United States Air and Radiation EPA420-R-92-009
Environmental Protection December 1992
Agency
&EPA Procedures for Emission
Inventory Preparation
Volume IV: Mobile Sources
Printed on Recycled Paper
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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
NOTK 7 -;
This technical report Joes 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 U'A decision, position, or regulatory action.
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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
Chapter 2
Chapter 3
Chapter 4
Chapter 5
Chapter 6
Natalie Dobie
Natalie Dobie
Terry Newell
Natalie Dobie
Greg Janssen
Joe Somers
Richard Wilcox
Peter Okurowski
Introduction
Overview
MOBILE4. 1
Vehicle Miles Traveled
Nonroad Sources
Aircraft
Locomotives
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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 2771 1.
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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-450/4-91-011. 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 O .JCO 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. EPA-
450/4-91-022. U.S. Environmental Protection Agency. Office of Air Quality
Planning and Standards. Research Triangle Park. North Carolina. September
1991
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SIP Air Emission Inventory Management Svstcm (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 Svstcm (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 Svstcm (SIMS)
Version 2.0. EPA-450/4-90-019b. U.S. Environmental Protection Agency.
Research Triangle Park. North Carolina. September 1990.
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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
3.2.1.1 Vehicle Fleet Activity
3.2.1.2 Emission Factors
3.2.1.3 Fleet Characteristics
3.2.1.4 Fuel Characteristics
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
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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
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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
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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 1 15
Appendix 4-A 117
Appendix 4-B 124
Appendix 4-C 132
Appendix 4-D 135
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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
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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 SO^ 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
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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
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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).
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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.
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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.
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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 (03) 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
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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 MOB1LE5 for ozone non-attainment areas.1 In addition, if the base
year inventory was originally developed using MOB1LE4.1, it should be recalculated using
MOB1LE5 and resubmitted.2
For CO non-attainment areas, the base year and projection year inventories may be
developed using either MOB1LE4.1 orMOBILE5. Submissions after the November 15, 1992
submission should use MOB1LE5. Such submissions may be voluntary or due to bump up or
other provisions of the Clean Air Act.
The release of MOB1LE5 will be accompanied by a supplement to this document
explaining the differences between MOB1LE4.1 and MOB1LE5 and the additional inputs
contained in MOB1LE5.
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 MOB1LE4.1.
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.
1 The SIP Attainment/Reasonable Further Progress and projection year inventories arc due on cither 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.
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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 non-
moving 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
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.
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differences between the volatility of local fuels and Indolene can influence the level of both
evaporative and tailpipe pollutants, MOB1LE4.1 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 11 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 MOB1LE4.1 Input Requirements
MOB1LE4.1, 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 MOB1LE4.1 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
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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 68"F to 86"F;
• 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 MOB1LE4.1 User's Guide. A
condensation of that material is included in Section 3.3 of this report.
MOB1LE4.1 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
MOB1LE4.1 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.) MOB1LE4.1 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. MOB1LE4.1 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.
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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 (75"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.
4 The speed correction factors in MOBILE5 may be significantly revised at speeds above 48 mph.
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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;
• NO.\ 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.
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.
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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
MOB1LE4.1.
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 11" (at the pump) and "onboard" (in the vehicle) vapor recovery systems.
MOB1LE4.1 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 1/M programs as a means of further reducing
mobile source air pollution. MOB1LE4.1 can model the impact of an operating 1/M program on
the calculated emission factors. There is no average national 1/M program; local inputs must be
supplied. Details are given in Section 3.3.6.2 of this document and in the MOB1LE4.1 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. MOB1LE4.1 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 MOB1LE4.1 User's Guide.
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3.3 GUIDANCE ON SELECTING M0BILE4.1 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.s
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.
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 arc 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.
s While future year inventories arc discussed in this document. MOBILE4.1 should not be used for projecting
VOC or NOx emissions beyond January 1. 1994. since it docs 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.
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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,"1 or to develop CO emission
factors for any calendar year through 2020.
3.3.1.1 Region
Description
MOB1LE4.1 provides two options for region: low-altitude and high-altitude. Low-
altitude 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. MOB1LE4.1, like MOB1LE4, 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 MOB1LE4.
Guidance
For the majority of MOB1LE4.1 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."
3.3.1.2 Calendar Year
Description
The value used for calendar year in MOB1LE4.1 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. MOB1LE4.1 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 MOB1LE4.
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 Retaliations.
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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.
12 For example, if most cxcecdances 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
scrappagc 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.
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M0BILE4.1 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 MOB1LE4.1,17
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 MOB1LE4.
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 MOB1LE2 Variables.1" 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 MOB1LE4.1 vehicle classes using the national
default mix within each group provided by MOB1LE4.1.
3.3.2.2 Annual Mileage Accumulation Rates and Registration Distributions by Vehicle Type
and Age
Description
MOB1LE4. l'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
15 Total HDDV registrations and annual mileage accumulations arc also distributed within the model by truck
weight class.
16 Highway functional systems arc commonly designated as the interstate system, other freeways and
expressways, other principal artcrials. minor artcrials. and collectors.
17 O/onc 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.
ls "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).
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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 MOB1LE4.1 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 MOB1LE4.1. 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
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 arc registered but do not
accumulate mileage. A warning will also be issued if there arc 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 arc used, they normally should not change from one evaluation year
to the next.
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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 MOB1LE4.1 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 MOB1LE2 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). MOB1LE4 was the first version of the emission factor model to
account for these emissions. In MOB1LE4.1 estimates of running loss emissions have been
extensively revised.
22 Marginal, sub-marginal, and transitional non-attainment areas may use the MOBILE4.1 distributions for all
vehicle types, if local distributions arc 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 scrappagc 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).
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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 MOB1LE4, 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 MOB1LE4.1 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
• 3 1 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 MOB1LE4.1 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 MOB1LE4.1 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
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).
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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.2S
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 MOB1LE4 contained
forecasts of increasing diesel sales for both LDVs and LDTs through the early 1990s,
MOB1LE4.1 assumes a more limited and slower increase from the current, very low diesel sales
rates. MOB1LE4.1 assumes that future LDV diesel sales never exceed 0.3% and that future LDT
sales never exceed 2.15%.
MOB1LE4.1, 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 MOB1LE4.1
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
2S 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 arc treated
separately within the MOBILE models.
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aues 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 MOB1LE4.1 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 MOB1LE4.1, 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
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 docs 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.
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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, MOB1LE4.1 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 45(>F and 75°F 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 MOB1LE4.1 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
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 arc 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 arc suitable for determining average RVP for inventory purposes.
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Procedure for Determining RVP Using the MVMA Survey
Obtain the appropriate edition of the MVMA National Gasoline Survey, published semi-
annually37 by the Motor Vehicle Manufacturers' Association. Ordering and price information is
available from:
Motor Vehicle Manufacturers' Association
300 New Center Building
Detroit, Ml 48202
Phone (313) 872-43 11
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:
37 The data reflected in MVMA National Gasoline Survey arc generally collected as of January 15th and July
15th.
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 w ith the largest population w ithin the inventory area and that w as subject to the
same EPA. state, or ASTM volatility limit at the time. If fuel distribution patterns arc 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 arc 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
arc 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 arc replacing those for regular leaded.
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• 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 MOB1LE4.1.
Procedure for Determination of RVP Using the N1PER Survey
Obtain the appropriate edition of the report Motor Gasolines, published semi-annually by
N1PER. Samples for the summer survey are taken in June, July, and August. Samples for the
winter survey are taken in December, January, and February.
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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 non-
attainment season. Use the winter NIPER survey to estimate CO emissions during the CO non-
attainment 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 MOB1LE4.1.
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
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.
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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
MOB1LE4.1 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
42 The non-compliancc margin is always positive: the compliance safety margin is always negative.
43 "Period 1" RVP was called base or prc-control RVP in MOBILE4; "period 2" RVP was called in-usc RVP in
MOBILE4.
44 MOBILE4.1 assumes this change to occur as of January 1 of the specified calendar year.
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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 1
volatility control limits are superseded by the Phase 11 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
MOB1LE4; 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 MOB1LE4.1,46 47 4S
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,
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.
4S MOBILE4.1 docs not model effects of RVP on emissions at temperatures of less than 45° F (7° C). nor docs 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.
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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
49 Alternatively, the default margin of 0.3 psi may be assumed.
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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:
50 Reductions in exhaust CO emissions arc 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 arc 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 arc assumed to have the same RVP as gasoline, indicated by the regular RVP value
input.
52 If. together, cthanol 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 cthanol blends arc readily available by state.
53 There have been no recent significant sales of other oxygenated blend types (e.g.. gasolinc/mcthanol).
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• 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.
MOB1LE4.1 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.
54 The speed correction factors in MOBILE4.1 arc 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 arc a non-linear function of speed, with significant curvature at low and high speeds, total daily area-
wide emissions arc to some degree incorrectly estimated if VMT "events" occurring at significantly different speeds arc
averaged together.
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Travel Demand Network Approach
The recommended approach to estimating speeds is to post-process the output from a local travel
demand network model.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/'"
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/'1 As such, this method is not as simple as using the direct traffic assignment output
without modification/'2
A second approach to estimating speeds using travel demand network models is to use the output
from traffic assignment directly/'3 If the network model assigns traffic to links on the basis
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 arc still required.
59 Once link-by-link speeds arc determined from speed formulas, the results may be aggregated into functional classes.
60 Both documents were prepared for EPA by Cambridge Systcmatics. 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 arc too high to match actual conditions: in some cities, they arc 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 Hialnvav Capacity Manual, the assignment-
predicted 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.
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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 MOB1LE4.1 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.6S
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
MOB1LE4.1 emission factors are calculated for each
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 arc 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 arc calculated for the midpoint
of each speed range and multiplied by the associated VMT.
6S 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.
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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 MOB1LE4.1 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 MOB1LE4.1. 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 MOB1LE4.1 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.
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 MOB1LE4.1. 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 inventor*' 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 inventor purposes. See section 3.3.5.2.
76 SOURCE: Federal Highway Administration. Highway Performance Monitoring System. Impact Analysis for 1989
Base Year.
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Table 3-1
Geographic
Area
Roadway
Functional Classification
Pickups
Autos, Vans
Trucks
All
Rural
Interstates
Other principal arterials
57.3
45.4
39.9
35.1
30.5
43.6
36.0
Minor arterials
Major collectors
Minor collectors
29.8
24.4
Urban
Interstates
Other freeways and expressways
Other principal arterials
Minor arterials
Collectors
46.3
43.3
39.0
36.5
16.0
19.6
16.4
18.9
19.6
19.6
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
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 75°F
(24°C). MOB1LE4.1 uses temperature correction factors to correct the emission factors for other
temperatures.
MOB1LE4.1 provides temperature correction factors for temperatures in the range of 0°F
(-18°C) to 110°F (43°C). If a temperature below 0°F is entered, a warning message is issued, and
0°F is used in the calculations. Similarly, if a temperature above 110°F is entered, a warning
message is also issued, and 110°F 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.
77 The maximum temperature must not be less than the minimum temperature.
Description
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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,7S 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 MOB1LE4.1 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/" 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 MOB1LE4.1 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 75°F (24°C), MOB1LE4.1 also adjusts these rates for other temperatures.
Using the minimum and maximum daily temperatures and a representative profile of temperature
versus time of day, MOB1LE4.1 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.S1
Hot soak emissions at FTP conditions are based on a temperature of 82°F (28°C). Again
using the minimum and maximum temperatures, MOB1LE4.1 calculates a temperature by which
to adjust hot soak emissions.
7X
Logically, the single temperature used to represent a typical day must be between a typical day's minimum and
maximum temperatures.
79 Diurnal emissions arc most frequently measured for a temperature range of 68-86°F (2()-3()"C). 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.
xo
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 5°F)
typical of a single hour.
X1
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 liaving 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 arc 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 arc the desired result.
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Resting loss and running loss VOC emissions are also dependent on temperature. As in
the cases of exhaust and hot soak emissions, MOB1LE4.1 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 MOB1LE4.
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.*2 x3
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.S4
s2 If hourly diurnal emissions arc 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 60-84°F within the 7 a.m. to 5 p.m. ten-
hour period, and if during the 1-2 p.m hour temperature increases from 76-80°F. then, assuming the total diurnal
emission factor is 3 g/\ chicle, the emission factor for the 1-2 p.m. hour is 0.5 g/\ chicle. 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 Incrcasc/(Ma.\imum Daily Temperature - Minimum
Dailv Temperature) • Total Diurnal Emission Factor
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:
Guidance
10 8
E Ambient Temperature,H„„sl
Davs=l Hours=l
X4
The temperatures used in the 1990 inventory must also be used for all projection inventories.
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Procedure
Determine the consecutive three-month period with the highest frequency of NAAQS
exceedance days occurring in the inventory area.*5 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 concentrations*6 that occurred in the inventory area during those
nine months and the dates of those concentrations."
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 Climatolouical 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.
Consider the three-year period as a whole when making this determination.
Sf> The 10 highest concentrations need not all be cxcccdcnccs.
X7
There arc 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.
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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 Operati ng M odes
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:
Bau 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.
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M0BILE4.1 uses three inputs to indicate vehicle operating mode.™ These inputs
represent VMT; that is, the percentage ofVMT (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 MOB1LE4.
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.*9
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
The values corresponding to the FTP cycle arc: PCCN 20.6 %
PCHC 27.3 %
PCCC 20.6%
S9 Catalysts begin to operate at full efficiency once they reach about 60()"F (316"C). 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 arc based on the concepts of trip-start emissions and
running emissions, rather than the method described above. In this alternative approach, trip-start emissions arc
assumed to be instantaneous and arc calculated as the difference between MOBILE4.1 total "start" emissions and
total "stabilized" emissions. Total start emissions per trip arc the product of the 100% cold- (or hot-) start emission
factor in grams per mile and the 3.59-milc distance attributed to the first 505 seconds of the FTP driving cycle.
Total stabilized emissions arc the product of the 100% stabilized emission factor in grams per mile and the same
3.59-milc distance and same speed as that used to estimate start emissions. Start emissions arc calculated as the
grams per trip event times trip productions, and arc typically located at the ccntroids.
Total stabilized emissions arc 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 arc simply the "hot soak" emissions expressed in grams per trip event times trip attractions.
Trip end emissions arc also typically located at ccntroids.
Daily diurnal emissions arc calculated as the emissions in grams per vehicle times vehicles present and must
39
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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
MOB1LE4.1 can provide four additional corrections to the exhaust emission factors for
LDGVs, LDGTls, and LDGT2s. These corrections are used to represent unique conditions not
typically assumed in MOB1LE4.1 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, LDGTls, 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
also be assigned to specific hours and locations. Methods for this assignment van'.
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 thin
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 arc 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
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extra load usage fractions (for LDGVs, LDGTls, LDGT2s), three trailer towing fractions (for
LDGVs, LDGTls, 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, LDGTls, 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, LDGT1 s, and LDGT2s. In the ten-input option, three values
are entered, and one each is applied to LDGVs, LDGTls, 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
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
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Dry and Wet Bulb Temperatures
M0BILE4.1 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 0°F (-18°C) to 110°F (43°C). 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 MOB1LE4.
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 MOB1LE4.1 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.
94
These values (in °F) 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.
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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.9*
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.
97 VMT should also be disaggregated so that the set of operating conditions under which the vehicles arc
generating the VMT is fairly homogeneous.
9X
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
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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."
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
99 There arc 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 arc often used for this purpose.
102 One alternative to using M0BILE4.1 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. M0BILE4.1 makes use of improved predictive equations to calculate refueling emission factors, and
these have not yet been incorporated into AP-42.
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be refueled at service stations (or other fuel dispensing locations, such as private refueling
depots) that will be exempted from Stage 11 requirements.
EPA has estimated the in-use efficiency of Stage 11 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 11 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 semi-
annual inspection frequency, results in 83% in-use efficiency for a Stage 11 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 MOB1LE4.1 inputs when
modeling Stage 11 controls as part of the 1990 SIP submittal.
Spillage
Emissions from fuel spillage also can be modeled using MOB1LE4.1. The "baseline"
spillage factor (assuming no controls) is 0.3 1 g/gal. of dispensed fuel. If no controls are
assumed, this factor is added to MOB1LE4. l's calculated displacement loss, which, in turn, is
based on ambient temperature and RVP. If Stage 11 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 0.3 1 g/gal.
To model the effects of Stage 11 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 (1/M) programs
as a means of reducing mobile source air pollution. MOB1LE4.1 can model the effect of an
operating 1/M program, based on the specification of certain parameters that describe the
program. Standard low-altitude area emission reduction credits are contained within the
MOB1LE4.1 code itself, while standard high-altitude area emission credits are included as a
separate file on the MOB1LE4.1 diskettes and tapes.103
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 arc inappropriate should contact the Office of Mobile Sources
(Air Quality Analysis Branch. 313/668-4325) to obtain the required matrices.
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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;
• 1M240 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 parameters"14 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
104 MOBILE4.1 will run correctly if an I/M program is specified and only the first ten parameters from the above
list arc 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).
"b There arc many details, such as instrument specifications, that arc 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 liavc
further questions regarding program requirements.
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.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
.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 1 st 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.
.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."1* 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%.
.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
106 Such tailpipe I/M and anti-tampering programs arc 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 arc sampled as the vehicle idles in
neutral gear, to more elaborate tests, such as the IM240. where the vehicle's emissions arc sampled during a
simulated drive using a chassis dynamometer.
1 OX
Emission cutpoints arc 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.
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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 MOB1LE4.1.
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
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 arc 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 arc generally very low.
112 MOBILE4.1 assumes that tampered or misfuclcd vehicles cannot receive waivers, and so docs not reduce the
ATP benefit based on the waiver rate.
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Guidance
For an historical inventory, the actual waiver rate must be determined and used as the
input to MOB1LE4.1. For future year inventories, the historical waiver rate should be used
unless a change will be made to the criteria for granting waivers."3
3.3.6.2.7 Compliance Rate
Compliance rate refers to the level of compliance with the inspection program."4 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
MOB1LE4.1 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:
113 If tighter criteria arc 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 arc 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.
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Table 3-2
Benefit Assumed for Enforcement Fraction
Non-
Non-Complier
Fraction
Fraction
ompliance 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."6 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."7
3.3.6.2.8 Inspection Frequency
MOB1LE4.1 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
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 ovcrcstiniation 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-iniplcnicntation.
if the actual compliance rate is substantially less than the rate assumed in inventory forecasts.
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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
MOB1LE4.1 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:us
• 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 light-
duty trucks."9 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.
2500/1 die 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.
us Those areas that do not use the same vehicle class designations in their vehicle registration data as arc used in
MOBILE4.1 must take carc 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 arc 1.2% CO and 220 ppm VOC.
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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.
1M240 Transient Test
The 1M240 transient test is a measurement of VOC and CO emission concentrations of a
vehicle operated over a range of speeds. The 1M240 was patterned after the Urban Dynamometer
Driving Schedule used to conduct the Federal Test Procedure (FTP). In order for MOB1LE4.1 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 MOB1LE4.1 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. MOB1LE4.1 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.
121 These arc provided on diskettes and tapes distributed with the model.
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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 MOB1LE4.1,122 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.
122 Examples of such programs arc 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 arc considered ccntrali/cd even if they arc dcccntrali/cd in the sense of multiple
businesses.
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Decentralized programs have been found to be less effective in reducing emissions than
are centralized programs. As a result, MOB1LE4.1 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.
MOB1LE4.1 assumes that the 1/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.12s
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 1/M program should contact EPA.130
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 arc 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.
12s For decentralized I/M programs, the waiver rate input of the model is disabled so that even if waiver rates arc
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 arc 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.
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3.3.6.2.15 Tech I-II and Tech IV+
The calculation of I/M benefits for MOB1LE4.1 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
I Pre-1975 Pre-1975
U 1975-80 1975-83
IV+ 1981+ 1984+
3.3.6.3 Anti-Tamperinu 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:
LDGT2
Pre-1979
1979-83
1984+
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.
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• 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 MOB1LE4.
The following sections discuss the terminology used to describe anti-tampering program
inspections for purposes of modeling the emission benefits of such programs using MOB1LE4.1.
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 non-
functional 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 anti-
tampering program, garners no emissions benefits, and should not be modeled in MOB1LE4.1.
The following sections discuss the terminology used to describe anti-tampering programs
for purposes of modeling the emission benefits of such programs using MOB1LE4.1. In general,
MOB1LE4.1 assumes that the anti-tampering program is mandatory, periodic, and covers a well-
defined group of vehicles.133
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 arc many details (such as replacement catalyst specifications) that arc 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 arc questions regarding the requirements of ATP inspections.
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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 anti-
tampering 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.
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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 MOB1LE4.1 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 MOB1LE4.1 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
134 MOBILE4.1 assumes that inspectors arc not allowed to skip this inspection because the fuel inlet is concealed
by a locked door.
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must be replaced to result in any substantial emission reduction. If the program regulators do not
require catalyst replacement, then the input to MOB1LE4.1 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 MOB1LE4.1 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 MOB1LE4.1 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.13s Purge and pressure testing is,
however, assumed to detect all evaporative control system tampering.
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.
1 IX
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
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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
MOB1LE4.1 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.
MOB1LE4.1 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 MOB1LE4.1 be used.143
139 MOBILE4.1 assumes that inspectors arc not allowed to skip this inspection even if the fuel inlet is concealed
by a locked door.
140 The four vehicle types arc LDGV. LDGT1. LDGT2. and HDGV.
141 The eight tampering types arc air pump disablement, catalyst removal, overall misfucling. fuel inlet rcstrictor
disablement, exhaust gas recirculation system disablement, evaporative control system disablement, positive
crankcase ventilation system disablement, and missing gas caps.
142 Tampering offsets arc the increases in emissions that result from a given type of tampering.
143 If EPA or local authorities have performed a statistically valid anti-tampcring 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.
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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-l/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 anti-
tampering program, contact OMS's Emission Planning and Strategies Division, 3 13/668-4367.
144 The three equations arc used to model pre-1981 model year vehicles. 1981-83 model year vehicles, and 1981
and later model year vehicles.
145 These rate equations arc 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 + 5*DR1 + 8*DR2).
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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.
14X
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 rccogni/cs 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 arc not fully consistent with the data submitted to HPMS. EPA Regional
Offices arc advised not to agree that the HPMS data arc less reliable than VMT estimates made by another statc-
rcqucstcd method without consulting with divisional or regional FHWA officials who have direct knowledge of the
HPMS data associated with the non-attainment area.
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Consistency between HPMS VMT149 and SIP VMT1MI 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
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 arc adjusted forday-of-wcck 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 arc 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.
j52 Exceptions to these general guidelines arc described in sections 3.4.1.3 and 3.4.2.4.
U.S.D.O.T.Codc Title
M 5600.1A Highway Performance Monitoring System (HPMS) Field Manual
M 5600.1 A. Chg. 1 Highway Performance Monitoring System (HPMS) Field Manual Updates
M 5600.1 A. Chg. 2
(Deleted by Chg. 3) Highway Performance Monitoring System (HPMS) Field Manual
M 5600.1 A. 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
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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
(NH1PS). 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.
155 Expansion factors for different FAU As may be different, even within the same state.
156 Vehicle counts taken by axle counting equipment require adjustment by axle correction factors,
adjustment factor is the ratio of vehicles to axles as determined by a vehicle classification count.
64
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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.
157 There arc 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 /one to another. See sections 3.4.2.4.1 and 3.4.2.4.2. Third, this
rule docs not apply to any areas with weak HPMS data that have been set aside in favor of a competing alternative.
65
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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 non-
attainment area (by HPMS functional system) on the basis of the number of roadway miles
according to equation (3-7).l5S
VMT(sn>. r. v) = (Roadway Miles(SI1,, v) / Roadway Miles(I.AlA , v)) • VMT(I,Al A , 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(SII,0 = EVMT(SI,i:,
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.
l5S 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 infcasiblc. If a state elects this option, it should use equation (3-7a).
VMTlS|Pl = (Roadway MilcslS|Pl / Roadway Miles,, Al Al) • VMT;(3-7a)
159 The functional systems listed arc for an HPMS Urbanized Area. Rural areas classify highway facilities as
intcrstatcs. 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.
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However, the recommended method of estimating VMT in a completely rural non-
attainment 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,,,. v) = (Roadway Miles(SII,, v) / Roadway Miles(IIPMS, v)) • VMT(IIPMS, v) (3-8)
where HPMS = HPMS Statewide Rural Area
SIP = SIP Non-Attainment Area
Functional System
Volume Group
VMT (SII, 0 = EvMT(SII,i;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
161 Within HPMS. all rural areas within the state arc 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. de-
based on equation 3-8.
163 Other alternative methods of estimating VMT in this type of non-attainment area arc discussed in section
3.4.1.6.
164 If all of the FAUA is inside of the non-attainment area, equation 3-7 docs not apply, since all FAUA VMT is
included as part of the total non-attainment area VMT estimate.
67
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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.16S The recommended method of
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-wcck variations in VMT.
16S The Urban Airshed model and its associate emissions preprocessor is an example of such a model. EPA also
maintains the Regional Oxidant Model, a mcsoscalc photochemical model providing coverage of the Northeastern
United States.
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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
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 arc not appropriate.
172 HPMS data submitted to FHWA on orbcforc September 15th of the year following the year of record arc
included in Hiahwav Statistics. FHWA therefore considers the data in Hiahwav Statistics preliminary and subject
to revision within the following twelve months.
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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, Fr, 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(SII,0 = F, • VMT(Statc 0 (3-9)
where VMT(SI1, 0 = estimated annual areawide VMT;
F, = 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(Statc 0 = 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(Statc0 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(Statc 0. Four methods for
apportioning statewide VMT to county or other subareas are presented below.
173 The recommended method for apportioning VMT in a completely rural non-attainment area is by roadway
miles.
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ANNUAL VEHICLE-MILES OF TRAVEL • 1990 '
BT STATE AND FUNCTIONAL SYSTEM
Qt-MCh ut- HlOHKRT IR9LE VH-2
INFORMATION BANRDEHENT tHltl IUNSI SEPTEMBER 1991
RURAL
URBAN
TOTAL
SlflfE
iHltRflfttlfc
OTHER
PHINCIPAL
AATERlAl
ING*
AKTEAJRL
MAJOR
COLLECTOR
HI NOR
COLLECTOR
LOCAL
TOTAL
JUFftSIAIF
01
FREEWAYS
flNO
txm&Mflra
OTHER
PftlNHPAl
AHlfHim
1IN0R
C01 LFCTO#
iocm
70TA1
DLRBflHA
fkfl6«A
RftlZOKR
RRHRN5A6
4.444
690
5.392
2.021
4.599
17
1.692
3.0*7
3.943
476
2.165
2.710
4.712
492
3.342
3.467
1.162
149
661
461
3.736
458
1.699
1.126
22.586
2.276
14.771
13.414
3.65!
419
2.742
1.601
337
668
673
(,. /OH
656
7.746
, 2.451
i. 527
156
3.598
1.622
32.989
2.236
2.671
499
1.950
147
1.627
b03
4.580
326
4.104
647
19.762
1.703
20.665
7 ,697
42.347
3.979
35.456
21.011
CAl irORNlfl
COLORADO
C0NWCT1CUT
OELftMflfiE
14,73?
3.496
1 .418
13.030
2.466
1.130
1.114
9.612
1.690
1.143
696
11.172
2.425
1.476
647
3.380
1.170
467
76
2.383
633
945
487
b4.9Z3
11.709
6 .097
2.924
6| .287
3.472
6.396
926
39.668
1 .633
2.418
9
63.989
6. J18
3.839
1.260
11.645
985
2.474
339
14.247
1.625
1.706
569
204.003
15.469
19.706
3.624
258,926
27.178
26.303
6.548
oi6i. or COL.
HClRlOfl
CCQROIR
HRKRII
8.907
0.809
102
S.h77
5.120
96
b .070
7.128
1.214
3.048
6.224
613
! .4fiy
1 .975
132
3.144
4.417
bbJ
J1 .'JbB
33.661
2.810
464
10.39!
9.812
1.401
443
4.143
1.691
738
1 .092
19.646
8.733
885
731
M.30G
7.403
641
331
9.088
3.675
4
346
20 .bbb
7.7C1
1 .Ob?
3.407
jb.uvs
39.0G5
5.256
3.407
109.997
72.746
8.066
IDAHO
ILLINOIS
INOSfiNA
tOUA
1 .404
7.460
6.640
3.270
1 .479
4.616
4.124
3.666
S81
6.230
5.590
2.9-79
1.162
B.04S
6,749
2.609
220
495
1.655
735
1 .905
3.325
2.433
1.470
6.831
26.139
29.391
14.627
618
13.712
S.279
1.343
940
923
863
16.380
6.942
3.in
652
12.381
6.239
1.666
317
6.677
1.696
667
356
1.105
4 .227
1.159
3.016
57.196
24 .306
8.166
9.849
63.334
53.697
22.993
KRNSRH
KiHrUCKT
LOUISIANA
HftlNE
2.472
4.567
4.377
) .708
3.625
3.653
2.291
1.644
t .022
2.247
2.3 67
i .662
2.689
6.040
5.298
2.098
20G
2.020
1.460
7t2
1.472
2.324
2.220
1.006
12,565
19.AVI
18.053
8.730
2.0GR
3.450
9.040
449
634
h4l
400
101
2.567
7.9SI
5.116
1 .136
2.435
3.B15
3.381
790
841
1 -iSR
1.249
420
1.721
1.735
6.429
?4S
10.284
t 3 .708
19.614
3.141
22.949
33.639
37.567
11.871
HHRTI RNO
ltR56RCHU5ETT3
niCHlORN
MINNESOTA
2.78b
2 .064
5 ,850
2.988
3.5U3
1.473
6.366
4 .837
3.136
1.966
6.060
3.401
2.309
1 .5BI
10.176
3.805
762
372
1 .624
1 .122
1.287
1.034
2.542
2.577
13.791
8.S09
32.536
18.730
8.204
10.347
11.114
4.780
2.819
4 .461
3.67*1
2.170
3.148
9.378
15.010
2.921
3.643
6.310
11.156
5.126
1 .985
2.877
3.748
2.667
1 .746
5.248
3.948
2.652
26.74S
37.6?1
4B.S53
20.216
40,535
46,130
91.091
36.946
MISSISSIPPI
MISSOURI
nnNiHNH
NF0RR5KA
2.666
S.fl?6
1 .BIK
1 .906
3.006
6.273
1 .482
2.249
3.246
3.660
1.094
1 .839
3.498
6.790
694
1.247
365
399
320
2 83
3.913
3.853
754
1.286
16,702
25.189
6,360
6.779
1.209
7.905
165
62 *
97
2.267
73
2.52]
6.423
734
1.968
1.528
l.UM
12.186
2.798
1.253
4.687
350
1.354
633
1.630
185
483
1.763
2.562
538
678
7.696
25.694
1.972
6.179
24.398
50.883
H.337
13.958
NEVADA
NEW HAMPSHIRE
HCH JERSEY
NfcH KtRiCO
1.563
1,359
1,912
3.466
626
1.079
2.266
1.634
590
1.465
2.209
1.193
882
1.269
2.514
1.153
206
414
665
266
30b
542
841
2.019
4.37?
6.148
10.517
9.725
9b6
673
8.337
1.068
740
462
5.322
35
1.469
962
6.662
949
535
330
3*024
477
S9G
255
10.665
1.0%
6.843
3.69C
48.406
6.423
10.255
9.944
56.923
16.149
NFW TORK
NORTH CAROLINA
NORTH DArOTR
OHIO
8.639
6.403
923
6 .044
4.666
5.751
792
4.992
1.020
3.327
958
6.716
E.473
11.168
607
6.717
S .310
3.713
165
2.091
3.415
3.358
883
6.060
31.423
33.776
4 .348
35.826
13.913
3.709
177
16.531
14.412
2.313
3.357
lb.876
9.036
538
10 >971
lh.7?H
5.G61
m
7 .029
S.A4H
1.194
177
4.136
h.?»?
7.117
209
10.260
7b.419
28.929
1.562
51.344
106.902
62*707
5.910
88.972
OKLAHOMA
ORCOON
PENNSYLVANIA
RHODE I SiRNO
3.630
3.811
7.967
206
2.944
3.314
7.496
265
3.054
2.081)
3.065
197
4.866
2.905
fi.115
1S1
164
626
2.764
65
1.646
1.591
6.474
72
16.495
14.639
38.871
976
3.221
2.73?
7.108
1.061
1.796
979
3.9U2
b2'J
3.463
3.272
16.955
1.603
3.990
2-80 J
6.267
1 .11.4
931
1.307
4.792
527
3.166
1.006
5.763
990
16.586
12.099
46.817
6.048
33.CJ01
26.736
65.708
7.024
SOUTH CAROLINA
SOUTH OMKOTA
TCNNLSSCE
U KH3
6,756
i .340
6.731
] 1.645
3.664
I .367
2.747
15 .556
4.669
927
6.200
6.355
6.093
966
3.206
14.661
662
16 /
V.M6
2.167
2.189
696
1.631
4.237
22.253
5.451
22.660
54.660
2.105
226
6.663
23.Uf*
376
20
14.266
4.520
646
B.864
20.167
2.920
261
3.676
16 .249
1.482
90
2.387
7.711
718
295
3.236
27.046
12.123
1 .538
23,830
107.&7Z
34.376
6.969
46.710
162.232
UTAH
VERMONT
VIROJMIA
WASHINGTON
7.300
996
7.061
3.636
949
66 2
5.271
9.156
871
as ?
6.566
2.166
8bB
1.070
6.408
5.091
?bl»
182
492
1.650
bus
479
3.239
1 .174
5.691
4.250
2H.059
18.764
'/.fiRG
230
8 .OS?
7.269
146
54
1 .994
2.4R4
1.691
456
7.743
7.204
l ,6ns
308
6.739
5.493
9b9
172
2.143
2.429
1 .629
3BU
5.454
3.073
8.115b
1 .588
32.119
27.931
14.546
5,030
60.178
44.695
WEST VIRQINIfl
WISCONSIN
NYD11ND
2.664
3.904
1.673
l.b»5
6.342
665
7.33S
4.776
895
3.419
4 .575
494
343
940
404
7fl?
2.895
346
10.948
23.390
4.479
1 .U79
2.600
159
422
1 .80S
B
1.129
4.970
515
903
6.241
?86
491
1 .256
228
446
5 .015
168
4.470
70.887
1 .354
15.416
44.277
5.633
lOlHI
200.673
Ub.362
156.644
191.302
50.462
96.946
670.4G9
278.404
127.431
335.687
235-03C
103.756
196.778
1.277.092
/.I47.bm
PERCENT - AREA
23.1
20.2
18.0
22.D
b .8
11.2
100.0
21. e
10.0
28.3
18.S
R. 7
IE.5
100.0
u.o
PERCENT - TOTAL
9.4
6.2
7.3
9.0
2.4
4.6
40.6
13-0
6.0
15.7
11.0
4.9
9.2
59.5
iOO-O
1/ OATA ARE
BA5£D ON 6
TATE HlGHMAT AOMCY CST(ttAT£9 AEPOKlEO FOR THE VARIOUS FUNCTIONAL SYSTEMS *N0 fWf 5U6JEC\ TO REVISION PENDING FURTHER FEDERAL HIGHWAY ADMINISTRATION REVIEW-
f
-------
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-Federal-
Aid 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:
F, = Roadway Miles(S„, 0/Roadway Miles(Statc 0 (3-10)
where F, = the apportioning factor to be applied to statewide VMT to
estimate areawide VMT for functional system f;
Roadway Miles(S„, 0 = roadway miles of functional system fin the area;
Roadway Miles(Statc0 = roadway miles of functional system fin 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.
72
-------
PUBLIC ROAD AND STREET MILEAGE • l»»0 1
u
o
BY FUNCTIONAL SYSTEM
nllEROE RS OF OCCEflBE* 31. 1990
COUP ILEO FROM REPORTS OF 6TBIE MJtrtMITIES
TABLE Ktl-20
STATE
RURAL
UR6AN
101AL
niLEROE
IHTERftTRfE
OTHER
PRINCIPAL
ARTERIAL
11 NOR
ARTERIAL
MAJOi
COLLECTOR
MNQfi
C0LLEC10H
10CRL
TOIRL
INTERSTATE
OTHgR
FREEHRY3
AND
£XP*E9SHAT6
OTHER
PRINCIPAL
arterial
IUK0R
arterial
COLLECTOR
LOCAL
TOIAL
«LR8A«A
ALASKA
ARIIONR
ARKANSAS
642
1.030
! .038
419
1*994
S3
1 .037
1 .931
9.994
902
2.191
3.167
11.691
1.904
3.744
12.460
5.971
90b
3.088
8.530
49.736
7.134
26.976
44.911
73.916
11.936
36.946
69.406
247
61
130
123
21
39
105
1.009
106
99$
936
1.811
81
1.010
996
1.707
194
1.660
1.006
12.260
1.147
10.946
4.8)2
19.964
1.649
14.987
7.877
90.672
13.496
61.612
77.095
CflLIFQRNfA
COIORAOO
CONNECT!lUf
OCLANARE
1 .41ft
799
109
2.992
1.901
226
IS4
9.699
1.947
472
163
12.921
7.302 '
960
609
9.991
12.066
1.137
1KP
66 .696
42.400
6-19?
2.731
69.662
66.406
9.066
3.679
663
149
232
41
1.263
164
191
1
6.841
929
710
139
8.312
1.140
949
138
7.747
(.156
1.916
169
49.676
7.734
6.907
I. J 33
79.922
11.272
10.90S
1.616
163.674
77.690
19.991
8.444
018T. Of COt.
FL0R10A
OEQSOIA
HANA1I
1*010
973
6
2.679
2.70S
19
3*409
6.674
907
4.696
14,034
469
6.196
7.266
I13
43.073
67.(21
1 .611
60.061
67.673
2.S67
12
416
372
39
24
269
146
53
99
1.935
1*468
94
162
2.406
2. lit
117
Ibb
4.790
1.909
180
869
36.229
(5.620
1.030
1.102
49.034
21.728
1.512
1.102
109.096
109.601
4.099
10AHO
ILL1N015
INDIANA
I0»A
690
1.41B
999
946
1 <640
2.741
1.102
9.169
1.027
6.061
9.134
4.990
4.992
14.199
9.764
13.697
3.909
9.676
10.303
16.399
46.111
78.930
46.994
96.101
60.006
103.94]
74.040
103.786
76
646
296
137
" 93
M2
194
2.972
1.316
921
397
9.167
2.269
1.286
396
3.291
1.961
1.047
1 .366
22.624
11,976
6.399
2.429
32.003
17.969
9.788
62.436
136.944
91.999
112.641
KANSAS
kentucry
LOUISIANA
HA IMC
7)2
679
959
9)9
3.260
1.636
1.094
739
4.466
1.756
1.576
1.099
22.726
7.216
7.962
3.276
9.321
9.272
4.306
2.264
63.997
41.619
31.366
12.229
124.473
91.976
48.330
19.996
160
194
199
63
90
90
29
14
677
497
1.018
223
1.036
1.094
1.111
297
770
992
1.146
394
6.470
4 .92b
6.799
1.613
9.106
7.692
12.290
2.494
133.676
89.669
69.920
22.399
NARTLANO
RA69ACHUSETTS
HlCNlOAN
MINNESOTA
199
no
77?
999
49$
242
2.399
3.3S7
1 .142
769
9.969
6.929
1*911
2.007
17.20)
16.604
1.993
1.961
7.493
11.978
10.949
9.091
69.050
77.339
16.462
19.230
90.773
116.169
231
397
466
217
191
174
200
136
891
1.946
1.962
696
969
2.419
9.669
1 .646
1.174
2.726
2.790
1.643
9.946
13.166
17.690
9.679
17.290
20.948
26.678
14.208
26.762
34.076
117.449
129.397
nisstssippi
MISSOURI
MONTANA
N(6RA6KA
b80
941
1 .144
444
1 .676
2.762
2.102
2.719
4.137
3.706
9.312
4.212
11 .704
16.102
6.691
11.456
2.909
5.430
9.261
9.233
44.276
74.647
46.626
69.36S
65.164
106.469
69.116
67.461
124
339
~7
37
34
270
10
600
1.039
17|
376
691
1.627
211
637
763
I .467
226
406
6.154
10.270
1.616
3.666
7.368
16.039
2.271
4 ,962
72.620
120,627
71.367
92.403
NEVADA
MEM HflrtPSHlNt
HCM JERSEY
NEW MEXICO
490
190
128
908
909
31A
279
1.376
1.179
664
646
2.293
2.329
1 .236
1 .734
4.201
2.466
1.230
1.264
2.3^3
36,371
8.77b
7.711
36.099
42.440
12.403
11 .760
49.239
46
44
270
94
36
33
269
3
172
190
1.366
469
342
366
2.668
331
432
942
1.919
296
2.068
1.469
16.600
4.326
3.094
2.433
22.602
6.498
46.824
14.996
34 .262
64.736
REM YORK
NORTH CflHOllNft
NORTH OJWOIA
OHIO
954
709
530
947
1.799
2.009
1.207
1.660
4.630
2.039
4.198
3.313
6.293
10.611
1\ .107
11.793
10.799
9.060
7.469
7.124
49.966
61.133
60.176
67.41$
73.329
76.446
64.706
62.172
646
226
40
726
762
207
367
2.407
1.746
166
2.167
4.166
2.204
270
2.762
3.443
1.375
226
4.146
26.997
13.496
1.120
21.241
37.913
19.246
1.911
31.428
111.242
94.990
86.617
113.600
OKLAHOMA
OAEOQN
PENNSYLVANIA
RttDOE ISLAND
729
698
1.196
21
1.679
2.266
t .799
74
3.220
2.467
6.966
92
21.409
9.649
7.999
201
9.092
7.327
9.376
163
69.369
64.271
62.999
992
99.662
66.669
68.164
1.623
207
192
403
49
199
66
364
64
792
566
2.916
346
1.663
1 .1118
2.822
291
1.206
97b
3.191
499
7.636
6.666
(9.729
3.339
12.093
9.410
26.344
4.689
111.766
94.989
1(6.699
6.111
SOUTH CAROLINA
SOUTH DAKOTA
TENNESSEE
ICXAS
673
631
790
2.292
1.619
2.319
1.069
7.90)
3.437
3.397
4.168
6.914
6.634
II .498
6.464
37.937
4 .004
6-986
10.782
19.626
36.636
49.163
47.046
143.614
34.703
72.962
69.299
217.176
118
47
292
947
34
3
926
669
170
1 326
3.944
996
232
970
6.694
1.169
114
1.811
6.983
6.447
1.169
10.962
70.692
9.343
t .734
15.340
99.778
b«.04b
74.696
64.639
306.96)
UTAH
VERNONT
VIROlNlA
washingrow
792
zee
777
629
69|
293
1.620
1.796
1.963
746
3.646
2.677
3.160
1.913
10.206
7.349
4.170
996
2.999
6.660
27.003
9.715
34.002
46,119
37.669
12.941
62.449
66.039
146
34
299
240
13
16
197
192
246
109
1.002
1.269
499
130
t .642
1.709
476
179
1.404
1.777
4.263
714
10.717
11.093
6.676
1.180
16.261
19.260
43.244
14.171
67.700
91.299
ME9T VIR0IN1A
WISCONSIN
NrOMlNO
427
SIC
969
512
9.299
1 .02)
1.729
6.0B8
2.098
6.362
13 742
2.496
2.161
6.606
7.486
20.336
66.360
29.339
31.516
95.461
97.281
90
124
§0
70
166
3
218
1.056
167
329
1.906
200
404
1.427
3?0
1.969
9.726
1.717
3.076
14.396
1.96?
34.692
109.976
39.213
TOTAL
33.S47
93.607
144.7%
439.366
793.912
7.130.427
3,122.799
11 .677
7.670
61.967
74.666
78.248
633.275
757.383
3.880.161
PERCENT - AREA
J.l
2.7
4.6
HO
9.4
66*2
100.0
1.5
1.0
9.9
9.9
10.3
70.4
100.0
.
PERCENT - TOTAL
0-9
22
3-8
11 .3
7.6
64.7
90.6
0.3
0.2
1.3
1.9
2.0
13.6
19.6
199.0
-------
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 area wide-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(Arca)/V(Statc) (3-11)
where F = the allocation factor to be applied to statewide VMT to derive areawide
VMT;
V(Aiva) = tota' number of motor vehicles of all types registered in the area;
V(state) = tota' 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(A,a) / P,S,a,) (3-12)
74
-------
where F
the allocation factor to be applied to statewide VMT to derive areawide
VMT;
p
1 (Area)
total population in the area;
P,
(Stale)
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 MF-
26 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 non-
highway purposes. The VMT apportioning factor is:
(3-13)
where F
the allocation factor to be applied to statewide VMT to derive areawide
VMT;
total quantity (gallons) of gasoline and diesel fuel sold in the area,
obtained from the state revenue agency;
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.
75
-------
PRIVATE AND COMMERCIAL HIGHWAY USE OF SPECIAL FUELS BY MONTHS - 1990 1
tftiriLED I'D* THE TER*
r.an rn rmh.Is of WtM»f uelwE
(THtuaANflS OF
Tfl«lE IF-16
OCTOBER l»»l
c«*«oc
1999
ir an
jftwjjur
FEIRuflif
HARCH
ftr*ic
MUl
JUNE.
JULY
fl'jQuil
lEfrcnetii
K709U
M»Enfr(9
OKttftKR
IOIRL
2s
04LLQN4
PEi-
CEM
RlfifiRrtR
flLflSKf*
MUD**
MKflN6n6
4J.232
8.811
11.141
79>m
H ,?90
(.HI
IMfil
21.896
41,94*
«.«<0
?9k^]0
42.488
7.J4J
27,;i<]
32r7C8
80«494
1.994
*8.»ft
14.898
50.085
8.068
28.008
34.179
82-027
8.278
27,878
38.799
SI>341
8 .202
28.9flB
34,414
48.097
7.388
2f>78i
31 >171
47,Jl* ,
7,228
29.439
93.028
46.101
5.967
26.611
31.661
94.269
4- 022
24.982
29.914
811 .091
83.574
53J.07J
166.802
MifiEti
21.062
8. in
-436
4.1
42 -9
1 .1
-C.I
CflLIFDRKlH
MlOfrojt
CONNECT ttVT
QiltUMt
J4A.057
18.110
IJ.986
S.7I3
MlJfll
1* ,610
15.220
l.tzl
IS9»«K
19 >981
!«*I84
4fiU
ll«-9]8
18.842
ti.flM
4.221
(92.944
19499
18*398
4«12*
'M
18.404
1.949
199if59
19-406
'MS
I7S.113
J9.9I7
21.241
8,310
]84 ,322
<7>?7i
18*820
4 >092
191.319
J?.418
tS.954
4.4B8
142.661
(6.631
14.651
4.121
149.135
IE,699
14.110
1.487
1.852.610
208.2C5
188.191
61.266
*41.721
11.400
-13433
-2(0
-4.1
4.9
•4.8
-0.4
0J6T. OF cot.
HOMO*
KH01M
1.664
10.188
81.824
1 .0*6
2044
*1.59*
8*'072
] >114
1 -W>
^7.912
70kll8
2>181
fc.t43
19.668
14,194
2.192
1.844
11.474
f8.42f
2.284
2.039
89.702
78,189
2.239
1-970
Sfi.533
7fl>29l
2*144
3 792
99 .971
10,4)2
2,285
2.040
*1.4(1
73.714
2,097
2,177
*8.9*4
74.079
2. *69
t.9?l
89.267
88.961
2,027
2.027
49.702
89.221
2.120
22 ,819
449>849
447>436
28,798
-834
•-18 * 344
11.703
I <209
-2,3
-1 >8
2>3
4.1
tM*0
flDHCIS
1*01 CM
Iflv*
fl.848
93*439
M >204
24.J84
• en
11.98*
49.794
2*.7*4
10,484
9t.923
*8>ISt
27,239
^,701
9f
80.689
29.991
ll<387
99.315
84,289
1I-2U
H .789
98 .261
86 .080
31 .447
H.134
99 >188
«7Jfi
M332
J 2.490
JOJ.723
66,188
32 >937
11,471
91.971
91.134
29>308
10.SM
93.914
92.618
21.907
1.999
87.(92
89.172
21.677
1.016
43.191
44,119
IS .241
124,238
(.096>000
726.928
376.714
it,141
96.984
-9.103
2M90
13,3
4,8
-1>I
4-t
Muses
K(NlUClU
(.6UISIIM
n*mi
20 JP
w.430
91 ,318
1.874
19,127
1IJ3I
19.Ml
7.852
23.13®
41.180
32>nt
8.KB
24.1C2
42.404
17.*99
9.394
28.973
41.021
31.868
9.935
24.0)8
43.285
32.890
I0.4|4
54 >388
43.393
12,711
J0>3I7
IB ,318
4*.*73
92 .888
IJ ,062
23 >008
49,200
30.0*0
9.994
24.496
41 .571
30.266
9.(66
21.119
18,144
18.397
7.949
12.393
31.121
27.670
9.801
914.089
4*9.482
37 4,tie
111,319
6. SSI
-26.7)$
-247
-12,202
1.4
MM
-0,1
-f >9
ntwiiAMO
W*83ftC«S€ETI6
NCCM/OMi
28.878
IS,7)9
91.824
24.770
24,221
ll.Kfl
U44t
23i44}
2I.M1
43»«19
29^80
30.294
2U«tt
43.940
27.3S3
91<899
22.828
*1.|47
29,571
23.951
40 >lQf
30.407
>?.55l
24,478
48>988
81 >8(6
32>367
24.498
50,488
3l>7jtf
29,082
22.249
46,9?J
?9<534
30.DIO
27.081
48.346
29.981
29.199
20.1*4
43.469
24.393
27.882
20>J09
40.618
2S.6S0
344.729
242,081
6)4 >84*
334.410
-€?«
-29,852
-922
-1.040
-0.2
-9,6
-0.2
-0.3
m»H31Pr]
NltMftil
non!***
NEIHSW
22.194
43.344
8.47*
is.io*
22.0*8
40.4J3
I.16&
27.81 J
47-811
9.6&4
17<801
29.1>4
4K.US
10.191
it.098
29.483
63.248
11.lit
20.1*4
30.077
54,260
)Mil
20>«19
32.40?
,567
\i >995
21.741
31.228
66.508
12.9(73
21,348
2ft.1*1
50.81 J
U.CT9I
19.789
29.694
82291
ja.570
18.124
$1,099
47.496
9. 499
19.430
34.997
43.971
6.444
16.101
329,949
694,302
126.344
220,244
7.188
-64 >474
4.421
9.117
7.2
-9.S
3.7
4 .7
N{VA(^
kEw MftnPfiHINt
UlU JER.5CY
win r.t * I CO
10*018
3.4*8
SMI!
1?.fl7
».1«
J,€7?
30.MB
f*,W
ia>8)6
J.HJ
S^7D0
13.347
19.798
4-099
34.H9
57,781
JQ,9t4
4.498
16.707
19.*«9
1 i .120
4,100
36>?<4
(9.749
12.434
4.4»j
39,928
k».9)1
J2.2?4
6.ttt
31.966
20.325
(0.660
A.417
36.(93
kl.919
n ,616
4,452
38.46(
11.183
10.808
3.134
)*}0
(T.477
($2.J 36
61.759
422.4B6
t??«6J6
2.176
-1,507
•32.973
14.263
1 1
-U,t
-1.2
8.9
nth row v
«0fl?H CAROLINA
Mat)H pftHOTfi
OMJO
«3J72
19,398
4>*l4
71-137
59.714
O.20I
69.903
623.890
H-498
fl.UI
8! »QJ4
78.M1
85.89)
8.792
94.426
ID, 2M
54'964
?.l28
87.514
82.299
88.617
9.10!
89.249
7^.499
ED.967
8.24?
Ra.374
78.133
14.214
8,326
82. no
93.170
43 ,719
7.279
7?>189
61,366
47.8*;
6.7*9
79,966
959.845
927,671
93.125
944.666
146.005
5.916
•30}
-96,152
20.6
1 0
-0.3
-8.2
QKL^HDhR
ORfOON 4/
PCnNSnVUNIA
R#[#l 351**0
31 >299
1)11}
II.Ml
JrllS
2»«S20
14<37l
21.999
78.9^9
J,? 78
3 4.166.
27,837
7?.6r2
S.JE?
W .8*4
29.921
9] 930
5 .874
J7-J>J
3I.KS
9>.4?4
3.729
33.310
83.754
4.091
16.919
92.709
18.092
1.991
91.473
30 >5v6
78.723
3 >461
14.890
28.878
82.110
3,439
34 ,390
2B.771
75.101
3,188
32.1*4
24.066
7?.365
3.172
<412.127
119.910
9It «63D
40.927
P9.957
23,4 >6
4.924
-17.694
8.r
1.*
0,5
-23 6
4DJTH CAROL IM
SDDTH 05WO1*
UH«E3$CE
infts
i$.48«
4.4J1
4flM7
Jt.Ofrl
ft. 327
108.»2l
38-$9ft
1.29&
48<39t
179.993
18.188
T.98L
Sk .8l3
J2I.2J?
M>178
9.233
i4.170
124 .Oil
36.473
19>231
8rr7)0
121.690
37.909
19.978
86*134
129-228
39.919
fe0<&99
§1«32?
sr(.794
36.416
9,739
49.724
116.394
38.309
i .282
50.197
) 14,243
33.4JQ
7 .418
51 .244
115,019
33<007
6.431
49.239
113.673
422*626
100*902
407.975
1>429.265
14.634
1.116
17.896
-4.306
3.4
7 -4
30
-0.3
UJRH
VCKNONT
VUOIHIR
NflthtN&TON
13,478
3-116
4 i.iflfl
77.JJ3
12.918
2,?6?
24.<»(
tB.(»)
1,7ft
5tl^78S
U.8|8
3.277
16 -341
29.841
IS >809
3 >803
48 099
3?0*2
15.878
3.792
41,374
J2.4^
(9.591
3.942
49.3(9
94 -933
19.909
4.062
90.6(7
35.032
18.461
3.841
•6.711
II .129
18.506
2 >898
44.?4|
29.881
14 .420
3>22?
42.344
26.924
14.793
3,202
43.043
28.424
190-927
41 .96(
5*4 .963
383.029
19 .997
-4 .893
-31,699
-1.628
11^
-id.6
-4.6
-o.«
VEST vrA01N!ft
1* F BCdNS L~u
KYVHNO
>0,741
11*119
kS.m
28.7M
LDtfiM
lli»»7
5S-t^4
D.828
n.flEi
4Q.I49
t« .834
18,330
40.894
^T.SlO
(7-123
4J.62B
S9.2tO
11.41?
43,383
19-122
18.526
31 ,E11
18 >029
14,383
31.923
1 * .898
k5-l1i
36.023
12,412
>5.291
12.812
H.929
197,926
»4J.69*
118,724
12 113
10.734
6,902
4.9
76
4.1
IQTIH
1.Bll.7D6
1 .190.398
1 ,188.88)
t.8?a.4«&
1.099.6tt
2.OH-(49
1<9714(53
1.792.099
1>808.893
1.596.491
1,44&.156
21 .399.904
124-2l8
0.6
PEHC(NlflQE
7,53
1.09
9.37
8 36
8.?9
4^3
9*49
92*
8 33
B.44
7.79
100.60
.
-
1/ ihji iHi.i js one of a aims cnr-21 i«muoh *f*28( qivinO mr rwcsio of
MTQN-FUH. COllfUllPTtW I05EO DM HEP0R16 fMM flfilE NOW-fUCl. (A1 ROUCUfi. $^£C 1BL
FUELS RB 8fNWH |M YA9tf HF-25 COHftlSl FRIABRlL* OF 0IC6U fUtL h(N $ft£U AMOtJNl* OF
LI0UEFf«O PEI90U1M 04$E9. rtl«U*Y USE OF 4P(C|Al FuElJ 13 REfORPEO 4* THt 3JTEO HIRE
IMCLU0E9 MOTOR FOEl CDK5UM0 8T VEHICLK6 Ttiflf fRt 114 MlUUK TAX, 1H16 0RLL0M05 18
CinilATEO IT ml 8T«TE.
-------
HIGHWAY USE OF GASOLINE BY MONTHS * 19901
COHPILCO FOft THE CftttNQAR YEAR TABIC HF-28
FROM AN ANALYSIS OF H0T0R-PUU USE (THOUSANOS OF OALlONS) OCTOBER 1901
STOIC
JANUARY
FEBRUARY
MARCH
APRIL
HAY
JUNE
JULY
AUCU5I
SEPTEMBER
OCTOBER
NOVEMBER
OECEROER
Tom
2/
CHftNOE
FROM
1989
oallons
PER-
CENT
RLAOANA
ALASKA
ARIZONA
ARKANSAS
166.4)8
16.096
134.903
91.129
146.466
16.113
190.979
66.072
176.764
16.774
149.966
101.000
174.926
20.191
194.969
102.209
161.614
21.726
196.66)
107.661
180.076
22.619
198.661
107.260
187.067
29.978
197.907
110.091
164.699
29.190
141.609
107.979
166.709
20.806
192.997
97.266
169.999
20.427
140.691
109.046
164.877
16.672
191.191
99.471
186.919
17.027
199.466
92.091
2.059.919
299.161
t.697.949
1.209.911
-9,967
94.011
-61.947
-16.946
-0.2
16.9
-9.6
-1.4
CALIFORNIA
COLORADO
CDNNECTICU!
OELAMARC
968,269
112.629
97.626
29.179
922.160
106.079
92.422
22.010
1.104.064
122.070
106.220
26.767
1.064.642
120.261
109.796
26.999
1.126.626
191.460
114.661
29.490
1.120.706
136.186
1M.68I
30.888
1.168.094
140.264
117.024
94.246
1.199.464
149.234
120.641
93.680
1.066.911
128.479
111.296
29.22$
1 .048.418
126.094
110.906
27.829
988.220
112.979
109.976
26.767
1.091.046
112.691
102.896
24.104
12.609.069
1,490.476
1.301.716
992.479
-168.016
11.481
-49.941
-9.978
-1.9
0.8
-3.9
-1 .2
0161. OF COL.
FtOA IOA
0E0R01A
HRHAlI
11.271
489.196
267.440
28.474
14.630
457.039
236.926
26.778
14.019
696.766
279.668
90.206
12.646
609.020
297.62$
90.242
14.102
493.860
304.496
91.642
14 .780
481.816
906.618
St .926
12.116
480.449
916.899
92.769
12.927
482.781
920.339
91.976
14.797
469.876
299.724
29.940
16.790
476.76$
296.106
30.206
19.672
471,709
274.718
28.988
14.864
461.616
276.766
29.666
166.619
6.890.699
9.466.676
960.888
-8.959
8.978
-10.199
-2.600
-6.)
0.2
-0.9
-0.7
IDAHO
ILLINOIS
1N01AHA
10HA
92.078
986.02$
189.774
84.296
91.242
962.666
177.948
78.661
91.996
424.890
209.966
99.986
98.819
426.217
216.664
96.914
41.269
449.691
226.869
107.779
42.691
447.606
231.716
108.807
46.166
469.900
241.8)9
224.662
46.281
473.068
242.862
119.904
41.806
427.296
217.798
101.117
99.616
493.B66
222.664
109.192
36.667
406.940
210.746
96.166
92.962
998.174
199.87)
87.117
464.699
6.092.209
2.689.010
1.299.981
20.9S8
268.946
19.209
-17.979
4.6
6.4
0.7
-1 .9
KANSAS
Kentucky
LOUISIANA
MAINE
76.626
132.426
149.721
40.66$
71.698
191.713
140.766
40.740
87.719
149.690
166.706
46.640
90.766
164.140
167.242
46.4^6
97.696
160.012
(•t.897
61.646
97.872
167.944
166.610
64.090
204.961
167.700
166.766
69.664
98.994
169.480
166.168
67.498
69.490
146.191
149.811
46.616
91.969
161.11$
144.706
47.601
87.126
198.866
196.672
99.297
64.177
141.609
13).812
49.28)
1,180.800
1.719.908
1.790.914
677.864
-46,214
-12.926
-121.427
702
-9.7
-0.7
-6.3
0.1
WARYIANO
HASSACHUSCTIO
MICHIGAN
MINNESOTA
147*770
176.766
908.7)0
136.969
139.714
169.911
280.966
129.020
189.097
191.892
936.163
148.120
167.819
191.428
940.639
169.176
176.666
209.991
966.604
166.696
172.137
219.970
972.989
170.216
178.211
218.096
379.699
177.144
179.407
219.904
990.799
177.620
180.936
199.199
966.367
169.790
166.241
196.796
969.288
162.164
169.963
184.890
936.910
147.746
162.883
190.920
314.118
143.914
1.996.029
2.994.469
4.144.034
1.872.687
••6.876
•66.046
•42.199
-81.890
•9.9
•9.6
-1.0
-4.2
MISSISSIPPI
MISSOURI
MONTANA
NE8RJ»SKA
63.88$
196.979
26*422
62.746
60.628
262.666
26.-736
46.467
JOI .946
216.114
91.996
69.110
96.961
223.691
99.991
60.798
107.928
240.646
36.698
#7.616
109.601
245.108
99.716
69.246
119.097
261.0)6
42.660
79.019
119.799
260.748
42.191
71.887
96.249
229.637
36.907
89.092
109.977
296.249
94.886
62.864
99.713
214.609
91.091
66.821
91.069
198.994
27.689
64.746
1.198.622
2.864.647
410.718
738,806
4.667
26.612
2.412
7.087
0.4
1.0
0.8
1.0
NCVAOA
N(H HAHP8N1RC
MM JERSEY
NEK M£XfCO
47.691
38.666
262.667
60.306
49.392
94.101
240.068
68.167
61.416
99.460
276.760
67.699
61.230
99.066
267.907
62.016
ft .969
42.666
280,660
•7.92)
66.620
44,610
264.610
66.992
69.009
46.636
266.246
66.249
90.994
49.660
269.461
70.966
60.641
42.689
272.619
•2.404
66.116
42.640
262.644
69.097
•1.269
97.60«
266.697
•0.849
49.637
37.467
280.701
61.706
•27.063
493.609
3.276.142
777.137
17.026
-20,866
-117.291
-7.404
2.6
-4.1
-9.6
-0.9
MEM YORK 3/
NORTH CAROLINA
NORTH DAKOTA
OHIO
432.346
262.697
21.707
360.671
397,434
241.469
19.266
326.971
472.499
266.626
29.266
992.196
470.763
276.467
24.622
362.946
619.061
269.943
29.026
999.120
610.922
266.769
29.242
404.692
642.909
281.274
90.990
419.492
666.879
269.822
90.809
427.807
490.699
2«0.724
27.444
986.267
609.676
277.742
27.724
993.689
491.449
249.467
24.219
372.771
468.208
244.991
22.808
974.168
6.616.961
3.210.880
310.104
4.624.942
276.094
-6.630
-9.066
-112.994
6.0
•0.2
-2.8
•2.4
OKLAHOMA
OREOON
PENNSYLVANIA
RHODE ISLAND
122.766
92.62$
393.370
24.666
114.619
64.994
317.602
26.072
196.069
106.414
971.689
29.966
194.263
108.878
974.8)6
29.617
144.779
116.780
996.990
32.466
146.912
121.701
999.798
32.936
149.669
129.992
404.999
96.364
144.192
126.964
418.289
34.379
131.938
118.412
380.672
30.666
196.188
111.906
397.341
90.976
134.90)
103.940
360.609
28.138
126.747
99.649
360.099
29*090
1.619.464
1.316.692
4.508.001
360.749
27.966
•2.40)
-49.699
•6.619
1.8
•0.2
-1.1
•1.6
SOOTH CAROLINA
SOUTH DAKOTA
TENNESSEE
TEXAS
>29.142
24.176
166.463
Ml. 290
129.672
22.466
170.620
660.860
162.992
26.661
184.648
741.904
169.699
28.399
206.668
719.462
169.622
32.774
217.926
796.966
162.462
38.321
206.839
721.018
166.469
96.971
219.978
742.160
169.176
99.006
228.066
746.694
146.046
31.0)9
191.961
•93.629
161.768
28.691
201.721
•77.064
139.742
$•.327
209.998
•82.196
137.976
24.249
196.9I«
679.682
1.766.662
368.187
2.419.720
9.462.733
49.649
•909
•76.469
122.166
2.9
•0.9
-9.1
l.t
UTAH
VERMONT
VlROlNlA
MASHlNOTON
62.670
21.261
224.776
166.669
49.932
19.799
210.966
160.367
66.194
22.006
249.299
169.166
67.276
21.666
244.466
169.986
69.999
24.044
269.166
197.216
61.761
26.106
266.206
199.671
•9.779
29.906
288.916
212.699
•4.967
27.028
272.990
216.266
69.723
24.296
246.•!•
194.996
69.993
24.668
241.299
161.823
66.737
21.690
228.304
177.138
66.247
21.962
294.786
182.414
•99.331
279,249
2.939.292
2.290.968
-24.064
6.788
-II .979
-7.662
-9.9
9.2
-0.4
•0.9
HE6T rlAOiNSA
N1SCONSIN
MTONlNO
61.266
199.282
16.207
66.979
190.420
18.869
67.602
169.929
22.967
69.910
169.769
21.786
71.996
192.266
26.294
71.426
166.080
27.684
72.299
197.136
90.666
79.468
196.694
90.649
69.717
179.061
26.604
88.894
176.936
29.797
•4 .029
169.176
20.467
64.611
(47.701
19.064
819.499
2.009.648
262.290
8.666
-6.070
-16.14$
1.1
-0.9
-6.4
TOTAL
8.963.216
7.661.889
9.219.289
9.206,62$
9.667.826
9
.702.991
10
.276.016
10.13).097
9.176.100
9.286.196
6.747.666
9.812.062
110.104.160
-968.478
-0.3
PERCENIAOE
7.68
7.14
8.98
6.98
8.77
6.80
9.28
9.19
6.33
8.49
7.94
7.82
100.00
-
-
1/ THJ8 TA8LE 16 ONE OF A SERIES 1HF-21 THROUGH HP-28) OIVINO AN ANALYSIS Or
HOTOR-FUEl CONSUMPTION SA6E0 ON REPORTS FROfl 8IATE MOTOR-FUEL TAl A0ENCIE6. HIOKNAY USE OF
OASOUNE UA8 ESTINATCO 0Y THE FEOCRAL HIOHHAY A0H1N18IRATION 1FMHA1 QT SUBTRACT! NO
NONHIOHHAY USE FROM TOTAL USE. IN ORDER TO MAKE THE ORlA UNIFORM AMD CO«PLCrC. NOMHIOHUAY
USES OF 0AS0L1NE HERE E8T1HATE0 8T FHHA OR OAIR MERE OBTRINCO FROM OTHER SOURCES. THE
REBULMND OALLONROCS OlFFER IN MRNV INSTANCES FROM THE UHADJUSIEO DATA RECORDED IN TRB4.C
HF-2. IN ORDER 10 APPROXIMATE ACTUAL USE. THE MONTHLY OlSIRlSUl10 US NCAC ESTlHATCO 8* FHNff
U9IN0 TRAVEL OATA. THE ENTRIES IN TABIC HF-28 NHL MOT AORCC H(?H TH09C IN TA61E MF-390A.
TABLE HF-20 8H0H8 HIOHMAY USE 0*1 T NH1LE TABLE HF-390A REFLECTS 0*089 0ALLON3 OF 0A80UNE
RIPOAIEO 6Y WHOLESALE O181R1BUT0R6 TO THE STATE TAXIHO A0ENCIE6 EACH H0NTH. 0A8QH0L IS
INCLUDED WITH OASOL INC*
If FOR SOHE STATES. DATA ARE HOT CORPARABLE TO PRIOR YEAR8 OUE TO CHANOES IN DATA
ANALYSIS AND/0* IMPROVEMENTS IN RE PORT IN) PROCEDURES*
2/ PRELIRINRRY OATA.
-------
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 MOB1LE4.1 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
174 The Federal Transit Administration was formerly the Urban Mass Transit Administration (UMTA).
175 Supplement 1 to "Methodology to Calculate Emission Factors forOn-Road Motor Vehicles". California Air
Resources Board. Technical Support Division. January 1988.
78
-------
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.
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 arc similar,
since, generally. UTPS served as the prototype for these other programs.
79
-------
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
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
-------
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-v 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.1™
17X
Hit>hwav Capacity Manual. Special Report 209. Transportation Research Board. National Research Council.
Washington. D.C.. 1985.
81
-------
LINK
ZONE
Figure 3-1
ATTRIBUTES
ZONE CtNTROlO
CENTROlO
CONNECTOR
A«T€BIA(_
XPflESSWftY
™ES««
TOLL FACILITY
UTOWN HIGHWAY NETWORK
-------
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.
83
-------
Figure 3-2
I FACILITY TYPE |
| AREA
| TYPE
—¥•
1
1
<1>
1
I
(2)
i
1
(3)
1
1 (4)
—»~-
!
1
(5)
I
(61 |
1 U)
• ^ C. f\
j ktrn&mV*
1
1
1
1750
/. c,
1
BOO
37
1
-i
600
** "1
cc
1 700
» - 22r
1
¦
i
10000
10
600 |
22 i
| (2)
| FRINGE
J
1
1750
*8
1
1
10G0
44
1
i
550
25
I 550
1 29
1
1
10000
15
BOO |
25 |
1 <31
| RESID*
1
I
1750
67
*
1
1100
47
»
1
550
20
I 900
1 32
1
1
10000
15
800 |
28 I
| <4) I
|OUTER CBO|
L750
58
1
1
1000
37
1
1
550
22
I 650
1 24
1
1
10000
15
800 |
22 I
I (5)
| RURAL
1
1
1750
67
1
1
1100
47
1
1
550
28
I 900
1 32
I
1
10000
15
BO 0*—Capacity
28 # —Speed
FACILITY TYPE COOES IN THE TABLE. ABOVE ARE DEFINED AS FOLLOWS:
I CODE I
FACILITY TYPE
1 | FREEWAY
I
2 I EXPRESSWAY
I
3 I TWO-WAY ARTERIAL WITH PARKING PERMITTED
I
4 I ONE-WAY ARTERIAL STREEl WITH PARKING »*£RMlTTEO
I EXECPT IN THE CBD. (AREA TYPE. II
I
5 I ALL OTHER
I
6 I TWO—WAY ARTERIAL STREET WITH NO PARKING PERMITTED
* Capacity per lane per hour,
84
-------
%
^ TYPE FACILITY
1 2 3 4 5 *
1
2
CELL VALUES:
3 • HOURLY 'POSSIBLE' CAPACITY* PER LANE
• 'FREE ROW SPEED
4
5
(•UEVEl OF SERVICE Yl
-------
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
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
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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.lso 1S1
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
1 SO
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.
1X1
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
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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.ls2
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 VMT1S4
should be made identical. The adjustment required to achieve this identity is described by
equation 3-14.185 186
1X2 Using HPMS rural area expansion factors is equivalent to allocating state rural totals by roadway miles.
1X ^
Interstate system, other freeways and expressways, other principal artcrials. minor artcrials. and collectors.
1X4
Non-attainment area VMT is the HPMS-bascd VMT estimated by the procedures described in Section
3.4.1.
1S5 States arc encouraged to make separate adjustments for each HPMS functional system. However, a state may
demonstrate that the more refined approach is infcasiblc 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.
VMTlAdl xotwori,- (VMT|S||,, / VMTlXc.nvoAl) • VMTlXc.nvoA n (.>-14a)
1Sf> 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 arc correctly converted to
grams per mile emission rates and so that cold start emissions arc correctly weighted into an overall emission factor.
88
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VMT(Atlj \ctwork. i) (VMT(SI1, 0 / VMT(Nctwork 0) • VMT(Nctwork i(
(3-14)
where VMT,
(Adj. Network, i)
Adj. Network Model VMT
VMT,
SIP Non-Attainment Area VMT
1X7. 1XX
(SIP. o
VMT(
(Network, i)
Original Network Model VMT
f
Functional System
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.1X9
1X7 Defined by equations 3-7. 3-7a and/or 3-8.
lss 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 arc advised that use of
equations 3-7. 3-7a and/or 3-8 is presumed to be the better approach foro/onc non-attainment areas.
1X9
Within HPMS all rural areas within the state arc 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
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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(SI1,, v) = (Roadway Miles(SII,, v) / Roadway Miles(III,XIS , v)) • VMT(IIPMS.i;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 non-
attainment 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
190 Other alternative methods of estimating VMT in this type of non-attainment area arc discussed in section
3.4.1.6.
191 Interstate system, other freeways and expressways, other principal artcrials. minor artcrials. and collectors.
90
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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
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
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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.
195 If 1990 demographic and economic input data arc used, a model validated for 1987 or later could provide an
acceptable VMT estimate for 1990.
196 EPA Regional Offices arc advised not to agree that the HPMS data arc weak without consulting with
divisional or regional FHWA officials who have direct knowledge of the HPMS data associated with the non-
attainment area. Desirable features of a network model that is a candidate for SIP VMT estimation arc 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 /one should be updated to 1990; preferably all socio-economic variables
would also be updated to 1990.)
197 EPA Regional Offices arc encouraged to consult with divisional or regional FHWA officials who have direct
knowledge of the network-based model under consideration.
92
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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.
93
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Appendix 3-A
Prescribed Volume Groups and Precision Levels
94
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APPENDIX F
Prescribed Volume
Grouos and Precision
Levels
Table F-l
RURAL AREA Volume
Groups and Precision
Levels
Vol.
i
J Other Principal j
Minor j
Grp.
Interstate
Arterial
Arterial
j (90-5)
j (90-5) j
(90-10) j
01
0- 9,999
0- 4,999
0- 2,499 |
02
10,000- 19,999
5,000- 9,999
2,500- 4,999
03
20,000- 29,999
10,000- 14,999
5,000- 9,999
04
30,000- 39,999
15,000- 19,999
10,000-19,999
05
40,000- 49,999
20,000- 29,999
20,000-29,999
06
50,000- 59,999
30,000- 39,999
30,000-39,999
07
60,000- 69,999
40,000- 49,999
40,000-49,999
08
70,000- 79,999
50,000- 59,999
50,000-59,999
09
80,000- 89,999
60,000- 69,999
60,000-69,999
10
90,000-104,999
70,000- 84,999
70,000-79,999
11
105,000-119,999
85,000- 99,999
80,000-89,999
12
120,000-134,999
100,000-114,999
90,000-99,999
13
i > or = 135,000
j > or = 115,000 j
> or = 100,000 1
+
iVol-i
Major j
Minor
i
1
j Grp.j
i i
Collector
(80-10)
Collector
(80-10)
1
1
i
+
1.
j
i 01
0- 2,499
0- 999
i
i
02
2,500- 4,999
1,000- 1,999
1
i
03
5,000- 9,999
2,000- 2,999
1
1
04
10,000-19,999
3,000- 4,999
1
i
05
20,000-29,999
5,000- 9,999
1
1
06
30,000-39,999
10,000-19,999
1
1
07
40,000-49,999
20,000-29,999
1
1
08
50,000-59,999
30,000-39,999
1
1
09
60,000-69,999
40,000-49,999
1
1
10
70,000-79,999
50,000-59,999
1
i
11
80,000-89,999
60,000-69,999
1
1
12
! 13 j
90,000-99,999
70,000-79,999
1
1
> or = 100,000 j
> or = 80,000
1
i
4-
95
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r-a
mtrnmcrlfaad Voli— CroutMi mm1 ffr«eIglon Levels
labi* r-2
mtMJ. imiMT VoIum Croups and Pneiatea IM1»
vol.
Otter Tzmmrwr*
1
1
I
J
otber Principal
¦4
1
1
1
1
t
interstate
(90-5)
and Expressways
(90—5)
Artorial
(90-5)
01
0- 9,999
0- 9,999
I
0- 4,999
*¦4
t
02
10,000- 19,999
10,000- 19,999
t
5,000- 9,999
j
03
20,000— 29,999
20,000- 29,999
10,000—14*999
I
04
30,000- 39,999
30,000- 39,999
I
1
15,000-19,999
1
OS
40,000- 49,999
40,000— 49,999
20,000-24,999
M
50.000- 59,999
50,000- 59,999
I
1
1
1
1
t
25,000-21,999
I 07
60,000- 69,999
60,t0«K 69»*99
30,000-34,999
I 08
70,000- 79,999
70,000- 79,999
33,000-39,999
1 09
•0,000- 99,999
SO,OOO- 89,999
40,000-44,999
1 10
M,OQO-104,9M
90,000-104,999
45,000-54,999
I 11 ;
105,000-119,999 :
105,000-119,999
55#©00—64,999
12 :
120,000-134,999
120,000-134,999
1
65,000-74,999
I " '
> or » 135,000
> or - 135,000
1
I
> or « 75,000
*
1
Vol,*
Grp.
i
~«
01
02
04
04
05
06
07
08
09
10
11
12
13
Miiwr
Mtmrlmi
(9O-10)
0- 2,499
2,300- 4,999
3,000- 9,999
10,000—14,999
19,000-19,999
20,000-24,999
25.000-29,999
30,000-34,999
13,000-39,999
40,000-49,999
30,000-99,999
60,000-69,999
> or • 70,000
Collector
(SO-IO)
0"
1,000- 1
2,000- 4
5,000- 9
10,000-14
15,000-19
10,000-24
25,000-29
30,000-34
35,000-44
45,000-54
55,000-64
> or » 65
999
,999
,999
,999
,999
,999
,999
,999
,999
,999
*999
,000
-------
F-3
yatgsrifrf fl Jtetowg ^feMPA,,aafl... ion frewit
Table F-3
URBANIZED AREA Volume Groups and Precision Levels
[vol.!
Grp.
i
+—
Interstate
(80-10) U
(90-5) 2/
1 other freeways
and Expressways
(80-10) 1/
{90-5) U
01
02
01
04
05
06
07
08
09
10
11
12
13
0-
25,000-
50.0QO-
75,000-
100,000-
125,000-
ISO.000-
175,000*
200,000"
22S,000-
250,000-
275,COO-
S' or -
24,999
• 49,999
¦ 74,999
99,999
•124,999
149,999
•174,999
•199,999
224,999
249,999
274,999
299,999
300,000
0-
25,000-
50,000-
75,000-
100,000-
125,000-
150,000-
175,000-
200,000-
225,000-
290,000*
275,000*
> or »
- 24,999
49,999
¦ 74,999
¦ 99,999
-124,999
¦149,999
¦174,999
>199,999
-224,999
¦249,999
•274,999
•299,999
300,000
Other Principal [
Arterial
(80-10) \/
(90-5) a/ 1
0- 2
2,500- 4
5,000- 9
10,000-14
15,000-19
20,000-24
25,000-34
35,000-44
4 5,000-54
55,000-69
70,000-84
85,000-99
> or « 100
,499 1
,999
,999
,999
r 999
,999
,999
,999
,999
,999
,999
,999
,000 [
j vol.j Minor
Grp. Arterial
V
\ (90-10) 2/
01
0- 2,499
02
2,500- 4,999
03
5,000- 9,999
04
10,000-14,999
05
15,000-19,999
06
20,000-24,999
07
25,000-34,999
08
35,000-44,999
09
45,000-54,999
10
55,000-69,999
11
70,000-84,999
12
85,000-99,999
» 1
> or ¦= 100,000
Collector
i/
(80-10) 2/ j
0- 999
1,000- 1,999
2,000- 4,999
5,000- 9,999
10,000-14,999
15,000-24,999
25,000-34,999
35,000-44,999
45,000-54,999
55,000-69,999
70,000-84,999
85,000-99,999
> or = 100,000
1/ precision levels for individual urbanised areas.
2/ Precision levels for collective urbanized areas.
3/ For individual urbanised areas, use (7o-iS) precision level
for States with 3 or more individual urbanized areas. Use
(80-10) precision level for States with lees than 3 individual
urbanised areas.
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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 1991.19X 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
19S U.S. Environmental Protection Agency. Nonroad Enaine and Vehicle Emission Studv. Report and
Appendices. EPA-21A-2001. Washington. D.C.. Office of Air and Radiation. November 1991.
98
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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.
199 U.S. Environmental Protection Agency. Nonroad Enaine and Vehicle Emission Studv. Report and
Appendices. EPA-21A-2001. Washington. D.C.. Office of Air and Radiation. November 1991.
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• 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 Jersey-
Connecticut CMSA/NECMA
• Philadelphia-Wilmington-Trenton, Pennsylvania-New Jersey-
Delaware-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 non-
attainment 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.
200 U.S. Environmental Protection Agency. Designation oC Areas for Air Quality Planning Purposes. 40 CFR
Part 81. Final Rule. Washington. D.C.. Office of Air and Radiation. November 6. 1991.
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• 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.
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.
• (A+B)/2 Inventory
• Inventory A
• Inventory B
• Baltimore
• Baton Rouge
• Houston-Galveston
• New York-New Jersey
• Philadelphia
• Seattle/Tacoma
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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.
201 Boo/ Allen & Hamilton. Inc. Commercial Marine Vessel Contributions to Emission Inventories. Final
Report to Environmental Protection Agency. Los Angeles. California. October 7. 1991.
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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.
202 SAF stands for seasonal adjustment factor. The columns 1/SAF arc 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.
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• 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 non-
attainment. 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 non-
attainment 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 non-
attainment 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.
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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
204 Adjustment factors arc not mandatory for calculations to proceed in AMS. but should be provided if modeling
will be done.
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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
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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 1
of the EPA nonroad report.206
205 Energy and Environmental Analysis. Inc. Methodoloav To Estimate Nonroad Enaine and Vehicle Emission
Inventories At the County and Sub-Countv Level. Draft Report to the Environmental Protection Agency.
Arlington. Virginia. February 11. 1992.
206 U.S. Environmental Protection Agency. Nonroad Enaine and Vehicle Emission Study. Report and
Appendices. EPA-21A-2001. Washington. D.C.. Office of Air and Radiation. November 1991.
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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.2™ 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
207 Energy and Environmental Analysis. Inc. Methodology To Estimate Nonroad Equipment Populations Bv
Nonattainment Areas, prepared for U.S. Environmental Protection Agency. September 1991.
20S U.S. Environmental Protection Agency. Nonroad Enaine and Vehicle Emission Studv. Report and
Appendices. EPA-21A-2001. Washington. D.C.. Office of Air and Radiation. November 1991.
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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 = N,, local x NA national (4-2)
N„ 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)
209 U.S. Environmental Protection Agency. Nonroad Enaine and Vehicle Emission Studv. Report and
Appendices. EPA-21A-2001. Washington. D.C.. Office of Air and Radiation. November 1991.
211) IU J
Ibid.
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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.2"
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.
211 U.S. Environmental Protection Agency. Nonroad Enaine and Vehicle Emission Studv. Report and
Appendices. EPA-21A-2001. Washington. D.C.. Office of Air and Radiation. November 1991.
212 Ibid.
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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
• Chicago
• Hartford
• Milwaukee
• Boston
• Denver
• Houston
• 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 non-
attainment 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-
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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 subcountv 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
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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 = Cntycquip pop x [(Area)subcntv/(Area)cntv)] (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. Cntycquippop is the population of a
particular recreational equipment type within the county of which the partial county is a part.
The ratio of Areasubcntv over Areacntv 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.
213 U.S. Environmental Protection Agency. Nonroad Eimine and Vehicle Emission Studv. 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 Bv
Nonattainmcnt Areas, prepared for U.S. Environmental Protection Agency. September 1991.
113
-------
• 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 45°F, a medium region was
classified as being between 35°F and 44°F, 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 * SAF_r (4-9)
tpwd = tpy * SAFwintcr (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).
SAFsumim;r = 4 * (% activity during summer/365 days) (4-11)
SAFwintcr = 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
215 Hare. C.T.. and K.J. Springer. Exhaust Emissions From Uncontrolled Vehicles and Related Equipment Usins>
Combustion Engines. Part 5. No. APRD-1494. San Antonio. TX. Southwest Research Institute. October 1973.
-------
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
Category
Agricultural
Construction
Industrial
Lawn & Garden
(excluding chainsaws)
Snowblower/
Snowmobiles
Cold/North
Summer Winter
50% 6%
43% 10%
30% 20%
50% 6%
0% 100%
Medium/Central Warm/South
Summer Winter Summer Winter
40% 6%
38% 15%
34%
-> ->0/
6%
20%
25% 25%
40% 6%
25%
34%
25%
6%
0% 100%
0%
100%
Airport Service
Logging
25% 25%
25% 25%
(including chainsaws)
Light Commercial 25% 25%
25% 25%
25% 25%
25% 25%
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.
216 U.S. Environmental Protection Agency. Nonroad Enaine and Vehicle Emission Studv. Report and
Appendices. EPA-21A-2001. Washington. D.C.. Office of Air and Radiation. November 1991.
115
-------
• 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.
217 Seasonal Adjustment Factor.
-------
Appendix 4-A
Emission Inventory Tables For New York CMSA
117
-------
Table 4-1
Counties and Sub-County Areas Included
In the New York CMSA Example
County
Bergen, NJ
Essex, NJ
Hudson, NJ
Hunterdon, NJ
Middlesex, NJ
City of
Perth Amboy
Monmouth, NJ
Borough of
Freehold
Morris, NJ
City of
Morristown
Ocean, NJ
City of Toms
River
Passaic, NJ
Clifton City
Patterson City
Passaic City
Somerset, NJ
Borough of
Sommerville
Sussex, NJ
Ozone
Classification
Nonattainment
Nonattainment
Nonattainment
Nonattainment
Nonattainment
Nonattainment
Nonattainment
Nonattainment
Nonattainment
Nonattainment
Nonattainment
CO
Classification
Nonattainment
Nonattainment
Nonattainment
Attainment
Nonattainment
Nonattainment
Nonattainment
Nonattainment
Nonattainment
Nonattainment
Nonattainment
Nonattainment
Attainment
118
-------
Table 4-1 continued
County
Union, NJ
Bronx, NY
Kings, NY
Nassau, NY
New York, NY
Orange, NY
Putnam, NY
Queens, NY
Richmond, NY
Rockland, NY
Suffolk, NY
Westchester, NY
Fairfield, CT
Ozone
Classification
Nonattainment
Nonattainment
Nonattainment
Nonattainment
Nonattainment
Nonattainment
Nonattainment
Nonattainment
Nonattainment
Nonattainment
Nonattainment
Nonattainment
Nonattainment
Litchfield, CT Nonattainment
Bridgewater Town
New Milford Town
Bethlehem Town
Thomaston Town
Watertown
Woodbury Town
CO
Classification
Nonattainment
Nonattainment
Nonattainment
Nonattainment
Nonattainment
Attainment
Attainment
Nonattainment
Nonattainment
Attainment
Attainment
Nonattainment
Nonattainment
Nonattainment
Nonattainment
Nonattainment
Nonattainment
Nonattainment
Nonattainment
New Haven, CT
Nonattainment
Nonattainment
119
-------
CMSA: NEW YORK
CMSA EMISSION INVENTORY A*B/2 - DIESEL EQUIPMENT
NEW Nonattalnment Boundiriti
(tons per year)
17:46 Thursday, June 16, 1992 73
Echauit Crinictit
HC HC E vap.
RefuelIng
HC HC
NJ
O
EQUIPMENT TYPES
Trimmert/Edgars/Brush Cutters
Lawn Mowers
Lee f Blowers/Vacuums
Rear Engine Riding Mowers
Front Howtrt
Chatnsews <4 HP
Shredders <5 HP
Ji I l«r« 5 HP
Swathers
Hydro Power Units
Other Agricultural Equipment
Chalntews >4 HP
Shredders >5 HP
Sktdders
Fellert/Bunchers
TOTAL DIESEL EQUIPMENT
0
0
0
0
0
0
0
0
22
0
0
34
0
0
90
3.147
0
0
0
0
0
0
75
0
0
e
o
269
60
JO
0
119
0
64
649
753
147
32
22
0
0
23
71
214
113
0
6
134
64
396
0
1
914
527
614
63
29)
966
125
1.007
2,4)9
363
1,450
0
92
0
90)
0
21
0
1
0
)2
0
2
0
0
0
0
14,576
0
2
22
0
0
0
0
0
0
0
0
0
0
0
6
1
1
0
2
0
2
16
15
3
1
0
0
0
0
2
3
2
0
0
3
1
7
0
0
20
10
13
2
6
22
J
22
54
7
29
0
2
0
17
0
0
0
0
0
0
0
0
0
0
0
0
296
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
0
0
0
0
0
0
0
0
0
0
0
)
0
0
0
a
o
0
2
1
0
0
0
0
0
0
0
1
0
0
0
0
0
2
0
0
2
1
2
0
0
3
0
2
5
1
2
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
31
0
0
0
0
0
0
0
0
23
0
0
35
0
0
91
1*161
0
0
0
0
0
0
76
0
0
6
0
277
62
31
0
)23
0
66
674
776
162
33
23
0
0
24
74
220
116
0
6
136
66
406
0
1
944
543
635
66
300
) ,002
129
1,039
2,499
394
1,493
0
95
0
927
0
22
0
1
0
13
0
2
0
0
0
0
15.032
CO (CO
Area)
0
0
0
0
0
0
0
0
52
0
0
76
0
0
34)
4.326
0
0
0
0
0
0
55
0
0
12
0
666
196
96
0
394
1
237
2,396
'¦tfj
92
8]
0
]
68
196
1,084
164
0
23
563
296
2.089
2
2
2,169
922
1,450
386
1,2)0
1,921
296
3,468
6,634
1.164
6,112
0
424
0
319
0
6
0
0
0
3
0
0
0
0
0
0
44,902
1.
ctW
0
0
0
1
0
0
0
0
94
0
0
140
0
0
349
4,429
0
0
O
0
0
0
114
0
O
14
0
.122
2SO
124
0
497
2
324
3,278
2,910
669
125
117
0
1
95
276
1,529
514
0
33
794
416
2,945
3
2
3,045
1.301
2,047
544
1.7J4
5.532
416
4,890
9,214
1,642
8,644
0
599
0
3,616
0
71
1
1
0
29
1
4
0
0
0
0
64,396
PM (OJ
Artt)
CH (CO
Ar«.)
CO tpxd CO tpid
VOC tp»d NO* tptd (CO Ar«a) (03 Ar«»)
O
0
0
1
0
0
o
0
ISO
0
0
224
0
0
807
10,232
0
0
0
0
0
0
612
0
0
10
0
1,795
400
199
0
796
1
748
7,573
6,723
1,314
289
377
0
3
209
829
2,660
1,210
0
52
870
498
6,089
3
6
7,468
3,286
7,017
651
1.387
11.871
1.426
7,263
19,771
1,751
7,011
71?
0
4,634
0
193
1
2
0
159
1
10
0
0
0
0
119,146
0
0
0
0
0
0
0
0
IB
0
0
21
81
1.029
0
0
0
0
0
0
14
0
0
1
0
184
41
20
0
82
0
58
836
632
124
27
32
0
0
18
64
375
84
0
111
64
670
0
0
868
333
525
71
228
1,113
91
747
1,898
216
965
0
78
0
668
0
32
0
0
0
13
0
1
0
0
0
0
12,695
0
0.00
0.00
o.oo
0.00
0
0.00
0.00
0.00
o.oo
0
ooo
0.00
0.00
0.00
0
0.00
0.00
0.00
0.00
0
0.00
0.00
0.00
0.00
0
0.00
0.00
0.00
0.00
0
0.00
0.00
0.00
o.oo
0
0.00
o.oo
o.oo
o.oo
10
0.11
0.82
0.00
0.51
0
0.00
0.00
0.00
0.00
0
0.00
0.00
0.00
0.00
13
0.19
1.22
0.00
0.77
0
0.00
0.00
o.oo
0.00
0
0.00
0.00
0.00
0.00
79
0.26
2.21
0.93
0.96
005
3.21
28.04
11.86
12.13
0
0.00
0.00
0.00
0.00
0
0.00
0.00
0.00
0.00
0
0.00
o.oo
0.00
o.oo
0
o.oo
0.00
0.00
0.00
0
0.00
o.oo
0.00
0.00
0
0.00
0.00
0.00
0.00
16
0.56
1.97
0.01
0.85
0
0.00
0.00
0.00
0.00
0
0.00
0.00
0.00
0.00
1
0.06
0.07
0.00
0.10
0
0.00
0.00
0.00
0.00
146
0.75
4.92
2.41
3.07
11
0.17
1.10
0.54
0.68
16
0.08
0.54
0.27
0. 34
0
0.00
0.00
0.00
0.00
65
0.11
2.18
1.08
1.36
0
0.00
0.00
0.00
0.00
41
0.26
2.05
0.65
0.89
611
2.17
20.75
6.56
8.98
462
2.11
18.42
5.83
7.97
90
0.41
1.60
1.14
1.56
20
0.09
0.80
0.25
0.34
21
0.10
1.78
0.09
0.55
0
0.00
0.00
0.00
0.00
0
0.00
0.02
0.00
0.00
11
0.11
0.98
0.07
0.45
45
0.35
1.91
0.22
1.30
266
1.01
12.54
1.19
7 21
59
0.54
5.80
0.40
2.42
0
0.00
0.00
0.00
0.00
4
0.04
0.24
0.03
0. IS
81
0.65
4.10
0.62
3.74
18
0.30
2.15
0.32
1.96
475
1.91
20.70
2.29
13.88
0
0.00
0.02
o.oo
0.01
0
0.00
0.01
0.00
0.01
615
4.41
36.19
2.36
14.35
236
2.54
15.48
1.01
6.13
372
297
33.06
1.59
9.64
50
0.41
3.07
0.42
2.56
162
1.40
6.54
1.35
8.17
945
4.69
55.94
4.30
26.07
64
0.60
6.72
0.32
1.96
529
4.86
34.22
3.80
23.04
146
11.68
93.17
7.16
43.42
168
1.84
8.25
1.28
7. 74
684
6.97
33.05
6.72
40.73
0
0.00
0.00
0.00
0.00
55
0.45
3.38
0.46
2.82
0
0.00
0.00
0.00
0.00
59
5.04
24.84
0.21
19.81
0
0.00
0.00
0.00
0.00
3
0.12
1.06
0.00
0. 39
0
0.00
o.oo
0.00
0.00
0
0.00
0.01
0.00
0.00
0
0.00
o.oo
0.00
0.00
1
0.07
0.87
0.00
0.15
0
0.00
0.00
0.00
0.00
0
0.01
o.os
0.00
0.02
0
o.oo
0.00
0.00
0.00
0
0.00
0.00
0.00
0.00
0
0.00
0.00
0.00
0.00
0
0.00
0.00
0.00
0 00
906
64.02
506.06
67.77
279.24
-------
CMSA EMISSIONS PER PERSON (INV. A*B/2) - OUSEL EQUIPMENT
NfW Nanette fninent Boundaries
17:46 Thur*d«y, June 18, 1992 740
CMSA.* NEW YORK
EQUIPMENT TYPES
Tr innert/fdger*/Brush Cu11 art
lewn Mowers
Lee f 8lowers/Vacuums
Beer Engine biding Mowers
Front Mower*
Chelnsew* <4 HP
Shr«dd*ri <5 HP
TUIiri <5 HP
Uwn I Gird«n Tractor*
Wood Splitters
Snowblowers
Chfppers/Sturop Grinders
Ceovnerdel Turf Equipment
Other Lawn ft Garden Equipment
Aircraft Support Equipment
T#rw1n*l Iractori
AU Urriin V«hiclii (ATV»)
Mlnibifcea
Off-Roed Motorcycle*
Golf Cirti
Snoiwnobl lea
Specialty Vehicles Carta
Vessels w/Inboard Engines
Vessels w/Outboerd Engines
Vessel* w/Sterndrfve tnglnti
Seflboet AwAltiery Inboard Engine*
Sillboit Auxiliary Outboard Engine*
Generetor Seta <50 HP
Pump* <$0 HP
Air Compressor* <50 HP
Get Comprtiiort <50 HP
Weldera <50 HP
Preasure Washers <50 HP
Atrial Lifts
Forklffta
Sw«*p*r»/Scrubb«rt
Othar Generel Industrial Equipment
Other Material Handling Equipment
Aaphelt Pavara
Tempera/ffamners
Plat* Compactors
Concrete Pavara
Do))era
Scraper*
Paving Equipment
Surfacing Equipment
Signal 6oaroa
Trenchers
Bore/Or11) Riga
Excevetors
Cone rate/Industrie 1 Sew*
Cement end Hortar Mlaer*
Cranaa
Greders
Off-Highway Truck*
Crushing/Proe. equipment
Rough Terrain forkllfta
Rubber Tired loadara
Rubber Tired Oozers
Treetors/loaders/Backhoes
Crawler Tractor*
SMd Steer Loader*
Off-Highway Tractor*
Oumpers/Tenders
Other Construction Equipment
2-Wheel Trectors
Agricultural Tractor*
cultural Mowers
Combines
Sprayers
Balers
Tillers >5 HP
Swather*
Hvdro Power Units
Other AgrfcuU ural Equipment
Chain**** >4 HP
Shredders >5 HP
Sk1dders
Fellers/Bunchers
TOTAL OUSEL CQUIPMENT
VOC*
0.00
0.00
0.00
0.22
0,00
0.00
0.00
o.oo
35.99
0.02
0.00
53.67
0.00
0.01
67. 16
652.63
0.00
0.00
0.00
0.00
0,00
O.U
124.85
0.00
0.00
9.77
0.00
297.68
66.34
33.08
0.00
131.90
0.45
105.87
1083.57
960.46
107.68
41.51
29.31
0.00
0.35
30.87
95.83
285.04
150.84
0.00
10.46
178.61
84.60
528.65
0.31
0.72
1223.61
704.36
824.41
111.47
388.41
1298.43
165.81
1347.07
3240.12
511.47
1929.77
0.03
123.36
0.00
3304.16
0.00
77.87
1.48
2.37
0.00
45.63
1.38
6.03
0.00
0.00
0.00
0.00
20756.03
CO* (CO
Area)
0.00
0.00
0.00
0. 33
0.00
0.00
0.00
0.00
54.98
0.04
0.00
82.23
o.oo
0.05
244.12
3098.65
0.00
0.00
0.00
0.00
0.00
0.03
56.95
0.00
0.00
14.09
0.00
752.83
167 .73
83.23
0.00
333.68
1.16
229.97
2328.45
2066.15
405.07
68.91
77.10
0.00
0.66
62.45
161.64
1005.28
337.66
0.00
21.42
521.69
273.64
1936.67
1.68
1.64
2001.68
855.17
1343.96
356.93
1140.12
3634.97
273.80
3213.82
6054.99
1079.00
5683.74
0. 10
393.70
0.00
469.21
0.00
9.16
0. 10
0.04
0.00
3.81
0.04
0.44
0.00
0.00
0.00
0.00
40945.16
CO* (03
Area)
0.00
0.00
0.00
0.89
0.00
0.00
0.00
0.00
145.60
0.07
0.00
217.23
0.00
0.06
251.81
3196.88
0.00
0.00
0.00
0.00
0.00
0.43
107.55
0.00
0.00
17.22
0.00
1205.03
268.56
133.90
0.00
533.97
1.83
397.09
4062.16
3601.56
704.54
155.64
151.63
0.00
1.32
124.50
358.43
1981.28
666.11
0.00
42.22
1029.00
534.56
3813.10
1.97
3.20
3949.19
1687.25
2657.78
704.31
2246.25
7170.93
534.51
6338.69
11945.17
2129.53
11171.78
0.U
779.41
0.00
12886.09
0.00
251.35
2.46
3.96
0.00
103.21
2.30
14.05
0.00
0.00
O.OO
0.00
88367.90
PH • (03 PM
Area)
0.00
0.00
0.00
1.42
0.00
0.00
0.00
0.00
232.95
0.11
0.00
347.50
0.00
0.10
581.74
7385.51
0.00
0.00
0.00
0.00
0.00
0.69
874.12
0.00
0.00
12.92
0.00
1928.05
429.69
214.24
0.00
854.34
2.93
917.39
9384.57
6320.45
1627.64
359.59
466.06
0.00
3.93
272.96
2075.29
3447.43
1594.32
0.00
67.57
1128.06
639.77
7682.84
2.36
7.65
9684.91
4262.51
9112.40
642.07
1797.00
15367.62
1632.60
9415.12
25632.36
2271.50
9063.75
0.38
932.76
0.00
16156.06
0.00
688.21
5.09
8.12
0.00
565.19
4.75
35.78
0.00
0.00
0.00
0.00
157787.25
0.00
0.00
0.00
0.16
0.00
0.00
0.00
0.00
26.71
0.01
0.00
35.70
0.00
0.01
58.50
742.66
0.00
0.00
0.00
0.00
0.00
0.07
55.19
0.00
0.00
0.66
0.00
198.18
44.17
22.02
0.00
67.82
0.30
71.30
1036.09
701.78
152.97
33.77
41.25
0.00
0.31
23.54
02.52
486,29
108.29
0.00
6.94
146.70
69.51
667.60
0.25
0.52
1125.07
431.40
662.02
91.62
295.14
1726.03
116.50
967,05
2460.76
306.64
1246.91
0.04
101.36
0.00
2381.69
0.00
115.50
0.70
l.Ol
0.00
45.15
0.71
3.67
0,00
0.00
o.oo
0.00
17280.30
Aree)
0.00
0.00
0.00
0.06
0.00
0.00
0.00
0.00
10.04
0.01
0.00
13.54
0.00
0.01
56.71
719.64
0.00
0.00
0.00
0.00
0.00
0.00
16.76
0.00
0.00
0.70
0.00
123.81
27.59
13.69
0.00
54.88
0.19
41.29
593.89
448.49
67.95
19.29
20.98
0.00
0.16
11.61
41.02
246.74
54.89
0.00
3.52
75.39
35.61
440.65
0.21
0.26
570.25
216.65
344.86
46.43
149.50
675.95
59.67
490.70
1247.35
155.37
634.37
0.04
51.20
o.oo
86.73
0.00
4.22
0.03
0.01
0.00
1.67
0.01
0.12
0.00
0.00
0.00
0.00
6099.04
• (CO
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NOx #
0.00
0.00
0.00
0.00
0.00
o.oo
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.20
0.80
1.28
0.00
o.oo
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.29
1. 19
1.90
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.67
0.19
0.69
1.60
6.49
2.32
6.76
20.24
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.92
1.40
6.52
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0,00
0.07
0.11
0.08
0.00
0.00
0.00
0.00
2.06
0.01
3.30
5.20
0.46
0.10
0.74
1.18
0.23
0.09
0.37
0.58
0.00
0.00
0.00
0.00
0.91
0.35
1.46
2.34
0.00
0.00
0.00
0.00
0.63
0.29
1.09
2.51
6.38
2.94
11.13
25.71
5.66
2.61
9.87
22.60
1.11
0.51
1.93
4.45
0.24
0.11
0.43
0.99
0.08
0.14
0.71
2.30
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.02
0.07
0.14
0.59
1.26
0.20
0.45
1.69
5.07
1. 10
1.33
9.34
16.25
0. 37
0. 70
3.14
7.51
0.00
0.00
0.00
0.00
0.02
0.05
0.20
0.32
0.57
0.84
4.65
5.31
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0.39
2.52
3.02
2. 12
2.47
17.97
37.15
0.00
0.00
0.01
0.01
0.00
0.00
0.01
0.04
2.19
5.71
18.61
45.64
0.94
3.29
7.95
20.06
1.47
3.85
12.52
42.93
0.39
0.53
3.32
3.97
1.25
1.61
10.59
8.47
3.99
6.07
33.79
72.51
0.30
0.77
2.52
6.64
3.52
6.30
29.87
44.37
6.64
15.14
56.29
120.79
1.18
2.39
10.03
10.70
6.23
9.01
52.64
42.71
0.00
0.00
0.00
0.00
0.43
0.50
3.67
4.40
0.00
0.00
0.00
0.00
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17.95
70.61
66.53
0.00
0.00
0.00
0.00
0.01
0.43
1.38
3.77
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0.00
0.01
0.01
0.00
0.00
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0.03
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0.00
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0.00
0.00
0.26
0.54
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0.01
0.01
0.00
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0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
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60.54
92.53
398.73
696.61
"... Gretna per year per peraon
-... Grems per winter dey per person
#... Gram* per suavrter dey per person
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Appendix 4-B
Equipment Categories
124
-------
Category 1, lawn and garden equipment, includes 14 types of equipment.21* 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 1-3 and 1-4 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).
1X
U.S. Environmental Protection Agency. Nonroad Engine and Vehicle Emission Studv. 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 Bv
Nonattainmcnt 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
-------
The agricultural equipment category is comprised of 11 types of equipment. Examples of
these are listed below.
• tractors
• combines
• swathers
• fertilizer spreaders
• agricultural mowers (> 5 h.p.)
• cotton pickers
• balers
• tillers
• sprayers
• harvesters
• strippers
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 1-07 in the nonroad report
presents the chosen emission factors from EAT in grams/horsepower-hour, and table 1-08 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.
221 U.S. Environmental Protection Agency. Compilation oC Air Pollutant Emission Factors. Volume 11. 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 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 SwRl224 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.
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-Highwav 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
-------
• forklifts
• boom lifts
• scissor lifts
• industrial sweepers
• winches
• hoists
• vacuums
• scrapers
• scrubbers
• blowers
• conveyors
For both gasoline and diesel industrial equipment, emission factors found in Volume 1 of
AP-42 were used. These factors were developed by SwRl 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 22s These
types are listed below.
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 1-09, 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
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 Studv. Report and
Appendices. EPA-21A-2001. Washington. D.C.. Office of Air and Radiation. November 1991.
-)->X
Energy and Environmental Analysis. Inc. Methodology To Estimate Nonroad Equipment Populations Bv
Nonattainmcnt 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.
• paving equipment
• roofing equipment
• signal boards
• cable layers
• drilling rigs
• excavators
• industrial saws
• backhoes
• cranes
• cement/mortar mixers
• crushing/processing equipment
• dozers
• loaders
• tractors
128
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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.
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.
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
230 Hare. C.T.. and K.J. Springer. Exhaust Emissions From Uncontrolled Vehicles and Related Equipment Usina
Internal Combustion Engines. Final Report. Part 7. Snowmobiles. San Antonio. Texas. Southwest Research
Institute. April 1974.
• load lifters
• de-icing equipment
• heating units
• utility service equipment
• starting units
• baggage conveyors
• towing/pushback tractors
• misc. service vehicles
• all terrain vehicles (ATVs)
• minibikes
• snow and ice maintenance equipment,
• go-carts
• gasoline powered golf carts
• snowmobiles
• industrial personnel carriers/ATVs
129
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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 1-1 la and 1-1 lb 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 1-1 lc 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 1-1 Id 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
231 Boo/ 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. Novcmcbcr6. 1991.
233 Energy and Environmental Analysis. Inc. Methodology To Estimate Nonroad Engine and Vehicle Emission
Inventories At the County and Sub-Countv Level. Draft Report to the Environmental Protection Agency.
Arlington. Virginia. February 11. 1992.
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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 ocean-
going, 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 1-12a and 1-12b in Appendix 1 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
234 Boo/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 Sen ice. 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.
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Appendix 4-C
Sample Inventory Calculation
132
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Sample QMS 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 1 (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.
-------
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 (03 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.
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Appendix 4-D
Inventory Request Form
135
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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
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1.
2 .
3 .
4 .
5 .
6 .
7 .
8 .
9 .
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
Areas Available
Anchorage AK
Atlanta GA
Baltimore MD
Baton Rouge LA
Beaumont-Port Arthur TX
Boston-Lawrence-Worcester MA
Chicago-Gary-Lake County IL-IN-WI
Cleveland-Akron-Lorain OH
Denver-Boulder CO
El Paso TX
Hartford-New Britain-Middletown-Bristol CT
Houston-Galveston-Brazoria TX
Las Vegas NV
Miami-Fort Lauderdale FL
Milwaukee-Racine WI
Minneapolis-St. Paul MN
Muskegon MI
New York-Northern New Jersey-Long Island NY-NJ-CT
Philadelphia-Wilmington-Trenton PA-NJ-DE-MD
Phoenix AZ
Portsmouth-Dover-Rochester NH
Providence RI
Provo-Orem UT
San Diego CA
San Joaquin Valley Air Basin CA
Seattle-Tacoma WA
Sheboygan WI
South Coast Air Basin CA
Spokane WA
Springfield MA
St. Louis MO
Tucson AZ
Washington DC
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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-42.23s
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
"" 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
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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.
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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 (NO J, sulfur dioxide (S02), 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
139
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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-ln-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.
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TABLE 5-1: DEFAULT TIME-IN-MODE
FOR VARIOUS AIRCRAFT CATEGORIES1
Aircraft
Taxi/
Idle-out
Time in Mode (Minutes)
Takeoff Climbout Approach
Taxi/
Idle-in
Total
CIVIL2
Commercial Carrier
Jumbo, long and
medium range
jet
Turboprop
Transport-
piston
General Aviation
Business jet
Turboprop
Piston
Helicopter
19.0
19.0
6.5
6.5
19.0
12.0
3.5
0.7
0.5
0.6
0.4
0.5
0.3
2.2
2.5
5.0
0.5
2.5
5.0
6.5
4.0
4.5
4.6
1.6
4.5
6.0
6.5
7.0
7.0
6.5
6.5
7.0
4.0
3.5
32.9
33.5
23.2
15.5
33.5
27.3
20.0
MILITARY3
Combat4
USAF
USN5
18.5
6.5
0.4
0.4
0.8
0.5
3.5
1.6
11.3
6.5
34.5
15.5
Trainer - Turbine
USAF T-38
USAF general
USN5
12.8
6.8
6.5
0.4
0.5
0.4
0.9
1.4
0.5
3.8
4.0
1.6
6.4
4.4
6.5
24.3
17.1
15.5
Transport - Turbine®
USAF general
USN
USAF B-52
and KC-135
9.2
19.0
32.8
0.4
0.5
0.7
1.2
2.5
1.6
5.1
4.5
5.2
6.7
7.0
14.9
22.6
33.5
55.2
Military
Piston
6.5
0.6
5.0
4.6
6.5
23.2
Military -
Helicopter
8.0
6.8
6.8
7.0
28.6
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TABLE 5-1; DEFAULT TIME-IN-MODE
FOR VARIOUS AIRCRAFT CATEGORIES1
(Concluded)
SOURCE: AP-42. Compilation of An Pollutant Emission Factors, Volume II: Mobile Sources, U.S. Environmen
taJ Protection Agency, Ann Arbor, Michigan, September, 1985. {Aircraft data from February 1980}.
Civil aircraft data is for large congested metropolitan airports.
USAF - U.S. Air Force, USN - U.S. Navy.
Fighters and attack aircraft only.
Time-in mode is highly variable. Taxi/idle out and in times as high as 25 and 17 minutes, respectively, have been
noted. Use local data base if possible.
Includes aU turbine aircraft not specified elsewhere (i.e., transport, cargo, observation, patrol, antisubmarine, early
warning, and utility).
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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.
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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
239 AOPA's Aviation USA. Aircraft Owners and Pilots Association. 1990.
144
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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 slow-
reacting pollutants in many urban areas. Figure 5-1, showing annual mixing heights, may be
used for creating an annual inventory. If
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 (XModcm. 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 Contii>uous United
States. U.S. Environmental Protection Agency. Research Triangle Park. North Carolina. January 1972. NTIS
Report Number PB 207103.
145
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FIGURE 5-2: RZPRODUCTION OF FIGU1I 4 FROM &EFC&ZHCS 5
147
-------
FIGURE 5-3: REPRODUCTION OF FIGOM 2 FROM REFERENCE 5
148
-------
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
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
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TABLE 5-2: COMMERCIAL AIRCRAFT TYPES AND ENGINE MODELS
(Concluded)
1 Source of Aircraft, Type, and No. of Engines is 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 2290303.
2 Engine Types: TF - Turbofan, TJ - Turbojet, TP - Turboprop, P - Piston
3 Following the engine model is the percent of aircraft in parentheses which correspond to the particular engine and the engine manufacturer.
GE engine data obtained from GE Aircraft Engines: Commercial Program Status. Volume 1, (General Electric, 1991, Cincinnati, Ohio) and Office of Combustion Technology,
GE Aircraft Engines (One Neumann Way MD A309, Cincinnati, Ohio 45215*6301, 513/774-4438). Corresponding percents of aircraft refer to U.S. commercial and government
aircraft in operation as of 12/31/90. P&W, P&WC, and RR engine data obtained from Turbine-En gjocd Fleets of the World's Airlines 1990 (Exxon Corporation, supplement to
Air World, Volume 42, Number 2, 1990). Corresponding percents of aircraft refer only to U.S. airlines. Engine Manufacturers: Con - Teledyne/Continental, GE - General
Electric, Grt - Garrett AiResearch, Lyc - Avco/Lycoming, PW - Pratt & Whitney, PWC - Pratt & Whitney Canada, RR - Rolls Royce
4 All Cargo Services.
5 Percent of aircraft assumed 100%.
6 Refers to B-737-300 and -500 aircraft.
7 Refers to B-747-200, -300, and SR aircraft.
8 Refers to B-767-200ER aircraft. GE combined the number of aircraft in operation of B-767-200ER and -30QER aircraft. It is assumed lhat an equal distribution
between the two aircraft models exists.
9 Refers to B-767-300ER aircraft. GE combined the number of aircraft in operation of B-767-200ER and -300ER aircraft. It is assumed that an equal distribution between the two
aircraft models exists.
10 Source of engine information is Modem Commercial Aircraft. Green, W., J. Mowinski, and G. Swanborough, 1987. Percent of aircraft assumed 100%.
11 Assumed EMB-110 aircraft.
12 Assumed MD-80 aircraft.
13 Source of engine information is Modern Commercial Aircraft. Percent of aircraft unknown.
14 Source of engine information is Modem Commercial Aircraft. Engine refers to METRO in aircraft. Percent of aircraft unknown.
13 Source of engine infonnaiion is Modem Commercial Aircraft. Engine refers to METRO EDA aircraft. Percent of aircraft unknown.
-------
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
155
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TABLE 5-3: ALTERNATIVE SOURCE OF EMISSION DATA
FOR SOME AIRCRAFT ENGINES'
Manufacturer
Engine Model
Source for
Emissions Data2
GE
CF6-6
CF6-50
CT7-5A
CT7-5A2
CT7-7E
CF6-6D
CF6-50E/CI/E1/C2/E2
CT7-5
CT7-5
CT7-5
GE (SCNECMA)
CFM56-2
CFM56-2-C1
CFM56-5A
CFM56-2B
CFM56-2B
CFM56-5A1
P&W
RR
JT3D series
JT8D-7D
JT8D-15B
JT9D-3A
JT9D-7A-SP
JT9D-7AH
JT9D-20
JT9D-70A
PW4060
RB2U-535E5
RB211-535F5
TRENT 600 series
TRENT 700 series
SPEY MK506
SPEY MK555-15
SPEY MK555-15P
SPEY MK555-15H
SPEY MK512
TAY MK651
Contact manufacturer3
JT8D-7/7A/7B
JT8D-15
Contact manafacturer
JT9D-7F/7A
JT9D-7F/7A
IT9D-7F/7A
JT9D-70/59/7Q
PW4460
Contact manufacturer*
Contact manufacturer
Contact manufacturer
Contact manufacturer
Contact manufacturer
SPEY MK555
SPEY MK555
SPEY MK555
Contact manufacturer
Contact manufacturer
Dart 514-7
Dart 528-7E
Dart 532-7
Dart 532-7N
Dart 532-7P
Dart 532-7R
Dart 535-7R
Dart 536-7E
Dart 542-4
Dart 542-10J
Dart 542-10K
Dart 552-7R
Dart RDa7
Dart RDa7
Dart RDa7
Dart RDa7
Dart RDa7
Dart RDa7
Dart RDa7
Dart RDa7
Dart RDalO
Dart RDalO
Dart RDalO
Dart RDa7
156
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TABLE 5-3: ALTERNATIVE SOURCE OF EMISSION DATA
FOR SOME AIRCRAFT ENGINES1
(Concluded)
1 FAA Aircraft Engine Emission Database does not identify these alternative emission factors. A manual
adjustment to the database output may be required
2 As recommended by engine manufacturers.
' For information, contact the Office of Certification & Airworthiness, Commerical Engine Business. United
Technologies Pratt & Whitney. 400 Main Street, East Hartford, Connecticut 06108, 203/565-2269.
1 For information, contact Manager Project Combustion. Rolls Royce pic. P.O. Box 31, Derby DE2 88J
England. Telephone - 0332 242424.
157
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TABLE 5-4; MODAL EMISSION RATES - CIVIL AIRCRAFT ENGINES1
Mode 1-Se lies
Manufacturer Power Emission Rales (lb/1000 lb)
Rated Dry Output Mode Setting Fuel Flow HC CO NOx S023 Particulate
(10001b thrust) (Ib/min)
501D22A4 Takeoff 100% 39.60 0.28 2.04 8.88 0.54
All. Climbout 85% 36.63 0.89 2.06 9.22 0.54
Approach 30% 19.00 1.96 5.10 7.49 0.54
Taxi/Idle 7% 10.17 17.61 43.61 3.52 0.54
0-2004 Takeoff 100% 0.75 20.81 974.10 4.87 0.11
Con Climbout 85% 0.75 20.81 974.10 4.87 0.11
Approach 40% 0.43 33.22 1187.84 1.14 0.11
Taxi/Idle 7% 0.14 29.00 644.42 1.58 ' 0.11
TSKkjeod Takeoff 100% 2.22 9.17 1081.95 2.71 0.11
Con Climbout 85% 1.66 9.55 960.80 4.32 0.11
Approach 40% 1.02 11.31 995.08 3.77 0.11
Taxi/Idle 7% 0.19 138.26 592.17 1.91 0.11
CF6-6D Takeoff 100% 229.63 0.30 0.50 40.00 0.54
GE Climbout 85% 189.29 0.30 0.50 32.60 0.54
39.3 Approach 30% 64.01 0.70 6.50 11.40 0.54
Taxi/Idle 7% 22.86 21.00 54.20 4.50 0.54
CF6-45 Takeoff 100% 281.22 0.10 1.00 30.60 0.54
GE Climbout 85% 234.13 0.10 1.30 26.60 0.54
45.6 Approach 30% 80.03 0.70 8.20 10.50 0.54
Taxi/Idle 7% 26.72 32.70 59.20 3.90 0.54
CF6-45A/A2 Takeoff 100% 268.12 0.09 0.43 25.45 0.54
GE Climbout 85% 219.97 0.14 0.54 21.61 0.54
45.6 Approach 30% 78.31 0.35 5.01 9.36 0.54
Taxi/Idle 4% 21.56 2.72 24.04 3.40 0.54
CF6-50E/C1/E1/C2/E2 Takeoff 100% 321.17 0.60 0.50 36.50 0.54
GE Climbout 85% 254.63 0.70 0.30 29.60 0.54
51.8 Approach 30% 87.86 1.00 5.70 9.70 0.54
Taxi/Idle 3% 22.24 49.30 81.30 2.40 0.54
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TABLE 5-4: MODAL EMISSION RATES - CIVIL AIRCRAFT ENGINES1 (Continued)
Model-Series
Manufacturer^ Power Emission Rates (lb/1000 lb)
Rated Dry Output Mode Setting Fuel Flow HC CO NOx SOj'* Particulate
(10001b thrust) (Ib/min)
CF6-80A Takeoff 100% 283.73 0.29 1.00 29.80 0.54
GE Climbout 85% 237.44 0.29 1.10 25.60 0.54
46.9 Approach 30% 81.35 0.47 3.10 10.30 0.54
Taxi/Idle 4% 19.84 6.29 28.20 3.40 0.54
CF6-80AI Takeoff 100% 283.73 0.29 1.00 29.80 0.54
QE Climbout 85% 237.44 0.29 1.10 25.60 0.54
46.9 Approach 30% 81.35 0.47 3.10 10.30 0.54
Taxi/Idle 4% 19.84 6.29 28.20 3.40 0.54
CF6-80A2 Takeoff 100% 298.15 0.30 1.00 29.60 0.54
GE Climbout 85% 249.34 0.37 1.10 26.60 0.54
48.6 Approach 30% 84.79 0.45 2.80 10.80 0.54
Taxi/Idle 4% 19.84 6.28 28.20 3.40 0.54
CF6-80A3 Takeoff 100% 298.15 0.30 1.00 29.60 0.54
GE Climbout 85% 249.34 0.37 1.10 26.60 0,54
48.9 Approach 30% 84.79 0.45 2.80 10.80 0.54
Taxi/Idle 4% 19.84 6.28 28.20 3.40 0.54
CF6-80C2A1 Takeoff 100% 317.46 0.08 0.56 32.22 0.54
GE Climbout 85% 258.34 0.09 0.54 24.85 0.54
57.9 Approach 30% 84.13 2.00 2.19 9.76 0.54
Taxi/Idle 7% 26.32 9.19 42.24 3.99 0.54
CF6-80C2A2 Takeoff 100% 280.03 0.14 0.58 27.90 0.54
GE Climbout 85% 230.82 0.11 0.56 20.71 0.54
52.5 Approach 30% 76.72 0.25 3.04 9.52 0.54
Taxi/Idle 7% 25.00 10.74 46.65 3.91 0.54
CF6-80C2A3 Takeoff 100% 325.00 0.08 0.59 34.44 0.54
GE Climbout 85% 264.95 0.10 0.57 25.45 0.54
58.9 Approach 30% 85.85 0.21 2.15 10.01 0.54
Taxi/Idle 7% 26.72 9.21 42.18 3.96 0.54
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TABLE 5-4: MODAL EMISSION RATES - CIVIL AIRCRAFT ENGINES1 (Continued)
Model-Series
Manufacturer- Power Emission Rates (lb/1000 lb)
Rated Dry Output Mode Setting Fuel Flow HC CO NOx SOjJ Particulate
(10001b thnist) (lb/min)
CF6-80C2A5 Takeoff
GE Gimbout
60,1 Approach
Taxi/Idle
100% 341.40 0.07
85% 275.40 0.08
30% 90.87 0.20
7% 27.38 8.99
0.52 34.38 0.54
0.52 22.86 0.54
1.93 9.11 0.54
41.65 3.79 0.54
CF6-80C2BI Takeoff
GE Climbout
56.0 Approach
Taxi/Idle
100% 302.25 0.08
85% 247.75 0.09
30% 81.48 0.21
7% 25.93 9-46
0.58 28.11 0.54
0.55 21.26 0.54
2J7 8.83 0.54
43.22 3.73 0.54
CF6-80C2B1F Takeoff
GE Climbout
57.2 Approach
Taxi/Idle
100% 311.25 0.08
85% 253.04 0.09
30% 83.60 0.20
7% 27.12 9.68
0.52 28j06 0.54
0.52 21.34 0.54
2.19 8.97 0.54
43.71 3.74 0.54
CF6-80C2B2 Takeoff
GE Climbout
52.0 Approach
Taxi/Idle
100% 281.88 0.08
85% 232.94 0.10
30% 76.32 0.22
7% 25.40 11.17
0.57 23.89 0-54
0.55 18.65 0-54
2.65 8.77 0.54
48.02 3.70 0.54
CF6-80C2B4 Takeoff
GE Climbout
57.2 Approach
Taxi/Idle
100% 321.43 0.08
85% 262.17 0.09
30% 85.98 0.21
7% 26.32 9.74
036 29.20 0.54
0.54 21.80 0.54
2.33 8.90 0.54
43.91 3.67 0.54
CF6-80C2B6 Takeoff
GE Climbout
60.1 Approach
Taxi/Idle
100% 341.14 0.07
85% 275.27 0.08
30% 90.74 0.20
7% 27.38 8.99
0.52 30.81 0-54
0.52 22.94 0.54
1.93 9.11 0.54
41.66 3.79 0.54
CF6-80C2DIF Takeoff
GE Climbout
60.2 Approach
Taxi/Idle
100% 337.83 0.08
85% 268.39 0.10
30% 85.36 0.21
7% 26.01 9.96
0.52 32.54 0.54
0.53 23.55 0.54
1.98 9.28 0.54
44.41 3.79 0.54
CT7-55 Takeoff
GE Climbout
Approach
Taxi/Idle
100% 13.36 1.00
90% 12.43 1.00
30% 5.95 1.50
7% 1.98 4.00
2.50 13.80 0.54
2.70 1320 0.54
5.30 6.90 0.54
35.40 2.20 0.54
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TABLE 54: MODAL EMISSION RATES - CIVIL AIRCRAFT ENGINES1 (Continued)
Model-Series
Manufacturer2 Power Emission Rates (lb/1000 lb)
Rated Dry Output Mode Setting Fuel Flow HC CO NOx SO^ Particulate
(10001b thrust) (lb/tnin)
CFM56-2A Takeoff
GE (SNECMA) Climbout
24.0 Approach
Taxi/Idle
100% 148.55 0.03
85% 12Z62 0.04
30% 45.64 0.10
7% 17.46 1.17
0.90 21.05 0.54
1.00 17.18 0.54
3.40 8.62 0.54
24.90 4.12 0.54
CFM56-2B Takeoff
GE (SNECMA) Climbout
22.0 Approach
Taxi/Idle
100% 132.54 0.05
85% 110.72 0.08
30% 42.59 0.10
7% 16.27 1.67
0.90 19.06 0.54
0.90 16.30 0.54
3.70 8.14 0.54
29.50 3.66 0.54
CFM56-3 Takeoff
GE (SNECMA) Climbout
20.1 Approach
Taxi/Idle
100% 134.92 0.04
85% 111.51 0.05
30% 44.71 0.10
7% 16.01 1.83
0.90 18.50 0.54
0.90 16.00 0.54
3.50 8.40 0.54
31.00 3.90 0.54
CFM56-3B Takeoff
GE (SNECMA) Climbout
22.0 Approach
Taxi/Idle
100% 150.79 0.04
85% 123.02 0.05
30% 47.62 0.08
7% 17.20 1.25
0.90 20.70 0.54
0.90 17.30 0.54
3.10 8.70 0.54
27.00 4.10 0.54
CFM56-3-B4 Takeoff
GE (SNECMA) Climbout
18.5 Approach
Taxi/Idle
100% 116.40 0.04
85% 96.56 0.05
30% 35.71 0.11
7% 14.55 3.33
0.90 16.60 0.54
1.10 14.50 0.54
4.20 8.00 0.54
38.50 3.90 0.54
CFM56-3C Takeoff
GE (SNECMA) Climbout
23.5 Approach
Taxi/Idle
100% 156.09 0.04
85% 128.31 0.04
30% 44.97 0.09
7% 15.87 2.14
0.90 20.17 0.54
1.00 17.15 0.54
3.20 8.88 0.54
33.40 4.00 0.54
CFM56-5A1 Takeoff
GE (SNECMA) Climbout
25.0 Approach
Taxi/Idle
100% 142.8 0.23
85% 116.40 0.23
30% 39.68 0.40
7% 14.55 1.53
0.83 28.03 0.54
0.87 23.10 0.54
2.47 9.48 0.54
18.00 4.36 0.54
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TABLE 5-4: MODAL EMISSION RATES - CIVIL AIRCRAFT ENGINES1 (Continued)
Model-Series
Manufacturer2 Power Emission Rales (lb/1000 lb)
Rated Dry Output Mode Setting Fuel Flow HC CO NO^ SO^ Particulate
(lOOOtb thrust) (Ib/min)
TFE 731-2 Takeoff 100% 27.12 0.11 1.39 15.25 0.54
Grt Qimbout 85% 22.88 0.13 2.03 13.08 0.54
3.51 Approach 30% 8.86 4.26 22.38 5.90 0.54
Taxi/Idle 7% 3.17 20.04 58.60 2.82 0.54
TFE 731-3 Takeoff 100% 29.76 0.06 1.13 19.15 0.54
Grt Qimbout 85% 24.60 0.07 1.62 16.02 0.54
3.7 Approach 30% 9.52 1.41 15.56 6.92 0.54
Taxi/Idle 7% 3.44 9.04 47.70 3.72 0.54
TPE331-36 Takeoff 100% 7.63 0.11 0.76 12.36 0.54 1.75
Grt Qimbout 90% 6.82 0.15 0.98 11.86 0.54 147
Approach 30% 4.17 0.64 6.96 9.92 0.54 240
Taxi/Idle 7% 1.87 79.11 61.52 2.86 0.54 2.95
ALF 502L-2 Takeoff 100% 52.90 0.02 0.40 13.43 0.54
Lyc Qimbout 85% 42.80 0.02 0.30 12.03 0.54
7.50 Approach 30% 15.50 0.18 3.97 6.47 0.54
Taxi/Idle 7% 6.31 6.65 45.63 3.38 0.54
ALF 502R-3 Takeoff 100% 45.98 0.06 0.43 11.20 0.54
Lye Qimbout 85% 38.10 0.05 0.50 9.94 0.54
6.69 Approach 30% 13.58 0.29 8.43 6.15 0.54
Taxi/Idle 7% 5.71 6.51 44.67 3.30 0.54
ALF 502R-5 Takeoff 100% 47.37 0.06 0.30 13.53 0.54
Lyc Qimbout 85% 39.09 0.05 0.25 10.56 0.54
6.96 Approach 30% 13.68 0.22 7.10 13.53 0.54
Taxi/Idle 7% 5.40 5.39 40.93 3.78 0.54
0-3204 Takeoff 100% 1.48 11.78 1077.44 2.19 0.11
Lyc Qimbout 85% 1.11 12.38 989JI 3.97 0.11
Approach 40% 0.78 19.25 1221.51 0.95 0.11
Taxi/Idle 7% 0.16 36.92 1077.00 0.52 0.11
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TABLE 5-4: MODAL EMISSION RATES - CIVIL AIRCRAFT ENGINES1 (Continued)
Model-Scries
Manufacturer2 Power Emission Rates (lb/1000 lb)
Rated Dry Output Mode Setting Fuel Flow HC CO NOx S02i Particulate
(10001b thrust) (lb/min)
JT8D-15A Takeoff
P&W Oimbout
15.5 Approach
Taxi/Idle
100% 147.49 0.25
85% 118.45 0.33
30% 41.27 0.65
7% 18.15 229
1.08 18.10 0.54
1.20 13.90 0.54
2.90 6.60 0.54
12.43 3.10 0.54
JT8D-177 Takeoff
P&W Climboul
16.0 Approach
Taxi/Idle
100% 164.68 0.66
85% 131.88 0.75
30% 46.83 1.86
7% 19.44 9.37
0.75 19.30 0.54
1.01 15.26 0.54
8.13 6.23 0.54
29.56 3.29 0.54
JT8D-17A Takeoff
P&W Climboul
16.0 Approach
Taxi/Idle
100% 155.16 0.25
85% 123.60 0.30
30% 43.70 0.64
7% 18.53 2.02
1.07 19.10 0.54
1.16 14.30 0.54
2.88 6.70 0.54
12.46 3.20 0.54
JT8D-17AR Takeoff
P&W Oimbout
17.4 Approach
Taxi/Idle
100% 180.56 0.21
85% 138.49 0.27
30% 47.28 0.55
7% 19.54 1.33
0.93 24.50 0.54
1.08 16.00 0.54
2.68 8.00 0.54
10.70 3.20 0.54
JT8D-17R Takeoff 100% 187.44 0.21 0.95 25.30 0.54
P&W Climboul 85% 145.90 0.27 1.03 17.60 0.54
17.4 Approach 30% 49.67 0.53 2.54 840 0.54
Taxi/Idle 7% 20.50 0.95 9.43 3.30 0.54
JT8D-209 Takeoff
P&W Climbout
19.2 Approach
Taxi/Idle
100% 157.54 0.35
85% 130.00 0.50
30% 47.51 1.69
1% 17.24 4,03
1.03 22.80 0.54
1.40 19.00 0.54
4.37 8.80 0.54
14.10 3.50 0.54
JT8D-217/217A/217C Takeoff
P&W Climbout
20.8 Approach
Taxi/Idle
100% 174.60 0.28
85% 142.59 0.43
30% 50.70 1.60
7% 18.15 3.33
0.80 25.70 0.54
1.23 20.60 0.54
4.17 9.10 0.54
12.27 3.70 0.54
JT8D-219 Takeoff
P&W Oimbout
21.7 Approach
Taxi/Idle
100% 179.10 0.27
85% 143.52 0.42
30% 50.49 1.59
7% 17.78 3.48
0.73 27.00 0.54
1.20 20.80 0.54
4.07 9.13 0.54
12.63 3.60 0.54
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TABLE 5-4: MODAL EMISSION RATES - CIVIL AIRCRAFT ENGINES1 (Continued)
Model-Series
Manufacturer^ Power Emission Rales (lb/1000 lb)
Rated Dry Output Mode Setting Fuel Flow HC CO NO, SOp Particulate
(10001b thrust) (Ib/min)
JT9D-70/59/7Q Takeoff
P&W Climbout
51.1 Approach
Taxi/Idle
100% 323.00 0.20
83% 264.50 0.20
30% 90.00 0.30
7% 31.35 12.00
0.20 31.60 0.54
0.20 25.60 0.54
1.70 7.80 0.54
53.00 3.00 0.54
PW2037 Takeoff
P&W Climbout
37.6 Approach
Taxi/Idle
100% 203.44 0.05
85% 167.46 0.06
30% 52.78 0.21
7% 18.65 2.26
0.40 31.10 0.54
0.41 24.80 0.54
2.30 10.30 0.54
23.10 440 0.54
PW2040 Takeoff
P&W Climbout
40.8 Approach
Taxi/Idle
100% 241.01 0.03
85% 191.54 0.04
30% 65.21 0.18
7% 20.50 2.36
0.20 47.70 0.54
0.20 27.70 0.54
2.60 11.00 0.54
23.60 4.40 0.54
PW20JI Takeoff
P&W Climbout
42.8 Approach
Tixi/Idle
100% 253.57 0.03
85% 203.18 0.04
30% 68.39 0.16
7% 21.03 2.23
0.20 37.00 0.54
0.20 29.00 0.54
2.50 11.00 0.54
23.10 4.50 0-54
PW4056/4156 Takeoff
P&W Climbout
55.9 Approach
Taxi/Idle
100% 309.79 0.06
85% 255.29 0.01
30% 87.04 0.13
7% 27 JI 1.92
0.44 28.10 0.54
0.57 22.90 0.54
2.00 11.60 0.54
21.86 4.80 0.54
PW4152 Takeoff
P&W Climbout
51.9 Approach
Taxi/Idle
100% 287.96 0.13
85% 236.11 0.16
30% 78.44 0.15
7% 23.41 0.74
0.12 26.90 0.54
0.17 22.70 0.54
1.09 11.10 0.54
12.76 4.90 0.54
PW4158 Takeoff
P&W Climbout
57.9 Approach
Taxi/Idle
100% 328.18 0.09
85% 265.08 0.02
30% 90.21 0.14
7% 27.91 1.78
0.40 30.20 0.54
0.54 23.70 0.54
1.88 11.80 0.54
20.99 4.80 0.54
PW4460 Takeoff
P&W Climbout
59.9 Approach
Taxi/Idle
100% 350.13 0.10
85% 275.80 0.03
30% 92.99 0.14
7% 28.17 1.66
0.37 32.80 0.54
0.51 24.70 0.54
1.78 12.00 0.54
20.32 4.90 0.54
-------
TABLE 5^: MODAL EMISSION RATES - CIVIL AIRCRAFT ENGINES1 (Continued)
Model-Series
Manufacturer^ Power Emission Rales (lb/1000 lb)
Rated Dry Output Mode Setting Fuel Flow HC CO NGX SOj3 Particulate
(10001b thrust) (Ib/min)
JT15D-I Takeoff
P&WC Climbout
2.39 Approach
Taxi/Idle
100% 19.58 0.01
85% 16.40 0.01
30% 6.75 4.43
7% 3.04 50.50
2.65 7.60 0.54
3.50 6.77 0.54
40.50 3.44 0.54
132.00 1.75 0.54
JTI5D-4 Takeoff
P&WC Climbout
2.72 Approach
Taxi/Idle
100% 22.45 0.09
85% 18.92 0.19
30% 7.80 5.15
7% 3.45 40.00
2.10 9.23 0.54
3.18 8.56 0.54
32.00 5.29 0.54
97.00 2.63 0.54
PT6A-276 Takeoff
P&WC Climbout
Approach
Taxi/Idle
100% 7.08 0.00
90% 6.67 0.00
30% 3.58 2.19
7% 1.92 50.17
1.01 7.81 0.54
1.20 7.00 0.34
23.02 8.37 0.54
64.00 2.43 0.54
PT6A-414 Takeoff
P&WC Gimbout
Approach
Taxi/Idle
100% 8.50 1.75
90% 7.88 2.03
30% 4.55 22.71
7% Z45 101.63
5.10 7.98 0.54
6.49 7.57 0.54
34.80 4.65 0.54
115.31 1.97 0.54
Dart RDa7 Takeoff
RR Gimbout
Approach
Taxi/Idle
100% 23.55 1.00
85% 20.77 1.10
30% 10.77 3.00
7% 6.84 23.90
3.20 5.60 0.54
3.50 4.50 0.54
33.30 0.90 0.54
91.40 0.70 0.54
Dart RDalO Takeoff
RR Gimbout
Approach
Taxi/Idle
100% 28.17 0.00
85% 22.49 0.00
30% 10.44 0.00
7% 6.96 8.90
2.20 4.30 0.54
3.00 3.90 0.54
23.20 2.20 0.54
41.40 1.60 0.54
M45H-01 Takeoff
RR Gimbout
7.28 Approach
Taxi/Idle
100% 65.87 0.75
85% 55.03 0.74
30% 19.31 7.40
7% 7.01 59 JO
6.20 11.50 0.54
7.90 9.30 0.34
51.00 3.60 0.54
178.40 1.50 0.54
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TABLE 5-4: MODAL EMISSION RATES - CIVIL AIRCRAFT ENGINES1 (Concluded)
Model-Series
Manufacturer" Power Emission Rates (lb/1000 lb)
Rated Dry Output Mode Setting Fuel Flow HC CO NO^ SO^ Particulate
(10001b thrust) (lb/min)
RB.2I I-535C Takeoff
RR Climbout
36.7 Approach
Taxi/Idle
100% 238.10 0.25
85% 194.45 0.14
30% 71.43 0.44
7% 26.46 1.44
0.70 33.71 0.54
0.27 24.89 0.54
0.84 6J7 0.54
18.79 3.44 0.54
RB.211-535E4 Takeoff
RR Climbout
39.5 Approach
Taxi/Idle
100% 246.03 0.69
85% 199.74 0.94
30% 75.40 1.33
7% 25.13 2.85
1.01 52.70 0.54
1.23 36.20 0.54
1.71 7 JO 0.54
15.44 4-30 0.54
SPEYMK511 Takeoff
RR Climbout
11.3 Approach
Taxi/Idle
100% 117.59 0.98
85% 96.03 1.32
30% 36.91 7.23
7% 15.74 56.73
1.81 23.27 0.54
2.06 19.18 0.54
20.30 7.94 0.54
97.96 1.48 0.54
SPEYMK511-8 Takeoff
RR Climbout
11.3 Approach
Taxi/Idle
100% 117.86 0.09
85% 96.03 0.12
30% 36.77 0.18
7% 16.80 3.69
0.12 22.70 0.54
0.63 17.30 0.54
2.65 7.20 0.54
31.77 3.60 0.54
SPEY MK5558 Takeoff
RR Climbout
9.89 Approach
Taxi/Idle
100% 73.50 0.74
85% 60.13 1.27
30% 22.66 5.43
7% 11.74 71.84
0.41 19,61 0.54
0.16 13.07 0.54
17.96 6.12 0.54
74.68 2.26 0J4
TAY MK620-15/MK611-8 Takeoff
RR Climbout
13.8 Approach
Taxi/Idle
100% 100.53 0.80
85% 83.33 0.30
30% 30.42 0.90
7% 14.55 3.40
0.70 21.10 0.54
0.80 16.80 0.54
3.90 5.70 0.54
24.10 2.50 0.54
TAY MK650' Takeoff
RR Climbout
15.1 Approach
Taxi/Idle
100% 115.61 0.40
85% 94.58 0.40
30% 33.60 0.90
7% 15.74 3.30
1.70 19.80 0.54
2.00 16.30 0.54
6.50 4.60 0.54
33.80 1.70 0.54
-------
TABLE 5 4: MODAL EMISSION RATES - CIVIL AIRCRAFT ENGINES1
(Concluded)
* SOURCE: ICAO Engine Exhaust Emissions Databank (ICAQ Committee on Aviation Ecvirmuni'iildj Protection, Woildng Gioup 3 Meeting,
Manchamn, Aland., October 1989), unless otherwise noted.
2 MANUFACTURERS: All. - Allison, Con - Teletlyne/Continental, GE - General Electric, Git - Garrett AiRescarch, Lyc - Avco/Lycotning,
P&W - Prjic & Whitney, P&WC - Pran &. Whitney Canada, RR - Rolls-Royce
' SOj emissions based oo national avenge sulfur content of aviation Fuels from Aviation Turbine Fuels. 1989. Dickson, Cheryl L. and Paul W.
Woodward, March, 1990, NIPER Report Number N1PER-164 PPS, Natioaal Institute for Petroleum and Energy Research, 1IT Research Institute,
Bartlesville, OUahoma.
4 Source of data is AP-42, Compilation of Air Pollutant Emission Factor Volume D: Mobile Sources. U.S. Envitonmenml Protection Agency, Ann
Arbor, Michigan. September, 1985. (Aircraft data from February 1980).
3 Source of engine data is General Electric Office of Combustion Technology, GE Aircraft Engines, One Neumann Way MD A309, Cincinnati, Ohio
45215-6301, 513/774-4438.
6 Source of data is AP-42. Source of Particulate data is AP-42 Reference 4 (M. Piatt, et al„ The Potential Impact of Aircraft Emissions upon Air
Quality. APTD-1085, US Environment a] Protection Agency, Research Triangle Park, NC, December 1971). The indicated reference does not specify
series number for this model engine.
7 Source of engine data is ICAO, ICAO Engine Exhaust Emissions Databank. Data arc sales weighted averages of two versions ol this engine. Tl>e
basis is 93% high emission combustois and 7% low emission contbusiorc.
* Source of engine data is ICAO, [CAP Engine Exhaust Emission* n.nahanir Data are sales weighted averages of two versions of this engine. Hie
basis ls 77% high emission combustois arid 23% low emission combnstois.
® Source of engine data is Rolls Roycc Combustion Research Department, Rolls Royce pic. P.O. Box 31, Deity DS2 88J England. Telephone - 0332
242424.
-------
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.
171
-------
TIMapp_(. = 4 X (H/3000) (5-1)
TIMclm.(. = 2.2 X [(H-500)/2500] (5-2)
TlMapp-c " t'1116 'n approach mode for commercial aircraft, in minutes
TIMclm.(. - 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 = _(TlM,k)X(FF,k/1000)X(El1|k)X(Ne,) (5-3)
Ejj = 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)
NE| = number of engines used on aircraft type j (from Table 5-2)
172
-------
Calculate Total Emissions for All Commercial Aircraft
Eri(C, = T. (Ey) X (LTO|) (5-4)
EIi(n - 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)
LTO| - 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 engine-
specific 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.
173
-------
TABLE 5-5: GENERAL AVIATION AIRCRAFT TYPES AND ENGINE MODELS'
No. of
No, of
No. of
Aircraft
Seats
Engines
Aircraft3
Ensine
Mnf
Piston
Bellanca 7GCBC Seaplane
3
1
567
0-320
Lyc
Cessna 150
2
1
13760
0-200
Con
Cessna 337 scries
6
2
1151
TSIO-360C
Con
Piper PA-18 series
2
1
3590
0-320*
Lyc
Turbojet
Aerospatiale SN601 Corvette
16
2
1
JT15D-4
PWC
Canadair CL-600 Challenger
13
2
61
ALF502L-2
Lyc
Dassault B/egue Falcon 10
7
2
126
TFE731-2
Grt
Dassault Bregue Falcon 50
10
3
125
TFE731-3
Gn
Gales Learjet 35/36
10
2
67
TFE73I-2-2B
Grt
Gates Learjet 35 A/36A
10
2
342
TFE731-2-2B
Grt
Israel Aircraft LAI 1124
10
2
151
TFE731-3
Grt
Learjet 31
10
2
6
TFE731-2
Grt
Mitsubishi MU-300 series
11
2
75
JT15D-4
PWC
Turboprop
tie Havilland DHC-6-300
22
2
40
PT6A-27
PWC
Fairchild PLIahis PC6 series
8
1
8
PT6A-275
PWC
Helio Aircraft HST-550A Stallion
10
1
1
PT6A-27
PWC
Piper PA-42 series
11
2
105
PT6A-41®
PWC
1 Source of aircraft, corresponding engines, and number of engines is FAA Aircraft Engine Emission Database (FAEED), U.S.
Department of Transportation, Federal Aviation Administration, Office of Environment and Energy, 1991. Source of number of
seals, aircraft type, and number of aircraft is Census of U.S. Gvil Aircraft, U.S. Department of Transportation, Federal Aviation
Administration, Office of Management Systems, Calendar Year 1989.
J No. of Aircraft refers to Total U.S. Registered Aircraft as of December 31, 1989.
' ENGINE MNF ABBREVIATIONS: Con - Teledyne/Continemal, GE - General Electric, Gft - Garrett AiResearch,
Lyc - Avco/Lycoming, P&W - Pratt Sc. Whitney. PWC - Pratt & Whitney Canada, RR - RoUs-Royce
4 Engine refers to a PA-18-150 Super aircraft.
5 Engine refers to a PC6/B2H2 aircraft.
6 Engine refers to a PA-42 Cheyenne aircraft.
174
-------
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,; = 6 X (H/3000) (5-5)
TIMdm.(; = 5 X [(H-500)/2500] (5-6)
TIMapP-(; _ t'me 'n the approach mode, in minutes
TIMclm.(; - 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.
Ejj = £ (TIMjk) X (FFjk/1000) X (EI1|k) X (Ne,) (5-7)
Eji = 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)
NE, = number of engines used on aircraft type j (from Table 5-5)
175
-------
Calculate Total Emissions for All General Aviation or Air Taxi Aircraft
(5-8)
F
tl(Ci)
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)
LTO,
total number of LTO cycles for aircraft typej, 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.
Since air taxis have fewer of the smallest engines in their fleet and more turboprop and
turbojet engines, their emission factors are somewhat different.
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
244 Memorandum from S. Webb to R. Wilcox. "General Aviation Generalized Emission Indexes." June 10. 1991.
HC 0.394 pounds per LTO
CO 12.014 pounds per LTO
NOx 0.065 pounds per LTO
S02 0.010 pounds per LTO
HC 1.234 pounds per LTO
CO 28.130 pounds per LTO
NOx 0.158 pounds per LTO
S02 0.015 pounds per LTO
176
-------
TABLE 4. FISCAL YEAH 1M»
AT AWPOW11 WTW FAA^PiWATPT^M^CCOWWOLTOWHII
am rr stats and avutkmi
LAKf GHARlfS
ITINERANT OPERATWNS-
LOCAL OPERATIONS
TOTAL OPERATIONS-
ItW^BMUT OPOttTXJNS-
LOCAL OPERATO*
TOTAL OPERATOR—
NEW ORLEANS LMVMONT
mMSUMT 0W«AT10NS_
LOCAL OPERATIONS
TOTAL OPERATOO-
NCW OWJANS MOttAWT
ITIttfRAHT OPERATIONS-
LOCAL OPERATXXS.
TOTAL OPERATIONS-
atmcvcPORT
ITINERANT OP^ATIONS-
LOCAL OTOIATKK*
TOTAL OPERATIONS—
SHAEVEPORT DOWNTOWN
mNERAMT OPERATWNS-
LOCAL OPERATIONS-
TOTAL OPERaTKJNS-
*TATt total loumuna
ITINERANT 0PWATWN9_
LOCAL OPERATIONS
TOTAL
SANGO* INTERNATIONAL
ITINERANT OPERATION-
LOCAL OPERATIONS -
TOTAL OPERATION#.
PORTLANO
ITINERANT OPERATIONS..
LOCAL OPERATIONS
TOTAL OPERATIONS
ST ATI TOTAL I
ITINERANT OPERATIONS -
LOCAL OPERATIONS -
TOTAL OPERATIONS.
MARYLAND
BALTIMORE WASHINGTON MR
ITINERANT OPERATIONS
LOCAL OPERATIONS.
TOTAL OPERATIONS-
CAMP SPRINGS ANOREWS AFS
ITINERANT O^RATIONS
LOCAL OPERATIONS
TOTAL OPERATIONS—
MAG&tSTOMN
mNERAWT OPERATIONS.
LOCAL OPERATIONS ..
TOTAL OPSUTIO»*~
STATE TOTAL MARYLAND
ITINERANT OPERATIONS
LOCAL OPERATIONS
TOTAL operations
BEDFORD
ITINERANT (
LOCAL OPERATIONS.
TOTAL OPBUTIONS-
SEVERLY MUNICIPAL
ITINERANT OTOWTIONS.
LOCAL OPERATIONS
TOTAL operations
(UXI
(MLUI
(NEW)
ISHV)
<0TX>
(8GRI
(AOW)
(MORI
Tom
(SCO)
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BOSTON LOGAN
ITINERANT OPERATIONS.
LOCAL OPBWTKJNS
TOTAL OPERATIONS
(80S)
EEEJ
nasr
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114432
10179*
31*17»
S1117
1433*
24300
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56125
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100
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24
FIGURE 5-5: REPRODUCTION OF A PAGE OF TABLE 4 FROM REFERENCE 3
177
-------
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.
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 Sen ice Center. RDUS. Tvndall AFB. Florida 32403.
178
-------
TABLES-* MIIJFARYAIRCRAFTTTFESAND 1NCHNEMODHJ1
No. Of infta*
Aitomft W ammo? Ebbbs MM EsSaC
Boeing B$2 H Stfliofcxurss
TP
USAP
8
mw-j
m
Boons JBC~13$C
TF
USAP
4
imM
pw
Pwgtaa Ad Skytame
Tl
vm
1
KNNtt
pw
Doofi«.AJMaytort1
Tl
r
2
JS3*4M
PW
Genoa! Oynwoi F-16 HMi Moo/
IF
ISAP
1
fioiure
PW
TF
USAFA.1SN
1
PW
Gmonai M iiraia*
Tl
vm
2
B2*tt
PW
G»wnm«> E*2 Hiwtrye*
TP
uam
2
156*. 16
AIL
fiMM FA.6B Nwta*
Tl
USMQUSN
2
m-p-4«
PW
CtwHuao F-14 ToMMM*
TF
USN
2
TFHM>-4I2A
PW
Lcaij«Co*pC-2t-A
TP
USAF
2
TPE 73I-2-2B
Gtl
t AffciMMMt jjL< vping*
TF
USN
2
VPHOUtQ
G£
LTV AiiaaA A-7B Cmkbt Q
TP'
USN
I
TF41-A-2
All,
McDonnell Douglas AV-g5
TP
USMC
1
P402
&R
McDocneU PougJbM F-* Phantom If
TJ
USAF/USN
2
J7W3E.10B
GE
McDonnell Dotagjas F-4B Phantom If
u
USMC/USN
2
J79-GE-8D
Gfi
McDmnrfl Dwijtas F-iH Ptootwn U*
TJ
USN
2
J?K®4D
GE
McDoaoell Dow|lai F-45 Rnnlon H
n
imf
2
ITMB-IO
GE
f** I5C/P
IF
USAF
2
R9WW-IOO
PW
McDoodcU Dowglas flfA-lt Hornet*
IF
USN
2
WM-GB4m
GE
MeOwot* Omtfm 1MB Pfaunon If
11
USMC
2
mmw
GE
NortwyF-SETtiwO
TJ
USAflfUSN
2
m-csai
OE
Nontet? "Hysc 11
TJ
USAPJUSX
2
J*3M3&tl
GE
Tl
USAF
2
JlMME*!
GE
Rncfewd OV-lO Bleach
TP
USAFASMC
2
T7WJ-I2A
Gfl
VoojINi A7Coca.tr
W
USAfifUSN
1
TKI-AJ
All
Boeing T-4JA
TF
WAP
2
JTOM
PW
CASA OIOI Anojrl
TP
1
TFB 731-2
Git
FMA Coftkrt* PAMPA 1A.63
TP
1
TPB731-2
Git
GrwnmM) Qui (sot am
TF
USN
2
DanRPa?
RR
McDonnell Douglas D P-15
IF
USAP
1
PIOO-PW-IOO
PW
McDonnell Douglas F-15 OD Eagle
TP
USAF
2
P100-PW.100
PW
/200T
McDoroell D@®s>» F/A-18 Homo'
TF
USN
2
F404-GE-A00
OE
Miisutadn T-S1
TJ
USN
2
JS5-GE.2
CE
-------
TABLE 5-6: MILITARY AIRCRAFT TYPES AND ENGINE MODELS'
(Continued)
Aircraft
Tvoe2
Operator3
No. of
Engines
Engine
Model
Mnf4
Transport
Australia Govt Nomad 22B
TP
2
250B17B
All.
Australia Govt Nomad 24
TP
2
250B17B
All.
BEECH C-12A/B/C
TP
Army/USAF
2
PT6A-41
PWC
Boeing B-747-200
TF
4
JT9D-7R4G2
PW
Boeing C-I35B Stratolifter
TF
USAF
4
TF33-P-5
PW
Boeing E-4A/B NEACP
TF
USAF
4
CF6-50E
GE
Boeing VC-25A
TF
USAF
4
CF6-80C2B1
GE
de Havilland UV-18A
TP
Army
2
FT6A-27
PWC
Fairchild C-26A
TP
NG
2
TPE331
Grt
Gmniman C-1A Trader5
P
USN
2
R-1820
W
Grumman Gulfs tre am
TF
USAF
2
Dart RDa7
RR
LASC Georgia C-141B Starlifter
TF
USAF
4
TF33-P-7
PW
Lockheed C-130E Hercules
TP
4
T56-A-7
All.
Lockheed C-130 Hercules'
TP
4
T56-A-16
All.
Lockheed C-141 Starlifter
TF
USAF
4
TF33-P-7
PW
Lockheed H00 Hercules
TP
4
501D22A
All.
McDonnell Douglas C-9A Nightingale
TF
USAF
2
JT8D-9
PW
McDonnell Douglas C-9B
TF
USN
2
JT8D-9
PW
McDonnell Douglas KC-10A Extender
TF
USAF
3
CF6-50C2
GE
McDonnell Douglas VC-9C
TF
USAF
2
JT8D-9
PW
Utility
BEECH RU-231J
TP
Army
2
PT6A-41
PWC
BEECH UC-12F/M
TP
USMC/USN
2
PT6A-41
PWC
Helicopter
Bell UH-1, AH-15
TS
Army
1
T53-L-11D
Lyc
Boeing Vertol H-46 Sea Knight5
TS
USMC/USN
2
T58-GE-8F
GE
Boeing Venol H-46E Sea Knight*
TS
USMC/USN
2
T58-GE-16
GE
Costruzioni HH-3F
TS
USCG
2
T58-GE-5
GE
Kaman H-2 Seasprite5
TS
USN
2
T58-GE-8F
GE
Sikorsky H-3 Sea King series3
TS
2
T58-GE-8F
GE
Sikorsky H-53 Sea Stallion/
Super Stallion5
TS
3
T64-GE-4I5
GE
Sikorsky HH-3E Jolly Green Giant
TS
USAF
2
T58-GE-5
GE
Sikorsky SH-3E
TS
2
T58-GE-5
GE
Sikorsky SH-3F
TS
2
T58-GE-5
GE
Sikorsky SH-61AA
TS
2
T58-GE-5
GE
-------
TABLE 5-6: MILITARY AIRCRAFT TYPES AND ENGINE MODELS'
(Concluded)
SOURCE: FAA Aire rait Engine Emission Database (FAJEED), (U.S. Department of Transportation, Federal Aviation
Administration. Office of Environment and Energy, 1991) unless otherwise noted.
Source of Type information is "Aviation Week & Space Technology," McGraw-Hill Publication, March 18, 1991.
TYPES: P - Piston, TF - Turbo fan, TJ - Turbojet, TP - Turboprop, TS - Turboshaft
Source of Operator information is Encyclopedia of Modem Military Aircraft. Taylor, Michael, 1987.
OPERATORS: Army, NG - National Guard, USAF - U.S. Air Force, USCG - U.S. Coast Guard. USMC - U.S. Marine Corps.
USN - U S Navy, US - USAF. USCG, USMC, & USN.
ENGINE MANLfFACTURERS: All. - Allison, GE - General Electric, Grt - Garrett AiResearch, Lyc - Avco/Lycoming,
PW - Pratt & Whitney, W - Curtis Wright
Source of aircraft and corresponding engine information is Example of an Air Base Emissions Inventory for the Couptv of San
Diego (1987). Aircraft Environmental Support Office, AESO Report No. 2-91, San Diego, California, March 1991.
Sources: Engines - Summary Table of Gaseous and Particulate Emissions from Aircraft Engines. Aircraft Environmental
Support Office, AESO Report No. 6-90, San Diego, California, June 1990.
Aircraft, Type, and No. of Engines - "Aviation Week & Space Technology," McGraw-Hill Publication, March 18.
1991.
Classification and Operator - Encyclopedia of Modem Military Aircraft. Taylor, Michael, 1987.
Source: "Aviation Week & Space Technology," McGraw-Hill Publication, March 18, 1991.
181
-------
13
?
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-------
TABLE 5-7: MODAL EMISSION RATES - MILITARY AIRCRAFT ENGINES1 (Continued)
Model-Series
Manufacturer^ Power Emission Rates (lb/1000 lb)
Rated Dry Output Mode Selling Fuel Flow HC CO NOx SO^ Paniculate
(10001b thrust) (lb/min)
0-200 Takeoff 100% 0.75 20.81 974.10 4.87 0.11
Con Climbout 75% 0.75 20.81 974.10 4.87 0.11
Approach 30% 0.43 33.22 1187.84 1.14 0.11
Idle 7% 0.14 29.00 644.42 1.58 0.U
T400 CP-400
CP
Takeoff
Climbout
Approach
Idle
Military
Cruise
Fl.idle
Or.idle
6.87
4.72
2.38
2.30
0.11
0.15
7.46
8.98
0.75
2.64
30.71
29.78
6.68
4.90
3.08
3.05
0.54
0.54
0.54
0.54
CF6-50E/CI/
E1/C2/E28
OE
51.79
Takeoff
Climbout
Approach
Idle
100%
83%
30%
3%
321.17
234.63
87.86
22.24
0.60
0.70
1.00
49.30
0.50
0.30
5.70
81.30
36.50
29.60
9.70
2.40
0.54
0.34
0.54
0.54
F404-GE-4007 Takeoff A/B max
GE Climbout IRP
Approach 76%
Idle Gr.idle
473.28 0.13 23.12
134.71 0.31 1.05
109.02 0.35 1.09
10.40 58.18 137.34
9.22 0.54
25.16 0.54 2.81
14.80 0.54 6.10
1.16 0.54 12.38
J79-GE-8D7
GE
Takeoff
Climbout
Approach
Idle
Afterburner
Military
75% rpm
Idle
571.92
I57J5
2533
20.08
0.91
0.14
4.40
16.93
13.25
2.07
30.61
55.70
4.72
10.44
2.98
2.37
0.54
0.54
0.54
0.54
10.67
1534
19.12
J79-GE-I04
OE
Takeoff
Climbout
Approach
Idle
Afterburner
Military
85%
Idle
589.83
163.83
103.17
1833
0,49
1.63
0.66
8.91
17.29
5.29
7.37
43.64
6.82
15.44
11.29
2.91
0.54
0.54
0.34
0.54
8.473
7.90s
10.82s
S2.559
J79-GF.-I0B7 Takeoff Afterburner 583.33 0.52 14.56 4.51 0.54 4.43
GE Climbout 75% Thrust 126.30 1.60 2.74 8.26 0.54
Approach 30% Throat 57.03 2.94 20.04 4.23 0.54 9.50
Idle Idle 20.83 39.19 111.41 1.33 0.54 15.73
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TABLE 5-7: MODAL EMISSION RATES - MILITARY AIRCRAFT ENGINES1
(Concluded)
' SOURCE: Example of an Air Base Emissions Inventory for the County of San Diego (1987) (Aircraft Environmental Support Office, AESO Repon No. 2-91, San
Diego, California. March 1991), tmless otherwise noted
2 MANUFACTURERS: A1I. - Allison, Con - TeledytWCominental. CP - United Aircraft of Canada. GE - General Electric, Grt • Garrett AiResearch, L.yc -
Avco/Lycoming, P&W - Pratt & Whitney, RR - Rolls-Royce, W - Curtis Wright
^ SO, emissions based on notional average sulfur content of aviation fuels from Aviation Turbine Fuels, 1989, Dickson, Cheryl L. and Paul W. Woodward, NEPER Report
Number N1PER-I64 PPS, National Institute for Petroleum and Energy Research, IIT Research Institute, Bartlesville, Oklahoma, March 1990.
4 Source of data is AP-42, Compilation of Aif Pollutant Emission Factors. Volume II: Mobile Sources, U.S. Environmental Protection Agency, Ann Aitior, Michigan,
September. 1983. (Aircraft data from February 1980). Nitrogen oxides reported as N02. HC refers to total hydrocarbons (Volatile orcanics, including unbumcd
hydrocarbons and organic pyrolysis products).
5 Includes all "condensable particulates," and thus may be much higher than solid particulates alone (AP-42).
* Source of data is FAA Aircraft Engine Emission Database (FAEED), U.S. Department of Transportation, Federal Aviation Administration, Office of Environment and
Energy, 1991.
7 Sonrce of data is Summary Tables of Gaseous and Particulate Emissions from Aircraft Engines, Aircraft Environmental Support Office, AESO Report No. 6-90, San
Diego, California, June 1990,
' Source of data is 1CAO Engine Exhaust Emissions Databank. ICAO Committee on Aviation Environmental Protection, Working Group 3 Meeting, Mariehamn. Aland.,
October 1989.
' Includes all "condensable particulates," and thus may be much higher than solid particulate!! alone. Data are interpolated values assumed for calculation^ purposes, in
the absence of experimental data (AP-42).
Particulate data refers to TF34-GE-400A engine.
11 Particulates refer to dry particulates only (AP-42).
12 Source of Particulate data is Tabic 4. Paniculate Mass Emissions From the TF-30-P-414 Engine, Summary Tables of Gaseous and Particulate Emissions from Aircraft
Engines. Aircraft Environmental Support Office, AESO Report No. 6-90, San Diego, California, June 1990.
-------
Adjust Approach and Climbout TIM to Represent Local Conditions
TlMapp_XI = 4 X (H/3000) (5-9)
TIMclm_XI = 1.4 X [(H-500)/2500] (5-10)
TIMapp.XI - time in the approach mode for military aircraft, in minutes
TIMclm.M " t'me 'n 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
Ejj = E(TlM,k)X(FF,k/1000)X(El1|k)X(NE,) (5-11)
Ejj - 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)
NE| - number of engines used on aircraft type j (from Table 5-6)
Calculate Total Emissions for All Military Aircraft
E-iiiM, = £ Ey (5-12)
EIi(XI) - 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)
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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.
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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.
Ejj = E(TlM|k)X(FF|k/1000)X(El1|k)X(NE|k) (5-13)
Eji - 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.
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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.
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Auxiliary
Power Unit
(Shaft HP)
TABLE 5-8: APU'S AND AIRCRAFT MODELS'
Aircraft Model
No. of
Aircraft
COMMERCIAL
Allied-Signal Aerospace Company
Garrett Auxiliary Power Division
GTP 30 Series
Fairchild F-272
GTCP 30 Series
Dassault-Bregue Falcon 7.02
Jet Commander2
GTCP 35-300
Airbus A-3213
GTCP 36 Series
Airbus A320
132
(80 HP)
Aerospatiale ATR-422
Brit. Aero. BAe 146
149
Canadair CL600/CL6012
Dassault-Bregue Falcon 502
Embraer EMB-1202
Fokker F-28
193
Fokker F-100
56
NAMC YS-ll'
Saab Fairchild 3402
GTC 85
Convair CV-5802
GTCP 85 Series
Boeing B-707
206
(200 HP)
Boeing B-727
1,652
Boeing B-737
1,825
Lockheed L-1002
McDonnell Douglas DC-8
300
McDonnell Douglas DC-9
842
McDonnell Douglas MD-80
806
GTCP 331 Series
Airbus A-300-600
85
(143 HP)
Airbus A-310
175
Airbus A-330'
Airbus A-3401
Boeing B-757
328
Boeing B-767
343
Boeing B-777'
GTCP 660
Boeing B-747
671
(300 HP)
TSCP 700
Airbus A-300-B2
52
Airbus A-300-B4
184
193
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TABLE 5-8: APU'S AND AIRCRAFT MODELS1
(Continued)
Auxiliary
Power Unit
(Shaft HP)
Aircraft Model
No. of
Aircraft
(142 HP)
Hamilton Standard
ST-6
Pratt & Whitney
PW 901A
McDonnell Douglas DC-10
McDonnell Douglas MD-11
Lockheed L-1011
Boeing B-747
365
3
226
103
MILITARY5
Allied-Signal Aerospace Company
Garrett Auxiliary Power Division
GTC 36-200
GTCP 36 Series
(80 HP)
GTC 85 Series
GTCP 85 Series
GTCP 660-4
(300 HP)
JFS 100 Series
JFS 190-1
McDonnell Douglas F-18 Hornet
Gulfstream II (VC-llA)
Gulfstream III (C-20A/B)
Lockheed S-3A Viking
Gulfstream I (VC-4A)
Lockheed C-130 Hercules
McDonnell Douglas C-9
Lockheed C-141 StarLifter
Boeing T-43
Boeing E-4 NEACP
Douglas A-4M Skyhawk
Vought A-7D Corsair 11
McDonnell Douglas F-15 Eagle
221
23
254
15
335'
895
194
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TABLE 5-8: APU'S AND AIRCRAFT MODELS'
(Concluded)
SOURCES: Civil - Federal Express Fleet Guide (Federal Express Aviation Services, Inc., January, 1991),
unless otherwise noted.
Military - Reference Guide - Auxiliary Power System,';, Garrett Turbine Engine Company,
Phoenix, Arizona.
SOURCE: Reference Guide - Auxiliary Power Systems, Garrett Turbine Engine Company, Phoenix, Arizona.
New aircraft scheduled to enter production.
No. of Aircraft refers to Airbus A-300 aircraft.
No. of Aircraft refers to the total number of aircraft in the Air National Guard, Air Force Reserve, Air Force,
and Coast Guard inventories.
SOURCES: Air National Guard, Air Force Reserve, Air Force - "AIR FORCE Magazine," Air Force
Association, May 1991.
Coast Guard - United States Coast Guard, 2100 Second Street, SW, Washington, DC 20593-0001,
202/267-0952.
No. of Aircraft refers to 14 A-7 and 321 A-7D aircraft.
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TABLE 5-9: MODAL EMISSION RATES - AUXILIARY POWER UNITS'
Emission Rates (lb/1000 lb)
Model-Series
(Shaft HP at Load)
Mode
Fuel Flow
(lb/min)
HC
CO
NO,
S02
GTC85-72
(200)
Load
3.50
0.13
14.83
3.88
0.54
GTCP100-54
(400)
Load
6.88
0.16
5.89
5.95
0.54
GTPC95-2
(300)
Load
4.88
0.36
3.20
5.65
0.54
T-62T-27
(100)
Load
1.70
7.79
42.77
3.94
0.54
WR27-1
(85)
Load
2.33
0.21
5.66
4.63
0.54
1 SOURCE: Summary Tables of Gaseous and Particulate Emissions from Aircraft Engines (Aircraft Environ-
mental Support Office, AESO Report No. 6-90, San Diego, California, June 1990), unless otherwise noted.
196
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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 1, 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
247 World Jet Airplane Inventory. Boeing. Commercial Airplane Group. Year-End 1990.
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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.24S
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.
VOC
commercial
THC
commercial
X 1.0947
(5-14)
VOC
MILITARY
THC
MILITARY
X 1.1046
(5-15)
24S Memorandum from R. Cook to R. Wilcox. "Exhaust THC to VOC Correction Factors for Aircraft." July.
1992.
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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
VOC(iAPISI()N = THC(;apisI()N X 0.9649 (5-16)
VOC(iA.IVRIJINI: = THC(iA.IVRIJINI:X 1.0631 (5-17)
VOCAmsI(lx = THCAmsI(lx X 0.9649 (5-19)
VOCAI IVRBIN, = THC.VI IVRBIN, X 1.063 1 (5-20)
Alternative. Fleet-Averaue Methodology
VOCGA = THC(;a X 0.9708 (5-18)
VOCA THCa X 0.9914 (5-21)
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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.2MI 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 (S02), 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).
249 The term inventory area can be quite diverse and may refer to an area as large as a multi-state CMS A 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 arc 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 arc 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
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Class II253 and III254 railroads represent the remainder of the rail transportation system and
generally operate within smaller, localized areas.2" 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 1 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, Ml 48105
(313)668-4200
253 Class II railroads arc 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 arc 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 arc covered by Class I railroads.
256 In this cliaptcr. line haul operations include intcrmodal freight service, mixed freight service, and passenger
service.
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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.
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In any given area, there will be only a few active Class 1 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 1 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 1 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 1 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 1 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
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Each Class I railroad is required to report these statistics each year to the ICC in an
annual report entitled "R-lThe R-l 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 Factors25*
Emission Factor
Pollutant (lbs/ual)
HC 0.0211
CO 0.0626
NOx 0.4931
SO,* 0.0360
PM~ 0.0116
* S02 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 1 line
haul locomotives in an inventory area, using the Santa Fe railroad in the State of Illinois.
6.2.2 Class 11 and 111 Line Haul Locomotives
257 The fuel consumption rate will be less if the weights of the locomotives are not included in the calculation.
25s Locomotive Emission Factors for Inventory Guidance Document. Office of Mobile Sources. U.S. EPA. June
1991.
204
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Similar to the recommended method for Class 1 line hauls, emissions from Class 11 and
111 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 11 and 111 railroad companies are not required to file R-l reports, annual fuel
consumption should be obtained directly through interviews or letters with each Class 11 and 111
railroad operating within the inventory area. This approach is sufficient because, unlike Class 1
line haul operations, most Class 11 and 111 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 11 and 111 railroads operating outside the
inventory area, EPA recommends simply allocating the fuel consumption by track length or track
density (GTM). Each Class 11 and 111 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.
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
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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:
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
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Table 6-2. Annual Emissions Per Yard Locomotive
Annual Emissions
Pollutant (lbs/vr)
HC 4,174
CO 7,375
Nox 41,608
SO,* 3,075
PM~ 1,138
S02 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/uallon)
HC 0.0506
CO 0.0894
NOx 0.5044
S02* 0.0360
PM~ 0.0138
* S02 calculated based on a fuel sulfur content of 0.25 percent by weight.
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
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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-
J) .
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).
208
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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 1 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 1 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 1 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 11 and 111 line haul locomotives should be easier than identifying Class 1
line hauls, due to the fact that the former locomotives travel predominantly within a small area.
EPA again recommends contacting each Class 11 and 111 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.
209
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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.
264 When the national roster was calculated, locomotives which might perform both functions were not entered as
indicated here: thus Appendix 6-5 docs not show any overlap of any locomotives.
210
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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 4 4
2 4 7
1 4 7
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.
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
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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 S02 Tailoring Method
The emission factors for S02 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 S02 Emission Factor.
266 It is assumed that all of the elemental sulfur in the fuel is oxidized into SO,
212
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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-ENG1NED 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 (THCnn),
this section illustrates the conversion factor method recommended for converting THCnn 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.
213
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The method for converting THC to VOC was based on the methodology for nonroad
conversion and is as follows:
VOCl.oroMOTIVF = THCfID I.OCOMOTIVF X NMHCfII) IIDDY X VOC IIDDY
THC 1 11) HIM >\" NMHCfIDIIDDV
where
THCnniocoMinivi represents the total hydrocarbon emissions measured from locomotives by
FID,
NMHClll) HDDV
THCfidhi)1)y 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
NMHCud hddv is a VOC correction factor and represents the ratio of VOC to non-
methane hydrocarbons, as emitted by heavy duty diesel vehicles.
Using the same method illustrated in Attachment 3 of the memorandum, EPA determined
that NMHCud 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:
VOCi.ix'omotivf = THCfid I,k omotivf X L07 X 1.0332
1.10
or
VOC i.oroMoTiYi: — THCfid u komotivf X 1.005
267 Springer. 1979 (KI'A-460 3-79-007) (PP. 47.9X)
214
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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, 1L, 1A, KS, LA, MO, NB, NM, OK, TX)
" Burlington Northern Railroad Company
(AL, AR, CA, CO, FL, 1A, ID, 1L, KS, KY, MN, MO, MT, MS, NM, ND, NE, OK, OR,
SD, TN, TX, WA, Wl, WY)
" Chicago and North Western Transportation Company
" Consolidated Rail Corporation (Conrail)
(CT, D C., DE, 1L, IN, KY, MA, MD, Ml, NJ, NY, OH, PA, VA, WV)
" CSX Corporation
CSX Transportation, Inc. (Includes Chessie System and Seaboard System)
(AL, DE, D C., FL, GA, IN, 1L, KY, LA, MD, Ml, 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
(1L, 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
215
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Appendix 6-2
Copy of schedules 750 and 755 from R-l Report for Santa Fe, 1990.
750. CONSUMPTION OF DIESEL FUEL
(Dollars in Thousands)
LOCOMOTIVE
Kind of locomotive service
Diesel
Lin*
No. (a)
Diesel oil (gallons)
tt>)
Lin*
Mo.
1. Freight
304,370,694
1
2. Passenger
2
3. Yard switching
7,522,208
3
4. Total
311,092,902
4
5. COST OF FUtL $(000)
226,890
5
6. Work Train
75,945
6
755. RAILROAD OPERATING STATISTICS - Concluded
Lin*
Ho.
Ctau
Check
Item Description
<•>
Freight
Train
Passenger
Train
(O
Line
No.
6. Grovs Ton-Miles (thousands) (K)
XTLTTXI
xxxrrr
98
6—01 Road Locomotives
24,631,118
98
6—02 Freight Trains, Crs., Cnta., and Caboose
xxxxxx
wttt
99
6-020 Unit Trains
10,345,677
XT T.tHT.
99
100
6-021 Hay Trains
4,002,717
100
101
6-022 Through Trains
136,446,265
zxxxxx
101
102
6-03 Passenger—Trains, Crs., & Cnts.
102
103
6-04 Noa—Revenue
11,215,578
XXXXXX
103
104
6-05 TOTAL (lines 98-103)
186,661,355
104
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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,
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 - 24,63 1,118,000) = 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) = 13,776,3 16 gal
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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/ual) x Fuel Consumption (ual)
2,000
Example for HC: (0.0211 X 13,776,508)/2,000 = 150.16 Tons
218
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Appendix 6-4
Conversions from Locomotive Model to Ermine 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 16-710G3 A
EMD
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Locomotive Engine
Model HP Type
MP 15 AC 1500 12-645E
MP 15 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 16-710G3 A
220
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GE
Locomotive
Model
B23-7
B30-7
B30-7A
B30-7AB
B36-7
B36-8
B39-8
B40-8
B40-8W
C30-7
C30-7A
C32-8
C36-7
C39-8
DASH 8-32B
DASH 8-40C
U23B
U23C
U25C
U25C
U28B
U28C
U30B
U30C
U33B
U33C
U34CG
U36B
U36C
U36CG
Engine
Type
12-2500
16-3000
16-3000
16-3000
16-3600
16-3600
16-4100
16-4100
16-4100
16-3000
16-3000
16-3000
16-3600
16-4100
12-2500
16-4100
12-2500
12-2500
12-2500
12-2500
12-3000
12-3000
12-3000
12-3000
16-3000
16-3000
16-3600
16-3600
16-3600
16-3600
HP
2250
3000
3000
3000
3600
3600
4100
4100
4100
3000
3000
3000
3600
4100
2500
4100
2500
2500
2500
2500
3000
3000
3000
3000
3000
3000
3600
3600
3600
3600
221
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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
222
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Appendix 6-6
Emission Factors For Locomotives
Eng. Type
EMD 8-645E
EMD 8-645E3C
HP Operation
1100 Yard
1650 Yard
EMD 12-567BC 1200 Yard
EMD 12-645E
1500 Yard
EMD 12-645F3B 2950 Line Haul
EMD 12-645E3
EMD 12-645E3B 2500
EMD 12-710G3A 3200 Line Haul
EMD 16-567C
EMD 16-645E
EMD 16-645E3 3000 Line Haul
EMD 16-645E3B 3000 Line Haul
EMD 16-645F3
3500 Line Haul
EMD 20-645E3 3800
GE 12-2500 2500
Line Haul
Line Haul
Emission Factors (lbs/uaD
HC
0.0525
0.0223
0.2209
0.0321
0.0155
CO
0.1571
0.0477
0.1608
0.0752
0.0490
EMD 12-710G3 3200 Line Haul 0.0155
0.0070
0.0373
0.0447
0.0198
0.0160
0.0178
EMD 16-645F3B 3600 Line Haul 0.0153
EMD 16-710G3 3600 Line Haul 0.0170
EMD 16-710G3A 3600 Line Haul 0.0091
0.0200
0.0229
0.0721
0.0460
0.0529
0.0295
0.0244
0.0935
0.0528
0.0970
NOx
0.4984
0.7232
0.3936
0.5141
0.4962
0.4306
0.4568
0.4744
0.5236
0.6060
0.6687
0.4986
0.4862
0.4590
0.4271
PM
0.0162
0.0121
0.0165
0.0138
0.0104
2300 Line Haul 0.0192 0.0939 0.5156 0.0113
Yard 0.0277 0.1130 0.5803 0.0135
Line Haul 0.0196 0.0878 0.5475 0.0115
Yard 0.0266 0.0761 0.5107 0.0133
0.0103
0.0108
1750 Line Haul 0.0284 0.0857 0.5109 0.0114
Yard 0.0435 0.0784 0.4452 0.0136
2000 Line Haul 0.0192 0.0604 0.5443 0.0114
Yard 0.0308 0.0747 0.5243 0.0136
0.0114
0.0071
0.0116
0.0111
0.0111
0.0110
0.0113
0.0117
Emission Factors For Locomotives
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Emission Factors (lbs/uaD
Eng. Type
GE 12-3000
GE 16-3000
GE 12-3300
GE 16-3600
GE 16-4100
HP Operation
3000 Line Haul
3000 Line Haul
3300 Line Haul
3600 Line Haul
4100 Line Haul
HC CO
0.0229 0.0852
0.0354 0.1025
0.0229 0.0852
0.0311 0.0780
0.0302 0.0659
NOx PM
0.4572 0.0115
0.4471 0.0196
0.4572 0.0115
0.4663 0.0173
0.4851 0.0171
224
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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 O50
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/ual
Pollutant
lbs/ual
HC
0.0161
HC
0.0274
CO
0.0233
CO
0.0624
NOx
0.4805
NOx
0.4655
PM
0.0107
PM
0.0157
SO,
0.0360
SO,
0.0360
*Note: The same procedures would be followed for yard locomotives.
Step 5 - Calculate new emission factors
225
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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
226
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Appendix 6-8
Duty Cycles
Line haul duty cycle data were taken from the Average California Profile as determined in the Booz-
Allen & 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
->
J
0.72
6
4
0.96
5
4
0.96
4
5
1.20
->
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
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