highway Vehicles 

Chapter 4 - Nonroad Sources 

Chapter 5 - Aircraft 

Chapter 6 - Locomotives 
2

2.0 OVERVIEW OF THE MOBILE SOURCE CATEGORY

An inventory of pollutant emission sources should classify sources into two major

categories - point sources and area sources. The point source category is described in detail in

Volume II of this series. The area source category is described in detail in Volume III of this

series. Mobile sources are a subcategory within the area source category of pollutant emission

sources. However, the procedures for preparing and maintaining an inventory of emissions from

mobile sources are presented herein, as a separate document in this series, because the

inventorying procedures are different from those for other area source subcategories and because

the mobile source emissions inventory represents a major portion of the total emissions of

volatile organics (VOC), nitrogen oxides (NOx), and carbon monoxide (CO).

The mobile sources for which inventory and emission calculation procedures are

presented in this document are highway vehicles, nonroad mobile sources, aircraft, and

locomotives. Recreational marine equipment and commercial marine vessels are discussed in the

nonroad mobile source section. The procedures describe how to calculate tailpipe emissions and

emissions from the fuel carried on the vehicle (evaporative VOC emissions) for these four

mobile source categories. The emissions that result from tire wear and travel over roads or other

surfaces should be calculated from the procedures in Volume III of this series and are specifically

excluded from consideration in this document.

2.1 INDIVIDUAL MOBILE SOURCE CATEGORIES

2.1.1 Highway Vehicles

Highway vehicles include all vehicles registered to use the public roadways. The

predominant emissions source in this category is the automobile, although trucks and buses are

also significant sources of emissions. 

The total highway vehicle population can be characterized by eight individual vehicle

type categories:

 Light duty gasoline powered vehicles (LDGV);

 Light duty gasoline powered trucks, from 0 to 6000 lb. 

gross vehicle weight (LDGT1);

 Light duty gasoline powered trucks, from 6001 to 8500 lb. 

gross vehicle weight (LDGT2);

 Heavy duty gasoline powered vehicles (HDGV);

 Light duty diesel powered vehicles, from 0 to 6000 lb. gross vehicle

weight (LDDV);

 Light duty diesel powered trucks (LDDT);

 Heavy duty diesel powered vehicles (HDDV); 

 Motorcycles (MC).
3

Numerous characteristics for each vehicle type are necessary before emissions can be

calculated. These characteristics include, among others, model year, the age distribution of

vehicles within the class, annual mileage by vehicle age, and average speed. Chapter 3 of this

document presents detailed procedures for identifying and using these and other key

characteristics.

2.1.2 Nonroad Sources

This mobile source category includes a diverse set of source types. The movement of

sources in this category occurs on surfaces other than the public highways. Nonroad vehicles can

be classified into ten categories:

 Lawn and Garden Equipment,

 Industrial Equipment,

 Airport Service Equipment,

 Construction Equipment,

 Recreational Equipment,

 Agricultural Equipment,

 Recreational Marine Equipment,

 Logging Equipment,

 Light Commercial Equipment, 

 Commercial Marine Vessels.

These categories are difficult to inventory, since few data are available to determine

either their activity levels or operating characteristics. Chapter 4 of this document provides

procedures for inventorying and estimating emissions from these categories.

2.1.3 Aircraft

Aircraft include all types of aircraft, whether civilian, commercial, or military. Emissions

from idling, taxiing, and during landings and takeoffs are included. Landing and takeoff cycle

(LTO) emissions are those that occur between ground level and an altitude of about 3000 feet. 

Aircraft emissions above 3000 feet need not be included in either the base year emission

inventory or in the modeling inventory.

The larger civil and commercial airports with continuously manned control towers

maintain records of LTO cycles by type of aircraft as part of their standard operating procedure. 

Smaller airports also maintain these records to the extent that their control towers are manned or

landing fees are recorded. Difficulty may be encountered in obtaining data on military aircraft

operations at military airports.

EPA has compiled a complete set of emission factors for different types of aircraft

operating in the different modes (idle, taxi, LTO). Chapter 5 of this document provides

instruction on how to calculate emissions from this mobile source category.
4

2.1.4 Locomotives

Locomotives include all fossil fuel fired locomotive engines operated on railways. The

quantity of fuel used by locomotives and the size, in horsepower, of the locomotives are

necessary to calculate emissions from this source. This information is discussed in Chapter 6. 
5

3.0 EMISSIONS FROM HIGHWAY VEHICLES

In most urban areas, highway vehicles represent the largest single source of carbon

monoxide (CO) emissions and contribute significantly to the area's production of volatile organic

compounds (VOC), sulfur oxides (SOx) and oxides of nitrogen (NOx).

Emission estimates for highway vehicles are usually based on the combination of two

fundamental measures of activity: travel and the average rate of pollutants emitted in the course

of travel. Both measures reflect complex patterns of behavior. 

The Environmental Protection Agency and the Department of Transportation Federal

Highway Administration (FHWA) have developed a series of tools/models to estimate the rate of

emissions produced by vehicles per mile of travel and the amount of travel itself. The

knowledge base and disciplines required to understand and operate these models are distinct, as

are their audiences. This distinction generally ensures that environmental analysts have little

appreciation for the accuracy of the travel estimates produced by transportation analysts and vice

versa.

The purpose of this chapter is to provide guidance for preparing the highway vehicle

portion of mobile source emission inventories, particularly those associated with the

development of State Implementation Plans (SIPs) for ozone (O3) and CO. The accuracy of the

inventory will be no better than the accuracy of the estimates of either the emission rates or

vehicle miles traveled (VMT).

This chapter responds to concerns that little effort has been devoted to the development of

accurate projections of travel within non-attainment areas, that projections of attainment dates

have been based on dated information and that highway vehicles are responsible for a greater

portion of the emissions inventory than recent estimates have suggested. Because of these

concerns, the earlier guidance on the use of available travel estimates has been carefully

reviewed and updated. 

3.1 GUIDANCE ON THE USE OF MOBILE4.1 VS MOBILE5 FOR THE 1990 BASE 

YEAR INVENTORY AND OTHER INVENTORIES

At the time of this writing, MOBILE4.1 is EPA's current emission factor model. 

MOBILE5 will be available within months of the publication of this document. EPA will accept

1990 base year emission inventories prepared with either MOBILE4.1 or MOBILE5 emission

factors. The November 15, 1992 submittal date for inventories will apply no matter which

version of the model is used. 

Since MOBILE5 will incorporate the new vehicle standards for VOC and NOx mandated

by the Clean Air Act (CAA), estimates of those emissions for years after 1990 will be

significantly different than those estimated by MOBILE4.1. Therefore, ozone non-attainment

areas should submit projections using MOBILE5. However, the 1990 highway vehicle emission

inventories should be recalculated as soon as possible after November 15, 1992 using MOBILE5

so that all required inventories are consistent. CO 
 1 The SIP Attainment/Reasonable Further Progress and projection year inventories are due on either November

15, 1993 or November 15, 1994, depending upon the non-attainment classification.

 2 EPA may set a date prior to November, 1993 for submission of draft projection and recalculated base year

inventories, similar to the current requirement to submit the draft base year inventory no later than May, 1992. 

6

non-attainment areas may use MOBILE4.1 for the November 15, 1992 projection submittal, and

if they do, recalculation of the 1990 inventory is not necessary. 

The SIP Attainment/Reasonable Further Progress Demonstration, including projection

year inventories, should use MOBILE5 for ozone non-attainment areas.1

 In addition, if the base

year inventory was originally developed using MOBILE4.1, it should be recalculated using

MOBILE5 and resubmitted.2

 

For CO non-attainment areas, the base year and projection year inventories may be

developed using either MOBILE4.1 or MOBILE5. Submissions after the November 15, 1992

submission should use MOBILE5. Such submissions may be voluntary or due to bump up or

other provisions of the Clean Air Act. 

The release of MOBILE5 will be accompanied by a supplement to this document

explaining the differences between MOBILE4.1 and MOBILE5 and the additional inputs

contained in MOBILE5. 

3.2 MOBILE SOURCE EMISSION ESTIMATION PROCESS

3.2.1 Overview of Factors Influencing Motor Vehicle Emission Inventories

Many complex processes govern the formation of pollutants in motor vehicles. The EPA

and the California Air Resources Board (CARB) maintain large data collection programs to

quantify the rate at which pollutants are emitted by individual categories of motor vehicles. Both

organizations have used this information to develop models that help analysts in estimating

motor vehicle contributions to the local emissions inventory. These models, commonly known

as emission factor models, are designed to account for the effect of numerous vehicle parameters

on the volume of pollutants emitted. The current EPA model is called MOBILE4.1.

The primary components of an emission factor model include the base emission factors,

characterization of the vehicle fleet, fuel characteristics, vehicle operating conditions and the

effect of local ambient conditions, the effect of alternative I/M programs and the effect of

tampering and misfueling. None of these factors is static: technology is continually evolving,

leading to changing in-use emission performance. Changes in fuel prices and economic

conditions lead to changes in vehicle sales and travel patterns. A substantial effort is required to

accurately quantify these factors and to stay current with the influence of all of these factors on

vehicular emission levels.
 3 VMT must usually be disaggregated such that each subset of it can be reasonably represented by a single

emission factor determined by one set of inputs of the types described below. EPA also accepts the trip-based

activity methods described in this document. 

7

3.2.1.1 Vehicle Fleet Activity

It is standard practice in preparing highway vehicle emission inventories to express

vehicle activity in terms of vehicle miles traveled, and the emission factors in units of grams per

mile of travel. Actually, vehicles also emit hydrocarbons while stationary. Estimates of

emission-producing activities that do not involve travel are built into MOBILE4.1. These nonmoving emissions are spread over estimated miles of travel by vehicles of a particular age and

output as an equivalent per mile emission factor. Therefore, EPA will accept VMT as the

measure of local vehicle activity for all inventories required under the Clean Air Act.3

 

VMT can be estimated in several possible ways. Direct observation via traffic counts

(usually at a sample of roadway points with statistical expansion to represent the universe of all

roadways in the area) and highway/transit network models are the more preferred approaches. 

EPA does not recommend reliance on fuel sales data, owner reports, or periodic odometer

surveys as substitutes. The two recommended methods are discussed in Section 3.4.

3.2.1.2 Emission Factors

Emission rates are computed from test measurements of in-use vehicles at various

odometer readings designed to capture two fundamental processes: the baseline emission rate and

the deterioration that takes place as the vehicle ages. Linear regressions are performed on the

data to quantify the level of pollutants emitted by each model year's vehicles. The results are

commonly referred to as the intercept, or zero-mile (ZM), emission rate and the slope, or

deterioration rate (DR), that occurs over each 10,000 mile interval.

3.2.1.3 Fleet Characteristics

The emission factors quantify the performance of individual model year vehicle fleets by

vehicle type. The age distribution, the rate of mileage accumulation and the mix of travel

experienced by each vehicular category can significantly alter the fleet average emission rate. 

While the emission factor models employ national average distributions for each of the factors,

local input is allowed, often encouraged, and, for some inputs, required. Differences between

local and national average distributions can alter the emissions contributions of the individual

vehicle categories.

3.2.1.4 Fuel Characteristics

Emission test measurements are conducted on a standardized test fuel known as Indolene. 

The characteristics of this fuel are well defined and ensure that test results are repeatable. Since

consumers cannot purchase Indolene at their local service stations and 
8

differences between the volatility of local fuels and Indolene can influence the level of both

evaporative and tailpipe pollutants, MOBILE4.1 requires local input of fuel volatility.

3.2.1.5 Correction Factors

To ensure the repeatability of measurements, standardized test conditions have been

specified for each vehicle category. They include driving cycle, temperature, humidity, vehicle

load, and the distribution of starting conditions. Since not all vehicle trips match these test

conditions, a series of correction factors has been developed to allow the emission factor model

to account for differences. 

3.2.1.6 Control Programs

Emission factors are based on the performance of vehicles independent of any local

control programs such as I/M, anti-tampering and Stage II refueling. Each of these programs is

designed to reduce the level of pollutants emitted by vehicles operating under in-use conditions. 

Further, differences in program designs can have a significant impact on their effectiveness in

reducing emissions. Therefore, it is important to specify correctly program parameters in order

to estimate correctly their effect on vehicular emissions.

3.2.2 Overview of MOBILE4.1 Input Requirements

MOBILE4.1, EPA's emission factor model, computes separate emission estimates for

eight vehicle categories:

 Light-duty gasoline-powered vehicles (LDGV), i.e., passenger cars;

 Light-duty diesel-powered vehicles (LDDV), i.e., diesel-powered passenger cars;

 Light-duty gasoline-powered trucks, type 1 (LDGT1), i.e., pickup trucks and vans

that have a gross vehicle weight (GVW) of 0 - 6000 pounds;

 Light-duty gasoline-powered trucks, type 2 (LDGT2), i.e., pickup trucks, vans,

and other small trucks that have a GVW of 6001 - 8500 pounds;

 Light-duty diesel-powered trucks, types 1 & 2 (LDDT);

 Heavy-duty gasoline-powered trucks (HDGV), i.e., all vehicles with a GVW

greater than 8,500 pounds, powered by gasoline engines;

 Heavy-duty diesel-powered vehicles (HDDV), i.e., all diesel powered trucks with

a GVW greater than 8,500 pounds; and

 Motorcycles (MC).

There are large differences in the emission characteristics of the vehicles represented by

these categories; therefore, it is important that estimates of local or regional emission rates

incorporate the distribution of VMT by vehicle type.

The emission factors produced by MOBILE4.1 are derived from measurements conducted

under standardized test conditions. For light-duty vehicles, the standard set of test conditions is

referred to as the Federal Test Procedure (FTP). It involves the simulated 
9

operation of a vehicle over a specific driving cycle, the Urban Driving Cycle, under controlled

operating and environmental conditions, during which emissions are measured in three

sequences. The Urban Driving Cycle represents an average trip over an urban network that

includes travel on local and arterial streets, major arterials, and expressways. The basic test

conditions include: 

 Ambient temperature range of 68oF to 86oF;

 Absolute humidity adjusted to 75 grains of water per pound of dry air;

 Average speed of 19.6 mph with 18 percent idle operation;

 Average percent of VMT in cold start operation of 20.6 percent;

 Average percent of VMT in hot start operation of 27.3 percent;

 Average percent of VMT in stabilized operation of 52.1 percent; and

 Average trip length of 7.5 miles.

In order to understand fully the derivation of emission factors and the influence of these

conditions on emission levels, refer to Chapter 2 of the MOBILE4.1 User's Guide. A

condensation of that material is included in Section 3.3 of this report.

MOBILE4.1 inputs can be altered to reflect city-specific conditions. A brief review of

each of the primary options is presented below. They are not organized as they are in the

MOBILE4.1 User's Guide, but rather in the order in which they will be discussed in more detail

later in this chapter.

3.2.2.1 Fleet Characteristics

3.2.2.1.1 VMT Mix

The distribution of travel across the eight vehicle categories determines how the

individual emission factors are weighted to produce a composite emission factor for the entire

highway vehicle fleet. The LDGVs generally comprise over 50 percent of the travel recorded in

any area of the country and, therefore, tend to be the dominant source of highway emissions. 

(HDDVs are an important source of NOx emissions.) MOBILE4.1 will calculate the VMT mix

based on national data characterizing registration distributions, annual mileage accumulation

rates by age, diesel sales fractions, and vehicle counts. These values may not, however, be

representative of certain areas, such as western states where pickup trucks form a larger share of

the vehicle population or rural areas where a broader distribution of vehicles exists. 

3.2.2.1.2 Annual Mileage Accumulation Rates

The primary effect of the rate of mileage accumulation by age (in combination with

registration data) is to determine the relative weighting of each model year's contribution to the

average emission factor computed for each vehicle category. MOBILE4.1 provides the option

of using a national average value or inputting data characterizing local conditions. The rate of

mileage accumulation may be different from national average conditions in both rural and urban

areas at either end of the economic spectrum.
 4 The speed correction factors in MOBILE5 may be significantly revised at speeds above 48 mph. 

10

3.2.2.1.3 Registration Distributions

These are used in concert with mileage accumulation rates to determine the relative

weighting of each model year's contribution to the average emission factor for each vehicle

category. MOBILE4.1 provides the option of using national average values or inputting data

characterizing local registrations. The areas most likely to be distinct from national average

values are rural areas, areas in which cars do not rust out and urban areas at either end of the

economic spectrum. 

3.2.2.2 Fuel Specifications

3.2.2.2.1 RVP

Evaporative and, to a lesser extent, exhaust emissions vary with fuel volatility. EPA's

new vehicle certification program and much of its in-use vehicle testing program use gasoline

with a fuel volatility (RVP) of 9.0 psi. In recent years much of the country has been supplied

with gasoline of higher volatility. MOBILE4.1 adjusts estimated emission factors to account for

the effects of volatility. No national average value for this variable is available in MOBILE4.1; 

one must supply this input. 

3.2.2.3 Correction Factors

3.2.2.3.1 Speed

Emission factors are very sensitive to the average speed that is assumed. In general,

emissions tend to increase as average speeds decrease from the 19.6 mph average FTP speed. 

MOBILE4.1 does not assume an average speed; rather it requires that an estimate of the speed

experienced by vehicles operating in the area and roadway segment or collection of interest be

specified. MOBILE4.1 adjusts the emission factors for speeds other than 19.6 mph through the

use of speed correction factors. These multiplicative adjustments to the base emission factors

tend to follow a non-linear relationship that increases the emission levels as speeds decline from

19.6 mph and increase beyond 48 mph.4

 

3.2.2.3.2 Temperature

Emissions from mobile sources are significantly influenced by the ambient temperatures

under which they are operating. Temperature has an effect on both the exhaust and the

evaporative emission levels. MOBILE4.1 deals with these effects separately. In general, exhaust

emissions are at a minimum at the temperature specified for the FTP (75o

F), with emissions

increasing as temperature either increases or decreases from that value. No ambient temperature

is assumed by MOBILE4.1. One must be provided as an input to the model. 
 5 "Bag 1" is usually a mix of cold and warmed operation, since, except under very cold ambient conditions, the

505 seconds of driving represented by this bag constitutes a longer period than is needed for the engine and catalyst

to get warm. 

11

3.2.2.3.3 Operating Modes

Emission factors based on FTP measurements are collected for three separate segments,

usually referred to as bags because the vehicle exhaust is collected in three separate teflon bags,

each with differing emissions performance. The three bags correspond to the following modes of

operation: cold start, hot stabilized, and hot start. Bag 1, the cold start mode, reflects conditions

experienced at the beginning of a trip when the engine and the emission control system begin

operation at ambient temperature and are not performing at optimum levels (i.e., the catalyst is

cold and has not reached the "light off" temperature needed to efficiently control emissions

coming from the engine) until part way through the trip.5 The hot start mode, Bag 3, reflects the

condition of an engine that has been restarted after being turned off for 10 minutes and, therefore,

has not cooled to ambient conditions. Under this circumstance the engine and catalyst are warm

and, although not at peak operating efficiency when started, still have significantly improved

emissions performance relative to the cold start mode. Bag 2, the hot stabilized mode, reflects

the condition of the engine when the vehicle has been in continuous operation long enough for all

systems to have attained stable operating temperatures. The proportion of VMT accumulated in

cold and hot start modes must be specified based on the conditions in the area to be modeled. 

Specifications must be made for catalyst and non-catalyst vehicles separately. 

3.2.2.3.4 Minor Correction Factors

This category has been added to cover the effects of four special correction factors that are

available:

 Air conditioning;

 Extra vehicle loading;

 Trailer towing;

 NOx humidity.

These factors are designed to account for the effect of unusual vehicle operating

conditions relative to those experienced in the FTP. Generally, it is difficult to quantify the

extent of these vehicle operating parameters, and their effect on emission factors tends to be

small. Therefore, EPA recommends that few resources be expended to develop the inputs

needed. The effect of the NOx humidity correction factor is also slight, and, unless NOx is of

particular concern, little effort should be devoted to its use.
12

3.2.2.4 Tampering and Misfueling

The basic emission factors in MOBILE4.1 receive an adjustment to account for estimates

of vehicle tampering rates as a function of accumulated mileage for each gasoline-fueled vehicle

category and eight categories of tampering (e.g., air pump disablement, misfueling, etc.). These

rates are combined with offsets (the increase in emissions that results from the given type of

tampering) and added to the non-tampered emission factors. Options are available to input local

tampering rates. The use of local information must be supported by an approved survey. If

locally developed information is not available, a national average rate will be used by

MOBILE4.1.

3.2.2.5 Control Programs

3.2.2.5.1 Refueling Emissions

The refueling of gasoline-fueled vehicles results in the displacement of fuel vapor from

the vehicle fuel tank to the atmosphere. 

There are two basic approaches to the control of vehicle refueling emissions, generally

referred to as "Stage II" (at the pump) and "onboard" (in the vehicle) vapor recovery systems. 

MOBILE4.1 can model refueling emissions with no controls as well as with either or both of the

control options.

3.2.2.5.2 Inspection and Maintenance Programs

Many areas of the country have implemented I/M programs as a means of further reducing

mobile source air pollution. MOBILE4.1 can model the impact of an operating I/M program on

the calculated emission factors. There is no average national I/M program; local inputs must be

supplied. Details are given in Section 3.3.6.2 of this document and in the MOBILE4.1 User's

Guide. 

3.2.2.5.3 Anti-Tampering Programs (ATPs)

Some areas of the country have implemented these programs to reduce the frequency and

related emission impacts of emission control system tampering. MOBILE4.1 allows the effects

of such a program on the calculated emission factors to be estimated. Due to the wide variation

in the characteristics of ATPs and the lack of a national program, there is no national average

estimate of ATP parameters. Details of the required inputs are given in Section 3.3.6.3 of this

document and in the MOBILE4.1 User's Guide.

 
 6 This section is in part a condensation of material that appears in the User's Guide to MOBILE4.1, Chapter 2. It

is not a substitute for the User's Guide. You are advised to obtain and thoroughly read the User's Guide before

running the model. It is available from the National Technical Information Service (NTIS), 5285 Port Royal Road,

Springfield, VA 22161 (703/487-4650). The NTIS accession number is PB91-228759.

 7 Highway vehicle emission factors and emission inventories for non-attainment areas in California may be

developed using the EMFAC model.

 8 While future year inventories are discussed in this document, MOBILE4.1 should not be used for projecting

VOC or NOx emissions beyond January 1, 1994, since it does not reflect new standards that begin to have an effect

after that date. MOBILE4.1 may be used for CO inventory projections. MOBILE5 will be released in final form in

August, 1992 and will allow VOC and NOx projections.

 9 A deterioration rate is the gram per mile increase in emissions per 10,000 miles accumulated mileage.

13

3.3 GUIDANCE ON SELECTING MOBILE4.1 INPUTS6

MOBILE4.1 may be used to develop highway vehicle emission factors and emission

inventories for use in the State Implementation Plan process.7 The proper version of

MOBILE4.1 to use in preparing SIP inventories is the one dated November 4, 1991. Older

versions should be discarded or erased.8

This section contains EPA's recommendations and suggestions with regard to

determining appropriate MOBILE4.1 inputs. However, for many inputs there is no single correct

answer or recommendation that is best for every local area. For those using MOBILE4.1 for

SIP-related modeling purposes, it is important that the appropriate EPA Regional Office

personnel be kept involved in decisions concerning questionable or controversial assumptions in

the MOBILE4.1 modeling and inventory development process. 

3.3.1 Emission Factors

Description

The basic emission rates (BERs) used in MOBILE4.1 are expressed as linear equations

and consist of a zero-mile level and one or two deterioration rates.9 There are different BER

equations in MOBILE4.1 for each vehicle type/pollutant/model year group, with the model year

groups defined on the basis of applicable emission standards and emission control technologies

used.

Although MOBILE4.1 provides the capability to change the BER equations, the BERs in

MOBILE4.1 accurately reflect all promulgated emission standards as of late 1990, and no

locality-specific changes to these equations are warranted for use in developing emission factors

or inventories for calendar years through 1992. Specifically, no need exists for modification of

the BERs in MOBILE4.1 in order to develop emission factors for the development of base year

1990 emission inventories by the states in response to the requirements of the Clean Air Act.
 10 EPA expects to update the model to version 5.0 to incorporate all of the requirements of the November 1990

CAA in time for states to project mobile source HC and NOx emissions and demonstrate attainment of the National

Ambient Air Quality Standard for ozone.

 11 A list of those counties EPA has designated as high-altitude appears in §86.088-30, paragraphs (a)(5)(ii) and

(iv), Code of Federal Regulations.

14

Guidance

No need exists for modifying the BERs in MOBILE4.1 in order to develop VOC or NOx

emission factors for any calendar year through 1992 inclusive,10 or to develop CO emission

factors for any calendar year through 2020.

 

3.3.1.1 Region

Description

MOBILE4.1 provides two options for region: low-altitude and high-altitude. Lowaltitude emission factors are based on conditions representative of approximately 500 feet above

mean sea level (+500 ft MSL), and high-altitude factors are based on conditions representative of

approximately +5500 ft MSL. MOBILE4.1, like MOBILE4, does not calculate California

emission factors. There have been no revisions to this variable or how it is input to the model

since the release of MOBILE4.

Guidance

For the majority of MOBILE4.1 applications, low-altitude is the appropriate choice. For

those areas designated as high-altitude by EPA for mobile source regulatory purposes, generally

those counties that lie "substantially" above +4000 ft MSL, high-altitude should be selected.11

 

3.3.1.2 Calendar Year

Description

The value used for calendar year in MOBILE4.1 defines the year (as of January 1) for

which emission factors are to be calculated. It is frequently referred to as the calendar year of

evaluation. MOBILE4.1 has the ability to model emission factors for the years 1960 through

2020 inclusive. There have been no revisions to this variable or how it is input to the model

since the release of MOBILE4.
 12 For example, if most exceedances of the ozone National Ambient Air Quality Ozone Standard occur during

the months of June, July, and August, then the appropriate base year emission factor is the average of the January 1,

1990 and January 1, 1991 emission factors.

 13 Since the accuracy gained by interpolating for typical summer days other than July 1st is minimal and since

the AIRS/AMS mainframe version of MOBILE4.1 for VOC and NOx inventories automatically generates July 1

emission factors, EPA will accept 1990 VOC and NOx emissions estimates based on July 1st emission factors. 

Areas preparing draft 1990 inventories may select an input of January 1, 1990 for their ozone season inventory and

note this prominently in the documentation. However, the inventory must be switched to a July 1, 1990 basis for

the final submission to EPA.

 

 14 January 1st and July 1st evaluations only differ in that the July 1st vehicle fleet is composed of more of the

latest model year vehicles and fewer of the 25th and older model year vehicles, as a result of new car sales and

scrappage of older vehicles between January 1 and June 30. The January 1 vs. July 1 choice is independent of all

temperature and other vehicle operating conditions, which should represent the appropriate pollutant season. 

15

Guidance

The 1990 base year SIP inventories represent emissions during a typical day in the

pollutant season, most commonly summer for ozone and winter for CO. Thus, base year VOC

inventories should be based on interpolation of the calendar year 1990 and 1991 MOBILE4.1

emission factors.12, 13, 14 

CO SIP inventories should be based on emission factors from January 1990 regardless of

the three-month period for which CO is being modeled. 

Similar instructions apply to the development of Reasonable Further Progress (RFP)

inventories. For modeling of specific episode days, the best results will be obtained by

interpolating exactly to the day being modeled. In attainment demonstrations, it is acceptable to

account for fleet turnover through November 15th of the year being modeled.

3.3.2 Fleet Characteristics

3.3.2.1 Vehicle Miles Traveled Mix by Vehicle Type

Description

The vehicle miles traveled mix specifies the fraction of total highway VMT that is

accumulated by each of the eight regulated vehicle types. The VMT mix is used in MOBILE4.1

only to calculate the composite (all vehicle) emission factor for a given scenario on the basis of

the model's eight vehicle class-specific emission factors.
 15 Total HDDV registrations and annual mileage accumulations are also distributed within the model by truck

weight class.

 16 Highway functional systems are commonly designated as the interstate system, other freeways and

expressways, other principal arterials, minor arterials, and collectors.

 17 Ozone and carbon monoxide non-attainment areas classified as marginal, submarginal, or transitional may use

the MOBILE4.1 default VMT mix if no local estimate is readily available. 

 18 "Techniques for Estimating MOBILE2 Variables" and "Additional Techniques for Estimating MOBILE2

Variables," Energy and Environmental Analysis, Inc. for EPA (EPA Contract Number 68-03-2888).

16

MOBILE4.1 calculates a typical urban area VMT mix based on national data

characterizing model-year-specific registration distributions and annual mileage accumulation

rates by age for each vehicle and fuel type,15 the fraction of travel by each vehicle type that 

occurs in typical urban areas, and the total number of vehicles of each vehicle type. 

For SIP-related highway vehicle emission inventory development in moderate and above

non-attainment areas, EPA expects states to develop and use their own specific estimates of

VMT by vehicle type and highway functional system.16 VMT fractions based on local estimates

of VMT by vehicle type should be used as input to MOBILE4.1.17

Each VMT mix supplied as input must consist of a set of eight fractional values,

representing the fraction of total mobile source VMT accumulated by each of the eight vehicle

types. All values must be between zero and one, and the eight values must sum to 1.0. There

have been no revisions to how alternate VMT mixes are supplied to the program as input data

since the release of MOBILE4.

Guidance

Techniques for calculating estimated VMT by vehicle type (and thus, total VMT and the

VMT mix fractions) from available data sources are described in Chapter 6 of the report,

Techniques for Estimating MOBILE2 Variables.

18 Metropolitan Planning Organizations (MPOs)

and state Departments of Transportation (DOTs) should also be consulted. Information from

these agencies can be used to determine the proportion of passenger vehicles and light duty

trucks relative to heavy duty trucks by time of day and facility class. These two groups of

vehicles can then be allocated into the eight MOBILE4.1 vehicle classes using the national

default mix within each group provided by MOBILE4.1.

3.3.2.2 Annual Mileage Accumulation Rates and Registration Distributions by Vehicle Type 

 and Age

Description

MOBILE4.1's emission factor calculations rely in part on travel fractions for vehicles of

each given age within a vehicle type, which in turn are based on estimates of the average annual

mileage accumulation by age (first year to 25th-and-greater years of operation) for 
 19 MOBILE4.0 modeled vehicles from age 0 through age 19 with the 20th year representing all vehicles 20 years

and older.

 20 MOBILE4.1 will issue an error warning if vehicles of a certain type and age are registered but do not

accumulate mileage. A warning will also be issued if there are no vehicles of a certain type and age yet the mileage

accumulation distribution includes a positive value for that category.

 21 If local annual mileage accumulation rates are used, they normally should not change from one evaluation year

to the next.

17

each of the eight vehicle types, and the registration distributions by age (age 0-1 to age 24 and

25+) for each vehicle type, except motorcycles, for which annual mileage accumulation rates and

registration distributions are only provided for the first to 12th-and-later years of operation (ages

0-1 to 11 and 12+). For all vehicles except motorcycles, this represents an increase in detail from

the 20 years of operation used in MOBILE4.19

To use locality-specific annual mileage accumulation rates by age, a total of 200 input

values is required: the estimated annual mileage accumulated by vehicles of each of the eight

types for each of 25 ages.

To use locality-specific registration distributions by age, a total of 200 input values is also

required. For each vehicle type, a set of 25 values is required to represent the fraction of all

vehicles of the given type that are of a given age.

If both annual mileage accumulation rates by age and registration distributions by age are

supplied, the annual mileage accumulation rate corresponding to any vehicle type/age

combination accounting for a non-zero fraction of registrations must be positive. That is, if

vehicles of a certain type and age are registered, then they are assumed to be driven.20

If locality-specific mileage accumulation rates and/or registration distributions by age are

not used, the information in MOBILE4.1 is used for all calendar years evaluated.

Guidance

Mileage Accumulation

EPA recommends the use of the national annual mileage accumulation rates by age that

are included in MOBILE4.1. Most local sources of data on mileage accumulation rates by age

are subject to sampling bias or data entry errors, and the use of such data should be approached

with caution. States that wish to use alternate mileage accumulation rates in their development

of highway vehicle emission inventories in response to the requirements of the new CAA should

obtain prior approval from their EPA Regional Office before using such rates in their emission

factor modeling.21
 22 Marginal, sub-marginal, and transitional non-attainment areas may use the MOBILE4.1 distributions for all

vehicle types, if local distributions are not available. 

 23 Registration distributions by age may be developed from data available through state motor vehicle

registration records, either directly or commercially through R.L. Polk Company. 

 24 Effectively, the routine will apply a scrappage curve to the existing 1990 registration distribution. The result

will be that the pattern of high and low vehicle sales will propagate down the registration distribution as vehicles

age with successive evaluation years.

 25 EPA will not accept a locally developed registration distribution that implies that the average age of the

vehicle fleet is becoming younger in the future than is reflected in the registration distribution used for the base year

unless the state provides adequate justification for the new distribution .

 26 "Techniques for Estimating MOBILE2 Variables" and "Additional Techniques for Estimating MOBILE2

Variables," Energy and Environmental Analysis, Inc. for EPA (EPA Contract Number 68-03-2888).

18

Registration Distributions

EPA recommends and encourages the use of actual locality-specific 1990 registration

distributions by age to develop base year SIP emission inventories.22, 23 Local registration

distributions are particularly appropriate for those inventory areas where there are significant

differences from the national average. The exception to the use of local data would be in those

areas that have relatively few local HDDV registrations, but that experience significant interstate

trucking activity. Such areas may want to retain and use the MOBILE4.1 national registration

distributions. 

EPA will issue at a later date additional guidance on how 1990 registration distributions

by age can be adjusted to reflect future years. This guidance will provide a mathematical routine

that preserves the average age of the fleet in 1990, while retaining the general shape of the local

distribution for 1990 and earlier model years.24, 25

Methods for estimating the annual mileage accumulation rates by age and the registration

distributions by vehicle type and age are presented in Chapters 2 and 3, respectively, of the report

Techniques for Estimating MOBILE2 Variables.

26

3.3.2.3 Trip Length Distribution

Description

Running loss emissions are a form of evaporative volatile organic compound (VOC)

emissions that occur while the vehicle is being operated. Running loss emissions are different

from "traditional" evaporative emissions that occur after the vehicle has been driven (hot soak

evaporative emissions) and while it is parked during periods of rising ambient temperatures

(diurnal evaporative emissions). MOBILE4 was the first version of the emission factor model to

account for these emissions. In MOBILE4.1 estimates of running loss emissions have been

extensively revised.
 27 "Length of trip" as used here refers to the duration of the trip (how long, in minutes, the vehicle has been

traveling), not on the distance traveled in the trip (how far the vehicle has been driven). 

19

EPA has determined through its running loss emission test programs that the level of

running loss emissions depends on several variables: average vehicle speed, ambient

temperature, fuel volatility, and the length of the trip.27 Test data show that for any given set of

conditions (average speed, ambient temperature, and fuel volatility), running loss emissions are

zero to negligible at first, but increase significantly as trip duration lengthens.

In MOBILE4, running loss emissions were modeled as direct functions of the input

temperature and volatility; average speed and trip duration were held constant within the model

to values representative of typical urban area traffic patterns. In MOBILE4.1 running loss

emissions are modeled as a direct function of the input temperature, fuel volatility, average speed

and trip duration. 

The input data record of the VMT-weighted trip duration distribution must list the fraction

of all travel (VMT) being accumulated over the time period that the emission factors apply:

 Under 10 minutes

 11 to 20 minutes

 21 to 30 minutes

 31 to 40 minutes

 41 to 50 minutes

 51 minutes and longer

Note that the first value should be the fraction of VMT that occurs in trips that end within

10 minutes of their start, not the fraction of VMT that occurs within 10 minutes of trip start for

longer trips. The other values are defined similarly. Note also that the running loss emission

factor that is calculated by MOBILE4.1 is a fleet and area-wide average that applies to all of the

VMT in all of the trips for each vehicle type. Any geographic disaggregation by VMT density

will be only approximate. Situations more heavily affected by emission rates at the end of trips,

such as a central business district in the morning rush hour, are more complex to model. EPA

staff should be consulted in such cases.

If this option of specifying trip length distributions is not selected, then MOBILE4.1 will

calculate the running loss emission factors on the basis of the typical trip duration included in the

model.

Guidance

Since reliable local data on the distribution of trip durations is often unavailable, EPA will

accept the use of the model's typical distributions for the estimation of running loss VOC

emission factors for the 1990 emission inventory. Where the transportation modeling process 
 28 The use of trip length distributions other than those included in MOBILE4.1 should be adequately documented

in the SIP. 

 29 LDV diesel sales accounted for less than 0.05% of total LDV sales in the 1988-1990 model years.

 

 30 Diesel sale fractions apply only to LDVs and LDTs. Heavy duty gasoline and diesel vehicles are treated

separately within the MOBILE models.

20

can produce reliable inputs for trip duration, use of such inputs will produce a more accurate

estimate of the benefits attributable to SIP measures which shorten average trip lengths without

eliminating entire trips.28 

Most SIP inventories will be constructed by adding together emission estimates for

several functional classifications of roadway. EPA recommends that one area-wide trip length

distribution be used for all roadway classifications, due to the complexity of trying to develop

separate distributions. 

3.3.2.4 Diesel Sales Fractions

Description

Sales of diesel powered light-duty vehicles and trucks underwent a surge in the late 1970s

and early 1980s, peaking at 5.9% of LDV sales in the 1981 model year, and at 9.3% of LDT

sales in the 1982 model year. Since then diesel sales have fallen precipitously, to virtually zero

for LDVs29 and to about 0.2% of LDTs since the 1988 model year. While MOBILE4 contained

forecasts of increasing diesel sales for both LDVs and LDTs through the early 1990s,

MOBILE4.1 assumes a more limited and slower increase from the current, very low diesel sales

rates. MOBILE4.1 assumes that future LDV diesel sales never exceed 0.3% and that future LDT

sales never exceed 2.15%.

MOBILE4.1, like earlier versions of the model, uses a single set of registration

distributions by age and annual mileage accumulation rates to describe all LDVs, and another set

to describe all LDTs. This is due in part to the fact that it is nearly impossible to develop such

information for gas and diesel LDVs and LDTs separately, and in part since there is little

evidence to suggest that typical use patterns and mileage accumulation rates are different for gas

and diesel LDVs and for gas and diesel LDTs.

Diesel sales fractions represent the share of all sales30 in a given model year that are

diesel-fueled vehicles. The use of model-year-specific diesel sales fractions allows MOBILE4.1

to internally split the LDVs and LDTs into gas and diesel sub-categories, which have distinctly

different emission rates.

If vehicle registration data that distinguish between gas and diesel LDVs and gas and

diesel LDTs exist, it is possible to input local diesel sales fractions by model year. These data

must be supplied for every calendar year of evaluation; since they apply to vehicles of 
 31 A vehicle is assumed to be one year old if the model year of that vehicle is the same as the evaluation year. 

Thus, a 1990 model year vehicle is assumed to be one year old in 1990. Similarly, a 1989 model year vehicle is

assumed to be two years old in 1990.

 32 EPA does not envision any circumstances in which a state or locality should substitute its own projection of

future diesel sales for that built into MOBILE4.1. 

21

ages 1, 2, 3, ..., to 25-and-older, different sets of fractions are required for each calendar year. 

Including this information will create a more accurate highway mobile source emission inventory

estimate. 

For each scenario, the fractions of LDV and of LDT sales that were diesel for each model

year from the calendar year of evaluation back to 25 model years ago must be entered as a model

input. For example, if the calendar year of evaluation is 1990, then diesel sales fractions for

model year 1990, 1989, 1988, ..., 1967, and 1966-and-older LDVs and LDTs must be provided. 

If two different scenarios are being run, both for calendar year 1990 but with other differences,

then the same set of diesel fractions would have to be supplied again as part of the second

scenario. If a scenario with calendar year 1995 was also being run, then the diesel sales fractions

would represent model year 1995, 1994, ..., 1972, and 1971-and-older vehicles. The same values

would be used for the model years in common to the two sets of sales fractions, but the five

oldest model year values would not be used in the second sequence to make room for the five

most recent model years sales fractions. 

The 50 diesel sales fractions, 25 each for LDVs and LDTs, must be specified as fractions. 

For example, if in a given area the 1990 model year had diesel sales of 1.1% of LDVs and 1.8%

of LDTs, the diesel sales fractions are 0.011 and 0.018 respectively. The values are supplied in

pairs: The first two values on the first record are the diesel sales fractions for one year old LDVs

and LDTs;31 the second two values are the sales fractions for two year old LDVs and LDTs, and

so on, with the last two values on the third record being the sales fractions for LDVs and LDTs

25 years and older.

Guidance

This option has been provided in MOBILE4.1 for two reasons. First, some users

performing highway vehicle emission factor modeling may have access to vehicle registration

data, or data from other sources, enabling them to characterize diesel sales of LDVs and LDTs in

the area being modeled. Particularly if these sales fractions differ significantly from those

included in MOBILE4.1, it will enhance the accuracy of the emission factors and inventory to

use those sales fractions as model input. Second, as can be seen by the sharp rise and equally

sharp fall of diesel sales in the late 1970s and early 1980s, it is extremely difficult to forecast

diesel sales fractions for future model years. This provision will allow modelers to account for

future increases in diesel sales, if such increases occur.32 
 33 High RVP fuel is used in the winter months to facilitate vehicle starting. If the same high RVP fuel were used

in the summer, a vehicle could experience vapor lock and stall. 

 34 EPA will also accept the use of RVP determined from either of two regularly published gasoline volatility

surveys, one performed by oil companies and compiled by the National Institute for Petroleum and Energy

Research (NIPER) and the other sponsored by the Motor Vehicle Manufacturers' Association (MVMA) and

conducted by the Southwest Research Institute (SwRI). Since the NIPER survey is not city-specific, the MVMA

survey is the preferred choice. 

 35 A third survey is sponsored by a consortium of oil companies, the American Petroleum Institute (API), and is

also conducted by Southwest Research Institute. This survey includes more cities and sampling months, but the

data from it are proprietary. 

 36 A final possible source of RVP data is the sampling done by some states to enforce their state RVP limits. 

However, before using this approach, it should be discussed with EPA to determine if RVP data collected for

enforcement purposes are suitable for determining average RVP for inventory purposes. 

22

3.3.3 RVP Determination

Description

The basic emission rates that underlie the emission factor calculations are developed from

vehicles tested at FTP conditions, including a fuel volatility of 9 psi Reid Vapor Pressure (RVP). 

For other fuel volatility levels, MOBILE4.1 adjusts the emission factors for exhaust and

evaporative emissions as well as for running loss, resting loss, and refueling loss emissions.

Vehicle emission rates increase as the volatility of the fuel increases, for temperatures

between 45OF and 75OF and for RVP values between 9.0 and 11.7 psi. This effect is most

pronounced at higher RVP levels and at higher ambient temperatures. Since there is a significant

interaction effect between RVP and temperature, it is important that RVP and temperature inputs

to MOBILE4.1 be consistent. That is, RVP and temperature should be chosen in such a way that

they represent the same time period.33 In general, use July 1990 RVP levels to estimate VOC

and CO emissions during the ozone non-attainment season . Use January 1990 RVP levels to

estimate CO emissions during the CO non-attainment season.

Guidance

Gasoline survey data should be used to determine historical RVP, if quality-assured

survey data are available. The survey samples should be drawn at the pump, not "upstream" of

the pump at a refinery or fuel distribution terminal.34, 35, 36
 37 The data reflected in MVMA National Gasoline Survey are generally collected as of January 15th and July

15th.

 

 38 If no city from the inventory area is included in the MVMA survey, use the RVP for a city that is both

geographically close to the city with the largest population within the inventory area and that was subject to the

same EPA, state, or ASTM volatility limit at the time. If fuel distribution patterns are known, give preference to a

survey city with the same distribution system. 

If the RVP for outlying areas of a state is desired (for example, to complete the inventory for the fringes of an

Airshed modeling domain) and a city within that state is included in the MVMA survey, use the RVP for that city. 

If two or more cities in that state are included in the MVMA survey, average the RVPs from those cities. If no city

within the state is included in the MVMA survey, use the RVP for a city that is both geographically close to the

state and that was subject to the same EPA, state, or ASTM volatility limit at the time. If fuel distribution patterns

are known, give preference to a survey city with the same distribution system.

 

 39 As the use (and market share) of regular leaded fuel continues to decline, survey values for mid-grade

unleaded are replacing those for regular leaded.

23

Procedure for Determining RVP Using the MVMA Survey

Obtain the appropriate edition of the MVMA National Gasoline Survey, published semiannually37 by the Motor Vehicle Manufacturers' Association. Ordering and price information is

available from:

Motor Vehicle Manufacturers' Association

300 New Center Building

Detroit, MI 48202

Phone (313) 872-4311

Use the summer MVMA survey to estimate VOC and CO emissions during the ozone

non-attainment season. Use the winter MVMA survey to estimate CO emissions during the CO

non-attainment season.

If the average RVP for a specific city is desired and that city is included in the MVMA

survey, use the RVP for that city.38 

Find the average RVP value(s) for the city or cities selected from the summary table that

appears near the end of the MVMA survey. The average RVP for regular unleaded gasoline is

provided for all cities; the average RVP for premium and/or mid-grade unleaded and/or regular

leaded gasoline is also provided for many cities. Ignore RVP values for any ethanol blends that

may also be listed.39

 

Calculate the overall average RVP from the averages supplied for different grades of

gasoline as follows:
24

 If only the average RVP for regular unleaded gasoline is provided, use that value;

 If the average RVP for regular unleaded and one of the other fuel grades (premium

unleaded, mid-grade unleaded, or regular leaded) is provided, weight the values using

the local sales mix, if known, or at 75 percent regular unleaded and 25 percent of the

other grade for which the RVP is provided, according to equation 3-1.

Average RVP = 0.75  (average RVP of regular unleaded) + 

0.25  (average RVP of premium unleaded or mid-grade unleaded or 

regular leaded)

(3-1)

 If the average RVP is provided for three fuel grades, weight the values, using

the local sales mix, if known, or at 50 percent regular unleaded, 25 percent premium

unleaded, and 25 percent mid-grade unleaded or regular leaded, according to equation

3-2.

Average RVP = 0.50  (average RVP of regular unleaded) +

0.25  (average RVP of premium unleaded) +

0.25  (average RVP of mid-grade unleaded or regular leaded)

(3-2)

If the average RVP is provided for all four fuel grades, weight the values using the local

sales mix, if known, or at 50 percent regular unleaded, 20 percent premium unleaded, 20 percent

mid-grade unleaded, and 10 percent regular leaded, according to equation 3-3.

Average RVP = 0.50  (average RVP of regular unleaded) +

0.20  (average RVP of premium unleaded) +

0.20  (average RVP of mid-grade unleaded) +

0.10  (average RVP of regular leaded)

(3-3)

The RVP thus calculated is used as the value of historical RVP in MOBILE4.1.

Procedure for Determination of RVP Using the NIPER Survey

Obtain the appropriate edition of the report Motor Gasolines, published semi-annually by

NIPER. Samples for the summer survey are taken in June, July, and August. Samples for the

winter survey are taken in December, January, and February. 
 40 Ignore RVP values for any ethanol blends that may be listed. 

 41 Historically, fuel volatility was subject to voluntary limits according to ASTM Standard D439, "Standard

Specification for Automotive Gasoline." More recently, fuel volatility has been subject to federal and/or state

regulatory requirements. 

25

The cost per report is $60, and it is available from:

Cheryl L. Dickson

National Institute for Petroleum and Energy Research

P. O. Box 2128

Bartlesville, OK 74005

Phone (918) 336-2400

Use the summer NIPER survey to estimate VOC and CO emissions during the ozone nonattainment season. Use the winter NIPER survey to estimate CO emissions during the CO nonattainment season.

The NIPER survey divides the country into seventeen districts, which are described in a

table and illustrated on a map of the U.S. Use the district in which the inventory area is located. 

If the RVP for an entire state is desired and that state lies entirely within one district, use that

district. If the state lies within two or more districts, average the RVPs from the districts within

which the state lies.

Table 4 of the NIPER survey presents the average RVP of three grades of gasoline for

each district: regular unleaded, regular leaded, and premium unleaded.40 

Determine the overall average RVP of gasoline in a district by weighting these three

values by the local sales mix, or, in the absence of local data, by an assumed sales mix of 50

percent regular unleaded, 25 percent premium unleaded and 25 percent regular leaded according

to equation 3-4.

Average RVP = 0.50  (average RVP of regular unleaded) +

0.25  (average RVP of premium unleaded) +

0.25  (average RVP of regular leaded)

(3-4)

The calculated RVP (or the average of the calculated RVPs, if the area for which the RVP

is being determined resides within two or more districts) is then used as the value of historical

RVP in MOBILE4.1.

Procedure for Determining RVP from Applicable RVP Limit

For an area without its own survey data and for which it is not possible to use a city or

district for which survey data exist, RVP can be determined from the applicable RVP limit41

adjusted by either a non-compliance margin or a compliance safety margin. Where ASTM 
 42 The non-compliance margin is always positive; the compliance safety margin is always negative.

 43 "Period 1" RVP was called base or pre-control RVP in MOBILE4; "period 2" RVP was called in-use RVP in

MOBILE4.

 44 MOBILE4.1 assumes this change to occur as of January 1 of the specified calendar year.

26

limits were the applicable limit, average RVP often exceeded the ASTM limit (non- compliance

margin) by an amount that varied with the year and the ASTM limit itself. On the other hand,

gasoline regulated by EPA or state RVP limits usually has had an average RVP below the EPA

or state ceiling. 

To estimate RVP using the "limit" approach, apply the historical margin to the applicable

limit according to equation 3-5. 

RVP = Applicable Limit + Margin (3-5)

where

Applicable Limit = Federal or state regulatory limit, or, if none applies,

ASTM standard for state and month for which an inventory is

being estimated;

Margin = Non-Compliance Margin, if average RVP is greater than the 

applicable limit, or Compliance Safety Margin, if average RVP is

less than the applicable limit.42

3.3.3.1 EPA-Provided 1990 RVP Estimates

For states that do not wish to apply one of the above methods themselves, EPA will post

the 1990 RVPs recommended for use in modeling mobile source HC, CO, and NOx emissions on

a typical summer day and the RVPs recommended for use in modeling mobile source CO

emissions on a typical winter day on the Chief Bulletin Board System maintained by the Office

of Air Quality Planning and Standards.

3.3.3.2 "Period 1" RVP and "Period 2" RVP43

MOBILE4.1 requires two RVP inputs, one for "period 1" and one for "period 2". The

purpose of having two RVP inputs is to allow a step change in fuel volatility as of a specific

calendar year.44 
 45 To model the effects of the Federal volatility control program promulgated by EPA, in which volatility is

limited in the summer months (May - September), see the relevant Federal Register notices (54 FR 11868, March

22, 1989; 55 FR 23658, June 11, 1990), or contact an EPA Regional Office to determine the applicable RVP limits

for a specific State and month. The interim (Phase I) controls were in effect during 1989, 1990, and 1991, and the

final (Phase II) controls took effect during 1992.

 46 The 1990 base year SIP inventories represent emissions during a typical day in the pollutant season, most

commonly summer for ozone and winter for CO. The procedure for choosing typical day temperatures is described

in section 3.3.5.2. 

 47 For attainment demonstrations, states should use temperature and RVP values that reflect the conditions of the

specific episodes being modeled. 

 48 MOBILE4.1 does not model effects of RVP on emissions at temperatures of less than 450

 F (70 C), nor does it

model effects of RVP greater than an in-tank (weathered) level of 11.7 psi. Under summer temperature conditions

an in-tank RVP of 11.7 psi corresponds to a dispensed fuel RVP of approximately 12.5 psi. 

27

The value to be used for the "period 1" RVP is the average in-use RVP of gasoline in

either the time before a volatility control program took effect or the years preceding a change in

the controlled RVP level such as will take effect for most areas in 1992 when EPA's Phase I

volatility control limits are superseded by the Phase II volatility control limits.45 Period 1 RVP

can be between 7.0 psi and 15.2 psi inclusive. "Period 2" RVP can be between 6.5 and 15.2 psi

inclusive. The earliest allowed "period 2" start year is 1989. 

There have been no revisions in the input of these two variables since the release of

MOBILE4; only the names of these variables have been changed. 

3.3.3.3 Interpolation

If emission factors are being calculated on a month-by-month basis, or if the consecutive

three-month period with the highest frequency of NAAQS exceedance days occurring in the

inventory area is some period other than June, July, and August for ozone modeling or

November, December, and January for carbon monoxide modeling, the RVP appropriate to each

of the specific months being modeled should be used. The July RVP value may be used for the

entire period of the EPA RVP control program (May through September). For periods other than

the period of EPA's control program, it is not correct to average RVP values from different

months or seasons together, and it may be incorrect to use RVP from a time period other than

that used to determine the temperatures input to MOBILE4.1.46, 47, 48

 

3.3.3.4 Inputs for Future Year RVP

3.3.3.4.1 Future Summer RVP

All parts of the United States will be subject to more stringent EPA summer RVP limits

beginning in 1992, with the highest limit being 9 psi. The 1992 summer survey data may not be

available in time to prepare draft or final inventories for 1996 and beyond. Also, 
 49 Alternatively, the default margin of 0.3 psi may be assumed. 

28

since 1992 is the first year of the "Phase II" volatility regulation, it may not be representative of

long-term RVP levels. ASTM Class A and B areas will have a limit of 7.8 psi. To forecast

future RVP, each area should determine its compliance safety margin in 1990 and/or 1991

relative to the 1990 EPA or state limit (ranging from 9.0 to 10.5). This margin should be

subtracted from the future EPA or state limit, if that limit is 9.0. Areas without 1990 or 1991

survey data should subtract a default compliance safety margin of 0.3 psi. Areas with a 1990/91

limit of 10.5 psi and a safety margin significantly greater than 0.3 (which may have been the

result of distribution of fuel intended to comply with a 9.0 limit in nearby areas, or which may be

the result of other unique circumstances) should consult with EPA. It may be appropriate to use

the 0.3 psi default, rather than the 1990/91 compliance safety margin for future years. Areas with

a 9.0 limit in 1990/91 which also observed a safety margin significantly in excess of 0.3 psi

should also consult with EPA as to the representativeness of the surveys involved. 

Areas with a future summer RVP limit of 7.8 should, in general, not assume a safety

margin, since RVP reductions below 7.8 psi are more costly than those below 9.0 psi, and loss of

RVP between refinery and pump will be lower. However, if an area subject to the 7.8 psi limit in

1992 determines that a safety margin does exist in 1992 based on quality assured survey data, it

may request that EPA review 1992 summer MVMA and/or API survey data from several cities

to support its claim. 

3.3.3.4.2 Future Winter RVP

There are no plans for EPA to establish winter RVP limits. If there are no state standards

for future winter RVP or if they are the same as the state limit in 1990/91, the 1990/91 winter

RVP input should be used for future years. 

If a state is tightening its winter RVP limit from a limit actively enforced in 1990/91, the

1990/91 RVP compliance safety margin should be applied to the future limit. If no margin was

applied in the 1990/91 inventory, none should be applied for the future year.

If a state is establishing a winter RVP limit where no limit or only an ASTM limit (not

backed by state law including active enforcement) applied in 1990/91, the safety margin relative

to the new limit should be the limit calculated from the 1990/91 (or more recent) summer

survey.49
 50 Reductions in exhaust CO emissions are estimated for gasoline-fueled vehicle types (LDGV, LDGT1,

LDGT2, HDGV, and MC). No effects on exhaust VOC or NOx emission factors or on any of the evaporative

components of VOC emissions are currently modeled with the exception that, if the oxygenated fuels have a higher

volatility than base gasoline in an area, exhaust and evaporative emissions will be increased to reflect the increased

volatility of the oxygenated fuels. MOBILE5 will contain adjustments for exhaust HC.

 51 Gasoline/ether blends are assumed to have the same RVP as gasoline, indicated by the regular RVP value

input.

 52 If, together, ethanol blends account for less than 2% of total gasoline sales within an inventory area, and if

there is no mandatory or locally endorsed voluntary program for ether blends, oxygenated fuels need not be

explicitly modeled for the 1990 base year inventory. Market shares for ethanol blends are readily available by state. 

 53 There have been no recent significant sales of other oxygenated blend types (e.g., gasoline/methanol). 

29

3.3.4 Oxygenated Fuels

Description

MOBILE4.1 can model the effects of two types of oxygenated fuels, gasoline/alcohol

blends and gasoline/ether blends, on exhaust carbon monoxide (CO) emissions50 provided that

the following information is input:

 Ether blend market share (as a fraction);

 Average oxygen content of ether blend fuels (percent weight, expressed 

as a fraction);

 Alcohol blend market share (as a fraction);

 Average oxygen content of alcohol blend fuels (percent weight, 

expressed as a fraction);

 RVP waiver. (If oxygenated fuels must meet the same RVP limits as 

gasoline, this indicator is set to 1; if such fuels have been granted a 1.0 

psi waiver, this indicator is set to 2.51)

Guidance

Areas that are known to have significant market penetration52, 53 of ether blends and/or

alcohol blends should characterize the relative market shares and oxygen content of these fuel

blends and account for them in their mobile source emission inventory. 

EPA should be contacted for assistance in modeling the effects of oxygenated fuels if any

of the following situations apply: 
 54 The speed correction factors in MOBILE4.1 are substantially revised from those in MOBILE4. 

 55 The average speed of the Highway Fuel Economy (HFET) test cycle is approximately 48 mph.

 56 The maximum average vehicle speed allowed in MOBILE4.0 was 55 mph.

 57 Since emissions are a non-linear function of speed, with significant curvature at low and high speeds, total daily areawide emissions are to some degree incorrectly estimated if VMT "events" occurring at significantly different speeds are

averaged together. 

30

 the fuels available in an area include blends containing both ether(s) and 

alcohol(s) in the same fuel;

 an RVP waiver greater than 1.0 psi is applicable to oxygenated fuels in an area;

 no RVP waiver is in effect, but the volatility of base gasoline is currently 

below the regulated limit (in this situation, the practical effect may be same as 

if a waiver were in effect);

 if two or more types of alcohol blends are marketed under different RVP 

waiver treatment (for example, gasoline/methanol blends might not be given the 

same waiver as gasoline/ethanol blends). 

3.3.5 Correction Factors

3.3.5.1 Speed

Description

There is considerable variation in vehicle emission factors as average vehicle speed

changes.54 In general, however, exhaust emissions are at a minimum at about 48 mph.55 All

emission rates (VOC, CO, NOx) display very high emissions at very low speeds, with emissions

decreasing (sharply at first and then more slowly) as average speed increases, until minimum

emissions are reached at around 48 mph. Above 48 mph, further increases in speed result in

increased emissions.

MOBILE4.1 will calculate emission factors for average speeds of 2.5 to 65.0 mph, in

increments of 0.1 mph.56 One average speed may be used for all vehicles, or a different average

speed may be used for each vehicle type. 

Guidance

Selection of vehicle speeds is a difficult and complex process. Although it is appropriate

for some purposes to use an average speed for all vehicle trips and vehicle types within urban

areas as a whole, such an approach is not suitable for SIP inventory preparation. Instead, VMT

should be left disaggregated into subsets that have roughly equal speed, with separate VOC, CO,

and NOx emission factors for each subset.57 At a minimum, speeds should be estimated

separately by roadway functional class. 
 58 Travel demand models that do not meet the performance and validation requirements for use in forecasting VMT

growth may nevertheless be suitable for deriving speed estimates. However, reasonable efforts and success in validating the

model are still required.

 59 Once link-by-link speeds are determined from speed formulas, the results may be aggregated into functional classes. 

 60 Both documents were prepared for EPA by Cambridge Systematics, Inc. Much of the information contained in the

remainder of this section was taken directly from these documents.

 61 In most metropolitan areas, transportation planners calibrate their highway assignment models to replicate observed

volume levels, treating highway speeds only as tools to obtain good volume estimates rather than as critical outputs in their

own right. In many cities, assignment-predicted speeds are too high to match actual conditions; in some cities, they are too

low.

 62 For those urban areas that can demonstrate that their assignment-predicted link speeds closely match observed speed

data and/or speeds estimated using the Federal Highway Administration's Highway Capacity Manual, the assignmentpredicted link speeds speeds may be used directly in vehicle emissions inventories. 

 63 If the year for which the inventory is being calculated is not the same as one of the years for which the network model

as been run, speeds may be interpolated between chronologically adjacent network model runs. 

31

Travel Demand Network Approach

The recommended approach to estimating speeds is to post-process the output from a local travel

demand network model.58, 59 Two documents that provide guidance on speed estimation for areas using

network models are: Highway Vehicle Speed Estimation Procedures for Use in Emissions Inventories

and A Study of Highway Vehicle Emission Inventory Procedures in Selected Urban Areas.

60 

The primary purpose of speed within a transportation planning model is to allocate travel across

the network. It is used primarily as a measure of impedance to travel rather than as a prediction of

accurate travel times. 

The report, Highway Vehicle Speed Estimation Procedures for Use in Emissions Inventories,

focuses on speed estimation methods that are extensions of traffic assignment procedures. The basic

method presented takes the link-specific traffic estimates provided as an output by a UTPS-type highway

assignment model and calculates speeds based on the estimated highway volume-to-capacity ratios and a

set of speed formulas that are more specific to different road types than the formula built into most

assignment models.61 As such, this method is not as simple as using the direct traffic assignment output

without modification.62 

A second approach to estimating speeds using travel demand network models is to use the output

from traffic assignment directly.63 If the network model assigns traffic to links on the basis 
 64 The capacity restraint method is a common type of traffic assignment algorithm. It is based on the inverse relationship

between speed and congestion. It attempts to model congested speeds during peak conditions for all facility types. As

congestion increases, vehicle operating speeds decrease. The capacity restraint methodology is used as the default formula

in many urban areas' traffic assignment models. 

 65 A potential problem with the use of any single function is that it may not account well for the variations in traffic

operating conditions across all types of links, especially on very congested links. A single formula may be unable to

accurately estimate speed for facility types having very different operating characteristics. A more appropriate procedure

would include separate equations for estimating speed for each facility class for each condition, i.e., peak versus off-peak

travel.

 66 In this case, emission factors are developed for each highway link and multiplied by the VMT on each link to calculate

link-specific vehicle emissions.

 67 Typically, a range would be one or two mph. If this approach is used, emission factors are calculated for the midpoint

of each speed range and multiplied by the associated VMT.

 68 FHWA designates roadway segments separately within urban and rural areas into six functional classes each.

 69 AIRS/AMS is set up according to this approach, with up to 12 roadway classifications and one to four time periods

within a day. 

 70 The start and end times of periods should be locally determined to reasonably separate higher from lower speed traffic

periods.

32

of a capacity restraint algorithm, then the associated link speeds are likely to be more accurate than if

another type of assignment methodology is used.64, 65 However, the unique manner in which the traffic

assignment algorithm manipulates speed for a particular link does not necessarily provide an accurate

estimate of speed for that link but rather provides a value that optimizes the traffic assignment over the

entire congested network. 

Highway Performance Monitoring System (HPMS) Roadway Classification Approach

Post-processing with better speed formulas is often combined with a direct link to the emission

factor model, and link speeds are either used directly as MOBILE inputs66 or grouped into ranges based

on the speed at which VMT occurs on each link.67 

One way to further reduce the number of MOBILE4.1 runs is to use FHWA's Highway

Performance Monitoring System (HPMS) roadway classification scheme to group portions of VMT by

the functional classification of the roadways on which they occur. This results in 12 subsets of VMT.68

Within each subset, speed is weighted by VMT to calculate an average speed and emission factor. 

This disaggregation of VMT by functional system avoids most of the undesirable VMT averaging

that might otherwise cause errors in the emission inventory. Further accuracy improvements can be

obtained by dividing the day into separate time periods so that congested VMT and free-flowing VMT

are not mixed. While two periods are the minimum split to get more homogeneity in vehicle speeds,

more than two periods are possible. Each functional system can, for example, be characterized by four

average speeds during distinct periods of the day: a morning peak period, a mid-day non-peak period, an 

afternoon peak period, and a late evening/night non-peak period.69, 70 Under this approach separate

MOBILE4.1 emission factors are calculated for each 
 71 Inputs other than speed and temperature might also differ by functional system and time of day. The hot/cold mix of

vehicle operation is one example of such an input.

 72 This approach is most worthwhile when a significant portion of the highway network gets much more congested during

part of the day, with considerable VMT in both the congested and non-congested periods. 

 73 The TEMFLG control flag should be set to accomplish this. See the User's Guide to MOBILE4.1, section 2.1.14.

 74 The recommended method of apportioning daily VMT to specific hours is to use the state's continuous monitors

available within the FAUA. If no such monitors exist within the inventory area, then the state may rely on other continuous

monitors located in areas similar in geographic, land use and demographic characteristics, or on those areas' final Airshed

Emission Preprocessor profiles.

 75 Hour-by-hour temperatures should be determined from the 10-worst-days method used to determine the minimum and

maximum temperatures for inventory purposes. See section 3.3.5.2.

 76 SOURCE: Federal Highway Administration, Highway Performance Monitoring System, Impact Analysis for 1989

Base Year.

33

period based on the speeds and temperatures prevailing during the period.71 This approach has most of

the advantages of link-specific hour-by-hour modeling, but requires fewer MOBILE4.1 runs.72 

Estimating emissions for separate time periods within the day also requires that particular

attention be paid to the treatment of the temperature inputs to MOBILE4.1. The sum of the emissions

within the four periods should be logically consistent (except for the effect of the speeds) with that

which would result from using the 24-hour approach. In order to achieve this consistency, the 24-hour

minimum and maximum temperatures should be used to determine diurnal evaporative emissions for

each of the time period-specific MOBILE4.1 runs. 

Ambient temperature, on the other hand, should be set to the VMT-weighted average temperature

of the period in question.73 For example, if the night period extends from 7 pm to 6 am, the temperature

for each of the hours occurring during the night should be weighted by the percent of night period VMT

in each hour.74, 75 

Highway Performance System National Estimates76

If no network model is available, and in marginal and sub-marginal non-attainment areas, the

national speed estimates listed in Table 3-1 may be used. Individual areas may be able to obtain

comparable but locally specific speed estimates through their state DOT or FHWA division office. 

These speeds are calculated from HPMS traffic counts and site-specific speed formulas and are not

actual speed observations.
 77 The maximum temperature must not be less than the minimum temperature. 

34

Table 3-1

Geographic Roadway Autos, Vans All

 Area Functional Classification Pickups Trucks

Rural Interstates 57.3 43.6

Other principal arterials 45.4 36.0

Minor arterials 39.9 33.3

Major collectors 35.1 29.8

Minor collectors 30.5 24.4

Urban Interstates 46.3 39.0

Other freeways and expressways 43.3 36.5

Other principal arterials 18.9 16.0

Minor arterials 19.6 19.6

Collectors 19.6 16.4

Consistency Over Time

Speed estimates for years other than 1990 must be logically related to the 1990

methodology and estimates, with no arbitrary or unsupported assumptions of speed changes. 

3.3.5.2 Temperature

Description

The basic emission rates that underlie the emission factor calculations are developed from

emission data from vehicles tested at FTP conditions, including an ambient temperature of 750F

(240

C). MOBILE4.1 uses temperature correction factors to correct the emission factors for other

temperatures. 

MOBILE4.1 provides temperature correction factors for temperatures in the range of 00F

(-180C) to 1100F (430C). If a temperature below 00F is entered, a warning message is issued, and

00

F is used in the calculations. Similarly, if a temperature above 1100F is entered, a warning

message is also issued, and 1100F is used in the calculations. 

The temperature used to adjust the exhaust emission factors for all three pollutants, the

hot soak component of evaporative emissions, refueling emissions, and resting loss and running

loss emissions can be calculated on the basis of the input minimum and maximum daily

temperatures.77 Alternatively, the model can use a single temperature that represents ambient

conditions at a particular time.
 78 Logically, the single temperature used to represent a typical day must be between a typical day's minimum and

maximum temperatures.

 79 Diurnal emissions are most frequently measured for a temperature range of 68-860

F (20-300C). However,

MOBILE4.1 adjusts diurnal emission rates for the minimum and maximum temperatures provided as input based on

special EPA testing over additional temperature ranges. 

 80 A single ambient temperature can also be used to determine the temperature corrections for exhaust VOC, CO,

and NOx emissions, hot soak evaporative emissions, dispensed fuel temperature in the refueling emissions

calculations, and resting loss and running loss emissions, through the choice of a value for the control flag

TEMFLG (see the "User's Guide to MOBILE4.1," section 2.1.14). This approach is not recommended unless

modeling a short time period, such as an hour. Refueling emissions should always be modeled using the "full day"

approach; hourly temperatures should not be used. Diurnal emissions can only be modeled directly in MOBILE4.1

using the "full day" approach, since the algorithm used is inaccurate over the very small temperature rises (1 to 50

F)

typical of a single hour. 

 81 The algorithm used in MOBILE4.1 to determine temperatures for correcting emissions on the basis of the

input minimum and maximum temperatures takes into account both the typical 24-hour diurnal temperature profile

for a day having the specified minimum and maximum, and the typical distribution of travel over the course of 24

hours. Thus, the emission factors calculated in this way are appropriately weighted for trips, vehicle miles traveled,

and emissions at different temperatures and result in factors that can be multiplied by total daily VMT when total

daily emissions are the desired result.

35

However, even if a single temperature is used as the basis of the temperature correction

factors for all exhaust emissions, hot soak evaporative emissions, refueling emissions, and

resting loss and running loss emissions,78 minimum and maximum daily temperatures will still be

used to calculate the diurnal component of evaporative emissions.

Minimum and Maximum Daily Temperatures

Minimum and maximum daily temperatures are used directly in MOBILE4.1 to calculate

the diurnal portion of evaporative VOC emissions79 and to estimate the temperature of dispensed

fuel for use in the calculating refueling emissions. Unless overridden,80 the temperatures used in

calculating temperature corrections for exhaust VOC, CO, and NOx emissions, the hot soak

portion of evaporative emissions, and resting loss and running loss VOC emissions are also

calculated by MOBILE4.1 based on the minimum and maximum temperatures entered as input

to the model. 

Since the basic exhaust emission rates for VOC, CO, and NOx are based on the standard

test temperature of 750

F (240C), MOBILE4.1 also adjusts these rates for other temperatures. 

Using the minimum and maximum daily temperatures and a representative profile of temperature

versus time of day, MOBILE4.1 first calculates a temperature for each pollutant representing

average emissions over the course of the day and then adjusts the exhaust emission factors for

temperature effects accordingly.81 

Hot soak emissions at FTP conditions are based on a temperature of 820

F (280C). Again

using the minimum and maximum temperatures, MOBILE4.1 calculates a temperature by which

to adjust hot soak emissions. 
 82 If hourly diurnal emissions are required for photochemical or other models, an acceptable approach is to first

calculate the daily diurnal emissions, then allocate to specific hours in proportion to the temperature rise per hour. 

For example, if during the modeling day the temperature increases from 60-840

F within the 7 a.m. to 5 p.m. tenhour period, and if during the 1-2 p.m hour temperature increases from 76-800

F, then, assuming the total diurnal

emission factor is 3 g/vehicle, the emission factor for the 1-2 p.m. hour is 0.5 g/vehicle. The diurnal emission factor

for hours other than 5 a.m. to 3 p.m. is zero. Other reasonable methods may also be acceptable. States wishing to

use another method should consult with EPA staff.

Hourly Emission Factor = Hour-Specific Temperature Increase/(Maximum Daily Temperature - Minimum

Daily Temperature)  Total Diurnal Emission Factor 

 (3-6) 83

 For CO modeling inventories, the recommended temperature is the average of the 8-hour high concentration

period temperatures rather than the minimum and maximum temperatures used to calculate a typical winter day

inventory:

 10 8

 
 
 Ambient Temperature(Hours)

 Days=1 Hours=1 

 

 84 The temperatures used in the 1990 inventory must also be used for all projection inventories. 

36

Resting loss and running loss VOC emissions are also dependent on temperature. As in

the cases of exhaust and hot soak emissions, MOBILE4.1 calculates appropriate average

temperatures for estimating resting loss and running loss emissions, weighted to account for

differing emission levels at different temperatures in the range of the minimum and maximum

daily temperatures and differing travel fractions over the course of a day. Restrictions on these

temperatures are: the maximum temperature must be greater than or equal to the minimum

temperature, and the ambient temperature should be between the minimum and maximum

(minimum < ambient < maximum). 

There have been no revisions to this variable's use or input data format requirements

since the release of MOBILE4.

Guidance

EPA recommends that the minimum and maximum daily temperatures be used to

determine the temperatures for corrections to the emission factors, if daily average, rather than

hour-by-hour, emissions are to be estimated.82, 83

Minimum and maximum temperatures are normally calculated from the most recent

three-year period for which validated ozone and/or CO monitoring data exists at the time the

emission inventory is due. For 1990 inventories, the period to be used for temperature

determination should be 1988-1990.84

 
 85 Consider the three-year period as a whole when making this determination.

 86 The 10 highest concentrations need not all be exceedences.

 87 There are four exceptions to selecting the 10 highest concentrations: 1) More than 10 concentrations may be

needed to identify 10 unique dates. 2) If the 10th ranked concentration level occurs on more than one day, all of

those days should be included in the temperature calculation. 3) If only two years of validated monitoring data exist

for the entire MSA monitoring network, use the seven highest concentrations. 4) If only one year of data exists for

the entire MSA monitoring network, use the four highest values.

37

Procedure

Determine the consecutive three-month period with the highest frequency of NAAQS

exceedance days occurring in the inventory area.85 The same consecutive three-month period

applies for each year, with a total of nine months used to determine temperature. If the months

containing the highest frequency of exceedances are not consecutive, or if two or more sets of

consecutive months have the same frequency, use the months of June, July, and August for ozone

modeling and the months of November, December, and January for carbon monoxide modeling.

Next, list the 10 highest concentrations86 that occurred in the inventory area during those

nine months and the dates of those concentrations.87 

The ten highest ozone concentrations for each site in a county and the dates on which

they occurred are contained in the Aerometric Information Retrieval System (AIRS)

AMP440/Maximum Values Report. Eight-hour average CO concentrations and the dates on

which they occurred can be found in the AIRS AMP350 raw data report. The AMP355/Standard

Report contains the CO values that exceed the NAAQS. These reports are available from EPA's

National Air Data Branch. Be sure to specify the year(s) and counties of interest and indicate

that the request is for preparation of a SIP emission inventory to avoid being charged the normal

processing fee. To obtain copies of these reports, contact Tom Link, U.S. EPA Office of Air

Quality Planning and Standards, at (919) 541-5456. 

Determine the maximum and minimum temperatures for each of the 10 days for the area

being inventoried. This information is contained in the Local Climatological Data Monthly

Summary for the inventory area and is available from:

National Climatic Data Center

Federal Building

Asheville, NC 28801-2696

Telephone: (704) 259-0682

Maximum and minimum daily temperatures are located in columns 2 and 3, respectively,

on page 1 of the Summary.
38

If there is more than one meteorological station within the non-attainment area, use the

station that best represents the conditions of most mobile source emissions within the inventory

area. 

The temperatures recommended for use in modeling mobile source HC, CO, and NOx

emissions on a typical summer day and the temperatures recommended for use in modeling

mobile source CO emissions on a typical winter day will be posted on the Chief Bulletin Board

System maintained by the Office of Air Quality Planning and Standards. 

3.3.5.3 Operating Modes

Description

One important determinant of emissions performance is the mode of vehicle operation. 

EPA's emission factors are based on testing over the FTP cycle, which is divided into three

driving segments (referred to as "bags"), each with differing associated emissions performance:

Bag Operating Mode

1 Cold start - first 505 seconds of a cold-start trip (or less, 

if the trip ends before 505 seconds);

2 Stabilized - all operation beyond 505 seconds of a trip;

3 Hot start - first 505 seconds of a hot-start trip (or less, if 

the trip ends before 505 seconds).

Emission data from each of these modes reflect the fact that emissions generally are

highest when a vehicle is first started, i.e., is operating in the cold-start mode. At that time, the

vehicle, engine, and emission control equipment (particularly the catalytic converter and oxygen

sensor) are all at ambient temperature and, therefore, are not performing at optimum levels. 

The hot start mode represents the case of a vehicle that was operating, was turned off, and

then was restarted. In this case the vehicle was not turned off for sufficient time to have cooled

completely to ambient temperatures. Since the vehicle is partially warmed up, emissions during

a hot start are generally lower than during a cold start. However, since the vehicle is not yet

completely warmed up, emissions are generally higher than when the vehicle is completely

warmed up and operating in what is known as stabilized mode. During stabilized mode the

vehicle has been in continuous operation long enough for all emission control systems to have

attained relatively stable, fully "warmed-up" operating temperatures.
 88 The values corresponding to the FTP cycle are: PCCN 20.6 %

PCHC 27.3 %

PCCC 20.6 %

 89 Catalysts begin to operate at full efficiency once they reach about 6000

F (3160C). Since non-catalyst vehicles

do not depend on attainment of such high temperatures for stabilization of emissions performance, they can remain

partially warmed up for up to four hours.

 

 90 Some transportation emissions modeling approaches are based on the concepts of trip-start emissions and

running emissions, rather than the method described above. In this alternative approach, trip-start emissions are

assumed to be instantaneous and are calculated as the difference between MOBILE4.1 total "start" emissions and

total "stabilized" emissions. Total start emissions per trip are the product of the 100% cold- (or hot-) start emission

factor in grams per mile and the 3.59-mile distance attributed to the first 505 seconds of the FTP driving cycle. 

Total stabilized emissions are the product of the 100% stabilized emission factor in grams per mile and the same

3.59-mile distance and same speed as that used to estimate start emissions. Start emissions are calculated as the

grams per trip event times trip productions, and are typically located at the centroids.

Total stabilized emissions are the product of the sum of the MOBILE4.1 stabilized exhaust and running loss

emission factors in grams per mile and the total distance traveled during the course of the trip.

Trip end emissions are simply the "hot soak" emissions expressed in grams per trip event times trip attractions. 

Trip end emissions are also typically located at centroids.

Daily diurnal emissions are calculated as the emissions in grams per vehicle times vehicles present and must

39

MOBILE4.1 uses three inputs to indicate vehicle operating mode.88 These inputs

represent VMT; that is, the percentage of VMT (not the percentage of vehicles) accumulated by

non-catalyst vehicles in cold-start mode (PCCN), by catalyst-equipped vehicles in hot-start mode

(PCHC), and by catalyst-equipped vehicles in cold-start mode (PCCC). The three specified

values must all be expressed as percentages (not as fractions). Each value must lie between 0.0%

and 100.0%, and the sum of PCHC + PCCC must not exceed 100%. There have been no

revisions in the definitions or in the use or format requirements of these variables since the

release of MOBILE4.

Guidance

Historically EPA has defined cold starts to be any start that occurs at least four hours after

the end of the preceding trip for non-catalyst vehicles and at least one hour after the end of the

preceding trip for catalyst-equipped vehicles. Hot starts are those starts that occur less than four

hours after the end of the preceding trip for non-catalyst vehicles and less than one hour after the

end of the preceding trip for catalyst-equipped vehicles. The shorter time interval associated

with the cold/hot start definition for catalyst-equipped vehicles reflects the fact that catalytic

converters do not operate at intended efficiency until they are fully warmed up.89 

In the absence of supporting data for values other than those listed above, EPA believes

that the values reflecting FTP conditions are appropriate. This is particularly true when the

emission factors being modeled are individually or collectively intended to represent a broad

geographic area (Metropolitan Statistical Area, entire state) and/or a wide time period (days,

months). When the modeling is intended to represent highly localized conditions (specific

highway links) or very limited periods of time (single hours), it may be possible to develop more

representative values for these variables.90 Areas known to have average trip 
also be assigned to specific hours and locations. Methods for this assignment vary.

If the transportation model produces reliable estimates for the relevant trip parameters, this alternative method

is believed to be a more accurate way to locate mobile source emissions within the inventory area than is the use of

average FTP hot/cold percentages. 

Recently it has been reported that one of the commercially available transportation models was modified to

distribute start VMT along individual links based on travel time. Since there is considerable variation among

vehicles in the time interval required for catalyst light-off, EPA recommends that those using this approach for their

1990 SIP submittal evenly distribute "start" emissions on the basis of the first 505 seconds of the FTP rather than

try to estimate the exact amount of time within that period required for catalyst light-off. As more information

becomes available, it may be possible at a later time to meld the instantaneous and distributed approaches to

locating "start" emissions.

 91 The driving cycle used in FTP testing is 7.5 miles long. If shorter trips are preponderant within a given area, it

is possible that the percentage of VMT occurring in one of the "start" modes is greater than the national average. 

Similarly, if longer trips predominate, the percentage of VMT occurring in the "stabilized" mode may be greater.

 92 The humidity correction factor is also applied to NOx emissions from motorcycles.

40

lengths significantly shorter or longer than 7.5 miles may also merit the use of alternate values.91

Thus for SIP-related modeling, EPA will accept the use of the FTP operating mode

values except for small-scale scenarios where their use would clearly be inappropriate. EPA will

not accept SIP-related modeling that includes different operating mode fractions for the base and

projection years without a clear demonstration that such a shift is warranted.

3.3.5.4 Additional Correction Factors for Light-Duty Gasoline-Fueled Vehicle Types

Description

MOBILE4.1 can provide four additional corrections to the exhaust emission factors for

LDGVs, LDGT1s, and LDGT2s. These corrections are used to represent unique conditions not

typically assumed in MOBILE4.1 runs, and include the emissions effect of air conditioning

(A/C) usage, extra loading, and trailer towing. There is also a humidity correction factor, which

applies only to exhaust NOx emissions.92 

If these corrections are to be applied, either six or ten inputs will be required. If six

values are required, they are an A/C usage fraction (for all LDGVs and LDGTs), three extra load

usage fractions (for LDGVs, LDGT1s, LDGT2s), a trailer towing fraction (for all LDGVs and

LDGTs), and a humidity level (for all LDGVs and LDGTs plus motorcycles). If ten values are

required, they are an A/C usage fraction (for all LDGVs and LDGTs), three 
 93 A value of 75 corresponds to the absolute humidity condition of the FTP. If 75 is entered as the input, then no

correction will be applied.

41

extra load usage fractions (for LDGVs, LDGT1s, LDGT2s), three trailer towing fractions (for

LDGVs, LDGT1s, LDGT2s), a humidity level (for all LDGVs and LDGTs plus motorcycles),

and dry bulb and wet bulb temperatures (used to calculate an A/C usage fraction for LDGVs and

LDGTs).

A/C Usage Fraction

In the six-input option, a correction factor for A/C usage will not be applied, regardless of

the value that is entered. Enter 0.0 in this case. If you wish to include the effect on the exhaust

emission factors of A/C usage, enter a non-zero fractional value for this variable and appropriate

dry and wet bulb temperatures, as explained below.

In the ten-input option, this variable acts as a flag, and the A/C usage fraction is

calculated on the basis of the dry bulb and wet bulb temperatures (see below). If 0.0 is entered

for A/C, no correction factor will be applied, although values of dry and wet bulb temperature

must still be provided if the ten-input option has been chosen.

Extra Load Usage Fractions

These values are used to model the exhaust emissions effect of vehicles carrying an extra

500 lb (227 kg) load. To include this effect, three fractional values are entered (one each for

LDGVs, LDGT1s, and LDGT2s), representing the fraction of all vehicles of the given type

carrying such an extra load. These inputs are restricted to the range of zero to one. If the value

entered is zero, no correction for the effects of extra load is applied.

Trailer Towing Usage Fraction

These inputs are used to modify exhaust emissions of vehicles towing trailers. Enter one

or three values that represent the fraction of vehicles of a given type that are to be assumed to be

towing trailers. These inputs are also restricted to the range of zero to one. If the value entered

is zero, no correction for the effect of trailer towing is applied. In the six-input option, one value

is entered and is applied to LDGVs, LDGT1s, and LDGT2s. In the ten-input option, three values

are entered, and one each is applied to LDGVs, LDGT1s, and LDGT2s.

NOx Humidity Correction

This input is used to correct exhaust NOx emission factors for absolute humidity. The

value entered is the absolute (specific) humidity, expressed as grains of water per pound of dry

air. Absolute humidity is restricted to the range 20 to 140.93 
 94

 These values (in 0F) will be used to calculate the A/C usage fraction on the basis of the discomfort index only

if the ten input option is selected and a non-zero value is entered for the variable AC. If used, this calculated value

overrides the value read in for AC, which serves as a flag indicating that this correction is desired (see above).

 95 If any of these three conditions is not met, MOBILE4.1 will print an error message.

 96 There is some uncertainty surrounding the air conditioning correction factors. The emissions effect of

operating the air conditioner for late model year vehicles is not well quantified. Also, the fraction of vehicles

equipped with air conditioning (built into MOBILE4.1) is substantially higher for the vehicle fleet of the late 1980s

than it was for the fleet of the late 1970s, which magnifies the consequence of a possible error. Thus, the use of the

air conditioning corrections to emissions is acceptable but not required in the development of SIP inventories. 

42

Dry and Wet Bulb Temperatures

MOBILE4.1 will estimate the fraction of A/C-equipped vehicles with the air conditioning

operating on the basis of a "discomfort index".94 The discomfort index is calculated from the dry

bulb and wet bulb temperatures, which are restricted to the range 00

F (-180C) to 1100F (430C). In

addition, the wet bulb temperature must be less than or equal to the dry bulb temperature.95 

There have been no revisions to any of the variables discussed in this section, or to how

they are supplied to the model as input data, since the release of MOBILE4.

Guidance

In most cases, ozone pollution episodes occur during summer months and very warm to

hot temperatures. It is reasonable to assume that vehicle air conditioning usage is high under

such conditions. The air conditioning correction factors that are calculated in MOBILE4.1 will

increase vehicle emissions, and areas that believe their motor vehicle inventory has been

underestimated in the past may choose to use them. However, EPA will accept SIP inventories

that do not attempt to explicitly account for vehicle air conditioning use.96 

The same approach that is taken in developing the base year inventory must also be used

for projection inventories.

The humidity correction for NOx emissions accounts for the fact that when "excess"

water vapor is present, some of the heat of combustion heats water vapor rather than enhancing

NOx formation. As with the air conditioning correction, EPA will accept SIP inventories that do

not attempt to account for local humidity. If the humidity correction is applied in the base year,

it must also be used in any projection inventories. While the humidity correction factors were

developed in the late 1970s, limited testing on current technology vehicles indicates that they are

still adequate. 
 97 VMT should also be disaggregated so that the set of operating conditions under which the vehicles are

generating the VMT is fairly homogeneous.

 98 For example, if it is difficult to tell which of two states' vehicles produce the VMT on each side of the border,

both states could assume that the VMT on their side comes from a random mix of their collective vehicle

population. 

43

3.3.6 Control Programs

In general, VMT should be disaggregated so that vehicles generating the VMT are subject

to a common control program.97 This issue applies especially for I/M versus no I/M and ATP

versus no ATP areas, specifically interstate areas but also where the inventory area is partially

designated attainment and partially designated non-attainment. EPA will accept the use of a

single correct pair of VMT fractions (with and without I/M) for the entire inventory area, even if

these fractions may be incorrect within one county or a state portion of a non-attainment area.98 

3.3.6.1 Refueling Emissions

Description

The refueling of gasoline-fueled vehicles results in the displacement of fuel vapor from

the vehicle fuel tank to the atmosphere. There are two basic approaches to the control of vehicle

refueling emissions, generally referred to as "Stage II" (at the pump) and "onboard" (on the

vehicle) vapor recovery systems (VRS). MOBILE4.1 has the ability to model uncontrolled

levels of refueling emissions (i.e., assuming no requirements for Stage II or onboard VRS

systems) as well as the effects of the implementation of either or both of the major types of vapor

recovery systems.

There are five approaches available in MOBILE4.1 for modeling vehicle refueling

emissions:

 Model uncontrolled refueling emissions for all gasoline-fueled vehicle types;

 Model refueling emissions assuming a Stage II VRS requirement;

 Model refueling emissions assuming an onboard VRS requirement;

 Model refueling emissions assuming both Stage II and onboard VRS requirements;

 Account for refueling emissions by some means other than MOBILE4.1.

No additional inputs are required for either the first or the last approach. Additional

information is needed, however, to model the effects of either or both VRS requirements on

refueling emissions.
 99 There are no national average or default values for Stage II efficiency.

 100 EPA has no plans to promulgate regulations for onboard vapor recovery. 

 101 State tax revenue receipts on county gasoline sales are often used for this purpose.

 102 One alternative to using MOBILE4.1 to calculate refueling emissions is to use the applicable AP-42 emission

factors. However, the effects of an onboard vapor recovery system requirement cannot be modeled accurately using

this approach. MOBILE4.1 makes use of improved predictive equations to calculate refueling emission factors, and

these have not yet been incorporated into AP-42.

44

Four inputs must be provided to model the effect of a Stage II VRS requirement: the

start year (calendar year in which the requirement takes effect), the phase-in period (number of

years for Stage II VRS installation to be completed), and the system efficiency (in percent) at

controlling refueling emissions from light-duty vehicles and trucks, and from heavy-duty

vehicles.99 

Only two inputs are required to model the effect of an onboard VRS requirement: the

starting model year and which of the four possible vehicle types (LDGV, LDGT1, LDGT2,

HDGV) are subject to the requirement.100 

Both sets of inputs must be supplied to model both VRS requirements concurrently.

Guidance

EPA recommends that states and others use MOBILE4.1 to model refueling emissions

for highway vehicle emission inventories. The refueling emission factors can be calculated in

grams per gallon of dispensed fuel (g/gal) or in grams per mile (g/mi). The preferred approach is

to calculate g/gal refueling emission factors that reflect the applicable Stage II requirements, then

multiply the g/gal emission factor by total gasoline sales. This is the most accurate method of

estimating the contribution of refueling emissions to the inventory, particularly for areas with

reliable data on gasoline sales.101 This method also accounts for refueling emissions generated

when gasoline is purchased in an area but consumed largely outside of the area, and does not

include refueling emissions for through traffic that does not refuel in the area.102 When good data

on gasoline sales is not available, the use of the g/mi refueling emission factor is more

convenient and, while also more approximate, acceptable for SIP inventory development.

Stage II

The overall effectiveness of a Stage II vapor recovery system at controlling refueling

emissions depends on a number of factors, including the baseline efficiency of the system used,

the portion of total area gasoline consumption handled by service stations exempt from Stage II

requirements, and the frequency and stringency of enforcement programs. In general, the

effectiveness of a Stage II VRS at controlling refueling emissions will be greater for light-duty

vehicles and trucks than for heavy-duty vehicles, since HDGVs are more likely to 
 103 The model can also accept alternate credit matrices as input. These must be developed by EPA. Areas for

which the standard emission reduction credit matrices are inappropriate should contact the Office of Mobile Sources

(Air Quality Analysis Branch, 313/668-4325) to obtain the required matrices.

45

be refueled at service stations (or other fuel dispensing locations, such as private refueling

depots) that will be exempted from Stage II requirements. 

EPA has estimated the in-use efficiency of Stage II programs based on the dispensed

volume of the stations exempted from the requirement and the frequency of inspections at

stations subject to it. The 1990 Clean Air Act exempts from the Stage II requirement stations

that sell less than 10,000 gallons of gasoline per month (50,000 gallons per month for

independent small marketers, as defined in the Act). This exemption level, along with a semiannual inspection frequency, results in 83% in-use efficiency for a Stage II program. If

inspections occur annually, efficiency is estimated to be 77%. Minimal inspections reduce the

efficiency to 56%. EPA will accepts these efficiency levels as MOBILE4.1 inputs when

modeling Stage II controls as part of the 1990 SIP submittal.

Spillage

Emissions from fuel spillage also can be modeled using MOBILE4.1. The "baseline"

spillage factor (assuming no controls) is 0.31 g/gal. of dispensed fuel. If no controls are

assumed, this factor is added to MOBILE4.1's calculated displacement loss, which, in turn, is

based on ambient temperature and RVP. If Stage II is modeled, then the in-use efficiency

percentages input determine the reduction in both displacement and spillage. 

Displacement loss can be separated from fuel spillage, using the grams per gallon

emission factors from the expanded evaporative output. If no controls are used, fuel

displacement emissions should be calculated by subtracting the 0.31 g/gal spillage factor from

the emission factor. In this case, spillage would be 0.31 g/gal.

To model the effects of Stage II on displacement and spillage losses, the percent emission

reduction for LDGVs, LDGTs, and HDGVs must be input. These percentages are then

multiplied by the 0.31 g/gal spillage factor to arrive at a value for spillage. Displacement loss is

then calculated as the gram/gallon emission factor minus the calculated spillage loss. 

3.3.6.2 Inspection and Maintenance Programs

Description

Many areas of the country have implemented inspection and maintenance (I/M) programs

as a means of reducing mobile source air pollution. MOBILE4.1 can model the effect of an

operating I/M program, based on the specification of certain parameters that describe the

program. Standard low-altitude area emission reduction credits are contained within the

MOBILE4.1 code itself, while standard high-altitude area emission credits are included as a

separate file on the MOBILE4.1 diskettes and tapes.103 
 104 MOBILE4.1 will run correctly if an I/M program is specified and only the first ten parameters from the above

list are provided. Additional information on the IM240 and purge and pressure testing can be found in the "User's

Guide to MOBILE4.1" (sections 2.2.5.4, 2A.1.16, 2A.1.17, and 2A.1.18).

 105 There are many details, such as instrument specifications, that are beyond the scope of this document to treat. 

I/M program planners should consult with EPA (Emission Control Strategies Branch, 313/668-4476) if they have

further questions regarding program requirements.

46

The following program parameters must be specified in order to model an I/M program:

 Program start year (calendar year that program begins);

 Stringency level (percent);

 First (earliest) and last (latest) model years of vehicles subject to the requirements of

the program;

 Waiver rates (percent of failed vehicles; one rate applicable to pre-model year 1981

vehicles and one rate applicable to 1981 and later model year vehicles);

 Compliance rate (percent);

 Program type (centralized; decentralized and computerized; or decentralized and

manual);

 Frequency of inspection (annual or biennial);

 Vehicle types covered by the program;

 Test type (idle, 2500/idle, loaded/idle);

 Whether alternate I/M credits are to be supplied;

 IM240 transient test first model year;

 Purge system test first model year;

 Pressure system test first model year.

The last three parameters in the list above are optional. They refer to the earliest model

year of vehicles subject to: 

 transient testing of HC and CO emissions (where the vehicle is tested on a chassis

dynamometer over a transient driving cycle, and mass emissions are measured using a

constant volume sampling (CVS) system);

 functional purge testing of the evaporative emission control system;

 functional pressure testing of the evaporative emission control system.

While these three types of testing may be incorporated into many future I/M programs,

there were no areas using any of these tests as part of their I/M programs in 1990. Thus, these

three parameters104 should not be included in estimating the 1990 base year emissions inventory.

The following sections discuss the terminology used to describe I/M programs for

purposes of modeling the emission benefits of such programs using MOBILE4.1. In general,

MOBILE4.1 assumes that the I/M program is mandatory, periodic, and covers a well-defined

group of vehicles.105 
 106 Such tailpipe I/M and anti-tampering programs are sometimes referred to collectively simply as "I/M

programs" in other EPA documents.

 107 A tailpipe emission short test is any one of several emission testing procedures authorized by EPA for use in

emission testing programs. They include a simple idle test, where emissions are sampled as the vehicle idles in

neutral gear, to more elaborate tests, such as the IM240, where the vehicle's emissions are sampled during a

simulated drive using a chassis dynamometer.

 

 108 Emission cutpoints are the emission level measurements used to determine whether a vehicle passes or fails

the short test. If the vehicle's tailpipe emission level exceeds the cutpoints set for any of the measured pollutants,

the vehicle fails. 

47

3.3.6.2.1 I/M

I/M refers to "inspection and maintenance" programs, which are inspections of vehicles

using a measurement of tailpipe emissions and which require that all vehicles with tailpipe

emissions higher than the program cutpoints be repaired to pass a tailpipe emission retest. 

Inspections that are aimed at verifying the presence and proper connection of emission control

devices are called anti-tampering programs.106 

3.3.6.2.2 Start Year

The year in which the periodic inspection program begins to require both inspection and

repairs is called the start year. MOBILE4.1 only provides for a January 1st start date. Other start

dates will require interpolation between two MOBILE4.1 runs to give accurate estimates of

benefits. Separate start dates may be entered for the tailpipe emissions check and anti-tampering

portions of an I/M program.

3.3.6.2.3 Stringency

Stringency is the tailpipe emission test failure rate expected in an I/M program among

pre-1981 model year passenger cars or pre-1984 light-duty trucks, based on the short test107

emission cutpoints.108 The expected failure rate can be determined by applying the program

cutpoints to a representative sample of vehicles tested in a survey. Actual failure rates reported

by a program can also be used to determine stringency, but only when there is no possibility of

significant testing or data reporting errors. MOBILE4.1 assumes that the failure rate remains

fixed at the stringency level for each evaluation year. MOBILE4.1 will not allow a stringency

level less than 10% or greater than 50%.

3.3.6.2.4 First Model Year

The first model year refers to the oldest model year vehicle that is always included in the

inspection program. MOBILE4.1 assumes that all vehicle classes have the same model year

coverage and does not allow for a separate coverage period for each vehicle class. Some

programs do not fix the model years covered by the program, and instead use a coverage

"window" to define those vehicles that must be inspected. For example, such a program may 
 109 An alternate approach is to add one extra model year to the coverage window to represent all model years still

experiencing some residual but declining I/M benefit. EPA will accept this approach for purposes of estimating

1990 emissions.

 110 MOBILE4.1 assumes, in the calculation of I/M credits, that vehicles less than one year old are exempt from

inspection.

 111 Programs may include delayed inspections because a state considers such a program to be more cost

effective, since emissions of new vehicles are generally very low.

 112 MOBILE4.1 assumes that tampered or misfueled vehicles cannot receive waivers, and so does not reduce the

ATP benefit based on the waiver rate.

48

cover only vehicles 15 years old or younger. Since model year cohorts that leave the I/M

program in this way retain a partial I/M influence for a period of some uncertain number of years

beyond their last inspection, such programs cannot be modeled exactly using MOBILE4.1. 

However, as a practical matter, EPA is willing to assume that a vehicle that has left the I/M

program as of a certain evaluation year was never inspected.109 

3.3.6.2.5 Last Model Year

The last model year refers to the youngest (newest) model year vehicle that is subject to

the inspection program. The combination of first and last model year inputs makes it possible to

model a program that covers only particular model years. Many programs routinely include new

model year vehicles in the program as they reach their one year anniversary. In such cases the

year 2020 should be designated as the last model year.110 If inspection is delayed until vehicles

are two or three years old, then the input value for the last model year will be different for each

evaluation year.111 

3.3.6.2.6 Waiver Rates

Many I/M programs waive the requirement to pass a retest if certain defined criteria are

met. Typically, waivers are granted for vehicles whose owners have spent more than a certain

dollar amount repairing the vehicle in an attempt to pass the test.

The waiver rate inputs to MOBILE4.1 reduce the estimated benefit of the I/M program. 

The waiver rates are always calculated as a percent of non-duplicate initial test failures. Waiver

rates must be provided for pre-1981 and for 1981 and later model year light-duty vehicles.112 
 113 If tighter criteria are planned, a lower waiver rate may be assumed. For areas subject to the requirements for

Enhanced I/M, including the $450 expenditure requirement, a future waiver rate as low as one percent may be

assumed, but planners should realize that an underestimation of the future waiver rate may cause later problems in

demonstrating reasonable further progress milestones. EPA may also consider a finding of SIP non-implementation

if an actual waiver rate substantially exceeds the rate assumed in inventory forecasts. 

 114 The compliance rate input is also used to account for vehicles that are waived from compliance without any

testing. For example, vehicles with special testing problems or vehicles owned by certain groups of individuals

may be automatically waived.

 115 Other possible reasons for the 5000 vehicle discrepancy include vehicles registered but scrapped or

transferred out-of-state prior to the inspection due date.

49

Guidance

For an historical inventory, the actual waiver rate must be determined and used as the

input to MOBILE4.1. For future year inventories, the historical waiver rate should be used

unless a change will be made to the criteria for granting waivers.113 

3.3.6.2.7 Compliance Rate

Compliance rate refers to the level of compliance with the inspection program.114 For example,

assume a program required that all passenger cars be inspected each year, and that 100,000

passenger cars were registered in the area covered by the program. If in a given year only 95,000

passenger cars completed the inspection process to the point of receiving a final certificate of

compliance or a waiver, the remaining 5,000 vehicles may have avoided the inspection

requirement. If those vehicles did, in fact, avoid the inspection requirement, the compliance rate

for the program would then be 95%.115 

MOBILE4.1 uses a single compliance rate to reduce both the I/M and ATP portions of

the program benefits. The reduction in benefit is not linear. The benefit loss per vehicle assumes

that the failure rate among non-complying vehicles will be larger than the expected failure rate in

the fleet. As the rate of non-compliance increases, the non-complying failure rate will approach

and finally equal the expected failure rate.

Table 3-2 shows the loss of benefit assumed for the enforcement fraction:
 116 The number of initial inspections should not be used to calculate the compliance rate, since some cars may

drop out after failing one or more tests. 

 117 An overestimation of the future compliance rate may cause problems later on in demonstrating that

Reasonable Further Progress milestones have been met. Also, EPA may issue a finding of SIP non-implementation,

if the actual compliance rate is substantially less than the rate assumed in inventory forecasts. 

50

Table 3-2

Benefit Assumed for Enforcement Fraction

 Non- Non-Complier Fraction Fraction

Compliance Compliance Failure Rate Benefit Benefit 

 Rate Rate Adjustment Loss Remaining

100% 0% 2.0 .000 1.000

99% 1% 2.0 .020 .980

98% 2% 2.0 .040 .960

97% 3% 2.0 .060 .940

96% 4% 2.0 .080 .920

95% 5% 1.5 .095 .905

90% 10% 1.4 .169 .831

85% 15% 1.3 .238 .762

80% 20% 1.2 .302 .698

75% 25% 1.1 .361 .639

70% 30% 1.0 .415 .585

50% 50% 1.0 .615 .385

Guidance

Historical compliance should be determined by sticker surveys, license plate surveys, or a

comparison of the number of final tests to the number of vehicles subject to the I/M

requirement.116 Planners should not assume a compliance rate of 100%. An area with a

registration denial system using automatically generated compliance documents that uniquely

identify the complying vehicle and that are serially numbered and accounted for, that rely on

centralized processing by government clerks with management oversight, may assume a 98%

rate unless there is evidence to indicate otherwise.117 

 3.3.6.2.8 Inspection Frequency

MOBILE4.1 allows for two inspection frequencies. "Annual" means that all covered

vehicles must be inspected once each year. "Biennial" means that each vehicle is inspected once

every two years, such that either half of the vehicles of each model year are inspected 
 118 Those areas that do not use the same vehicle class designations in their vehicle registration data as are used in

MOBILE4.1 must take care not to claim coverage for too many vehicles.

 119 The concept of stringency already takes into account the effect of test type on the benefits that accrue to older

vehicles. 

 120 In all cases MOBILE4.1 assumes that the cutpoints used for the inspections are 1.2% CO and 220 ppm VOC.

51

 each calendar year, or vehicles of one model year are inspected in alternate calendar years. Any

other inspection frequency would require alternate I/M credits provided by EPA.

 3.3.6.2.9 Vehicle Classes

MOBILE4.1 program benefits are calculated separately for each gasoline-fueled vehicle

class. No emission benefits are estimated for diesel vehicles or motorcycles. The vehicle class

designations are based on the same definitions under which vehicles are certified:118

 LDGV - light-duty gasoline-fueled vehicles (passenger cars);

 LDGT1 - light-duty gasoline-fueled trucks less than 6000 lbs gross vehicle weight

(lighter pick-up trucks and vans);

 LDGT2 - light-duty gasoline-fueled trucks greater than 6000 lbs but less than 8,500

lbs GVW (heavier pick-up trucks and vans and many commercial trucks);

 HDGV - heavy-duty gasoline-fueled vehicles greater than 8500 lbs GVW (heavier

commercial trucks, including highway hauling trucks).

3.3.6.2.10 I/M Test Types

There are four I/M tailpipe test types allowed in MOBILE4.1. These test types only

apply to the inspection of 1981 and newer model year passenger cars and 1984 and newer lightduty trucks.119 The chosen test type is assumed to be applied to all 1981 and newer passenger

cars and 1984 and newer light-duty trucks both at the initial inspection and at the retest.120 

Idle Test

The idle test is a measurement of VOC and CO emission concentrations of a fully

warmed vehicle as it idles in neutral or park.

2500/Idle Test

The 2500/idle test is a measurement of VOC and CO emission concentrations of a fully

warmed vehicle operating at 2500 rpm, first, in neutral or park and second, at idle. The vehicle

must pass both 2500 rpm and idle tests.
 121 These are provided on diskettes and tapes distributed with the model. 

52

Loaded/Idle Test

The loaded/idle test is a measurement of VOC and CO emission concentrations of a fully

warmed vehicle operated first, on a chassis dynamometer at a constant cruise speed and

dynamometer load, and second, at idle in neutral or park. The vehicle must pass both the cruise

and idle tests. 

IM240 Transient Test

The IM240 transient test is a measurement of VOC and CO emission concentrations of a

vehicle operated over a range of speeds. The IM240 was patterned after the Urban Dynamometer

Driving Schedule used to conduct the Federal Test Procedure (FTP). In order for MOBILE4.1 to

estimate the effects of using the I/M 240 test in an I/M program, a set of alternative I/M credits

must be entered as input.121 MOBILE4.1 assumes that transient testing is applied to all model

years and to all vehicle types covered by the I/M program.

Purge Test

The purge test is a functional test of the purge capabilities of the evaporative emission

control system. The flow rate of canister purge is measured during transient operation of a

vehicle on a chassis dynamometer using a flow measurement device, and cutpoints for minimum

flow rate are used to determine if the vehicle passes or fails. Vehicles failing the purge test are

required to have repairs performed to enable the vehicle to pass the test. MOBILE4.1 assumes

that all model years and vehicle types subject to the I/M program are also subject to functional

purge testing, if a first model year for such testing is specified as an input. 

Pressure Test

The pressure test is a functional test of the evaporative emission control system for leaks. 

The fuel tank and related hoses and pipes are pressurized, and the pressure loss is monitored over

time. Cutpoints defining the maximum allowable loss of pressure are set and used to determine

if the vehicle passes or fails. Vehicles failing the pressure test are required to have repairs

performed to enable the vehicle to pass the test. MOBILE4.1 assumes that all model years and

vehicle types subject to the I/M program are also subject to functional pressure testing if, a first

model year for such testing is specified as an input.
 122 Examples of such programs are those with a semi-annual or tri-annual inspection frequency.

 123

 Normally these factors will be supplied by EPA at the request of the program manager or air quality planner.

 124 Test-only programs are considered centralized even if they are decentralized in the sense of multiple

businesses.

53

3.3.6.2.11 Alternate I/M Credits

In special cases where the design of an I/M program does not fit into any of the

categories defined in MOBILE4.1,122 an alternative set of credits may be input. These credits

are then used by the model to determine the benefits of the I/M program.123 

One set of alternate I/M credits applies to purge and pressure system checks of the

evaporative control system. To estimate these credits MOBILE4.1 requires that the oldest model

year covered by the purge system check and the oldest model year covered by the pressure check

be entered as inputs. MOBILE4.1 assumes that all vehicle types covered by the I/M program are

also covered by the purge and pressure system checks. It also assumes that the purge system

check is done as part of a transient exhaust emission check. 

3.3.6.2.12 Centralized Programs

Centralized inspection programs refer to those programs that completely separate vehicle

inspection from vehicle repair. Usually, high-volume inspection stations, run either by the local

agency itself or by a contractor, perform all initial tests and retests after repair. Garages and

other repair facilities are not allowed to perform official tests. Independent centralized programs

are the standard used to determine the emission benefits for I/M and ATP program designs.124 

3.3.6.2.13 Decentralized Programs (Manual)

Decentralized inspection programs refer to those programs where the local program

agency licenses service stations and garages to perform official inspections and re-inspections. 

These licensed inspection stations are allowed to perform repairs on the vehicles they inspect. 

The number of licensed inspection stations in decentralized programs is larger, and the volume

per station is smaller than for centralized programs. 
 125 The 50% reduction in benefits from the tailpipe portion of the test includes the loss due to waivers, if any. 

For decentralized I/M programs, the waiver rate input of the model is disabled so that user input of waiver rates has

no effect on I/M benefits. 

 126 Since the degree to which manual decentralized programs are less effective than centralized programs is not a

MOBILE4.1 input, it is necessary for EPA to prepare a special version of the model to account for the effects of a

decentralized I/M program that has been shown to have an effectiveness level different from that of a centralized

program by more or less than 50%. The demonstration of increased effectiveness should rely on historical data and

not on arguments for an anticipated increase in effectiveness. 

 127 Although the computerized analyzers make it easier for inspections to be performed correctly, EPA audits

have shown that the overall performance of inspectors in computerized decentralized I/M programs is no better than

in manual decentralized I/M programs. 

 128 For decentralized I/M programs, the waiver rate input of the model is disabled so that even if waiver rates are

input to MOBILE4.1, they will have no effect on I/M benefit calculations. 

 129 Most of the deterrence effect of the program, which deters tampering that has not yet occurred, is unaffected

by the decentralized discount. 

 130 Since the degree to which computerized decentralized programs are less effective than centralized programs

is also not a MOBILE4.1 input, it is necessary for EPA to prepare a special version of the model to account for the

effects of a decentralized I/M program that has been shown to have an effectiveness level different from that of a

centralized program by something other than 50%. The demonstration of increased effectiveness should rely on

historical data and not on arguments for an anticipated increase in effectiveness.

54

Decentralized programs have been found to be less effective in reducing emissions than

are centralized programs. As a result, MOBILE4.1 reduces the emission benefits of a

decentralized program to 50% of that attributed to a centralized design for both the tailpipe test

portion and the ATP portion of the program.125 Modelers who can demonstrate a higher level of

effectiveness for a decentralized I/M program should contact EPA.126 

3.3.6.2.14 Computerized Inspection

Some decentralized I/M programs require the use of computerized emission analyzers. 

These analyzers contain small computers which keep track of all official inspection activity,

automatically calibrate the instrumentation, and prompt the inspector during the inspection

procedure. The computer also prepares a machine-readable record of all official inspections and

calibrations, and will not allow inspections whenever it determines that the instrumentation is out

of calibration. 

MOBILE4.1 assumes that the I/M portion of a decentralized computerized inspection

program will be 50% as effective as a centralized program of similar stringency (i.e., the benefits

of the program are discounted by 50%). This benefit discount is the same as for manual

decentralized programs.127 As noted above, this benefit reduction includes the effect of waivers,

if any, and is not applied on top of a waiver-related loss of potential benefits.128 

Decentralized computerized inspection programs will also have some of the benefits

from the ATP portion of the program reduced by 50%.129 Modelers who can demonstrate a

higher level of effectiveness for a decentralized I/M program should contact EPA.130 
 131 Sets of alternate I/M credits may contain both Tech I and II credits, only Tech IV+ credits, or Tech I and II

and Tech IV+ credits together. This is usually indicated in the header block of the alternate I/M credit deck.

55

3.3.6.2.15 Tech I-II and Tech IV+

The calculation of I/M benefits for MOBILE4.1 was done by technology group, which

can roughly be determined by model year for each vehicle type. These technology groups have

come to be referred to by numbers. The table below summarizes the technology groupings used

in MOBILE4.1 and their respective application to gasoline-fueled passenger cars and light

trucks. Within the Tech IV group, there are separate I/M credits for each model year of LDGVs,

and a mapping of LDGT model years to similar technology LDGV model years.131

Model Years Covered

Technology 

Grouping LDGV LDGT1 LDGT2

I Pre-1975 Pre-1975 Pre-1979

II 1975-80 1975-83 1979-83

IV+ 1981+ 1984+ 1984+

3.3.6.3 Anti-Tampering Programs

Description

Some areas of the country have implemented anti-tampering programs (ATPs) to reduce

the frequency and resulting emission effect of emission control tampering (e.g., misfueling,

removal or disablement of catalytic converters). MOBILE4.1 can estimate the emission factor

effects of such programs. The following inputs are required to model an anti-tampering

program:
 132 MOBILE4.1 will only model an ATP with an evaporative system inspection and provide appropriate

emission credits if a gas cap inspection is also included. If an evaporative system inspection is indicated, but a gas

cap inspection is not indicated, MOBILE4.1 will issue a warning message, and no emission credit will be given for

the evaporative system inspection. However, the converse is not true. A gas cap inspection may be indicated

without an indication of an evaporative system inspection.

 133 There are many details (such as replacement catalyst specifications) that are beyond the scope of this

discussion. Program planners should consult with EPA's Office of Mobile Sources (Emission Control Strategies

Branch, 313/668-4476) if there are questions regarding the requirements of ATP inspections. 

56

 Start year (calendar year in which the program begins);

 First (earliest) and last (most recent) model years of vehicles subject to the program;

 Vehicle types covered by the program;

 Program type (centralized or decentralized);

 Frequency of inspection (annual or biennial);

 Compliance rate (percent);

 Inspections performed (air system, catalyst, fuel inlet restrictor, tailpipe lead deposit

test, EGR system, evaporative system, PCV, gas cap).132

There have been no revisions to the information required to model ATP effects since the

release of MOBILE4.

The following sections discuss the terminology used to describe anti-tampering program

inspections for purposes of modeling the emission benefits of such programs using MOBILE4.1. 

In general, it is assumed that the program is mandatory, periodic, and covers a well-defined

group of vehicles.

It is also assumed that the inspections are primarily visual rather than functional and

involve no disassembly or disconnection to gain access to hidden components (other than

removal of the gas cap to view the fuel inlet restrictor). However, program regulation writers are

encouraged to define failure in broad enough terms of visual damage and proper operating

condition so that any emission control component determined by the inspector to be nonfunctional can be properly failed and repaired.

A program that inspects for tampering only when a vehicle has failed its tailpipe I/M

inspection, or only when a vehicle owner requests a test waiver, is not considered as an antitampering program, garners no emissions benefits, and should not be modeled in MOBILE4.1. 

The following sections discuss the terminology used to describe anti-tampering programs

for purposes of modeling the emission benefits of such programs using MOBILE4.1. In general,

MOBILE4.1 assumes that the anti-tampering program is mandatory, periodic, and covers a welldefined group of vehicles.133 
57

3.3.6.3.1 ATP

Anti-tampering programs are periodic inspections of vehicles to detect damage to,

disablement of, or removal of emission control components. Owners are required to restore the

vehicle's emission control system and have the vehicle reinspected. Programs that inspect for

tampering only those vehicles failing an I/M tailpipe test are not considered to have an antitampering program and should not be included in estimating a mobile source emissions

inventory.

3.3.6.3.2 Tampering and Misfueling

Any physical damage to, or disablement or removal of, an emission control component is

considered tampering in MOBILE4.1. This does not limit tampering only to deliberate

disablements or only to those disablements of which the vehicle owner is aware. Tampering,

therefore, can often be a result of poor maintenance rather than some deliberate action by the

vehicle owner or service mechanic.

Misfueling is the use of leaded fuel in any vehicle that is equipped with a catalytic

converter. This includes inadvertent use of leaded fuel without the knowledge of the vehicle

owner.

3.3.6.3.3 Air Pump Inspection

Air pump systems supply fresh air needed by the catalytic converter to reduce engine

emissions before they leave the tailpipe. Inspectors should check for missing belts and hoses and

proper connection at the exhaust manifold. Sometimes the entire pump and its plumbing are

removed. A valve is sometimes used to route air away from the exhaust stream during certain

operating modes. This valve should be checked for proper hose and wire connections. Often the

air is injected directly into the catalytic converter underneath the vehicle. If so, this connection

should be checked. Any missing, damaged, or altered components of the air pump system

should be replaced.

3.3.6.3.4 Catalyst Inspection

The catalytic converter, sometimes referred to simply as the catalyst, oxidizes excess

volatile organic compounds and carbon monoxide from the engine exhaust into water and carbon

dioxide. Newer catalysts also reduce oxides of nitrogen in the exhaust. The metals that

accomplish this task are most commonly coated on a ceramic honeycomb inside the stainless

steel shell of the catalyst. The catalyst resembles a muffler in some ways, but would not be

confused with a muffler because it is farther forward on the vehicle, and its stainless steel shell

will not rust.
 134 MOBILE4.1 assumes that inspectors are not allowed to skip this inspection because the fuel inlet is concealed

by a locked door.

58

Some cars will have more than one catalyst, so the number of catalysts expected should

be determined before the inspection begins. Some catalysts are located very near the exhaust

manifold, so the inspector should be sure to check the entire length of the exhaust piping from

the exhaust manifold to the muffler before determining that the catalyst is not present.

Emission credit should not be claimed using MOBILE4.1 unless regulations provide a

mechanism to ensure that failed cars are correctly repaired with original equipment manufacturer

(OEM) or approved aftermarket replacements. Program planners should consult with EPA to

avoid incorrectly claiming credit.

3.3.6.3.5 Fuel Inlet Restrictor Inspection

Vehicles requiring the use of only unleaded gasoline have been equipped with fuel inlets

that only allow use of narrow fuel nozzles. Leaded fuel is required to be dispensed only from

pumps using wider nozzles. Any vehicle found to have a fuel inlet which allows a leaded fuel

nozzle to be inserted, such as having the nozzle size restriction removed, is assumed to have used

leaded fuel. Leaded fuel permanently reduces the ability of the catalytic converter to reduce

emissions. Therefore, vehicles found with a fuel inlet that allows insertion of a leaded fuel

nozzle should be required to replace the catalytic converter. In addition, the vehicle's fuel inlet

should be repaired to allow only the insertion of unleaded fuel nozzles.

Repair of the fuel inlet restrictor only is not considered a repair that will reduce the

emissions of the vehicle. Since the damage to the emission control of the vehicle occurs in the

catalyst, it is the catalyst that must be replaced to result in any substantial emission reduction. 

The inlet restrictor must be replaced simply as protection for the new catalyst. If the program

regulators do not require catalyst replacement, the MOBILE4.1 inputs should indicate that an

inlet check is not performed.134

3.3.6.3.6 Tailpipe Lead Detection Test

Leaded fuel permanently reduces the ability of the catalytic converter to reduce engine

emissions before they leave the tailpipe. Therefore, vehicles found to have used leaded fuel

should be required to replace the catalytic converter. EPA has allowed for the use of a lead

detection test in the vehicle tailpipe as a method to detect the use of leaded fuel. Since this is a

chemical test, care must be taken to ensure that the test is properly conducted and that the results

are properly interpreted.

Vehicles with evidence of lead deposits in the tailpipe have used leaded fuel. Since the

damage to the emission control of the vehicle occurs in the catalyst, it is the catalyst that 
 135 The tailpipe as well as the catalyst should also be replaced to avoid failing a subsequent inspection test. 

 136 Hoses may be plugged, either deliberately or by neglect. 

 137 Hoses may be plugged, either deliberately or by neglect. 

 138 Modeling the benefits of functionally testing purge and/or pressure evaporative systems requires that the

initial model year of vehicles subject to such tests be input. See section 3.3.6.2.10.

59

must be replaced to result in any substantial emission reduction. If the program regulators do not

require catalyst replacement, then the input to MOBILE4.1 should indicate that a tailpipe lead

test was not preformed.135 Anti-tampering programs that require failure of both the fuel inlet

restrictor inspection and the tailpipe lead detection test before requiring replacement of the

catalyst get credit for neither. The input to MOBILE4.1 should not indicate either inspection was

performed.

3.3.6.3.7 EGR Inspection

The exhaust gas recirculation (EGR) system reduces oxides of nitrogen by routing some

of the exhaust back into the intake manifold. Although the primary component of the system is

the valve that controls the flow between the exhaust and intake manifolds, most systems are quite

complex, with various sensors and valves which together control the operation of the entire

system. Any system observed with missing or damaged components or misrouted or plugged

hoses and wires should be failed and repaired.136 While MOBILE4.1 has an input flag for EGR

inspections, there are no emission reductions associated with them. This reflects EPA's

assessment that these difficult visual inspections are virtually never performed correctly and

result in virtually no repairs. Programs with evidence to the contrary should consult EPA. 

3.3.6.3.8 Evaporative Control System

The evaporative control system collects gasoline vapors from the gas tank and carburetor

bowl and stores them in a charcoal canister. During certain engine operations, the canister

purges, releasing the vapors, which are then routed to the engine to be burned. In addition to the

evaporative canister itself, the system includes varying numbers of hoses, wires, and control

valves.137 Any system observed with missing or damaged components or misrouted or visually

obvious plugged hoses and wires should be failed and repaired. This inspection flag should not

be used to indicate any functional pressure or purge testing of the evaporative emission control

system. The benefits of such tests are calculated separately.138 Purge and pressure testing is,

however, assumed to detect all evaporative control system tampering.
 139 MOBILE4.1 assumes that inspectors are not allowed to skip this inspection even if the fuel inlet is concealed

by a locked door.

 140 The four vehicle types are LDGV, LDGT1, LDGT2, and HDGV.

 141 The eight tampering types are air pump disablement, catalyst removal, overall misfueling, fuel inlet restrictor

disablement, exhaust gas recirculation system disablement, evaporative control system disablement, positive

crankcase ventilation system disablement, and missing gas caps. 

 142 Tampering offsets are the increases in emissions that result from a given type of tampering.

 143 If EPA or local authorities have performed a statistically valid anti-tampering survey in a particular area, the

Office of Mobile Sources will consider whether it is possible to develop locality-specific tampering rates from that

survey for use in modeling for the area. A sample size larger than that collected by EPA in the typical one week of

its survey is essential. 

60

3.3.6.3.9 PCV Inspection

The positive crankcase ventilation (PCV) system routes the vapors from the crankcase to

the intake manifold where they can be burned by the engine. The PCV system has two major

loops. The most critical connects the crankcase to the throttle or the intake manifold via a hose

and usually contains a valve. Another hose connects the crankcase to the air cleaner to provide

the crankcase with filtered fresh air. Any system observed with damaged or missing components

or with hoses misrouted or plugged should be failed and repaired.

3.3.6.3.10 Gas Cap Inspection

Gas caps are actually part of the evaporative control system. Without a properly

operating gas cap, fuel vapors from the gas tank would escape. On some vehicles, a missing gas

cap will also cause the evaporative system canister to purge incorrectly. Inspectors should

examine the fuel inlet area of each vehicle to determine that the gas cap is present. If not, the

vehicle should be failed and the gas cap replaced.139 Pressure testing is assumed to detect all

missing gas caps. 

3.3.6.3.11 Tampering Rates

Description

MOBILE4.1 calculates tampering rates as a piecewise linear function of accumulated

mileage for each gasoline-fueled vehicle type140 and for eight types of tampering.141 These rates

are combined with the corresponding fractions of vehicles equipped with the given control

technology and emissions rates to obtain the tampering offsets.142 These offsets are later added to

the non-tampered emission factors.

MOBILE4.1 uses tampering rates based on EPA Office of Mobile Sources (OMS)

analysis of multi-city tampering survey results. EPA recommends that the tampering rates

included within MOBILE4.1 be used.143
 144 The three equations are used to model pre-1981 model year vehicles, 1981-83 model year vehicles, and 1981

and later model year vehicles.

 145 These rate equations are based on OMS analysis of national tampering survey data.

 146 A second, higher deterioration rate is applied only to LDGVs in MOBILE4.

 147 MOBILE4.1 assumes that the maximum rate of tampering for vehicles of any given model year is the rate at

130,000 mi (ZML + 5DR1 + 8DR2). 

61

EPA has determined through its tampering surveys that tampering rates are lower in areas

with operating I/M programs than in areas without such programs. Two complete sets of

tampering rates representing I/M and non-I/M cases therefore come with the model. 

If no I/M program exists, the set of non-I/M program tampering rates must be input. If

an I/M program does exist, however, then two sets of tampering rates must be input; the one

representing the non-I/M case accounts for tampering that occurred before the start of the I/M

program, and the one representing the I/M case accounts for tampering that occurred after the

start of the I/M program. 

MOBILE4.1 uses three rate equations for each type of tampering, one for each vehicle

type subject to tampering144 in non-I/M areas and three more rate equations for each type of

tampering in the I/M areas.145 

The only change to anti-tampering program inputs since MOBILE4 is that when alternate

tampering rates are used, additional equations are required. This is due both to the increase in

model year groups (from two in MOBILE4 to three in MOBILE4.1), and the use of a second

deterioration rate to describe the increase in tampering rates as a function of mileage for mileages

over 50,000.146, 147 

Guidance

The tampering rates built into MOBILE4.1 are the rates that should be used in all Clean

Air Act (CAA) mandated development of mobile source emission inventories. Use of any other

tampering rates in CAA-related work must be based on actual in-use tampering surveys, and

must be approved in advance by EPA. A local tampering survey would have to be quite large to

justify reliance on it in preference to the MOBILE4.1 rates. For guidance regarding EPA

approval of local tampering surveys and the development of tampering rates based on such

surveys, contact the Office of Mobile Sources' Field Operations and Support Division, 202/382-

2633. For guidance on the analysis of data collected in a local tampering survey or for further

guidance on developing the information required to model the emissions effect of an antitampering program, contact OMS's Emission Planning and Strategies Division, 313/668-4367.
 148 In 1990, the states of California, Florida, Hawaii, Maine, Michigan, Missouri, North Carolina, Oregon, South

Carolina, and Washington based HPMS VMT estimates on one or more collective sample panels while the states of

Connecticut, New York, and Ohio based HPMS VMT estimates on a combination of individual and collective

sample panels. In some of these states, such as California, the state reports area-specific VMT estimates to HPMS

as if they were derived in the same way as in other states. EPA recognizes that such estimates may not be as

reliable as estimates based on individual sample panels and therefore may allow the state to submit a 1990 SIP

inventory based on VMT estimates that are not fully consistent with the data submitted to HPMS. EPA Regional

Offices are advised not to agree that the HPMS data are less reliable than VMT estimates made by another staterequested method without consulting with divisional or regional FHWA officials who have direct knowledge of the

HPMS data associated with the non-attainment area.

62

3.4 VEHICLE MILES TRAVELED

This section describes two methods of estimating highway vehicle miles traveled. Both

are related to the Department of Transportation's (DOTs) Highway Performance Monitoring

System (HPMS).

3.4.1 Highway Performance Monitoring System

3.4.1.1 Role of the HPMS in SIP Development

EPA and DOT have both endorsed the Highway Performance Monitoring System

(HPMS) as the appropriate source of VMT estimates. All states, except for the states of

California, Connecticut, Florida, Hawaii, Maine, Michigan, Missouri, North Carolina, New

York, Ohio, Oregon, South Carolina and Washington, should base their 1990 estimates of actual

annual VMT on unique sample panels for each Federal Aid Urbanized Area (FAUA) within the

state, since sampling has already occurred at that level of geographic detail.148 The effect of this

agreement is that the VMT used to construct mobile source emission inventories should be

consistent with that reported through the HPMS. However, since the Federal Aid Urbanized

Area geographic boundaries of HPMS are not generally coincident with EPA's non-attainment

area boundaries, the two estimates of VMT will not necessarily be identical.

Ideally, the VMT in that portion of the non-attainment area that is encompassed by the

FAUA should be the same as the VMT reported for that FAUA to the U.S. Department of

Transportation. If a non-HPMS method used by the state does not achieve this goal, then an

adjustment factor should be applied to the state-estimated VMT to make it match the HPMS

report.
 149 HPMS VMT refers to the vehicle miles traveled reported to the Federal Highway Administration's Highway

Performance Monitoring System. Under this program, traffic counts taken on samples of an area's roadway

network are adjusted for day-of-week and season and expanded to include the area's entire roadway network. 

 150 SIP VMT refers to the vehicle miles traveled that is used to construct the mobile source emissions inventory.

 151 SIP functional systems and the VMT reported thereon may not be identical to those reported to the U.S.

DOT, if the state demonstrates that HPMS data are sufficiently uncertain and the competing alternative proposed by

the state is more accurate. Consult with divisional or regional FHWA officials who have direct knowledge of the

HPMS data associated with the non-attainment area.

 152 Exceptions to these general guidelines are described in sections 3.4.1.3 and 3.4.2.4. 153

U.S.D.O.T.Code Title

M 5600.1A Highway Performance Monitoring System (HPMS) Field Manual

M 5600.1A, Chg. 1 Highway Performance Monitoring System (HPMS) Field Manual Updates

M 5600.1A, Chg. 2

(Deleted by Chg. 3) Highway Performance Monitoring System (HPMS) Field Manual

M 5600.1A, Chg. 3 Highway Performance Monitoring System (HPMS) Field Manual

 154 Traffic Monitoring Guide, June, 1985, U.S. Department of Transportation, Federal Highway Administration,

Office of Highway Planning.

63

Consistency between HPMS VMT149 and SIP VMT150 means, in general, that the same

factors used within the FAUA to seasonally adjust and expand the HPMS 24- and 48-hour traffic

count samples by functional system and volume group to annual average daily traffic (AADT)

VMT should also be applied to all segments within the non-attainment area. Similarly, whatever

method is used to estimate VMT on local facilities within the state should also be applied to local

facilities within the non-attainment area. Finally, consistency means that the SIP functional

systems are identical to the HPMS functional systems.151, 152

Since the VOC, NOx, and summer CO emission inventories are typical summer day

inventories, VMT for ozone non-attainment areas should be adjusted to the summer season using

the inverse of the factors used to adjust summer 24- and 48-hour counts to AADT. Similarly,

VMT for winter CO emission inventories should be adjusted using the same technique. 

Modeling inventories for particular days should also be adjusted for average day-of-week

variations in VMT.

3.4.1.2 Overview of HPMS

Urban areas with populations over 50,000 are required to maintain formal transportation

planning programs in order to meet Federal requirements for securing transportation funds. 

These programs are intended to establish the analytical basis for assessing current and future

transportation needs and for evaluating projects that will satisfy those needs. Although not a

requirement of this process, the Highway Performance Monitoring System can be very useful to

it. 

The Highway Performance Monitoring System was developed by the U.S. Department of

Transportation Federal Highway Administration in the mid-1970s to collect and report

information on the nation's highways. Traffic data reporting for the system is documented in the

HPMS Field Manual153 and the Traffic Monitoring Guide.154
 155 Expansion factors for different FAUAs may be different, even within the same state.

 156 Vehicle counts taken by axle counting equipment require adjustment by axle correction factors. An

adjustment factor is the ratio of vehicles to axles as determined by a vehicle classification count.

64

The HPMS universe consists of all public highways or roads within a state. The reporting

strata for the HPMS include type of area (rural, small urban, and individual or collective

urbanized areas) and functional class. In rural areas the functional classes are Interstate, Other

Principal Arterial, Minor Arterial, Major Collector, and Minor Collector. In urban areas they are

Interstate, Other Freeway or Expressway, Other Principal Arterial, Minor Arterial, and Collector. 

A third level of stratification based on 13 volume groups was added as a statistical device to

reduce sample size, insure the inclusion of higher volume sections in the sample, and increase the

precision of VMT at a lower sample rate.

The HPMS sample design is a stratified simple random sample. The sample size

estimation process was tied to annual average daily traffic, although nearly 75 data items are

collected. The decision for using AADT was based partly on the fact that AADT is one of the

most variable data items in the HPMS. As such, the reliability of the other data is expected to

equal or exceed that of AADT. 

The HPMS sampling element was defined on the basis of road segments or links that

include both directions of travel and all travel lanes within the section. AADT variability was

estimated based on data from the 1976 National Highway Inventory and Performance Study

(NHIPS). Sample size was determined and the sample selected as a simple random sample

within strata according to predetermined levels of precision. For the higher volume strata the

sample size is estimated on the basis of providing a 90% confidence that the sample strata mean

was within + 5% of the universe strata mean. 

Typically 24- or 48-hour counts are taken on each sample segment once every three

years. These short counts are adjusted, based on day-of-week and season, to annual averages

using a small number of continuous traffic recorders. The HPMS expansion factors are

computed as the ratio of universe mileage to sample mileage within each stratum.155 This

procedure expands the HPMS sample to represent the universe of all roadways in the area by

multiplying each segment's AADT, segment length, and expansion factor and summing the

product for each sample section. Axle correction factors are also incorporated into the process.156

Growth factors are used to convert counts on sections unmonitored during a year to current year

annual estimates, i.e., segments not counted during the year of record are estimated by

multiplying the earlier counts by growth factors.
 157 There are three exceptions to this generality. In the first case, separate expansion factors may be available for

functional systems in the rural portion of the non-attainment area outside of the FAUA, and they should be used for

that area. In the second case, if a state uses a network model to spatially and/or temporally allocate HPMS VMT

(adjusted to match the HPMS total) within a non-attainment area, then the model's assignment to different

functional systems may prevail. In this second case, the model may show that intensity of use by functional system

may be quite different from one traffic analysis zone to another. See sections 3.4.2.4.1 and 3.4.2.4.2. Third, this

rule does not apply to any areas with weak HPMS data that have been set aside in favor of a competing alternative. 

65

While a statistically valid sample design could be developed independently of the HPMS,

the availability of the clearly defined and implemented HPMS sample design results in a

significant reduction of effort. The HPMS sample has now been implemented in every State, the

District of Columbia, and Puerto Rico. It provides a statistically valid, reliable, and consistent

data base for analysis within States, between States, and for any aggregation of States up to the

national level. 

3.4.1.3 Consistency Between HPMS and SIP VMT

VMT used to construct mobile source emission inventories should be consistent with that

reported through the HPMS. However, since the Federal Aid Urbanized Area geographic

boundaries of HPMS are not generally coincident with EPA's non-attainment area boundaries,

the two estimates of VMT will not necessarily be identical.

3.4.1.3.1 Expansion Factors

Consistency between HPMS VMT and SIP VMT means, in general, that the same factors

used to seasonally adjust and expand the HPMS 24- and 48-hour samples by functional system

and volume group to annual average daily traffic (AADT) VMT within the FAUA should also be

applied to all segments within the non-attainment area.157 This in effect assumes that all roads of

a given functional system and volume group are used with equal intensity, allowing geographic

allocation of total HPMS VMT within the non-attainment area based only on knowledge of

roadway miles. 

3.4.1.3.1.1 Non-Attainment Area the Same As the Federal Aid Urbanized Area

If the boundaries of the non-attainment area are coincident with the boundaries of the

FAUA, then the SIP VMT and HPMS VMT should be identical for each functional system. This

may require that state-estimated non-attainment area VMT be adjusted to make it equal the VMT

reported to HPMS.
 158 EPA will accept an adjustment based on total FAUA VMT and not require that separate adjustment factors be

applied to make VMT identical for each functional system and volume group, if a state demonstrates that the more

refined approach is infeasible. If a state elects this option, it should use equation (3-7a).

VMT(SIP) = (Roadway Miles(SIP) / Roadway Miles(FAUA))  VMT(FAUA) (3-7a)

 159 The functional systems listed are for an HPMS Urbanized Area. Rural areas classify highway facilities as

interstates, other principal arterials, minor arterials, major collectors and minor collectors.

 160 Volume groups vary by geographic area and functional system. Appendix F from the HPMS Operations

manual, included at the end of this report, is a listing of functional systems and volume groups within each HPMS

geographic area.

66

3.4.1.3.1.2 Non-Attainment Area Inside of the Federal Aid Urbanized Area

If the boundaries of the non-attainment area are entirely within the boundaries of the

FAUA, then the FAUA VMT by HPMS functional system should be allocated to the nonattainment area (by HPMS functional system) on the basis of the number of roadway miles

according to equation (3-7).158

VMT(SIP, f, v) = (Roadway Miles(SIP, f, v) / Roadway Miles(FAUA, f, v))  VMT(FAUA, f, v) (3-7) (3-7)

where FAUA = Federal Aid Urbanized Area

SIP = SIP Non-Attainment Area

f = Interstate System, Other Freeways and Expressways, Other 

Principal Arterials, Minor Arterials, Collectors159

v = Volume Group160

 VMT(SIP, f) = 
 VMT(SIP, f, v)

 all v 

3.4.1.3.1.3 Non-Attainment Area Outside of the Federal Aid Urbanized Area

If the non-attainment area is entirely outside the boundaries of all FAUAs within the state,

states may use any reasonable method to estimate 1990 VMT on the separate functional systems

within the non-attainment area. 
 161 Within HPMS, all rural areas within the state are grouped into one sampling universe.

 162 Alternatively, a state may estimate VMT on the basis of another rural area similar in terms of land use, etc.,

based on equation 3-8. 

 163 Other alternative methods of estimating VMT in this type of non-attainment area are discussed in section

3.4.1.6.

 164 If all of the FAUA is inside of the non-attainment area, equation 3-7 does not apply, since all FAUA VMT is

included as part of the total non-attainment area VMT estimate.

67

However, the recommended method of estimating VMT in a completely rural nonattainment area is on the basis of the expansion factors used for the universe of rural samples

within the state.161 The recommended method of allocating VMT to this type of non-attainment

area is described by equation (3-8).162, 163

VMT(SIP, f, v) = (Roadway Miles(SIP, f, v) / Roadway Miles(HPMS, f, v))  VMT(HPMS, f, v) (3-8)

where HPMS = HPMS Statewide Rural Area

SIP = SIP Non-Attainment Area

f = Functional System

v = Volume Group

 VMT (SIP, f) = 
 VMT(SIP, f, v)

 all v

3.4.1.3.1.4 Non-Attainment Area and Federal Aid Urbanized Area Crossover

If the boundaries of the non-attainment area are such that some of the non-attainment area

is inside an FAUA and some of it lies outside of any FAUA, then VMT in that portion of the

non-attainment area within the FAUA should be estimated by allocating HPMS FAUA VMT to

the non-attainment area on the basis of equation (3-7),164 (assuming that only some of the FAUA

is in the non-attainment area; if all of it is, allocation is not necessary), while VMT in that

portion outside of the FAUA should be estimated according to equation (3-8) and Section

3.4.1.3.1.3.

3.4.1.3.2 Local Functional System

Section 3.4.1.3.1.3 above applies only to VMT on functional systems designated collector and

above. While HPMS includes state-provided estimates of VMT on the local functional system,

these estimates are not now generally based on current ground counts at statistically

representative sites. Instead, the estimates are based on a method chosen by the state in light of

its own circumstances. States may continue to use the same method as they 
 165 A state may substitute, for the 1990 estimate of actual VMT accumulated on the local functional system, a

methodology superior to that used for HPMS reporting in the past, provided that the substitution is reflected both in

the required emission inventories and the attainment demonstrations. Similarly, if, after a state submits a required

emission inventory or an attainment demonstration, it wishes to change the methodology it used to estimate VMT

on the local functional system, it should re-submit its emission inventory and attainment demonstration using the

same alternative methodology. 

 166 Weather conditions may be too severe to take 24- or 48 hour traffic counts during the winter. In that case, it

may be possible to use continuous monitors within the inventory area to adjust summer counts to winter levels. 

National VMT monthly profiles could also be used to make the adjustment.

 

 167 Modeling inventories for particular days can also be adjusted for average day-of-week variations in VMT.

 168 The Urban Airshed model and its associate emissions preprocessor is an example of such a model. EPA also

maintains the Regional Oxidant Model, a mesoscale photochemical model providing coverage of the Northeastern

United States.

68

have used in the past to estimate 1990 VMT on the local functional system within the FAUA,

and they may also apply that method to the portion of the non-attainment area outside of the

FAUA.165 For example, local road VMT within the non-attainment area might be estimated as a

simple percentage of all collector and higher VMT.

 Proper estimation of actual travel on the local functional system is most important for

areas subject to the highest ambient ozone and CO concentrations. However, increasing the

accuracy of these estimates will require some lead time. 

3.4.1.3.3 Seasonal Adjustment

HPMS-based annual average daily VMT should also be adjusted for seasonal effects. 

Since the VOC, NOx, and summer CO emission inventories are typical summer weekday

inventories, VMT for ozone non-attainment areas should be adjusted to the summer season using

the inverse of the factors used to adjust the 24- and 48-hour counts to AADT. Similarly, VMT

for winter CO emission inventories should be adjusted using the same technique.166

3.4.1.3.4 Daily Adjustment

Since base year emission inventories must also be calculated for a typical day, a similar

adjustment using the inverse of the factors used to adjust the 24- and 48-hour counts to AADT

should be made to convert typical summer day VMT to typical summer weekday VMT and to

convert typical winter day VMT to typical winter weekday VMT.167

3.4.1.4 Allocating VMT to Time of Day

It may also be necessary to allocate daily VMT to each hour of the day. This is

commonly done for purposes of preparing emissions estimates for the photochemical grid

models used in forecasting ozone concentrations.168 The recommended method of 
 169 The Airshed Emission Preprocessor System has a default profile that can be used.

 170 One exception is that the Interstate System and Other Freeways and Expressways may be combined into a

single functional system. A second exception is that the Collector, Local, and Frontage Roads may be combined

into a single functional system.

 171 If a state has the capability of reporting rural or small urban area VMT directly, the indirect methods

described here for apportioning state-level VMT data to the applicable area are not appropriate.

 172 HPMS data submitted to FHWA on or before September 15th of the year following the year of record are

included in Highway Statistics. FHWA therefore considers the data in Highway Statistics preliminary and subject

to revision within the following twelve months. 

69

apportioning daily VMT to specific hours is to use the state's continuous monitors available

within the FAUA. If no such monitors exist within the non-attainment area being modeled, then

the state may rely on other continuous monitors located in areas similar in geographic, land use,

and demographic characteristics, or on those areas' final Airshed Emission Preprocessor

profiles.169

 

3.4.1.5 Allocating VMT to Functional Systems

To be consistent with HPMS, the SIP functional systems should, with few exceptions, be

identical to the HPMS functional systems (Interstate System, Other Freeways and Expressways,

Other Principal Arterials, Minor Arterials, and Collectors).170

The recommended method for estimating VMT on each HPMS functional system within

the non-attainment area is to follow the procedures outlined in Section 3.4.1.3; that is, to allocate

VMT on the basis of roadway miles and functional class. The underlying assumption in this

methodology is that VMT is generally a function of total roadway miles and that this relationship

becomes stronger as individual types of highway facilities within specific areas are considered.

3.4.1.6 Estimating VMT in Rural and Small Urban Areas171

The general process of estimating VMT in rural and small urban areas involves the

apportionment of statewide VMT to the county or other area for which mobile source emissions

estimates are required. Statewide VMT data are tabulated by all state transportation agencies and

reported to the Federal Highway Administration, which, in turn, annually publishes these and

other similar data in Highway Statistics. Highway Statistics is based upon and consistent with

HPMS.172

 

Central to the overall method of estimating VMT in rural and small urban areas is the

development of apportioning factors, which, when applied to the statewide total, yield areawide

VMT. Several options exist for apportioning VMT, such as roadway miles, motor 
 173 The recommended method for apportioning VMT in a completely rural non-attainment area is by roadway

miles. 

70

vehicle registrations, population, and fuel sales.173 The option selected will depend on the

availability of the required data. A key component of this process is the assistance of state and

county transportation engineers and planners who should be able to provide the best assessment

of both data availability and quality.

Once the apportioning method has been developed, the resulting factors are applied to

statewide VMT to produce estimates of areawide travel. Other data are applied to yield VMT by

roadway classification and vehicle type. 

Statewide VMT estimates are available directly from state transportation and highway

agencies and from Table VM-2 in Highway Statistics (included here as Table 3-3). To provide

the most accurate estimates of travel that occurred in 1990, the data contained in the 1991 edition

of Highway Statistics should be used. 

Areawide VMT is estimated by applying the allocation factor, Ff, to statewide VMT

statistics obtained from the state transportation agency, or from Table 3-3, from Highway

Statistics. Expressed as an equation, the estimated annual VMT occurring in the area is:

VMT(SIP, f) = Ff  VMT(State, f) (3-9)

where VMT(SIP, f) = estimated annual areawide VMT;

Ff = the apportioning factor to be applied to statewide VMT to 

estimate areawide VMT for functional system f, derived from 

one of equations 3-10 through 3-13;

VMT(State, f) = total statewide VMT for functional system f, obtained from the 

state transportation agency or from Table 3-3.

In all instances except where the apportioning factor is based on roadway miles (equation

3-10), the value assigned to VMT(State,f) is found in the TOTAL column for ALL HIGHWAY

CLASSES in Table 3-3. If equation 3-10 is used, the individual values of VMT for each

roadway type in urban and rural areas in Table 3-3 are used for VMT(State,f). Four methods for

apportioning statewide VMT to county or other subareas are presented below.

72

3.4.1.6.1 Apportionment of Statewide VMT-Recommended Method

The recommended method of allocating statewide VMT to rural or small urban areas is

on the basis of roadway miles by functional class. The underlying assumption in this method is

that VMT is generally a function of total roadway miles and that this relationship becomes

stronger as individual types of highway facilities within specific areas are considered.

State transportation and highway agencies report total roadway miles by functional class

(i.e., interstate, other freeways and expressways, other principal arterials, minor arterials, and

collectors) in urbanized, small urban, and rural areas, for both the Federal-Aid and non-FederalAid portions of the highway system. A summary of these data is published by FHWA in

Highway Statistics as Table HM-20, which is shown here as Table 3-4. As Tables 3-3 and 3-4

show, roadway miles and VMT are reported in exactly the same format, i.e., by functional class

on Federal-Aid and non-Federal-Aid highways in both urban and rural portions of each state. 

The one additional set of data required is the areawide roadway miles disaggregated by the same

categories as those for the statewide data. This information should be available directly from the

state transportation agency, or it can be derived based on input from both state and county

transportation agencies.

The VMT allocation factor is then derived as the ratio of areawide to state roadway miles

for each category of highway in the applicable rural or small urban area:

Ff

 = Roadway Miles(SIP, f) /Roadway Miles(State, f) (3-10)

where Ff = the apportioning factor to be applied to statewide VMT to 

estimate areawide VMT for functional system f;

Roadway Miles(SIP, f) = roadway miles of functional system f in the area;

Roadway Miles(State,f) = roadway miles of functional system f in the state.

The result will be as many as 13 individual allocation factors in each area, each of which

is applied to the corresponding VMT figure in Table 3-3 from Highway Statistics.

74

3.4.1.6.2 Apportionment of Statewide VMT-Alternative Methods

One of the remaining three apportioning methods may be used as an alternative to

apportioning by roadway miles in rural counties if the state can demonstrate that the

recommended method is either not feasible or less accurate than one of the alternative methods. 

Such might be the case in rural counties entirely outside of the non-attainment area but within a

photochemical modeling domain.

3.4.1.6.2.1 Motor Vehicle Registrations

The first of these alternative methods utilizes motor vehicle registration data to derive an

apportioning factor. The premise here is that the amount of travel occurring in an area is a

function of the area's vehicle population. This method assumes that travel by vehicles registered

outside the area is balanced by travel outside the area by vehicles registered in the area and that

individual areawide travel patterns are not significantly different from the statewide average for

the area in question.

The allocation factor is the ratio of areawide-registered vehicles to state-registered

vehicles. Registration statistics can be obtained from the state Department of Motor Vehicles

(DMV) for both the state and county, although there may be a requirement for special processing

of state registration files to produce areawide-specific data. The factor is defined by:

F = V(Area) / V(State) (3-11)

where F = the allocation factor to be applied to statewide VMT to derive areawide 

VMT;

V(Area) = total number of motor vehicles of all types registered in the area;

V(State) = total number of motor vehicles of all types registered in the state.

3.4.1.6.2.2 Population

A second alternative method for allocating statewide VMT apportions statewide VMT to

the area based on the relative area and state population. This method has the advantage of

utilizing data that are routinely available from several sources, such as the Bureau of Census and

state and county agencies, and therefore VMT estimates can be developed with minimal effort. It

is important to use 1990 data to allocate the travel in order to have a representative estimate of

the travel that occurred in the base year of the emissions inventory. The apportioning factor is:

F = P(Area) / P(State) (3-12)
75

where F = the allocation factor to be applied to statewide VMT to derive areawide 

VMT;

P(Area) = total population in the area;

P(State) = total population in the state.

3.4.1.6.2.3 Fuel Sales

Finally, statewide VMT can be apportioned to the area based on fuel sales data. An

assumption inherent in this method is that VMT and fuel sales are directly related. In order for

this method to be practical, areawide fuel sales data must be available. If such data are not

available, one of the other methods will need to be used.

All states collect taxes on motor fuel sold within their boundaries, and formal records are

maintained regarding both the fuel throughput and the revenue derived therefrom. Since these

statistics are usually aggregated as state totals, special processing may be required to identify fuel

sales by area. The data requirements should be discussed with appropriate officials in the state

taxation or revenue agency.

As a minimum, total annual sales (gallons) of gasoline and diesel fuel in both the area and

state are required. The monthly distribution of sales is also required. Note that each state reports

monthly fuel sales data to the Federal Highway Administration, which, in turn, reports various

fuel use statistics in Highway Statistics and in a monthly publication by FHWA entitled Motor

Fuel Consumption Reports (MF26G).

The apportioning factor is the ratio of areawide motor fuel use to state fuel use. Tables

MF-25 and MF-26, respectively, in Highway Statistics tabulate the monthly highway use of

special fuels and gasoline for each state in the U. S. These tables are included here as Tables 3-5

and 3-6. Special fuels are essentially diesel fuel and some liquified petroleum gases. Table MF26 indicates the actual use of gasoline and gasohol by highway vehicles; the data shown in that

table have been adjusted to account for handling losses and exclude gasoline used for nonhighway purposes. The VMT apportioning factor is:

F = G(Area) / G(State) (3-13)

where F = the allocation factor to be applied to statewide VMT to derive areawide 

VMT;

G(Area) = total quantity (gallons) of gasoline and diesel fuel sold in the area, 

obtained from the state revenue agency;

G(State) = total quantity (gallons) of gasoline and diesel fuel sold in the state, 

obtained from the state revenue agency or from Tables MF-25 and 

MF-26 in Highway Statistics.


 174 The Federal Transit Administration was formerly the Urban Mass Transit Administration (UMTA).

 175 Supplement 1 to "Methodology to Calculate Emission Factors for On-Road Motor Vehicles", California Air

Resources Board, Technical Support Division, January 1988.

78

3.4.2 Travel Demand Network Models

3.4.2.1 Role of Transportation Models in SIP Development

A common and highly useful information source for the preparation of the baseline

inventory is a transportation planning model run configured to the same base year (1990). With

this tool one is able to combine the appropriate travel estimates with emission factors developed

by MOBILE4.1 to prepare an estimate of the emissions inventory. In addition, network model

results can be used to develop certain critical inputs to the emission factor program. These

include speeds, vehicles' operating conditions, trip starts, trip ends, number of trips per day per

vehicle, and vehicle mix. In addition, network models can be used to spatially and temporally

allocate VMT, and therefore emissions, within the non-attainment area. However, since EPA

and DOT have both endorsed the Highway Performance Monitoring System as the most

appropriate means by which to measure VMT, the VMT estimates produced by the transportation

planning process should be made consistent with HPMS. The mechanism for making this

adjustment is discussed in Section 3.4.2.4.

The initial development of new transportation planning model runs for both a base and a

future year can take a substantial effort, especially for a large urban area. EPA recognizes that,

generally, local air quality agencies do not operate the transportation planning models themselves

and that they must work with the agencies responsible for the operation of such models. 

3.4.2.2 Background

An important element of the transportation planning process is an assessment of the

regional highway network. An extensive effort is required to collect and integrate the

information needed to assess how the network is currently used and where growth will occur in

the future. The mathematical models used to assess the effects of growth on the highway

network allow the transportation analyst to evaluate the improvements that are needed and when

they should be constructed. From the perspective of air quality, important products of these

models are estimates of VMT and speed on each of the links coded into the highway network. 

Basic requirements of the transportation planning process are an understanding of where

travel occurs, what factors stimulate it, and how demand is satisfied. The Federal Highway

Administration and the Federal Transit Administration (FTA)174 developed a series of models to

help communities satisfy these requirements. Historically, the most frequently used model has

been the Urban Transportation Planning System (UTPS).175 In recent years 
 176 UTPS as a computer system is no longer supported by either FHWA or FTA. However, although some of the

conventions used by UTPS may not be identical to those used by the other UTPS-type programs, they are similar,

since, generally, UTPS served as the prototype for these other programs. 

79

many variations of the UTPS have been developed in the private sector as Federal funding for the

model decreased and sufficiently powerful microcomputers became available.176

 

Responsibility for implementing and operating transportation planning models generally

falls into two categories: metropolitan planning organizations and state Departments of

Transportation. In some cases, transportation or planning agencies within communities operate

the models. Responsibility for operating the models generally falls outside of the jurisdiction of

the air quality planning agency. Thus, the development of an emissions inventory for an urban

area requires a cooperative effort between the air quality agency and the relevant transportation

planning agency (the one operating the UTPS-type model). This should not come as a surprise to

most communities, since a cooperative effort between the two types of agencies was required to

develop the SIP inventories in 1979 and 1982.

Despite the fact that air quality planners are not responsible for operating the highway

network models, it is important that they have an understanding of the principles guiding the

operation of the models and the information that they generate. Section 3.4.2.3 provides an

overview of UTPS-type operation and outputs. It is not designed to supplant the need to have a

transportation planner actively involved in both generating and assessing the travel information

used to prepare a highway emissions inventory estimate but does provide an introduction to the

transportation planning process.

3.4.2.3 Overview of Network Models

UTPS-type models consist of manual and computerized planning procedures that provide

decision-makers with information on long-range transit and roadway travel patterns. UTPS-type

computer-based packages allow planners to simulate the operation of a transportation system to

determine what would happen if population and economic activity increased and/or if changes

were made in either the roadway or transit networks. When population, economic activity, and

roadway and transit network inputs are matched to historical conditions, an estimate of VMT for

that year is produced. The estimate, however, is based on many assumptions and estimates, not

on direct observation of travel in that year. UTPS-type computer packages consist of a number

of programs that parallel steps in the transportation planning process. In general, this process

involves the following major steps:

 Representation of the roadway or transit system;

 Estimation of the number of current and future drivers and transit riders, the

 numbers of trips of various types they will choose to take in a typical day, and

 their trip origins and destinations;

 Assignment of trips to appropriate roads and transit routes; and

 Preparation of maps, tables and graphs to display results and compare different

 transportation alternatives.
 177 This description was abstracted from "UTPS Highway Network Development Guide", prepared by COMSIS

Corporation for the Federal Highway Administration, U.S. Department of Transportation, January 1983.

80

The capabilities of a UTPS-type package include estimation of the impacts of

long-range land development, transportation system costs, travel demand, and major facility and

corridor travel volumes. The package has been characterized as "data hungry". For most

applications, planners must prepare a description of the roadway and/or transit networks as well

as detailed demographic and economic forecasts. In addition, policy makers must agree on

transportation alternatives to be tested and identify the impacts about which they are interested. 

Depending on the complexity of problems to be addressed, the availability of raw data, and the

experience of the analytical staff, preparing initial inputs for a UTPS-type model can take from

two months to over two years. The following discussion provides a more detailed overview of

steps involved in configuring a UTPS-type package to a community.

The development of a realistic abstraction of the existing highway and/or transit

network is the most time-consuming step required to implement a UTPS-type package. A

network177 describes the characteristics of roads or transit lines to the computer in the same way a

map describes roads to a driver. The first step in network coding is the development of the zone

system.

Zones are geographic areas dividing the study area into relatively homogeneous

areas of land use, land activity, and aggregate travel demand. Zones represent the origins and

destinations of travel activity within the study area. Since it is not computationally feasible to

represent every household, place of employment, shopping center, and other activity as a

separate origin and destination, these entities are first aggregated into zones and then further

compressed into a single node. A centroid is a point that represents all travel origins and

destinations in a zone. Typically in the highway network, these centroids are connected to the

highway system at several points to represent the many paths over which each of the discrete

origins and destinations within a zone access the balance of the highway system.

Once the zone system is developed and mapped, zonal socioeconomic data can be

assembled for the transportation planning process. Zone centroids can be located in the center of

activity of the zone, using land use maps, aerial photographs, and local knowledge. The center of

activity is not necessarily the geographic center, but it is the midpoint of activity. The maximum

number of allowable zones in UTPS is 2,500. UTPS-type microcomputer packages may have

different limits. 

Selection of links is the second major step in developing a network, since links

represent those facilities (highways, roads, streets, etc.) that actually comprise the highway

system. The two nodes that mark a link's end points define the link in the transportation

network. Nodes can be defined as those locations in the highway system where vehicles are able

to change direction of travel (e.g., intersections, interchanges, etc.) or where the level of service

of a highway facility alters significantly (i.e., where a road narrows from four lanes to two lanes). 

It should also be noted that some nodes represent origins and destinations of 
 178 Highway Capacity Manual, Special Report 209, Transportation Research Board, National Research Council,

Washington, D.C., 1985.

81

travel within the study area. These nodes are actually centroids and, as such, represent

geographic units of travel demand at a single point. Figure 3-1 provides an example of network

components.

In most UTPS-type applications travel time must be assigned to the link, since

links define the actual paths along which traffic flows through the study area. UTPS conventions

also call for separate links to designate opposite travel directions. One link is used to represent

the east-west direction of flow, for example, and another to represent the west-east direction.

UTPS allows for a variety of highway attributes to be associated with each link,

including:

  x-y coordinates to locate the nodes for plotting purposes;

  zones, which generally follow census data boundaries;

  geographic locations that generally define a corridor or larger (than zone)

 indication of location;

  area types to describe the kind of business or residential development that may

 be occurring around the node or link; and

  turn penalties and prohibitions to provide an indication of additional time

 required to make a particular movement through a node.

Link attributes summarize basic network information about highway facilities and are

generally grouped into three broad categories.

3.4.2.3.1 Level of Service

Level of service is a qualitative measure describing operational conditions within a traffic

stream and their perception by motorists and/or passengers. A level-of-service definition

generally describes these conditions in terms of such factors as speed and travel time, freedom to

maneuver, traffic interruptions, comfort and convenience, and safety.

Level of service is used to determine path choice and vehicle assignments in the network. 

Six levels of service are defined for each type of facility for which analysis procedures are

available. They are given letter designations, from A to F, with level-of-service A representing

the best operating conditions, and level-of-service F, the worst.178

83

3.4.2.3.2 Physical Attributes

Physical attributes describe the type of area where a link is located, the number of lanes,

and its observed volume. The functional system of a link serves as an index to the link

speed/capacity tables. These tables assign free flow speed and per-roadway capacity to the links

using a single digit integer. The integer corresponds to default speed/capacity values:

Functional

System Code Functional System

1 Freeway

2 Expressway

3 Two-way arterial with curb parking

4 One-way arterial without parking

6 Two-way arterial without parking

All other coded values (5 or greater than 6) are treated as centroid connector links in the

default condition. The interpretation of functional system codes can be changed by modifying

the speed/capacity table values. Functional system is also used to aggregate and summarize

traffic assignment results in output reports.

Example speed/capacity tables are provided as Figures 3-2 and 3-3.

Area type describes the part of the area in which the facility is located. Like functional

system, area type is indexed to the speed/capacity table so that free flow speed and capacity can

be determined. Single digit integers used to represent link area types are:

Area Type

Code Area Type

1 Central business district (CBD)

2 CBD Fringe

3 Residential

4 Outlying

All other values (greater than 4) are interpreted in the default table as rural values. The

interpretation of area type codes can be changed by modifying the default values in the

speed/capacity table. Information on traffic assignment results can also be aggregated by area

type in output reports.

3.4.2.3.3 Locational Link Attributes

Locational link attributes define each link's place in the study area in relation to other

links. These attributes include the area type in which the link lies, the analysis zone in which it is

found, its geographic location, and the group of links with which it belongs. With the exception

of geographic location, the other link attributes have already been defined. 


 179 The following descriptions of trip generation, trip distribution, modal split, and traffic assignment were

obtained from Urban Origin-Destination Surveys, U.S. Department of Transportation, Federal Highway

Administration, Washington, D.C.

86

It is important that air quality analysts understand the basic structure of the networks

employed in a UTPS-type package so that they can interpret and manipulate the various output

reports that are available from the individual programs. The remaining steps179 in the

transportation planning process are as follows.

3.4.2.3.4 Trip Generation

The relationships between trip making and the social-economic characteristics of the

residents of an urban area, as well as the relationships between trip making and land use, are

obtained from travel data and land use inventories. Trip generation procedures, which relate

these characteristics, are then developed. There are several trip generation procedures available,

such as regression analysis, cross classification analysis, and rate analysis.

Forecasted social, economic, and land use data are substituted for base year data in the

trip generation procedure, and forecasts of trips are obtained for each analysis unit.

3.4.2.3.5 Trip Distribution

The origin-destination data collected in dwelling unit, truck, taxi, and external surveys

provide an estimate of the existing travel taking place within, into, out of, and through the urban

area on an average day. The trip distribution model is developed to simulate the manner in

which trips are made between small analysis units within the study area. The Gravity Model is

used in various urban areas throughout the United States. 

3.4.2.3.6 Modal Split

This term is used to define the division of total person trips in an urban area between

public (buses, trains, etc.) and private (automobiles, trucks, etc.) transportation, or the process of

separating person trips by mode of travel. Thus, a modal split model is one that is used to

forecast the amount of person trip travel that will use mass transit facilities. The calibration of

this model is dependent upon the relationships that have been found from the travel data

collected for the study year. Modal split analysis varies in the degree of complexity, ranging

from simple estimates in smaller urban areas to complex mathematical relations in larger areas. 

It generally involves characteristics of the trip maker, the trip, and the transportation system.

3.4.2.3.7 Traffic Assignment

The trip data collected in travel surveys describe the total number of trips occurring

between small analysis areas; however, these surveys do not collect data that describe the

specific routes used to travel from an origin to a destination. Consequently, a traffic assignment

technique is developed. This technique can be used to estimate the routes of 
 180 The Federal District Court of Northern California ruled that where a model had the capability to incorporate

feedback effects, the planning agency was obligated to project travel with those effects included.

 181 EPA considers that the feedback effect between trip assignment and the trip origin/destination distribution is

the most important at this time, given the current state of modeling practice and the potential for model

improvement that incorporating such effects may have. The link travel times used for trip distribution should be

consistent with the result of the trip assignment step. 

87

travel that are used for trips occurring within the urban area. Traffic assignment may be

described as the process of allocating trip interchanges to a specific transportation network. It is

a tool that allows the transportation planner to assign either present trips (those trip interchanges

between zones obtained from the travel surveys) or future trips (those forecasted for some future

year) to various alternative transportation systems. 

3.4.2.3.8 Feedback

Feedback refers generally to the relationships within and among the various steps of the

transportation process. For example, in trip assignment, the constrained equilibrium approach

first assigns trips to pathways that result in the quickest journey under an initial set of link-speed

assumptions. However, under the constrained equilibrium algorithm, the initial set of speeds is

altered as trips are assigned. As more and more trips are assigned to links, vehicle speed is

reduced, often to the point where alternate routes from point A to point B are quicker.

Feedback among different planning steps is also logically important but often not

implemented. For example, travel projections from transportation models are often not fed back

to the original regional growth and land use projections that formed the basis for the

transportation model. Ideally, this type of feedback should also proceed to equilibrium. 

However, there is now only limited information in the literature that describes exactly how to

incorporate feedback effects, particularly feedback all the way back to regional growth and land

use assumptions. Further, estimates of the degree to which incorporating such effects changes

predictions of travel behavior are also limited.180, 181

 

3.4.2.4 Consistency Between Transportation Model VMT and HPMS

EPA encourages the use of transportation models in the development of SIP emission

inventories. A transportation planning model run configured to the same base year (1990) as the

required emission inventory can be an excellent source of geographic and temporal detail for

transportation activity levels. However, since EPA and DOT both endorse the Highway

Performance Monitoring System as the appropriate means by which to measure VMT, the

detailed VMT estimates produced by the transportation planning process should be made

consistent in the aggregate with HPMS. 

The process of making the network model VMT estimates consistent with HPMS VMT

estimates begins with the procedures discussed in Section 3.4.1. Recall that since the Federal

Aid Urbanized Area boundaries of HPMS are not generally coincident with EPA's 
 182 Using HPMS rural area expansion factors is equivalent to allocating state rural totals by roadway miles.

 183 Interstate system, other freeways and expressways, other principal arterials, minor arterials, and collectors.

 184 Non-attainment area VMT is the HPMS-based VMT estimated by the procedures described in Section

 3.4.1.

 185 States are encouraged to make separate adjustments for each HPMS functional system. However, a state may

demonstrate that the more refined approach is infeasible due to inconsistent classification schemes, data problems,

or constraints on time and staff. If it is not be possible to identify network links with HPMS functional systems, a

state may adjust VMT and other network factors according to equation 3-14a. 

VMT(Adj. Network, i) = (VMT(SIP) / VMT(Network))  VMT(Network, i) (3-14a)

 186 Other network model parameters, such as the number of trips, number of cold starts, etc., (if used) should be

increased or decreased by the same factor(s) so that, for example, evaporative emissions are correctly converted to

grams per mile emission rates and so that cold start emissions are correctly weighted into an overall emission factor.

88

non-attainment area boundaries, the HPMS and non-attainment area VMT estimates will not

necessarily be identical. Therefore, the first step in making network model VMT consistent with

HPMS VMT is to make non-attainment area VMT consistent with HPMS VMT. Once that is

accomplished, that consistent non-attainment area VMT becomes the benchmark VMT to which

network model VMT should be adjusted.

The actual adjustment of network model VMT is straightforward and parallels the

discussion in Section 3.4.1.3.182

 

3.4.2.4.1 Non-Attainment Area the Same As the Network Model Area

Even if the boundaries of the non-attainment area are coincident with the geographic

domain of the network model, there are several reasons why the estimates of VMT produced by

the HPMS and the network model may be different. 

 Not all higher level functional system links183 may be coded into the 

network;

 Links on local functional systems may not be coded at all;

 Network VMT may be estimated for different time periods; e.g., annual rather 

than seasonal, average day rather than average weekday, separate peak and 

off-peak travel estimates rather than an average weighted by hour-of-the-day.

If the boundaries of the non-attainment area are coincident with the boundaries of the

travel demand network model, then network model VMT and non-attainment area VMT184

should be made identical. The adjustment required to achieve this identity is described by

equation 3-14.185, 186
 187 Defined by equations 3-7, 3-7a and/or 3-8.

 188 Under some circumstances the adjustment factor could be based on an area other than the non-attainment

area. For example, a designated CO non-attainment area may be considerably smaller than either the geographic

domain of the network or the FAUA. In this case, if the network domain exceeds the FAUA boundaries, then the

VMT contained within the FAUA, including VMT on local and other functional systems, could be the point of

departure for equation 3-14. Or, if the network domain is smaller than the FAUA, network VMT could be

supplemented with reasonable estimates of VMT outside of the network but within the FAUA, and that total VMT

could be the point of departure for equation 3-14. A state may elect this option, provided that it demonstrates that it

produces a more accurate estimate of VMT than equations 3-7, 3-7a and/or 3-8. Further, the state must continue to

utilize the same approach for all of its CAAA reporting requirements. EPA Regional Offices are advised that use of

equations 3-7, 3-7a and/or 3-8 is presumed to be the better approach for ozone non-attainment areas.

 189 Within HPMS all rural areas within the state are also grouped into one sampling universe. One alternative to

estimating VMT on the basis of another rural area similar in terms of land use, etc., is to base the estimate on all

other fully rural areas combined.

89

VMT(Adj. Network, i) = (VMT(SIP, f) / VMT(Network, f))  VMT(Network, i) (3-14)

where VMT(Adj. Network, i) = Adj. Network Model VMT

VMT(SIP, f) = SIP Non-Attainment Area VMT187, 188

VMT(Network, i) = Original Network Model VMT

f = Functional System

i = Individual network link or group of links (e.g., links of 

one functional system in one area type)

3.4.2.4.2 Non-Attainment Area Inside of the Network Model Area

If the boundaries of the non-attainment area are entirely within the geographic domain of

the network model, then the procedures described in Section 3.4.1.3.1.2 should be used to

calculate an adjusted network VMT. This requires that network links or portions thereof are

identified as to whether or not they are in the non-attainment area. 

3.4.2.4.3 Non-Attainment Area Outside of the Network Model Area

If the boundaries of the non-attainment area are entirely outside of the geographic domain

of the network model, then the procedures described in Section 3.4.1.3.1.3 should be used to

calculate VMT. 

The recommended method of estimating VMT in a completely rural non-attainment area

is on the basis of the HPMS expansion factors used for an area within the state that is comparable

in terms of land use, transportation use, and demographic characteristics.189 
 190 Other alternative methods of estimating VMT in this type of non-attainment area are discussed in section

3.4.1.6.

 191 Interstate system, other freeways and expressways, other principal arterials, minor arterials, and collectors.

90

The recommended method of allocating VMT to this type of non-attainment area is described by

equation (3-15).190 This equation is similar to equation (3-8), which describes how to allocate

VMT to a non-attainment area completely outside of the FAUA.

VMT(SIP, f, v) = (Roadway Miles(SIP, f, v) / Roadway Miles(HPMS, f, v))  VMT(HPMS, f,v ) (3-15)

where HPMS = Applicable HPMS Area

SIP = SIP Non-Attainment Area

f = Functional System

v = Volume Group

3.4.2.4.4 Non-Attainment Area and Network Model Area Crossover

If the boundaries of the non-attainment area are neither entirely outside nor entirely inside

the geographic domain of the network model, then a combination of the approaches described in

Sections 3.4.2.4.2 and 3.4.2.4.3 will need to be applied. VMT in that portion of the nonattainment area that is within the network model's geographic domain should be based on

equation 3-14; VMT in that portion of the non-attainment area that is outside of the network

should be based on the procedures described in Section 3.4.1.3.1.3. 

3.4.2.5 Local Functional System

Regional planning analyses frequently only represent the higher functional systems.191

While in smaller urban areas the level of detail on the lower functional systems may be higher,

conversations with FHWA officials have indicated that the local roads normally excluded from

the network can represent up to 15 percent of the VMT that occurs in the planning area.

Further, the low speeds generally recorded on these streets can magnify their emissions

contribution to the inventory. This omission can lead to a significant underestimate of the

highway contribution to the total emissions inventory.

Therefore, if not accounted for by the highway network model explicitly, a separate

estimate of the travel occurring within the transportation planning area on these lower functional

systems must be prepared. The estimate of VMT may be based on MPO or DOT 
 192 See section 3.4.1.3.2.

 193 Modeling inventories for particular days should also be adjusted for average day-of-week variations in VMT.

 194 One exception is that the Interstate System and Other Freeways and Expressways may be combined into a

single functional system. A second exception is that the Collector, Local, and Frontage Roads may be combined

into a single functional system. Finally, if it is not possible to map the classification system built into the network

model into the HPMS functional systems, then the state may develop its own typing scheme as long as it is

reasonable and represents the entire roadway network. 

91

judgment and/or FHWA studies of areas of comparable size.192 The estimate of off-network

VMT should be added to network VMT prior to use of equation 3-14.

3.4.2.6 Seasonal Adjustment

HPMS Annual Average Daily VMT should also be adjusted for seasonal effects. Since

the VOC, NOx, and summer CO emission inventories are typical summer weekday inventories,

VMT for ozone non-attainment areas should be adjusted to the summer season using the inverse

of the factors used to adjust the 24- and 48-hour counts to AADT. Similarly, VMT for winter

CO emission inventories should be adjusted using the same technique. 

3.4.2.7 Daily Adjustment

Since base year emission inventories must also be calculated for a typical day, a similar

adjustment using the inverse of the factors used to adjust the 24- and 48-hour counts to AADT

should be made to convert typical summer day VMT to typical summer weekday VMT and to

convert typical winter day VMT to typical winter weekday VMT.193

3.4.2.8 Allocating VMT to Time of Day

It may also be necessary to allocate daily VMT to each hour of the day. This is

commonly done for purposes of preparing emissions estimates for the photochemical grid

models used in forecasting ozone concentrations. The recommended method of apportioning

daily VMT to specific hours is to use the HPMS continuous monitors available within the

FAUA. If no such monitors exist within the non-attainment area being modeled, then the state

may rely on other continuous monitors located in areas similar in geographic, land use, and

demographic characteristics. 

3.4.2.9 Allocating VMT to Functional Systems

To be consistent with HPMS, the SIP functional systems should, with few exceptions, be

identical to the HPMS functional systems (Interstate System, Other Freeways and Expressways,

Other Principal Arterials, Minor Arterials, and Collectors).194
 195 If 1990 demographic and economic input data are used, a model validated for 1987 or later could provide an

acceptable VMT estimate for 1990. 

 196 EPA Regional Offices are advised not to agree that the HPMS data are weak without consulting with

divisional or regional FHWA officials who have direct knowledge of the HPMS data associated with the nonattainment area. Desirable features of a network model that is a candidate for SIP VMT estimation are that a) the

model is validated with 1990 ground counts and that b) the model uses demographic inputs properly updated to

1990. (At a minimum, population by zone should be updated to 1990; preferably all socio-economic variables

would also be updated to 1990.)

 197 EPA Regional Offices are encouraged to consult with divisional or regional FHWA officials who have direct

knowledge of the network-based model under consideration. 

92

The recommended method for estimating VMT on each HPMS functional system within

the non-attainment area is to follow the procedures outlined in Section 3.4.1.3; that is, to allocate

VMT on the basis of roadway miles and functional class. The underlying assumption in this

methodology is that VMT is generally a function of total roadway miles and that this relationship

becomes more direct as individual types of highway facilities within specific areas are

considered.

3.4.3 Exception to the Use of HPMS VMT

Since 1990 ground counts submitted to HPMS may not be as comprehensive and of as

high a quality as FHWA intends all states to obtain for 1993 and later and since it may be

possible for network-based travel demand models to be validated for 1990,195 this guidance

allows for the use of travel demand models to estimate 1990 VMT under certain circumstances. 

However, this method is not considered to be viable for most areas due to the general disrepair of

a large number of network models. Areas should use this method only if their network model is

particularly strong and their 1990 HPMS data are particularly weak, and only after consulting

with EPA.196 

An affected area with a strong network-based travel demand model that is based on

reasonably recent demographic trip-making data may use its model to estimate 1990 VMT after

consultation with EPA197 and under the following conditions:

 Urban areas within the state were not sampled separately under HPMS in

1990;

  The state Department of Transportation did not adequately follow HPMS

guidance in 1990, resulting in poor quality traffic counts;

  The state has made substantial progress in preparing its 1990 inventory using

a network-based model and does not have the time and resources to switch

approaches and still meet the Clean Air Act expectations for the November

1992, 1993, and 1994 SIP submittals. 
93

An area using this method should make sure that all VMT in the entire non-attainment

area is included in the estimate. Most network-based models normally do not assign intra-zonal

trips, VMT on some local roads, or trips on functional classes outside of the modeling area. 

States may use any reasonable method to estimate VMT on those functional systems that are

within the non-attainment area but that are not included in the model. 

States adopting this approach should realize that, beginning in 1993, all urbanized areas

with a population above 200,000 will be required to conduct HPMS sample panels for individual

FAUAs and, therefore, will be required to estimate mobile source emissions in such a way that

the VMT estimates used by the state are consistent with HPMS. This means that there should be

no reason for an ozone area with poor HPMS data in 1990 not to base the "periodic inventory"

for 1993 and the Reasonable Further Progress tracking inventory for 1996 on HPMS estimates,

even if EPA accepted another method for the 1990 inventory. This switch in basis for the

inventory may reveal that the method used for 1990 was not accurate, and it may be

disadvantageous in terms of demonstrating progress in emissions reduction. A possible solution

is for the area to project 1990 VMT backwards from the higher quality 1993 HPMS figures and

submit a revision of its 1990 inventory using this revised estimate of 1990 VMT. Where the

disparity between 1990 and 1993 estimates by two different methods appears to EPA to

constitute an erroneous estimate of actual VMT changes, EPA may require such backward

projections from 1993 data. 
94

Appendix 3-A

Prescribed Volume Groups and Precision Levels



 198 U.S. Environmental Protection Agency. Nonroad Engine and Vehicle Emission Study, Report and

Appendices, EPA-21A-2001, Washington, D.C., Office of Air and Radiation, November 1991.

98

4.0 EMISSIONS FROM NONROAD SOURCES

4.1 Introduction

Nonroad sources include motorized vehicles and equipment which are normally not

operated on public roadways to provide transportation. The study and regulation of nonroad

emission sources is mandated by the 1990 Clean Air Act. Section 213(a) of the 1990 Clean Air

Act directs EPA to conduct a study of emissions from nonroad engines and vehicles in order to

determine if such emissions cause, or significantly contribute to, air pollution which may be

reasonably anticipated to endanger public health or welfare. This study was completed in

November 1991.198 The Clean Air Act also requires EPA to regulate emissions from nonroad

engines and vehicles within 12 months after completion of the study if EPA makes a

determination that these sources are significant contributors to concentrations of ozone or carbon

monoxide (CO) in more than one area which has failed to attain the National Ambient Air

Quality Standards (NAAQS) for these pollutants. 

This chapter summarizes and discusses information from several studies, which EPA

used to define emission factors and inventories for nonroad equipment. It also discusses work

updating and expanding nonroad equipment inventories for use by state and local agencies. The

nonroad inventories for the 24 non-attainment areas in the November 1991 EPA nonroad report

are presently being updated to include areas that are within the recently redefined non-attainment

boundaries. Inventories will also be compiled for nine additional areas. A sample inventory of

nonroad equipment populations and emissions in the New York-New Jersey area is provided in

this chapter (Appendix 4-A). States should use this chapter to guide them in the preparation of

nonroad emission inventories for use in determining needed VOC reductions and developing

implementation plans. The ten nonroad equipment categories are listed below.

 Lawn and Garden Equipment

 Agricultural Equipment

 Logging Equipment

 Light Commercial Equipment

 Industrial Equipment

 Construction Equipment

 Airport Service Equipment

 Recreational Equipment

 Recreational Marine Equipment

  Commercial Marine Vessels
 199 U.S. Environmental Protection Agency. Nonroad Engine and Vehicle Emission Study, Report and

Appendices, EPA-21A-2001, Washington, D.C., Office of Air and Radiation, November 1991.

99

A description of these categories, including the 79 equipment types within them, can be

found in Appendix B of this chapter. In general, each equipment type comes in three possible

engine types: diesel, 4-stroke, and 2-stroke. However, for some types of equipment, there are no

two-stroke engines, but units fueled by propane or CNG are in service. For simplicity, propane

and CNG equipment is included in the 2-stroke engine type tables, but with their correct

emission factors when operated on gaseous fuel. 

4.2 Inventory Options Under This Guidance

In its nonroad report, entitled "Nonroad Engine and Vehicle Emission Study," EPA

developed two emission inventories for the first nine categories listed above and a single

inventory for the tenth.199

The first nine categories consist of nonroad engines and vehicles for 24 areas. Inventories

for the last equipment category (commercial marine vessels) are only approximate and available

for only six areas. 

For the first inventory, designated as Inventory A, EPA used commercially and publicly

available data so that the method could be repeated by state agencies and other groups. EPA

used confidential industry-supplied sales and other data, which are not publicly available, for the

second inventory, Inventory B. The second inventory provided EPA with a cross check for the

first inventory results. Both inventories agreed reasonably well.

4.2.1 Options for Areas With EPA Provided Inventories

 EPA has contracted with Energy and Environmental Analysis, Inc. to update the nonroad

equipment inventories based on new non-attainment boundaries for ozone and carbon monoxide

for the 24 areas in the nonroad report. These areas, which were selected to be geographically

representative of areas with significant air pollution problems, are defined as metropolitan

statistical areas (MSAs), consolidated metropolitan statistical areas (CMSAs), north east county

metropolitan areas (NECMAs), or air basins. The exact definitions of these terms can be found

in the State and County Metropolitan Area Data Book, U.S. Bureau of the Census, 1986. These

areas are listed below, as presented in Table 1-03 of the EPA nonroad report.
 200 U.S. Environmental Protection Agency. Designation of Areas for Air Quality Planning Purposes, 40 CFR

Part 81, Final Rule, Washington, D.C., Office of Air and Radiation, November 6, 1991. 

100

 Atlanta, Georgia MSA

 Baltimore, Maryland MSA

 Baton Rouge, Louisiana MSA

 Boston-Lawrence-Salem-Lowell-Brockton, Massachusetts NECMA

 Chicago-Gary-Lake County, Illinois, Indiana, Wisconsin CMSA

 Cleveland-Akron-Lorain, Ohio CMSA

 Denver-Boulder, Colorado CMSA

 El Paso, Texas MSA

 Hartford-New Britain-Middletown-Bristol, Connecticut NECMA

 Houston-Galveston-Brazoria, Texas CMSA

 Miami-Fort Lauderdale, Florida CMSA

 Milwaukee-Racine, Wisconsin CMSA

 Minneapolis-St. Paul, Minnesota-Wisconsin MSA

 New York-Northern New Jersey-Long Island, New York-New JerseyConnecticut CMSA/NECMA

 Philadelphia-Wilmington-Trenton, Pennsylvania-New JerseyDelaware-Maryland CMSA

 Provo-Orem, Utah MSA

 St. Louis, Missouri-Illinois MSA

 San Diego, California Air Basin

 San Joaquin, California Air Basin

 Seattle-Tacoma, Washington CMSA

 South Coast, California Air Basin

 Spokane, Washington MSA

 Springfield, Massachusetts NECMA

 Washington, D.C.-Maryland-Virginia MSA

Air quality non-attainment boundaries, established by the Office of Air Quality Planning

and Standards, for these and all other areas are defined in the November 6, 1991, Federal

Register Notice, "Designation of Areas for Air Quality Planning Purposes".200 The new

boundaries sometimes divide up counties and MSAs/CMSAs. A county or MSA/CMSA was

divided in this manner if a state and/or local government could show that sources in a part of the

county or MSA/CMSA did not contribute significantly to violations of the ambient standard.

In addition, EPA is developing inventories for nine additional areas. With these

additional areas, EPA will have determined nonroad inventories for all moderate-2 or worse nonattainment areas for CO (greater than 12.7 ppm), all the areas in serious or worse non-attainment

for ozone (16.0 ppm or greater), and several miscellaneous areas. These additional areas are

listed below. 
101

 Anchorage, Alaska

 Tucson, Arizona

Pima County

 Las Vegas, Nevada

 Phoenix, Arizona

Maricopa County

 Muskegon, Michigan

 Portsmouth-Dover-Rochester Area, New Hampshire

Rockingham County

Strafford County

 Providence, Rhode Island

 Beaumont-Port Arthur, Texas

 Sheboygan, Wisconsin

4.2.2 Options For Areas With EPA Provided Inventories

For the 33 areas listed above, states have several options as listed below. For the 24 areas

originally included in the EPA nonroad report, there are three EPA inventories that can be used.

 (A+B)/2 Inventory

 Inventory A

 Inventory B

State and local agencies wanting to examine these inventories should send in the request

sheet at the end of this chapter for a disk with the inventories in Lotus compatible files and a

report discussing them. In general, the average of inventories A and B is preferred since it

utilizes all available input, both from the EPA study and that provided by industry. However,

either the A or B inventory may be used by either category or equipment type if local agencies

have data or knowledge to support its use over the average of the two inventories. With

sufficient technical justification, states may also move equipment types and emissions

inventories among counties within the non-attainment area in a way which they believe to be

more realistic. All such changes should be noted in the documentation of the inventory. Also,

any changes that are made should be kept within the given non-attainment area, unless the state

does a comprehensive analysis of the equipment type across the entire CMSA/MSA.

 

Limited data for commercial marine vessels can be found in the EPA nonroad report for

the six areas listed below.

 Baltimore  New York-New Jersey

 Baton Rouge  Philadelphia

 Houston-Galveston  Seattle/Tacoma
 201 Booz Allen & Hamilton, Inc. Commercial Marine Vessel Contributions to Emission Inventories, Final

Report to Environmental Protection Agency. Los Angeles, California, October 7, 1991.

102

The three types of commercial vessels include harbor, ocean-going, and fishing vessels. 

States may use the commercial marine inventories found in the Booz, Allen, and Hamilton report

for these six areas, making and documenting whatever changes are needed to include only partial

county areas where appropriate.201 States may also use the methodology in this report to create

local inventories. Upon request, EPA will supply the states with the Booz, Allen, & Hamilton

report. States may also use the methodology in the previous edition of Volume IV, being certain

that commercial and recreational marine are handled as separate categories.

4.2.3 Options For Areas Without EPA Provided Inventories

For areas not among the 33 areas listed above, there are several options. The states may

choose one of the 33 areas, which is similar in terms of climate and economic activity, so that

emission inventories can be produced by applying the ratio of the populations of the two areas. 

States may opt to produce inventories by doing a ratio of the populations at the county level,

choosing counties from several of the 33 areas if appropriate. Please use the form at the end of

this chapter to request one or more of the 33 non-attainment area inventories. States may also

use the EPA methodology, using local data to develop inventories for one or all of the nine

categories. States may also apply the Energy and Environmental Analysis, Inc. methodology

themselves or obtain consultant services to do so. If for some reason one of the two methods

discussed above cannot be used for areas not among the 33 areas already inventoried, states may

use the 1989 Volume IV guidance. However, this should only be considered as an option of last

resort. Other approaches may also be used if they have technical support at least equal to or

better than the EPA methodologies.

4.3 Explanation of EPA Provided Inventory

Nonroad emission inventories have been calculated for 33 areas, including all areas that

are serious and above for ozone and moderate-2 and above for carbon monoxide. The

inventories can be used in turn to develop the Area and Mobile Source (AMS) inputs for the

Aerometric Information and Retrieval System (AIRS), which is discussed in Section 4.4. The

AMS inputs can in turn be used to recreate nonroad inventories. Since the AMS methodology is

the official way to calculate and document the inventory, the use of AMS inputs is needed.
 202 SAF stands for seasonal adjustment factor. The columns 1/SAF are taken directly from the spread sheets

used for the EPA nonroad report. Although, SAF itself is in units of tons per seasonal day/tons per year and is used

to multiply the annual inventory to obtain seasonal tons/day.

 203 U.S. Environmental Protection Agency. Designation of Areas for Air Quality Planning Purposes, 40 CFR

Part 81, Final Rule, Washington, D.C., Office of Air and Radiation, November 6, 1991.

103

Section 4.3.1 explains how the AMS inputs are derived from the EPA inventories. 

Section 4.3.2 explains the AMS inputs themselves and how they can be used to calculate

emission inventories. The general methodology used in developing the EPA inventories will be

explained later in Section 4.4.

4.3.1 Derivation of AMS Inputs

The following general information is included in the overall EPA nonroad inventory

tables.

 Equipment population (for ozone and CO non-attainment areas)

 Emission factors (g/hp-hr, g/hr, g/gal, g/day)

 Hours/year (gallons/year in some cases)

 Average horsepower

 Average load

 Evaporative emission season (229 days)

 1/SAF202 (tons per year/tons per summer day)

 1/SAF (tons per year/tons per winter day)

 VOC tons per summer day (ozone non-attainment area)

 NOx tons per summer day (ozone non-attainment area)

 CO tons per summer day (ozone non-attainment area)

 CO tons per winter day (CO non-attainment area)

 Particulates tons per year

 Population (human) and tons/person

Each non-attainment area is broken down into individual counties and, where appropriate,

portions of counties that are included within the non-attainment boundaries (i.e., townships and

boroughs). The methodology for developing the county and sub-county data is summarized in

Section 4.4. The above information is given as needed for each county or sub-county, as well as

the non-attainment area as a whole. The sub-county boundaries are defined in the November 6,

1991, 40 CFR Part 81.203

Emission factors are given for 79 equipment types and include VOC, CO, NOx, and

particulates. VOC emissions are divided into the following subcategories.
104

 exhaust

 evaporative

 crankcase

 refueling

These emission factors are derived from EPA and other test data with appropriate

extrapolations to the different equipment types. Evaporative emissions presently include only

diurnal emissions assumed to occur for 229 days of the year. Note that particulate inventories

are being calculated simply because the information is available. These calculations are only

being done for ozone and CO non-attainment boundaries, rather than the specific boundaries for

PM10. The reason for this is that the emphasis of the present work is on ozone and CO nonattainment. A sample inventory calculation using the given information is shown in Appendix 4-

C.

It is important to note that the definition of VOC excludes methane and ethane but

includes formaldehyde and acetaldehyde. Instead of VOC, the 1991 EPA nonroad report

contains total hydrocarbons (THC, as measured by a flame ionization detector), which includes

methane and ethane but excludes formaldehyde and part of acetaldehyde. In the process of

revising the emission inventories for the original 24 areas and developing inventories for the

additional areas, THC has been converted into VOC for 4-stroke and diesel equipment using a

correction factor. This is being done in order for the data to be compatible with AMS, as

discussed in Section 4.3.2. For 2-stroke engines it is being assumed that THC is equivalent to

VOC (that is, a THC to VOC correction factor of 1.00). One reason for this assumption is that 2-

stroke emissions contain significant amounts of unburned fuel, for which THC and VOC are the

same, compared to 4-stroke engines. Another reason is that no quantitative data exists on

methane, ethane, and aldehyde emissions from 2-stroke engines.

The seasonal adjustment factor is provided to calculate winter and summertime

inventories for VOC, CO, NOx, and particulates. The annual inventories are adjusted so that the

output is in tons per summer day (tpsd) for the ozone non-attainment areas. Emission inventories

for CO are also adjusted so that the output is in tons per winter day (tpwd) for the CO nonattainment areas.

For each CMSA, tables are available in hard copy (paper) or on disk in a text or Lotus

format. States may use the order form in the back of this chapter to request the data for the nonattainment area of interest.

Again, separate information is given for 2-stroke, 4-stroke, and diesel engines. All 79

equipment types spanning 9 nonroad engine categories are included. However, as mentioned

earlier, the commercial marine vessel category is not included.
 204 Adjustment factors are not mandatory for calculations to proceed in AMS, but should be provided if modeling

will be done.

105

Another important point to make on the eventual application of these data is that diesel,

4-stroke, and 2-stroke engine emissions all have different exhaust HC speciations. The 4-stroke

gasoline and diesel engines can use the standard EPA motor vehicle speciations. For the present

time, we recommend that the standard EPA speciation for non-catalyst gasoline engines also be

used for 2-stroke and propane engines. In addition, evaporative emission speciation differs from

exhaust, consisting of more volatile fuel components with no combustion products. However, in

order to keep inventory speciation simpler, the two categories are being combined based on the

relative amounts of exhaust and evaporative emissions for the 2-stroke and 4-stroke engines. 

EPA will provide later guidance concerning the typical fraction for combining the exhaust and

evaporative speciations, or the user can determine it from the detailed inventory tables.

4.3.2 AMS Inputs

The AMS system has the following five mandatory inputs.

 Annual activity level (hp-hr, gal, hrs, day)

 Emission factor (g/hp-hr, g/gal, g/hr, g/day)

 Period throughput (% annual activity based on emission mass during 3 month period)

 Adjustment factors204 (weekday, Saturday, Sunday, operating fractions)

 Category operating parameters

The first two inputs have to be compatible so that one can calculate overall emissions. 

The EPA nonroad report generally gives exhaust emissions in g/hp-hr units but sometimes they

are given in g/gal and g/hr units. Evaporative emissions are in g/day but can be artificially

converted into one of the above units by knowing how many horsepower-hours, gallons, or hours

of operation occur each day. 

Item #1, the annual activity level for an equipment type, has to be the sum of all activity

within an area (that is, equipment type population times activity per unit piece of equipment)

rather than activity per unit equipment type, as given in the EPA nonroad report. Therefore,

these levels will be greatly different from one area to another. It is important to note that the

activity levels will be different for each county or portion of a county within a non-attainment

area due to the changes in equipment population from one county to another.

Item #2, emission factors, are directly available from the November 1991 EPA nonroad

study for CO and NOx. Approximate factors are available for particulates. These factors are in

g/hp-hr, g/gal, and g/hr. The underlying emission factors are the same for all non-attainment

areas. However, as with motor vehicles, there are separate emission factors for exhaust,

crankcase, evaporative (diurnal), and refueling VOC. In addition, there will 
106

eventually be information on evaporative (hot soak), running loss, and resting loss HC. There is

no nonroad emission factor model, such as MOBILE 4.1, to combine exhaust and evaporative

emissions that are in different units. The nonroad report multiplies each emission factor by the

appropriate activity level to compile the composite VOC inventory, as illustrated in Appendix D

of this chapter.

For development of the base year inventory and for AMS data entry, a single composite

emission factor for VOC, combining the different sources of VOC (i.e., evaporative versus

exhaust), is being provided. This composite factor is being created by dividing the total VOC in

annual tons by the activity levels. The total evaporative inventory, which is dependent only on

equipment population and days per year, is divided by activity levels (hp-hr, hours, or gallons of

fuel) as one part of the emission factor. Since this particular fraction (evaporative

inventory/activity level) will vary from area to area, the overall Item #2 VOC emission factors

will vary slightly from one area to another.

Item #3, period throughput, is the percent of annual activity occurring in the 3 month

summer and winter periods. This is being calculated from the EEA information for summer and

winter. The tons per winter day and tons per summer day are being compared to tons per year in

deriving these factors. The throughput is based on emission tons rather than activity level. 

Therefore, it is compatible with the annual emission factors in calculating summer and winter

inventories.

Item #4, adjustment factors, account for activity variation in different periods of the week

(weekdays, Saturdays, Sundays). EPA has no quantitative information here. EPA recommends

the same treatment that is implicit in the November 1991 nonroad report, assuming all nonroad

activity is distributed equally over every day of the week. For this case, the adjustment factor is

1.0. This is an approximate assumption and, in the aggregate, may be justified because some

categories (e.g., construction equipment) operate mostly during the week while others (e.g.,

recreational equipment and recreational marine equipment) operates largely on weekends. The

states may use their own judgement or data to assign other factors.

Item #5, category operating parameters, are days/week and weeks/year for equipment

operation. The states should assume that the equipment operates seven days/week and 52

weeks/year. This is an artificial treatment which will make the calculations work out properly,

since the period throughput already accounts for weeks/year because it is emission weighted.

Not all of the detail needed to revise nonroad inventories, if emission factors are revised

at a later date, will be provided in the AMS format. Instead, inventory revisions would be made

(if decided by the states) by going back into the EEA input, which is available separately, and

altering specific items (such as equipment populations, hours of 
 205 Energy and Environmental Analysis, Inc. Methodology To Estimate Nonroad Engine and Vehicle Emission

Inventories At the County and Sub-County Level, Draft Report to the Environmental Protection Agency. 

Arlington, Virginia, February 11, 1992.

 206 U.S. Environmental Protection Agency. Nonroad Engine and Vehicle Emission Study, Report and

Appendices, EPA-21A-2001, Washington, D.C., Office of Air and Radiation, November 1991.

107

usage, and emission factors) and then recalculating the factors used for AMS. For this purpose,

the specific EEA data discs for the items given in Section 4.3.1, which were used to calculate the

AMS inputs for the non-attainment areas that were examined, must be used.

4.4 General Methodology Used In Deriving Emission Inventories For 33 Areas

This section explains the methodology developed and used by EEA and EPA to update

emission inventories for a given non-attainment area from the 1991 EPA nonroad report. Much

of the information in this section has been taken directly from an EEA draft report entitled,

"Methodology to Estimate Nonroad Engine and Vehicle Emission Inventories at the County and

Sub-County Level," which gives information primarily for the New York area and describes the

methodology planned for use for the other areas.205 This methodology is frequently generic in

nature with extrapolations being made to smaller areas from equipment populations in larger

areas. This might lead to some minor cases of some equipment types being listed in areas where

they would not be expected to be found. EPA and EEA will be reviewing the inventories to try

to screen out these anomalies. 

The following inputs are used to develop nonroad emission inventories.

 The equipment populations in a given area;

 The annual hours of use of each type of equipment adjusted for 

 geographic region and for the season of interest for each pollutant 

 studied; 

 The average rated horsepower of each type of equipment;

 The typical load factor for each type of equipment;

 An emission factor (EF). 

The emission factor is defined as the average emissions of each pollutant per unit of use

(gram/horsepower-hour) for each category of equipment. In order to calculate emission factors

for nonroad equipment, EPA compiled and used data from past tests and studies, as well as new

data supplied to EPA from engine manufacturers. Using these data, EPA developed emission

factors for tailpipe exhaust, refueling, evaporative, and crankcase emissions with appropriate

adjustments to account for in-use emissions. These emission factors can be found in Appendix I

of the EPA nonroad report.206 
 207 Energy and Environmental Analysis, Inc. Methodology To Estimate Nonroad Equipment Populations By

Nonattainment Areas, prepared for U.S. Environmental Protection Agency, September 1991.

 208 U.S. Environmental Protection Agency. Nonroad Engine and Vehicle Emission Study, Report and

Appendices, EPA-21A-2001, Washington, D.C., Office of Air and Radiation, November 1991.

108

For the EPA nonroad report, EEA estimated equipment populations by CMSA or

NECMA using regression analysis of state level populations and activity indicator statistics.207

EEA relied on Power Systems Research (PSR) as a major source of data for national and state

equipment populations, annual hours of use, load factors, horsepower, 2-cycle/4-cycle

distributions, and LPG/CNG penetrations. Linear relationships were derived between economic

activity indicators and equipment category populations. County-level indicators were summed

across each CMSA or NECMA and these sums were plugged into the corresponding fitted

regression to arrive at equipment population estimates for each area in the study. However, the

methodology from the EEA final report, "Methodology to Estimate Nonroad Equipment

Populations by Nonattainment Areas," did not address developing inventories for counties and

sub-counties which EPA later calculated and included within the boundaries of the 24 CO and

ozone non-attainment areas in the EPA nonroad report. 

4.4.1 Explanation of Methodologies to Distribute Equipment Within Each Category Type 

at the County Level

Adjustments to the emissions inventories contained in the EPA nonroad report must be

made through changes in the county populations of nonroad equipment, since load factors,

annual hours of use, emission factors, average horsepower, 2 cycle/4 cycle distribution,

LPG/CNG penetration, and seasonality factors remain essentially constant throughout an area

and, in some cases, on a state or national level. In order to do this, activity indicators used in the

previous EEA analysis are used at the county level to determine equipment populations by

county and equipment type. In general, these indicators are derived from economic data

presented in various census publications. By using regression analysis, it can be determined

whether there is a strong relationship between specific activity indicators and an equipment

category's state population. These regressions were done for the areas in the EPA nonroad

report.208 If an activity indicator proved to have a strong relationship with the equipment

category of interest, it was used to distribute the equipment types within a category at the county

level, using data supplied by Power Systems Research. Shown below is the general formula

(equation 4-1) used to distribute national equipment populations to the local county level unless

otherwise specified.

County Pop = County Activity Indicator x National Pop (4-1)

 National Activity Indicator
 209 U.S. Environmental Protection Agency. Nonroad Engine and Vehicle Emission Study, Report and

Appendices, EPA-21A-2001, Washington, D.C., Office of Air and Radiation, November 1991.

 210 Ibid.

109

Using logging activity (employees) as an indicator, logging equipment populations were

determined in the EPA nonroad report at the county level by taking the ratio of county logging

employment over national logging employment and multiplying it by national logging equipment

populations.

For the lawn and garden equipment category, the number of single family housing units

and the number of landscape and horticultural service employees in the county of interest were

used to distribute equipment populations. However, for chainsaws, which are included in the

lawn and garden category, EPA used a methodology suggested by the Portable Power Equipment

Manufacturers Association (PPEMA) using a combination of inventories A and B.209 This

method was based on a combination of activity indicators, including rural area population, urban

population outside of major urbanized areas, and landscaping/horticultural employment. This

methodology is shown below in equation 4-2. 

NA local = NB local x NA national (4-2)

 NB national

In this formula, N refers to the number of chain saws (all sizes), and A and B refer to

inventories A and B.210

Motorcycle dealers were used as an activity indicator in order to distribute recreation

equipment (e.g., nonroad motorcycles, minibikes, golf carts, snowmobiles, and specialty vehicle

carts) from the state to the CMSA level. However, this indicator does not accurately reflect

recreation equipment populations at the county level. Another problem is that there exists an

inverse relationship between population and recreational equipment (i.e., recreation equipment is

not usually used in densely populated areas). Therefore, EEA developed another methodology to

use at the county level. First, the mean population density (people per square mile) is calculated

for the MSA, CMSA, NECMA, or air basin and all the counties within it. Second, the standard

deviation (sigma) from the mean is calculated using the individual county data. Third, those

counties with a population density greater than a certain amount (e.g., the mean minus sigma) are

assigned an equipment population of zero. Fourth, the equipment populations are then

distributed among the remaining (lower population) counties according to the following formula

(equation 4-3).

Cntypop = Areapop x [Area/Sum(Area)] (4-3)
 211 U.S. Environmental Protection Agency. Nonroad Engine and Vehicle Emission Study, Report and

Appendices, EPA-21A-2001, Washington, D.C., Office of Air and Radiation, November 1991.

 212 Ibid.

110

The variable Cntypop is the population of a particular recreation equipment type in a

county which has a human population density less than that of the CMSA. The variable Areapop

is the population of a recreation equipment type in the CMSA, of which the county (Cnty) is a

part. The ratio within the brackets consists of a particular county's area divided by the sum of the

area for all counties in the CMSA which have a population density less than that of the CMSA.

 Air carrier operations were used as an activity indicator to distribute airport service

equipment populations in counties in which an airport was located. If more than one airport was

located in a county at which air carrier operations took place, the relevant activity levels at these

airports were summed together.211 

For agricultural equipment, EPA decided to use the following methodology, shown below

in equation 4-4, for both the A and B inventories .

County pop = Census county pop x PSR national pop (4-4)

 Census national pop

Both census data and PSR data were used because census data provided the best indicator

of county distribution of agricultural equipment (i.e., total number of units in the county), while

the PSR data gave a better estimate of equipment actually used regularly in agricultural activity

versus idle equipment.212

In order to distribute light commercial equipment (<50 hp) to the county level, the total

amount of wholesale activity (number of establishments) was used as an activity indicator. EPA

used the number of employees in manufacturing at the state and county level and regressed these

data on PSR's state population for industrial equipment. For construction equipment, total

construction activity (number of employees) was used to determine county level populations. 

For industrial equipment, the number of people employed in manufacturing was used as an

activity indicator and was used to distribute state level populations to the county level. For

construction equipment, the number of employees involved in total construction activity,

including road construction, was chosen to distribute state level construction equipment

populations to the county level.

For recreational marine vessels, the nonroad report used local boat registration data to

ascertain the number of each marine equipment type in each non-attainment area. However, an

adjustment was made in the marine vessel data to derive the number of marine engines. 
111

This was done in order to match the vessel data to the horsepower and hours of use estimates,

which were calculated per engine. The second adjustment was done to determine how many

engines were used in the non-attainment areas. Survey results provided by NMMA were used in

this adjustment for 8 of the 24 areas, which are listed below.

 Baltimore  Boston

 Chicago  Denver

 Hartford  Houston

 Milwaukee  Seattle

Data from the survey was used in the following formula (equation 4-5).

EU = ER x Fuel Usedna + % Use Offshore (4-5)

 Fuel Usedboats na

The variable EU stands for the number of engines used in the non-attainment area.

The variable ER is equal to the number of engines registered in the non-attainment area

Fuel Usedna is equal to the sum of the reported amount of fuel consumed inside the nonattainment area by boats registered inside the non-attainment area, plus the fuel consumed within

the non-attainment area by boats registered outside the non-attainment area.

Fuel Usedboats na is equal to the total reported amount of fuel consumed by boats registered

inside the non-attainment area without regard to where the fuel was consumed.

The variable % Use Offshore is equal to the percentage of boats used in coastal waters or the

Great Lakes 0-1 mile from the shore.

For the 16 non-attainment areas that NMMA did not include in their survey, the average

ratios derived from the eight surveyed areas were applied. However, in some cases, the average

ratios were too large for non-attainment areas with lesser amounts of navigable water area. In

these cases, a calculation was made of the maximum number of boats that could be operated

normally on the available water area, which was supplied by EEA. The area required per boat

was supplied by NMMA. This calculation is shown in equation (4-6).

Max. Boats = Water Surface Areana (4-6)

 Area Requiredboat

Max. Boats is equal to the theoretical maximum amount of boats that can operate on the

available water surface area. Water Surface Areana is equal to the total water surface area in the

non-attainment area. Area Requiredboat is equal to the average water surface area required per

boat. 

The result of the above calculation multiplied by the available hours of prime boating use

(assumed nationwide), which is 384 hours/year (12 weeks/year x 4 days/week x 8 hours/day),

provided the theoretical maximum number of summer boat hours inside the non-
112

attainment area, which was compared to the amount of summer boat hours calculated from the

survey results and the local boat registrations. In the cases where the summer boat hours

calculated from registrations and survey results exceeded the theoretical maximum calculated

using 384 hours/year, the calculated number of engines used in the non-attainment area was

reduced by the ratio of the theoretical maximum summer boat hours to the calculated summer

boat hours. Because this correction ratio does not include offshore boat use, the average offshore

use was subtracted out prior to applying the correction ratio. For areas on the ocean or on a

Great Lake, the average of the offshore usage proportion for all the areas with offshore use was

added back after applying the correction ratio. Note that recreational marine equipment was not

allocated to the county level in the November 1991 nonroad report. 

4.4.2 Explanation of Methodologies For Distributing Equipment Within Each 

Category at the Sub-County Level

When the non-attainment boundaries include only a portion of a county, the nonroad

equipment population at the county level must be adjusted. This adjustment can usually be made

based on the following fraction (equation 4-7).

Human population at subcounty level (4-7)

Human population at county level

This adjustment factor works well for nonroad equipment populations that can be

expected to track human populations reasonable well in going from the county to subcounty

level. This adjustment is used for the following nonroad equipment categories.

 lawn and garden

 light commercial

 industrial

 construction

For other equipment categories, different methodologies were used.

The following equipment categories are adjusted from a county to subcounty level using

the same methodology, found in Section 4.4.1, for distributing recreation equipment from the

CMSA, MSA, NECMA, or Air Basin to the county level. 

 recreational

 logging

 agricultural 
 213 U.S. Environmental Protection Agency. Nonroad Engine and Vehicle Emission Study, Report and

Appendices, EPA-21A-2001, Washington, D.C., Office of Air and Radiation, November 1991.

 214 Energy and Environmental Analysis, Inc. Methodology To Estimate Nonroad Equipment Populations By

Nonattainment Areas, prepared for U.S. Environmental Protection Agency, September 1991.

113

This methodology uses a mathematical relationship based on population density to

distribute the equipment population to sparsely populated areas of a sub-county. Equation 

(4-8) shows this calculation below.

Subcnty = Cntyequip pop. x [(Area)subcnty/(Area)cnty)] (4-8)

The variable Subcnty is a township or borough in the partial county of interest with a

population density that is less than that of the CMSA. Cntyequip pop. is the population of a

particular recreational equipment type within the county of which the partial county is a part. 

The ratio of Areasubcnty over Areacnty is the ratio of the area of the partial county of interest to the

area of the total county. In effect, this moves this equipment completely from highly populated

areas of the partial county, where this equipment is not used much if at all, to the lower

population areas where available land exists. 

For recreational marine equipment, a similar method is used for county to subcounty

allocations of equipment population, except that it does not limit the allocation of equipment to

only partial counties that have a population density less than that of the CMSA. This is because

in many cases, recreational marine equipment is used in bodies of water that are close to

populated areas (e.g., the Potomac River in Washington, D.C.). Although this could be done by

inspecting maps and considering other factors, such as usage patterns for the available water, it is

quite difficult to determine the water area available for recreational marine equipment from a

county to subcounty level. 

For airport service equipment, subcounty populations are obtained simply by inspecting a

map to see if the airport is in the subcounty portion being considered.

4.4.3 Seasonal Adjustment Methodology

EEA and EPA also applied seasonal adjustments to the emission inventories based on

annual hours of use data in eight regions of the United States at different times of 

the year.213, 214 These adjustments were also based on the fact that ozone violations usually occur

in the summer and CO violations usually occur in the winter. In Inventory A, EEA and EPA

used eight seasonality adjustments based on classifying each of the 24 original areas into eight

regions, which are listed below.
 215 Hare, C.T., and K.J. Springer. Exhaust Emissions from Uncontrolled Vehicles and Related Equipment Using

Combustion Engines, Part 5, No. APRD-1494. San Antonio, TX, Southwest Research Institute, October 1973.

114

 Northeast  Southeast

 Mid-Atlantic Coast  Great Lakes

 Southwest  Rocky Mountains

 Northwest  West Coast

 

These regions were also classified into cold, medium and warm regions, which were

geographically similar to regions found in a 1973 report by Hare and Springer.215 The United

States was divided up into these three temperature regions based on average January

temperatures. A warm region was classified as being above 450F, a medium region was

classified as being between 350F and 440F, and a cold region was classified as being below 35_F. 

For more detailed information, please refer to Appendix L of the EPA nonroad report.

The formulas listed below (equations 4-9 and 4-10) were applied using this information

to determine summertime total HC and NOx emissions and wintertime CO emissions.

tpsd = tpy * SAFsummer (4-9)

tpwd = tpy * SAFwinter (4-10)

 

TPSD and TPWD refer to tons per summer and winter day, respectively. TPY stands for

tons per year. SAF is the seasonal adjustment factor, which can be derived by the following

formulas (equations 4-11 and 4-12).

SAFsummer = 4 * (% activity during summer/365 days) (4-11)

SAFwinter = 4 * (% activity during winter/365 days) (4-12)

The seasonal adjustment factors were calculated based on data from the Hare and

Springer report mentioned above, the CARB Technical Support Document concerning lawn and

garden equipment, 1987 SIP emission inventories, the Motorcycle Industry Council (MC), and

the National Marine Manufacturers Association (NMMA). Some seasonal activity percentages

are listed in the table below, which is the same as Table L-02, excluding 
 216 U.S. Environmental Protection Agency. Nonroad Engine and Vehicle Emission Study, Report and

Appendices, EPA-21A-2001, Washington, D.C., Office of Air and Radiation, November 1991.

115

commercial marine equipment, in the EPA nonroad report. Recreational marine and recreation

equipment seasonal activity percentages can be found in tables L-03, and L-04 in Appendix L of

the EPA nonroad report.216

Equipment Cold/North Medium/Central Warm/South

Category Summer Winter Summer Winter Summer Winter

Agricultural 50% 6% 40% 6% 34% 6%

Construction 43% 10% 38% 15% 33% 20%

Industrial 30% 20% 25% 25% 25% 25% 

Lawn & Garden 50% 6% 40% 6% 34% 6% 

(excluding chainsaws)

Snowblower/ 0% 100% 0% 100% 0% 100%

Snowmobiles 

Airport Service 25% 25% 25% 25% 25% 25%

Logging 25% 25% 25% 25% 25% 25%

(including chainsaws)

Light Commercial 25% 25% 25% 25% 25% 25%

4.5 New York Non-attainment Area Example

EEA has prepared an updated nonroad inventory for the New York CMSA, including

partial counties included in the non-attainment boundaries. Some example tables from the final

report containing the updated New York CMSA inventory for diesel, 4-stroke, 2-stroke, and

propane/CNG engine types can be found in Appendix 4-A at the end of this chapter. These

tables include information for some of the following items, most of which are in the spreadsheets

for the November 1991 nonroad report. All of these items are being listed in the final EEA

report for New York and the other areas.
 217 Seasonal Adjustment Factor.

116

 Equipment population (for ozone and CO non-attainment areas)

 Emission factors (g/hp-hr, g/hr, g/gal, g/day)

 Hours/year

 Average horsepower

 Average load

 Evap season (days)

 1/SAF217 (tons per year/tons per summer day)

 1/SAF (tons per year/tons per winter day)

 VOC - tons per summer day

 NOx - tons per summer day

 CO - tons per summer day (ozone area)

 CO tons per winter day (CO area)

 Particulates tons per year 

 Population (human) and tons/person 

Table 4-1 lists the 26 counties and partial counties included in the New York CMSA, as

well as the air quality classification of each county or partial county for CO and ozone. Tables 4-

2 through 4-4 present nonroad inventory data for the New York CMSA using the (A+B)/2

inventories. Table 4-2 presents emission inventories for diesel equipment. Table 4-3 presents

emissions per person for diesel equipment. Table 4-4 shows the AMS input parameters for diesel

equipment.
117

Appendix 4-A

Emission Inventory Tables For New York CMSA
118

Table 4-1

 

Counties and Sub-County Areas Included 

In the New York CMSA Example

 Ozone CO

County Classification Classification

Bergen, NJ Nonattainment Nonattainment

Essex, NJ Nonattainment Nonattainment

Hudson, NJ Nonattainment Nonattainment

Hunterdon, NJ Nonattainment Attainment

Middlesex, NJ Nonattainment

 City of 

 Perth Amboy Nonattainment

Monmouth, NJ Nonattainment

 Borough of

 Freehold Nonattainment

Morris, NJ Nonattainment

 City of 

 Morristown Nonattainment

Ocean, NJ Nonattainment

 City of Toms

 River Nonattainment

Passaic, NJ Nonattainment

 Clifton City Nonattainment

 Patterson City Nonattainment

 Passaic City Nonattainment

Somerset, NJ Nonattainment

 Borough of

 Sommerville Nonattainment

Sussex, NJ Nonattainment Attainment
119

Table 4-1 continued

 Ozone CO

County Classification Classification

Union, NJ Nonattainment Nonattainment

Bronx, NY Nonattainment Nonattainment

Kings, NY Nonattainment Nonattainment

Nassau, NY Nonattainment Nonattainment

New York, NY Nonattainment Nonattainment

Orange, NY Nonattainment Attainment

Putnam, NY Nonattainment Attainment

Queens, NY Nonattainment Nonattainment

Richmond, NY Nonattainment Nonattainment

Rockland, NY Nonattainment Attainment

Suffolk, NY Nonattainment Attainment

Westchester, NY Nonattainment Nonattainment

Fairfield, CT Nonattainment Nonattainment

Litchfield, CT Nonattainment

 Bridgewater Town Nonattainment

 New Milford Town Nonattainment

 Bethlehem Town Nonattainment

 Thomaston Town Nonattainment

 Watertown Nonattainment

 Woodbury Town Nonattainment

New Haven, CT Nonattainment Nonattainment

 




124

Appendix 4-B

 Equipment Categories 
 218 U.S. Environmental Protection Agency. Nonroad Engine and Vehicle Emission Study, Report and

Appendices, EPA-21A-2001, Washington, D.C., Office of Air and Radiation, November 1991.

 219 Energy and Environmental Analysis, Inc. Methodology To Estimate Nonroad Equipment Populations By

Nonattainment Areas, prepared for U.S. Environmental Protection Agency, September 1991.

 220 California Air Resources Board. Technical Support Documents for California Exhaust Emission Standards

and Test Procedures for 1994 and Subsequent Model Year Utility and Lawn and Garden Equipment Engines,

attachment C to CARB Mailout #90-64, El Monte, California: State of California, December 1991.

125

Category 1, lawn and garden equipment, includes 14 types of equipment.218, 219 These are

mostly powered by small gasoline engines having less than 25 horsepower. Examples of these

are listed below. 

 lawnmowers 

 trimmers

 edgers

 brush cutters 

 chainsaws 

Some larger lawn and garden equipment types, such as those listed below, have diesel

engines.

 chippers/grinders 

 rear engine riding mowers 

 wood splitters 

 commercial turf equipment 

The main source of data used by EPA in its nonroad report to derive the emission factors

for gasoline engines in this category was the California Air Resources Board (CARB) Technical

Support Document (TSD).220 CARB relied on testing done by manufacturers, Southwest

Research Institute, and Heiden Associates for the Portable Power Equipment Manufacturers

Association (PPEMA). Since there were no emissions data available for the small percentage of

lawn and garden equipment that have diesel engines (rear engine riding mowers, lawn and garden

tractors, wood splitters/chippers, stump grinders, and commercial turf equipment), the emission

factors for diesel light commercial equipment (less than 50 horsepower) were considered to be

the substitutes for use in the nonroad equipment study. Please refer to tables I-3 and I-4 in the

appendix of the nonroad report for the actual emission factors. The activity indicators used by

Energy and Environmental Analysis, Inc. (EEA) for developing lawn and garden equipment

populations included the number of single family housing units in a given area and SIC 078 -

Landscape and Horticultural Services (Employees).
 221 U.S. Environmental Protection Agency. Compilation of Air Pollutant Emission Factors, Volume II, EPA

Report No. AP-42, Fourth Edition, Research Triangle Park, North Carolina, Office of Air Quality Planning and

Standards, September 1985.

 222 Environmental Research and Technology, Inc. Feasibility, Cost, and Air Quality Impact of Potential

Emission Control Requirements on Farm, Construction, and Industrial Equipment in California, Document PA841,

sponsored by the Farm and Industrial Equipment Institute, Engine Manufacturers Association, and Construction

Industry Manufacturers Association, May 1982.

126

The agricultural equipment category is comprised of 11 types of equipment. Examples of

these are listed below. 

 tractors  balers

 combines  tillers 

 swathers  sprayers 

 fertilizer spreaders  harvesters

 agricultural mowers (> 5 h.p.)  strippers 

 cotton pickers 

Some specialized equipment, such as cotton pickers and strippers have relatively small

populations and can only be found in certain areas of the country. For agricultural equipment

using gasoline, the emission factors used to calculate emission inventories were from the Fourth

Edition of AP-42.221 The factors found in AP-42 were selected because no other sources had

specific emission factors by equipment type for gasoline nonroad equipment. For particulate

emission factors for gasoline equipment, a value of 1.64 lb./1000 gallons was used. For diesel

agricultural equipment, emission factors were taken from a report by Environmental Research

and Technology, Inc. (EAT) entitled, "Feasibility, Cost, and Air Quality Impact of Potential

Emission Control Requirements on Farm, Construction, and Industrial Equipment in

California".222 Emission factors were given by equipment category. Emission factors for

particulate matter were taken from AP-42, Fourth Edition. Table I-07 in the nonroad report

presents the chosen emission factors from EAT in grams/horsepower-hour, and table I-08 gives

the emission factors converted to pounds/1000 gallons of fuel. EEA used data from the 1987

Census of Agriculture to derive activity indicators for agricultural equipment. SIC 07 -

Agricultural Services (Employees), modified to exclude SIC 78 (used for the lawn and garden

category), was found to be the best activity indicator for this category.
 223 Ingalls, M.N. Nonroad Emission Factors of Air Toxics, Report No. 08-3426-005. San Antonio, Texas,

Southwest Research Institute, February 1991.

 224 Weaver, C.S. Feasibility and Cost Effectiveness of Controlling Emissions from Diesel Engines in Rail,

Marine, Construction, Farm, and Other Mobile Off-Highway Equipment, Final Report for U.S. Environmental

Protection Agency. Sacramento, California, Radian Corporation, February 1988.

 225 Hare, C.T., and K.J. Springer. Exhaust Emissions from Uncontrolled Vehicles and Related Equipment Using

Internal Combustion Engines, Final Report Part 5, Heavy-Duty Farm, Construction, and Industrial Engines. San

Antonio, Texas, Southwest Research Institute, October 1973.

127

The logging equipment category includes the following equipments types.

 chainsaws (> 5 h.p.) 

 shredders (> 5 h.p.) 

 skidders 

 delimbers 

 fellers

 bunchers

 other miscellaneous equipment 

Significant amounts of logging equipment can only be found in parts of the United States

where large-scale logging operations take place, such as the Pacific Northwest. Emission factors

for this category were taken from the CARB Technical Support Document and data submitted to

EPA by the Engine Manufacturers Association (EMA).223 SIC 241 (Employees) was chosen by

EEA as the best activity indicator to distribute logging equipment populations.

Light commercial equipment is categorized as having engines under 50 horsepower. This

equipment is used in various wholesaling, retailing, and manufacturing capacities. Examples of

this category include various types of the following equipment.

 electrical generators 

 pumps

 compressors 

Emission factors recommended by SwRI224 and contained in a report produced by Radian

Corporation225 were used for equipment fueled with diesel in this category. For equipment using

gasoline, emission factors for utility and lawn and garden equipment from the CARB Technical

Support Document were used. 

Somewhat related to the light commercial equipment category, the industrial equipment

category includes equipment used in manufacturing and warehousing operations. This category

includes the types of equipment listed below. 
 226 California Air Resources Board, Mailout #90-58. El Monte, California, State of California, September 7,

1990.

 227 U.S. Environmental Protection Agency. Nonroad Engine and Vehicle Emission Study, Report and

Appendices, EPA-21A-2001, Washington, D.C., Office of Air and Radiation, November 1991.

 228 Energy and Environmental Analysis, Inc. Methodology To Estimate Nonroad Equipment Populations By

Nonattainment Areas, prepared for U.S. Environmental Protection Agency, September 1991.

 229 Environmental Research and Technology, Inc. Feasibility, Cost, and Air Quality Impact of Potential

Emission Control Requirements on Farm, Construction, and Industrial Equipment in California, Document PA841,

sponsored by the Farm and Industrial Equipment Institute, Engine Manufacturers Association, and Construction

Industry Manufacturers Association, May 1982.

128

 forklifts  vacuums 

 boom lifts  scrapers

 scissor lifts  winches

 industrial sweepers  hoists 

 scrubbers  conveyors

 blowers

For both gasoline and diesel industrial equipment, emission factors found in Volume I of

AP-42 were used. These factors were developed by SwRI in 1973.226 EEA use total wholesale

activity (number of establishments) as the indicator for the distribution of light commercial

equipment populations.

The category of construction equipment includes 27 kinds of equipment.227, 228 These

types are listed below.

 paving equipment  cranes

 roofing equipment  cement/mortar mixers 

 signal boards  crushing/processing equipment 

 cable layers  dozers

 drilling rigs  backhoes 

 excavators  loaders

 industrial saws  tractors 

The emission factors used for diesel construction equipment were derived from data from

EMA. For some types of diesel equipment, EMA emission factors were unavailable. In these

cases, EPA used factors from AP-42, Fourth Edition, which were originally derive from the EAT

report mentioned earlier.229 For the actual emission factors, please refer to Table I-09, which

compares the AP-42 and the EMA emission factors, in the appendix of the EPA nonroad report. 

For gasoline construction equipment, the emission factors which EPA selected came from the

fourth edition of AP-42. For particulate matter and aldehyde 
 230 Hare, C.T., and K.J. Springer. Exhaust Emissions from Uncontrolled Vehicles and Related Equipment Using

Internal Combustion Engines, Final Report, Part 7, Snowmobiles, San Antonio, Texas, Southwest Research

Institute, April 1974.

129

construction equipment emission factors, EPA used the gasoline and diesel agricultural

equipment emission factors. Local construction activity was used by EEA to determine local

construction equipment populations.

For airport equipment, only equipment owned by each airline was included (EEA). 

Airport equipment owned and operated by the airport authority was inventoried within the other

categories. This was done to prevent double counting. This category also does not include

aircraft engines, which are addressed in Chapter 5. Examples of this equipment are listed below.

 load lifters  starting units 

 de-icing equipment  baggage conveyors 

 heating units  towing/pushback tractors

 utility service equipment  misc. service vehicles

The emission factors for industrial equipment were also applied to airport service

equipment. Air carrier operations, including certified carriers, air taxis, supplemental air carriers,

commercial operators of large aircraft, and air travel clubs, were used by EEA as the activity

indicator for determining local airport equipment populations. 

The recreational category includes a varied array of equipment. Examples of these are

listed below. 

 all terrain vehicles (ATVs) 

 minibikes

 snow and ice maintenance equipment,

 go-carts

 gasoline powered golf carts

 snowmobiles

 industrial personnel carriers/ATVs 

Some equipment in this category is limited to certain specific areas or regions. Golf carts

are mostly found in resorts and golf courses. Snowmobiles and snow/ice maintenance equipment

are mostly found in areas that have a significant amount of snowfall. Emission factors developed

by CARB for off-road motorcycles with both 2- and 4-stroke engines were used by EPA. EPA

also applied these emission factors to all-terrain vehicles, minibikes, golf carts, and specialty

vehicle carts.230 For snowmobiles, very little data exist on emission rates. EPA is considering

using emission factors found in AP-42, which were derived from 
 231 Booz Allen & Hamilton, Inc. Commercial Marine Vessel Contributions to Emission Inventories, Final

Report to Environmental Protection Agency. Los Angeles, California, October 7, 1991.

 232 U.S. Environmental Protection Agency. Designation of Areas for Air Quality Planning Purposes, 40 CFR

Part 81, Final Rule, Washington, D.C., Office of Air and Radiation, Novemeber 6, 1991.

 233 Energy and Environmental Analysis, Inc. Methodology To Estimate Nonroad Engine and Vehicle Emission

Inventories At the County and Sub-County Level, Draft Report to the Environmental Protection Agency. 

Arlington, Virginia, February 11, 1992.

130

testing done by SwRI in 1974.231 SIC 557 - Motorcycle Dealers (Establishments) was the

primary indicator used by EEA to determine local recreational equipment populations. For some

areas SIC 557 had no data. In such cases, SIC 55 - Automotive Dealers and Service Stations

(Employees) - was used as a substitute.

Five types of recreational marine vessels are addressed in the nonroad report. These are

listed below.

 vessels with inboard engines

 vessels with outboard engines 

 vessels with sterndrive engines

 sailboats with auxiliary outboard engines

 sailboats with auxiliary inboard engines 

Emission factors for outboard engines were derived from test data supplied to EPA by the

National Marine Manufacturers Association, which tested 25 two-stroke and three four-stroke

outboard engines. Please refer to Tables I-11a and I-11b in the November 1991 EPA "Nonroad

Engine and Vehicle Emission Study" for further information. For four-stroke outboards,

emission factors recommended by SwRI were used for particulate matter emissions.232 Since no

data were available for 2-stroke outboard engine particulate matter emissions, EPA used

emission factors from the CARB Technical Support Document for utility and lawn/garden

equipment as approximations.233 For inboard/sterndrive gasoline engines, EPA derived emission

factors on the basis of test data on three 4-stroke gasoline marine inboard/sterndrive engines

supplied by NMMA (See table I-11c in the appendix of the EPA nonroad report). The

particulate emission factor used was 1.64 lb./1000 gal (0.74 grams/gallon). Please refer to

Section 1.2.2 of Appendix I of the EPA November 1991 nonroad study for more information. 

EPA used test data on a small diesel sailboat inboard and three large diesel inboard engines,

which NMMA supplied, as the basis for calculating emission factors for inboard diesel engines. 

Please refer to table I-11d in appendix of the EPA nonroad study for more information. The

activity indicator that EEA used to distribute marine engine populations at the county level

consisted of taking a ratio of the water surface area of the given county to the total water surface

area of the state in which the county is located. This includes miles of public beach with an

assumed operating distance from shore of one mile, as well as inland waterways. Data on miles

of public beach were found in the 
 234 Booz Allen & Hamilton, Inc. Commercial Marine Vessel Contributions to Emission Inventories, Final

Report to Environmental Protection Agency. Los Angeles, California, October 7, 1991.

 235 U.S. Army Corps. of Engineers. Waterborne Commerce of the United States, Calendar Year 1988, Water

Resources Support Center.

 236 U.S. Department of Commerce, National Oceanic and Atmospheric Administration, National Marine

Fisheries Service. Fisheries of the United States, 1990, Washington D.C., U.S. Government Printing Office, May

1991.

 237 U.S. Environmental Protection Agency. 1985 National Emissions Report, Research Triangle Park, NC,

Office of Air Quality Planning and Standards, March 1991.

131

National Oceanic and Atmospheric Administration's (NOAA) National Estuarine Inventory:

Data Atlas, 1988. Data on inland water covered surface area were derived from a census report

entitled, Area Measurements Reports, GE-20, No. 1, 1970. 

Commercial marine vessels can be subdivided into three categories, including oceangoing, harbor, and fishing vessels. These vessels have similar characteristics of size, speed,

engine design, and distance traveled. Booz Allen & Hamilton developed the commercial marine

vessel inventories and emission factors under contract to EPA for the EPA nonroad study. These

are contained in The Booz Allen & Hamilton final report.234 In addition, the emission factors are

contained in tables I-12a and I-12b in Appendix I of the EPA nonroad report. In developing

commercial marine populations for six ports (Baltimore, Baton Rouge, Houston-Galveston, New

York-New Jersey, Philadelphia, and Seattle-Tacoma), Booz Allen & Hamilton requested data

from several sources, including port authorities, Lloyds exchange, local marine exchanges, bar

pilots associations, maritime trade organizations, state regulatory and licensing boards, and the

U.S. Army Corps of Engineers. For the ports of Houston-Galveston and Baton-Rouge,

inventories were based on data published in Waterborne Commerce of the United States,

Calendar Year 1988.

235 For fishing vessel populations, data supplied by the National Marine

Fisheries Service was used.236 For ports in non-attainment areas not addressed in the Booz Allen

& Hamilton report, EPA relied on data from SIP inventories and the 1985 National Emissions

Report.

237

 
132

Appendix 4-C

Sample Inventory Calculation
133

Sample OMS and EEA Inventory Calculation for VOC

Exhaust

(g/hp-hr) x (rated hp) x (percent of rated hp typically used) 

x (hrs/yr per engine) x (equipment population) x (ton/g) 

= (tons/yr)

Evaporative

(g/day) x (229 days/yr)* x (equipment population) x (ton/g) =

(tons/yr)

* Evaporative diurnal VOC emissions are assumed to occur 229 days/year, which

includes each day of the ozone season, no winter days, and most other days. Future OMS

work will determine emission factors for hot soak, running loss, and resting loss

emissions. 

Refueling 

Refueling emissions are the sum of the spillage and vapor displacement emissions. They

are calculated on a g/gal basis and then, as appropriate, converted to a g/hp-hr or g/hr basis to be

in the same unit as the exhaust emission factors. Please see Appendix I (pages 26-31) of the

EPA nonroad study for details on the calculations. The example below is shown for a g/gal

emission factor.

(g/gal) x (gal fuel used) x (equipment population) x (ton/g) 

= (tons/yr)

The total of these three emission categories are combined to give total annual VOC

emissions as shown below.

Total annual VOC emissions = Exhaust VOC + Evaporative VOC + Refueling VOC

Annual emissions for CO and particulates are calculated using just the exhaust portion of

this example.
134

The total annual emissions (tons/year) can be apportioned to tons/summer day or

tons/winter day by use of one of the conversion factors developed by EEA.

SAF (tons per summer day/tons per year)

SAF (tons per winter day/tons per year)

These factors consider different fractions of summer and winter operations for the nine

equipment categories in three different geographical areas of the country (northern, central, and

southern). Thus, the factors vary from area to area.

By use of these conversion factors, the following inventories are obtained.

VOC tons per summer day

NOx tons per summer day

CO tons per summer day (O3 area)

CO tons per winter day (CO area)

Particulate tons per summer day

Particulate tons per winter day

The conversion factors can also be applied to particulates if one is considering the 24-hr.

particulate National Ambient Air Quality Standard instead of the annual average. 
135

Appendix 4-D

Inventory Request Form
 Non-Road Mobile Sources Inventory

 Guidance Request Form

 Please Print or Type

 

Requester:___________________________________________________

 

Agency:______________________________________________________

 

Street:______________________________________________________

City, ST, Zip:_______________________________________________

Fed.Exp.Acct: _________________ Telephone: __________________

Nonattainment

Areas Under

Your Agency: _________________________________________________

______________________________________________________________

 Materials Requested

 _____ New York - New Jersey inventory example

 _____ Inventory disks for areas listed above

 (If among 33 areas analyzed by EPA - see back)

 _____ Booz-Allen study on commercial vessels in six areas

 (Oct. 1991)

 _____ Inventories for others among the 33 areas, for

 purposes of population-ratio estimates (limit 5)

 _______________ _______________ _______________

 _______________ _______________

Return this form to: Natalie Dobie Voice: (313) 741-7812

 U.S. EPA FAX: (313) 668-4368

 2565 Plymouth Rd.

 Ann Arbor, MI 48105
 

 Areas Available

1. Anchorage AK

2. Atlanta GA

3. Baltimore MD

4. Baton Rouge LA

5. Beaumont-Port Arthur TX

6. Boston-Lawrence-Worcester MA

7. Chicago-Gary-Lake County IL-IN-WI

8. Cleveland-Akron-Lorain OH

9. Denver-Boulder CO

10. El Paso TX

11. Hartford-New Britain-Middletown-Bristol CT

12. Houston-Galveston-Brazoria TX

13. Las Vegas NV

14. Miami-Fort Lauderdale FL

15. Milwaukee-Racine WI

16. Minneapolis-St. Paul MN

17. Muskegon MI

18. New York-Northern New Jersey-Long Island NY-NJ-CT

19. Philadelphia-Wilmington-Trenton PA-NJ-DE-MD

20. Phoenix AZ

21. Portsmouth-Dover-Rochester NH

22. Providence RI

23. Provo-Orem UT

24. San Diego CA

25. San Joaquin Valley Air Basin CA

26. Seattle-Tacoma WA

27. Sheboygan WI

28. South Coast Air Basin CA

29. Spokane WA

30. Springfield MA

31. St. Louis MO

32. Tucson AZ

33. Washington DC
 238 Compilation of Air Pollutant Emission Factors, Volume II: Mobile Sources, AP-42, U.S. Environmental

Protection Agency, Ann Arbor, Michigan, September, 1985. (Aircraft data from February 1980.) 

137

5.0 EMISSIONS FROM AIRCRAFT

This chapter describes the procedure for calculating emissions from civilian and military

aircraft within an inventory area. The basic methodology determines aircraft fleet make-up and

level of activity and then calculates air pollutant emissions on an annual basis. Variations to the

methodology, which account for seasonal changes or specific operational considerations, are

discussed. Changes expected in the fleet in the future and the effect on emissions are also briefly

described. Finally, a method for converting total hydrocarbon (THC) emissions to volatile

organic compound (VOC) emissions is presented at the end of the chapter. 

The inventory methodology and emission factors have been updated since the last edition

of this report. This chapter also updates the emission factor information that appears in

Compilation of Air Pollutant Emission Factors, Fourth Edition and Supplements, AP-42.

238

Subsequent to the publication of this document, AP-42 will be formally updated and may include

some additional data, primarily on general aviation and military aircraft, which was unavailable

when this report was prepared.

5.1 OVERVIEW OF THE INVENTORY METHODOLOGY

Preparing an emissions inventory for aircraft focuses on the emission characteristics of

this source relative to the vertical column of air that ultimately affects ground level pollutant

concentrations. This portion of the atmosphere, which begins at the earth's surface and is

simulated in air quality models, is often referred to as the mixing zone. The aircraft operations of

interest within this layer are defined as the landing and takeoff (LTO) cycle. The cycle begins

when the aircraft approaches the airport on its descent from cruising altitude, lands, and taxis to

the gate. It continues as the aircraft taxis back out to the runway for subsequent takeoff and

climbout as it heads back up to cruising altitude. Thus, the five specific operating modes in an

LTO are:

 Approach

 Taxi/idle-in

 Taxi/idle-out

 Takeoff

 Climbout
138

Most aircraft go through a similar sequence during a complete operating cycle. 

Helicopters may combine certain modes such as takeoff and climbout.5.1.1 Factors Affecting

Emissions

The LTO cycle provides a basis for calculating aircraft emissions. During each mode of

operation, the aircraft engines operate at a fairly standard power setting for a given aircraft

category. Emissions for one complete cycle for a given aircraft can be calculated by knowing

emission factors for specific aircraft engines at those power settings. Then, if the activity of all

aircraft in the modeling zone can be determined for the inventory period, the total emissions can

be calculated. Each of the dominant factors that affect the emissions from this source is

discussed below.

5.1.1.1 Aircraft Categorization 

For a single LTO cycle, aircraft emissions vary considerably depending on the category

of aircraft and the resulting typical flight profile. Aircraft can be categorized by use. 

Commercial aircraft include those used for scheduled service transporting passengers, freight, or

both. Air taxis also fly scheduled service carrying passengers and/or freight but usually are

smaller aircraft and operate on a more limited basis than the commercial carriers. Business

aircraft support business travel, usually on an unscheduled basis, and general aviation includes

most other non-military aircraft used for recreational flying, personal transportation, and various

other activities.

For the purpose of creating an emissions inventory, business aircraft are combined with

general aviation aircraft because of their similar size, use frequency, and operating profiles. In

this inventory methodology they are referred to simply as general aviation. Similarly, air taxis

are treated much like the general aviation category because they are typically the same types of

aircraft. Military aircraft cover a wide range of sizes, uses, and operating missions. While they

often are similar to civil aircraft, they are handled separately because they typically operate

exclusively out of military air bases and frequently have distinctive flight profiles. Helicopters,

or rotary wing aircraft, can be found in each of the categories. Their operation is distinct because

they do not always operate from an airport but may land and takeoff from a heliport at a hospital,

police station, or similarly dispersed location. Military rotorcraft are included in the military

category and non-military rotorcraft are included in the general aviation category since

information on size and number are usually found in common sources. However, they are

combined into a single group for calculating emissions since their flight profiles are similar.
139

Commercial aircraft typically are the largest source of aircraft emissions. Although they

make up less than half of all aircraft in operation around a metropolitan area their emissions

usually represent a large fraction of the total because of their size and operating frequency. This

may not hold true, of course, for a city with a disproportionate amount of military activity or a

city with no major civil airports.

5.1.1.2 Pollutant Emissions

Aircraft pollutants of significance are hydrocarbon (HC), carbon monoxide (CO), oxides

of nitrogen (NOx), sulfur dioxide (SO2), and particulates (PM10). The factors that determine the

quantity of pollutant emitted are the emission index for each operating mode (pounds of pollutant

per 1000 pounds of fuel consumed), the fuel consumption rate, and the duration of each

operating mode. HC and CO emission indexes are very high during the taxi/idle phases when

aircraft engines are at low power and operate at less than optimum efficiency. The emission

indexes fall as the aircraft moves into the higher power operating modes of the LTO cycle. Thus,

operation in the taxi/idle mode, when aircraft are on the ground at low power, is a significant

factor in calculating total HC and CO emissions. For areas which are most concerned about the

contribution of aircraft to the inventory of HC and CO, special attention should be paid to the

time the aircraft operate in the taxi/idle modes.

NOx emissions, on the other hand, are low when engine power and combustion

temperature are low but increase as the power level is increased and combustion temperature

rises. Therefore the takeoff and climbout modes have the highest NOx emission rates. If NOx is

a primary concern for the inventory area, special effort should focus on determining an accurate

height of the mixing layer, which affects the operating duration of climbout.

Sulfur emissions typically are not measured when aircraft engines are tested. In

evaluating sulfur emissions, it is assumed that all sulfur in the fuel combines with oxygen during

combustion to form sulfur dioxide. Thus, sulfur dioxide emission rates are highest during

takeoff and climbout when fuel consumption rates are high. Nationally the sulfur content of fuel

remains fairly constant from year to year at about 0.05% wt. for commercial jet fuel, 0.025% wt.

for military fuel, and 0.006% wt for aviation gasoline. This is the basis for the sulfur dioxide

emission indexes in the tables included in this methodology. If the sulfur content of fuel varies

significantly on a local basis, the emission index can be adjusted according to a ratio of the local

value to the national value.

Particulates form as a result of incomplete combustion. Particulate emission rates are

somewhat higher at low power rates than at high power rates since combustion efficiency

improves at higher engine power. However, particulate emissions are highest during takeoff and

climbout because the fuel flow rate also is high. It is particularly difficult to estimate the

emissions of this pollutant. Direct measurement of particulate emissions from aircraft engines 
140

typically are not available, although emission of visible smoke is reported as part of the engine

certification procedure. Particulate emission factors for only a few aircraft engines are included

in this chapter.

5.1.1.3 Aircraft Engines 

The aircraft powerplant is the source of emissions of the key pollutants that result from

fuel combustion. Emission rates vary depending on the fuel consumption rate and engine

specific design factors. In 1984, EPA established standards for HC emissions. In developing the

emission limits, EPA defined an operating regimen to standardize the engine certification testing

procedure and method for determining engine HC emissions. The standard applies to jet engines

over 6,000 lbs-thrust and emissions are calculated based on a specific LTO cycle. EPA

considered in%use engine deterioration when the standards were developed but concluded that,

because of the high levels of maintenance of aircraft engines for reasons of safety and fuel

economy, emission performance would not deteriorate significantly. The operating parameters

used in the standard for the LTO cycle can be used as default values in calculating emissions

when more specific information is not known. These default values are defined in later sections

of this methodology.

When the standards went into effect, some engines in production could already meet them

due to design changes made previously for improved fuel efficiency. Other engines had to be

redesigned to reduce their HC emissions so that they could remain in production. In-service

engines were not required to be retrofitted in the normal course of periodic servicing and

rebuilding. These older engines, many of which remain in service, have HC emissions that

exceed the standard. New engine designs, produced since the standards went into effect, have

HC emissions much lower than the standards. As a result of design changes made to the engines

that meet the HC standard, emissions of CO also generally went down while NOx emissions

tended to increased. However, the change in these pollutants was much less dramatic than the

decrease in hydrocarbons. The smoke number for the newer engines also is lower due to specific

design changes intended to reduce smoke production, which is regulated by EPA.

5.1.1.4 Operating Modes

During the LTO cycle, aircraft operate for different periods of time in various modes

depending on their particular category, the local meteorological conditions, and operational

considerations at a given airport. The "Time-In-Mode," or TIM, as used in this methodology,

takes these factors into consideration. Table 5%1 shows representative LTO cycle times for

several aircraft categories.


143

Duration in approach and climbout depends largely on the local meteorology. Since the

period of interest is during operation of the aircraft within the air modeling zone, the inversion

layer thickness determines how long the aircraft is in this zone. The inversion layer thickness is

also known as the mixing height or mixing zone since the air in this layer is completely mixed

and pollutants emitted anywhere within the layer will be carried down to ground level. When the

aircraft is above the mixing layer, whether on descent or when climbing to cruising altitude, the

emissions tend to disperse, rather than being trapped by the inversion, and have no ground level

effect.

Taxi/idle time, whether from the runway to the gate (taxi/idle-in) or from the gate to the

runway (taxi/idle-out), depends on the size and layout of the airport, the amount of traffic or

congestion on the ground, and airport-specific operational procedures. Taxi/idle time is the most

variable of the LTO modes. Taxi/idle time can vary significantly for each airport throughout the

day, as aircraft activity changes, and seasonally, as general travel activity increases and

decreases.

The takeoff period, characterized primarily by full-throttle operation, typically lasts until

the aircraft reaches between 500 and 1000 feet above ground level when the engine power is

reduced and the climbout mode begins. This transition height is fairly standard and does not

vary much from location to location or among aircraft categories.

This methodology describes techniques and data sources for determining the critical

variables in the inventory calculations. When an inventory is being created for a particular area,

the fleet make-up, aircraft activity, and times-in-mode will be specific to that area. Engine

emission indexes, on the other hand, depend on the engine design and are provided in reference

tables. 

Where specific information may be difficult to obtain, simplifying assumptions are

discussed. An automated (computerized) calculation procedure, which can simplify data

management, has been developed by the Federal Aviation Administration (FAA) with support

from EPA and can be obtained from the FAA Technology Division, Office of Environment and

Energy, 800 Independence Avenue, SW, Washington, DC 20591, (202) 267-8933. The FAA

Aircraft Engine Emission Database (FAEED) includes information on the engines mounted on

specific aircraft with emission factors for each of the engines, in addition to a menu-driven

procedure for calculating an aircraft emissions inventory.
 239 AOPA's Aviation USA, Aircraft Owners and Pilots Association, 1990. 

144

5.2 INVENTORY METHODOLOGY

The steps in the methodology are basically the same for each aircraft classification and

each location, even though several factors used in creating an inventory are site specific.

(1) Identify all airports to be included in the inventory

(2) Determine the mixing height to be applied to the LTO cycle

(3) Define the fleet make-up for aircraft category using each airport

(4) Determine airport activity as the number of LTOs for each aircraft category

(5) Select emission indexes for each category

(6) Estimate a time-in-mode for each aircraft category at each airport

(7) Calculate an inventory based on the airport activity, TIM, and aircraft emission

factors.

For a specific region where an emissions inventory is being created, steps one and two,

the airports to be included and the mixing height, will be determined largely by the assumptions

used in defining the scope of the modeling area. Steps three through six are repeated for

commercial aircraft, general aviation, military aircraft, and helicopters. The primary difference

in creating an inventory for each type of aircraft is the references used to determine the fleet

make-up and activity. The following sections discuss each of these steps. Steps one and two are

discussed in terms of the specific modeling area while steps three through six are addressed

together for each aircraft category.

5.2.1 Airport Selection

Maps and regional information directories are good sources for identifying civil airports

and military air fields. Sectional aeronautical charts, published by the Aeronautical Charts

Distribution Division (C44), National Ocean Survey, NOAA, Riverdale, MD 20840, (301) 436-

6990 ($5.25 per map), particularly show the location of large and small airports. Specific

airports to be included will be limited by the geographic boundaries of the modeling area. A

secondary reference is AOPA's Aviation USA239 which lists publicly and privately owned civil

airports, including heliports and seaplane bases, and locates them with directions relative to

specific cities, as well as providing latitude and longitude coordinates. Much like the sectional

aeronautical charts, this reference provides general information on all but a few small landing

strips. These small air fields are unlikely to be considered for most analyses because they have

low activity, typically can accommodate only small general aviation aircraft, and therefore,

contribute insignificantly to the emissions inventory. (Many private 
 240 FAA Air Traffic Activity, U.S. Department of Transportation, Office of Management Systems, Federal

Aviation Administration, Fiscal Year 1989. NTIS Report Number ADA 226063.

 241 U.S. Environmental Protection Agency, (SCRAM BBS). To access SCRAM BBS with a modem: (919)

541-5742 (XModem, 8 Bit System, NO Parity, 1 Stop Bit). Research Triangle Park, North Carolina.

 242 Mixing Heights, Wind Speeds, and Potential for Urban Air Pollution Throughout the Contiguous United

States, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, January 1972. NTIS

Report Number PB 207103.

145

use landing sites are listed in AOPA's Aviation USA by city and site name but a telephone

number is the only information given). FAA Air Traffic Activity240 lists all airports with air

traffic control towers operated by the FAA. While this is a subset of the airports listed in these

other references, all of the airports in urban areas with significant air traffic are included.

5.2.2 Mixing Height Determination

The height of the mixing zone influences only the time-in-mode for approach and

climbout. This factor is significant primarily when calculating NOx emissions rather than HC or

CO. If NOx emissions are an important component of the inventory, specific data must be

gathered on mixing heights. If NOx emissions are unimportant, mixing height will have little

effect on the results and the default value of 3000 feet can be used for more generalized results.

Mixing height should be determined in conjunction with those responsible for the air

quality modeling of the region to insure that assumptions used for creating different sections of

the overall inventory are consistent. If the inventory is being created independently of any air

quality modeling, the mixing height can be determined by contacting the National

Meteorological Center at (301) 763-8298 or alternatively the National Climatic Data Center

(NCDC) at (704) 259-0682. Another source of mixing height data is the EPA Office of Air

Quality Planning and Standards' SCRAM (Support Center for Regulatory Air Models) Bulletin

Board.241 This electronic date base contains data used by various air quality models. Mixing

height data, which appears under the Meteorological Data Main Menu, comes from the NCDC. 

As a third alternative, typical mixing heights can be found on Figures 5%1, 5%2, and 5%3 which

come from Mixing Heights, Wind Speeds, and Potential for Urban Air Pollution Throughout the

Contiguous United States.

242 These figures, which show mixing height for a mean annual

morning, a mean summer morning, and a mean winter morning, illustrate the seasonal variation

in the mixing height. The morning data corresponds to the few hours centered near the morning

commuter rush hours, which roughly coincide with the diurnal maximum concentration of slowreacting pollutants in many urban areas. Figure 5%1, showing annual mixing heights, may be

used for creating an annual inventory. If 



 243 Airport Activity Statistics of Certificated Route Air Carriers, U.S. Department of Transportation, Research

and Special Programs Administration, Federal Aviation Administration, Calendar Year 1989. NTIS Report

Number ADA 229303.

149

a seasonal inventory is being used for evaluating emissions during a peak ozone period, the

summer morning data from Figure 5%2 may be preferred. Episodes lasting two to five days

occur most frequently during the winter for much of the U.S. If these episode periods are of

primary interest, the data from Figure 5%3 should be used. Mixing Heights, Wind Speeds, and

Potential for Urban Air Pollution Throughout the Contiguous United States should be consulted

for additional information on the use of these figures. As a final alternative for mixing height, a

default of 3000 feet may be used. This value, which is used as the default value for the EPA

standard LTO, is incorporated into the calculations used for determining time-in-mode.

5.2.3 Activity and Emissions for Commercial Aircraft

The next four steps relate specifically to creating an emissions inventory for commercial

aircraft. The procedures for other aircraft categories are discussed subsequently. Definition of

the mix of commercial aircraft that uses each airport (step three) can be found in Airport Activity

Statistics of Certified Route Air Carriers,

243 published annually by FAA. Figure 5%4, a copy of a

page from Table 7 of that report, shows the information that is included by airport. All of the

commercial aircraft that used the airport for the given year are listed, along with the number of

departures during the year. This is the fleet that should be used for the inventory.

In step four the number of LTOs is determined by aircraft type. Since Airport Activity

Statistics of Certificated Route Air Carriers lists departures, which are equivalent to LTOs, it is

again the preferred source. From Table 7, the total departures performed for all service (both

scheduled and non scheduled) should be used as the number of LTOs for each aircraft type.

The engines used on each aircraft type must be determined to select the emission factors

for step five. Table 5-2 lists aircraft and the corresponding engines used to power them. Many

aircraft use only a single engine model, while others have been certified to use engines from two

or three different manufacturers. When a single engine is listed for an aircraft model, emissions

data for that engine should be used. For aircraft with engines from more than one manufacturer,

defining the specific engine mix used on the fleet of aircraft operating at a specific airport may be

extremely difficult. Individual airlines probably are the only source of detailed fleet data on

specific engine models and they likely do not have it readily available. To develop a

representative engine mix for aircraft with more than one engine model, the percentage of each

model likely to be found on those aircraft in the U.S. fleet is shown adjacent to the engine model

number in Table 5-2. The recommended procedure for compensating for the lack of detailed

engine data is using the percentages 





155

shown in the table as weighing factors. For example, Boeing 757-200 cargo aircraft have been

sold to U. S. airlines with Pratt & Whitney PW2040 engines as well as Rolls Royce RB.211-

535E4 engines. The number of aircraft with each engine model is 15 and 43, respectively, to

give the percentages shown in Table 5-2 of 26 and 74. These percentages can be used to divide

the total LTOs for B 757-200 cargo aircraft into two groups representing the two engine types. 

This makes the inventory more representative than assigning a single engine for all cargo

versions of B 757-200s, since the emission factors are different for each engine.

After identifying the engines included in the fleet, engine emission factors are used to

calculate mass of emissions. For some of the engines shown in Table 5-2, emission factors have

never been determined. For these engines it is necessary to use emission factors from an

alternative engine. Table 5-3 lists alternative engines recommended by the engine

manufacturers. For most of these engines, emission factors are available for a very similar

engine, usually one of the same model and a related series. For a small number of engines there

is no emissions data available and there are no suggested alternatives. In these instances there

are three approaches available. First, the needed data may appear in the latest update of the

FAEED data base. The FAA should be contacted for the latest version of the data base as

mentioned earlier. Second, for an aircraft with several potential engine types, where no

emissions data is available for one engine, the recommended procedure is to reallocate the market

share among the engines for which data is available. Third, if emission rate information (fuel

consumption and emission index) for an engine model still cannot be located the engine

manufacturer should be contacted directly. 

After the engine types have been identified, fuel flow rates and emission indexes can be

found in Table 5%4. The data in this table has been updated since the last edition of this

reference and of AP%42, to include new engine models and to reflect new data on models already

in AP%42. The next version of AP%42 may have some additional new data for engines that have

not been updated here. (Updates primarily will be for general aviation aircraft engines.) The

fuel flow rates and emission indexes that appear in Table 5-4 for commercial aircraft are based

on information engine manufacturers provide to FAA and the International Civil Aviation

Organization. These data are representative of production engines. Emission indexes are given

for specific fuel flow rates which are representative of the power settings used during the

different operating modes. The emission index multiplied by the fuel flow rate gives an emission

rate.

Step 6 is to specify a time-in-mode for each aircraft type. Take%off time is fairly standard

for commercial aircraft and represents the time for initial climb from ground level to about 500

feet. The default take%off time for calculating emissions is 0.7 minutes (42 seconds) and, unless

more specific data is available, should be used in this methodology. The time in the approach

and climbout modes depends on mixing height. As mentioned earlier, a 















171

default mixing height of 3000 feet was assumed for calculating an approach time of 4 minutes

and a climbout time of 2.2 minutes, which can be used if specific information on mixing height is

unavailable. The procedure for adjusting these times to correspond to a different mixing height

is shown below.

The mode most likely to vary by time for each specific airport is taxi/idle time. Total

taxi/idle time for a very congested airport can be as much as three or four times longer than for

an uncongested airport. Taxi/idle-in time typically is shorter than taxi/idle-out time because

there are usually fewer delays for aircraft coming into a gate than for aircraft lining up to takeoff. 

For a large congested airport the taxi/idle-out time can be three times longer than taxi/idle-in

time. Taxi/idle time also may vary by aircraft type. For example, wide-body jets may all use

special gates at the terminal that place them further from the runway than narrow-body jets or

small regional commuter aircraft so their taxi/idle-in and taxi/idle-out times are longer. Because

of the variation in taxi/idle time, it is important to get data specific to the airports of interest in

the inventory. Commercial airlines must keep track of their taxi/idle time at each airport for

different aircraft types so that their flight schedules reflect anticipated daily and seasonal

variations. These data are important to the airlines since they report schedule delays to the

Department of Transportation as a measure of their operating performance. Therefore, the

airlines' Flight Operations departments at their headquarters locations are the best source of data

for taxi/idle time by aircraft type at a particular airport. Since all airlines using a particular

airport will experience similar taxi/idle times it is only necessary to get information from a

single source. If taxi/idle times are not available for a particular airport, Table 5%1 lists default

values of taxi/idle periods, as well as other modes, for different aircraft classifications. For

commercial aircraft this information is based on data collected prior to 1971 at large airports

during periods of congestion. Idle times that reflect more recent experience will be incorporated

in the next version of AP-42. For the inventory calculations, taxi/idle%in and taxi/idle%out time

are added together to get a total time for the taxi/idle mode.

The final step in the procedure is to calculate total emissions for each aircraft type and to

sum them for a total commercial aircraft emission rate. The following series of equations

illustrates the calculation:

Adjust Approach and Climbout TIM to Represent Local Conditions

These equations adjust the times%in%mode, which are based on a default mixing height of

3000 feet, to an airport specific value based on the local mixing height. Equation 5%2 assumes

the climbout mode begins with the transition from takeoff to climbout at 500 feet and continues

until the aircraft exits the mixing layer.
172

TIMapp-C = 4 X (H/3000) (5-1)

TIMclm-C = 2.2 X [(H-500)/2500] (5-2)

TIMapp-C - time in the approach mode for commercial aircraft, in minutes

TIMclm-C - time in the climbout mode for commercial aircraft, in minutes

 H - mixing height used in air quality modeling for time and region of

interest

Calculate Emissions for Each Aircraft Type

 Eij = _ (TIMjk) X (FFjk/1000) X (EIijk) X (Nej) (5-3)

 Eij = total emissions of pollutant i, in pounds, produced by aircraft type j for one

LTO cycle

 TIMjk = time in mode for mode k, in minutes, for aircraft type j

 FFjk = fuel flow for mode k, in pounds per minute, for each engine used on

aircraft type j (from Table 5-4)

 EIijk = emission index for pollutant i, in pounds of pollutant per one thousand

pounds of fuel,in mode k for aircraft type j (from Table 5-4)

 NEj = number of engines used on aircraft type j (from Table 5-2)
173

Calculate Total Emissions for All Commercial Aircraft

 ETi(C) = 
 (Eij) X (LTOj) (5-4)

 ETi(C) - total emissions of pollutant i, in pounds, produced by all commercial

aircraft operating in the region of interest (where j covers the range of

commercial aircraft operating in the area)

 LTOj - total number of LTO cycles for aircraft type j, during the inventory period

(annual data available from Airport Activity Statistics of Certificated

Route Air Carriers, Table 7)

After completing this series of equations, the inventory of emissions is complete for

commercial aircraft. The next series of calculations is a repeat of steps three through six for

general aviation aircraft.

5.2.4 Activity and Emissions for General Aviation and Air Taxi Aircraft

5.2.4.1 Aircraft-Specific Procedure

The overall methodology for general aviation and air taxi aircraft is similar to that for

commercial aircraft. Unfortunately, defining the fleet mix and associated activity level of

general aviation and air taxi aircraft is more difficult than for commercial aircraft. FAA does not

track operations by aircraft model for the general aviation category and no other sources of these

data cover all states. For some states, this information is available for some airports from the

State Airport Authority or from the operations officials at individual airports. Detailed model

information for aircraft operating in the inventory area is difficult to locate, except perhaps for air

taxis, and may add only relatively small improvement in accuracy to the emissions inventory

compared to treating general aviation and air taxis as though they were made up of a

representative mix of aircraft. For some smaller airports, air taxi activity may predominate and it

may be possible to locate aircraft specific information on the operations there. 

Where information on specific aircraft is available, it can be combined with enginespecific emission factors and the time in each operational mode to estimate total engine

emissions from the general aviation and air taxi categories. Table 5-4 shows emission factors for

the various engines. Table 5-5 shows some examples of the aircraft and engine combinations. 

Information on these categories may be expanded in the next update of AP-42 to include more

aircraft and engine combinations as well as emission indices for additional engines.

175

 If the detailed estimation procedure is being followed based on specific aircraft and

engines, airport specific estimates on time-in-mode might be used if available from airport

officials. These data likely vary quite widely because of the many different types of services

provided by this aircraft category. Otherwise, the estimation procedure is based on the default

times-in-mode from Table 5-1. The rest of the detailed estimation procedure uses the same set of

equations used for commercial aircraft. Emissions should be calculated separately for the

general aviation and air taxi categories. 

Adjust Approach and Climbout TIM to Represent Local Conditions

TIMapp-G = 6 X (H/3000) (5-5)

TIMclm-G = 5 X [(H-500)/2500] (5-6)

TIMapp-G - time in the approach mode, in minutes

TIMclm-G - time in the climbout mode, in minutes (assumes transition from

takeoff to climbout occurs at 500 feet)

 H - mixing height used in air quality modeling for time and region of

interest

Calculate Emissions for Each Aircraft Type

The emission factors that appear in Table 5%4 for general aviation and air taxi aircraft

have not been updated since the last version of AP%42. The next edition of AP%42 should

include updates to much of the date that appears in the table.

 Eij = 
 (TIMjk) X (FFjk/1000) X (EIijk) X (Nej

) (5-7)

 Eij = total emissions of pollutant i, in pounds, produced by aircraft type j

for one LTO cycle.

TIMjk = time in mode for mode k, in minutes, for aircraft type j

 FFjk = fuel flow for mode k, in pounds per minute, for each engine used

on aircraft type j (from Table 5-4)

 EIijk = emission index for pollutant i, in pounds of pollutant per one

thousand pounds of fuel, in mode k for aircraft type j (from Table

5-4)

 NEj = number of engines used on aircraft type j (from Table 5-5)
 244 Memorandum from S. Webb to R. Wilcox, "General Aviation Generalized Emission Indexes," June 10, 1991.

176

Calculate Total Emissions for All General Aviation or Air Taxi Aircraft

ETi(G) = 
 Eij (5-8)

 Eti(G) = total emissions of pollutant i, in pounds, produced by all general

aviation or air taxi aircraft operating in the region of interest

(where j covers the range of aircraft operating in the area)

 LTOj = total number of LTO cycles for aircraft type j, during the inventory

period

5.2.4.2 Alternative, Fleet-Average Procedure

Where detailed information on specific aircraft mix and activity is unavailable, a rough

estimate of emissions for each aircraft category can be made using emission indices based on a

representative fleet mix.244 The following indices were calculated based on 1988 fleet data for

general aviation aircraft.

HC 0.394 pounds per LTO

CO 12.014 pounds per LTO

NOx 0.065 pounds per LTO

SO2 0.010 pounds per LTO

Since air taxis have fewer of the smallest engines in their fleet and more turboprop and

turbojet engines, their emission factors are somewhat different.

HC 1.234 pounds per LTO

CO 28.130 pounds per LTO

NOx 0.158 pounds per LTO

SO2 0.015 pounds per LTO

Airport activity for general aviation aircraft and air taxis can be found in FAA Air Traffic

Activity. Figure 5%5 is a copy of a page from Table 4 which reports airport operations at airports

with FAA-operated traffic control towers. Table 22 from the same report lists operations at

airports with FAA contractor-operated traffic control towers. In this report, an operation could

be either a takeoff or landing, so the number of operations should be divided by two to get LTOs. 

In addition to these airports, general aviation and air taxi activity is common at smaller airports

and landing strips not included in FAA's reporting system. These airports must be contacted

directly to determine if information is available on 

 245 Aircraft Environmental Support Office (AESO). Commanding Officer, Attn: AESO, Code 04210, Naval

Aviation Depot, North Island, San Diego, California 92135-5112, (619) 545-2901.

 246 Air Force Engineering and Service Center, RDUS, Tyndall AFB, Florida 32403.

178

general aviation activity. Air taxi operators located at the airports, may be a source for

information on air taxi activity. These steps may have little impact on the inventory and should

be considered discretionary.

The annual emissions are then calculated as the product of airport activity in LTOs from

FAA Air Traffic Activity and the emission index in pounds per LTO listed above. Total

emissions should be computed separately for general aviation and air taxis.

5.2.5 Activity and Emissions for Military Aircraft

FAA Air Traffic Activity contains information on the number of military operations at

airports with FAA%operated traffic control towers. This information can be used in much the

same way as for general aviation aircraft, however, military air bases are not included in this

reference. The information only addresses military operations at civil airports. Military air bases

included in the modeling area should be apparent from maps of the area. For these bases, it

likely will be difficult to get good information on fleet make up and activity. In some cases,

information may be available from the Office of the Base Commander on fleet make-up and

possibly some measure or estimate of activity such as LTOs for one day or one month. Where

specific information is available for aircraft type and LTOs, Table 5%6 lists military aircraft and

their engines, and Table 5%7 lists the modal emission rates for these engines. Much of the data in

Table 5%7 has been updated since the last version of AP%42.

Where data on military aircraft operations and fleet make-up cannot be obtained from the

base commander, a centralized support office may be able to provide the required information. 

The Navy245 and Air Force246 both have environmental support offices responsible for

information on emissions from military aircraft including complete inventories for many bases. 

If inventory information is unavailable after contacting the Navy or Air Force environmental

support office, a letter requesting an inventory should be sent to the base commander through the

EPA regional office with copies to the appropriate environmental support office.

If data on fleet make up and activity are obtained from the base commander or the

environmental support offices, the procedure for calculating an inventory for military aircraft is

the same as that used for both commercial and general aviation. The calculations for each

subsequent step follow.










189

Adjust Approach and Climbout TIM to Represent Local Conditions

TIMapp-M = 4 X (H/3000) (5-9)

TIMclm-M = 1.4 X [(H-500)/2500] (5-10)

TIMapp-M - time in the approach mode for military aircraft, in minutes

TIMclm-M - time in the climbout mode for military aircraft, in minutes 

(assumes transition from takeoff to climbout occurs at 500 

feet)

 H - mixing height used in air quality modeling for time and 

region of interest

Calculate Emissions for Each Aircraft Type

 Eij = 
 (TIMjk) X (FFjk/1000) X (EIijk) X (NEj) (5-11)

 Eij - total emissions of pollutant i, in pounds, produced by 

aircraft type j for one LTO cycle

 TIMjk - time in mode for mode k, in minutes, for aircraft type j

 Ffjk - fuel flow for mode k, in pounds per minute, for each 

engine used on aircraft type j (from Table 5-7)

 Eiijk - emission index for pollutant i, in pounds of pollutant per 

one thousand pounds of fuel, in mode k for aircraft type j 

(from Table 5-7)

 NEj - number of engines used on aircraft type j (from Table 5-6)

Calculate Total Emissions for All Military Aircraft

ETi(M) = 
 Eij (5-12)

ETi(M) - total emissions of pollutant i, in pounds, produced by all 

military aircraft operating in the region of interest (where 

j covers the range of military aircraft operating in the 

area)
190

After completing the emissions inventory for military aircraft, the overall inventory is

complete, made up of emissions from commercial, general aviation, and military aircraft. The

final three sections of the report address changes to the inventory due to alternative operating

practices, addition of minor emission sources, and changes to the aircraft fleet in the future.

5.3 VARIATIONS TO THE INVENTORY CALCULATION PROCEDURE

There are several variations to the basic inventory procedure that can adjust the period

covered by the inventory or address some operational procedures followed by some pilots or

airlines that affect aircraft emissions. These adjustments to the inventory are discussed in this

section.

5.3.1 Variability of Activity - Daily and Seasonal

The calculation procedure described in the methodology does not address daily or

seasonal variations. If the air quality modeling period requires emissions data that accounts for

these variations, certain adjustments must be made to the equations. The daily or seasonal

variations will be exhibited in LTOs, mixing height, and idle time, primarily idle-out.

The references for determining LTOs in Section 5.2 give data on an annual basis and

adjustment may be necessary to capture changes over time. The frequency of LTOs at most civil

airports are reasonably uniform during daylight hours with lower activity during the night and

uniform during week days with lower activity on the weekends, although some airports that cater

to recreational flying may show higher activity on weekend days. For most large urban airports,

LTOs are uniform on a monthly basis with a slight increase in activity during the summer, which

typically is a time of high travel, although some regions may attract more travelers during the

winter as a result of their climate. The seasonal variation in activity at smaller urban airports or

airports that serve smaller cities may be more pronounced because of factors that affect travel on

a local basis such as tourism or seasonal business activity. Obtaining specific information on

daily and seasonal variation is difficult. The best source likely will be the airport operators,

many of who keep some type of records of activity such as total number of LTOs, number of

visitors/passengers, number of cars using the parking lots, or some similar measure that may be

representative of the daily or seasonal variation in use of the airport. Another source of

information on the daily and weekly variation of LTOs is published flight schedules. These

schedules can be reviewed to evaluate the number of scheduled flights during daylight hours

versus night-time hours or week day versus weekend. It would be difficult to use this source to

evaluate seasonal variations.

Mixing height changes throughout the day and from season to season depending on

meteorological conditions such as wind, cloud cover, temperature, and humidity. The

adjustments to the time in approach and climbout mode should be based on a weighted average

of the mixing heights for the time periods of interest, using variations in LTOs as the weighing

factors. See Section 5.2.2 for more information about determining the mixing height.
191

Taxi/idle time may vary in proportion to variations in LTOs because they are partially a

function of airport congestion such that the greater number of LTOs the more likely that airport

congestion will increase the time for aircraft to taxi to the runway. The airlines' scheduling

departments are the best sources of taxi/idle-time data and their projections typically show daily

variations estimated for a particular season. Airport operators also may have information on

taxi/idle time variation during a day or from one season to another. Availability of this data will

be highly variable.

5.3.2 Operational Activity that Affects Aircraft Emissions

There are variations to standard operating procedures which pilots follow that will affect

the aircraft's emissions. Two examples, which may be found in commercial operations, are

single-engine taxiing and derated takeoff. Both of these procedures have the potential to save

fuel as well as reduce emissions. Where detailed air quality modeling is being performed, these

refinements may merit consideration. However, in most cases these procedures are performed at

the discretion of the pilots and their use may not be consistent or predictable.

5.3.2.1 Reduced Engine Taxiing 

Single-engine taxiing or reduced-engine taxiing is, as the name implies, taxiing with one

or more engines shutdown. This is usually practiced during taxi-out. An aircraft can taxi using a

single engine at idle without significantly increasing the emissions of that engine since adequate

power for taxi generally is available at idle power setting. The emissions reductions are equal to

the calculated emissions of the engines that are shutdown. The change to the calculation

procedure to account for single-engine taxiing is shown in Equation 5-13.

Eij = 
 (TIMjk) X (FFjk/1000) X (EIijk) X (NEjk) (5-13)

Eij - total emissions of pollutant i, in pounds, produced by aircraft type j

 TIMjk - time in mode for mode k, in minutes, for aircraft type j

 FFjk - fuel flow for mode k, in pounds per minute, for each engine used on

aircraft type j (from Table 5-4)

 EIijk - emission index for pollutant i, in pounds of pollutant per one thousand

pounds of fuel, in mode k for aircraft type j (from Table 5-4)

 NEjk - number of engines used on aircraft type j, for mode k (from Table 5-2)

NE for the taxi/idle-out mode would be the number of engines actually used rather than

the number on engines shown in Table 5%2.
192

5.3.2.2 Derated Take%off

A derated take%off is a procedure where the pilot sets the throttle for takeoff at less than

100%. The derated throttle setting is determined based on worst-case operating conditions, i.e.,

performance of the aircraft as though it were at maximum weight on a hot day. In some cases

this may allow a takeoff throttle setting of 90% or less. To adjust the emissions calculations to

account for this change, engine manufacturers recommend a linear interpolation between the

takeoff and climbout fuel flow rates and emission factors. Information on the degree and

frequency of derating for takeoff should be collected directly from the airlines.

Other operational factors may affect engine exhaust emissions, such as the use of full

throttle, reverse thrust to decelerate the aircraft during landing. These effects may also be

significant and are being evaluated by EPA. Any additional information on operational factors

will be included in the next update to AP-42.

5.3.3 Particulate Emissions

As mentioned in Section 5.1.1.2, very few measurements have been made of particulate

emissions from aircraft engines. However, for most turbine engines, EPA does limit the amount

of smoke that may be emitted. This limit is specified as a smoke number. Attempts have been

made to derive a correlation between smoke and particulates which could be used to create a

particulate emission index based on smoke number. Thus far, these efforts do not match

experimental results very closely. If particulates are of concern for the inventory area it may be

of help to discuss the issue further with the engine manufacturers or the FAA Office of

Environment and Energy. EPA will continue to investigate this area and may provide further

information in the next update to AP-42.

5.4 OTHER EMISSION SOURCES

5.4.1 Auxiliary Power Units

When large aircraft are on the ground with their engines shut down, they need power and

preconditioned air to maintain the aircraft's operability. If a ground-based power and air source

is unavailable, an auxiliary power unit (APU), which is part of the aircraft, is operated. These

units are essentially small jet engines, which generate electricity and compressed air. They burn

jet fuel and generate exhaust emissions like larger engines. In use, APUs essentially run at full

throttle. Table 5-8 lists several APUs and the aircraft on which they are installed. Emission

factors for some of these APUs are provided in Table 5-9. Emission factors for APUs under load

should be used where information is available on time of use. 




 247 World Jet Airplane Inventory, Boeing, Commercial Airplane Group, Year-End 1990.

197

Where emission factors are unavailable for a specific APU, factors for an alternative unit of the

same or similar horsepower should be used. It will be necessary to contact the airlines or

military base commander directly to find out whether APUs are used regularly at a specific

airport and, if so, how long an aircraft is expected to stay at a gate with the APU running. This

information may be difficult to get.

 

5.4.2 Evaporative Emissions

For general aviation aircraft, there are evaporative emissions that result from refueling

and fuel spillage. Emissions also occur from preflight checks of the aircraft and diurnal

temperature cycles that cause the fuel tanks to vent. Refueling emissions are addressed in

Volume I, Section 5.4.1. EPA is continuing to evaluate the other emission sources and may

provide information in the next update to AP-42.

5.5 EFFECT OF FUTURE CHANGES TO THE FLEET

Airlines continually acquire newer aircraft, gradually phasing out older models. While

commercial aircraft often remain in service for more than 25 years, over time, this process phases

out the aircraft using engines that do not meet EPA's hydrocarbon emission standard. The

current world aircraft fleet averages 12.4 years old according to the 1990 World Jet Inventory

published by the Boeing Corporation.247 Significant among the older aircraft are engines that do

not meet the EPA standard such as the Spey MK511 and older JT8Ds and CF6-50s. The JT8Ds

and CF6-50s are prevalent on B-727s, DC-9s, and DC-10s, many nearly 20 years old. As new

aircraft are added to the fleet the older aircraft are the most likely to be retired. The effect is one

of replacing older, dirty engines with newer engines on the new aircraft that are much cleaner

from an emissions standpoint. Airport noise regulations also are forcing changes to the

commercial aircraft fleet. National noise regulations which were recently passed by Congress

are forcing airlines to phase out use of loud aircraft by 2000. This can be accomplished by

retiring the loud, older aircraft, replacing their engines with newer, quieter ones, or modifying the

engines to muffle the noise. The first two alternatives result in aircraft with reduced emissions. 

Because this legislation is so new, the airlines are yet to formulate specific plans meeting the

requirements. However, as the equipment is updated, the changes to the fleet will be reflected in

FAA's reports on aircraft activity. Since there is a significant engineering and development

leadtime for producing new aircraft engines, most of the commercial aircraft to be added to the

fleet in the next five to seven years will be powered by engines that are included in Tables 5%2,

5%3 and 5-4.

Since specific plans to upgrade their fleets have not been announced recently by the

airlines, it is difficult to project what future changes will be and how they will effect the

inventory of emissions for all locations. Some carriers will update their fleets more quickly 
 248 Memorandum from R. Cook to R. Wilcox, "Exhaust THC to VOC Correction Factors for Aircraft," July,

1992.

198

than others so there may be changes that can be captured on an area specific basis. If it is

desirable to project changes to the inventory for this source category, the predominant airlines for

the airports included in the inventory area should be contacted for their specific plans. EPA is

continuing to look at better data sources and methods for projecting changes to aircraft fleet

emissions.

Another change that will affect future emissions from aircraft is the growth in travel. Air

travel has experienced strong growth over the past several years and this growth is expected to

continue for the foreseeable future. Many existing airports are near capacity and others will reach

their capacity limits in the near future. This will have two effects: air traffic at small feeder

airports and regional hubs will grow and the current major hubs will experience additional

congestion. The net effect these changes will have on air quality is unclear. Increased

congestion at some airports will increase taxi/idle times but the expanded use of smaller airports

may relieve congestion at others.

5.6 CONVERTING FROM TOTAL HYDROCARBONS (THC) TO VOLATILE ORGANIC 

 COMPOUNDS (VOC)

EPA recognizes that it may be necessary to determine the level of volatile organic

compounds (VOC) emitted from aircraft engines. Since the emission factors for exhaust HC

contained in this document represent total hydrocarbons (THC), this section illustrates the

method that is recommended for converting THC to VOC emissions.248

5.6.1 Commercial and Military Conversions

The commercial and military aircraft fleets are dominated by turbine engines. Therefore,

a single correction factor can be used to convert THC to VOC emissions for each aircraft

category as follows. 

VOCCOMMERCIAL = THCCOMMERCIAL X 1.0947 (5-14)

VOCMILITARY = THCMILITARY X 1.1046 (5-15)
199

5.6.2 General Aviation and Air Taxi Conversions

The general aviation (GA) fleet and, to a much lesser extent, the air taxi (AT) fleet may

have a significant proportion of piston engines, in addition to turbine engines. Therefore,

separate correction factors should be used for each engine type within the respective aircraft

categories if the detailed, aircraft-specific inventory methodology described in Section 5.2.4.1

was used to estimate THC emissions. Otherwise, if the alternative, fleet-average procedure

described in Section 5.2.4.2 was used, a single correction factor can be used for each aircraft

category. 

Detailed Methodology

VOCGA PISTON = THCGA PISTON X 0.9649 (5-16)

VOCGA TURBINE = THCGA TURBINE X 1.0631 (5-17)

VOCAT PISTON = THCAT PISTON X 0.9649 (5-19)

VOCAT TURBINE = THCAT TURBINE X 1.0631 (5-20)

Alternative, Fleet-Average Methodology

VOCGA FLEET = THCGA FLEET X 0.9708 (5-18)

VOCAT FLEET = THCAT FLEET X 0.9914 (5-21)
 249 The term inventory area can be quite diverse and may refer to an area as large as a multi-state CMSA or an

area as small as a county, or part of a county, within a state. 

 250 A third type, steam locomotives, is used in very localized operations, primarily as tourist attractions, and

emissions from these locomotives are insignificant. In addition, the particulate emissions from operating steam

locomotives is so large that nearly all of it falls to the surface within 50 meters.

 251 Class I railroads are classified by the Interstate Commerce Commission as having annual revenues greater

than $93.5 million.

 252 Class I railroads carried 93 percent of total freight revenues in 1989.

200

6.0 EMISSIONS FROM LOCOMOTIVES

This chapter illustrates how a state or local agency can calculate emissions from 

locomotives within an inventory area.249 Railroad locomotives used in the United States are

primarily of two types: electric and diesel-electric.250 Electric locomotives are powered by

electricity generated at stationary power plants and distributed by either a third rail or overhead

catenary system. Emissions are produced only at the electrical generation plant, which is

considered a point source and therefore not of interest here. Diesel-electric locomotives, on the

other hand, use a diesel engine and an alternator or generator to produce the electricity required

to power its traction motors. Emissions produced by these diesel engines are of interest in

emission inventory development. Emissions for hydrocarbons (HC), carbon monoxide (CO),

oxides of nitrogen (NOx), sulfur dioxide (SO2), and particulate matter (PM) from this source are

covered in this chapter. 

This chapter is a complete revision of the corresponding chapter in the previous edition of

this document. In addition, this chapter also updates the emission factor information that appears

in Compilation Of Air Pollutant Emission Factors, Fourth Edition And Supplements, AP-42. 

Subsequent to the publication of this document, AP-42 will be formally updated. 

Other sources of emissions from railroad operations include the small gasoline and diesel

engines used on refrigerated and heated rail cars. These engines are thermostatically controlled,

working independently of train motive power, and fall in the category of off-highway equipment

which are addressed elsewhere in this document. (See Section 3.3 of Volume IV.) 

Railroads can be separated into three classes based on size: Class I , Class II, and Class

III. Class I railroads251 represent the largest railroad systems in the country. (See Appendix 6-1

for a complete list.) Because of their size, Class I railroads operate over a large geographic area. 

Also, they carry most of the interstate freight252 and carry most of the passenger service. They

are required to keep detailed records of their operations and to report yearly to the Interstate

Commerce Commission (ICC). 
 253 Class II railroads are classified by the Interstate Commerce Commission as having annual revenues greater

than $18.7 million but less than $93.5 million.

 254 Class III railroads are classified by the Interstate Commerce Commission as having annual revenues less than

$18.7 million.

 255 A "smaller" area can still be an area as large as a state. The term "smaller" is used in contrast with the large

interstate areas which are covered by Class I railroads. 

 256 In this chapter, line haul operations include intermodal freight service, mixed freight service, and passenger

service.

201

Class II253 and III254 railroads represent the remainder of the rail transportation system and

generally operate within smaller, localized areas.255 These smaller railroads are not subject to the

same reporting requirements, and their recordkeeping may be less extensive. Also, their fleet of

locomotives tends to be older, with the Class I railroads buying almost all of the new

locomotives.

Locomotives within each of the Classes can perform two different types of operations:

line haul256 and yard (or switch). Line haul locomotives, which perform the line haul operations,

generally travel between distant locations, such as from one city to another. Yard locomotives,

which perform yard operations, are primarily responsible for moving railcars within a particular

railway yard. 

This chapter of the guidance document will be divided into six sections plus eight

appendices. Section 6.1 will be an overview of the recommended methodology. Section 6.2 will

specifically describe the recommended methods for calculating the emissions from various types

of rail service based on generic or national operating characteristics. Section 6.3 will present

procedures for tailoring the recommended methods to more closely reflect local operating

conditions. Section 6.4 will introduce alternative methods which are not fully discussed in this

chapter. Section 6.5 will discuss "remotored" locomotives; locomotives which have had their

original diesel engines replaced by newer, more efficient power plants. Section 6.6 will illustrate

the conversion factor method recommended for converting total hydrocarbons (THC) to volatile

organic compound (VOC) emissions. 

All correspondence pertaining to this chapter of the guidance document should be

directed to:

Emission Planning and Strategies Division

U.S. EPA

2565 Plymouth Road

Ann Arbor, MI 48105

(313) 668-4200 
202

6.1 OVERVIEW OF RECOMMENDED INVENTORY METHODOLOGY

Three steps are necessary in order to assess locomotive emissions within an inventory

area. First, railroad operations are separated into three distinct categories: Class I line haul, Class

II and Class III line haul, and yard. Second, emissions for each pollutant are calculated for each

of the three categories using either the recommended methods described in Section 6.2 or, if

circumstances explained later occur, the alternative methods described in Sections 6.3 or 6.4. 

Third, the total locomotive emissions in the inventory area are calculated by summing the

quantities of each pollutant for each of the three categories.

The methods illustrated in this chapter are based on annual inventories and annual data. 

Developing inventories for shorter time periods is straight forward because railroad traffic is

relatively constant throughout the year and therefore, less than annual calculations can be done

by simple apportionment. In addition, the recommended methods described in Section 6.2 are

based on a national locomotive fleet mix and average fuel consumption figures. 

 

6.2 RECOMMENDED METHODS

The recommended methods for each of the three categories, as follows: Class I line haul,

Class II and Class III line haul, and yard, are discussed separately below.

6.2.1 Class I Line Haul Locomotives 

For Class I line haul locomotives, emissions are calculated by multiplying the amount of

fuel consumed in the inventory area by the appropriate emission factors.

 Inventory Area Emissions = Fuel Consumption x Emission Factors 

6.2.1.1 Fuel Consumption

If Class I line haul locomotives only traveled within the inventory area, fuel consumption

could be determined directly from the amount of fuel dispensed into the units. However, these

line haul locomotives travel predominantly interstate. Hence, they do not necessarily burn the

fuel in the same location where the fuel was pumped, making it impossible to determine fuel

consumption in the area of interest in this manner. 

In order to determine inventory area fuel consumption, it is necessary to allocate the total

amount of fuel consumed "systemwide" for Class I railroads to the inventory area. This is done

by dividing the traffic density (expressed in Gross Ton Miles or GTM) for each Class I railroad

track segment within the inventory area by the systemwide fuel consumption index (expressed in

Gross Ton Miles per gallon or GTM/gal) for that railroad. This process is repeated for each

railroad. 
203

In any given area, there will be only a few active Class I railroads, and the railroad

company staff should be able to perform this step and provide the amount of fuel consumed

within the inventory area on request. In addition, EPA has included a detailed explanation of

how this step is performed based on published data and information which is generally available

from each railroad.

Fuel consumption, for each Class I railroad within an inventory area, is therefore

specifically calculated using the following formula:

 Fuel Consumption = Traffic Density (GTM) / Fuel Consumption Index (GTM/gal) 

The inventory area traffic density and the fuel consumption index are described

separately below.

 Traffic Density 

For every track segment within a state, each Class I railroad maintains information on

traffic density (GTM), length (miles), direction, and geographic location. Therefore, it is

possible to calculate the traffic density for an inventory area by summing the traffic densities for

each track segment or portion thereof within the inventory area. 

This information can be obtained, for each area, either directly from the individual

railroads or from the Association of American Railroads in Washington, D.C. The information

should contain enough detail so that track segments or portions thereof can be assigned to the

inventory area. However, if the agency is unable to perform this task, it may become necessary

to obtain assistance from the Class I railroad in order to determine where the inventory area

boundary intersects the track segment. 

The gross ton mile information may be supplied in one of two ways. The first way is

without the weight of the locomotives included. The second way is with the weight of the

locomotives included. This distinction is important when calculating the fuel consumption

index. 

 Fuel Consumption Index

The fuel consumption index (GTM/gal), for each Class I railroad within an inventory

area, should be calculated by dividing the systemwide gross ton miles (GTM) by the systemwide

fuel consumption (gal). See the following formula:

 Fuel Consumption Index (GTM/gal) = System Gross Ton Miles/System Fuel Consumption
 257 The fuel consumption rate will be less if the weights of the locomotives are not included in the calculation.

 258 Locomotive Emission Factors for Inventory Guidance Document, Office of Mobile Sources, U.S. EPA, June

1991.

204

Each Class I railroad is required to report these statistics each year to the ICC in an

annual report entitled "R-1." The R-1 report should be used, for each carrier, to obtain

information on annual fuel consumption (Schedule 750: line 1), total gross ton miles including

locomotives (Schedule 755: line 104), and, when needed, total gross ton miles excluding

locomotives (Schedule 755: line 104 minus line 98). An example of these schedules is included

in Appendix 6-2.

The fuel consumption index will vary depending on whether the weight of the

locomotives is included in the calculation.257 Also, calculating fuel consumption within the

inventory area requires the multiplication of traffic density by fuel consumption index; therefore,

it is important to match the units of each of these components. If traffic density is supplied

without the weight of the locomotives included, then the fuel consumption index should be

determined without the weight of the locomotives included in the calculation. If traffic density is

supplied with the weight of the locomotives included, then the fuel consumption index should be

determined with the weight of the locomotives included in the calculation. 

The fuel consumption index, with locomotives, is calculated by dividing total gross ton

miles with locomotives, Schedule 755: line 104, by the total fuel consumed, Schedule 750: line

1. The fuel consumption index, without locomotives, is calculated by dividing total gross ton

miles without locomotives, Schedule 755: line 104 minus line 98, by the total fuel consumed,

Schedule 750: line 1. Examples of these calculations are shown in Appendix 6-3.

6.2.1.2 Emission Factors

Now that fuel consumption has been calculated, inventory area emissions are determined

by multiplying that value by the fleet average emission factors for each pollutant (expressed in

pounds per gallon of fuel burned (lbs/gal). The recommended default emission factors for all

line haul locomotives are shown in Table 6-1.

 Table 6-1. Line Haul Locomotive Emission Factors258

 Emission Factor

 Pollutant (lbs/gal) 

HC 0.0211

CO 0.0626

NOx 0.4931

SO2* 0.0360

PM 0.0116

* SO2 calculated based on a fuel sulfur content of 0.25 percent by weight. 

Appendix 6-3 gives a full example of how to calculate emissions from the Class I line

haul locomotives in an inventory area, using the Santa Fe railroad in the State of Illinois. 

6.2.2 Class II and III Line Haul Locomotives 
 259 In addition, tabulations of track mile data may be available for counties, Metropolitan Statistical Areas

(MSA), or urban areas from some state transportation agencies, or from the county or metropolitan planning

organization within whose jurisdiction the study area is located. Alternatively, route miles can be obtained by direct

measurement from an appropriate map, such as the County Series maps (obtained from the state transportation

agency), U.S. Geologic Survey maps, U.S. Transportation Zone maps, or locally prepared maps.

205

Similar to the recommended method for Class I line hauls, emissions from Class II and

III line haul locomotives are calculated by multiplying the amount of fuel consumed in the

inventory area by the appropriate emission factors.

 Inventory Area Emissions = Fuel Consumption x Emission Factors

6.2.2.1 Fuel Consumption

Since Class II and III railroad companies are not required to file R-1 reports, annual fuel

consumption should be obtained directly through interviews or letters with each Class II and III

railroad operating within the inventory area. This approach is sufficient because, unlike Class I

line haul operations, most Class II and III line haul travel is predominantly within a relatively

small geographic area (see footnote 7). Therefore, in many instances, it is unnecessary to 

apportion system fuel use to an inventory area, because the fuel is consumed by the locomotives

within the inventory area. 

However, for the small number of Class II and III railroads operating outside the

inventory area, EPA recommends simply allocating the fuel consumption by track length or track

density (GTM). Each Class II and III railroad can supply both track length and track density

information.259 So, the percentage of fuel consumed is based on the percentage of track length or

track density within the inventory area. If, for example, 30 percent of the track length, for a

particular railroad, runs within the inventory area, then, in order to apportion the total fuel

consumed in the inventory area, multiply the total fuel consumption for the railroad by 0.30.
 260 In actuality, Class II and III railroads tend to have an older fleet mix. With local information, this could be

included in the calculation of an appropriate emission factor, as shown in Section 6.3, but the improvement in

accuracy is believed to be small. 

206

6.2.2.2 Emission Factors

The emission factors for Class II and III line haul locomotives are assumed to be the

same as Class I locomotives.260 A complete list of the emission factors is provided in Table 6-1

(See Section 6.2.1.2).

6.2.3 Yard Operations

The recommended method for yard locomotives is different from the method used for

line haul locomotives. Yard locomotive emissions, for each pollutant, are derived by multiplying

the number of yard locomotives operating within the inventory area by the amount of emissions

generated by each unit during the year. See the formula below:

 Inventory Area Emissions = Number of Yard Locomotives x Annual Emissions Per Yard 

 Locomotive

6.2.3.1 Number of Yard Locomotives

Since yard locomotives operate within the boundaries of a railway yard, it is possible to

calculate the number of locomotives operating within an inventory area through interviews with

the railway yard managers, who keep accurate records of yard locomotive operations. If this first

approach proves unproductive, the number of yard locomotives can be determined by actually

counting the units operating in each railway yard during a day. This is sufficient because the

number of yard locomotives in operation each day remains relatively constant throughout the

year. Switch yard engines are sent to railroad maintenance facilities according to regular

schedules. When a particular yard locomotive is away getting maintenance or repair, the yard

will replace the unit with another of approximately the same horsepower.

6.2.3.2 Emissions Per Yard Locomotive 

EPA estimates that the average yard engine emits the following amount of each pollutant

per year:
 261 The fuel consumption data used for this calculation were considered proprietary by the locomotive

manufacturers and hence could not be printed in this document.

 262 Some yards operate partially or not at all on weekends. Information on the operation schedule for yards may

be easily obtained from the railroads, and the figure of 365 can be adjusted accordingly.

 263 Locomotive Emission Factors for Inventory Guidance Document, Office of Mobile Sources, U.S. EPA, June

1991.

207

Table 6-2. Annual Emissions Per Yard Locomotive

 

 Annual Emissions 

Pollutant (lbs/yr) 

HC 4,174

CO 7,375

Nox 41,608

SO2* 3,075

PM 1,138

* SO2 calculated based on a fuel sulfur content of 0.25 percent by weight. 

These emission levels were calculated as follows. EPA estimated that, based on a

reasonable activity or duty cycle and typical fuel consumption rates, the average yard engine

consumes 228 gallons of fuel per day.261 Since yard locomotives can be assumed to operate 365

days a year262 (this assumes that when a yard engine is taken in for repairs it is replaced during

that period), the average yard engine consumes 82,490 (226 X 365) gallons of fuel per year.

EPA also determined that the average yard locomotive has the following emission factors

(lbs/gal): 

 Table 6-3. Emission Factors For Yard Locomotives263

 Emission Factor

 Pollutant (lbs/gallon) 

HC 0.0506

CO 0.0894

NOx 0.5044

SO2* 0.0360

PM 0.0138

* SO2 calculated based on a fuel sulfur content of 0.25 percent by weight. 
208

Therefore, the annual emissions per yard locomotive, Table 6-2, were determined by

multiplying the fuel consumption estimate (85,410 gal/year) by each emission factor in Table 6-

3.

6.3 TAILORING METHODS

EPA recognizes that railroad operations may vary significantly from the national average

and that some state and local air quality agencies may have access to more detailed information

regarding the locomotive activity in their inventory area. Because of this, EPA has included two

additional methodologies to allow these agencies to tailor the emissions calculations based on

actual locomotive fleet, or roster, data and local operational characteristics. Using these tailoring

methods is not required, but they have been included here should a state or local agency decide

that a more precise calculation is desirable. 

As explained in Section 6.2, the recommended method for calculating total emissions in

an inventory area requires multiplying a fleet averaged emission factor by fuel consumption. An

implicit element of the composite emission factor is the locomotive roster. If the actual roster for

an inventory area is different from the one used in the recommended method, then the composite

emission factor, calculated using the recommended method for the inventory area, could be

different than if the composite emission factor were calculated using the actual locomotive roster.

Another element implicit in both the composite emission factor and the estimate of fuel

consumption is the duty cycle which an engine goes through during operation. If the actual duty

cycle in an inventory area is different from that assumed in the recommended method, then the

values used in the recommended method for the inventory area could be different than if the

values were calculated using the actual duty cycle for that area.

6.3.1 Locomotive Roster Tailoring Method

The roster tailoring method requires the development of an area specific roster, and

subsequently the calculation of new fleet average emission factors. These new emission factors

will then be substituted for the national fleet average emission factors in Section 6.2, and

subsequently, will be multiplied by the fuel consumption figure to give the emissions for the

inventory area. The tailoring method for both line haul and yard locomotives will be the same,

but, the new tailored rosters should be calculated separately. The roster tailoring method is

composed of the following steps: 

6.3.1.1 Identify the locomotives in the area

The first step in the roster tailoring method is to identify all of the locomotives within an

inventory area. Identification should be made based on make and model number (EMD GP9 for

example). 
209

EPA recognizes that identifying Class I line haul locomotives within an inventory area

may be difficult because these locomotives travel predominantly interstate. EPA recommends

that the agency performing the emissions inventory contact each Class I railroad within the

inventory area and ask for an estimate of the number and type of locomotives operating within

the area. 

If it is not possible to identify the Class I line haul locomotives within the inventory area

using the above procedure, EPA suggests, as a next best alternative, that the agency performing

the emissions inventory contact each Class I railroad operating within the inventory area and

request a copy of its systemwide locomotive roster. The agency may then assume that these

locomotives operate on routes that enter or lie within the inventory area.

Identifying Class II and III line haul locomotives should be easier than identifying Class I

line hauls, due to the fact that the former locomotives travel predominantly within a small area. 

EPA again recommends contacting each Class II and III railroad which operates within the

inventory area and requesting a copy of its locomotive roster. 

Identifying yard engines within an inventory area has already been explained in Section

6.2.3.1, and that approach should be followed here as well. 

Once the locomotives have been identified, the agency calculating the emissions within

the inventory area should create a list, including number of engines and model type, similar to

the one listed as "Locomotive Model" in Appendix 6-4. "Locomotive Model" is a detailed

listing of most of the locomotives models operating today which could exist in any fleet. (For

Example: "GP9", "SD50", "U30C", etc.) 

6.3.1.2 Determine the engine type

The second step is to convert from the locomotive model to a specific engine type for

which EPA has emissions data. For example, a "GP9" model number would equate to a "16-

567C" diesel engine type. Again, Appendix 6-4 shows how this conversion would appear. 

6.3.1.3 Sum the total of the conversions

Once all of the conversions have been made, the third step is to calculate the new

inventory area roster by summing the total of the conversions and then calculating the percent of

the total for each engine type. Appendix 6-5 illustrates how this procedure was performed for the

national roster used in Section 6.2.
 264 When the national roster was calculated, locomotives which might perform both functions were not entered as

indicated here; thus Appendix 6-5 does not show any overlap of any locomotives.

210

It is important to remember that it is possible for some engines to perform both yard and

line haul service (usually at different times). If this is the case, the same engine type may be

entered as both a line haul and a yard engine.264

6.3.1.4 Calculate the new fleet average emission factors

The fleet average emission factors given in the recommended methods (Section 6.2) were

derived using a national roster (Appendix 6-5). Since the roster changes with the tailoring

method, the fleet average emission factors will change as well. The fourth step, therefore, is to

re-calculate the emission factors using the new roster. To perform these calculations, simply

multiply the new roster percentage for each engine by the emission factor (Appendix 6-6) for

each pollutant for that engine. Appendix 6-7 illustrates how this is done.

6.3.1.5 Multiply the new emission factors by fuel consumption

Now that the new emission factors have been calculated for both line haul and yard

locomotives based on the new roster, emissions are calculated by multiplying by fuel

consumption. This procedure is the same as the recommended methodology which is explained

in Section 6.2.

6.3.2 Duty Cycle Tailoring Method

The Agency believes that the duty cycles which are indicated in the recommended

methods are reasonably representative of railroad operations across the nation, including

nonattainment areas. These duty cycles, for line haul and yard locomotives, are shown in the

following table and again in Appendix 6-9. 
 265 This effect pertains only to the fuel consumption value obtained by apportioning systemwide fuel to the

inventory area (Section 6.2.1.1 or 6.2.2.1), or the estimated fuel consumption value for each yard locomotive

(Section 6.2.3.2). 

211

 Table 6-4. Locomotive Duty Cycles 

 Time in Notch (%) 

 Throttle Notch Line Haul Yard 

8 1 1

7 3 0.5 

6 4 0.5 

5 4 1

4 5 2

3 44

2 4 7

1 47

Idle 49 77

 Dynamic Brake 12 0

 Total 100 100

If local conditions are likely to result in duty cycles that are substantially different from

those shown above, State or local authorities may consider adjusting the emissions inventory

methodology to incorporate this information. Any modifications, however, should be done in

consultation with local railroad officials to determine if actual duty cycle measurements are

available for this purpose, or if less specific adjustments are appropriate, based on past operating

experience. 

The most significant effect of altering the duty cycle would be to change the amount of

fuel that is estimated for the inventory area.265 Generally, the fuel consumption rate of a

locomotive engine is determined by throttle notch position. The more time a locomotive spends

in higher throttle notches, the more fuel it uses. Conversely, the more time spent in lower

throttle notch positions, the less fuel is used. Therefore, the amount of fuel consumed is

generally proportional to the time a locomotive spends in each throttle notch position. 

The preferred approach for incorporating a tailored duty cycle into the analysis is for

State or local authorities to recalculate the fuel consumption of each locomotive model in the

inventory area, using the new time-in-notch data and the appropriate fuel consumption rate for

each throttle position. Unfortunately, EPA is unable to provide notch-specific fuel consumption

rates in this document because the locomotive manufacturers have claimed that such information

is proprietary. Fortunately, there are two alternative methods for incorporating alternative duty

cycles without having these data. 
 266 It is assumed that all of the elemental sulfur in the fuel is oxidized into SO2.

212

The first approach is to use the information obtained in consultation with railroad

officials to develop a "general correction factor" that can be applied to the fuel consumption

estimates determined with the recommended methods in Section 6.2. The second approach is to

contact EPA at the address previously provided in this chapter with the alternative duty cycle

data. After analyzing this information in conjunction with the State or local agency, EPA could

provide a "tailored correction factor" for the inventory area. 

A secondary effect of altering the duty cycle is to change the emission factors (i.e.,

pounds of pollutant per gallon of fuel). This occurs because the combustion characteristics of the

engine vary by throttle notch position. Also, the significance of this effect varies for each of the

primary pollutants from this source (i.e., HC, CO, and NOx). 

In most internal combustion engines, fuel is usually burned more nearly completely as the

throttle position increases. Generally, this results in a smaller mass of certain pollutants being

produced for each unit of fuel consumed. For locomotives, this effect is most significant for HC

emissions, less so for CO emissions, and essentially non-existent for NOx emissions (i.e., the

amount of this pollutant is essentially constant per unit of fuel regardless of notch position). 

Therefore, only state or local agencies that are particularly concerned about HC emissions from

railroad operations are likely to benefit from including this effect in the inventory. 

Accounting for this phenomenon is similar to that discussed above for estimating the

amount of fuel used in the inventory area, because the preferred methodology involves the use of

proprietary notch-specific fuel consumption data. As a consequence, any agency wishing to

include this aspect of duty cycle tailoring in the emissions inventory must contact EPA with the

requisite information for a customized composite emission factor. 

6.3.3 SO2 Tailoring Method

The emission factors for SO2 are calculated based on the amount of sulfur contained in

the fuel.266 These emission factors are based on a sulfur content of 0.25 percent sulfur by weight. 

EPA recognizes that the amount of sulfur contained in diesel fuel may vary significantly from

one inventory area to another. In order tailor to sulfur emission factors based on the inventory

area fuel sulfur content, a recalculation should be performed by first calculating an adjustment

factor and then multiplying by the sulfur emission factor.

Tailored Sulfur = Adjustment Factor x Guidance Document SO2 Emission Factor.
213

The adjustment factor is determined by dividing the inventory area sulfur percentage by

the existing sulfur percentage. If the inventory area had a fuel sulfur content of 0.20 percent,

then the adjustment factor would be 0.80 (0.20/0.25). In order to recalculate the emission factor,

multiply the sulfur emission factor, 0.0340 lbs/gal, by the adjustment factor, 0.80, to get an

answer of 0.0272 lbs/gal.

6.4 ALTERNATIVE METHOD

EPA believes that the line haul locomotive methods presented in this chapter are

practical, feasible, and accurate. However, if for some unforeseen reason it is not possible to

acquire, or apportion, fuel consumption as required by these methods, an alternative approach,

such as the one described in EPA's Report to Congress On Railroad Emissions - A Study Based

On Existing Data, (no date available at time of printing) may be appropriate. This particular

alternative, if needed, may be most appropriate for inventorying congested urban areas. If it

proves necessary to consider any alternatives, please contact EPA at the address previously

provided in this chapter for additional details and assistance.

6.5 RE-ENGINED LOCOMOTIVES

EPA recognizes that some older locomotives have been re-engined with newer, more

efficient engines. Some of these engines are manufactured by EMD and GE and are most likely

represented in the data base. However, a small number of older GE and EMD chassis also have

been retrofitted with engines from other manufacturers, such as Caterpillar, Sulzer (Germany),

and Cummins. EPA acknowledges the existence of these engines, but because there are so few

engines of this type in the fleet and because EPA has not been able to obtain emission data on

these engines, they are not included in the data base. 

6.6 CONVERTING FROM TOTAL HYDROCARBONS (THC) TO VOLATILE ORGANIC 

 COMPOUNDS (VOC)

EPA recognizes that it may be necessary to determine the level of volatile organic

compounds (VOC) emitted from locomotives. Since the emission factors for HC contained in

this document represent total hydrocarbons as measured by a flame ionization detector (THCFID),

this section illustrates the conversion factor method recommended for converting THCFID to VOC

emissions. 

The method listed below was derived from an April 21, 1992, EPA memorandum from

Greg Janssen to Phil Lorang entitled "THC to VOC Correction Factors for Nonroad Emissions

Inventories" (the memorandum). Since locomotive emissions are created by large diesel engines,

and since locomotive diesel correction factors do not exist, EPA has assumed that the correction

factors for heavy-duty diesel vehicles (HDDV) can also be used as locomotive correction factors.
 267 Springer, 1979 (EPA-460/3-79-007) (PP. 47,98)

214

The method for converting THC to VOC was based on the methodology for nonroad

conversion and is as follows:

 VOCLOCOMOTIVE = THCFID LOCOMOTIVE X NMHCFID HDDV X VOC HDDV 

 THCFID HDDV NMHCFID HDDV

where

 THCFID LOCOMOTIVE represents the total hydrocarbon emissions measured from locomotives by

FID, 

 NMHCFID HDDV

THCFID HDDV is a non-methane hydrocarbon correction factor and represents the

ratio of non-methane hydrocarbons to total hydrocarbons, as

emitted by heavy duty diesel vehicles, and 

VOC HDDV

NMHCFID HDDV is a VOC correction factor and represents the ratio of VOC to nonmethane hydrocarbons, as emitted by heavy duty diesel vehicles.

Using the same method illustrated in Attachment 3 of the memorandum, EPA determined

that NMHCFID HDDV = 1.07 g/mile and THCFID HDDV = 1.10 g/mile.267 Furthermore, the VOC

correction factor, as derived for HDDV in Appendix 3 in the memorandum, was determined to

equal 1.0332. 

Thus, EPA has determined that the correction factor to determine VOC emissions from

locomotives is as follows:

VOCLOCOMOTIVE = THCFID LOCOMOTIVE X 1.07 X 1.0332 

 1.10

 or

 VOCLOCOMOTIVE = THCFID LOCOMOTIVE X 1.005 
215

Appendix 6-1

Class I Railroad Systems In The United States as of 4/91*:

 AMTRAK

 Atchison, Topeka and Santa Fe Railway Company (Santa Fe)

(AZ, CA, CO, IL, IA, KS, LA, MO, NB, NM, OK, TX)

 Burlington Northern Railroad Company

(AL, AR, CA, CO, FL, IA, ID, IL, KS, KY, MN, MO, MT, MS, NM, ND, NE, OK, OR,

SD, TN, TX, WA, WI, WY) 

 Chicago and North Western Transportation Company

 Consolidated Rail Corporation (Conrail)

(CT, D.C., DE, IL, IN, KY, MA, MD, MI, NJ, NY, OH, PA, VA, WV)

 CSX Corporation

CSX Transportation, Inc. (Includes Chessie System and Seaboard System)

(AL, DE, D.C., FL, GA, IN, IL, KY, LA, MD, MI, MS, NC, OH, PA, SC, TN, VA, WV) 

 Denver and Rio Grande Western Railroad

 Florida East Coast Railway

(FL)

 Grand Trunk Corporation

Grand Trunk Western Railroad

 Guilford Industries 

Boston and Maine Corporation

 Illinois Central Railroad

(IL, TN, KY, MS, LA)

 Kansas City Southern Railway

 Norfolk Southern Corporation 

Norfolk and Western Railway

Southern Railway System

 Soo Line Railroad

 Southern Pacific Transportation Company

St. Louis Southwestern Railway

 Union Pacific Railroad Corporation

Missouri Pacific Railroad

*Sources: Association of American Railroads and Federal Railroad Administration

217

Appendix 6-3 

Sample Calculation of Inventory Area Fuel Consumption for Santa Fe in Illinois

 Inventory Area Emissions = Fuel Consumption x Emission Factors

 Fuel Consumption = Traffic Density x Fuel Consumption Index

Traffic Density Without Locomotives

If the traffic density data for Illinois are supplied without locomotive weight included, emissions

would be calculated as followed:

Traffic Density

Santa Fe Traffic Density in Illinois:

(Furnished by Santa Fe without 

locomotives) = .........................7,329,000,000 GTM

Fuel Consumption Index

Santa Fe System 

Fuel Consumption: 

Schedule 750: line 1 = ..................304,370,694 gal

Santa Fe System 

Gross Ton Miles (w/o locomotives): 

Schedule 755: line 104 - line 98

(186,661,355,000 - 24,631,118,000) = 162,030,237,000 GTM

Santa Fe Fuel Consumption 

Index (w/o locomotives)

(162,030,118,000 / 304,370,694) = ...........532 GTM/gal

Fuel Consumption 

Fuel Consumption for

Santa Fe in Illinois

(7,329,000,000 / 532) = ..................13,776,316 gal
218

Traffic Density With Locomotives

If the traffic density data for Illinois are supplied with locomotive weight included, emissions

would be calculated as follows:

Traffic Density

Santa Fe Traffic Density in Illinois:

(Furnished by Santa Fe with 

locomotives) = .........................8,445,000,000 GTM

Fuel Consumption Index

Santa Fe System 

Fuel Consumption: 

Schedule 750: line 1 = ..................304,370,694 gal

Santa Fe System 

Gross Ton Miles (with locomotives): 

Schedule 755: line 104 = ............ 186,661,355,000 GTM

Santa Fe Fuel Consumption 

Index (with locomotives)

(186,661,355,000 / 304,370,694) = ...........613 GTM/gal

Fuel Consumption 

Fuel Consumption for

Santa Fe in Illinois

(8,445,000,000 / 613) = ...................13,776,508 gal

Emission Factors

The emission factors for line haul locomotives are located in Table 6-1 above. Emissions can

now be calculated as follows:

Emissions (Tons) = Emission Factor (lbs/gal) x Fuel Consumption (gal)

 2,000

 Example for HC: (0.0211 X 13,776,508)/2,000 = 150.16 Tons
219

Appendix 6-4

Conversions from Locomotive Model to Engine Type

 EMD 

Locomotive Engine 

 Model HP Type 

E8A 2250 12-567BC

F40C 3200 16-645E3

F40PH 3000 16-645E3B

F40PH-2 3200 16-645E3B

F45 3600 20-645E3

FP45 3600 20-645E3

GP7 1500 12-567BC

GP9 1750 16-567C

G18U 1100 8-645E

G18W 1100 8-645E

G18A1A 1100 8-645E

GP15-1 1500 12-645E

GP15T 1650 8-645E3C

GP18 1800 16-567C

GP20 2000 16-567C

GP28 1800 16-567C

GP30 2250 12-645E3

GP35 2500 12-645E3

GP38 2000 16-645E

GP38-2 2000 16-645E

 GP38-2P 2000 16-645E

GP38-AC 2000 16-645E

GP39-2 2300 12-645E3B

GP40 3000 16-645E3

GP40-2 3000 16-645E3B

GP40-P 3000 16-645E3B

GP40P-2 3000 16-645E3B

GP40X 3500 16-645F3

GP49 2850 12-645F3B

GP50 3500 16-645F3

GP59 3200 12-710G3/G3A+

GP60 3600 16-710G3/G3A*

GP60M 3800 16-710G3A

 +For locomotives built after 4/91, use the 12-710G3A

 * For locomotives built after 4/91, use the 16-710G3A

 EMD 
220

Locomotive Engine

 Model HP Type 

MP15AC 1500 12-645E

MP15 1500 12-645E

MP15T 1650 8-645E3C

SD9 1750 16-567C

SD35 2500 12-645E3 

SD38 2000 16-645E

SD38-2 2000 16-645E

SD38AC 2000 16-645E

SD39 2500 12-645E3

SD40 3000 16-645E3

SD40-2 3000 16-645E3

SD40A 3000 16-645E3

SD40T2 3000 16-645E3

SD40X 3500 16-645F3

SD45 3600 20-645E3

SD45-2 3600 20-645E3

SD50 3500 16-645F3B

SD60 3800 16-710G3

SD60M 3800 16-710G3/G3A*

SDF40-2 3000 16-645E3

SDF45 3600 20-645E3

SDP45 3600 20-645E3

SDL39 2300 16-645E3

SDP40 3000 16-645E3

SDP40FM 3000 16-645E3

SW7 1200 12-567BC

SW900 900 8-645E

SW1000 1000 8-6453

SW1001 1000 8-645E

SW1200 1200 12-567BC

SW1500 1500 12-645E

 * For locomotives built after 4/91, use the 16-710G3A
221

 GE 

Locomotive Engine

 Model HP Type 

B23-7 2250 12-2500

B30-7 3000 16-3000 

B30-7A 3000 16-3000

B30-7AB 3000 16-3000

B36-7 3600 16-3600

B36-8 3600 16-3600

B39-8 4100 16-4100

B40-8 4100 16-4100

B40-8W 4100 16-4100

C30-7 3000 16-3000

C30-7A 3000 16-3000

C32-8 3000 16-3000

C36-7 3600 16-3600

C39-8 4100 16-4100

DASH 8-32B 2500 12-2500

DASH 8-40C 4100 16-4100

U23B 2500 12-2500

U23C 2500 12-2500

U25C 2500 12-2500

U25C 2500 12-2500

U28B 3000 12-3000

U28C 3000 12-3000

U30B 3000 12-3000

U30C 3000 12-3000

U33B 3000 16-3000

U33C 3000 16-3000

U34CG 3600 16-3600

U36B 3600 16-3600

U36C 3600 16-3600

U36CG 3600 16-3600 
222

Appendix 6-5

National Fleet Percentages

Category Engine Type Number Percentage of Total 

Line Haul 16-645E3 1562 16.1 

16-645E3B 2693 27.7

16-645F3 232 2.4

16-645F3B 400 4.1

20-645E3 723 7.4

16-710G3 537 5.5

16-710G3A 250 2.6

12-2500 843 8.7

12-3000 145 1.5

12-3300 0 0.0

16-3000 801 8.3

16-3600 451 4.6

16-4100 1029 10.6

 12-645F3B 6 0.1

12-710G3 2 0.0

12-710G3A 34 0.4

Yard 12-567BC 131 2.9

12-645E 1216 26.7

16-567C 1279 28.1

16-645E 1763 38.8

12-645E3B 125 2.7

12-645E3 32 0.7

8-645E 1 0.0

8-645E3C 42 0.8
223

Appendix 6-6

Emission Factors For Locomotives 

 Emission Factors (lbs/gal) 

Eng. Type HP Operation HC CO NOx PM 

EMD 8-645E 1100 Yard 0.0525 0.1571 0.4984 0.0162

EMD 8-645E3C 1650 Yard 0.0223 0.0477 0.7232 0.0121

EMD 12-567BC 1200 Yard 0.2209 0.1608 0.3936 0.0165 

 

EMD 12-645E 1500 Yard 0.0321 0.0752 0.5141 0.0138

EMD 12-645F3B 2950 Line Haul 0.0155 0.0490 0.4962 0.0104

EMD 12-645E3 2300 Line Haul 0.0192 0.0939 0.5156 0.0113 

 Yard 0.0277 0.1130 0.5803 0.0135 

EMD 12-645E3B 2500 Line Haul 0.0196 0.0878 0.5475 0.0115

Yard 0.0266 0.0761 0.5107 0.0133

EMD 12-710G3 3200 Line Haul 0.0155 0.0373 0.4306 0.0103

EMD 12-710G3A 3200 Line Haul 0.0070 0.0447 0.4568 0.0108 

EMD 16-567C 1750 Line Haul 0.0284 0.0857 0.5109 0.0114 

Yard 0.0435 0.0784 0.4452 0.0136 

EMD 16-645E 2000 Line Haul 0.0192 0.0604 0.5443 0.0114

Yard 0.0308 0.0747 0.5243 0.0136

EMD 16-645E3 3000 Line Haul 0.0198 0.0721 0.4744 0.0114

EMD 16-645E3B 3000 Line Haul 0.0160 0.0460 0.5236 0.0071

EMD 16-645F3 3500 Line Haul 0.0178 0.0529 0.6060 0.0116 

EMD 16-645F3B 3600 Line Haul 0.0153 0.0295 0.6687 0.0111

EMD 16-710G3 3600 Line Haul 0.0170 0.0244 0.4986 0.0111 

EMD 16-710G3A 3600 Line Haul 0.0091 0.0935 0.4862 0.0110

EMD 20-645E3 3800 Line Haul 0.0200 0.0528 0.4590 0.0113 

GE 12-2500 2500 Line Haul 0.0229 0.0970 0.4271 0.0117 

Emission Factors For Locomotives
224

 Emission Factors (lbs/gal) 

Eng. Type HP Operation HC CO NOx PM 

GE 12-3000 3000 Line Haul 0.0229 0.0852 0.4572 0.0115 

GE 16-3000 3000 Line Haul 0.0354 0.1025 0.4471 0.0196

GE 12-3300 3300 Line Haul 0.0229 0.0852 0.4572 0.0115

GE 16-3600 3600 Line Haul 0.0311 0.0780 0.4663 0.0173

GE 16-4100 4100 Line Haul 0.0302 0.0659 0.4851 0.0171
225

Appendix 6-7

Sample Roster Tailoring For Line Haul Locomotives*

Step 1 - Identify the locomotives in the area

Assume that there are ten line haul locomotives which operate within the inventory area: 5 -

EMD GP59's and 5 - GE C36-7's

Step 2 - Determine the data base equivalent

According to the list in Appendix 6-5, the two locomotives convert as follows:

Locomotive Data Base Equivalent

 5 - GP59 5 - 16-710G3 

 5 - C36-7 5 - 16-3600

Step 3 - Calculate the tailored roster

The new tailored roster for line haul locomotives looks as follows:

Line Haul

Engine Type Population Fraction of Total

16-710G3 5 0.50

16-3600 5 0.50

Total 10 1.00

Step 4 - Locomotive emissions factors

Select the appropriate emission factors for each engine type from Appendix 6-6. The emission

factors for each locomotive in the tailored roster are:

EMD 16-710G3 GE 16-3600

Pollutant lbs/gal Pollutant lbs/gal

HC 0.0161 HC 0.0274

CO 0.0233 CO 0.0624

NOx 0.4805 NOx 0.4655

PM 0.0107 PM 0.0157

SO2 0.0360 SO2 0.0360

*Note: The same procedures would be followed for yard locomotives.

Step 5 - Calculate new emission factors
226

The new fleet average emission factors are calculated by multiplying the engine roster percentage

by the engine emission factor and then summing the weighted emission factors for all engines. For

this example, the result is as follows:

HC emission factor: [(0.50 x 0.0161) + (0.50 x 0.0274)] = 0.0218
227

Appendix 6-8

Duty Cycles

Line haul duty cycle data were taken from the Average California Profile as determined in the BoozAllen & Hamilton, Inc. report entitled Locomotive Emission Study, 1991. It represents the most

extensive analysis of time in notch profiles for line haul locomotives operating in both mountainous

and flat terrain and, in terms of actual testing done, it is without equal. It is also reasonably

consistent with the existing EMD and GE line haul duty cycles. EPA believes that the Average

California Profile adequately represents average line haul locomotive travel throughout the nation.

Line Haul

 Notch Percent of Time In Notch Hrs Per Day In Notch

8 11 2.64

7 3 0.72

6 4 0.96

5 4 0.96

4 5 1.20

3 4 0.96

2 4 0.96

1 4 0.96

 Idle 49 11.76

 Dyn Brk 12 2.88

Yard

Yard duty cycle data were taken from the Report to Congress. This duty cycle was the same as the

EMD duty cycle and is consistent with most other recommended duty cycles.

 Notch Percent of Time In Notch Hrs Per Day In Notch

8 1 0.24

7 0.5 0.12

6 0.5 0.12

5 1 0.24

4 2 0.48

3 4 0.96

2 7 1.68

1 7 1.68

 Idle 77 18.48