Transportation Conformity Guidance for
Quantitative Hot-Spot Analyses in
PM2.5 and PMi0 Nonattainment and
Maintenance Areas
Transportation and Climate Division
Office of Transportation and Air Quality
U.S. Environmental Protection Agency
&EPA
United States
Environmental Protection
Agency
EPA-420-B-13-053
November 2013
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Table of Contents
LIST OF EXHIBITS V
LIST OF APPENDICES VI
SECTION 1: INTRODUCTION 1
1.1 PURPOSE OF THIS GUIDANCE 1
1.2 TIMING OF QUANTITATIVE PM HOT-SPOT ANALYSES 1
1.3 DEFINITION OF A HOT-SPOT ANALYSIS 2
1.4 PROJECTS REQUIRING A PM HOT-SPOT ANALYSIS 2
1.5 OTHER PURPOSES FOR THIS GUIDANCE 3
1.6 ORGANIZATION OF THIS GUIDANCE 3
1.7 ADDITIONAL INFORMATION 4
1.8 GUIDANCE AND EXISTING REQUIREMENTS 5
SECTION 2: TRANSPORTATION CONFORMITY REQUIREMENTS 6
2.1 INTRODUCTION 6
2.2 OVERVIEW OF STATUTORY AND REGULATORY REQUIREMENTS 6
2.3 INTERAGENCY CONSULTATION AND PUBLIC PARTICIPATION REQUIREMENTS 8
2.4 HOT-SPOT ANALYSES ARE BUILD/NO-BUILD ANALYSES 9
2.4.1 General 9
2.4.2 Suggested approach for PM hot-spot analyses 9
2.4.3 Guidance focuses on refined PM hot-spot analyses 11
2.5 EMISSIONS CONSIDERED IN PM HOT-SPOT ANALYSES 13
2.5.1 General requirements 13
2.5.2 PM emissions from motor vehicle exhaust, brake wear, and tire wear 13
2.5.3 PM2,5 emissions from re-entrained road dust. 13
2.5.4 PM10 emissions from re-entrained road dust 13
2.5.5 PM emissions from construction-related activities 14
2.6 NAAQS CONSIDERED IN PM HOT-SPOT ANALYSES 14
2.7 BACKGROUND CONCENTRATIONS 14
2.8 APPROPRIATE TIME FRAME AND ANALYSIS YEARS 15
2.9 AGENCY ROLES AND RESPONSIBILITIES 16
2.9.1 Project sponsor 16
2.9.2 DOT 16
2.9.3 EPA 16
2.9.4 State and local transportation and air agencies 16
SECTION 3: OVERVIEW OF A QUANTITATIVE PM HOT-SPOT ANALYSIS 18
3.1 INTRODUCTION 18
3.2 DETERMINE NEED FOR A PM HOT-SPOT ANALYSIS (STEP 1) 18
3.3 DETERMINE APPROACH, MODELS, AND DATA (STEP 2) 18
3.3.1 General 18
3.3.2 Determining the geographic area and emission sources to be covered by the analysis 20
3.3.3 Deciding the general analysis approach and analysis year(s) 20
3.3.4 Determining the PM NAAQS to be evaluated 21
3.3.5 Deciding on the type of PM emissions to be modeled. 22
3.3.6 Determining the models and methods to be used. 22
3.3.7 Obtaining project-specific data 22
3.4 ESTIMATE ON-ROAD MOTOR VEHICLE EMISSIONS (STEP 3) 23
3.5 ESTIMATE EMISSIONS FROM ROAD DUST, CONSTRUCTION, AND ADDITIONAL SOURCES
(STEP 4) 23
3.6 SELECT AN AIR QUALITY MODEL, DATA INPUTS AND RECEPTORS (STEP 5) 23
3.7 DETERMINE BACKGROUND CONCENTRATIONS FROM NEARBY AND OTHER SOURCES
(STEP 6) 24
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3.8 CALCULATE DESIGN VALUES AND DETERMINE CONFORMITY (STEP 7) 24
3.9 CONSIDER MITIGATION OR CONTROL MEASURES (STEP 8) 24
3.10 DOCUMENT THE PM HOT-SPOT ANALYSIS (STEP 9) 25
SECTION 4: ESTIMATING PROJECT-LEVEL PM EMISSIONS USING MOVES 26
4.1 INTRODUCTION 26
4.2 CHARACTERIZING A PROJECT IN TERMS OF LINKS 28
4.2.1 Highway and intersection projects 29
4.2.2 Transit and other terminal projects 31
4.3 DETERMINING THE NUMBER OF MOVES RUNS 31
4.3.1 General 31
4.3.2 Projects with typical travel activity data 33
4.3.3 Projects with additional travel activity data 34
4.4 DEVELOPING BASIC RUN SPECIFICATION INPUTS 34
4.4.1 Description 35
4.4.2 Scale 35
4.4.3 Time Spans 36
4.4.4 Geographic Bounds 36
4.4.5 Vehicles/Equipment 36
4.4.6 Road Type 37
4.4.7 Pollutants and Processes 38
4.4.8 Manage Input Data Sets 39
4.4.9 Strategies 39
4.4.10 Output 40
4.4.11 Advanced Performance Features 40
4.5 ENTERING PROJECT DETAILS USING THE PROJECT DATA MANAGER 41
4.5.1 Meteorology 42
4.5.2 Age Distribution 43
4.5.3 Fuel Supply and Fuel Formulation 44
4.5.4 Inspection and Maintenance (I/M) 44
4.5.5 Link Source Type 44
4.5.6 Links 45
4.5.7 Describing Vehicle Activity 45
4.5.8 Deciding on an approach for activity 47
4.5.9 Off-Network 47
4.6 GENERATING EMISSION FACTORS FOR USE IN AIR QUALITY MODELING 49
4.6.1 Highway and intersection links 49
4.6.2 Transit and other terminal links 50
SECTION 5: ESTIMATING PROJECT-LEVEL PM EMISSIONS USING EMFAC2011
(IN CALIFORNIA) 51
5.1 INTRODUCTION 51
5.2 CHARACTERIZING A PROJECT IN TERMS OF LINKS 54
5.2.1 Highway and intersection projects 54
5.2.2 Transit and other terminal projects 55
5.3 DETERMINING THE NUMBER OF EMFAC2011 RUNS 56
5.5.7 General 56
5.3.2 Projects with typical travel activity data 56
5.3.3 Projects with additional travel activity data 57
5.4 DETERMINING THE MODELING APPROACH 58
5.4.1 Highway and intersection projects 59
5.4.2 Transit and other terminal projects 60
5.5 APPLYING THE SIMPLIFIED APPROACH: USING EMFAC2011-PL 60
5.5.7 Vehicle Category Scheme 61
5.5.2 Region Type 61
5.5.3 Region 62
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5.5.4 Calendar Year 63
5.5.5 Season 63
5.5.6 Vehicle Category 64
5.5.7 Fuel Type 64
5.5.8 Speed. 64
5.5.9 Generating and post-processing EMFAC 2011-PL emission factors 64
5.6 OVERVIEW OF THE DETAILED APPROACH 65
5.6.1 General 65
5.6.2 Introduction to EMFAC2011 bus types 67
5.6.3 Obtaining idling emissions using the detailed approach 67
5.6.4 Obtaining start emissions using the detailed approach 68
5.7 APPLYING THE DETAILED APPROACH: USING EMFAC2011-LDV 70
5.7.7 Specifying basic scenario inputs 72
5.7.2 Configuring mode and output 74
5.7.3 Editing program constants 77
5.7.4 Generating EMFAC2011-LDV emission factors 80
5.8 APPLYING THE DETAILED APPROACH: USING EMFAC2011-HD 84
5.8.1 Obtaining EMFAC2011-HD vehicle running exhaust emission rates 86
5.8.2 Obtaining EMFAC2011-HD vehicle brake and tire wear emission rates 89
5.8.3 Obtaining EMFAC2011-HD vehicle idling exhaust emission rates 91
5.8.4 Obtaining EMFAC2011-HD vehicle start exhaust emission rates 92
5.8.5 Diesel retrofits in EMFAC2011 93
5.9 USING THE DETAILED APPROACH FOR PROJECTS CONTAINING BOTH LIGHT-DUTY AND
HEAVY-DUTY VEHICLES 93
SECTION 6: ESTIMATING EMISSIONS FROM ROAD DUST, CONSTRUCTION, AND
ADDITIONAL SOURCES 95
6.1 INTRODUCTION 95
6.2 OVERVIEW OF DUST METHODS AND REQUIREMENTS 95
6.3 ESTIMATING RE-ENTRAINED ROAD DUST 96
6.3.1 PM2s nonattainment and maintenance areas 96
6.3.2 PM10 nonattainment and maintenance areas 96
6.3.3 Using AP-42 for road dust on paved roads 96
6.3.4 Using AP-42 for road dust on unpaved roads 96
6.3.5 Using alternative local approaches for road dust 97
6.4 ESTIMATING TRANSPORTATION-RELATED CONSTRUCTION DUST 97
6.4.1 Determining whether construction dust must be considered 97
6.4.2 Using AP-42 for construction dust 97
6.4.3 Using alternative approaches for construction dust 97
6.5 ADDING DUST EMISSIONS TO MOVES/EMFAC MODELING RESULTS 98
6.6 ESTIMATING ADDITIONAL SOURCES OF EMISSIONS IN THE PROJECT AREA 98
6.6.1 Construction-related vehicles and equipment 98
6.6.2 Locomotives 98
6.6.3 Additional emission sources 98
SECTION 7: SELECTING AN AIR QUALITY MODEL, DATA INPUTS, AND RECEPTORS 99
7.1 INTRODUCTION 99
7.2 GENERAL OVERVIEW OF AIR QUALITY MODELING 99
7.3 SELECTING AN APPROPRIATE AIR QUALITY MODEL 101
7.3.1 Recommended air quality models 101
7.3.2 How emissions are represented in CAL3QHCR and AERMOD 104
7.3.3 Alternate models 104
7.4 CHARACTERIZING EMISSION SOURCES 105
7.4.1 Physical characteristics and location 105
7.4.2 Emission rates/emission factors 106
7.4.3 Timing of emissions 106
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7.5 INCORPORATING METEOROLOGICAL DATA 106
7.5.1 Finding representative meteorological data 106
7.5.2 Surface and upper air data 108
7.5.3 Time duration of meteorological data record 109
7.5.4 Considering surface characteristics 110
7.5.5 Specifying urban or rural sources Ill
7.6 PLACING RECEPTORS 113
7.6.1 Overview 113
7.6.2 General guidance for receptors for all PM NAAQS 114
7.7 RUNNING THE MODEL AND OBTAINING RESULTS 115
SECTION 8: DETERMINING BACKGROUND CONCENTRATIONS FROM NEARBY AND
OTHER EMISSION SOURCES 116
8.1 INTRODUCTION 116
8.2 NEARBY SOURCES THAT REQUIRE MODELING 117
8.3 OPTIONS FOR BACKGROUND CONCENTRATIONS 118
8.3.1 Using ambient monitoring data to estimate background concentrations 119
8.3.2 Adjusting air quality monitoring data to account for future changes in air quality:
using chemical transport models 122
8.3.3 Adjusting air quality monitoring data to account for future changes in air quality:
using an on-road mobile source adjustment factor 125
SECTION 9: CALCULATING PM DESIGN VALUES AND DETERMINING CONFORMITY...126
9.1 INTRODUCTION 126
9.2 USING DESIGN VALUES IN BUILD/NO-BUILD ANALYSES 127
9.3 CALCULATING DESIGN VALUES AND DETERMINING CONFORMITY FOR PM HOT-SPOT
ANALYSES 130
9.3.1 General 130
9.3.2 Annual PM2.S NAAQS. 130
9.3.3 24-hour PM2 s NAAQS 134
9.3.4 24-hour PM10 NAAQS. 141
9.4 DETERMINING APPROPRIATE RECEPTORS FOR COMPARISON TO THE ANNUAL PM2.5 NAAQS ... 145
9.4.1 Overview 145
9.4.2 2012 PM NAAQS final rule and revised conformity guidance 145
9.5 DOCUMENTING CONFORMITY DETERMINATION RESULTS 148
SECTION 10: MITIGATION AND CONTROL MEASURES 149
10.1 INTRODUCTION 149
10.2 MITIGATION AND CONTROL MEASURES BY CATEGORY 149
10.2.1 Retrofitting, replacing vehicles/engines, and using cleaner fuels 149
10.2.2 Reduced idling programs 150
10.2.3 Transportation project design revisions 151
10.2.4 Fugitive dust control programs 151
10.2.5 Addressing other source emissions 152
IV
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List of Exhibits
EXHIBIT 3-1. OVERVIEW OF A PM QUANTITATIVE HOT-SPOT ANALYSIS 19
EXHIBIT 4-1. STEPS FOR USING MOVES IN A QUANTITATIVE PM HOT-SPOT ANALYSIS 27
EXHIBIT4-2. TYPICAL NUMBER OF MOVES RUNS FOR AN ANALYSIS YEAR 32
EXHIBIT 5 -1. STEPS FOR USING EMFAC2011 IN A QUANTITATIVE PM HOT-SPOT ANALYSIS 53
EXHIBIT5-2. GENERAL DECISION MATRIX FOR USING EMFAC2011 FOR PM HOT-SPOT ANALYSES 59
EXHIBIT 5 -3. USING THE SIMPLIFIED APPROACH (EMFAC2011 -PL TOOL) FOR A PM HOT-SPOT ANALYSIS .... 62
EXHIBIT 5-4. EMFAC2011 -PL GRAPHICAL USER INTERFACE (GUI) 63
EXHIBIT 5-5. USING THE DETAILED APPROACH FOR A PM HOT-SPOT ANALYSIS 67
EXHIBIT 5-6. BusTYPESiNEMFAC2011 68
EXHIBIT 5-7. EMFAC2011-LDV VEHICLE CATEGORIES 70
EXHIBIT 5-8. USING EMFAC2011 -LDV TO OBTAIN EMISSION RATES FOR PM HOT-SPOT ANALYSES 71
EXHIBIT 5 -9. SUMMARY OF EMFAC2011 -LDV INPUTS NEEDED TO EVALUATE A PROJECT SCENARIO FOR
A PM HOT-SPOT ANALYSIS 72
EXHIBIT 5-10. CHANGING EMFAC2011 -LDV DEFAULT SETTINGS FOR TEMPERATURE AND RELATIVE
HUMIDITY 75
EXHIBIT 5-11. SELECTING POLLUTANT TYPES IN EMFAC2011-LDV FOR PM10 AND PM2.5 76
EXHIBIT 5-12. EMFAC2011 PROGRAM CONSTANTS AND MODIFICATION NEEDS FOR PM HOT-SPOT
ANALYSES 77
EXHIBIT 5-13. EXAMPLE DEFAULT EMF AC2011-LDV VMT BY VEHICLE CLASS DISTRIBUTION
(HEAVY-DUTY VEHICLE VMT HIGHLIGHTED) 78
EXHIBIT 5-14. EXAMPLE ADJUSTED EMF AC2011 -LDV VMT BY VEHICLE CLASS DISTRIBUTION
(HEAVY-DUTY VEHICLE VMT HIGHLIGHTED) 79
EXHIBIT 5-15. EXAMPLE EMF AC2011 -LDV RUNNING EXHAUST, TIRE WEAR, AND BRAKE WEAR
EMISSION FACTORS IN THE SUMMARY RATES (RTS) OUTPUT FILE 81
EXHIBIT 5-16. EMFAC2011-HD VEHICLE CATEGORIES 84
EXHIBIT 5-17. DATA SOURCES FOR EMFAC2011 -HD VEHICLE EMISSION RATES PET AILED APPROACH) 85
EXHIBITS-IS. GRAPHICAL USER INTERFACE FOR CARB's EMF AC WEB DATABASE 86
EXHIBIT 5-19. OBTAINING RUNNING EMISSIONS (RUNEX) EMISSION RATES FOR EMF AC2011 -HD
VEHICLES (DETAILED APPROACH) 88
EXHIBIT 5-20. PM BRAKE WEAR AND TIRE WEAR (PMBW/PMTW) EMISSION RATES FOR
EMFAC2011-HD VEHICLES (DETAILED APPROACH) 90
EXHIBIT 5-21. OBTAINING IDLING (IDLEX) EMISSION RATES FOR EMFAC2011 -HD VEHICLES
(DETAILED APPROACH) 91
EXHIBIT 7-1. OVERVIEW AND DATA FLOW FOR AIR QUALITY MODELING 100
EXHIBIT 7-2. SUMMARY OF RECOMMENDED AIR QUALITY MODELS 101
EXHIBIT7-3. AIR QUALITY MODEL CAPABILITIES FOR METEOROLOGICAL DATA FOR EACH SCENARIO 110
EXHIBIT 9-1. GENERAL PROCESS FOR CALCULATING DESIGN VALUES FOR PM HOT-SPOT ANALYSES 126
EXHIBIT 9-2. GENERAL PROCESS FOR USING DESIGN VALUES IN BUILD/NO-BUILD ANALYSES 128
EXHIBIT 9-3. DETERMINING CONFORMITY TO THE ANNUALPM25NAAQS 132
EXHIBIT9-4. DETERMINING CONFORMITY TO THE 24-HOUR PM2.5NAAQS USING FIRST TIER ANALYSIS 136
EXHIBIT 9-5. RANKING OF 98™ PERCENTILE BACKGROUND CONCENTRATION VALUES 137
EXHIBIT 9-6. DETERMINING CONFORMITY TO THE 24-HOUR PM2 5 NAAQS USING SECOND TIER ANALYSIS. . 139
EXHIBIT 9-7. RANKING OF 98™ PERCENTILE BACKGROUND CONCENTRATION VALUES 140
EXHIBIT 9-8. DETERMINING CONFORMITY TO THE 24-HOUR PM10NAAQS 143
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List of Appendices
APPENDIX A: CLEARINGHOUSE OF WEBSITES, GUIDANCE, AND OTHER TECHNICAL RESOURCES FOR PM
HOT-SPOT ANALYSES
APPENDIX B : EXAMPLES OF PROJECTS OF LOCAL AIR QUALITY CONCERN
APPENDIX c: HOT-SPOT REQUIREMENTS FOR PMIO AREAS WITH PRE-2006 APPROVED CONFORMITY SIPS
APPENDIX D : CHARACTERIZING INTERSECTION PROJECTS FOR MOVES
APPENDIX E : EXAMPLE QUANTITATIVE PM HOT-SPOT ANALYSIS OF A HIGHWAY PROJECT USING MOVES
AND CAL3QHCR
APPENDIX F : EXAMPLE QUANTITATIVE PM HOT-SPOT ANALYSIS OF A TRANSIT PROJECT USING MOVES AND
AERMOD
APPENDIX G: EXAMPLE OF USING EMFAC2011 FOR A HIGHWAY PROJECT
APPENDIX H: EXAMPLE OF USING EMFAC2011 TO DEVELOP EMISSION FACTORS FOR A TRANSIT PROJECT
APPENDIX i: ESTIMATING LOCOMOTIVE EMISSIONS
APPENDIX J: ADDITIONAL REFERENCE INFORMATION ON AIR QUALITY MODELS AND DATA INPUTS
APPENDIX K: EXAMPLES OF DESIGN VALUE CALCULATIONS FOR PM HOT-SPOT ANALYSES
VI
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Section 1: Introduction
1.1 PURPOSE OF THIS GUIDANCE
This guidance describes how to complete quantitative hot-spot analyses for certain
highway and transit projects in PIVb.s and PMio (PM) nonattainment and maintenance
areas. This guidance describes transportation conformity requirements for hot-spot
analyses, and provides technical guidance on estimating project emissions with the
Environmental Protection Agency's (EPA's) MOVES model, California's EMFAC
model, and other methods. It also outlines how to apply air quality models for PM hot-
spot analyses and includes additional references and examples. However, the guidance
does not change the specific transportation conformity rule requirements for quantitative
PM hot-spot analyses, such as what projects require these analyses. EPA has coordinated
with the Department of Transportation (DOT) during the development of this guidance.
Transportation conformity is required under Clean Air Act (CAA) section 176(c) (42
U.S.C. 7506(c)) to ensure that federally supported highway and transit project activities
are consistent with (conform to) the purpose of a state air quality implementation plan
(SIP). Conformity to the purpose of the SIP means that transportation activities will not
cause or contribute to new air quality violations, worsen existing violations, or delay
timely attainment of the relevant national ambient air quality standards (NAAQS) or
required interim milestones. EPA's transportation conformity rule (40 CFR 51.390 and
Part 93) establishes the criteria and procedures for determining whether transportation
activities conform to the SIP. Conformity applies to transportation activities in
nonattainment and maintenance areas for transportation-related pollutants, including
PM2.5 and PMio. This guidance is consistent with existing regulations and guidance for
the PM NAAQS, SIP development, and other regulatory programs as applicable. This
guidance does not address carbon monoxide (CO) hot-spot requirements or modeling
procedures.l
1.2 TIMING OF QUANTITATIVE PM HOT-SPOT ANALYSES
On March 10, 2006, EPA published a final rule establishing transportation conformity
requirements for analyzing the local PM air quality impacts of transportation projects (71
FR 12468). The conformity rule requires a qualitative PM hot-spot analysis to be
performed until EPA releases guidance on how to conduct quantitative PM hot-spot
analyses and announces in the Federal Register that such requirements are in effect (40
CFR 93.123(b)).2 EPA also stated in the March 2006 final rule that quantitative PM hot-
1 EPA has issued a separate guidance document on how to use MOVES for CO project-level analyses
(including CO hot-spot analyses for conformity purposes). This guidance is available online at:
www.epa.gov/otaq/stateresources/transconf/policy.htm.
2 For more information on qualitative PM hot-spot analyses, see "Transportation Conformity Guidance for
Qualitative Hot-spot Analyses in PM2.5 and PMi0 Nonattainment and Maintenance Areas," EPA420-B-06-
902 (March 2006); available online at: www.epa.gov/otaq/stateresources/transconf/policy.htm. The
qualitative PM hot-spot requirements under 40 CFR 93.123(b)(2) will no longer apply in any PM2.5 and
1
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spot analyses would not be required until EPA released an appropriate motor vehicle
emissions model for these project-level analyses.3
Quantitative PM hot-spot analyses will be required after the end of the conformity grace
period for applying motor vehicle emissions models for such analyses. See the Federal
Register notice of availability for more information on EPA's approval of MOVES (and
EMFAC in California) for PM hot-spot analyses. The effective date of the Federal
Register notice constitutes the start of the two-year conformity grace period.4 EPA has
issued policy guidance on when these models will be required for PM hot-spot analyses
and other purposes.5
1.3 DEFINITION OF A HOT-SPOT ANALYSIS
A hot-spot analysis is defined in 40 CFR 93.101 as an estimation of likely future
localized pollutant concentrations and a comparison of those concentrations to the
relevant NAAQS. A hot-spot analysis assesses the air quality impacts on a scale smaller
than an entire nonattainment or maintenance area, including, for example, congested
highways or transit terminals. Such an analysis of the area substantially affected by the
project demonstrates that CAA conformity requirements are met for the relevant NAAQS
in the "project area." When a hot-spot analysis is required, it is included within a project-
level conformity determination.
1.4 PROJECTS REQUIRING A PM HOT-SPOT ANALYSIS
PM hot-spot analyses are required for projects of local air quality concern, which include
certain highway and transit projects that involve significant levels of diesel vehicle traffic
and any other project identified in the PM SIP as a localized air quality concern. See
Section 2.2 of the guidance for further information on the specific types of projects where
a PM hot-spot analysis is required. A PM hot-spot analysis is not required for projects
that are not of local air quality concern. This guidance does not alter the types of projects
that require a PM hot-spot analysis.
Note that additional projects may need hot-spot analyses in PMio nonattainment and
maintenance areas with approved conformity SIPs that are based on the federal PMio hot-
spot requirements that existed before the March 2006 final rule.6 EPA strongly
PM10 nonattainment and maintenance areas once the grace period is over and quantitative requirements are
in effect. At that time, the 2006 EPA/FHWA qualitative PM hot-spot guidance will be superseded by
EPA's quantitative PM hot-spot guidance.
3 See EPA's March 2006 final rule (71 FR 12498-12502).
4 EPA posts all Federal Register notices for approving new emissions models on its website:
www.epa.gov/otaq/stateresources/transconf/policy.htm#models.
5 "Policy Guidance on the Use of MOVES2010 for State Implementation Plan Development,
Transportation Conformity, and Other Purposes," EPA-420-B-09-046 (December 2009); available online
at: www.epa.gov/otaq/stateresources/transconf/policy.htm#models.
6 A "conformity SIP" includes a state's specific criteria and procedures for certain aspects of the
transportation conformity process (40 CFR 51.390).
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encourages states to revise these types of approved conformity SIPs to take advantage of
the streamlining flexibilities provided by the current CAA.7 See Appendix C for further
details on how these types of approved conformity SIPs can affect what projects are
required to have PM hot-spot analyses.
1.5 OTHER PURPOSES FOR THIS GUIDANCE
This guidance addresses how to complete a quantitative PM hot-spot analysis for
transportation conformity purposes. However, certain sections of this technical guidance
may also be applicable when completing analyses of transportation projects for general
conformity determinations and for other purposes. For example, Sections 4 or 5 can be
used to estimate transportation project emissions using MOVES or EMFAC, and Sections
7 and 8 can be used to conduct PM air quality analyses of transportation projects.
1.6 ORGANIZATION OF THIS GUIDANCE
The remainder of this guidance is organized as follows:
• Section 2 provides an overview of transportation conformity requirements for PM
hot-spot analyses.
• Section 3 describes the general process for conducting PM hot-spot analyses.
• Sections 4 and 5 describe how to estimate vehicle emissions from a project using
the latest approved emissions model, either MOVES (for all states other than
California) or EMFAC (for California).
• Section 6 discusses how to estimate emissions from road dust, construction dust,
and additional sources, if necessary.
• Section 7 describes how to determine the appropriate air quality dispersion model
and select model inputs.
• Section 8 covers how to determine background concentrations, including nearby
source emissions in the project area.
• Section 9 describes how to calculate the appropriate design values and determine
whether or not the project conforms.
• Section 10 describes mitigation and control measures that could be considered, if
necessary.
The following appendices for this guidance may also help state and local agencies
conduct PM hot-spot analyses:
• Appendix A is a clearinghouse of information and resources external to this
guidance that may be useful when completing PM hot-spot analyses.
• Appendix B gives examples of projects of local air quality concern.
7 For more information about conformity SIPs, see EPA's "Guidance for Developing Transportation
Conformity State Implementation Plans (SIPs)," EPA-420-B-09-001 (January 2009); available online at:
www.epa.gov/otaq/stateresources/transconf/policy/420b09001.pdf.
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• Appendix C discusses what projects need a PMio hot-spot analysis if a state's
approved conformity SIP is based on pre-2006 requirements.
• Appendix D demonstrates how to characterize links in an intersection when
running MOVES.
• Appendices E and F are abbreviated PM hot-spot analysis examples using
MOVES and air quality models for a highway and transit project, respectively.
• Appendices G and H are examples on how to configure and run EMFAC for a
highway and transit project, respectively.
• Appendix I describes how to estimate locomotive emissions in the project area.
• Appendix J includes details on how to input data and run air quality models for
PM hot-spot analyses, as well as prepare outputs for design value calculations.
• Appendix K has examples of how to calculate design values and determine
transportation conformity.
Except where indicated, this guidance applies equally for the annual PM2.5 NAAQS, the
24-hour PM2.5 NAAQS, and the 24-hour PMio NAAQS. This guidance is written for
current and future PM2.5 and PMio NAAQS. EPA will re-evaluate the applicability of
this guidance, as needed, if different PM NAAQS are promulgated in the future.
1.7 ADDITIONAL INFORMATION
For specific questions concerning a particular nonattainment or maintenance area, please
contact the transportation conformity staff person responsible for your state at the
appropriate EPA Regional Office. Contact information for EPA Regional Offices can be
found at: www.epa.gov/otaq/stateresources/transconf/contacts.htm.
General questions about this guidance can be directed to Meg Patulski at EPA's Office of
Transportation and Air Quality, patulski.meg(a!epa. gov. (734) 214-4842.
Technical questions about conformity hot-spot analyses can be directed to conformitv-
hotspot@epa. gov.
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1.8 GUIDANCE AND EXISTING REQUIREMENTS
This guidance does not create any new requirements. The CAA and the regulations
described in this document contain legally binding requirements. This guidance is not a
substitute for those provisions or regulations, nor is it a regulation in itself. Thus, it does
not impose legally binding requirements on EPA, DOT, states, or the regulated
community, and may not apply to a particular situation based upon the circumstances.
EPA retains the discretion to adopt approaches on a case-by-case basis that may differ
from this guidance but still comply with the statute and applicable regulations. This
guidance may be revised periodically without public notice. As noted above, EPA's
Federal Register notice describes the two-year conformity grace period for MOVES and
EMFAC for PM hot-spot analyses, and when the requirements for quantitative PM hot-
spot analyses in 40 CFR 93.123(b) will take effect.
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Section 2: Transportation Conformity Requirements
2.1 INTRODUCTION
This section outlines the transportation conformity requirements for quantitative PM hot-
spot analyses, including the general statutory and regulatory requirements, specific
analytical requirements, and the different types of agencies involved in developing hot-
spot analyses.
2.2 OVERVIEW OF STATUTORY AND REGULATORY REQUIREMENTS
CAA section 176(c)(l) is the statutory requirement that must be met by all projects in
nonattainment and maintenance areas that are subject to transportation conformity.
Section 176(c)(l)(B) states that federally-supported transportation projects must not
"cause or contribute to any new violation of any standard [NAAQS] in any area; increase
the frequency or severity of any existing violation of any standard in any area; or delay
timely attainment of any standard or any required interim emission reductions or other
o
milestones in any area."
Section 93.109(b) of the conformity rule outlines the requirements for project-level
conformity determinations. For example, PM hot-spot analyses must be based on the
latest planning assumptions available at the time the analysis begins (40 CFR 93.110).
Also, the design concept and scope of the project must be consistent with that included in
the conforming transportation plan and transportation improvement program (TIP) or
regional emissions analysis (40 CFR 93.114).
Section 93.123(b)(l) of the conformity rule defines the projects that require a PM2.5 or
hot-spot analysis as:
"(i) New highway projects that have a significant number of diesel vehicles, and
expanded highway projects that have a significant increase in the number of diesel
vehicles;
(ii) Projects affecting intersections that are at Level-of-Service D, E, or F with a
significant number of diesel vehicles, or those that will change to Level-of-
Service D, E, or F because of increased traffic volumes from a significant number
of diesel vehicles related to the project;
8 See EPA's March 2006 final rule (71 FR 12469-12490) and March 24, 2010 final rule (75 FR 14274-
14285). Both of these final rules address the statutory conformity requirements and explain how the hot-
spot analyses required by EPA's regulations satisfy those requirements. Issues relating to the statutory
conformity requirements are therefore not addressed in this guidance document. See also Environmental
Defense v. EPA 467 F.3d 1329 (B.C. Cir. 2006) and Environmental Defense vs. EPA, 509 F.3d 553 (B.C.
Cir. 2007).
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(iii) New bus and rail terminals and transfer points that have a significant number
of diesel vehicles congregating at a single location;
(iv) Expanded bus and rail terminals and transfer points that significantly increase
the number of diesel vehicles congregating at a single location; and
(v) Projects in or affecting locations, areas, or categories of sites which are
identified in the PIVb.s or PMio applicable implementation plan or implementation
plan submission, as appropriate, as sites of violation or possible violation."
A PM hot-spot analysis is not required for projects that are not of local air quality
concern. For these projects, state and local project sponsors should document in their
project-level conformity determinations that the requirements of the CAA and 40 CFR
93.116 are met without a hot-spot analysis, since such projects have been found not to be
of local air quality concern under 40 CFR 93.123(b)(l). Note that all other project-level
conformity requirements must continue to be met. See Appendix B for examples of
projects that are most likely to be of local air quality concern, as well as examples of
projects that are not.9
Section 93.123(c) of the conformity rule includes the general requirements for all PM
hot-spot analyses. A PM hot-spot analysis must:
• Estimate the total emissions burden of direct PM emissions that may result from
the implementation of the project(s), summed together with future background
concentrations;
• Include the entire transportation project, after identifying the major design
features that will significantly impact local concentrations;
• Use assumptions that are consistent with those used in regional emissions
analyses for inputs that are needed for both analyses (e.g., temperature, humidity);
• Assume the implementation of mitigation or control measures only where written
commitments for such measures have been obtained; and
• Consider emissions increases from construction-related activities only if they
occur during the construction phase and last more than five years at any
individual site.
Finally, the interagency consultation process must be used to develop project-level
conformity determinations to meet all applicable conformity requirements for a given
project. In general, when a hot-spot analysis is required, it is done when a project-level
conformity determination is completed. Conformity determinations are typically
developed during the National Environmental Policy Act (NEPA) process, although
conformity requirements are separate from NEPA-related requirements. There can also
9 See the preamble of the March 2006 final rule for further information regarding how and why EPA
defined projects of local air quality concern (71 FR 12491-12493). EPA also clarified Section
93.123(b)(l)(i) in the January 24, 2008 final rule (73 FR 4435-4436).
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be limited cases when conformity requirements apply after the initial NEPA process has
been completed.10
2.3 INTERAGENCY CONSULTATION AND PUBLIC PARTICIPATION
REQUIREMENTS
The interagency consultation process is an important tool for completing project-level
conformity determinations and hot-spot analyses. Interagency consultation must be used
to develop a process to evaluate and choose models and associated methods and
assumptions to be used in PM hot-spot analyses (40 CFR 93.105(c)(l)(i)). For example,
each area's interagency consultation procedures must be used to determine the models
and associated methods and assumptions for:
• The geographic area covered by the analysis (see Section 3.3);
• The emissions models used in the analysis (see Section 4 for MOVES and
Section 5 for EMFAC);
• Whether and how to estimate road and construction dust emissions (see
Section 6);
• The nearby sources considered, background data used, and air quality model
chosen, including the background monitors/concentrations selected and any
interpolation methods used (see Sections 7 and 8); and
• The appropriateness of receptors to be compared to the annual PM2.5 NAAQS
(see Section 9.4).
State and local agencies have flexibility to decide whether the process outlined in the
interagency consultation procedures should be used for aspects of PM hot-spot analyses
where consultation is not required. The roles and responsibilities of various agencies for
meeting the transportation conformity requirements are addressed in 40 CFR 93.105 or in
a state's approved conformity SIP. See Section 2.9 for further information on the
agencies involved in interagency consultation.
This guidance describes when consultation on specific decisions is necessary, but for
many aspects of PM hot-spot analyses, the general requirement for interagency
consultation can be satisfied without consulting separately on each and every specific
decision that arises. In general, as long as the consultation requirements are met,
agencies have discretion as to how they consult on hot-spot analyses. For example, the
interagency consultation process could be used to make decisions on a case-by-case basis
for individual transportation projects for which a PM hot-spot analysis is required. Or,
agencies involved in the consultation process could develop procedures that will apply
for any PM hot-spot analysis and agree that any departures from procedures would be
discussed by involved agencies. For example, interagency consultation is required on the
emissions model used for the analysis, but agencies could agree up front that the latest
EPA-approved version of MOVES will be used for any hot-spot analysis necessary in an
10 Such an example may occur when NEPA is completed prior to an area being designated nonattainment,
but additional federal project approvals are required after conformity requirements apply.
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area that is not located in California. As a second example, agencies could agree ahead
of time that, if appropriate, instead of modeling all four quarters of the year for a 24-hour
PM NAAQS, only the quarters that were modeled for the latest SIP demonstration for
that NAAQS need to be modeled in a hot-spot analysis.
The conformity rule also requires agencies completing project-level conformity
determinations to establish a proactive public involvement process that provides
opportunity for public review and comment (40 CFR 93.105(e)). The NEPA public
involvement process is typically used to satisfy this public participation requirement.11 If
a project-level conformity determination that includes a PM hot-spot analysis is
performed after NEPA is completed, a public comment period must still be provided to
support that determination. In these cases, agencies have flexibility to decide what
specific public participation procedures are appropriate, as long as the procedures provide
a meaningful opportunity for public review and comment.
2.4 HOT-SPOT ANALYSES ARE BUILD/NO-BUILD ANALYSES
2.4.1 General
As noted above, the conformity rule requires that the emissions from the proposed
project, when considered with background concentrations, will not cause or contribute to
any new violation, worsen existing violations, or delay timely attainment of the relevant
NAAQS or required interim milestones. As described in Section 1.3, the hot-spot
analysis examines the area substantially affected by the project (i.e., the "project area").
In general, a hot-spot analysis compares the air quality concentrations with the proposed
project (the build scenario) to the air quality concentrations without the project (the no-
build scenario).12 These air quality concentrations are determined by calculating a
"design value," a statistic that describes a future air quality concentration in the project
area that can be compared to a particular NAAQS. It is always necessary to complete
emissions and air quality modeling on the build scenario and compare the resulting
design values to the relevant PM NAAQS. However, it will not always be necessary to
conduct emissions and air quality modeling for the no-build scenario, as described further
below.
2.4.2 Suggested approach for PM hot-spot analyses
To avoid unnecessary work, EPA suggests the following approach when completing a
PM hot-spot analysis:
11 Section 93.105(e) of the conformity rule requires agencies to "provide opportunity for public
involvement in conformity determinations for projects where otherwise required by law."
12 See 40 CFR 93.116(a). See also November 24, 1993 conformity rule (58 FR 62212-62213). Please note
that a build/no-build analysis for project-level conformity determinations is different than the build/no-
build interim emissions test for regional emissions analyses in 40 CFR 93.119.
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• First, model the build scenario and account for background concentrations in
accordance with this guidance. If the design values for the build scenario are less
than or equal to the relevant NAAQS, the project meets the conformity rule's hot-
spot requirements and no further modeling is needed (i.e., there is no need to
model the no-build scenario). If this is not the case, the project sponsor could
choose mitigation or control measures, perform additional modeling that includes
these measures, and then determine if the build scenario is less than or equal to
the relevant NAAQS.
• If the build scenario results in design values greater than the NAAQS, then the
no-build scenario will also need to be modeled. The no-build scenario will model
the air quality impacts of sources without the proposed project. The modeling
results of the build and no-build scenarios should be combined with background
concentrations as appropriate. If the design values for the build scenario are less
than or equal to the design values for the no-build scenario, then the project meets
the conformity rule's hot-spot requirements. If not, then the project does not meet
conformity requirements without further mitigation or control measures. If such
measures are considered, additional modeling will need to be completed and new
design values calculated to ensure that the build scenario is less than or equal to
the no-build scenario.
The project sponsor can decide to use the suggested approach above or a different
approach (e.g., conduct the no-build analysis first, calculate design values at all build and
no-build scenario receptors). The project sponsor can choose to apply mitigation or
control measures at any point in the process. This guidance applies to any of the above
approaches for a given PM hot-spot analysis.
In general, assumptions should be consistent between the build and no-build scenarios for
a given analysis year, except for traffic volumes and other project activity changes or
changes in nearby sources that are expected to occur due to the project (e.g., increased
activity at a nearby marine port or intermodal terminal due to a new freight corridor
highway). Project sponsors should document the build/no-build analysis in the project-
level conformity determination, including the assumptions, methods, and models used for
each analysis year(s).
The conformity rule defines how to determine if new NAAQS violations or increases in
the frequency or severity of existing violations are predicted to occur based on the hot-
spot analysis. Section 93.101 states:
"Cause or contribute to a new violation for a project means:
(1) To cause or contribute to a new violation of a standard in the area
substantially affected by the project or over a region which would
13 If mitigation or control measures are used to demonstrate conformity during the hot-spot analysis, the
conformity determination for the project must include written commitments to implement such measures
(40CFR93.125).
10
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otherwise not be in violation of the standard during the future period in
question, if the project were not implemented; or
(2) To contribute to a new violation in a manner that would increase the
frequency or severity of a new violation of a standard in such area."
"Increase the frequency or severity means to cause a location or region to exceed
a standard more often or to cause a violation at a greater concentration than
previously existed and/or would otherwise exist during the future period in
question, if the project were not implemented."
A build/no-build analysis is typically based on design value comparisons done on a
receptor-by-receptor basis. However, there may be certain cases where a "new" violation
at one receptor (in the build scenario) is relocated from a different receptor (in the no-
build scenario). As discussed in the preamble to the November 24, 1993 transportation
conformity rule, EPA believes that "a seemingly new violation may be considered to be a
relocation and reduction of an existing violation only if it were in the area substantially
affected by the project and if the predicted [future] design value for the "new" site would
be less than the design value at the "old" site without the project - that is, if there would
be a net air quality benefit" (58 FR 62213). Since 1993, EPA has made this interpretation
only in limited cases with CO hot-spot analyses where there is a clear relationship
between a proposed project and a possible relocated violation (e.g., a reduced CO
NAAQS violation is relocated from one corner of an intersection to another due to traffic-
related changes from an expanded intersection). Any potential relocated violations in PM
hot-spot analyses should be determined through an area's interagency consultation
procedures.
2.4.3 Guidance focuses on refined PM hot-spot analyses
Finally, the build/no-build analysis described in this guidance represents a refined PM
hot-spot analysis, rather than a screening analysis. Refined analyses rely on detailed
local information and simulate detailed atmospheric processes to provide more
specialized and accurate estimates, and can be done for both the build and no-build
scenarios. In contrast, screening analyses estimate the maximum likely air quality
impacts from a given source under worst case conditions for the build scenario only.14
EPA believes that, because of the complex nature of PM emissions, the statistical form of
each NAAQS, the need to consider temperature effects throughout the time period
covered by the analysis, and the variability of background concentrations over the course
of a year, quantitative PM hot-spot analyses need to be completed using the refined
analysis procedures described in this guidance.
However, there may be cases where using a screening analysis or components of a
screening analysis could be supported in PM hot-spot analyses, such as:
14 Screening analyses for the 1-hour and 8-hour CO NAAQS have been completed based on peak emissions
and worst case meteorology. The shorter time period covered by these NAAQS, the types of projects
modeled, and other factors make screening analyses appropriate for the CO NAAQS.
11
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• Where a project can be characterized as a single source (e.g., a transit terminal
that could be characterized as a single area source). Such a case may be a
candidate for a screening analysis using worst case travel activity and
meteorological data and an appropriate screening model.15
• Where emissions modeling for a project is completed using worst case travel
activity and a recommended air quality model (see Section 7.3).
Both of these options would be appropriate only for the build scenario and may be most
feasible in areas where monitored PM air quality concentrations are significantly below
the applicable NAAQS. In addition, other flexibilities that can simplify the hot-spot
analysis process are included in later parts of this guidance (e.g., calculating design
values in the build scenario first for the receptor with highest modeled concentrations
only).
EPA notes, however, that this guidance assumes that emissions modeling, air quality
modeling, and representative background concentrations are all necessary as part of a
quantitative PM hot-spot analysis in order to demonstrate conformity requirements. For
example, an approach that would involve comparing only emissions between the build
and no-build scenarios, without completing air quality modeling or considering
representative background concentrations, would not be technically supported.16
Furthermore, EPA believes that the value of using a screening option decreases for a PM
hot-spot analysis if a refined analysis will ultimately be necessary to meet conformity
requirements.
Evaluating and choosing models and associated methods and assumptions used in
screening options must be completed through the process established by each area's
interagency consultation procedures (40 CFR 93.105(c)(l)(i)). Please consult with your
EPA Regional Office, which will coordinate with EPA's Office of Transportation and Air
Quality (OTAQ) and Office of Air Quality Planning and Standards (OAQPS), if a
screening analysis option is being considered for a PM hot-spot analysis.
Such as AERSCREEN or AERMOD using meteorological conditions suitable for screening analyses.
16 Since Section 93.123(b)(l) of the conformity rule requires PM hot-spot analyses for projects with
significant new levels of PM emissions, it is unlikely that every portion of the project area in the build
scenario would involve the same or fewer emissions than that same portion in the no-build scenario. Such
an approach would not consider the variation of emissions and potential NAAQS impacts at different
locations throughout the project area, which is necessary to meet conformity requirements.
12
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2.5 EMISSIONS CONSIDERED IN PM HOT-SPOT ANALYSES
2. 5. 1 General requirements
PM hot-spot analyses include only directly emitted PIVb.s or PMio emissions. PM2.5 and
precursors are not considered in PM hot-spot analyses, since precursors take time at
the regional level to form into secondary PM.
2.5.2 PM emissions from motor vehicle exhaust, brake wear, and tire wear
Exhaust, brake wear, and tire wear emissions from on-road vehicles are always be
included in a project's PM2 5 or PMio hot-spot analysis. See Sections 4 and 5 for how to
quantify these emissions using MOVES (outside California) or EMFAC (within
California).
2.5.3 PM2.5 emissions from re-entrained road dust
Re-entrained road dust must be considered in PM2.5 hot-spot analyses only if EPA or the
state air agency has made a finding that such emissions are a significant contributor to the
PM2.5 air quality problem in a given nonattainment or maintenance area (40 CFR
93.102(b)(3) and 93.119(f)(8)).18
• If a PMg^area has no adequate or approved SIP budgets for the PMgjjNAAOS,
re-entrained road dust is not included in a hot-spot analysis unless the EPA
Regional Administrator or state air quality agency determines that re-entrained
road dust is a significant contributor to the PM2.5 nonattainment problem and has
so notified the metropolitan planning organization (MPO) and DOT.
• If a PM^area has adequate or approved SIP budgets, re-entrained road dust
would have to be included in a hot-spot analysis only if such budgets include re-
entrained road dust.
See Section 6 for further information regarding how to estimate re-entrained road dust for
PM2 5 hot-spot analyses, if necessary.
2. 5. 4 PMi o emissions from re-entrained road dust
Re-entrained road dust must be included in all PMio hot-spot analyses. Because road
dust is a significant component of PMio inventories, EPA has historically required road
dust emissions to be included in all conformity analyses of direct PMio emissions -
17 See 40 CFR 93.102(b) for the general requirements for applicable pollutants and precursors in
conformity determinations. Section 93.123(c) provides additional information regarding certain PM
emissions for hot-spot analyses. See also EPA's March 2006 final rule preamble (71 FR 12496-8).
18 See the July 1, 2004 final conformity rule (69 FR 40004).
13
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including hot-spot analyses.19 See Section 6 for further information regarding how to
estimate re-entrained road dust for PMio hot-spot analyses.
2.5.5 PM emissions from construction-related activities
Emissions from construction-related activities are not required to be included in PM hot-
spot analyses if such emissions are considered temporary as defined in 40 CFR
93.123(c)(5) (i.e., emissions which occur only during the construction phase and last five
years or less at any individual site). Construction emissions would include any direct PM
emissions from construction-related dust and exhaust emissions from construction
vehicles and equipment.
For most projects, construction emissions would not be included in PM2.5 or PMio hot-
spot analyses (because, in most cases, the construction phase is less than five years at any
one site).20 However, there may be limited cases where a large project is constructed
over a longer time period, and non-temporary construction emissions must be included
when an analysis year is chosen during project construction. See Section 6 for further
information regarding how to estimate transportation-related construction emissions for
PM hot-spot analyses, if necessary.
2.6 NAAQS CONSIDERED IN PM HOT-SPOT ANALYSES
The CAA and transportation conformity regulations require that conformity be met for all
transportation-related NAAQS for which an area has been designated nonattainment or
maintenance. Therefore, a project-level conformity determination must address all
applicable NAAQS for a given pollutant.21
Accordingly, results from a quantitative hot-spot analysis will need to be compared to all
relevant PM2.5 and PMio NAAQS in effect for the area undertaking the analysis. For
example, in an area designated nonattainment or maintenance for only the annual PM2.5
NAAQS or only the 24-hour PM2.5 NAAQS, the hot-spot analysis would have to address
only that respective PM2.5 NAAQS. If an area is designated nonattainment or
maintenance for the annual and 24-hour PM2.5 NAAQS, the hot-spot analysis would have
to address both NAAQS for conformity purposes.
2.7 BACKGROUND CONCENTRATIONS
As required by 40 CFR 93.123(c)(l) and discussed in Section 2.2, a PM hot-spot analysis
"must be based on the total emissions burden which may result from the implementation
of the project, summed together with future background concentrations...." By
19 See the March 2006 final rule (71 FR 12496-98).
20 EPA's rationale for limiting the consideration of construction emissions to five years can be found in its
January 11, 1993 proposed rule (58 FR 3780).
21 See EPA's March 2006 final rule (71 FR 12468-12511).
14
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definition, background concentrations do not include emissions from the project itself.
Background concentrations include the emission impacts of all sources that affect
concentrations in the project area other than the project. Section 8 provides further
information on how background concentrations can be determined.
2.8 APPROPRIATE TIME FRAME AND ANALYSIS YEARS
Section 93.116(a) of the conformity rule requires that PM hot-spot analyses consider
either the full time frame of an area's transportation plan or, in an isolated rural
nonattainment or maintenance area, the 20-year regional emissions analysis.22
Conformity requirements are met if the analysis demonstrates that no new or worsened
violations occur in the year(s) of highest expected emissions - which includes the
project's emissions in addition to background concentrations.23 Areas should analyze the
year(s) within the transportation plan or regional emissions analysis, as appropriate,
during which:
• Peak emissions from the project are expected; and
• A new NAAQS violation or worsening of an existing violation would most likely
occur due to the cumulative impacts of the project and background concentrations
in the project area.
If such a demonstration occurs, then no adverse impacts would be expected to occur in
any other years within the time frame of the transportation plan or regional emissions
analysis.24
The following factors (among others) should be considered when selecting the year(s) of
peak emissions:
• Changes in vehicle fleets;
• Changes in traffic volumes, speeds, and vehicle miles traveled (VMT); and
• Expected trends in background concentrations, including any nearby sources that
are affected by the project.
In some cases, selecting only one analysis year, such as the last year of the transportation
plan or the year of project completion, may not be sufficient to satisfy conformity
requirements. For example, if a project is being developed in two stages and the entire
two-stage project is being approved, two analysis years should be modeled: one to
examine the impacts of the first stage of the project and another to examine the impacts
22 Although CAA section 176(c)(7) and 40 CFR 93.106(d) allow the election of changes to the time
horizons for transportation plan and TIP conformity determinations, these changes to do not affect the time
frame and analysis requirements for hot-spot analyses.
23 If such a demonstration can be made, then EPA believes it is reasonable to assume that no adverse
impacts would occur in any other years within the time frame of the transportation plan or regional
emissions analysis.
24 See EPA's July 1, 2004 final conformity rule (69 FR 40056-40058).
15
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of the completed project.25 Selecting appropriate analysis year(s) should be considered
through the process established by each area's interagency consultation procedures (40
CFR93.105(c)(l)(i)).
2.9 AGENCY ROLES AND RESPONSIBILITIES
The typical roles and responsibilities of agencies implementing the PM hot-spot analysis
requirements are described below. Further details are provided throughout later sections
of this guidance.
2.9.1 Project sponsor
The project sponsor is typically the agency responsible for implementing the project (e.g.,
a state department of transportation, regional or local transit operator, or local
government). The project sponsor is the lead agency for developing the PM hot-spot
analysis, meeting interagency consultation and public participation requirements, and
documenting the final hot-spot analysis in the project-level conformity determination.
2.9.2 DOT
DOT is responsible for making project-level conformity determinations. PM hot-spot
analyses and conformity determinations would generally be included in documents
prepared to meet NEPA requirements. It is possible for DOT to make a project-level
conformity determination outside of the NEPA process (for example, if conformity
requirements apply after NEPA has been completed, but additional federal action on the
project is required). DOT is also an active member of the interagency consultation
process for conformity determinations.
2.9.3 EPA
EPA is responsible for promulgating transportation conformity regulations and provides
policy and technical assistance to federal, state, and local conformity implementers. EPA
is an active member of the interagency consultation process for conformity
determinations. In addition, EPA reviews submitted SIPs, and provides policy and
technical support for emissions modeling, air quality modeling, monitoring, and other
issues.
2.9.4 State and local transportation and air agencies
State and local transportation and air quality agencies are part of the interagency
consultation process and assist in modeling of transportation activities, emissions, and air
quality. These agencies are likely to provide data required to perform a PM hot-spot
analysis, although the conformity rule does not specifically define the involvement of
See EPA's July 1, 2004 final rule (69 FR 40057).
16
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these agencies in project-level conformity determinations. For example, the state or local
air quality agency operates the air quality monitoring network, processes meteorological
data, and uses air quality models for air quality planning purposes (such as SIP
development and modeling applications for other purposes). MPOs often conduct
emissions modeling, maintain regional population forecasts, and estimate future traffic
conditions relevant for project planning. The interagency consultation process can be
used to discuss the role of the state or local air agency, the MPO, and other agencies in
project-level conformity determinations, if such roles are not already defined in an area's
conformity SIP.
17
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Section 3: Overview of a Quantitative PM Hot-Spot Analysis
3.1 INTRODUCTION
This section provides a general overview of the process for conducting a quantitative PM
hot-spot analysis. All individual elements or steps presented here are covered in more
depth and with more technical information throughout the remainder of the guidance.
The general steps required to complete a quantitative PM hot-spot analysis are depicted
in Exhibit 3-1 (following page) and summarized in this section.
As previously noted in Section 2.3, the interagency consultation process is an essential
part of developing PM hot-spot analyses. As a number of fundamental aspects of the
analysis need to be determined through consultation, it is recommended that these
discussions take place as early and as often as necessary for the analysis to be completed
on schedule. In addition, early consultation allows potential data sources for the analysis
to be more easily identified.
3.2 DETERMINE NEED FOR A PM HOT-SPOT ANALYSIS (STEP i)
The conformity rule requires a PM hot-spot analysis only for projects of local air quality
concern. See Section 2.2 regarding how to determine if a project is of local air quality
concern according to the conformity rule.
3.3 DETERMINE APPROACH, MODELS, AND DATA (STEP 2)
3.3.1 General
There are several decisions that need to be made before beginning a PM hot-spot
analysis, including determining the:
• Geographic area to be covered by the analysis (the "project area") and emission
sources to be modeled;
• General approach and analysis year(s) for emissions and air quality modeling;
• Applicable PM NAAQS to be evaluated;
• Type of PM emissions to be modeled for different sources;
• Emissions and air quality models and methods to be used;
• Project-specific data to be used; and
• Schedule for conducting the analysis and points of consultation.
Further details on these decisions are provided below. Evaluating and choosing models
and associated methods and assumptions must be completed through the process
established by each area's interagency consultation procedures (40 CFR 93.105(c)(l)(i)).
18
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Exhibit 3-1. Overview of a PM Quantitative Hot-spot Analysis
itepl:
forAn»IysIi
Is this a project of \
local air quality
concern?
^
M»
W
PM hot-spot analysis
not required
VahidaEiHiuiou
/
^/ Is project located
\ IB C'alifoiiiia?
*
mm
if
Estimate using
MOVES
\ Vm
**
f
Estimate using
EMFAC
1
Stgpj; from Road Dnit,
Obtain and input
required site data (e.|
meteorological)
Input MOVES/
EMFAC, dust, and
nearby source outputs
I
Ron air quality model
obtain results
CoBCBtttratlKBi
Valno and Determine
Confenatty
Add Step 5 results to
background concentrations
to obtain design values for
build'no-bnild scenarios
/ Do the design \
/ values allow the \
\ project to
conform?
Consider or
Cemtwi Measure*
Consider measures to
reduce emissions and redo
analysis
19
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3.3.2 Determining the geographic area and emission sources to be covered by the
analysis
The geographic area to be covered by a PM hot-spot analysis (the "project area") is to be
determined on a case-by-case basis.26 PM hot-spot analyses must examine the air quality
impacts for the relevant PM NAAQS in the area substantially affected by the project (40
CFR 93.123(c)(l)). To meet this and other conformity requirements, it is necessary to
define the project, determine where it is to be located, and ascertain what other emission
sources are located in the project area.27 In addition to emissions from the proposed
highway or transit project,28 there may be nearby sources of emissions that need to be
estimated and included in air quality modeling (e.g., a freight rail terminal that is affected
by the project). There also may be other sources in the project area that are determined to
be insignificant to project emissions (e.g., a service drive or small employee parking lot).
See Sections 4 through 6 for how to estimate emissions from the proposed project, and
Sections 6 through 8 for when and how to include nearby source emissions and other
background concentrations.
Hot-spot analyses must include the entire project (40 CFR 93.123(c)(2)). However, it
may be appropriate in some cases to focus the PM hot-spot analysis only on the locations
of highest air quality concentrations. For large projects, it may be necessary to analyze
multiple locations that are expected to have the highest air quality concentrations and,
consequently, the most likely new or worsened PM NAAQS violations. If conformity is
demonstrated at such locations, then it can be assumed that conformity is met in the entire
project area. For example, if a highway project involves several lane miles with similar
travel activity (and no nearby sources that need to be modeled), the scope of the PM hot-
spot analysis could involve only the point(s) of highest expected PM concentrations. If
conformity requirements are met at such locations, then it can be assumed that
conformity is met throughout the project area. Such an approach would be preferable to
modeling the entire length of the highway project, which would involve additional time
and resources.
Questions regarding the scope of a given PM hot-spot analysis can be determined through
the interagency consultation process.
3.3.3 Deciding the general analysis approach and analysis year(s)
As stated in Section 2.4, there are several approaches for completing a build/no-build
analysis for a given project. For example, a project sponsor may want to start by
completing the build scenario first to see if a new or worsened PM NAAQS violation is
26 Given the variety of potential projects that may require a PM hot-spot analysis, it is not possible to
provide one definition or set of parameters that can be used in all cases to determine the area covered by the
PM hot-spot analysis.
27 See more in the March 24, 2010 final conformity rule entitled "Transportation Conformity Rule PM2 5
and PMjo amendments," 75 FR 14281; found online at: www.epa.gov/otaq/stateresources/transconf/conf-
regs.htm
28 40 CFR 93.101 defines "highway project" and "transit project" for transportation conformity purposes.
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predicted (if not, then modeling the no-build scenario would be unnecessary). In
contrast, a project sponsor could start with the no-build scenario first if a future PM
NAAQS violation is anticipated in both the build and no-build scenarios (even after
mitigation or control measures are considered).
It is also necessary to select one or more analysis years within the time frame of the
transportation plan or regional emissions analysis when emissions from the project, any
nearby sources, and background are expected to be highest. See Section 2.8 for more
information on selecting analysis year(s).
3.3.4 Determining the PM NAAQS to be evaluated
As stated in Section 2.6, PM hot-spot analyses need to be evaluated only for the NAAQS
for which an area has been designated nonattainment or maintenance. In addition, there
are aspects of modeling that can be affected by whether a NAAQS is an annual or a 24-
hour PM NAAQS. It is also important to conduct modeling for those parts of an analysis
year where PM concentrations are expected to be highest. For example, a hot-spot
analysis for the annual PM2 5 NAAQS would involve data and modeling throughout a
given analysis year (i.e., all four quarters of the analysis year).29
A hot-spot analysis for the 24-hour PM2 5 or PMi0 NAAQS would also involve data and
modeling throughout an analysis year, except when future NAAQS violations and peak
emissions in the project area are expected to occur in only one quarter of the future
analysis year(s). In such cases, a project sponsor could choose to complete emissions and
air quality modeling for only that quarter, as determined through the interagency
consultation process. For example, if an area's SIP demonstration is based on only one
quarter for a 24-hour PM NAAQS, it may be appropriate to make the same assumption
for hot-spot analyses for that NAAQS. This could be the case in a PMio nonattainment or
maintenance area that has PMio NAAQS violations only during the first quarter of the
year (January-March), when PM emissions from other sources, such as wood smoke, are
highest. In such an area, if the highest emissions from the project area are also expected
to occur in this same quarter, then the project sponsor could complete the PM hot-spot
analysis for only that quarter. EPA notes, however, that it may be difficult to determine
whether 24-hour PM2.5 NAAQS violations will occur in only one quarter. State and local
air quality agencies should be consulted regarding when it may be appropriate for a PM
hot-spot analysis for a 24-hour PM NAAQS to cover only one quarter in an analysis year.
These agencies are responsible for monitoring air quality violations and for developing
SIP attainment demonstrations.
29 Calendar quarters in this guidance are defined in the following manner: Ql (January-March), Q2 (April-
June), Q3 (July-September), and Q4 (October-December). These quarters are also used by EPA and state
and local agencies to calculate design values for air quality monitoring purposes and for SIP development.
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3.3.5 Deciding on the type of PM emissions to be modeled
See Section 2.5 for further information on what types of directly emitted PM must be
included in hot-spot analyses and Sections 4 through 6 and Section 8 on when and how to
quantify PM emissions.
3.3.6 Determining the models and methods to be used
The emissions and air quality models and methods used in PM hot-spot analyses must be
evaluated and chosen through the process established by each area's interagency
consultation procedures (40 CFR 93.105(c)(l)(i)). The latest approved emissions
models must be used in PM hot-spot analyses (40 CFR 93.111). See Sections 3.4 through
3.6 and the subsequent sections of the guidance they refer to for specific information
about models and methods that apply.
Note: It is important to select an air quality model to be used in the PM hot-spot analysis
early in the process, since this information is necessary to prepare emissions model
outputs for air quality modeling purposes. See Section 7 for further information on when
AERMOD and CAL3QHCR are recommended air quality models for PM hot-spot
analyses.
3.3.7 Obtaining project-specific data
The conformity rule requires that the latest planning assumptions available at the time
that the analysis begins be used in conformity determinations (40 CFR 93.110). In
addition, the regulation states that hot-spot analysis assumptions must be consistent with
those assumptions used in the regional emissions analysis for any inputs that are required
for both analyses (40 CFR 93.123(c)(3)).
The project sponsor should use project-specific data for both emissions and air quality
modeling whenever possible, though default inputs may be appropriate in some cases.
The use of project-specific versus default data is discussed further in this guidance.
The following are examples of data needed to run MOVES or EMFAC, as described in
Sections 4 and 5:
• Traffic data sufficient to characterize each link in the project area;
• Starts per hour and number of vehicles idling during each hour for off-network
links/sources;
• Vehicle types and age distribution expected in the project area; and
• Temperature and humidity data for each month and hour included in the analysis.
Depending on the air quality model to be used, the following are examples of data that
will likely be needed, as described in Sections 7 through 9:
• Surface meteorological data from monitors that measure the atmosphere near the
ground;
22
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• Upper air data describing the vertical temperature profile of the atmosphere;
• Land use data describing surface characteristics near the surface meteorological
monitors;
• Nearby population data; and
• Information necessary for determining locations of air quality modeling receptors.
To complete the PM hot-spot analysis, areas will also need data on background
concentrations in the project area from nearby or other emission sources, as described in
Section 8.
3.4 ESTIMATE ON-ROAD MOTOR VEHICLE EMISSIONS (STEP 3)
There are two approved motor vehicle emissions models available for estimating the
project's exhaust, brake wear, and tire wear emissions. See Section 4 for more on
estimating these PM emissions with EPA's MOVES model. Section 5 describes how to
apply EMFAC for estimating these emissions for projects in California.
3.5 ESTIMATE EMISSIONS FROM ROAD DUST, CONSTRUCTION, AND
ADDITIONAL SOURCES (STEP 4)
Section 2.5 provides more information about when re-entrained road dust and/or
construction emissions are included in PM hot-spot analyses. Section 6 describes
methods for estimating these emissions.
There may be other sources of emissions that also need to be estimated, and included in
air quality modeling. Section 8 provides further information regarding how to account
for these emissions in a PM hot-spot analysis and Appendix I describes how to estimate
locomotive emissions.
3.6 SELECT AN AIR QUALITY MODEL, DATA INPUTS AND RECEPTORS
(STEP 5)
An air quality model estimates PM concentrations at specific points in the project area
known as "receptors." Emissions that result from the project (including those from
vehicles, dust, and construction from Steps 3 and 4) as well as any other nearby emission
sources that are affected by the project (e.g., expanded locomotive emissions at a freight
terminal) are included in the selected air quality model, which predicts how emissions are
dispersed based on meteorological and other input data.
There are two air quality models—AERMOD and CAL3QHCR— recommended for use
in PM hot-spot analyses, depending on the project involved. Basic information about
23
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these models, including how to select an appropriate model for a particular project and
the data needed to run them, is found in Section 7 and Appendix J.
3.7 DETERMINE BACKGROUND CONCENTRATIONS FROM NEARBY AND
OTHER SOURCES (STEP 6)
The PM hot-spot analysis must also account for background PM concentrations in the
project area. Section 8 provides further information on selecting representative
background concentrations, including when to incorporate nearby sources into air quality
modeling.
3.8 CALCULATE DESIGN VALUES AND DETERMINE CONFORMITY (STEP 7)
In general, the PM concentrations estimated from air quality modeling (from Step 5) are
then combined with background concentrations (from Step 6) at the receptor locations for
both the build and no-build scenarios. The resulting statistic is referred to as a design
value; how it is calculated depends on the form of the NAAQS. If the design value in the
build scenario is less than or equal to the relevant PM NAAQS at appropriate receptors,
then the project meets conformity requirements. In the case where the design value is
greater than the NAAQS in the build scenario, a project could still meet conformity
requirements if the design values in the build scenario were less than or equal to the
design values in the no-build scenario at appropriate receptors. See Sections 2.4 and 9
for further details on build/no-build approaches and implementation.
3.9 CONSIDER MITIGATION OR CONTROL MEASURES (STEP 8)
Where a project does not meet conformity requirements, a project sponsor may consider
mitigation or control measures to reduce emissions in the project area. If such measures
are considered, additional modeling will need to be completed and new design values
calculated to ensure that conformity requirements are met. A project sponsor could
decide to add mitigation or control measures at any time in the process; such measures
must include written commitments for implementation (40 CFR 93.125). See Section 10
for more information on possible measures for consideration.
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3.10 DOCUMENT THE PM HOT-SPOT ANALYSIS (STEP 9)
The PM hot-spot analysis should include sufficient documentation to support the
conclusion that a proposed project meets conformity rule requirements per 40 CFR
93.116 and 93.123. This documentation should include, at a minimum:
• A description of the proposed project, including where the project is located, the
project's scope (e.g., adding an interchange, widening a highway, expanding a
major bus terminal), when the project is expected to be open to traffic, travel
activity projected for the analysis year(s), and what part of 40 CFR 93.123(b)(l)
applies;30
• A description of the analysis year(s) examined and the factors considered in
determining the year(s) of peak emissions;
• Emissions modeling, including the emissions model used (e.g., MOVES),
modeling inputs and results, and how the project was characterized in terms of
links;
• Modeling inputs and results for estimating re-entrained road dust, construction
emissions, and any nearby source emissions (if applicable to a particular PM hot-
spot analysis);
• Air quality modeling data, including the air quality model used, modeling inputs
and results, and description of the receptors employed in the analysis;
• A description of the assumptions used to determine background concentrations;
• A discussion of any mitigation or control measures that will be implemented, the
methods and assumptions used to quantify their expected effects, and associated
written commitments;
• A description of how the interagency consultation and public participation
requirements in 40 CFR 93.105 were met; and
• A conclusion for how the proposed proj ect meets 40 CFR 93.116 and 93.123
conformity requirements for the PM2.5 and/or PMio NAAQS.
Documentation should describe the sources of data used in preparing emissions and air
quality modeling inputs. This documentation should also describe any critical
assumptions that have the potential to affect predicted concentrations. Documentation of
PM hot-spot analyses would be included in the project-level conformity determination.
30 This information could reference the appropriate sections of any NEPA document prepared for the
project.
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Section 4: Estimating Project-Level PM Emissions Using
MOVES
4.1 INTRODUCTION
This section of the guidance describes how to use MOVES to estimate PM exhaust, brake
wear, and tire wear emissions for PM hot-spot analyses outside of California.31 This
section focuses on determining the appropriate project-level inputs and how MOVES
should be run to provide the necessary information to complete air quality modeling.32
MOVES is a computer model designed by EPA to estimate emissions from cars, trucks,
buses and motorcycles. MOVES replaces MOBILE6.2, EPA's previous emissions
model.33 MOVES is based on an extensive review of in-use vehicle data collected and
analyzed since the release of MOBILE6.2. MOVES estimates PM emissions to account
for speed and temperature variations and models emissions at a high resolution. As a
result, MOVES allows users to incorporate a much wider array of vehicle activity data
for each roadway link, as well as start and extended idle activity in transit or other
terminal projects.
Exhibit 4-1 (following page) shows the necessary steps for applying the MOVES model
for project-level PM hot-spot analyses.
This section presumes users already have a basic understanding of how to run the
MOVES model.34 MOVES includes a default database of meteorology, fleet, activity,
fuel, and control program data for the entire United States. The data included in this
database come from a variety of sources which are not necessarily the most accurate or
up-to-date information available at the local level for a particular project. This section
describes when the use of that default database is appropriate for PM hot-spot analysis, as
well as when available local data must be used (40 CFR93.110 and 93.123(c)).
31 This guidance is applicable to current and future versions of the MOVES model, unless EPA notes
otherwise when approving the model for conformity purposes.
32 Technical guidance on using MOVES for regional emissions inventories can be found in "Technical
Guidance on the Use of MOVES2010 for Emission Inventory Preparation in State Implementation Plans
and Transportation Conformity," EPA-420-B-10-023 (April 2010); available online at:
www.epa.gov/otaq/stateresources/transconf/policy.htm.
33 EPA stated in the preamble to the March 2006 final rule that finalizing the MOVES emissions model was
critical before quantitative PM hot-spot analyses are required, due to the limitations of applying
MOBILE6.2 for PM at the project level. See EPA's March 2006 final rule for further information (71 FR
12498-12502).
34 The MOVES model, user guide, and supporting documentation are available online at:
www.epa.gov/otaq/models/moves/index.htm.
26
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Exhibit 4-1. Steps for Using MOVES in a Quantitative PM Hot-spot Analysis
Divide the project into
links
4,2)
Determine the number of
MOVES mas
f Section 4,3}
Enter time period
(Section 4,4.3}
Specify count}7
(Section 4,4,4)
Select
fuel/vehicle
combination
(Section 4,4.5)
Select road type
(Section 4.4.6)
/Does project
an "off-network"
^ component with
significant engine
TCa
\
or idling?
Include "off-
network"
type
PM
pollutants &
processes
(Section 4,4.7)
Enter meteorology
data
(Section 4,5.1)
Build age
distribution table
(Section 4,5.2)
i
L
Define
fuels/fuel mix
(Section 4.53)
Populate off-
network table
(Section 4.5.9)
Populate link
source type
(Section 4,5,5)
Describe link
activity
(Sections 4.5,6-
4.5,8}
RUB MOVES &
generate emission
factors
(Section 4.6)
Note: The steps in this exhibit and in the accompanying text describe how to use MOVES at the
project-level for a PM hot-spot analysis.
-------
As discussed in Section 2.4, it is suggested that project sponsors conduct emissions and
air quality modeling for the project build scenario first. If the resulting design value does
not exceed the NAAQS, then the project meets the hot-spot analysis requirements of
project-level conformity, and it is not necessary to model the no-build scenario.
Following this approach will allow users to avoid unnecessary emissions and air quality
modeling.
Finally, Section 4 describes how to use MOVES to estimate emissions from a highway or
transit project that requires a PM hot-spot analysis ("the project"); this section could also
be used to estimate emissions for any other highway and transit facilities in the project
area, when necessary.
4.2 CHARACTERIZING A PROJECT IN TERMS OF LINKS
Prior to entering data into MOVES, the first step is to identify the project type and the
associated emission processes (running, start, brake wear, tire wear, extended idle, and
crankcase) to be modeled. This guidance distinguishes between two types of
transportation projects: (1) highway and intersection projects, and (2) transit or other
terminal projects:
• For highway and intersection projects, running exhaust, crankcase, brake wear,
and tire wear emissions are the main focus.
• For transit and other terminal projects, start, crankcase, and extended idle
emissions are typically needed; in some cases, these projects will also need to
address cruise, approach and departure running exhaust emissions on affected
links.
The goal of defining a project's links is to accurately capture emissions where they occur.
Within MOVES, a link represents a segment of road or an "off-network" location where
a certain type of vehicle activity occurs.35 Generally, the links specified for a project
should include segments with similar traffic/activity conditions and characteristics (e.g.,
decelerating vehicles approaching an intersection should be treated as one link). From
the link-specific activity and other inputs, MOVES calculates emissions from every link
of a project for a given time period (or run). In MOVES, running emissions, including
periods of idling at traffic signals, are defined in the Links Importer (see Section 4.5.6),
while starts and extended periods of idling (e.g., truck idling at a freight terminal) are
defined in the Off-Network Importer (see Section 4.5.9). There are no limits to the
number of links that can be defined in MOVES.
35 "off-network" in the context of MOVES refers to an area of activity not occurring on a roadway.
Examples of off-network links include parking lots and freight or bus terminals.
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4.2.1 Highway and intersection projects
General
A PM hot-spot analysis fundamentally depends on the availability of accurate data on
roadway link speed and traffic volumes for build and no-build scenarios.36 Thus, local
traffic data should be used to characterize each link sufficiently. It is recommended that
the user divide a project into separate links to allow sufficient resolution at different
vehicle traffic and activity patterns; characterizing this variability in emissions within the
project area will assist in air quality modeling (see Section 7).
In MOVES, activity on free-flow highway links can be defined by an average speed, link
drive schedule, or operating mode ("Op-Mode") distribution (discussed in Section 4.5.7).
For analyses with MOVES, average speed and traffic volume, at a minimum, is needed
for each link. If no other information is available, MOVES uses default assumptions of
vehicle activity patterns (called drive cycles) for average speed and type of roadway to
estimate emissions. Default drive cycles use different combinations of vehicle activity
(acceleration, deceleration, cruise, and/or idle) depending on the speed and road type.
For example, if the link average speed is 30 mph and it is an urban arterial (urban
unrestricted road type), MOVES uses a default drive cycle that includes a high proportion
of acceleration, deceleration, and idle activity as would be expected on an urban arterial
with frequent stops. If the average speed is 60 mph and it is a rural freeway (rural
restricted road type), MOVES uses a default drive cycle that assumes a higher proportion
of cruise activity, smaller proportions of acceleration and deceleration activity, and little
or no idle activity.
Project sponsors should determine average congested speeds by using appropriate
methods based on best practices used for highway analysis.37 Some resources are
available through FHWA's Travel Model Improvement Program (TMIP).38
Methodologies for computing intersection control delay are provided in the Highway
Capacity Manual 2000.39
As described further in Section 4.5.7, users should take advantage of the full capabilities
of MOVES for estimating emissions on different highway and intersection project links.
Project sponsors should document available traffic data sets, their sources, key assumptions, and the
methods used to develop build and no-build scenario inputs for MOVES. Documentation should include
differences between how build and no-build traffic projections are obtained. For projects of local air
quality concern, differences in traffic volumes and other activity changes between the build and no-build
scenarios must be accounted for in the data that is used in the PM hot-spot analysis.
37 As discussed in Section 7, the use of the CAL3QHCR queuing algorithm for intersection idle queues is
not recommended. Rather, idling vehicles should be represented in combination with decelerating,
accelerating, and free-flow traffic on an approach segment of an intersection.
38 See FHWA's TMIP website: http://tmip.fhwa.dot.gov/.
39 Users should consult the most recent version of the Highway Capacity Manual. As of the release of this
guidance, the latest version is the Highway Capacity Manual 2000, which can be obtained from the
Transportation Research Board (see http://144.171.ll.107/Main/Public/Blurbs/152169.aspx for details).
29
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Although average speeds and travel volumes are typically available for most
transportation projects and may need to be relied upon during the transition to using
MOVES, users can develop and use more precise data through the MOVES Operating
Mode Distribution Importer or Link Drive Schedule Importer, as described further below.
When more detailed data are available to describe the pattern of changes in vehicle
activity (proportion of time in acceleration, deceleration, cruise, or idle activity) over a
length of road, MOVES is capable of calculating these specific emission impacts. EPA
encourages users to consider these options for highway and intersection projects,
especially as MOVES is implemented further into the future, or for more advanced
MOVES applications.
Free-flow Highway Links
The links defined in MOVES should capture the expected physical layout of a project and
representative variations in vehicle activity. A simple example would be a single, one
directional, four-lane highway that could be characterized as just one link. More
sophisticated analyses may break up traffic flow on that single link into multiple links of
varying operating modes or drive cycles that may have different emission factors
depending on the relative acceleration, cruise, or deceleration activity on each segment of
that link. In general, the definition of a link will depend on how much the type of vehicle
activity (acceleration, deceleration, cruise or idle) changes over a length of roadway, the
level of detail of available data, and the modeling approach used with MOVES. For a
highway lane where vehicle behavior is fairly constant, the length of the link could be
longer and the use of detailed activity data will have a smaller impact on results.
Intersection Links
If the project analysis involves intersections, the intersections need to be treated
separately from the free-flow links that connect to those intersections. Although road
segments between intersections may experience free-flow traffic operations, the
approaches and departures from the intersections will likely involve acceleration,
deceleration, and idling activity not present on the free-flow link. For intersection
modeling, the definition of link length will depend on the geometry of the intersection,
how that geometry affects vehicle activity, and the level of detail of available activity
information. Guidance for defining intersection links is given in Appendix D, but the
definition of links used for a particular project will depend of the specific details of that
project and the amount of available activity information.40
Note: For both free-flow highway and intersection links, users may directly enter output
from traffic simulation models in the form of second-by-second individual vehicle
trajectories. These vehicle trajectories for each road segment can be input into MOVES
using the Link Drive Schedule Importer and defined as unique LinklDs. There are no
limits in MOVES as to how many links can be defined; however, model run times
40 As discussed in Section 7, the use of the CAL3QHCR queuing algorithm for intersection idle queues is
not recommended. Rather, idling vehicles should be represented in combination with decelerating,
accelerating, and free-flow traffic on an approach segment of an intersection.
30
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increase as the user defines more links. More information on using vehicle trajectories
from traffic micro-simulation models is found in Appendix D.
4.2.2 Transit and other terminal projects
For off-network sources such as a bus terminal or intermodal freight terminal, the user
should have information on starts per hour and number of vehicles idling during each
hour. This activity will likely vary from hour to hour. Additionally, if there are vehicles
starting, it is necessary to provide an estimate of the duration that vehicles are parked
before starting (soak-time distribution). It is recommended that the user divide such a
project into separate links to appropriately characterize variability in emission density
within the project area (as discussed in Section 7). In this case, each "link" describes an
area with a certain number of vehicle starts per hour, or a certain number of vehicles
idling during each hour.
Some transit and other terminal projects may have significant running emissions similar
to free-flow highway projects (such as buses and trucks coming to and from an
intermodal terminal). These emissions can be calculated by defining one or more unique
running links as described in Section 4.2.1 and Appendix D (that is, in addition to any
other roadway links associated with the project). These running link emissions can then
be aggregated with the emissions from starts and idling from non-running activity on the
transit or other terminal link outside of the MOVES model to generate the necessary air
quality model inputs.
Long duration idling (classified in MOVES as OpModelD 200) can only be modeled in
MOVES for long-haul combination trucks. Idling for other vehicles and shorter periods
of idling for long-haul combination trucks should be modeled as a project link with an
operating mode distribution that consists only of idle operation (OpMode 1). This can be
specified in the Links table by inputting the vehicle population and specifying an average
speed of "0" mph.
Note: The user may choose to exclude sources such as a separate service drive, separate
small employee parking lot, or other minor sources that are determined to be
insignificant to project emissions.
4.3 DETERMINING THE NUMBER OF MOVES RUNS
4.3.1 General
When MOVES is run at the project scale, it estimates emissions for only the hour
specified by the user. Before running MOVES to calculate emission factors, users should
first determine the number of unique scenarios that can sufficiently describe activity
variation in a project. In most projects, traffic volume, average speed, idling, fleet mix,
and the corresponding emission factors will likely vary from hour to hour, day to day,
and month to month. However, it is unlikely that data are readily available that capture
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such finite changes. Project sponsors may have activity data collected at a range of
possible temporal resolutions. The conformity rule requires the use of the latest planning
assumptions or data available at the time the conformity analysis begins (40 CFR
93.110).41 Depending on the sophistication of the activity data analysis for a given
project, these data may range from a daily average-hour and peak-hour value to hourly
estimates for all days of the year. EPA encourages the development of sufficient travel
activity data to capture the expected ranges of traffic conditions for the build and no-build
scenarios.
The number of MOVES runs should be based on the best available activity data and the
PM NAAQS involved. One of the advantages to using MOVES is that, for the first time,
PM emission estimates are sensitive to temperature changes through a day and across a
year. Therefore, EPA is recommending the minimum number of MOVES runs that is
necessary for PM hot-spot analysis to capture changes in emission rates due to changes in
ambient conditions.42 Exhibit 4-2 includes EPA's recommendations for PM hot-spot
analyses:
Exhibit 4-2. Typical Number of MOVES Runs for an Analysis Year
Applicable NAAQS
Annual PM2.5 NAAQS only
24-hour PM2.5 NAAQS only
24-hour PMio NAAQS only
Annual and 24-hour PM
NAAQS44
Build Scenario
16
1 6 (4 in certain cases)
1 6 (4 in certain cases)
16
No-build Scenario43
16
1 6 (4 in certain cases)
1 6 (4 in certain cases)
16
Hot-spot analyses for the annual PM2.5 NAAQS should include 16 unique MOVES runs
(i.e., four runs for different time periods for each of four calendar quarters). For a typical
build/no-build analysis, a total of 32 runs would be needed (16 for the build scenario and
16 for the no-build scenario). Hot-spot analyses for only the 24-hour PM2.5 or PMio
NAAQS should also be completed with 16 MOVES runs for each scenario, except in
cases where potential PM NAAQS violations are expected to occur in only one quarter of
the calendar year. In such cases, the user may choose to model only that quarter with
41 See "EPA and DOT Joint Guidance for the Use of Latest Planning Assumptions in Transportation
Conformity Determinations," EPA-420-B-08-901 (December 2008) for a more detailed discussion of the
latest planning assumptions requirements:
www.epa.gov/otaq/stateresources/transconf/policy/420b08901.pdf.
42 Information on PM emission rate sensitivity to temperature inputs is available in "Draft MOVES2009
Highway Vehicle Temperature, Humidity, Air Conditioning, and Inspection and Maintenance
Adjustments" at: www.epa.gov/otaq/models/moves/techdocs/420p09003.pdf.
43 There are some cases where the no-build scenario and associated emissions and air quality modeling is
not necessary. See Section 2.4 for further information.
44 Such a situation would include cases where a project is located in a nonattainment/maintenance area for
both the annual PM2.5 NAAQS and either a 24-hour PM2.5 NAAQS or the 24-hour PM10 NAAQS.
32
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four MOVES runs for each scenario. See Section 3.3 for more information on when
using fewer MOVES runs is appropriate for the 24-hour PM NAAQS.
The product of the MOVES analysis is a year's (or quarter's) worth of hour-specific
emission factors for each project link that will be applied to the appropriate air quality
model (discussed in Section 7) and compared to the relevant PM NAAQS (discussed in
Section 9). The following subsections provide further information for determining
MOVES runs for all PM NAAQS, based on the level of available travel activity data.
4.3.2 Projects with typical travel activity data
Traffic forecasts for highway and intersection projects are often completed for annual
average daily traffic volumes, with an allocation factor for a daily peak-hour volume.
This data can be used to conduct an analysis with MOVES that is representative for all
hours of the year. To complete 16 MOVES runs as outlined above, the user should run
MOVES for four months: January, April, July, and October; and four weekday time
periods: morning peak (AM), midday (MD), evening peak (PM), and overnight (ON).45
The AM and PM peak periods should be run with peak-hour traffic activity; MD and ON
periods should be run with average-hour activity. The most reasonable methods in
accordance with good practice should be used to obtain the peak hour allocation factors
and diurnal distribution of traffic; these methods must be determined in accordance with
interagency consultation procedures (40 CFR 93.105(c)(l)(i)).
The results for each of the four hours can then be extrapolated to cover the entire day.
For example, the peak-hour volume can be used to represent activity conditions over a
three-hour morning (AM) and three-hour evening (PM) period. The remaining 18 hours
of the day can be represented by the average-hour volume. These 18 hours would be
divided into a midday (MD) and overnight (ON) scenario.
The following is one suggested approach for an analysis employing the average-
hour/peak-hour traffic scenario:
• Morning peak (AM) emissions based on traffic data and meteorology occurring
between 6 a.m. and 9 a.m.;
• Midday (MD) emissions based on data from 9 a.m. to 4 p.m.;
• Evening peak (PM) emissions based on data from 4 p.m. to 7 p.m.; and
• Overnight (ON) emissions based on data from 7 p.m. to 6 a.m.
If there are local or project-specific data to suggest that the AM or PM peak traffic
periods will occur in different hours than the default values suggested here, or over a
longer or shorter period of time, that information should be documented and the hours
representing each time period adjusted accordingly. Additionally, users should determine
peak periods for the build and no-build scenarios independently and not assume that each
scenario is identical.
45 If only four MOVES runs are required for a PM hot-spot analysis for a 24-hour PM NAAQS, four runs
would be done for the same weekday time periods, except only for one quarter (i.e., January, April, July, or
October) for each build or no-build scenario.
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The emission factors for each month's runs should be used for the other months within
the quarter. The months suggested for the minimum number of MOVES runs correspond
to the first month of each quarter. For instance, January emissions should be assumed to
represent February and March emissions, April should be used to represent May and June
emissions, and so forth.46
4.3.3 Projects with additional travel activity data
Some project sponsors may have developed traffic or other activity data to show
variations in volume and speed across hours, days, or months. Additionally, if users are
modeling a transit or other terminal project, traffic volumes, starts, and idling estimates
are likely to be readily available for each hour of the day. Under either of these
circumstances, users have the option of applying the methodology described above (using
average-hour and peak-hour as representative for all hours of the year) if it is determined
through the interagency consultation process that using the additional data would not
significantly impact the emissions modeling results. Alternatively, additional MOVES
runs could be generated to produce unique emission factors using these additional activity
data and emission factors for each period of time for which specific activity data are
available.
4.4 DEVELOPING BASIC RUN SPECIFICATION INPUTS
Once the user has defined the project conceptually in terms of links and determined the
number of MOVES runs, the next step in using MOVES for project-level analyses is to
develop a run specification ("RunSpec"). The RunSpec is a computer file in XML
format that can be edited and executed directly or with the MOVES Graphical User
Interface (GUI). MOVES needs the user to set up a RunSpec to define the place and time
of the analysis as well as the vehicle types, road types, fuel types, and the emission-
producing processes and pollutants that will be included in the analysis.
The headings in this subsection describe each set of input options needed to create the
RunSpec as defined in the Navigation panel of the MOVES GUI. In order to create a
project-level RunSpec, the user would go down the Navigation panel filling in the
appropriate data for each of the items listed. A new panel will open for each item:
• Description
• Scale
• Time Spans
• Geographic Bounds
• Vehicles/Equipment
• Road Type
• Pollutants and Processes
• Manage Input Data Sets
46 Rather than use the middle month of the first quarter (February), January is used because it is typically
the coldest month of the year and therefore has the highest PM emission rates.
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• Strategies
• Output
• Advanced Performance Features
Additional information on each panel can be found in the MOVES User Guide available
on EPA's website (www.epa.gov/otaq/models/moves/index.htm). The appropriate
sections of the user guide are referenced when describing the RunSpec creation process
below.
4.4.1 Description
(MOVES User Guide Section 2.2.1)
The Description panel allows the user to enter a description of the RunSpec using up to
5,000 characters of text. Entering a complete description of the RunSpec is important for
users to keep track of their MOVES runs as well as to provide supporting documentation
for the regulatory submission. Users may want to identify the project, the time period
being analyzed, and the purpose of the analysis in this field.
4.4.2 Scale
(MOVES User Guide Section 2.2.2)
The Scale panel in MOVES allows the user to select different scales or domains for the
MOVES analysis. All MOVES runs for project-level analysis must be done using the
"Project" domain in the Scale panel. Selecting the "Project" domain is necessary to
allow MOVES to accept detailed activity input at the link level.47
Users can select either "Inventory" or "Emission Rates" as output, depending on the air
quality model being used:
• When using AERMOD, a grams/hour emission factor is needed. Users should
select "Inventory," which produces results for total emissions on each link; this is
equivalent to a grams/hour/link emission factor.
• When using CAL3QHCR, the "Emission Rates" option should be selected to
produce link specific grams/vehicle-mile emission factors.
This guidance explains the steps of post-processing both "Inventory" and "Emission
Rates" results to produce the desired emission factors in Section 4.6.
47 Running MOVES using the "County" or "National" domains would not allow for detailed link-level
input or output that is needed for PM hot-spot analyses.
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4.4.3 Time Spans
(MOVES User Guide Section 2.2.3)
The Time Spans panel is used to define the specific time period covered in the MOVES
run. The Time Spans panel allows the user to select the time aggregation level and the
year, month, day, and hour included in the run.
For the project domain, the MOVES model processes one hour, of one day, of one
month, of one year for each run; that is, each MOVES run represents one specific hour.
The user should enter the desired time period in the MOVES Time Span panel for
estimating PM2.5 and/or PMio emissions for the relevant NAAQS in a given
nonattainment or maintenance area. Time aggregation should be set to "hour," which
indicates no pre-aggregation. The "day" selection should be set to "weekday" or
"weekend," but not both. Most users will be defining activity for a typical weekday. The
year, month, and hour should be set to specifically describe each MOVES run. For
instance, one run might be: 2015, January, 8:00 to 8:59 a.m. (the start and end hours both
set to 8:00 to 8:59 a.m.). The user may choose to build a batch file to automate the
process of running multiple scenarios.48
4.4.4 Geographic Bounds
(MOVES User Guide Section 2.2.4)
The Geographic Bounds panel allows the user to define the specific county that will be
modeled. The MOVES database includes county codes and descriptive information for
all 3,222 counties in the United States. Specifying a county in MOVES determines
certain default information for the analysis. Users should select the specific county
where the project is located. Only a single county (or single custom domain) can be
included in a MOVES run at the project level. If a project spans multiple counties, users
have three options:
1. If the fuel supply and age distribution of vehicles in the fleet are the same for all
of the counties, select the county in which the majority of the project area is
located;
2. If not, separate the project into multiple parts (each of which is in a separate
county) and do a separate MOVES run for each part; or
3. Use the custom domain option to model one unique area that represents all the
project counties.
4.4.5 Vehicles/Equipment
(MOVES User Guide Section 2.2.5)
The Vehicles/Equipment panel is used to specify the vehicle types that are included in the
MOVES run. MOVES allows the user to select from among 13 "source use types" (the
terminology that MOVES uses to describe vehicle types) and several different fuels.
48 For more information about using batch commands, see Appendix C of the MOVES User Guide,
available online at: www. epa. gov/oms/models/moves/index.htm.
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Some fuel/source type combinations do not exist (e.g., diesel motorcycles) and therefore
are not included in the MOVES database. PM hot-spot analyses must include all vehicle
types that are expected to operate in the project area. Users should select the appropriate
fuel and vehicle type combinations in the On Road Vehicle Equipment panel to reflect
the full range of vehicles that will operate in the project area. The fuel type "Placeholder
Fuel Type" should not be selected as it can cause errors.
4.4.6 Road Type
(MOVES User Guide Section 2.2.6)
The Road Type panel is used to define the types of roads that are included in the project.
MOVES defines five different road types:
• Rural Restricted Access - a rural highway that can be accessed only by an on-
ramp;
• Rural Unrestricted Access - all other rural roads (arterials, connectors, and local
streets);
• Urban Restricted Access - an urban highway that can be accessed only by an on-
ramp;
• Urban Unrestricted Access - all other urban roads (arterials, connectors, and local
streets); and
• Off-Network - any location where the predominant activity is vehicle starts and
idling (parking lots, truck stops, rest areas, freight or bus terminals).
MOVES uses these road types to determine the default drive cycle on a particular link.
For example, MOVES uses drive cycles for unrestricted access road types that assume
stop-and-go driving, including multiple accelerations, decelerations, and short periods of
idling. For restricted access road types, MOVES uses drive cycles that include a higher
fraction of cruise activity with much less time spent accelerating or idling.
For project-level analyses, the extent upon which MOVES uses these default drive cycles
will depend on how much additional information the user can supply for the link. The
process of choosing default or local drive cycles is described in Sections 4.2 and 4.5.7.
However, even if the user will be supplying detailed, link-specific drive cycle
information or an Op-Mode distribution, road type is a necessary input in the RunSpec
and users should select one or more of the five road types that correspond to the road
types of the links that will be included in the project area. The determination of rural or
urban road types should be based on the Highway Performance Monitoring System
(HPMS) functional classification of the road type.
Additionally, any project that includes a significant number of engine starts or significant
amounts of extended idling for heavy-duty vehicles needs to include the "Off-Network"
road type to account for emissions from those activities properly. More details on
describing inputs for engine start and idling activity are given in Section 4.5.9.
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4.4.7 Pollutants and Processes
(MOVES User Guide Section 2.2.7)
The Pollutant and Processes panel is used to select both the types of pollutants and the
emission processes that produce them. For PM2 5 or PMio emissions, MOVES calculates
emissions for several pollutant species:
• Organic Carbon (OC)
• Elemental Carbon (EC)
• Sulfate Particulate
• Brake Wear Particulate
• Tire Wear Particulate
In addition, MOVES divides emissions by pollutant process. For a PM hot-spot analysis,
the categories are:
• Running Exhaust
• Start Exhaust
• Extended Idle Exhaust
• Crankcase Running Exhaust
• Crankcase Start Exhaust
• Crankcase Extended Idle Exhaust
• Brake Wear
• Tire Wear
For a PM2 5 hot-spot analysis, the user should select "Primary Exhaust PM2 5 - Total" (or
"Primary Exhaust PMio - Total" if it is a PMio hot-spot analysis), which is an aggregate
of each of the pollutant species (OC, EC, and sulfate) for each process. For MOVES to
run, the user would select each individual PM species (i.e., "Primary PM2 5 - Organic
Carbon," "Primary PM2 5 - Elemental Carbon," "Primary PM2 5 - Sulfate Particulate," or
the PMio equivalents). In addition, if the analysis has road links with running emissions,
users would also select "Primary PM2 5 - Brake Wear Particulate" and "Primary PM2 5 -
Tire Wear Particulate" (or their PMio equivalents) as brake wear and tire wear are not
included in the exhaust totals.
MOVES does not automatically sum the appropriate processes to create an aggregate
emission factor, although EPA is considering creating one or more MOVES scripts that
would automate the summing of aggregate emissions when completing project-level
analyses.49 Therefore, the user should calculate total PM from the MOVES output table
results for each link using the formulas described below:
For highway links (roads, intersections, ramps, etc.) where output was specified as a
grams/vehicle-mile emission factor ("Emission Rates" output), the aggregate total PM
49 These scripts would be made available for download on the MOVES website
(www.epa.gov/otaq/models/moves/tools.htm'), when available.
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emission factor (i.e., the sum of all PM emission factors for a link) needs to be calculated
using the formula:
PMaggregate total = (PMtotal running) + (PMtotal crankcase running) + (brake Wear) + (tire Wear)
For transit and other terminal project activity (starts and extended idle) where output was
selected as grams/hour ("Inventory" output), the aggregate total PM emission factor (i.e.,
the sum of all PM emission factors for a link) needs to be calculated using the formula:
PMaggregate total = (PMtotal starts) + (PMtotal crankcase starts) + (PMtotal ext. idle) +
(PMtotal crankcase ext. idle)
For transit and other terminal project links that contain starts and extended idling as well
as running emissions, and output was selected as "Inventory" output (grams/hour/link),
the aggregate total PM emission factor for each link needs to be calculated using the
formula:
PMaggregate total = (PMtotal running) + (PMtotal crankcase running) + (PMtotal starts) +
(PMtotal crankcase starts) + (PMtotal ext. idle) + (PMtotal crankcase ext. idle) +
(brake wear) + (tire wear)
4. 4. 8 Manage Input Data Sets
(MOVES User Guide Section 2.2.8)
Most analyses will not use the Manage Input Data Sets panel. One possible application is
to specify user-supplied databases to be read by the model during execution of a run.
However, for project-level analysis in MOVES, the Project Data Manager (described
below) serves this same function while providing for the creation of data table templates
and for the review of default data. EPA specifically developed the Project Data Manager
for project analyses and recommends using it, instead of the Manage Input Databases
panel, to create and specify user supplied database tables.
4.4.9 Strategies
(MOVES User Guide Section 2.2.9)
In MOVES, the Strategies panel can be used to model alternative control strategies that
affect the composition of the vehicle fleet. The MOVES model has two alternative
control strategies built into the Strategies panel:
• The Alternative Vehicle Fuels and Technologies (AVFT) strategy allows users to
modify the fraction of alternative fuel vehicles in each model year.
• The On-Road Retrofit strategy allows the user to enter information about diesel
trucks and buses that have been retrofitted with emission control equipment.
A common use of the AVFT panel would be to change the diesel fractions of the fleet.
Users can modify the default assumptions about diesel, gasoline, and CNG use for each
source type and model year. If local information is available on these fractions, the
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AVFT should be used to modify the defaults. For instance, users modeling a transit
facility may use the AVFT to specify that the entire fleet of buses uses CNG, or entirely
diesel, rather than a default mix of both fuel types.
Another application of the Strategies panel would be to apply a retrofit program to the
fleet. For example, a bus terminal project might include plans to mitigate emissions by
retrofitting the bus fleet that will operate at that terminal with control equipment that
reduces PM emissions. In that case, the user would specify the details of the retrofit
project using the On-Road Retrofit Strategy panel. The latest guidance on retrofit
programs can be located at the EPA's conformity website:
www. epa. gov/otaq/stateresources/transconf/policy. htm. Strategies that affect vehicle
activity, such as implementing a truck idle reduction plan, should be handled in the Off-
Network Importer and Links Importer.
See Section 10 for further information regarding the inclusion of mitigation and/or
control measures in PM hot-spot analyses.
4.4.10 Output
(MOVES User Guide Section 2.2.10)
Selecting Output in the Navigation panel provides access to two additional panels:
General Output and Output Emissions Detail. Each of these allows the user to specify
aspects of the output data.
Under General Output, users should make sure to choose "grams" and "miles" for the
output units in order to provide results for air quality modeling. Also, "Distance
Traveled" and "Population" should be selected under the "Activity" heading to obtain
vehicle volume information for each link in the output.
Output Emissions Detail is used to specify the level of detail desired in the output data.
Emissions by hour and link are the default selections and cannot be changed. Road type
will also be checked if output by Emission Rates was selected. EPA recommends that
users check the box labeled "Emission Process." No other boxes should be selected in
order to produce fleet aggregate emission factors for each link.50 Emission rates for each
process can be appropriately summed to calculate aggregate PM emission factors for each
link (as described in Section 4.4.7).
4.4.11 Advanced Performance Features
(MOVES User Guide Section 2.2.11)
Most analyses will not use the Advanced Performance Features panel. This menu item is
used to invoke features of MOVES that improve run time for complex model runs by
50 Users may choose to select output by Source Type if using AERMOD to model a volume source. It may
be appropriate to characterize a volume source with an initial vertical dimension and source release height
that is the emission-weighted average of light-duty and heavy-duty vehicles. See Section J.3.3 of the
Appendix for more information on characterizing volume sources.
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saving and reusing intermediate results. For specific applications, the user may want to
"save data" for deriving the intermediate MOVES calculation of an Op-Mode
Distribution from an average speed or link drive schedule. This is discussed further in
the MOVES User Guide, as well as demonstrated in the quantitative PM hot-spot analysis
example of a transit project in Appendix F.
4.5 ENTERING PROJECT DETAILS USING THE PROJECT DATA MANAGER
After completion of all the necessary panels to create the RunSpec, the user would then
create the appropriate input database tables that describe the project in detail. As
described in Section 4.3, a typical PM hot-spot analysis will involve 32 MOVES runs (16
runs for each build and no-build scenario), each run needing individual sets of input
database tables to be created. This is done using the Project Data Manager, which can be
accessed from the Pre-Processing menu item at the top of the MOVES GUI or by
selecting Enter/Edit Data in the Domain Input Database section of the Geographic
Bounds panel.
Since modeling a project involves many MOVES runs, good data management practices
are essential to prevent confusion and errors. For example, the name of the project input
database for each run should reflect the purpose of that run (e.g.,
"NoBuildSpringAMPeak_in"). A similar naming protocol should be used for the
RunSpec for each run. Also, each tab of the Project Data Manager includes a box for
entering a "Description of Imported Data." Modelers should make liberal use of these
descriptions to (1) indicate whether default or local data were used, and (2) indicate the
source and date of any local data, along with the filename of imported spreadsheets.
These descriptions are preserved with the input database so reviewers (or future users of
the same runs) will have the documentation of inputs readily at hand.
The Project Data Manager includes multiple tabs to open importers used to enter project-
specific data. These importers are:
• Meteorology
• Age Distribution
• Fuel Supply
• Fuel Formulation
• Inspection and Maintenance
• Link Source Type
• Links
• Link Drive Schedule
• Operating Mode Distribution
• Off-Network
Each of the importers allows the user to create a template file with the necessary data
field names and some key fields populated. The user then edits this template to add
project-specific local data with a spreadsheet application or other tool and imports the
data files into MOVES. In some importers, there is also the option to export default data
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from the MOVES database in order to review and then use it. Once the user determines
that the default data are accurate and applicable to the particular project, or determines
that the default data need to be changed and makes those changes, the user can then
import that data into MOVES. Details of the mechanics of using the data importers are
provided in the MOVES User Guide. Guidance for the use of these importers in PM hot-
spot analyses is described below.
4.5.1 Meteorology
(MOVES User Guide Section 2.3.3.4.1)
The Meteorology Data Importer is used to import temperature and humidity data for the
month and hour that are defined in the MOVES run specification. Although temperature
and humidity data can be entered for all hours, only the one hour selected in the run
specification will be used for PM hot-spot analyses. Meteorology inputs for MOVES
should be the same for build and no-build scenarios.
Users should enter data specific to the project's location and time period modeled, as PM
emissions are found to vary significantly depending on temperature. The accuracy of
emission estimates at the project level improves when meteorological data specific to the
modeled location is included. Default temperature and humidity values are available in
MOVES, but are not recommended for use in a PM hot-spot analysis.
Temperatures must be consistent with those used for the project's county in the regional
emissions analysis (40 CFR 93.123(c)(3)) as well as the air quality modeling inputs used
in the hot-spot analysis. Meteorological data may be obtained either from the National
Weather Service (NWS) or as part of a site-specific measurement program. Local
universities, the Federal Aviation Administration (FAA), military stations, and state and
local air agencies may also be sources of such data. The National Oceanic and
Atmospheric Administration's National Climatic Data Center (NCDC; online at
www.ncdc.noaa.gov/oa/ncdc.html) is the world's largest active archive of weather data
through which years of archived data can be obtained. A data source should be selected
that is representative of local meteorological conditions. Meteorological site selection is
discussed further in Section 7.5.
As discussed in Section 4.3, MOVES will typically be run for multiple time periods and
specific meteorology data that accurately represents these runs is needed to produce
emission estimates for comparison with both the 24-hour and annual PM NAAQS. The
user should employ a minimum of four hours (corresponding to AM peak traffic/PM
peak traffic/MD traffic/ON traffic), for one day (weekday), for January, April, July, and
October. Within each period of day in each quarter, temperatures should be used that
represent the average temperature within that time period. For example, for January AM
peak periods corresponding to 6 a.m. to 9 a.m., the average January temperature based on
the meteorological record for those hours should be used in estimating the average
January AM peak period temperature for MOVES runs. The user may choose to run
additional hours and temperatures beyond the number of traffic periods for which data
exist. For example, within an 11 -hour overnight (ON) modeling period, temperature data
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could be used to differentiate hours with significantly different temperatures, despite
having assumed identical traffic estimates. Humidity estimates should be based on the
same hours and data source as the temperature estimates. See Section 4.3 for further
information on the number of MOVES runs recommended for different project analyses.
4.5.2 Age Distribution
(MOVES User Guide Section 2.3.3.4.3)
The Age Distribution Importer is used to enter data that provides the distribution of
vehicle fractions by age for each calendar year (yearlD) and vehicle type
(sourceTypelD). These data are needed for running MOVES at the project level. The
distribution of agelD (the variable for age) fractions must sum to one for each vehicle
type. These inputs should generally be the same for build and no-build scenarios, unless
something about the project would change them (e.g., a bus terminal project that includes
the purchase of new buses in the build scenario).
To build a MOVES-compatible age distribution table, there are three possible options.
1. If available, users should use the latest state or local age distribution assumptions
from their SIP or transportation conformity regional emissions analysis. For the
initial transition from MOBILE6.2 to MOVES, EPA has provided a registration
distribution converter.51 The tool allows users to input a MOBILE6.2 registration
distribution table (10, 10, 5 format) and obtain a MOVES age distribution table.
Over time, users should develop age distribution data consistent with MOVES.
Some users may have local registration distribution tables for all vehicle classes.
However, there may be cases where the user has registration distributions only for
one or more vehicle classes (e.g., LDVs) and therefore relies on MOBILE6.2
defaults for the remaining vehicle classes. In these cases, the user may use
MOVES default distributions available on the EPA's website.
2. If the project is designed to serve a fleet that operates only locally, such as a
drayage yard or bus terminal, the user should provide project-specific fleet age
distribution data. For most captive fleets, an exact age distribution should be
readily available or obtainable. The data should be in a format compatible with
MOVES. This format includes age fractions in 30-year bins rather than the 25
used in MOBILE6.2. Additionally, vehicle categories need to be in terms of the
13 MOVES source types.
3. If no state or local age distribution is available, the MOVES default age
distribution should be used. This can be obtained from the tables available on the
EPA website: www.epa.gov/otaq/models/moves/tools.htm. The user can select
the analysis year(s) and find the corresponding age distribution. These fractions
are national defaults and could be significantly different than the local project age
distribution. Age distribution can have a considerable impact on emission
This converter can be found online at: www.epa.gov/otaq/models/moves/tools.htm.
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estimates, so the default data should be used only if an alternative state or local
dataset cannot be obtained.
4.5.3 Fuel Supply and Fuel Form ulation
(MOVES User Guide Section 2.3.3.4.8 and 2.3.3.4.9)
The user needs to define in MOVES what fuel(s) and fuel mix will be used in the project
area. The Fuel Supply Importer and Fuel Formulation Importer are used to enter the
necessary information describing fuel mix and fuel type for each MOVES run. These
inputs should generally be the same for build and no-build scenarios, unless something
about the project would change them (e.g., a project that includes alternate fuel vehicles
and infrastructure in the build scenario).
Users should review the default fuel formulation and fuel supply data in MOVES and
make changes only if local volumetric fuel property information is available. Otherwise,
EPA recommends that the MOVES default fuel supply and formulation information be
used. The lone exception to this is in the case of Reid Vapor Pressure (RVP), where a
user should change the value to reflect the differences between ethanol and non-ethanol
blended gasoline.
For additional guidance on defining fuel supply and formulation information, consult the
EPA document "Technical Guidance on the Use of MOVES2010 for Emission Inventory
Preparation in State Implementation Plans and Transportation Conformity" available
online at: www. epa. gov/otaq/stateresources/transconf/policy. htm.
4.5.4 Inspection and Maintenance (I/M)
(MOVES User Guide Section 2.3.3.4.10)
MOVES does not provide a PM emission benefit from an I/M program. If the user
includes an I/M program in the run specification, the selection will have no impact on PM
emissions.
4.5.5 Link Source Type
(MOVES User Guide Section 2.3.3.4.13)
The Link Source Type Importer allows the user to enter the fraction of the link traffic
volume that is represented by each vehicle type (source type). It is not needed if the
project contains only a transit or other terminal (off-network) link. For each LinkID, the
"SourceTypeHourFractions" must sum to one across all source types.
Additionally, the user needs to ensure that the source types selected in the MOVES
Vehicles/Equipment panel match the source types defined through the Link Source Type
Importer.
There are no defaults that can be exported from the Link Source Type Importer. For any
analysis at the project level, the user needs to provide source type fractions for all
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vehicles being modeled and for each MOVES run (as vehicle mixes may change from
hour to hour and month to month). There are two options available to populate the Link
Source Type input:
1. For projects that will have an entirely different source type distribution than that
of the regional fleet, the preferred option is for the user to collect project-specific
data. For projects such as bus or freight terminals or maintenance facilities that
contain links that are primarily used by a specific subset of the regional fleet,
users need to develop the fractions of link traffic volume by vehicle type data
specific to the project. This could be based on analysis of similar existing
projects through the interagency consultation process.
2. If the project traffic data suggests that the source type distribution for the project
can be represented by the distribution of the regional fleet for a given road type,
the user can provide a source type distribution consistent with the road type used
in the latest regional emissions analysis. For example, highways tend to have a
higher fraction of truck traffic than arterial roads. Therefore, the highway source
type distribution used in the regional emissions analysis may be appropriate to use
for a highway project.
4.5.6 Links
(MOVES User Guide Section 2.3.3.4.12)
The Links Importer is used to define the individual roadway links. All links being
modeled should have unique IDs. The Links Importer requires information on each
link's length (in miles), traffic volume (units of vehicles per hour), average speed (miles
per hour), and road grade (percent). Users should follow guidance given above in
Section 4.2 when determining the number of links and the length of specific links.
Consult Section 7 for information on how these links should be formatted for use in air
quality modeling.
4.5.7 Describing Vehicle Activity
(MOVES User Guide Section 2.3.3.4.14 through Section 2.3.3.4.16)
MOVES determines vehicle emissions based on operating modes, which represent
different types of vehicle activity such as acceleration (at different rates), deceleration,
idle, and cruise that have distinct emission rates. MOVES handles these data in the form
of a distribution of the time vehicles spend in different operating modes. This capability
is central to the use of MOVES for PM hot-spot analyses because it allows for the
analysis of fine distinctions between vehicle behavior and emissions before and after
construction of the project. For example, the full emission benefits of a project designed
to smooth traffic flow can best be realized by taking into account the changes in
acceleration, deceleration, and idle activity that result from the project. There are several
methods that users may employ to calculate an Op-Mode distribution based on the project
design and available traffic information. MOVES currently offers three options that the
user can employ to add link activity data, depending on data availability. These are:
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1. Provide average speed and road type through the Links input:
Using this approach, MOVES will calculate emissions based on a default drive
cycle for a given speed, grade, and road type. Input of link drive schedules or
operating mode distributions is not needed. For users modeling a free-flow link
with only basic information on average speed and volume on a link, this option
may be appropriate. This approach accounts for some differences in emissions
due to changes in operating modes associated with different average speeds on a
specific road type. However, this approach provides the least resolution when
analyzing the emission impact of a project because the default drive cycles used
by the model may not accurately reflect the specific project. For instance, due to
the range of operating modes associated with intersection projects, a single
average speed would not spatially capture localized idling and acceleration
emissions.
2. Provide a link drive schedule using the Link Drive Schedule Importer:
The Link Drive Schedule Importer allows the user to define the precise speed and
grade as a function of time (seconds) on a particular roadway link. The time
domain is entered in units of seconds, the speed variable is miles-per-hour and the
grade variable in percent grade (vertical distance/lateral distance, 100% grade
equals a 45-degree slope). MOVES builds an Operating Mode Distribution from
the Link Drive Schedule and uses it to calculate link running emissions.
Individual Link Drive Schedules cannot be entered for separate source types. The
Link Drive Schedule therefore represents the "tracer" path of an average vehicle
on each link. Link drive schedules could be based on observations using methods
such as chase (floating) cars on similar types of links, or on expected vehicle
activity based on an analysis of link geometry. Link drive schedules will only
represent average vehicle activity, not the full range of activity that will occur on
the link. As described in Section 4.2 and Appendix D, users can overcome this
limitation by defining multiple links for the same portion of the project (links that
"overlap") with separate source distributions and drive schedules to model
individual vehicle types.
3. Provide a detailed operating mode distribution for the link:
The Operating Mode Distribution Importer allows the user to directly import
operating mode fraction data for source types, hour/day combinations, roadway
links, and pollutant/process combinations that are included in the run
specification. Operating mode distributions may be obtained from:
• Op-Mode distribution data from other locations with similar geometric
and operational (traffic) characteristics;52 or
• Output from traffic microsimulation models.53
52 For example, chase (or floating) cars, traffic cameras, and radar guns have been used previously to
collect some traffic data for use in intelligent transportation systems and other applications. EPA
encourages the development of validated methods for collecting verifiable vehicle operating mode
distribution data at specific locations representative of different projects covered by this guidance.
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4.5.8 Deciding on an approach for activity
Users should consider the discussion in Section 4.2 when deciding on the appropriate
activity input. The MOVES model is capable of using complex activity datasets with
high levels of resolution to calculate link-level emissions. EPA encourages the
development of validated methods for collecting verifiable vehicle Op-Mode distribution
data at locations and in traffic conditions representative of different projects covered by
this guidance. However, the user should determine the most robust activity dataset that
can be reasonably collected while still achieving the goal of determining an accurate
assessment of the PM air quality impacts from a given project. The decision to populate
the Links table, Link Drive Schedule, or Op-Mode Distribution should be based on the
data available to the user and should reflect the vehicle activity and behavior on each
link.
Note: If either the average speed or link-drive schedule approach is used, it is not
necessary to input an Op-Mode distribution for on-road link activity.
4.5.9 Off-Network
(MOVES User Guide Section 2.3.3.4.16)
The Off-Network Importer is where the user can provide information about vehicles not
driving on the project links, but still contributing to the project's emissions. Currently,
only one off-network link may be described per run. If more than one off-network link is
associated with the project, another set of 16 MOVES runs would be needed to
characterize each additional off-network location for each build or no-build scenario.
The Off-Network Importer should be used if the project includes an area where highway
vehicles are parked, starting their engines, or in extended idling mode (such as at a truck
stop, parking lot, or passenger or freight intermodal terminal). All such areas within the
project area should be modeled, regardless of whether they are part of the project.
There are no default values available for any of the off-network inputs, so users will need
to populate the Off-Network table with information describing vehicle activity in the off-
network area being modeled. The necessary fields are vehicle population, start fraction,
and extended idle fraction:
• The vehicle population reflects the total number of vehicles parked, starting, or
idling on the off-network area over the course of the hour covered by the MOVES
run.
• The start fraction is the fraction of the total vehicle population that starts during
the hour.
A traffic microsimulation model can be used to construct link drive schedules or operating mode
distributions if prior validation of the model's predictions of speed and acceleration patterns for roadway
links similar to those in the project was conducted. If a user has a microsimulation model that has been
previously demonstrated to adequately predict speed/acceleration patterns for relevant vehicle classes (e.g.,
heavy-duty), and has a procedure for importing data into MOVES, it may be appropriate to use the
microsimulation model, subject to interagency consultation.
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The extended idle fraction specifies the fraction of time that the vehicle
population spends in extended idle operation in the hour.
54
Extended idle operation applies only to long-haul combination trucks and is defined as
the operation of the truck's propulsion engine when not engaged in gear for a period
greater than 15 consecutive minutes, except when associated with routine stoppages due
to traffic movement or congestion.55 As discussed in Section 4.2.2, shorter periods of
idling for long-haul combination trucks and all idling for other vehicles should be
modeled as a project link with an Op-Mode distribution that consists only of idle
operation (Op-Mode 1). This can be specified in the Links table by inputting the vehicle
population and specifying an average speed of "0" mph.
For vehicle population inputs, the user should be able to rely on existing project
documentation. The user will also need to estimate the number of starts and idle
operation of the facility for other inputs, which will depend on the project involved. For
example, in a bus terminal project, the user could estimate the number of starts and idling
based on expected passenger ridership and proposed operating schedules for the buses
using the terminal. Most buses would be expected to first start early in the morning, prior
to the morning peak period. The buses might operate all day, with little or no start
activity during the midday hours. Idle operation is likely a function of the volume of
buses accessing the terminal each hour and the duration that those buses idle prior to
leaving the terminal. Conversely, an employee parking lot would have little or no idle
activity and may have the opposite trend in start activity. Typically, employees arrive
during the morning peak period and leave during the evening peak period. In this case,
most starts would occur during the evening peak period.
Information on start and idle activity should be specific to the project being modeled.
However, data from similar projects could be adapted for use in a quantitative PM hot-
spot analysis, when appropriate. For instance, the ratio of starts to vehicles and the
distribution of starts throughout the day for a project being analyzed could be determined
by studying a similar parking lot.
If an off-network link is defined, users need to also define an Op-Mode distribution that
describes the soak-time distribution of vehicles on the link; this will affect the start
emissions. Additionally, any extended idle operation on an off-network link needs to be
described by the Op-Mode distribution with a fraction of 1.0 for Op-Mode 200 (Extended
Idle Mode). Since there is only one possible extended idle mode in MOVES, this
fraction should always be 1.0.
The soak time is the time a vehicle is stationary with the engine turned off, following the
last time it was operated. There are no default soak-time distributions available. Soak
times and soak-time distributions should be specific to the type of project being modeled.
54 Parked fraction is not required as an input and can be left blank.
See "Guidance for Quantifying and Using Long Duration Truck Idling Emission Reductions in State
Implementation Plans and Transportation Conformity"; available online at
www.epa.gov/smartwav/documents/420b04001 .pdf.
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This information could either be directly collected or obtained from information collected
for a similar project. For instance, a park-and-ride lot may have vehicles parked for eight
or nine hours prior to starting, while an intermodal freight terminal may have vehicles
parked for only one hour before starting. This information should be defined through the
appropriate distribution of soak-time Op-Modes (OpModes 101-108) in the Op-Mode
Distribution table.
The methods and assumptions used to derive off-network inputs (including starts, idle
activity, and soak-time distributions) should be documented as part of the analysis,
including any adjustments based on data from similar projects.
4.6 GENERATING EMISSION FACTORS FOR USE IN AIR QUALITY
MODELING
The MOVES model provides results as either an emission total (if "Inventory" output is
selected) or an emission factor (if "Emission Rates" output is selected). The emission
results are produced for each pollutant and process and are calculated in terms of grams
per link or grams/vehicle-mile per link. Using the equations in Section 4.4.7, the user
will need to sum the appropriate pollutants and processes to derive a link total
grams/vehicle-mile or grams/hour emission factor. These totals will be needed as inputs
into the appropriate air quality model. Instructions on running AERMOD and
CAL3QHCR for quantitative PM hot-spot analyses are in Section 7 and Appendix J.
Note: If MOVES is being run in batch-mode, or if multiple runs are being saved to the
same output database, the user should make sure to separate link emissions in the result
database by "MOVESRunID" or "monthID, daylD, hourlD. " Aggregating separate
runs will result in incorrect emission rates.
4.6.1 Highway and intersection links
For links characterized as "highway" or "running" segments of a project, a
grams/vehicle-mile emission rate is needed for CAL3QHCR; if AERMOD is being used,
a grams/hour emission factor for each roadway link is needed:
• CAL3QHCR uses grams/vehicle-mile emission factors and calculates air quality
estimates based on the volume of traffic and length of a given link. All of the
information necessary to generate the necessary inputs is available in the MOVES
MySQL output database. After running MOVES for a particular hour/day/month
scenario, emission results can be located in the user defined MOVES output
database in the table "rateperdistance." All links defined in the Project Level
Importer will have results in the column "rateperdistance." The units should have
been defined as grams and miles in the MOVES RunSpec (see Section 4.4.10).
As shown in the equations in Section 4.4.7, all relevant pollutants and processes
should be summed together to get a single "rateperdistance" value. This value
can then be paired with link volume and link length for use in CAL3QHCR for
each link.
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• AERMOD uses a grams/hour emission factor for each hour of the day (which
should be mapped based on the time periods analyzed with MOVES, as described
in Section 4.3). If "Inventory" is selected in the Scale panel, MOVES will
produce output in terms of grams/hour/link. The user should then calculate
aggregate PM grams/hour emission factors by summing the appropriate pollutants
and processes as described in Section 4.4.7. Since AERMOD processes emission
factors in terms of grams/hour (or second), no further calculation is necessary.
Section 7 and Appendix J discuss input formats for different AERMOD source
configurations.
4.6.2 Transit and other terminal links
For transit and other terminal projects, or a combination of highway and transit or other
terminal components, AERMOD is recommended (see Section 7). AERMOD uses a
grams/hour emission factor for each hour of the day (which should be mapped based on
the time periods analyzed with MOVES as described in Section 4.3). If "Inventory" is
selected in the Scale panel, MOVES will produce output in terms of grams/hour/link.
The user should then calculate aggregate PM grams/hour emission factors by summing
the appropriate pollutants and processes as described in Section 4.4.7. Since AERMOD
processes emission factors in terms of grams/hour (or second), no further calculation is
necessary. Section 7 and Appendix J discuss input formats for different AERMOD
source configurations.
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Section 5: Estimating Project-Level PM Emissions Using
EMFAC2011 (in California)
5.1 INTRODUCTION
This section of the guidance addresses the necessary steps to run EMFAC2011 to
estimate a project's exhaust, brake wear, and tire wear emissions for PM hot-spot
analyses in California. The California Air Resources Board (CARB) maintains the
EMission FACtors (EMFAC) model, which is approved by EPA for developing on-road
motor vehicle emission inventories and conformity analyses in California. EMFAC
models on-road mobile source emissions under multiple temporal and spatial scales; it
produces composite emission factors for an average day of a month (January to
December), a season (summer and winter), or an annual average, for specific California
geographic areas by air basin, district, and county as well as the statewide level. EMFAC
can produce PM2 5 and PMi0 emission rates for three exhaust emission processes
(running, starting, and idle), tire wear, and brake wear.
EMFAC2011 consists of three modules:
• EMFAC2011-LDV, which estimates passenger vehicle emissions;
• EMFAC2011-HD, which estimates emissions from diesel trucks and buses over
14,000 pounds; and
• EMFAC2011 -SG, which integrates the output of EMFAC2011 -LDV and
EMFAC2011-HD and provides users with the ability to conduct scenario
assessments for air quality and transportation planning.57
CARB has also made available, through its mobile emissions inventory web site,
EMFAC2011 databases which provide regional population, activity, emissions, and
emission rates at varying levels of detail. EPA approved EMFAC2011 for SIP and
transportation conformity purposes on March 6, 2013 (78 FR 14533). When the grace
period ends on September 6, 2013, EMFAC2011 will become the only approved motor
vehicle emissions model for all new regional emissions analyses and CO, PMio and PM2.5
hot-spot analyses for transportation conformity determinations across California.
EPA also approved use of the EMFAC2011-PL tool for hot-spot analyses that involve a
"simplified approach." EMFAC2011-PL extracts emissions factors for analyses of
projects that are consistent with the default assumptions in EMFAC2011. Section 5.5
describes how to use EMFAC2011-PL for projects covered by the simplified approach,
but some aspects of this guidance may be applicable when an alternate project-level tool
has been approved by EPA.58 Sections 5.6 through 5.9 describe how to apply
56 This guidance is applicable to EMFAC2011 and future versions of the EMFAC model, unless EPA notes
otherwise when approving the model for conformity purposes. This guidance updates the previous
EMFAC2007 guidance contained in the December 2010 version of this document (EPA-420-B-10-040).
57 The current version of EMFAC2011 model, database updates, and supporting documentation can be
downloaded from the CARB website at: www.arb.ca. gov/msei/modeling.htm
58 EPA noted in its March 2013 Federal Register notice that alternate project-level tools could be used if
EPA approves such tools as having similar performance (78 FR 14534).
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EMFAC2011 using the "detailed approach" for projects that have project-specific vehicle
age distributions and/or project-specific rest and soak time data (e.g., any project that
includes starts or idling). Sections 5.2 through 5.4 apply to all PM hot-spot analyses.
More details about applying the different approaches to PM hot-spot analyses are
included later in this section.
Many of the processes and procedures contained in this section are based on procedures
described in CAKB's project-level handbook for EMFAC201159 and follow the same
general organization, with additional detail and guidance for using EMFAC2011
specifically for quantitative PM hot-spot analyses, as appropriate. In addition, Appendix
G of this EPA guidance contains an example of using EMFAC2011 for a highway
project, and Appendix H contains an example of using EMFAC2011 for a transit project.
As discussed in Section 2.4, it is suggested that project sponsors conduct emissions and
air quality modeling for the project build scenario first. If the design values for the build
scenario are less than or equal to the relevant NAAQS, then the project meets the hot-spot
analysis requirements of project-level conformity and it is not necessary to model the no-
build scenario. Following this approach will allow users to avoid additional emissions
and air quality modeling. Please see Section 2.4 for additional information if the design
values for the build scenario are greater than the relevant NAAQS.
Finally, this section describes how to use EMFAC2011 to estimate emissions from a
highway and transit project that requires a PM hot-spot analysis ("the project"); this
section could also be used to estimate emissions for any other highway and transit
facilities in the project area, when necessary. The emission factors obtained from the
EMFAC2011 modules and databases can then be used in air quality modeling as
discussed in Section 7 of the guidance.
The general steps to using EMFAC2011 are illustrated in Exhibit 5-1. This section
presumes users already have a basic understanding of how to run EMFAC2011. Note
that there are some aspects of Section 5 that differ from the MOVES guidance discussed
in Section 4, due to the inherent differences between MOVES and EMFAC2011. For
example, using EMFAC2011 may require the use of multiple modules to obtain all the
emission factors for a project, whereas MOVES uses a single GUI. In addition,
EMFAC2011 produces emission rates for a range of average speeds only. In contrast,
MOVES calculates emission rates based on a distribution of operating modes, which
allows the option of more advanced methods of defining link-level activity.
As described in Section 2.3, decisions on how to use EMFAC2011 for a quantitative PM
hot-spot analysis should be considered through the process established by each area's
interagency consultation procedures (40 CFR 93.105(c)(l)(i)). Any technical questions
about EMFAC2011 should be directed to CARB.
59 EMFAC2011 "Handbook for Project-level Analyses" (CARB, January 2013), available online at:
www.arb.ca.gov/msei/emfac2011 -pl-handbook-for-proiect-level-analyses-final-020713 -2.pdf
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Exhibit 5-1. Steps for Using EMFAC2011 in a Quantitative PM Hot-spot Analysis
. 60
Divide the project into
links
(Section 5.2)
Determine the number of
EMFAC20 limns
(Section 5.3)
Determining the
Modeling Approach
(Section 5.4)
Use Simplified
Approach
(Section 5.5)
Does the project vehicle
age distribution differ
fromtheEMFAC2011
defaults for the region?
Yes
No
No
Does the project include
vehicle start and or idling
emissions?
Yes
Use Detailed
Approach
(Sections 5.6-5.8)
60 The process shown in this exhibit differs in several ways from the decision matrix in CARS's
EMFAC2011 "Handbook for Project-level Analyses" in several respects due to the application here to PM
hot-spot analyses. See Section 5.4 for more information.
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5.2 CHARACTERIZING A PROJECT IN TERMS OF LINKS
Prior to using EMFAC2011, users first need to identify the project type and the
associated emission processes (running, start, brake wear, tire wear, and idle exhaust) to
be modeled. This guidance distinguishes between two types of transportation projects:
(1) highway and intersection projects, and (2) transit or other terminal projects:
• For highway and intersection projects, running exhaust, brake wear, and tire wear
emissions are the main focus.
• For transit and other terminal projects, start and idle emissions are typically
needed, and in some cases these projects will also need to address cruise,
approach and departure running exhaust emissions on affected links.
The goal of defining a project's links is to accurately capture emissions where they occur.
A link represents a segment of a highway or transit project characterized by a certain type
of vehicle activity. Generally, the links specified for a highway project should include
road segments with similar traffic conditions and characteristics. Links representing
transit or other terminal projects should similarly reflect variation in idle and start
activity, as well as other relevant cruise, approach and departure running exhaust
emissions.
5.2.1 Highway and intersection projects
A PM hot-spot analysis fundamentally depends on the availability of accurate data on
roadway link speed and traffic volumes for build and no-build scenarios.61 Thus, local
traffic data should be used to characterize each link sufficiently. It is recommended that
the user divide a project into separate links to allow sufficient resolution at different
vehicle traffic and activity patterns; characterizing this variability in emissions within the
project area will assist in air quality modeling (see Section 7).
For analyses with EMFAC2011, an average speed and traffic volume is needed for each
link.62 A simple example would be a single, one directional, four-lane highway that
could be characterized as one link with one average speed. If the project analysis
involves intersections, the intersections need to be treated separately from the free-flow
links that connect to those intersections. Although road segments between intersections
may experience free-flow traffic operations, the approaches and departures from the
intersections will involve acceleration, deceleration, and idling activity not present on the
free-flow link. For intersection modeling, the definition of link length will depend on the
61 Project sponsors should document available traffic data sets, their sources, key assumptions, and the
methods used to develop build and no-build scenario inputs for EMFAC. Documentation should include
differences between how build and no-build traffic projections are obtained. For projects of local air
quality concern, differences in traffic volumes and other activity changes between the build and no-build
scenarios must be accounted for in the data that is used in the PM hot-spot analysis.
62 Unlike MOVES, EMFAC2011 does not allow a user to account for more detailed data to describe the
pattern of changes in vehicle activity (proportion of time in acceleration, deceleration, cruise, and idle
activity) over the length of a road.
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geometry of the intersection, how that geometry affects vehicle activity, and the level of
detail of available activity information.
When using EMFAC2011, project sponsors can use average speeds for highway and
intersection links based on travel time and distance. Travel time should account for the
total delay attributable to traffic signal operation, including the portion of travel when the
light is green and the portion of travel when the light is red. The effect of a red signal
cycle on travel time includes deceleration delay, move-up time in a queue, stopped delay,
and acceleration delay. Each approach link would be modeled as one link to reflect the
higher emissions associated with vehicle idling through lower speeds affected by stopped
delay; each departure link would be modeled as another link to reflect the higher
emissions associated with vehicle acceleration through lower speeds affected by
acceleration delay.
Project sponsors should determine average congested speeds by using appropriate
methods based on best practices used for highway analysis.63 Some resources are
available through FHWA's Travel Model Improvement Program (TMIP).64
Methodologies for computing intersection control delay are provided in the Highway
Capacity Manual.65
5.2.2 Transit and other terminal projects
For transit and other terminal projects such as a bus terminal or intermodal freight
terminal, the user should have information on starts per hour and number of vehicles
idling during each hour. This activity will likely vary from hour to hour. It is
recommended that the user divide such a project into separate links to characterize
variability in emission density within the project area appropriately (as discussed in
Section 7). In this case, each "link" describes an area with a certain number of vehicle
starts per hour, or a certain number of vehicles idling during each hour.
Generally, users need to account for the number of vehicle starts and the amount of idle
activity (in hours). Grams/trip rates can be calculated for start exhaust emissions.
Additionally, grams/idle-hour (grams/hour) emission rates can be calculated for both
regular idle and extended idle exhaust emissions. Users need to have data on the number
of vehicle starts per hour and number of vehicles idling during each hour to get the total
project or project area emission factor.
In addition, some transit and other terminal projects may have significant running
emissions similar to free-flow highway projects (such as buses and trucks traveling to and
from an intermodal terminal). These emissions can be calculated by defining one or
63 As discussed in Section 7, the use of the CAL3QHCR queuing algorithm for intersection idle queues is
not recommended. Rather, idling vehicles should be represented in combination with decelerating,
accelerating, and free-flow traffic on an approach segment of an intersection.
64 See FHWA's TMIP website: http://tmip.fhwa.dot.gov/.
65 Users should consult the most recent version of the Highway Capacity Manual. As of the release of this
guidance, the latest version is the Highway Capacity Manual 2010, which can be obtained from the
Transportation Research Board (see www.trb.org/main/blurbs/164718.aspx for details).
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more unique running links as described in Section 5.2.1 and Appendix G (that is, in
addition to any other roadway links associated with the project). These running link
emissions can then be aggregated with emissions from starts and idling from non-running
activity on the transit or other terminal link outside of the EMFAC2011 model to
generate the necessary air quality model inputs.
Note: The user may choose to exclude sources such as a separate service drive, separate
small employee parking lot, or other minor sources that are determined to be
insignificant to project emissions.
5.3 DETERMINING THE NUMBER OF EMFACIOIi RUNS
5.3.7 General
Before using EMFAC2011 to calculate emission factors, users should first determine the
number of unique scenarios that can sufficiently describe activity variation in a project.
In most projects, traffic volume, average speed, idling, fleet mix, and the corresponding
emission factors will likely vary from hour to hour, day to day, and month to month.
However, it is unlikely that data are readily available to capture such finite changes.
Project sponsors may have activity data collected at a range of possible temporal
resolutions. The conformity rule requires the use of latest planning assumptions or data
available at the time the conformity analysis begins (40 CFR 93.110).66 Depending on
the sophistication of the activity data analysis for a given project, these data may range
from a daily average-hour and peak-hour value to hourly estimates for all days of the
year. EPA encourages the development of sufficient travel activity data to capture the
expected ranges of traffic conditions for the build and no-build scenarios.
5.3.2 Projects with typical travel activity data
Traffic forecasts for highway and intersection projects are often completed for annual
average daily traffic volumes, with an allocation factor for a daily peak-hour volume.
This data can be used to conduct an analysis with EMFAC2011 that is representative for
all hours of the year. The most reasonable methods in accordance with good practice
should be used to obtain the peak-hour allocation factors and diurnal distribution of
traffic and the methods must be determined in accordance with interagency consultation
procedures (40 CFR 93.105(c)(l)(i)).
One option is to represent traffic over four time periods: morning peak (AM), midday
(MD), evening peak (PM), and overnight (ON). For example, the peak-hour volume can
be used to represent activity conditions over a three-hour morning (AM) and three-hour
evening period (PM). The remaining 18 hours of the day can be represented by the
average off-peak hourly volume (AADT minus the total volume assigned to the peak
66 See "EPA and DOT Joint Guidance for the Use of Latest Planning Assumptions in Transportation
Conformity Determinations," EPA-420-B-08-901 (December 2008); available online at:
www.epa.gov/otaq/stateresources/transconf/policy/420b08901.pdf.
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period, divided by the number of off-peak hours). These 18 hours would be divided into
a midday (MD) and overnight (ON) scenario.
The following is one suggested approach for an analysis employing the average-
hour/peak-hour traffic scenario:
• Morning peak (AM) emissions based on peak hour traffic data, applied to hours
between 6 a.m. and 9 a.m.;
• Midday (MD) emissions based on average off-peak hourly traffic data, applied to
hours from 9 a.m. to 4 p.m.;
• Evening peak (PM) emissions based on peak hour traffic data, applied to hours
from 4 p.m. to 7 p.m.; and
• Overnight (ON) emissions based on average off-peak hourly traffic data, applied
to hours from 7 p.m. to 6 a.m.
If there are local or project-specific data to suggest that the AM or PM peak traffic
periods will occur in different hours than the default values suggested here, or over a
longer or shorter period of time, that information should be documented and the hours
representing each time period adjusted accordingly. Additionally, users should determine
peak periods for the build and no-build scenarios independently and not assume that each
scenario is identical.
The number of EMFAC2011 "runs" needed to represent changes in fleet mix depends on
what modeling approach is required to complete the analysis (see Section 5.4). In some
cases, only one run will be necessary, with the resulting emissions rates being weighted
and aggregated through post-processing to reflect a particular fleet mix. In other cases,
multiple model runs will be required. This will be described in more detail in Sections
5.5 through 5.9.
Since PM emission rates do not vary with temperature and humidity in EMFAC2011, it is
not necessary to run multiple EMFAC2011 scenarios to capture seasonal variation in
emission rates. An exception to this concerns medium-heavy and heavy-heavy diesel
truck idling rates, which do vary by season to account for load factor changes due to
heating, air conditioning, and accessory use. See Section 5.8.3 for more information
about these idling rates and options for accounting for this variation in a particular
analysis.
5.3.3 Projects with additional travel activity data
Some project sponsors may have developed traffic or other activity data to show
variations in volume and speed across hours, days, or months. Additionally, if users are
modeling a transit or other terminal project, traffic volumes, starts, and idling estimates
are likely to be readily available for each hour of the day. Under either of these
circumstances, users have the option of applying the methodology described above (using
average-hour and peak-hour as representative for all hours of the year) if it is determined
through the interagency consultation process that using the additional data would not
significantly impact the emissions modeling results. Alternatively, additional
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EMFAC2011 scenarios could be generated to produce a unique emission factor for each
activity scenario (i.e., each period of time for which specific activity data are available).
5.4 DETERMINING THE MODELING APPROACH
EMFAC2011 uses a modular emissions modeling approach that departs from the single
model approach used by EMFAC2007. Because of this, it may now be necessary to use
more than one method - or go to more than one source - to obtain all the emission rates
needed to complete a particular quantitative PM hot-spot analysis. The following
sections describe where the emission rates can be found for different vehicle types, the
tools available to obtain them, and approaches that can be used to determine which tools
are applicable to a specific analysis.
This guidance describes two general approaches to using EMFAC2011 for quantitative
PM hot-spot analyses: simplified and detailed. Users should follow the general decision
matrix shown in Exhibit 5-2 to determine which approach is appropriate for their
particular analysis. EPA anticipates that the majority of projects that require PM hot-
spot analyses should be covered by the simplified approach, where emissions factors for
projects are consistent with the default assumptions in EMFAC2011. In contrast, the
detailed approach is appropriate when projects:
• Have a vehicle age distribution that differs from EMFAC2011 default parameters
for the county in which the project is located; and/or
• Have project-specific rest and soak time data (e.g., any project that includes
vehicle start or idling emissions).67
In the context of the general decision matrix, "idling emissions" are those project
emissions resulting from dedicated idling activity (e.g., idling at a truck stop or bus or
intermodal terminal); in these cases, the detailed approach is to be used. Any idling that
occurs as part of a regular vehicle drive cycle (e.g., idling while paused at a signal light)
would be captured as part of a project's running emissions and should considered when
calculating link average speed as described in Section 5.2; if this is the only idling
occurring as part of a project, use of the simplified approach would be appropriate.
67 The general decision factors described here (and shown in Exhibits 5-land 5-2) differ from those
included in CARB's EMFAC2011 "Handbook for Project-level Analyses" in two respects. First, CARB's
handbook includes a third factor that has to be met to use the simplified approach ("Are project-specific
ambient temperature and relative humidity profiles available profiles available and different from EMFAC
defaults?") However, since PM emission rates do not vary based on temperature and relative humidity in
EMFAC2011, this factor is irrelevant for PM hot-spot analyses. Second, CARB's handbook does not
indicate whether the project includes vehicle start and idling emissions as a factor in deciding to use the
detailed approach. While there is some default information on rest and soak times included in
EMFAC2011, for a PM hot-spot conformity analysis the project sponsor is expected to have and use
project-specific soak/idle and start times; therefore any PM hot-spot analysis which includes starts or idle
emissions should use the detailed approach.
58
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While the general decision matrix should be used as a guide, the final decision on which
approach is used for a particular project should be determined consistent with the
interagency consultation procedures.
The remainder of this section contains additional guidance for selecting an approach
based on the type of project being analyzed in the PM hot-spot analysis. The two
approaches themselves are explained in further detail in Section 5.5 (simplified approach)
and Sections 5.6 through 5.9 (detailed approach).
Exhibit 5-2. General Decision Matrix for Using EMFAC2011 for PM Hot-spot
Analyses68
Docs the project vehicle
age distribution differ
from the EMFAC2011
defaults for the region?
Yes
No
Use Simplified
Approach
(Section 5,5)
Does: the project include
vehicle start and or iilhiiL;
emissions r
/
Use Detailed
Approach
(Sections 5,6-5,8)
5.4.1 Highway and intersection projects
The simplified approach can be used for highway and intersection projects for PM hot-
spot analyses if the project-specific vehicle age distributions do not differ from the
EMFAC2011 defaults for the county in which the project is located. The simplified
approach is described further in Section 5.5.
For PM hot-spot analyses, project sponsors should use the latest state or local age
distribution assumptions from their SIP or transportation conformity regional emissions
analysis, or other project-specific age distribution data, if available. If the age
distribution to be used in the PM hot-spot analysis differs from the EMFAC2011 defaults
for the county in which the project is located, this would necessitate use of the detailed
approach, described further in Sections 5.6 through 5.9.
68 As previously noted in this section, this matrix differs in several ways from the general decision matrix in
CARB's EMFAC2011 "Handbook for Project-level Analyses" due to the application here to PM hot-spot
analyses.
59
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Start and idle emissions would not normally be part of a highway or intersection project
analysis; however, if they are, the detailed approach should be used.
5.4.2 Transit and other terminal projects
Transit and other terminal projects will be expected to have project-specific rest/soak
times to generate start and idle emissions; for these projects, the detailed approach
described in Sections 5.6 through 5.9 should be used. If the terminal project is designed
to serve a fleet that operates only locally, such as a drayage yard or bus terminal, the
sponsor should provide project-specific fleet age distribution data, which would also
necessitate use of the detailed approach.
There may be limited cases where the simplified approach described in Section 5.5 could
be appropriate when modeling certain vehicle activity associated with a transit or other
terminal project (such as modeling the running emissions associated with a terminal); this
should be decided on a case-by-case basis using the interagency consultation process.
When modeling transit or terminal projects involving bus fleets, care should be taken to
obtain emission rates for the appropriate EMFAC2011 bus type; see Section 5.6.2 for
details.
5.5 APPLYING THE SIMPLIFIED APPROACH: USING EMFACIOH-PL
As noted in Section 5.4, the simplified approach described here may be appropriate for
highway and intersection projects meeting certain criteria. Most transit and terminal
projects would not qualify to use this approach since they will involve project-specific
rest/soak times (except to obtain any running emissions associated with the terminal);
these projects would instead use the detailed approach.
The simplified approach uses EMFAC2011-PL, a project-level assessment tool CARB
has developed to assist in the generation of emission rates for certain project-level
analyses.69 EMFAC2011-PL uses emissions and activity data from EMFAC2011-SG
module inventory files (default inventories of EMFAC2011-LDV and EMFAC2011-HD
modules) and calculates emission factors consistent with the default fleet distributions in
the region in which the project is located. The tool is available for download from
CARB's Mobile Source Emission Inventory website
(www.arb.ca.gov/msei/modeling.htm). The EMFAC2011-PL tool is used only with the
simplified approach as described in this section. The steps for using EMFAC2011-PL for
the simplified approach for a PM hot-spot analysis are shown in Exhibit 5-3.
69 As previously noted, EPA noted in its March 2013 Federal Register notice that alternative project-level
tools could be used if EPA approves such tools as having similar performance (78 FR 14534). This
guidance will cover only the use of EMFAC2011-PL for the simplified approach.
60
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The EMFAC2011-PL tool will generate the following emission rates for the vehicle
category type, geographic area, fuels, and timeframe selected, relevant for PM hot-spot
analyses:
• Running Exhaust Emissions Rates [RUNEX] in g/mile/vehicle
• Idling Exhaust Emissions Rates [IDLEX] in g/hr/vehicle
• Starting Exhaust Emissions Rates [STREX] in g/trip/vehicle
• PM Brake Wear [PMBW] and PM Tire Wear [PMTW] in g/mile/vehicle
Note that EMFAC2011-PL does not allow one to enter any project-level activity data
with which to associate these emission rates and also does not generate composite rate
that includes brake wear and tire wear. Therefore, in most situations the rates obtained
from EMFAC2011-PL will have to be post-processed in order to calculate the emissions
from the project; see Section 5.5.9 for more details.
EMFAC2011-PL contains a graphical user interface (GUI) to enable the selection of
emission rates relevant for a particular project (see Exhibit 5-4). The following sections
describe the selections available in the GUI and how to use EMFAC2011-PL to obtain
project emission rates.
5.5.1 Vehicle Category Scheme
This selection allows one to select the vehicles categories for which emission rates will
be obtained. Users must select one of the following options:70
• EMFAC2011 Vehicle Categories
• EMFAC2007 Vehicle Categories
• Trucks/Non-Trucks Categories
• Trucks 1/Trucks 2/Non-Trucks Categories
• Total (Fleet Average)
In many cases, project travel activity data is likely to be in truck/non-truck categories, in
which case selection of the "Trucks/Non-Trucks" option would be appropriate. If project
data is not available at the vehicle category level, the "Total" option should be selected.
Users modeling one or more specific vehicle types would choose the appropriate EMFAC
vehicle category options as a later selection (see Section 5.5.6).
5.5.2 Region Type
EMFAC2011-PL offers six geographic scales (State, Air Basin, Air District, MPO,
County, and GAI)71; each corresponds to specific defaults for fleet characteristics. For
PM hot-spot analyses, users will typically select the County region type.
70 More information on the various EMFAC model vehicle categories is available online at:
www.arb.ca.gov/msei/vehicle-categories.xlsx
71 The GAI sub-area option is used in EMFAC2011 to distinguish certain heavy-duty idling rates in specific
parts of the state and is not an appropriate selection here.
61
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Exhibit 5-3. Using the Simplified Approach (EMFAC2011-PL tool) for a PM Hot-
spot Analysis
OpcuEMFAC2011-PL
tool
1
+
Select Vehicle Category r, , n ,
,. . , Select Region tvpe i
Scheme — > .... — >
„- i- ,-~ . (Section 5.3.2)
Select Region _ ^
(Section 5.5.3)
1
L'ncheck the "Vehicle / Does the project ^\
Category" checkbox Yes / contain multiple \ ' "
(defaults to "_\LL" N. vehicle categories'" J
option) \. (Section 5.5.6) /
1 ^
Uncheck the "Fuel / Do
Tvpe" checkbox \e*/ acti\i
(defaults to "ALL" \
option) \^ ( S
1 ^
4-
36 the project \x
.y data vary by \
hiel type? /
;ction 5.5.7) /
1
Uneheek the "Speed" / .\iv the activity data X.
L-heckhox Ye< / distributed Liver \ No
(defaults to "ALL" ™ \ multiple speed bins? /
option) \ (Section 5.5.S) /
1 ^
Select Calendar Year .
(Section 5.5.4)
Select Season
(Section 5.5.5j
i
Check the "Vehicle
i\ Categon-" Checkbox
and SL'loot Josired
vehicle
1
1 Check the "Fuel Type"
^ checkbox and select
"1 desired fuel ["TOT"
for GAS 1 DSL]
1
Check the "Speed"
-> checkbox and select
desired speed bin
1
Output emission
factor lookup
table
5.5.3 Region
After "County" has been selected for Region Type as recommended in Section 5.5.2, the
county in which the project is located should be selected here (e.g., "Sacramento"). For
projects which may be located in more than one county, options include selecting the
county in which the majority of the project is located, or running EMFAC2011-PL
multiple times to obtain rates for the parts of the project located in each county. For these
situations, the interagency consultation process should be used to determine what
approach may be most appropriate.
62
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Exhibit 5-4. EMFAC2011-PL Graphical User Interface (GUI)
EMFAC2011-PL{Verl.l)
Project-level Emission Rates Database
r
Vehicle Category
Scheme:
Region type: &
EMFAC2011 Vehicle Categories ^ EMFAC30Q7 Vehicle Categories
Trucks / Non-Trucks Categories O Trucks I/ Trucks 2 /Non-Trucks Categories
©[Total (Fteet average)!
State <~
Air Basin f AltOM r MPO <~ County ** GAI
Region Q
CalYr [7]
Season | » |
•net
D
Vehicle Category AitVehicles Combined JT]
D
n
Fuel Type ALL
Speed ALL
Download txit
5.5.4 Calendar Year
EMFAC2011-PL is able to analyze calendar years from 1990 to 2035 but is limited to
one year per run. The calendar year (CalYr) selected here should be that of the project
analysis year. If an analysis year beyond 2035 is needed, select 2035 to represent that
year.
5.5.5 Season
EMFAC2011-PL can estimate emission factors for two seasons (winter and summer) or
an annual average. In general, since there is no seasonal variation in the PM emission
rates generated by EMFAC2011-PL, it will be appropriate to use the annual average.
72
72 The only seasonal variation in PM emission rates in EMFAC2011 is in the medium-heavy and heavy-
heavy duty diesel truck idling rates (see Section 5.8.3). Since this guidance recommends obtaining all
63
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As previously noted, any variations in project fleet mix will be handled through post-
processing and will not require additional EMFAC2011-PL runs (see Section 5.5.9); a
single EMFAC2011-PL will therefore be able to generate all the emission rates for a
project eligible to use the simplified approach.
5.5.6 Vehicle Category
The options available in this category depend on the selection previously made for
Vehicle Category Scheme (see Section 5.5.1):
• If either the EMFAC2011 vehicle category scheme were selected, the option for
vehicle category will include all the vehicle categories for each model. Output for
all categories can be selected, or only one category if that is the only rate desired.
• If the Trucks/Non-Trucks scheme was selected, then the options are to obtain
rates for either both categories or just one.
• If the Total (Fleet Average) scheme was selected, the only option is to obtain rates
for All Vehicles Combined.
In most cases, "ALL" should be selected to ensure all vehicle classes are included in the
output.
5.5.7 Fuel Type
This selection offers the option of selecting emission rates by fuel type (GAS, DSL, TOT,
or ALL). In most cases "TOT" should be selected, which will ensure all fuel types are
included in resulting composite rate. However, when using EMFAC2011-PL to obtain
emissions for a vehicle category using a single fuel, selecting only the desired fuel type is
recommended. Selecting "ALL" will give separate output for gas and diesel fuel types,
which would be useful in the event project VMT was available by fuel type.
5.5.5 Speed
EMFAC2011-PL can give emission rates in 14 speed bins (5-70 MPH in 5 MPH
increments). The speed bin selected should be the speed that most closely matches the
average speed for the link for which the EMFAC scenario applies. If the project contains
links with a large range of average speeds, it may be useful to select all speed bins
("ALL") for efficiency.
5.5.9 Generating and post-processing EMFAC 2011-PL emission factors
Once all the selections have been made on the EMFAC2011-PL GUI, the user should
select "Download" to obtain the desired rates. Once the download process is completed,
an Excel file containing the results will appear in the drive where the EMFAC program is
located. Rates for different processes will be on separate tabs within the spreadsheet.
vehicle idling rates using the detailed process (see Section 5.6), annual average is the recommended
selection here when using EMFAC2011-PL.
64
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Because the rates for different processes are output into different spreadsheet tabs in this
way, for running emission links, the EFMAC2011-PL results will then have to be post-
processed to add brake wear and tire wear emission rates to the associated running
emission rates to obtain a composite rate suitable for use in air quality modeling. This
post-processing will have to occur outside of EMFAC2011-PL and can be accomplished
using a spreadsheet or similar tool.
As previously mentioned, only one EMFAC2011-PL "run" is necessary to obtain
emissions rates for a project using the simplified approach. However, if the project fleet
mix differs from the EMFAC2011 default county vehicle mix, those rates will then have
to be weighted and aggregated to reflect the project-specific fleet mix before being used
in air quality modeling. Typically, this would mean weighting the emission rates to
reflect the appropriate truck/non-truck vehicle mix of a project. See Appendix G for an
example of this post-processing for a simplified highway project. An additional example
can be found in Scenario #4 in the Appendices to CARB's EMFAC2011 "Handbook for
Project-level Analyses." There may be limited cases in which no post-processing of
EMFAC2011-PL results are needed.
5.6 OVERVIEW OF THE DETAILED APPROACH
5.6.1 General
The detailed approach is to be followed when completing a quantitative PM hot-spot
analysis when (a) the vehicle age distributions for the project differ from EMFAC2011
defaults, and/or (b) the project includes vehicle idling and/or start emissions. As noted in
Section 5.4, most transit and other terminal projects are likely to use the detailed
approach. In addition, any highway or intersection project that has a vehicle age
distribution which differs from the EMFAC2011 default values would also have to use
the detailed approach.
The detailed approach consists of two parts:
• The EMFAC2011 -LDV procedure, which gives emission rates for light duty
vehicles and some bus types (see Section 5.7); and
• The EMFAC2011-HD procedure, which gives emission rates for heavy duty
vehicles and the remaining bus types (see Section 5.8)
Depending on the fleet mix for the project, users may need to use either the
EMFAC2011-LDV procedure, the EMFAC2011-HD procedure, or both procedures in
order to obtain all the emission rates needed for a particular project. Exhibit 5-5 shows
an overview of using the detailed approach for a quantitative PM hot-spot analysis. In
addition, Section 5.9 describes the process for combining emission rates from
EMFAC2011-LDV and EMFAC2011-HD into a link aggregate emission rate suitable for
use in dispersion modeling.
65
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Because project analyses necessitating use of the detailed approach cannot use the
EMFAC2011-PL tool (or similar interface) to obtain EMFAC2011 emission rates, this
section of the guidance contains detailed instructions on how obtain data directly from
the various EMFAC2011 modules. In addition, this guidance is geared towards
addressing the most likely situations likely to be part of a PM hot-spot analysis. CARB is
available to help answer questions on how to obtain emission rates for project situations
not covered by this guidance.
The general steps to the EMFAC2011-LDV procedure can be summarized as:
• Open EMFAC2011-LDV and determine appropriate inputs to describe the
geographic area, time period, and vehicles for which you need emission rates;
• Select "Emfac" mode to generate area-specific fleet average emission factors;
• Change settings for temperature and humidity, to input one appropriate value for
each that represents the project area;
• Edit program constants to change distribution of VMT, trips, and vehicle
population (as needed) to reflect the project's fleet mix;
• Run EMFAC2011-LDV and obtain the relevant project emissions factors for
running exhaust, tire wear, brake wear, MDT and HOT idling, and gasoline
vehicle start emissions;
• If needed, estimate idling emissions for all other vehicle types, based on the
EMFAC emission factor for 5 mph;
• If needed, estimate diesel start emissions by multiplying the time between ignition
and driving by the appropriate idle rate;
• For a link total emissions factor, add running, tire wear, and brake wear emission
factors together;
• Process idling and start emissions to reflect the activity anticipated at the project
when transit and other terminal links are modeled.
Section 5.7 will cover these steps in detail.
The general steps to using the EMFAC2011-HD procedure can be summarized as:
• Obtain running exhaust, brake wear, and tire wear emission rates from CARB's
EMFAC website, selecting the relevant geographic area, time period, and vehicle
types;
• If needed, obtain idling emission rates from CARB's website, selecting the
relevant geographic area and filtering the spreadsheet for the appropriate calendar
year and vehicle type;
• If needed, weight the rates from the individual EMFAC2011-F£D vehicle classes
into an aggregate heavy-duty emission rate based on the default VMT mix and the
project-specific age distribution;
• If needed, estimate diesel start emissions by multiplying the time between ignition
and driving by the appropriate idle rate;
• To calculate the total emissions factors for each link, add running, tire wear, and
brake wear emission factors together;
• Process idling and start emissions to reflect the activity anticipated at the project
when transit and other terminal links are modeled.
-------
Section 5.8 will cover these steps in detail.
The remainder of this section discusses two situations which may cause confusion when
applying the detailed approach for a transit or other terminal project: (1) where to obtain
emission rates for the bus types included in EMFAC2011, and (2) how to address idling
and start emissions.
Exhibit 5-5. Using the Detailed Approach for a PM Hot-spot Analysis
EMFAC2011-LDV
Categories
EMFAC2011-HD
Categories
Divide
project data
b vehicle
Follow EMFAC2011-LDV
procedure
(Section 5.7)
Follow EMFAC2011-HD
procedure
(Section 5.8)
5.6.2 Introduction to EMFAC2011 bus types
EMFAC2011 contains emission rates for seven different bus types. When using the
detailed approach to model a bus fleet (for a transit or terminal project, for example),
users need to determine the appropriate EMFAC2011 vehicle bus type and make
selections accordingly. Exhibit 5-6 contains a list of the bus types, a brief description of
each, and the associated EMFAC2011 vehicle category and module (EMFAC2011 -LDV
or EMFAC2011-HD) which should be used to obtain the desired rate.
5.6.3 Obtaining idling emissions using the detailed approach
Idling emissions in EMFAC2011 are handled differently depending on the vehicle type
involved. In general:
• For EMFAC2011-LDV vehicle types, in most (but not all) cases, it will be
necessary to use the appropriate 5 mph running emission rate to obtain an idling
rate - see Section 5.7.4 for details.
• For EMFAC2011-F£D vehicle types, idling rates have been explicitly included in
the model. In this case, the appropriate idle rate should be identified and used in
the analysis - see Section 5.8.3 for details.
67
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Therefore, if idling emissions for a project are required for vehicle types found in both
the EMFAC2011-LDV and EMFAC2011-HD modules, then both methods will need to
be used to extract all the required idling emission rates for that project.
Exhibit 5-6. Bus Types in EMFAC2011
Bus type
Urban transit buses
Intercity buses
(motor coach)
Other diesel buses
Small transit/
paratransit buses
Other gas buses
School buses (diesel)
School buses (gas)
Description
Publicly-owned urban transit buses. Either
diesel buses or (more commonly) natural gas
buses certified to diesel standards.
Heavy buses with a specific body type used
for inter-regional transit. Regulated by the
Truck and Bus rule.
Catch-all diesel bus category. Includes rental
car shuttles, school buses sold to a private
entity like a church, etc. Regulated by the
Truck and Bus rule.
Lighter, smaller buses used by transit or
paratransit fleet, etc.
Catch-all category for gas buses or shuttles
not owned by a transit fleet or school district.
Self-explanatory. Regulated by the Truck
and Bus rule.
Self-explanatory; few in number.
EMFAC2011 vehicle category
[Module in which found]
UBUS-DSL
[EMFAC201 1-LDV]
Motor Coach-DSL
[EMFAC2011-HD]
OBUS-DSL
[EMFAC2011-HD]
UBUS-GAS
[EMFAC201 1-LDV]
OBUS-GAS
[EMFAC201 1-LDV]
SBUS-DSL
[EMFAC2011-HD]
SBUS-GAS
[EMFAC201 1-LDV]
5.6.4 Obtaining start emissions using the detailed approach
General
Obtaining start emissions using the detailed approach also depends on the vehicle type
involved. EMFAC2011 does not include explicit start emission rates for any diesel
vehicle types in either the EMFAC2011-LDV or EMFAC2011 -HD modules. However,
EMFAC2011 does include start emission rates for gasoline vehicles.
In general, then, when needing to estimate project start emissions:
• For gasoline vehicles, obtain the appropriate start emission rate from the
EMFAC2011-LDV module;
• For diesel vehicles, estimate the start emissions rate based on the vehicle's idling
rate, as described below.
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Obtaining start emission rates for EMFAC2011 diesel vehicle types
A diesel start can be defined as the period following "key-on" ignition, an initial warm-
up period before the vehicle begins driving. The duration of this process will be specific
to the project, but can be simply modeled as a period of idle activity.
To estimate start emissions, users should multiply the length of this period in terms of
hours (e.g., 3 minutes = 0.05 hour) by the appropriate idle rate in grams/hour extracted
from EMFAC2011, to determine a gram/start emission rate for use in air quality
modeling. For instance, to account for a 30 second start-up period, the EMFAC2011 idle
rate (in grams/hour) should be multiplied by .0083 hours to obtain the total grams of
emissions per start. This grams/start rate can then be multiplied by the number of vehicle
starts present in the project in that hour to obtain total start emissions.
More Section 5.6.3 for more information about obtaining idling rates using the detailed
approach.
69
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5.7 APPLYING THE DETAILED APPROACH: USING EMFACIOH-LDV
The procedure described here should be used to generate emission rates for any of the
EMFAC2011-LDV vehicle categories listed in Exhibit 5-7 when using the detailed
approach for a PM hot-spot analysis.
Exhibit 5-7. EMFAC2011-LDV Vehicle Categories
EMFAC2011 Vehicle & Technology
LDA - DSL
LDA - GAS
LDT1 - DSL
LDT1 - GAS
LDT2- DSL
LDT2 - GAS
LHD1-DSL
LHD1-GAS
LHD2-DSL
LHD2-GAS
MCY - GAS
MDV - DSL
MDV - GAS
MH - DSL
MH - GAS
T6TS - GAS
T7IS - GAS
SBUS - GAS
UBUS - DSL
UBUS - GAS
OBUS - GAS
Description
Passenger Cars
Passenger Cars
Light-Duty Trucks (0-3750 Ibs)
Light-Duty Trucks (0-3750 Ibs)
Light-Duty Trucks (3751-5750 Ibs)
Light-Duty Trucks (3751-5750 Ibs)
Light-Heavy-Duty Trucks (8501-10000 Ibs)
Light-Heavy-Duty Trucks (8501-10000 Ibs)
Light-Heavy-Duty Trucks (10001-14000 Ibs)
Light-Heavv-Dutv Trucks (10001-14000 Ibs)
Motorcycles
Medium-Duty Trucks (5751-8500 Ibs)
Medium-Duty Trucks (5751-8500 Ibs)
Motor Homes
Motor Homes
Medium-Heavy Duty Gasoline Truck
Heavy-Heavy Duty Gasoline Truck
School Buses
Urban Buses
Urban Buses
Other Buses
Exhibit 5-8 shows the general process for using the EMFAC2011-LDV module to obtain
emission rates for EMFAC2011 -LDV vehicle types for PM hot-spot analyses. However,
how EMFAC2011-LDV is to be configured and run depends entirely upon the specific
types of rates required for a particular PM hot-spot analysis. This section will describe
the various EMFAC2011-LDV inputs and show, as an example, how to use
EMFAC2011-LDV to obtain an aggregate light duty emission rate from vehicles types
LDA, LDT1, LDT2, and MCY. In addition, Appendix H contains an example of how to
use EMFAC2011-LDV to generate bus idling rates for a transit terminal for a PM hot-
spot analysis.
70
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Exhibit 5-8. Using EMFAC2011-LDV to Obtain Emission Rates for PM Hot-spot
Analyses
Open
EMFAC2011-LDY
Specify Basic Scenario Inputs (Section 5.7.1)
Select geographic
;u~e;i :ind
calculation
method
Select calendar
year
±
Does fleet
activity vary by
season mouth '
II
Use annual
average
Yes
Build
F.MFAC2011-I.DV
scenario for each
month/season
Enter scenario
title
Modify vehicle
classes
Does project
include all
vehicle
classes?
Yes
Configure Mode and Output
(Section 5.7.2)
Select "Einlac"
mode as Scenario
I
Select Output
Participate
Configure temp.,
relative humidity,
& speed
Select Output
Summary Rate
File (RTS File)
Edit Program
Constants
(Section 5.7.3)
Change distributions of
YMT, trips, and or
vehicle population to
reflect project fleet mix
Generate Emission
Factors
(Section 5.7.4)
Save scenario
and iiin Emfac
mode
Output emission
factor look-up
table
71
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5.7.1 Specifying basic scenario inputs
To generate emission factors in EMFAC2011-LDV for PM hot-spot analyses, users need
to first enter a series of basic inputs using the user interface. Exhibit 5-9 presents a
summary of all basic inputs needed to complete an EMFAC2011-LDV scenario run
("scenario"). The EMFAC2011-LDV defaults can be used directly for most basic input
categories; however, some inputs need to be modified to reflect project-specific
information.
Exhibit 5-9. Summary of EMFAC2011-LDV Inputs Needed to Evaluate a Project
Scenario for a PM Hot-spot Analysis
Step
1
2
3
4
5
6
7
EMFAC Basic Input Category
Geographic Area
Calculation Method
Calendar Year
Season or Month
Scenario Title
Model Years
Vehicle Classes
I/M Program Schedule
EMFAC Basic Input Data
State
Air Basin
District
County
By Sub-Area
Use Average
Calendar Year
Month
Season
Annual
Default
Modify
All
Modify
All
Modify
Default
Modify
Modification Needed?
Yes
No*
Yes
Yes
Optional
No
Optional**
No
* Defaults to "Use Average" if "County" selected. If "District" selected, "By Sub-Area" option is
available.
** If a project uses a subset of the default fleet, users should delete unwanted vehicle classes
through the "Vehicle Classes" user interface.
Geographic area and calculation method
Upon creating a new scenario in EMFAC2011-LDV, users should enter into GUI the
geographic area where the project is located. EMFAC2011-LDV offers four geographic
scales and each corresponds to specific defaults for fleet characteristics. The "Area
Type" category includes State, Air Basin, District, and County. For PM hot-spot
analyses, users will typically select the County area type. When "County" is selected, a
list of all the counties in California will be available. Users should select the county
where the project is located.
If the selected county is part of only one air basin, users can continue to the next step to
specify calendar years. However, if the selected county is within multiple air basins,
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EMFAC2011-LDV will show two options, "By Sub-Area" and "Use Average," as
calculation methods. Users should select "By Sub-Area" to generate EMFAC2011
emission factors in look-up tables for all sub-areas within the selected county.
For instance, Los Angeles County is located in both the Mojave Desert Air Basin and the
South Coast Air Basin. If the project is located near the Port of Los Angeles and "Los
Angeles County" with "By Sub-Area" selected, EMFAC2011-LDV will provide
emission data for both the Mojave Desert Air Basin and the South Coast Air Basin. Only
the look-up tables for the South Coast Air Basin would be used because this is where the
port is located; the Mojave Desert Air Basin data would be ignored.
Calendar year
EMFAC2011-LDV is able to analyze calendar years from 1990 to 2035 and allows
emission rates to be obtained for multiple calendar years in a single run. Users should
select one or more calendar years based on the project scenarios to be analyzed. If an
analysis year beyond 2035 is needed, select 2035 to represent that year.
Season or month
EMFAC2011-LDV can give emission factors for each month, two seasons (winter and
summer), or an annual average. Although VMT and speed are handled external to the
model, the vehicle mix may vary by hour and season and these scenarios should be
modeled explicitly. As discussed in Section 5.3, users should use EMFAC for the
appropriate number of scenarios based on the availability of travel activity data. Users
with typical travel activity data (i.e., average and peak hour data) may run one or two
scenarios (depending whether vehicle mix varies between the peak-hour and average-
hour) and will select "annual average" in the "Season or Month" selection panel. Users
with additional data that shows variation in fleet mix across seasons or months should
select the appropriate month or season for each run.
Scenario title
EMFAC2011-LDV generates a default scenario title that includes the name of the county,
calculation method, season or month, and calendar year. A replacement scenario title can
be specified, if desired.
Model years
EMFAC2011 includes vehicle model years from 1965 to 2040 and default assumptions
about mileage accumulation that vary by model year. EMFAC2011-LDV will generate
emission factors for 45 model years (ages 1 through 45). Users can change the range of
model years to be included in an EMFAC2011-LDV run through the model interface. If
a project involves a specialized and simple fleet (e.g., buses operating in a bus terminal)
for which the range of model years is well known or reliably estimated, users may
73
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consider including only those model years and exclude unrelated vehicle types in an
EMFAC2011-LDVrun.
Vehicle classes
Typically, all 21 default vehicle classes should be selected for most projects. The
exception would be a project or link that involves a specialized fleet of limited vehicle
types (e.g., a bus terminal). The EMFAC2011-LDV module assumes vehicle population
and travel activity distributions by vehicle class, depending on the geographic area and
analysis year selected. Editing the default distribution of vehicle classes, and excluding
vehicle classes from the rate calculations will be discussed in Section 5.7.3. If only one
vehicle type is selected, all emission information in the EMFAC2011-LDV output will be
calculated for that one vehicle type.
I/M program schedule
Currently, no PM emission benefit from I/M programs exists in EMFAC2011. Although
EMFAC2011-LDV allows edits for each I/M program, users should not alter the default
settings and parameters associated with I/M programs and their coverage.
5.7.2 Configuring mode and output
EMFAC includes three scenario types or modeling modes: Burden, Emfac, and Calimfac.
For PM hot-spot analyses, users should select the "Emfac" mode, which generates area-
specific fleet average emission factors for running exhaust, starting and idling emissions.
Once Emfac mode is selected, the following additional settings can be modified:
Temperature and relative humidity
The default settings in the Emfac mode include 15 temperature bins (-20F to 120F) and
11 relative humidity bins (0% to 100% RH) to generate average emission factors.
However, because EMFAC2011 PM emission rates are insensitive to changes in
temperature and humidity, generating emission factors for all default temperature/relative
humidity combinations throughout an analysis year is not necessary. As shown in
Exhibit 5-10, users need to remove the default temperature/relative humidity settings and
input only one value (e.g., 60F, 70% RH) for temperature and relative humidity,
respectively, to perform an Emfac mode run. Selecting one combination of
temperature/relative humidity will reduce computer run time and produce PM emission
factor look-up tables that can be easily used.
74
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Exhibit 5-10. Changing EMFAC2011-LDV Default Settings for Temperature and
Relative Humidity
Select/Edit temperature for Emfac calculations
Enter date f« lernpeiature
<• Detete tempeiature 1
f* Detete ten^wrature 2
' Delete ten*wa(ure 3
" Oek?teterrpetature4
f* Delete tercpeiature 5
^ D etete terrpwattire 6
*" Delete tempeiartire 7
'•" OetetererrpHarureS
" DefetererroeiarureS
^ Detete terrsjwetute 10
f" Deters temperature 11
f* Detete tempeiature 1 2
F? S oil th* -stray (done ali
Click button
_E
•10
0
10
20
30
40
50
SO
70
80
90
y eat]
:o enable new value.
f Detete ternpewtwei:
<~ DeleJeternieiatuieU
1" Delete tenveiature 15
•" Ente»empei9tue1E
r
r
r
r
r
^
f^
f
Of. | D
100
110
120
red |
Select/Edit re! hum for Emfac calculations
Entei data lor tel hum Cid
<* Delete ill hum 1
<~ Oeteteielhum2
'" DeteterelhumS
'" Dstet! rel hum 4
•" Detete rd hum 5
<~ [ieMrn-ihi.il 6
r Oetoterelhtm?
<~ BelelereihimS
<~ Deleters) him 9
(~ OelelerelhumlO
i" Delete re) hum 11
f~ Enlenelhum12
i^ Sort (he airav [done a(t
t button to er
^
10
20
3D
40
50
eo
70
80
90
100
iienitl
abl* new value.
r
r
r
r
r
r
r
r
r
r
r
r
OK | C.
incd |
Select/Edit temperature for Emfac calculations
Entodalifalenvaatua
•'• Delete terreeialure 1
^* Entet temperature. 2
r
r
^~ •
r
r
r
r
f*
r**
<~
v Sort the array (done alt
Cfcfc button to enable new vaiue.
~~H rr
r
r
r
r
r
c
(*
f
r
i««i | or. c,
incel |
Select/Edit rel hum for Emfac calculations
Ent« data lor lei him Clic
• Deteterelhuml
• Enteirelhum2
r i
f •
r
r
r
r
r
f •
C ,
r
& Sort Ihe anay (done alt(
t button to enable new value.
-1 ?
r
r
r
r
r
r
r
r
r
» ei*l | OK D
reel |
Note: Radio button selection will default to delete even after change has been made.
Speed
The Emfac mode allows users to input up to 24 speed values to populate average
emission factors. The default setting specifies speed bins for 0 mph through 65 mph in 5
mph increments. Emission factors for intermediate speeds can also be generated if
specific speed values are input into the EMFAC2011-LDV module.
Users have several options to calculate appropriate speed-dependent emission factors for
a project. For instance, if a highway link in a build scenario is known to have an average
speed of 32 mph, it can be directly input into the speed list of EMFAC2011 -LDV to
produce the associated PM emission factors. Alternatively, if the EMFAC2011 -LDV
default settings are used to generate a look-up table for different speed bins, users can
either select the emission factors associated with the closest speed bin (e.g., 30 mph bin,
representing speeds of 27.5 mph to 32.5 mph), or interpolate between the emission
factors for speed bins of 30 mph and 35 mph.
For specific cases for which the average link speed is less than 5 mph, users can either
select the emission factors from the 5 mph speed bin, or extrapolate the desired speed by
75
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using the emission factors from the speed bins for 5 mph and 10 mph to create a trend
line to lower speeds.
Output rate file
The Emfac mode can provide emission information in four output formats with different
levels of detail. Users should select "Summary Rates (RTS)." The Summary Rates
format generates average emission factors by speed for six vehicle groups (aggregated
from the 21 vehicle classes modeled in EMFAC2011-LDV) and an overall average
emission factor for the entire vehicle fleet. Typically, the "ALL" emission factor
(aggregate) should be used.
Output particulate
As shown in Exhibit 5-11, users have to select either PMio or PIVb.s in an Emfac mode
run to obtain particulate emission factors. EMFAC2011-LDV must be run twice to
obtain both PMio andPlVb.s data for those projects that are located in both PMio andPlVb
nonattainment/maintenance areas.
Exhibit 5-11. Selecting Pollutant Types in EMFAC2011-LDV for PMio and PM2.5
| Input 1 | Input 2 Mode and Output | TecMM | CYr Basis ] .
Burden -Area planning inventory
i
{
—
Emfac - Area fleet average emissions Ca
mfac- Detailed vehicle data 1
cenario Type: EMFAC -- Afea-specific fleet average emissions (g/hr) for selected temperatures, relative humidites, ;
peeds
Temperal
Relative Humidities |
Speed...
Cancel
Binary Impacts (BIN)
Summary Rates (RTS)
petaiiedirnpattF i'ates'JHT LJlj
Output Particulate As...
r Total PM
G PM10 ' PMZ5
Output Hydrocarbons As...
* TOG r THC
<~ ROG r CH4
= Edit Program p: 1 —
< Back Constants Fi™sh
76
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5.7.3 Editing program constants
Default data in the Etnfac mode
The Emfac mode is associated with a range of pre-populated program constants linked to
specific time periods and California geographic areas. Exhibit 5-12 lists the default data
available in the Emfac mode that can be accessed through the "Edit Program Constants"
in the user interface. For a PM hot-spot analysis, many of the defaults do not need to be
modified. However, users do need to determine which adjustments are needed for the
default distributions of VMT, trips, and vehicle population by vehicle class. The
EMFAC2011-LDV interface has "Copy with Headers" and "Paste Data Only" tabs that
are helpful for users to easily export the default data and import the adjusted data.
Exhibit 5-12. EMFAC2011 Program Constants and Modification Needs for PM
Hot-spot Analyses
EMFAC2011-LDV
Program Constants
Exh Tech Fractions
Evap Tech Fractions
Interim I/M
Population
Accrual
Trips
VMT
Speed Fractions
Idle Time
Description
Exhaust control technology fractions
Evaporative control technology factions
Enhanced interim I/M program
Vehicle population by class, fuel type, and age
Odometer accrual rate by class, fuel type, and age
Vehicle trips/starts per day by class, fuel type, and age
Vehicle miles traveled per day by class, fuel type, and age
VMT by speed bin distribution for each vehicle class
Idle times by vehicle class, fuel, and hour of day
Modification
Needed for PM
Analyses?
No
No
No
Yes*
No
Yes*
Yes*
No
No
* Different distributions in VMT, trips, or vehicle population than those reflected by the EMFAC2011
defaults should be updated through the user interface to incorporate project-specific vehicle activity
information.
EMFAC2011-LDV allows users to adjust the calculated fleet-average emission factors by
varying the relative weightings of the 21 vehicle classes. This adjustment is done by
replacing the default numbers for each vehicle class in the EMFAC2011-LDV user
interface, using the "VMT" option for a highway project, or the "Trips" or "Population"
option if analyzing a transit or other terminal project, under the "Edit Program Constants"
function available via the Emfac mode screen (an example is discussed below).
Note: EMFAC2011-LDV also allows users to modify the fuel characteristics
(gas/diesel/electric) for each vehicle class. For most PM hot-spot analyses for highway
projects with non-captive fleets, users will not need to modify the fuel assumed for the
fleet vehicles. For projects involving captive fleets with known fuel use distributions, the
default fractions should be modified.
11
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For the scenario described earlier, where only an aggregate light-duty emission rate is
needed, the heavy-duty classes included in EMFAC2011-LDV should be functionally
"zeroed-out" by assigning a value of "1" (see Exhibits 5-13 and 5-14).73 The default
VMT for the light duty (non-truck) vehicle classes (PC, Tl, T2, and MC) would remain
unchanged unless project-specific VMT is available for these vehicle classes, in which
case these entries should be adjusted to reflect project data. ,.
Exhibit 5-13. Example Default EMFAC2011-LDV VMT by Vehicle Class
Distribution (Heavy-duty Vehicle VMT Highlighted)
Editing VMT data for scenario 1: Sacramento County Subarea Annual CYr 2015 Default Title
Total VMT for area
Sacramento County
| Copy with Headings]
Paste Data Only
Editing Mode Editing VMT (vehicle miles traveled per weekday)
Total VMT By Vehicle Class By Vehicle and Fuel ] By Vehicle/Fuel/Hour I
01 -Light-DutyAutos (PC)
02-Light-Duty Trucks (T1)
03-Light-DutyTrucks(T2)
04-Medium-DutyTrucks[T3)
05-Light HOT rucks (T4)
06 - Light HD Trucks (T5)
07 - CAIRP+OOS+IS Trc/Sngl (T6)
08-Agriculture (T6)
Q9-Public + Utility(T6)
10-Out of State (T 7)
11 -CAIRP(T7)
12-Instate Tractor (T7)
13-Instate Single (T7)
14-Port(Drayage)(T7)
15-Agriculture (T 7)
16-Public+Util+SolidWaste(T7)
17 - Other Buses
18-Urban Buses
19- Motorcycles
20 - School Buses
21 - Motor Homes
19693386.
:;!950b.
38112.
90968.
242062.
4 J
85366
Done
' EMFAC2011-LDV will not accept "0" as a valid input.
78
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Exhibit 5-14. Example Adjusted EMFAC2011-LDV VMT by Vehicle Class
Distribution (Heavy-duty Vehicle VMT Highlighted)
Editing VMT data for scenario 1: Sacramento County Subarea January CYr 2012 Default Title
Total VMT for area
Sacramento County
Copy wilh Heading' I
Pa; te Data Li ill
Editing Mode Editing VMT (vehicle miles traveled per weekday)
Total VMT By Vehicle Class ] By Vehicle and Fuel | By Vehicle/Fuel/Hour |
01 -Light-Duty Autos (PC)
02 -Light-DutyT rucks (T1)
03 - Light-Duty Trucks (T2)
04 - Medium-Duty Trucks (T3)
05 - Light HD Trucks (T4)
06 - Light HD Trucks (T5)
07 - CAIRP+QQS+IS Trc/Sngl (TG)
08-Agriculture (T 6)
09 - Public + Utility (T6)
10 -Outof State (T7)
11 -CAIRP(T7]
12 -InstateTractor (T7)
13 -Instate Single [T7]
14-Port(Drayage)[T7)
15-Agriculture (T 7)
16-Public+Util+SolidWaste(T7)
17-Other Buses
18 - Urban Buses
19 -Motorcycles
20-School Buses
21 - Motor Homes
242062
Apply
Cancel
Note: The average emission factors provided by EMFAC2011-LDV in the "Emfacmode"
are VMT-weighted (for running emissions), vehicle trip-weighted (for start emissions), or
vehicle population-weighted (for idle emissions) across different vehicle classes. If a
user runs the model for a county, the weighting reflects county-level VMT, trips (starts),
or vehicle fleet and their absolute values are not relevant at the project level.
For most transit and other terminal projects, users may have detailed information on not
only vehicle mix, but also fuel mix (diesel/gas/electric) and age distribution (model year
distribution). Users should adjust the fuel mix (changed through the "By Vehicle and
Fuel" tabs of the VMT, Population, and Trips panels) to reflect the known or expected
fuel use (if, for instance, a bus fleet is expected to use entirely diesel fuel). Similarly, if
79
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the age distribution (model year distribution) is known for a particular fleet, this should
be entered in place of the EMFAC2011-LDV default values (found in the "By
Vehicle/Fuel/Age" tab of the Edit Population panel). An example showing the steps
involved in defining a project-specific age distribution for a single vehicle type is shown
in Appendix H.
Note that EMFAC2011-LDV s ability to model alternate fuel options is not uniform
among vehicle classes. If users determine that modification of the fleet in terms of fuel
or age distribution is needed, they should contact CARB for further guidance. However,
for most highway and intersection projects with a non-captive fleet, the EMFAC2011-
LDV default fuel mix should be used.
5.7.4 Generating EMFAC2011-LDV emission factors
For each EMFAC2011-LDV run, emission factors will be generated in the "Summary
Rates (RTS)" file (.rts file) in the form of look-up tables. These tables are organized and
numbered by different emission processes and pollutant types. PM emission factors for
running exhaust, idle exhaust, tire wear, and brake wear are included in Table 1 of the .rts
file; PM start emission factors are included in Table 2 of the .rts file. Exhibit 5-15
(following page) includes example screenshots of EMFAC2011-LDV .rts file output.
Highway and intersection links
For each speed value (greater than 0 mph), EMFAC2011-LDV outputs running exhaust,
tire wear, and brake wear emission factors in grams/vehicle-mile, for six vehicle groups
plus an aggregate emission factor named as "All". Note that the .rts output file includes
only six vehicle groups - an aggregation of the 21 vehicle classes manipulated during the
input process. In general, assuming users have run the model with VMT-weighted
distributions appropriate for the project's fleet activity (see Section 5.7.2), only the
emission factors from the "All" column will be needed. The "All" column includes a
grams/vehicle-mile value that is a VMT-weighted average based on the user-provided
vehicle activity mix. The sum of running exhaust, tire wear, and brake wear grams/mile
PM emission factors for a given speed is the total fleet-average grams/vehicle-mile
emission factor appropriate for modeling highway project links:
Total Link Emission Factor = (EFmrm^ + (EF^ wear) + (£Fbrake wear)
The total link emission factor (grams/vehicle-mile) can be used in combination with the
link volume and link length as input into CAL3QHCR. If using AERMOD, an emission
rate (in grams/hour) should be calculated for each link. This can be done by multiplying
the total link emission factor (calculated above) by the link hourly volume and link
length. If the project contains heavy-duty vehicle activity, an additional process is
necessary to weight together heavy-duty and light-duty emission rates based on link-
specific heavy-duty/light-duty volumes. See Section 5.9 for additional information.
80
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Exhibit 5-15. Example EMFAC2011-LDV Running Exhaust, Tire Wear, and Brake
Wear Emission Factors in the Summary Rates (rts) Output File
• default. rts - WordPad Q 0(5]®
File Edit View Insert
D Or y S Ei
Pollutant
Speed
HPH
0
5
10
15
20
25
30
35
40
45
50
55
60
65
Pollutant
Speed
HPH
0
5
10
15
20
25
30
35
40
45
50
55
60
65
Pollutant
Speed
HPH
0
5
10
15
20
25
30
Format
M
Name :
LDA
0.000
O.OSO
0.033
0.022
0.016
0.013
0.010
0.009
0.008
0.007
0.007
0.007
0.008
0.009
Name :
LDA
0.000
0.008
0.008
0.008
0.008
0.008
0.008
0.008
0.008
0.008
0.008
0.008
0.008
0.008
Name :
LDA
0.000
0.013
0.013
0.013
0.013
0.013
0.013
Help
PH10
0
0
0
0
0
0
0
0
0
0
0
0
0
0
PH10
0
0
0
0
0
0
0
0
0
0
0
0
0
0
PH10
0
0
0
0
0
0
0
B-
LDT
.000
.095
.062
.043
.032
.024
.020
.017
.015
.014
.014
.014
.015
.018
~> ^S
HDT
0.057
0.098
0.065
0.046
0.034
0.026
0.021
0.018
0.016
0.015
0.014
0.015
0.016
0.018
1
1
1
0
0
0
0
0
0
0
0
0
0
0
HDT
.380
.630
.129
.763
.549
.460
.395
.350
.327
.324
.340
.376
.431
.505
- Tire Wear
LDT
.000
.008
.008
.008
.008
.008
.008
.008
.008
.008
.008
.008
.008
.008
HDT
0.000
0.009
0 . 009
0.009
0.009
0.009
0.009
0.009
0.009
0.009
0.009
0.009
0.009
0.009
0
0
0
0
0
0
0
0
0
0
u
0
0
0
HDT
.000
.026
.026
.026
.026
.026
.026
.026
.026
.026
.026
.026
.026
.026
- Brake Uear
LDT
.000
.013
.013
.013
.013
.013
.013
HDT
0.000
0.013
0.013
0.013
0.013
0.013
0.013
0
0
0
0
0
0
0
HDT
.000
.022
.022
.022
.022
.022
.022
Temperature:
UBUS
0.000
0.888
0.643
0.483
0.376
0.303
0.252
0.218
0.195
0.181
0. 173
0. 172
0.177
0.189
Temperature:
UBUS
0.000
0.008
0.008
0.008
0.008
0.008
0.008
0.008
0.008
0.008
0.008
0.008
0.008
0.008
Temperature:
UBUS
0.000
0.013
0.013
0.013
0.013
0.013
0.013
60F
HCT
0.000
0.051
0.040
0.033
0.029
0.026
0.025
0.024
0.025
0.027
0.031
0.037
0.046
0.060
60F
HCT
0.000
0.004
0.004
0.004
0.004
0.004
0.004
0.004
0.004
0.004
0.004
0.004
0.004
0.004
60F
HCT
0.000
0.006
0.006
0.006
0.006
0.006
0.006
Relative Humidity: 70%
ALL
0.084
0.163
0.111
0.076
0.055
0.045
0.037
0.033
0.030
0.029
0.030
0.032
0.036
0.042
Relative Humidity: 70%
ALL
0.000
0.009
0.009
0.009
0.009
0.009
0.009
0.009
0.009
0.009
0.009
0.009
0.009
0.009
Relative Humidity: 70%
ALL
0.000
0.013
0.013
0.013
0.013
0.013
0.013
v
gf >
For Help, press Fl
MUM
Transit and other terminal links
For transit and other terminal projects, such as bus terminals or intermodal freight
terminals, the emissions contribution will be a combination of idling, starting, and/or
running emissions. EMFAC2011-LDV allows users to generate emission factors for both
the bus terminal itself (idling and start emissions) and approaching/departing links
(running emissions) in a single run. To obtain project-specific running exhaust emission
factors, users can modify the VMT associated with the buses at the approaching link by
81
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adjusting the values for each of the EMFAC2011-LDV vehicle classes in the user
interface with the method described in Section 5.7.3. In the same EMFAC2011-LDV
run, users can enter project-specific vehicle population to generate the necessary idle
emission factors. Note that since AERMOD will always be used for complex projects
involving both highway/intersections and terminals, the running rates from EMFAC
(grams/veh-mile) should be converted to grams/hour rates.
Other special projects may need additional data manipulation. Project sponsors should
contact CAKB or the local air quality management district for further guidance.
Idling Emissions. Idling emission factors for some EMFAC2011-LDV vehicle types (the
MDT and HOT groups) are reported as grams/idle-hour and are available in Table 1 of
the .rts file associated with a speed value of 0 mph. For all other vehicle types (including
passenger cars and urban buses), an idle rate may be calculated based on the reported rate
for 5 mph, also in Table 1 of the .rts file. This rate in grams/vehicle-mile should be
multiplied by 5 miles/hour to obtain a grams/veh-hour rate. This grams/veh-hour idle
rate can then be multiplied by the number of idling vehicles in the area and the resulting
grams/hour rate can be used in air quality modeling.
Note that in many transit projects, buses will not typically idle for the entire hour.
Therefore, the grams/veh-hour rate should be adjusted to include the actually number of
idling buses, as well as the "dwell time." For instance, a transit terminal may have a
particular area where 50 buses idle for 6 minutes per hour while they pick-up/drop-off
passengers. The idle rate generated by EMFAC2011-LDV should be multiplied by the
number of idling buses, as well as the fraction of the hour (0.1 hour) when idling is
occurring. The resulting grams/hour rate can be used in air quality modeling.
Start Emissions. Start emissions may be a significant source of PM for many transit or
other terminal projects. EMFAC2011-LDV reports start emissions as grams/trip (or
grams/start) emission factors for gasoline vehicles only. These factors can be combined
with project-specific estimates of vehicle trips (or starts) per hour to calculate grams/hour
emissions. Starting emission factors depend on the vehicle soak time (the soak time is
the time a vehicle is stationary with the engine turned off, following the last time it was
operated). The longer a vehicle is turned off, or soaks, the higher the start emissions
embedded in EMFAC2011-LDV. The output look-up table for start emissions includes
18 time bins (5 minutes to 720 minutes); users need to choose an appropriate time bin
that is representative for the project activity. A particular area of starting activity may
have a soak time distribution (e.g., 10 percent soaking 5 minutes, 40 percent soaking 320
minutes, and 50 percent soaking 720 minutes), the subsequent rates should be
appropriately weighted together to calculate a grams/hour emission rate for use in air
quality modeling.
Since EMFAC2011-LDV does not contain any start rates for any diesel vehicle type in
the module, the approach described in Section 5.6.4 should be used to estimate a start rate
for these vehicles. Note that idling emissions (and therefore start emissions) will vary
between EMFAC2011-LDV vehicle types; care should be taken to ensure rates are
82
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matched to the correct vehicle type and that starts for all appropriate vehicle types are
accounted for.
Running Emissions. Finally, users may need to model running exhaust emissions from
cruise, approach, and departure link activity, as well as start and idle emissions at the
project site. For instance, to assess impacts from a proposed bus terminal, users may
need to evaluate the idle emissions from buses at the terminal as well as the bus running
exhaust emissions along the links approaching and departing from the terminal.
Given that the link activity will likely involve a unique vehicle fleet (one with a
disproportionate amount of bus activity), users should modify the default travel activity
in EMFAC-LDV to reflect the bus activity.
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5.8 APPLYING THE DETAILED APPROACH: USING EMFACIOII-HD
The procedure described here should be used when emission rates are needed for any of
the EMFAC2011-HD vehicle categories listed in Exhibit 5-16.
Exhibit 5-16. EMFAC2011-HD Vehicle Categories
EMFAC2011 Vehicle & Technology
T6 Ag - DSL
T6CAIRP heavy- DSL
T6CAIRP small - DSL
T6 instate construction heavy - DSL
T6 instate construction small - DSL
reinstate heavy- DSL
T6 instate small - DSL
T6 DOS heavy - DSL
T6 DOS small - DSL
TSPublic- DSL
T6 utility- DSL
T7 Ag - DSL
T7CAIRP - DSL
T7 CAIRP construction - DSL
T7NNOOS- DSL
T7 NCOS - DSL
T7 other port - DSL
T7 POAK - DSL
T7 POLA - DSL
T7 Public- DSL
T7 Single - DSL
T7 single construction - DSL
T7 SWCV - DSL
T7 tractor - DSL
T7 tractor construction - DSL
T7 utility- DSL
PTO - DSL
SBUS - DSL
Motor Coach - DSL
All Other Buses - DSL
Description
Medium-Heavy Duty Diesel Agriculture Truck
Medium-Heavy Duty Diesel CA International Registration Plan Truck
with GVWR>26000lbs
Medium-Heavy Duty Diesel CA International Registration Plan Truck
with GVWR<=26000 Ibs
Medium-Heavy Duty Diesel instate construction Truck with
GVWR>26000lbs
Medium-Heavy Duty Diesel instate construction Truck with
GVWR<=26000lbs
Medium-Heavy Duty Diesel instate Truck with GVWR>26000 Ibs
Medium-Heavy Duty Diesel instate Truck with GVWR<=26000 Ibs
Medium-Heavy Duty Diesel Out-of-state Truck with GVWR>26000 Ibs
Medium-Heavy Duty Diesel Out-of-state Truck with GVWR<=26000 Ibs
Medium-Heavy Duty Diesel Public Fleet Truck
Medium-Heavy Duty Diesel Utility Fleet Truck
Heavy-Heavy Duty Diesel Agriculture Truck
Heavy-Heavy Duty Diesel CA International Registration Plan Truck
Heavy-Heavy Duty Diesel CA International Registration Plan
Construction Truck
Heavy-Heavy Duty Diesel Non-Neighboring Out-of-state Truck
Heavy-Heavy Duty Diesel Neighboring Out-of-state Truck
Heavy-Heavy Duty Diesel Drayage Truck at Other Facilities
Heavy-Heavy Duty Diesel Drayage Truck in Bay Area
Heavy-Heavy Duty Diesel Drayage Truck near South Coast
Heavy-Heavy Duty Diesel Public Fleet Truck
Heavy-Heavy Duty Diesel Single Unit Truck
Heavy-Heavy Duty Diesel Single Unit Construction Truck
Heavy-Heavy Duty Diesel Solid Waste Collection Truck
Heavy-Heavy Duty Diesel Tractor Truck
Heavy-Heavy Duty Diesel Tractor Construction Truck
Heavy-Heavy Duty Diesel Utility Fleet Truck
Power Take Off
School Buses
Motor Coach
All Other Buses
84
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In order to capture all the emission processes for EMFAC2011-HD vehicle categories
using the detailed approach, users will need to access multiple data sources (described in
Exhibit 5-17, below). This is because the data formats and input requirements are quite
different for different processes:
• Running Exhaust Emission Rates (g/mile) change by speed, and therefore, require
speed as an input.
• PM Brake Wear and Tire Wear Emissions Rates (g/mile) are assumed to be same
at all speeds (EMFAC2011-HD outputs it at the "ALL Combined Speed" level).
• Idling Exhaust Emission Rates (g/hour) are based on idling time.
• Start Exhaust Emission Rates (g/start) can be estimated using EMFAC2011-HD
idling exhaust rates and the procedure described in Section 5.8.4.
All the required rates to calculate these emissions are available on the CARB website.
The specific tools used to generate emission rates for the EMFAC2011-HD vehicle
categories will vary depending on the particular type of emissions selected. Exhibit 5-17
provides a quick reference for data sources for each of the emission processes. However,
users need to follow all the procedures detailed in following sections (5.8.1 through
5.8.4) to obtain complete emission rates for EMFAC2011-HD vehicles.
Exhibit 5-17. Data Sources for EMFAC2011-HD Vehicle Emission Rates (Detailed
Approach)
Emission Process
Running Exhaust
Emission Rates
(RUNEX)
PM Brake Wear
and Tire Wear
(PMBW/PMTW)
Idling Exhaust
Emission Rates
(IDLEX)
Start Exhaust
Emission Rates
Where to Find
www.arb.ca.gov/emfac
Download "by speed" for RUNEX
www.arb.ca. gov/emfac
Download "Combined" speeds for PMBW and PMTW
http://www.arb.ca.gov/msei/emfac2011 idling emission rates.xlsx
Estimate using appropriate idling exhaust rate; see Section 5.8.4.
Units
g/mile
g/mile
g/hr
g/start
As noted, for some processes it will be necessary to go to CARB's EMFAC web database
(www.arb.ca. gov/emfac). A screenshot of the database's graphical user interface is
shown in Exhibit 5-18. Details on how and when to access the database emission factors
are described further in this section.
85
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In addition, the CARB EMFAC2011 "Handbook for Project-level Analyses" contains
examples in the appendices (see, in particular, Scenario #5B and Scenario #7) that show
using EMFAC2011-HD to obtain emission rates for some illustrative projects. These can
be referenced as a general guide on how to employ EMFAC2011-HD as part of the
detailed approach.
Exhibit 5-18. Graphical User Interface for CARB's EMFAC Web Database
California Environmental Protection Agency
©= Air Resources Board
A A Search AR
A| A| A
{*) Google
Thursday. February 14.2013
UP LINKS
EMFAC Emissions Database
»> Reducing Air Pollution - ARB
Programs
O Mobile Sources
O Manufacturers
O Emissions
'~rj Emission Rates
Reyion:
Ctileiuliir Year:
t> Atr Quality
O Emissions Inventory
o Mobile Sources
Emissions
Inventory
Vehicle Category: Please Seled
PROGRAM LINKS
Background
O Categories
o Current Methods
o Historical Methods
RESOURCES
O Contact Us
O Join the MSEI Email List
^ RSS / N9"1'.''7 i
5.8.1 Obtaining EMFAC'2011-HD vehicle running exhaust emission rates
The general methodology for generating Running Exhaust Emission Rates (RUNEX) for
EMFAC2011-HD vehicles using the detailed approach is shown in Exhibit 5-19.
The emission rates and default VMT by vehicle class (which can be used when
weighting, per Section 5.9) are available through the EMFAC2011 web database
(www.arb.ca.gov/emfac). Users are required to select the following options:
• Data Type: Emission Rates
• Region Type: Statewide Average, Air Basin, Air District, MPO, County, Sub-
Area (GAI)
• Region (based on Region Type selection)
• Calendar Year
• Season
• Vehicle Category scheme (EMFAC2011 or EMFAC2007)
• Vehicle Type (based on Vehicle Category scheme selection)
-------
• Model Year
• Speed
• Fuel
See Exhibit 5-19 for additional input guidance. In addition, guidance for using
EMFAC2011-LDV applies to the Region, Region Type, Calendar Year and Season
selections for PM hot-spot analyses; see Section 5.5 for details.
87
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Exhibit 5-19. Obtaining Running Emissions (RUNEX) Emission Rates for
EMFAC2011-HD Vehicles (Detailed Approach)"
74
GotoEMFAC2011
web database
Select Data Type
"Emission Tiiitirs"
Select Region type
Select Region
Select
Calendar Year
Select
Sent
on
Select Vehicle Category
[EMFAC2011 or EMFAC2007]
Unclieck tlie "Vehicle
Category" checkbox (defaults
to "ALL" option)
Cheek the "Model Year"
checkbox and select desired
model year (or "ALL" for
multiple model years)
Does the project
contain multiple
vehicle categories?
Check (he "Speed" checkbox
and select the "ALL" option
(for multiple speed outputs)
Check the "Fuel" checkbox
and selcel the "DSL" option
Are activity data
distributed over
multiple speed
^ bins?
Check the "Vehicle Category"
checkbox aiul select desired
vehicle
Unchcck the "Model Year"
checkbox (defaults to
"Combined" option)
Cheek the "Speed" checkbox
and select the desired speed
bin
Click "Download" and save
the Emission Rate file
Output emission
factor lookup
table
74 Exhibit is the same as in CARS's EMFAC2011 "Handbook for Project-level Analyses" for consistency
purposes. Users may find that the checkboxes now may be menu selections.
88
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5.5.2 ObtainingEMFAC2011-HD vehicle brake and tire wear emission rates
The general methodology for generating PM Brake Wear (PMBW) and PM Tire Wear
(PMTW) emission rates for EMFAC2011-HD vehicles using the detailed approach is
explained in Exhibit 5-20.
The emission rates are available through the EMFAC2011 web database
(www.arb.ca.gov/emfac). Users are required to select the following options:
• Data Type: Emission Rates
• Region Type: Statewide Average, Air Basin, Air District, MPO, County, Sub-
Area (GAI)
• Region (based on Region Type selection)
• Calendar Year
• Season
• Vehicle Category scheme (EMFAC2011 or EMFAC2007)
• Vehicle Type (based on Vehicle Category scheme selection)
• Model Year
• Speed (select "Combined" Speeds option)
• Fuel
See Exhibit 5-20 for additional input guidance. In addition, guidance for using
EMFAC2011-LDV applies to the Region, Region Type, Calendar Year and Season
selections for PM hot-spot analyses; see Section 5.5 for details.
89
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Exhibit 5-20. PM Brake Wear and Tire Wear (PMBW/PMTW) Emission Rates for
EMFAC2011-HD Vehicles (Detailed Approach)"
75
Uncheck the "Vehicle
Category" checkbox (ilet'aults
to "ALL" option)
GotoEMFAC2011
web database
Select Data Type
"Emission R;iles"
'Select Region type
Seleet Reuion
Select Calendar Year
Sele
ct Season
SuLvt Yirhiirk' CaK^uy ;iJ]cme
[EMFAC2011 orEMFAC2007]
Check Hie "Rid" irheckhox
and select the "DSL" option
Check the "Vehicle Category"
cliecklit>\ mul select desireJ
vehicle
Check The "Model Year'
checkbox and select desired
model year (or "ALL" for
multiple model years)
Is activity data "---. ^o
;i\;iil;il>lf by m
y«r?
Uncheck the "Speed"
drcekbox (defaults to
"Combined" option)
I
Click "Download" and save
the Emission Rate file
Output emission
factor lookup
table
Uuchcck the "Model Year"
L-'lifi-kbox ulctuilts to
"Combined" option I
75 Exhibit is the same as in CARS's EMFAC2011 "Handbook for Project-level Analyses" for consistency
purposes. Users may find that the checkboxes now may be menu selections.
90
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5.5.3 Obtaining EMFAC2011-HD vehicle idling exhaust emission rates
The general methodology for generating Idling Exhaust Emission Rates (IDLEX) for
EMFAC2011-HD vehicles using the detailed approach is shown in Exhibit 5-21.
Exhibit 5-21. Obtaining Idling (IDLEX) Emission Rates for EMFAC2011-HD
Vehicles (Detailed Approach)
OpenCARB's Mobile Source Emissions
Inventory webpage
(www.arb.ca.gov nisei mocleling.hlm)
4
Right-click on the "EMFAC011 Idling
Emission Rates" file and select the "Save
As" option
,, ,
Output emission
factor lookup
table
^~~~
Browse to the appropriate
region
Filter the Excel data table
and soled the appropriate
Calendar Year and Vehicle
The emission rates are available in an Excel spreadsheet that can be downloaded from the
web at www.arb.ca.gov/msei/emfac2011 idling emission rates.xlsx.
• The spreadsheet provides idling emission rates for EMFAC2011 -HD vehicle
categories (Diesel Vehicles classes for T6/MHDT, T7/HHDT, OBUS, and
SBUS).
• Emission rates are in grams/hour
• Emission rates are corrected for cleaner fuel, but not for retrofit requirements of
the idling rule.
• HD Idling emission rates are available for two geographic areas: (1) the South
Coast Air Basin and the South Central Coast (Ventura County) Air Basin; and (2)
all other areas.
91
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Specific idling emission rates can be selected by selecting select the "Filter" function
from the "Data" menu and then selecting the following from the drop-down menus:
• By Calendar Year
• By Season
• By Vehicle Class
• By Fuel Type
• By Model Year
Idle rates are available for annual, winter, or summer periods. Depending on the season,
assumptions are made about the engine load based on the expected use of heaters, air
conditioners, and other vehicle accessories. The annual average rate should not be used,
as it is a simple composite of both winter and summer rates. Instead, users may either
select the most conservative emission rate (usually winter), or emission rates from
summer (S) and winter (W) can be paired with activity on a seasonal basis. Users may
consult with the Section 7 of the guidance for information on how seasonal variation in
emission rates impacts the air quality modeling procedures.
If project-specific engine loads are known for idling vehicles, CARB has created
supplemental guidance that, off-model, provides MHDDT and HHDDT emission rates
for activity that CARB has termed "high idle" and "low idle."76 Low idle (sometimes
also called "curb idle") involves short-term idling with engine speeds of 800 rpm or less
and no accessory loading. High idle is idling over an extended period of time with
engine speeds over 800 rpm, usually involving the use of heaters, air conditioners, or
other vehicle accessories. If the project under evaluation involves either MHDDT or
HHDDT vehicle types and the user has detailed information about the fleet (vehicle
model years and the amount of time spent in low and high idle, in particular), the
information from this supplemental guidance may be used to obtain more specific idle
emission factors for MHDDT and HHDDT than those available in the web-based
spreadsheet.
5.8.4 ObtainingEMFAC2011-HD vehicle start exhaust emission rates
Since EMFAC2011-HD does not contain any start rates for any vehicle type in the
module (they are all diesel vehicles), the approach described in Section 5.6.4 should be
used to estimate a start rate for these vehicle types. Note that idling emissions (and
therefore start emissions) will vary between EMFAC2011-HD vehicle types; care should
be taken to ensure rates are matched to the correct vehicle type and that starts for all
appropriate vehicle types are accounted for.
76 For MHDDT rates, see Table 11-5 of the EMFAC2011 Technical Documentation, available through
CARB online at: www.arb.ca.gov/msei/modeling.htm. For HHDDT rates, see pages 13-15 of the EMFAC
Modeling Change Technical Memo, "Revision of Heavy Duty Diesel Truck Emissions Factors and Speed
Correction Factors" (original and amendment), October 20, 2006; available at:
www.arb.ca. go v/msei/supportdocs.htm#onroad.
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5.5.5 Diesel retrofits in EMFAC2011
Regarding diesel engine retrofits, benefits from the retrofits contained in the Truck and
Bus Rule are already included in the appropriate EMFAC2011 emission rates. Only
retrofits not included in EMFAC2011 are potentially eligible for consideration outside of
the model. Any issues regarding the models and associated methods and assumptions for
the inclusion of state control measures in PM hot-spot analyses must be considered
through the process established by each area's interagency consultation procedures (40
CFR93.105(c)(l)(i)).77
5.9 USING THE DETAILED APPROACH FOR PROJECTS CONTAINING BOTH
LIGHT-DUTY AND HEAVY-DUTY VEHICLES
Individual projects will often have a mix of vehicle types that varies from the regional
average fleet mix. A common practice in California is to define, for emissions purposes,
"truck" activity as being comprised of all activity associated with what EMFAC identifies
as medium-duty and heavier vehicles. In addition, travel activity data typically identify
"trucks" in a general sense, without regard to their fuel type. A useful spreadsheet
showing vehicle class mapping between trucks/non-trucks and the EMFAC2007 and
EMFAC2011 vehicle categories can be found on CARB's website:
www.arb.ca.gov/msei/vehicle-categories.xlsx. To obtain a single aggregate link emission
rate for a detailed analysis, users should properly weight together summary rates from
EMFAC2011-LDV and EMFAC2011-HD as described below.
For the light-duty ("non-truck") fleet, users will need to adjust the project fleet and fleet
activity (VMT, trips) to reflect the expected project fleet mix for each EMFAC2011-LDV
run. Depending on the project, users should modify some combination of VMT (which
affects running exhaust emission factors), vehicle trips (which affects starting emission
factors), and/or vehicle population (which affects running and idling emission factors).
Typically, users should adjust the EMFAC2011-LDV VMT defaults to "zero-out" all
non-light-duty vehicle classes (demonstrated in Section 5.7.3.) Running the model will
produce an aggregate light duty-only emission rate for the appropriate light-duty vehicle
classes.
To estimate an aggregate emission rate for heavy-duty ("truck") vehicle classes, it is
recommended that ARB's web database be used. As described in Section 5.8, emission
rates and default VMT can be obtained for each heavy-duty vehicle type. For a detailed
analysis where a project-specific age distribution is known, emission rates should be
queried for each heavy-duty vehicle type and vehicle age. A spreadsheet program can be
used to properly weight the heavy-duty vehicle types to correctly account for the project-
77 For information about quantifying the benefits of retrofitting diesel vehicles and engines to conformity
determinations, see EPA's website for the most recent guidance on this topic:
www.epa.gov/otaq/stateresources/transconf/policy.htm. Also, see CARB's website at:
www.arb.ca.gov/msprog/onrdiesel/calculators.htm.
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specific age distribution. If a detailed heavy-duty vehicle mix is not known (i.e., only a
heavy-duty/light-duty split is known), the default VMT reported by the online emission
rate database can be used to properly weight together all heavy-duty vehicle classes into a
single aggregate heavy-duty emission rate. Users can contact ARB if they have questions
or need additional information about this process.
Once aggregate light-duty and heavy-duty emission rates have been calculated for each
link, they should be weighted together based on the link specific light-duty and heavy-
duty vehicle mix. The resulting emission rate for each link can be used in dispersion
modeling.
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Section 6: Estimating Emissions from Road Dust,
Construction, and Additional Sources
6.1 INTRODUCTION
This section provides guidance on how to estimate re-entrained road dust and
transportation-related construction dust emissions. MOVES and EMFAC do not estimate
emissions of road or construction dust, so this section must be consulted if dust is
required to be included in the PM hot-spot analysis. See Section 2.5 for further
information regarding when dust emissions are required to be included in a PM hot-spot
analysis. This section also includes information on quantifying emissions from
construction vehicles and equipment and additional sources in the project area, when
applicable. The models and associated methods and assumptions used in estimating these
emissions must be evaluated and chosen through the process established by each area's
interagency consultation procedures (40 CFR 93.105(c)(l)(i)).
6.2 OVERVIEW OF DUST METHODS AND REQUIREMENTS
In summary, road or construction dust can be quantified using EPA's AP-42 method or
alternative local methods. AP-42 is EPA's compilation of data and methods for
estimating average emission rates from a variety of activities and sources from various
sectors. Refer to EPA's website (www.epa.gov/ttn/chief/ap42/index.html) to access the
latest version of AP-42 sections and for more information about AP-42 in general. The
sections of AP-42 that address emissions of re-entrained road dust from paved and
unpaved roads and emissions of construction dust are found in AP-42, Chapter 13,
"Miscellaneous Sources." The key portions of the chapter include:
• Section 13.2: "Introduction to Fugitive Dust Sources,"
• Section 13.2.1: "Paved Roads"
• Section 13.2.2: "Unpaved Roads"
• Section 13.2.3: "Heavy Construction Operations" (includes road construction)
Users should consult EPA's website to ensure they are using the latest approved version
•yo
of AP-42, as the methodology and procedures may change over time.
In addition to the latest version of AP-42, alternative local methods can be used for
estimating road or construction dust; in some areas, these methods may already exist and
can be considered for use in quantitative PM hot-spot analyses.
This section presumes users already have a basic understanding of how to use AP-42 or
other dust methods.
78 This guidance is applicable to current and future versions of AP-42, unless otherwise noted by EPA in
the future.
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6.3 ESTIMATING RE-ENTRAINED ROAD DUST
6.3.1 PM2.5 nonattainment and maintenance areas
The transportation conformity rule requires a hot-spot analysis in a PIVb.s nonattainment
and maintenance area to include emissions from re-entrained road dust only if emissions
from re-entrained road dust are determined to be a significant contributor to the PM2.5
nonattainment problem. See Section 2.5 for further information.
6.3.2 PMw nonattainment and maintenance areas
Re-entrained road dust must be included in all PMio hot-spot analyses. EPA has
historically required road dust emissions to be included in all conformity analyses of
direct PMio emissions - including hot-spot analyses. See Section 2.5 for further
information.
6.3.3 Using AP-42for road dust on paved roads
Section 13.2.1 of AP-42 provides a method for estimating emissions of re-entrained road
dust from paved roads for situations for which silt loading, mean vehicle weight, and
mean vehicle speeds on paved roads fall within ranges given in AP-42, Section 13.2.1.3
and with reasonably free-flowing traffic (if the project doesn't meet these conditions, see
Section 6.3.5, below). Section 13.2.1 of AP-42 contains predictive emission factor
equations that can be used to estimate an emission factor for road dust. This section can
be downloaded from EPA's website at: www.epa. gov/ttn/chief/ap42/ch 13/index.html.
When estimating emissions of re-entrained road dust from paved roads, site-specific silt
loading data must be consistent with the data used for the project's county in the regional
emissions analysis (40 CFR 93.123(c)(3)). In addition, if the project is located in an area
where anti-skid abrasives for snow-ice removal are applied, information about their use
should be included (e.g., the number of times such anti-skid abrasives are applied).
6.3.4 Using AP-42 for road dust on unpaved roads
Section 13.2.2 of AP-42 provides a method for estimating emissions of re-entrained road
dust from unpaved roads. Different equations are provided for vehicles traveling
unpaved surfaces at industrial sites and vehicles traveling on publicly accessible roads.
Most PM hot-spot analyses will involve only vehicles traveling on publicly accessible
roads. When applying an equation that accounts for surface material moisture content,
the percentage of surface material moisture must be consistent with the data used for the
project's county in the regional emissions analysis (40 CFR 93.123(c)(3)).
96
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6.3.5 Using alternative local approaches for road dust
Some PM areas have historically used locally-developed methods for estimating re-
entrained road dust emissions that may be more appropriate than the AP-42 methods
given specific local conditions. Other areas may develop alternatives in the future.
Also, an alternative method could be used if the equations in AP-42 do not apply
to a particular project, as they were developed using a particular range of source
conditions. Section 13.2.1 of AP-42 currently states that users should use caution
when applying the 13.2.1 equation outside of the range of variables and operating
conditions specified. In these cases, users are encouraged to consider alternative
methods that can better reflect local conditions.
6.4 ESTIMATING TRANSPORTATION-RELATED CONSTRUCTION DUST
6.4.1 Determining whether construction dust must be considered
Construction-related PIVb.s or PMio emissions associated with a particular project are
required to be included in hot-spot analyses only if such emissions are not considered
temporary as defined in 40 CFR 93.123(c)(5) (see Section 2.5.5). The following
discussion includes guidance only for construction-related dust emissions; any other
construction emissions (e.g., exhaust emissions from construction equipment) would need
to be calculated separately, as discussed in Section 6.6.
6.4.2 Using AP-42 for construction dust
Section 13.2.3 of AP-42 describes how to estimate emissions of dust from construction of
transportation projects. This section can be downloaded from EPA's website at:
www. epa. gov/ttn/chief/ap42/chl 3/index.html. Section 13.2.3 of AP-42 indicates that a
substantial source of construction-related emissions could be from material that is tracked
out from the site and deposited on adjacent paved streets. Therefore, AP-42 states that
persons developing construction site emission estimates need to consider the potential for
increased adjacent emissions from off-site paved roadways; users should refer to the
discussion regarding paved roads in Section 6.3.3.
6.4.3 Using alternative approaches for construction dust
Some PM nonattainment or maintenance areas have historically used alternative methods
for estimating construction dust that may be more appropriate than AP-42, given specific
local conditions. Other areas may develop alternatives in the future.
Also, an alternative method may be more appropriate if the project's conditions - such as
surface material silt and moisture content percentages, mean vehicle weight and speed -
are not within the ranges of source conditions that were tested in developing the
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equations. In such cases, users may consider alternative methods that are more
appropriate for local conditions.
6.5 ADDING DUST EMISSIONS TO MOVES/EMFAC MODELING RESULTS
Emission factors for road and construction dust should be added to the emission factors
generated for each link by MOVES or EMFAC (in California). Once this data is
available, the user can move on to Section 7 to develop input files for the appropriate air
quality model.
6.6 ESTIMATING ADDITIONAL SOURCES OF EMISSIONS IN THE PROJECT
AREA
6.6.1 Construction-related vehicles and equipment
In certain cases, emissions resulting from construction vehicles and equipment, including
exhaust emissions as well as dust, must be included in an analysis; refer to Section 2.5.5
for more information on when to include such emissions. State and local air agencies
may have quantified these types of emissions for the development of SIP non-road
mobile source inventories, and related methods should be considered for PM hot-spot
analyses. Evaluating and choosing models and associated methods and assumptions for
quantifying construction-related emissions must be determined through an area's
interagency consultation procedures (40 CFR 93.105(c)(l)(i)).
6.6.2 Locomotives
EPA has developed guidance to quantify locomotive emissions when they are a
component of a transit or freight terminal or otherwise a source in the project area being
modeled. See Appendix I for further general guidance, resources, and examples.
6.6.3 Additional emission sources
When applicable, additional sources need to be estimated and included in air quality
modeling, as described in Section 8.
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Section 7: Selecting an Air Quality Model, Data Inputs, and
Receptors
7.1 INTRODUCTION
This section describes the recommended air quality models, data inputs, and receptor
considerations for PM hot-spot analyses. This guidance is consistent with the conformity
rule and recommendations for air quality modeling in EPA's "Guideline on Air Quality
Models" (Appendix W to 40 CFR Part 51).
Regardless of the model used, the quality of a model's predictions depends on
appropriate input data, proper formatting, model setup, quality assurance, and other
assumptions. As noted in Section 2, air quality modeling for PM hot-spot analyses must
meet the conformity rule's general requirements for such analyses (40 CFR 93.123(c))
and rely on the latest planning assumptions available when the conformity analysis
begins (40 CFR 93.110).
This section presumes that users already have a basic understanding of air quality models
and their operation. EPA has also included additional details on air quality modeling in
Appendix J of this guidance. The models in this section, user guides, and supporting
documentation are available through EPA's Support Center for Regulatory Air Models
(SCRAM) website at: www.epa.gov/scram001. Project sponsors conducting PM hot-spot
analyses will need to refer to the latest user guides and available guidance for complete
instructions.
7.2 GENERAL OVERVIEW OF AIR QUALITY MODELING
Air quality models, methods, and assumptions need to be determined for each PM hot-
spot analysis through the interagency consultation process (40 CFR 93.105(c)(l)(i)).
Exhibit 7-1 (following page) outlines the basic process for conducting air quality
modeling for a given project. This exhibit depicts the flow of information developed for
air quality modeling (as described in this section), the development of background
concentration estimates (see Section 8), and the calculation of design values and
comparison to the NAAQS (see Section 9).
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Exhibit 7-1. Overview and Data Flow for Air Quality Modeling
Appendix W to
4QCFRPart51
(throughout)
AERMOD
Implementation
Guide
N
<
C.
IPRMUser
juide (for
\L3QHCR)
AERMETUser
Guide (for
AERMOD)
AERiiOD
loipleniewtation
Guide
tfci
7)
Select appropriate air
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7.3 SELECTING AN APPROPRIATE AIR QUALITY MODEL
7.3.1 Recommended air quality models
PM hot-spot analyses should be developed consistent with EPA's current recommended
models under Appendix W to 40 CFR Part 51. The purpose of recommending a
particular model is to ensure that the best-performing methods are used in assessing PM
impacts from a particular project and are employed in a consistent fashion.79 Exhibit 7-2
summarizes the recommended air quality models for PM hot-spot analyses for required
projects under 40 CFR 93.123(b)(l).
Exhibit 7-2. Summary of Recommended Air Quality Models
Type of Project
Highway and intersection projects
Transit, freight, and other terminal projects
Projects that involve both highway/intersections
and terminals, and/or nearby sources*
Recommended Model
AERMOD, CAL3QHCR
AERMOD
AERMOD
* Note that "nearby sources" refers to those sources that (1) are not part of the project but are affected by
the project or (2) are sources in the project area whose emissions are not adequately captured by the
selected background concentrations. See Section 8.2 for more information.
The American Meteorological Society/EPA Regulatory Model (AERMOD) is EPA's
recommended near-field dispersion model for many regulatory applications. EPA
recommended AERMOD in a November 9, 2005 final rule that amended EPA's
"Guideline on Air Quality Models" after more than ten years of development and peer
review that resulted in substantial improvements and enhancements.80 AERMOD
includes options for modeling emissions from volume, area, and point sources and can
therefore model the impacts of many different source types, including highway and
transit projects. In addition, EPA conducted a study to evaluate AERMOD and other air
quality models in preparation for developing this guidance and the study supported
The best performing model is one that best predicts regulatory design values for a particular pollutant.
EPA's "Protocol for Determining the Best Performing Model" (EPA-454/R-92-025) defines operational
and statistical criteria for this evaluation. According to the document: "For a pollutant... for which short-
term ambient standards exist, the statistic of interest involves the network-wide highest concentration... the
precise time, location, and meteorological condition is of minor concern compared to the magnitude of the
highest concentration actually occurring."
80 The final rule can be found at: www.epa.gov/scramOOl/guidance/guide/appw_05.pdf. Extensive
documentation is available on EPA's SCRAM website describing the various components of AERMOD,
including user guides, model formulation, and evaluation papers. See:
www. epa. go v/scramOO 1 /dispersion_prefrec. htm#aermod.
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AERMOD's use.81 To date, AERMOD has already been used to model air quality near
roadways, other transportation sources, and other ground-level sources for regulatory
applications by EPA and other federal and state agencies.82
CAL3QHCR is an extension of the CAL3QHC model, which is the model recommended
for use in analyzing CO impacts from intersections.83 In addition, CAL3QHCR
incorporates enhancements to process up to a year of meteorological data and emissions
data that vary by day of week and hour of day. It is appropriate to use CAL3QHCR for
PM hot-spot modeling for specified projects; however, its queuing algorithm should not
be used.
Both the AERMOD and CAL3QHCR models (and related documentation) can be
obtained through EPA's SCRAM website. OAQPS maintains the SCRAM website and
maintains, codes, and supports AERMOD on an ongoing basis. Modelers should
regularly check this website to ensure use of the latest regulatory version. CAL3QHCR
is not maintained by EPA and is no longer updated; therefore, technical support for the
model code is not available through OAQPS. However, EPA will provide technical
support for implementing AERMOD and the current version of CAL3QHCR for PM hot-
spot analyses completed with this guidance.
Appendix J includes important additional information about configuring AERMOD and
CAL3QHCR when using these models to complete PM hot-spot analyses. In the future,
it is possible that other recommended models will become available.
Highway and Intersection Projects
Some projects may consist exclusively of highways and intersections, with little or no
emissions coming from extended idling, non-road engine operations, or modeled nearby
sources (see more below). Both AERMOD and CAL3QHCR are recommended air
quality models for these types of projects.84 When using CAL3QHCR for such highway
and intersection projects, its queuing algorithm should not be used. As discussed in
Sections 4 and 5, as well as in Appendix D, idling vehicle emissions should instead be
Hartley, W. S.; Can, E.L.; Bailey, C.R. (2006). Modeling hotspot transportation-related air quality
impacts using ISC, AERMOD, and HYROAD. Proceedings of Air & Waste Management Association
Specialty Conference on Air Quality Models.
For example, EPA used AERMOD to model concentrations of nitrogen dioxide (NO2) as part of the 2008
Risk and Exposure Assessment for revision of the primary NO2 NAAQS. Also, other agencies have used
AERMOD to model PM and other concentrations from roadways (represented as a series of area sources)
for purposes of NEPA and CAA analyses.
83 CAL3QHC is a CALINE3-based screening model with a traffic model to calculate delays and queues at
signalized intersections; CAL3QHCR is a refined model based on CAL3QHC that requires local
meteorological data. The CAL3QHCR's User Guide ("User's Guide to CAL3QHC Version 2.0: A
Modeling Methodology for Predicting Pollutant Concentrations Near Roadway Intersections") can be
found at: www.epa.gov/scram001.
84 Appendix W to 40 CFR Part 51 describes both AERMOD and CAL3QHCR as being appropriate for
modeling line sources. For further background, see Sections 3.0, 4.0, 5.0, and 8.0 of Appendix W, as well
as Appendix A to Appendix W of 40 CFR Part 51.
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accounted for by properly specifying links for emission analysis and reflecting idling
activity in the activity patterns used for MOVES or EMFAC modeling.
Note: Users should be aware that, to handle quarterly emissions and multiple years of
meteorological data, AERMOD and CAL3QHCR need different numbers of input files
and runs. AERMOD can handle quarterly variations in emissions and multiple years of
meteorological data using a single input file and run. In contrast, CAL3QHCR can
handle only one quarter's emissions and one year of meteorological data at a time. See
further information in Section 7.5.3.
Transit and Other Terminal Projects
Other projects may include only transit or freight terminals and transfer points where a
large share of total emissions arise from engine start and idling emissions or from non-
road engine activity. AERMOD is the recommended air quality model for these types of
projects.
Projects that Involve Both Highway/Intersection and Terminal Projects, and/or Nearby
Sources
There may be some projects that are a combination of the "highway and intersection" and
"transit and freight terminal" project types. AERMOD is the recommended model for
these projects. As a general recommendation, if AERMOD is used for modeling any
source associated with the project, it should be the only air quality model used for the PM
hot-spot analysis.85 There may be other cases where the project area also includes a
nearby source that is affected by the project, and as a result, needs to be modeled to
account for background concentrations around the project (e.g., locomotives at a nearby
freight terminal or marine port). In these cases, AERMOD should be used for the project
and any such nearby sources. In general, it should be unnecessary to include nearby
sources in air quality modeling if they are not affected by the project (assuming the
impacts of such sources are adequately accounted for in the selected representative
background concentrations). See Section 8.2 for further information on nearby sources.
There are several reasons for this recommendation. First, AERMOD is flexible in how different sources
are represented, while CAL3QHCR represents all sources as "line sources" (see Section 7.3.2). Second,
AERMOD allows a much wider number of receptors and sources to be modeled simultaneously, which is
useful for large projects with different source configurations. Third, AERMOD's treatment of dispersion in
the lower atmosphere is based on more current atmospheric science than CAL3QHCR. Furthermore, the
use of a single model, rather than multiple models, is recommended to avoid the need to run the same
meteorological data through different preprocessors (AERMET, MPRM), avoid different receptor networks
for different sources, reduce the number of atmospheric modeling runs required to analyze a project, avoid
the use of different modeling algorithms that perform the same task, and reduce double-counting or other
errors.
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7.3.2 How emissions are represented in CAL3QHCR and AERMOD
Both CAL3QHCR and AERMOD simulate how pollutants disperse in the atmosphere.
To do so, the models classify emission sources within a project as line, volume, area, and
point sources:
• Line sources are generally linear emission sources, which can include highways,
intersections, and rail lines. They are directly-specified in the CAL3QHCR input
file using road link coordinates. AERMOD can simulate a highway "line source"
using a series of adjacent volume or area sources (see the AERMOD User Guide
and the AERMOD Implementation Guide for suggestions).86
• Volume sources (used in AERMOD only) are three-dimensional spaces from
which emissions originate. Examples of sources that could be modeled as volume
sources include areas designated for truck or bus queuing or idling (e.g., off-
network links in MOVES), driveways and pass-throughs in bus terminals, and
locomotive activity at commuter rail or freight rail terminals.87
• Area sources (used in AERMOD only) are flat, two-dimensional surfaces from
which emissions arise (e.g., parking lots).
• Point source emissions (used in AERMOD only) emanate from a discrete location
in space, such as a bus garage or transit terminal exhaust stack.
Each of these source types may be appropriate for representing different sources in a PM
hot-spot analysis. For example, highways may be modeled as line sources in
CAL3QHCR, but they may also be modeled as a series of adjoining volume or area
sources in AERMOD, as described below. Using another example, an exhaust vent from
a bus garage might be best represented as a point source, area source, or volume source,
depending on its physical characteristics. Project sponsors should consult with the most
recent user guides for air quality models to determine the most appropriate way to
represent a particular source within a model. Appendix J includes additional specific
information for modeling highway and transit projects.
7.3.3 Alternate models
In limited cases, an alternate model for use in a PM hot-spot analysis may be considered.
As stated in Section 3.2 of Appendix W, "Selection of the best techniques for each
individual air quality analysis is always encouraged, but the selection should be done in a
consistent manner." This section of Appendix W sets out objective criteria by which
alternate models may be considered.
Analyses of individual projects are not expected to involve the development of new air
quality models. However, should a project sponsor seek to employ a new or alternate
model for a particular transit or highway project, that model must address the criteria set
forth in Section 3.2 of Appendix W. Determining model acceptability in a particular
86 The AERMOD Implementation Guide is updated on a periodic basis. The latest version is posted on the
SCRAM web site at: www.epa.gov/ttn/scram/dispersion_prefrec.htm#aermod.
87 See Appendix I for information on estimating locomotive emissions.
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application is an EPA Regional Office responsibility involving consultation with EPA
Headquarters, when appropriate.
7.4 CHARACTERIZING EMISSION SOURCES
Characterizing sources is the way in which the transportation project's features and
emissions are represented within an air quality model. In order to determine the
concentrations downwind of a particular emission source, an air quality model needs to
have a description of the sources, including:
• Physical characteristics and location;
• Emission rates/emission factors; and
• Timing of emissions.
There may be several different emission sources within the project area. Sections 4 and 5
describe how a project can be characterized into different links, which will each have
separate emission rates to be used in air quality modeling. Sections 6 and 8.2 outline how
nearby source emissions, when present, can be characterized to account for emissions
throughout the project area. Properly characterizing all of these distinct sources within
the PM hot-spot analysis will help ensure that the locations with the greatest impacts on
PM air quality concentrations are identified.
This section describes the major elements needed to characterize a source properly for
use in an air quality model.
7.4.1 Physical characteristics and location
When modeling an emission source, its physical characteristics and location need to be
described using the relevant model's input format, as described in the appropriate user
guide. Sources with the same emission rate but with different physical characteristics
may have different impacts on predicted concentrations.
Refer to Appendix J of this guidance and to the user guides for CAL3QHCR and
AERMOD for specific information about how physical characteristics and location of
sources are included in these models.
In addition, for emissions on or near rooftops, such as those from exhaust stacks on
transit or other terminal projects, building downwash can result in higher concentrations
on the downwind side of nearby buildings than would otherwise be present.88 Consult
Appendix J for guidance on when to include building downwash for these projects when
using AERMOD.
88 Building downwash occurs when air moving over a building mixes to the ground on the downwind side
of the building.
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7.4.2 Emission rates/emission factors
The magnitude of emissions within a given time period or location is a necessary
component of dispersion modeling. For motor vehicles, MOVES-based emission rates
are required in all areas other than the state of California, where EMFAC-based emission
rates are required, as described in Sections 4 and 5, respectively. For road and
construction dust, emission factors from AP-42 or a local method are required, as
described in Section 6. For nearby sources, the appropriate emission rates should also be
estimated, as described in Sections 6 and 8.2.
CAL3QHCR and AERMOD accept emission rates in different formats. For highways
and intersections, CAL3QHCR needs emissions to be specified in grams/vehicle-mile
traveled (grams/mile).89 AERMOD needs emission rates in grams/hour (or
grams/second). When employing area sources with AERMOD (e.g., parking lots),
emission rates must be specified in grams/second per unit area.
7.4.3 Timing of emissions
The proper description of emissions across time of year, day of week, and hour of day is
critical to the utility of air quality modeling.90 Sections 4 and 5 describe how to account
for different periods of the day in emissions modeling with MOVES and EMFAC. This
approach is then applied to air quality modeling to estimate air quality concentrations
throughout a day and year. As described in Section 3.3.4, air quality modeling for the
annual PM2 5 NAAQS would involve data and modeling for all four quarters of the
analysis year; air quality modeling for the 24-hour PM NAAQS may involve all four
quarters, or one quarter in certain circumstances.
Sections 4 and 5 and Appendix J describe how results from MOVES and EMFAC should
be prepared for use as inputs in both AERMOD and CAL3QHCR.
7.5 INCORPORATING METEOROLOGICAL DATA
7.5.1 Finding representative meteorological data
One of the key factors in producing credible results in a PM hot-spot analysis is the use
of meteorological data that is as representative as possible of the project area.
Meteorological data are necessary for running either AERMOD or CAL3QHCR because
meteorology affects how pollutants will be dispersed in the lower atmosphere. The
following paragraphs provide an overview of the meteorological data needed and sources
of this data. More detailed information can be found in Appendix J and in model user
89 CAL3QHCR uses the hourly volume of vehicles on each road link and the emission factor (in
grams/mile) for the vehicles on each link to calculate time-specific emission rates for use in air quality
modeling. As described in Sections 4 and 5, the idle emission factor inputs in CAL3QHCR should not be
used in a PM hot-spot analysis.
90 The timing of emissions in AERMOD is described in Section 3.3.5 of the AERMOD User Guide.
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and implementation guides. EPA's SCRAM web site also contains additional
information, including additional guidance, archived meteorological data (which may be
suitable for some analyses), and links to data sources.
Meteorological data is used by air quality dispersion models to characterize the extent of
wind-driven (mechanical) and temperature-driven (convective) mixing in the lower
atmosphere throughout the day.91 For emissions near the ground, as is common in
transportation projects, dispersion is driven more by mechanical mixing, but temperature-
driven mixing can still have a significant impact on air quality. As a source's plume
moves further downwind, temperature-driven mixing becomes increasingly important in
determining concentrations.
Depending on the air quality model to be used, the following types of information are
needed to characterize mechanical and convective mixing:
• Surface meteorological data, from surface meteorological monitors that measure
the atmosphere near the ground (typically at a height of 10 meters—see Section
7.5.2);
• Upper air data on the vertical temperature profile of the atmosphere (see Section
7.5.2);
• Data describing surface characteristics, including the surface roughness, albedo,
and Bowen ratio (see Section 7.5.4); and
• Population data to account for the "urban heat island effect" (see Section 7.5.5).
Project sponsors may want to first consult with their respective state and local air quality
agencies for any representative meteorological data for the project area. In addition,
some state and local air agencies may maintain preprocessed meteorological data suitable
for use in PM hot-spot analyses. Interagency consultation can be used to determine
whether preprocessed meteorological data are available, which could reduce time and
resources for PM hot-spot analyses.
To format meteorological data appropriately and prepare them for use in air quality
Q9
models, EPA maintains meteorological processing software on the SCRAM website.
These programs produce input data files that the air quality models read to produce
calculations of atmospheric dispersion. AERMOD and CAL3QHCR employ different
meteorological preprocessing programs. AERMET is the meteorological preprocessor
for AERMOD. The Meteorological Processor for Regulatory Models (MPRM) program
is the meteorological preprocessor for CAL3QHCR. User guides for both AERMET and
MPRM should be consulted for specific instructions.
The meteorological data used as an input to an air quality model should be selected on the
basis of geographic and climatologic representativeness and how well measurements at
91 Mechanical turbulence arises when winds blow across rough surfaces. When wind blows across areas
with greater surface roughness (roughness length), more mechanical turbulence and mixing is produced.
Temperature-driven mixing is driven by convection (e.g., hot air rising).
92 These programs and their user guides may be downloaded from the SCRAM website at:
www.epa.gov/scramOO 1 /metobsdata procaccprogs.htm.
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one site represent the likely transport and dispersion conditions in the area around the
project. The representativeness of the data depends on factors such as:
• The proximity of the project area to the meteorological monitoring site;
• The similarity of the project area to the meteorological monitoring site in surface
characteristics (particularly surface measurements);
• The time period of data collection;
• Topographic characteristics within and around the project area; and
• Year-to-year variations in weather conditions (hence, a sufficient length of
meteorological data should be employed, as discussed in Section 7.5.3 and
Appendix J).
The AERMOD Implementation Guide provides up-to-date information and
recommendations on how to judge the representativeness of meteorological data.93
Modelers should consult the most recent version of the AERMOD Implementation Guide
for assistance in obtaining and handling meteorological information. Although intended
for users of AERMOD, its recommendations for how to assess the representativeness of
meteorological data apply to analyses employing CALSQHCRas well.
7.5.2 Surface and upper air data
Surface Data
Air quality models need representative meteorological data from a near-ground surface
weather monitoring station ("surface data"). Models have minimum needs for surface
observations. For example, when using National Weather Service (NWS) data to
produce meteorological input files for AERMOD, the following surface data
measurements are needed:
• Wind vector (speed and direction);
• Ambient temperature; and
• Opaque sky cover (or, in the absence of opaque sky cover, total sky cover).
Station barometric pressure is recommended, but not needed (AERMET includes a
default value in the absence of such data).
When processing data using MPRM for use in CAL3QHCR, information on stability
category is also needed. MPRM estimates stability internally. Alternatively, when using
NWS data, the calculation needs:
• Wind speed and direction;
• Ceiling height; and
• Cloud cover (opaque or total).
For details, refer to the AERMET or MPRM user guides on the SCRAM website.94
93 See www.epa.gov/scram001/dispersion_prefrec.htm#aermod.
94 See www.epa.gov/scram001/metobsdata_procaccprogs.htm.
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Upper Air Data
Upper air soundings measure gradients of vertical temperature in the atmosphere. The
vertical temperature gradients of the lower atmosphere are used by air quality models to
calculate convective mixing heights. Models need upper air sounding data from a
representative measurement site. For AERMOD, consult the AERMOD Implementation
Guide for specific recommendations. For CAL3QHCR, consult the MPRM user guide.
Obtaining Surface and Upper Air Meteorological Data
Meteorological data that is most representative of the project area should always be
sought. Meteorological data that can be used for air quality modeling are routinely
collected by the NWS. Other organizations, such as the FAA, local universities, military
bases, industrial facilities, and state and local air agencies may also collect such data.
Project sponsors may also choose to collect site-specific data for use in PM hot-spot
analyses, but it is not necessary to do so. If site-specific data are used, it should be
obtained in a manner consistent with EPA guidance on the topic.95
There are several locations where such data can be obtained. The National Oceanic and
Atmospheric Administration's National Climatic Data Center (NCDC) contains many
years of archived surface and upper air data (www. ncdc. noaa. gov) from NWS and other
sources. In addition, EPA's SCRAM web site contains archived surface and upper air
data from several sources, including NWS, as well as internet links to other data sources.
Some states can provide processed meteorological data for use in regulatory air quality
modeling applications. Other local agencies and institutions may also provide
meteorological data, as described above.
7.5.3 Time duration of meteorological data record
PM hot-spot analyses can be based on either off-site or site-specific meteorological data.
When using off-site data, five consecutive years of the most recent representative
meteorological data should be used.96 Meteorological data files that have been
preprocessed by the relevant state or local air agency may be used, when appropriate. If
meteorological data are collected on the project area prior to analysis, at least one year of
site-specific data is needed. Consult Section 8.3.1 of Appendix W for additional
explanation.
AERMOD and CAL3QHCR have different capabilities for modeling meteorological
data, as illustrated in Exhibit 7-3 (following page). The numbers in the exhibit pertain to
each analysis year and build or no-build scenario analyzed.
95 See Section 8.3.3 in Appendix W to 40 CFR Part 51 ("Site Specific Data") and the "Monitoring
Guidance for Regulatory Modeling Applications" (www.epa.gov/scram001/metguidance.htm'). Other
meteorological guidance documents are also available through SCRAM, including procedures for
addressing missing data and for quality assuring meteorological measurements.
96 As noted above, meteorological data are available through the NCDC website. Meteorological data are
continuously collected by NWS from sources such as airports. Five years of meteorological data are also
routinely used in other dispersion modeling applications.
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Exhibit 7-3. Air Quality Model Capabilities for Meteorological Data for Each
Scenario
Type of Air
Quality Model
AERMOD
CAL3QHCR
Number of Runs with 5
Years of Off-Site
Meteorological Data
1-5
20
Number of Runs with 1 Year
of Site-Specific
Meteorological Data
1
4
AERMOD can model either five years of representative off-site meteorological data (e.g.,
from NWS) or one year of site-specific data in a single run, since the model handles
different emissions within a year and multiple years of meteorological data with a single
input file. This requires a user to externally join meteorological data files before
preprocessing them with AERMET. Alternatively, AERMOD can be run five times, with
one year of meteorological data processed per run.
CAL3QHCR needs different input files for each quarter that is modeled using MOVES or
EMFAC, since CAL3QHCR does not distinguish between emission changes due to
seasonal differences. If site-specific data are collected, CAL3QHCR needs to be run only
four times, once for each quarter. If off-site data are used (e.g., from NWS), modeling
five years of consecutive meteorological data involves five runs of CAL3QHCR for each
quarter, which results in 20 runs for all four quarters.
7.5.4 Considering surface characteristics
In addition to surface and upper air meteorological data, three surface characteristics for
the site of meteorological monitoring are needed for air quality modeling, depending on
the model used:
• The surface roughness length (z0), which indicates how much the surface features
at a given site (e.g., buildings, trees, grass) interrupt a smooth-flowing wind;
• Albedo (r), which is the amount of solar radiation reflected by the surface; and
• Bowen ratio (B0), which indicates how much heat the ground imparts to the air,
instead of evaporating moisture at the surface.
AERMOD and AERMET make use of these parameters directly. CAL3QHCR and
MPRM do not need data on surrounding surfaces' albedo or Bowen ratio for modeling
ambient PM concentrations, but surface roughness is an input to CAL3QHCR.97 As
described above, surface characteristics are also used to assess a meteorological
monitor's representativeness.
The AERMOD Implementation Guide should be consulted for the latest information on
processing land surface data, when using either AERMOD or CAL3QHCR. Although its
recommendations are intended for AERMOD, they also apply to CAL3QHCR with
97 As described in Section 4.2 of its user guide, MPRM makes use of surface roughness in calculating
stability categories.
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meteorological data processed by MPRM.98 More detailed information about each of
these characteristics is found in Appendix J.
Sources of data that can be used to determine appropriate surface characteristics include
printed topographic and land use/land cover (LULC) maps available from the U. S.
Geological Survey (USGS), aerial photos from web-based services, site visits and/or site
photographs, and digitized databases of LULC data available from USGS. For specific
transportation projects, detailed nearby LULC data may be developed as part of project
design and engineering plans. Furthermore, some MPOs have adopted modeling
techniques that estimate the land use impacts resulting from individual highway and
transit projects.
LULC data may only be available for particular years in the past. As such, planning for
modeling should consider how representative these data are for the year when
meteorological data were collected, as well as the PM hot-spot analysis year(s).
The National Land Cover Database (NLCD) is a set of satellite-based land cover
measurements that are updated periodically." As of the writing of this guidance,
versions of the NLCD have been released representing calendar years 1992 and 2001,
with five areas/states (New England, Mississippi, South Dakota, Washington, and
Southern California) being updated to reflect 2006. Consult the AERMOD
Implementation Guide for recommendations for using NLCD data when processing
meteorological data.100
In most situations, the project area should be modeled as having flat terrain. However, in
some situations a project area may include complex terrain, such that sources and
receptors included in the model are found at different heights. See Appendix J for
information on handling complex terrain in air quality modeling.
7.5.5 Specifying urban or rural sources
In addition to surface characteristics, night-time dispersion in urban areas can be greater
than in surrounding rural areas with similar surface characteristics as a result of the
"urban heat island effect."101 After sunset, urban areas cool at slower rates than
surrounding rural areas, because buildings in urban areas slow the release of heat.
Furthermore, the urban surface cover has greater capacity for storing thermal energy due
to the presence of buildings and other urban structures. As a result, the vertical motion of
urban air is enhanced through convection, a phenomenon lacking (or reduced) in rural
98 The CAL3QHCR User Guide does not address preprocessing meteorological data, which is necessary for
PM hot-spot analyses. In the absence of such information, project sponsors should rely on the AERMOD
Implementation Guide when using either dispersion model.
This database can be accessed at: www.mrlc.gov.
100 The AERSURFACE model, a non-regulatory component of AERMOD, may also be used to generate
information on surface roughness, albedo, and Bowen ratio. As of this writing, AERSURFACE is based on
the 1992 NLCD. The latest version of AERSURFACE may be accessed via SCRAM
(www. epa. gov/scramOO 1 /).
101 The MPRM User Guide refers to the "urban heat island effect" as "anthropogenic heat flux."
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areas. The magnitude of the urban heat island effect is driven by the urban-rural
temperature difference that develops at night.
The implications for highway and transit projects are that the same emissions in a rural
area will undergo less dispersion than the same source in an urban area, all other factors
(e.g., surface characteristics, meteorology) being equal. For the purposes of a hot-spot
analysis, then:
• In urban areas, sources should generally be treated as urban.
• In isolated rural nonattainment and maintenance areas (as defined by 40 CFR
93.101), sources should be modeled as rural.
• Near the edge of urban areas, additional considerations apply that should be
addressed through the interagency consultation process.102
Modeling sources as urban or rural can have a large impact on predicted concentrations.
Both AERMOD and CAL3QHCR can account for the urban/rural differences in
dispersion. When sources are modeled as urban in AERMOD, the urban area's
population is a necessary input.
For projects near or beyond the edge of an urbanized area, there may be situations where
the build and no-build scenarios result in different degrees of urbanization. In these
situations, sources in the build scenario might be treated as urban, while in the no-build
they are treated as rural. Local data on such cases may not be universally available,
although some planning agencies have adopted models that may allow the impacts of
projects on population growth to be described. Given the potentially large impact of
modeling sources as either urban or rural, all available information on population growth
in the greater area around the project should be used when modeling projects near or
beyond the edge of an urbanized area.
When using AERMOD, consult the latest version of the AERMOD Implementation
Guide for additional information, including instructions on what type of population data
should be used in making urban/rural determinations. When using CAL3QHCR, consult
Section 7.2.3 of Appendix W for guidance on determining urban sources. Refer to
Appendix J for additional information on how to handle this data for each model.
102 Since the urban heat island is not a localized effect, but regional in character, Section 7.2.3 of Appendix
W recommends that all sources within an "urban complex" be modeled as urban.
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7.6 PLACING RECEPTORS
Note: Section 7.6 has been revised in accordance with EPA 's 2012 PMNAAQSfinal rule
that was published on January 15, 2013 (78 FR 3264) m
7.6.1 Overview
Receptors for conformity purposes are locations in the project area where an air quality
model estimates future PM concentrations. Section 93.123(c)(l) of the conformity rule
requires PM hot-spot analyses to estimate air quality concentrations at "appropriate
receptor locations in the area substantially affected by the project." An "appropriate
receptor location" is a location that is suitable for comparison to the relevant PM
NAAQS, consistent with how the PM NAAQS are established and monitored for air
quality planning purposes.104
The paragraphs below provide general guidance for placing receptors for all PM
NAAQS. Placing receptors should take into account project emissions as well as any
modeled nearby sources. Project sponsors should place receptors in the project area for
the relevant NAAQS consistent with applicable requirements. Evaluating and choosing
the models and associated methods and assumptions for placing receptors must be
completed through the process established by each area's interagency consultation
procedures (40 CFR 93.105(c)(l)(i)). State and local air quality agencies have significant
expertise in air quality planning for the PM NAAQS that may be relevant for PM hot-
spot analyses.
Receptors can be placed for PM2 5 hot-spot analyses consistent with EPA's general
guidance for any air quality modeling, as described below; there are no longer special
considerations for receptor placement for either the 24-hour or annual PM2.5 NAAQS.105
As a result, EPA has revised Section 7.6 of this guidance document to remove the
previous additional guidance for placing receptors for hot-spot analyses involving either
PM2.5 NAAQS. In addition, EPA has revised Section 9.4 for determining appropriate
receptor locations for the annual PM2.5 NAAQS.106
EPA committed to "review whether there is a need to issue new or revised transportation conformity
guidance in light of this final rule." (78 FR 3264) EPA is fulfilling this commitment through this guidance
revision. The previous version of Section 7.6 was issued in December 2010, EPA-420-B-10-040.
CAA section 176(c)(l)(B) requires that transportation activities do not cause or contribute to new
NAAQS violations, worsen existing NAAQS violations, or delay timely attainment of the NAAQS or
interim milestones in the project area. EPA interprets "NAAQS" in this provision to mean the specific
NAAQS that has been established through rulemaking.
The previous PM2.5 monitoring regulations required that air quality monitors for the 24-hour and annual
PM2.5 NAAQS be placed at "population-oriented" locations. This requirement was eliminated from the
monitoring regulations under the 2012 PM NAAQS final rule, and as a result, this is no longer a
consideration for placing receptors for hot-spot analyses for either PM2.5 NAAQS.
106 The 2012 PMNAAQS final rule also resulted in receptors for the annual PM25 NAAQS needing to
represent "area-wide" locations, rather than the previous "community-wide air quality" requirement.
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7.6.2 General guidance for receptors for all PMNAAQS
Section 7.2.2 of Appendix W to 40 CFR Part 51 provides guidance on the selection of
critical receptor sites for refined analyses, and recommends that receptor sites be placed
in sufficient detail to estimate the highest concentrations and possible violations of a
NAAQS. The selection of receptor sites for all PM NAAQS should be determined on a
case-by-case basis taking into account project-specific factors that may influence areas of
expected high concentrations, such as prevailing wind directions, monitor locations,
topography, and other factors. In designing a receptor network (e.g., the entire coverage
of receptors for the project area), the emphasis should be placed on resolution and
location, not the total number of receptors. Design of the receptor network should also
consider whether any locations within the project area should be excluded from the
modeling based on a location being restricted from public access or where a member of
the public would normally be present only for a very short period of time. Examples
include locations within a fenced property of a business, a median strip of a highway, a
right-of-way on a limited access highway, or an approach to a tunnel.
As described in Appendix W, air quality dispersion models are more reliable for
estimating the magnitude of highest concentrations somewhere within a specified area
and span of time than in predicting concentrations at a specific place and time.
Therefore, receptors should be sited at all locations at which high concentrations may
occur, rather than simply focusing on the expected worst case location.
Receptor spacing in the vicinity of the source should be of sufficient resolution to capture
the concentration gradients around the locations of maximum modeled concentrations.
The majority of emissions from a highway or transit project will occur within several
meters of the ground, and concentrations are likely to be greatest in proximity of near-
ground sources. As such, receptors should be placed with finer spacing (e.g., 25 meters)
closer to a near-ground source, and with wider spacing (e.g., 100 meters) farther from
such a source. While prevailing wind directions may influence where maximum impacts
are likely to occur, receptors should also be placed in all directions surrounding a project.
It should not be assumed that the location of maximum concentration will always be
located closest to the project itself. For example, if a highway project consists of a new
bypass that branches off an existing highway with significant emissions, maximum
concentrations may be expected at receptors farther from the project, but closer to the
existing highway.
Receptors should be sited as near as five meters from a source (e.g., the edge of a traffic
lane or a source in a terminal), except possibly with projects involving urban street
canyons where receptors may be appropriate within 2-10 meters of a project.107 In
Although this is not a consideration for placing receptors, it is relevant for interpreting design values for the
annual PM25 NAAQS for cases involving unique locations, as described further in Section 9.4.
107 See 40 CFR Part 58, Appendix D, Section 4.7. l(c)(l); Appendix E, Section 6.3(b) and Table E-4. The
interagency consultation process should be used to determine when these provisions are relevant for a given
analysis.
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addition, if AERMOD is used to create a standardized receptor network (e.g., using
AERMOD's Cartesian or polar grid functions), receptors may inadvertently be placed
within five meters of a project, and subsequently modeled. Such receptors should not be
used when calculating design values in most cases.
Receptors should be placed to capture the impacts of the project and any nearby source
that needs to be modeled. Receptor placement should be extended out to a sufficient
distance from sources to account for emissions that affect concentrations throughout the
project area, depending on the spatial extent of the project and the impacts of other
modeled sources.
EPA recommends that receptors should be sited to represent concentrations near-ground
level, generally at a height of 1.8 meters above grade or less. Receptors should also be
placed at higher elevations if needed to represent concentrations at several heights along
multi-story buildings, such as apartment or office buildings.
When completing air quality modeling for build and no-build scenarios, receptors should
be placed in the same geographic locations in both scenarios so that direct comparisons
can be made between the design values calculated at each receptor. Receptors are first
determined based on the build scenario, and then placed in the same locations in the no-
build scenario (when this scenario is modeled). See Section 9 for further information
regarding calculating design values in a build/no-build analysis and appropriate receptors.
7.7 RUNNING THE MODEL AND OBTAINING RESULTS
After preparing all model inputs, the air quality model should be run to predict
concentrations. Next, background concentrations need to be determined, as described in
Section 8. Finally, the resulting concentrations at receptors should be combined with
background concentrations from other sources to calculate design values, as described in
Section 9.
Note that, before the results of either AERMOD or CAL3QHCR are ready for use in
calculating design values and determining conformity, the data will have to undergo
some post-processing, depending on how the data was run in the models and the NAAQS
being evaluated. See Appendix J for more details.
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Section 8: Determining Background Concentrations from
Nearby and Other Emission Sources
8.1 INTRODUCTION
This section describes how to determine background concentrations for PM hot-spot
analyses. Section 93.123(c)(l) of the conformity rule states that "estimated pollutant
concentrations must be based on the total emissions burden which may result from the
implementation of the project, summed together with future background
concentrations...." Background concentrations do not include the emissions from the
project itself108 Instead, background concentrations for PM hot-spot analyses involve:
• Nearby sources: These are individual sources other than the highway or transit
project that contribute to ambient concentrations in the project area. Some nearby
sources may be included in the air quality modeling for PM hot-spot analyses,
while other nearby sources can be reflected in representative background
concentrations. In general, nearby sources would be included in air quality
modeling only when those sources would be affected by the project; and
• Other sources: This term is intended to capture the background concentrations in
the project area that are not from the project or any nearby sources that are
modeled.
Further information is provided in Section 8.2 on when to include nearby sources in air
quality modeling and in Section 8.3 on how to include the impact of other sources of
emissions in a future analysis year. It is important to note that nearby sources may only
be present for some PM hot-spot analyses.
This section is consistent with EPA's "Guideline on Air Quality Models" (Appendix W
to 40 CFR Part 51), which provides the appropriate framework for defining the elements
of background concentrations. Section 8.2.1 of Appendix W states that "background
concentrations are an essential part of the total air quality concentration to be considered
in determining source impacts."109 Concentrations are expected to vary throughout a PM
nonattainment or maintenance area, resulting from differences in emission sources,
meteorology, terrain, and other factors. EPA believes that meeting Section 93.123(c)(l)
requirements for PM hot-spot analyses will be different from what has occurred
historically for CO hot-spot analyses, due to the fundamental differences between the
contributors to PM and CO pollution and the projects that are required to have
quantitative PM and CO hot-spot analyses. Additional information is provided in Section
8.3 of this guidance.
108 See Sections 4 through 6 for more information on how to estimate project emissions.
109 Section 8.2.3 recommends for "multi-source areas" that "two components of background should be
determined: contributions from nearby sources and contributions from other sources."
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Evaluating and choosing the models and associated methods and assumptions for nearby
sources and representative background concentrations must be completed through the
process established by each area's interagency consultation procedures (40 CFR
State and local air quality agencies will have the primary expertise on what emission
sources are expected to affect background concentrations, including any nearby sources.
The state or local air agency is likely to have an understanding of the project area and
knowledge about information needed to characterize background concentrations
appropriately, due to experience in developing air quality demonstrations, emission
inventories, and siting air quality monitors for a given NAAQS. The EPA Regional
Office is also a key resource for discussions regarding the air quality monitoring network,
SIP modeling, and other issues.
8.2 NEARBY SOURCES THAT REQUIRE MODELING
Nearby sources are individual sources that contribute PM concentrations to the project
area.110 In general, nearby sources need to be included in air quality modeling only when
those sources would be affected by the project. An example of a project that could affect
nearby sources would be a highway project whose primary purpose is to accommodate
future growth in freight and goods movement; such a project could affect emissions from
related activity at nearby marine ports, rail yards, or intermodal facilities. These types of
nearby sources (that is, those affected by the project) need to be included in air quality
modeling for the PM hot-spot analysis, as described in Section 7, because their emissions
will change between build and no-build scenarios.
EPA anticipates that most PM hot-spot analyses will not involve modeling of nearby
sources that are not affected by the project, such as a stationary source, since these types
of nearby sources would typically be captured in the representative background
concentrations described in Section 8.3.
The following questions can be used by project sponsors, the relevant state or local air
agency, the EPA Regional Office, and other members of the interagency consultation
process to identify any nearby sources that are affected by the project:
• Are there any nearby sources in the project area? If no, then the remainder of
Section 8.2 can be skipped.
• If yes, then:
o Do these sources emit significant levels of emissions that could affect PM
concentrations in the project area?
o Are emissions from any nearby sources expected to differ between the
build and no-build scenarios as a result of the project?
110 Section 8.2.3 of Appendix W describes "nearby sources" more generally as: "All sources expected to
cause a significant concentration gradient in the vicinity of the source or sources under consideration for
emission limit(s) should be explicitly modeled."
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EPA notes that there may be limited cases where nearby sources not affected by the
project would also need to be included in the modeling for a PM hot-spot analysis.
However, such cases would only occur when these sources are not captured in
background concentrations for the project area. See Section 8.3 for further information
on the factors used to determine representative background concentrations for these
cases.
For example, if a stationary source is located upwind of the project area, representative
background concentrations should include concentrations from such a source whenever
possible. As stated above, state and local air quality agencies and the EPA Regional
Office are key resources in understanding how to characterize nearby sources in PM hot-
spot analyses, including those nearby sources not affected by the project.
As discussed in Section 7.3, EPA recommends that AERMOD be used for any PM hot-
spot analyses that involve nearby sources that need to be modeled. The air quality
modeling for nearby sources that would be affected by the project must include any
reasonably expected changes in operation of the nearby source between the build and no-
build scenarios when both scenarios are necessary to demonstrate conformity. Refer to
Section 7 for more information about using AERMOD, placing receptors, and other
information for air quality modeling.
Specific information on emissions from nearby sources should be obtained. The state and
local air agency should be consulted on characterizing nearby sources. In addition,
emission rates and other parameters of nearby sources should be consistent with any
permits approved by the state or local air agency, when applicable. For unpermitted
sources, emission information should be consistent with information used by air agencies
for developing emission inventories for regulatory purposes. Sections 8.1 and 8.2 of
Appendix W describe the information needed to characterize the emissions of nearby
sources for air quality models. For the 24-hour PM2.5 and PMio NAAQS, it is also
important to consider Section 8.2.3 of Appendix W, which states that it is appropriate to
"model nearby sources only during those times when they, by their nature, operate at the
same time as the primary source(s) being modeled." Finally, estimation of nearby source
impacts may take into account the effectiveness of anticipated control measures in the
SIP if they are already enforceable in the SIP.
8.3 OPTIONS FOR BACKGROUND CONCENTRATIONS
PM hot-spot analyses should also include background concentrations from "other
sources" as well as any nearby sources that are not included in modeling.1U There are
several options provided below that meet the requirements of Section 93.123(c)(l) of the
conformity rule that involve using representative air quality monitoring data. Whatever
option is selected, the same background concentrations would be used at every receptor
111 Section 8.2.3 of Appendix W defines "contributions from other sources" as "that portion of the
background attributable to all other sources (e.g., natural sources, minor sources and distant major
sources)...."
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used in the build and no-build scenarios for a PM hot-spot analysis. Additional options
for background concentrations can be considered by the EPA Regional Office, OTAQ,
and OAQPS. See Section 1.7 for contact information.
8. 3. 1 Using ambient monitoring data to estimate background concentrations
Ambient monitoring data for PMio and PIVb.s provide an important source of information
to characterize the contributions from sources that affect the background concentrations
in the project area, but are not captured by air quality modeling for the PM hot-spot
analysis. Nonattainment and maintenance areas, and areas that surround them, have
numerous sites for monitoring PIVb.s and PMio concentrations that may be appropriate for
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estimating background concentrations. Project sponsors, relevant state or local air
agencies, and the EPA Regional Office should identify the appropriate PMio and PM2.5
monitoring data, along with information on each monitor's site location, purpose,
geographic scale, nearby land uses, and sampling frequency. EPA offers Air Explorer
(based on Google Earth™ mapping software) as a user-friendly way to identify and
visualize where monitoring sites are in operation and to obtain concentration data and
descriptions of the site (such as the reported scale of spatial representation). 113
The evaluation and selection of monitoring data for use in a particular analysis must
follow the process defined in each area's interagency consultation procedures. These
discussions, as well as any maps or statistical techniques used to analyze background
data, should be well-documented and included in the project-level conformity
determination.
Project sponsors should not use monitoring data for which EPA has granted data
exclusion under the Exceptional Events rule (see 40 CFR 50. 14).
Using a Single Monitor
Background concentration data should be as representative as possible for the project area
examined by the PM hot-spot analysis. 114 In most cases, the simplest approach will be to
use data from the monitor closest to and upwind of the project area. However, all of the
following factors need to be evaluated when considering monitors for use of their data as
representative background concentrations:
112 Monitors in adjacent nonattainment, maintenance, and attainment areas should also be evaluated for use
in establishing background concentrations, which may be appropriate if the air quality situation at those
monitors can be determined to be reasonably similar to the situation in the project area.
113 Available online at: www.epa.gov/airexplorer/monitor_kml.htm.
114 In particular, there should be interagency consultation prior to using any ambient monitoring data set for
PM2.5 that does not meet EPA requirements in Appendix N to 40 CFR Part 50 regarding data completeness,
and any data set that reflects a sampling schedule that has been erratic or has resulted in more frequent
samples in some seasons of a year than others. The guidance in Section 9 of this document assumes that
the normal data completeness requirement (75% of scheduled samples in each calendar quarter of each
year) has been met and that the monitoring data is evenly distributed across the year. Deviation from these
conditions may make the steps given in Section 9 inappropriate.
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• Similar characteristics between the monitor location and project area: Monitors at
locations that are similar to the project area should be preferred for this factor,
whenever possible. If several monitors are available, preference should be given to
the monitor with the most similar characteristics as the project area. Some questions
to be considered include:
o Is the density and mix of emission sources around the monitor location
similar to those around the project site?
o How well does the monitor capture the influence of nearby sources that
are not affected by the project?
o Are there differences in land use or terrain between the two locations that
could influence air quality in different ways?
o Is the monitor probe located at a similar height as the project (e.g., is the
project at grade, but the monitor is on top of a high building)?
o What is the purpose of the monitor and what geographic scale of
representation does the monitor have?
• Distance of monitor from the project area: Monitors closer to the project may have
concentrations most similar to the project area. If more than one such monitor is
available, preference may be given to the closest representative monitor for this
factor. There are some cases, however, where consideration of distance alone may
mask the influence of other factors that need to also be considered (e.g., a monitor
upwind of the project location may be preferred to an even closer monitor located
downwind of the project).
• Wind patterns between the monitor and the project area: Monitors that are located in
directions that are frequently upwind of a project are more likely to represent a
project area's background concentrations than monitors that are frequently
downwind.115 Preference should be given to upwind monitors for this factor,
whenever appropriate.
The factors considered when selecting a particular monitor to represent background
concentrations should be documented as part of the PM hot-spot analysis.
Interpolating Between Several Monitors
If, during interagency consultation, agencies conclude that no single ambient monitor is
sufficiently representative of the project area, interpolating the data of several monitors
surrounding the project area is also an option. The advantage of interpolation is that no
single monitor is used exclusively in representing air quality for a project area. There
may be projects sited in locations between large emission sources and areas several miles
away with relatively low emissions, suggesting a gradient in concentrations across the
nonattainment or maintenance area. If there are no monitors within or near the project
Constructing a "wind rose" (a graph that depicts the frequency of wind blowing from different
directions) can be a useful tool in examining the frequency of wind blowing from different directions.
EPA's SCRAM website contains two programs for calculating wind statistics and wind roses, WINDROSE
andWRPLOT.
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area, then background concentrations from other sources may be difficult to estimate.
Interpolation is an approach that allows estimates of background concentrations for a
project to take advantage of monitoring data from multiple monitoring sites. Any
planned interpolation methods must be addressed through the interagency consultation
process.
There are several approaches to interpolation that can be used. One simple method is
weighted averaging, which places greater weight on nearby monitors and uses the inverse
distance between the project site and the monitor to weight each monitor. For example,
suppose monitors A, B, and C surround an unmonitored location, at distances 5, 10, and
1 5 miles from the site, respectively, the weighting of data from monitor A:
Weight(A} = -/[- + — + — I = 0.55
5/1,5 10 15}
The weighting for monitor B:
Weight(B} = — /{- + — + — } = 0.27
V ' 10/ 1,5 10 15}
The weighting for monitor C:
If concentrations at A, B, and C are 10.0, 20.0, and 30.0 |J,g/m3, respectively, then the
predicted concentration at the unmonitored site is 16.3 |J,g/m3. In most situations, the
inverse-distance weighted average will provide a reasonable approximation of
background concentrations due to other sources. Another interpolation approach is the
inverse-squared distance weighting that weights monitors based on how close they are to
the project (I/distance squared).
Other, more advanced statistical methods to interpolate monitoring data may also be
used, but these require significant geostatistical expertise.116
116 EPA's MATS (www.epa.gov/ttn/scram/modelingapps_mats.htm') and BenMAP
(www. epa. gov/air/benmap') models incorporate another interpolation-based approach (Voronoi Neighbor
Averaging). Consult those models' documentation for further information.
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8.3.2 Adjusting air quality monitoring data to account for future changes in air quality:
using chemical transport models
Options Using Chemical Transport Models (CTMs)
To account for future emission changes, it may be appropriate in some cases to use future
background concentrations that have been calculated based on modeled outputs from a
CTM. CTMs are photochemistry models that are routinely used in regulatory analyses,
including attainment demonstrations for PM SIPs and EPA regulatory analyses to support
national or regional final rules. 117 In these types of analyses, CTM modeling is
completed for a base and future year, and then these resulting PM concentrations are used
to develop relative response factors (RRFs). These factors are then used to adjust the air
quality monitoring data from the base year of the SIP or EPA final rule modeling. The
end result will be predicted PM concentrations for monitoring locations for a future year
(e.g., the attainment year addressed in the SIP).
Although project sponsors are not expected to operate CTMs, there may be available
information from CTM modeling to support PM hot-spot analyses. There are two CTM-
based options that may be available for PM hot-spot analyses:
1. Use existing pre-calculated future year PM concentrations from EPA or state or
local air quality agency modeling. If available, the future year concentrations at a
monitor used in the SIP or EPA rulemaking can be used for a PM hot-spot
analysis, if the monitor is representative of the project area. Typically, projected
annual average and/or 24-hour average PM design values for a future year will be
available for monitoring site locations that are part of such modeling
demonstrations.
2. In some cases, site-specific, post-processed concentrations may not be readily
available from states or EPA. Depending on the nature of the modeling, it may be
possible to obtain CTM outputs that can be used to derive background
concentrations.118 This may be an option if the standard post-processed data
includes only a subset of monitoring sites in the domain or a subset of averaging
times (e.g., annual average results are available, but not 24-hour average results).
Details on the recommended procedures for projecting PM2.5 concentrations using CTMs
are contained in EPA's "Guidance on the Use of Models and Other Analyses for
Demonstrating Attainment of Air Quality Goals for Ozone, PM2.5, and Regional
Examples of commonly employed CTMs are shown on the SCRAM website at:
www.epa.gov/scram001/photochemicalindex.htm.
118 Many CTM applications are post-processed with EPA's MATS program available at:
www.epa.gov/ttn/scram/modelingapps_mats.htm . MATS produces future year annual and quarterly PM2.5
outputs for both the annual and 24-hour PM2 5 NAAQS. The quarterly concentration information may not
be routinely documented.
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Haze."119 The location where CTM modeling is completed, the location of the project,
and determining representative monitors are important considerations in using CTM-
based options for PM hot-spot analyses. Evaluating and choosing the models and
associated methods and assumptions for using CTM-based options must be determined
through interagency consultation (40 CFR 93.105(c)(l)(i)). The EPA Regional Office
should consult with OTAQ and OAQPS in applying the above options or considering
other options.
Additional Information and Considerations about CTMs
EPA's photochemical modeling guidance recommends using CTM outputs in a relative
sense. Therefore the absolute predictions of a CTM in a future analysis year are not used
to predict future background concentrations directly. Instead, appropriate future year
design values or concentrations are derived from monitoring data that have been adjusted
using the modeled relative change in PM concentrations. RRFs are calculated from the
outputs of current (base) year and future year CTM results. These RRFs reflect the
relative changes in concentrations between current and future years. 12° An RRF is
generally calculated as:
Concentrations in future year, predicted by CTM
KKr =
Concentrations in base year, predicted by CTM
Future year concentrations are then calculated by multiplying base year monitoring data
by modeled RRFs, as follows:
Base year measured concentration * RRF = Future year concentration
Additionally, when using the CTM-based options, several criteria should be met:
• The CTM has demonstrated acceptable performance for the project area using
standard indicators of model performance.121
• The results of CTM runs are appropriate for the project and future analysis year(s)
covered by the PM hot-spot analysis (e.g., the CTM modeling includes the project
area and the modeling was completed for the analysis year or a year earlier than
the analysis year).
• Any future emission reductions for sources within the CTM modeling
demonstration are based on enforceable commitments in the SIP and/or are
consistent with the conformity rule's latest planning assumptions requirements
(40 CFR 93.110).
119 See guidance for further information at: www.epa.gov/scram001/guidance/guide/final-03-pm-rh-
guidance.pdf.
120 Future year concentrations of PM2.5 are calculated based on PM2.5 species concentrations that have been
projected using RRFs for individual PM2 5 species.
121 Details on model performance evaluation and examples of model evaluation statistics may be found in
Chapter 18 and Appendix A of the document "Guidance on the Use of Models and Other Analyses for
Demonstrating Attainment of Air Quality Goals for Ozone, PM2.5, and Regional Haze," referenced above.
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• EPA or state modeling which includes future emissions reductions from a
proposed rule or hypothetical emissions reductions that are not associated with
enforceable SIP commitments or state or Federal rules should not be used.
• Any future emission reductions for sources within the CTM modeling
demonstration should take effect prior to the year(s) for which the PM hot-spot
analysis is conducted.
The PM hot-spot analysis year(s) will often be after a year for which CTM modeling is
performed. In this case, the future background concentration for the analysis year should
be the same year for which CTM modeling was performed. It is not technically justified
to extrapolate background concentrations beyond the year in which data are available for
the CTM modeling. For example, if future background concentrations were estimated
based on CTM modeling for the year 2014, and the PM hot-spot analysis year was 2016,
then the 2014 background estimate could be used for 2016. A project sponsor could not
make a further adjustment based on an extrapolation to the year 2016; such an
extrapolation would not be based on credible modeling or mathematical practices.
Similarly, emissions-based "roll-back" and "roll-forward" techniques for adjusting
current air quality monitoring data for future background concentrations are also not
technically supported and would not allow projects sponsors to meet Section 93.123(c)(l)
requirements.
Note that in some cases, CTM adjusted background predictions for a future year may
already incorporate emissions from the project's no-build scenario (e.g., if the monitor
used in the SIP modeling demonstration included emissions from the current project
area). Adding modeled concentrations for the build scenario to this value would be
essentially adding build emissions to the no-build emissions already accounted for in the
background. In these cases, an adjustment may be appropriate only when comparing the
build scenario to the NAAQS. In such cases, to evaluate predicted concentrations in the
build scenario, the difference between modeled concentrations at each receptor in the
build and no-build scenarios should be calculated as:
Difference receptori = Concentration receptori!bmldscenano - Concentration receptorijnobuildscenano
The result - the difference between the build and no-build scenarios at each receptor -
should be added to background concentrations when calculating design values for the
build scenario. Comparing a build scenario to the no-build scenario to demonstrate
conformity will not involve any similar adjustments, since the same background
concentrations are used in the build and no-build scenarios. Using this approach, only the
changes in receptor concentrations affected by emission changes from the project or
modeled nearby sources used in calculating design values. Evaluating and choosing the
models and associated methods and assumptions for using these adjustments must be
determined through interagency consultation (40 CFR 93.105(c)(l)(i)).
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8.3.3 Adjusting air quality monitoring data to account for future changes in air quality:
using an on-road mobile source adjustment factor
There may be limited cases in PMio nonattainment or maintenance areas where it would
be appropriate to adjust representative air quality monitoring data by the factor described
in Section 93.123(c)(2) of the conformity rule. This provision states that "...the future
background concentration should be estimated by multiplying current background by the
ratio of future to current traffic and the ratio of future to current emission factors." This
method has been a credible option for CO hot-spot analyses. Since CO air quality
problems are primarily due to on-road CO emissions, such a ratio is appropriate for CO
hot-spot analyses.
EPA has determined that this method may also be a credible option when on-road mobile
sources overwhelm overall PMio SIP inventories. Such a case could occur in a limited
number of PMio areas where on-road mobile emissions for directly emitted PMio
represent most of the overall directly emitted PMio emission inventory (e.g., are 75% or
more of the overall inventory).122 Such cases include smaller PMio areas where paved
and unpaved road dust are the main source of direct PMio emissions. EPA notes that this
option would increase background concentrations (as compared to options discussed in
Section 8.3.1), in cases where road dust and VMT are expected to increase in the future.
The EPA Regional Office should be consulted on a case-by-case basis if Section
93.123(c)(2) is considered for a PMio hot-spot analysis.
However, EPA has determined that the method described in Section 93.123(c)(2) is not
required by the conformity rule and is not a technically viable option for estimating
background concentrations in all PIVb.s hot-spot analyses and most PMio hot-spot
analyses. PIVb.s and PMio nonattainment problems are typically more complex and result
from many different types of emission sources, including emissions from on-road, non-
road, stationary, and area sources. It would not be appropriate to adjust PM air quality
monitoring data from all source types based on an on-road mobile source adjustment
factor only, as has been done in CO hot-spot analyses. While the conformity rule
requires CO hot-spot analyses for only the largest and most congested intersections in a
given area (40 CFR 93.123(a)(2)), PM hot-spot analyses are required for more complex
highway and transit projects that can also involve nearby sources (40 CFR 93.123(b)(l)).
For all of the above reasons, using the same ratios in most PM hot-spot analyses would
not allow project sponsors to meet Section 93.123(c)(l) requirements.
122 Precursor emissions inventories should not be considered in such a determination, since precursor
emissions are not considered in hot-spot analyses.
125
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Section 9: Calculating PM Design Values and Determining
Conformity
9.1 INTRODUCTION
This section describes how to combine all previous steps of a PM hot-spot analysis into a
design value so that a project sponsor can determine if conformity requirements are met.
For conformity purposes, a design value is a statistic that describes a future air quality
123
In
concentration in the project area that can be compared to a particular NAAQS.
general, design values are calculated by combining two pieces of data:
• Modeled PM concentrations from the project and nearby sources (Sections 7 and
8); and
• Monitored background PM concentrations from other sources (Section 8).
Exhibit 9-1 illustrates the conceptual flow of information described in this section, which
is similar for all PM NAAQS.
Exhibit 9-1. General Process for Calculating Design Values for PM Hot-spot
Analyses
Data Inputs
(from Sections 7 and 8)
f Project and /^
/ nearby source /
\ from air quality \
\^ model jx_
/ Background /
\ concentrations \
E
>etermining Conformity
(Section 9)
Combine to determine
total concentrations
i
Calculate design value(s)
1
Determine conformity
123 Design values based on monitoring data are used to determine the air quality status of a given
nonattainment or maintenance area (40 CFR Part 50). Design values are also used for SIP modeling and
other air quality planning purposes.
126
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This section describes how to calculate the specific statistical form of design values for
each PM NAAQS and how to apply design values in build/no-build analyses for
conformity purposes. This section also discusses appropriate receptors for the annual
PM2.5 NAAQS.
This guidance is consistent with how design values are calculated for designations and
other air quality planning purposes for each PM NAAQS. EPA is considering whether
spreadsheet tools can be developed to assist state and local agencies in calculating design
values for PM hot-spot analyses. This guidance is written for current and future PM2.5
and PMio NAAQS. EPA will re-evaluate the applicability of this guidance as needed, if
different PM NAAQS are promulgated in the future.
The interagency consultation process must be used to determine the models, methods,
and assumptions used for PM hot-spot analyses, including those used in calculating
design values and completing build/no-build analyses (40 CFR 93.105(c)(l)(i)). State
and local air quality agencies and EPA have significant expertise in air quality planning
that may be useful resources for the topics covered by this section. Project sponsors
should document the data and other details used for calculating design values for the
build and no-build scenarios for a project-level conformity determination, as well as how
appropriate receptors were determined in cases involving unique locations as described in
Section 9.4.
9.2 USING DESIGN VALUES IN BUILD/NO-BUILD ANALYSES
Design values are a fundamental component of PM hot-spot analyses, as they are the
values compared to the NAAQS and between build and no-build scenarios. In general, a
hot-spot analysis compares air quality concentrations with the proposed project (the build
scenario) to air quality concentrations without the project (the no-build scenario). The
conformity rule requires that the build scenario not cause or contribute to any new
violations of the NAAQS, increase the frequency or severity of existing violations, or
delay timely attainment as compared to the no-build scenario (40 CFR 93.116(a) and
93.123(c)(l)).
Exhibit 9-2 (following page) illustrates the build/no-build analysis approach suggested in
Section 2.4.
127
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Exhibit 9-2. General Process for Using Design Values in Build/No-build Analyses
Identity the receptor
with the highest
concentration and
^ih'iihilc ns iksign
value
Is design value
less than or
equal to
NAAQS?
No
Yes
Calculate build
scenario design values
at all receptors
Calculate no-build
design values at all
receptors that exceeded
NAAQS in build
Are build design
values less than or
equal to no-build
design values?
Annual PM2 5 NAAQS only*
/ Are the receptors
/ where the build
exceeds the no-
liuilfl jipproprinte
for comparison to
the NAAQS?
No
* See Section 9.4 for receptor considerations
forthe amiu.ilPM25 NAAQS in cases
involving unique receptors
** Mitigation and control measures L.MII be
considered at any point in the process
In general, project sponsors could begin by determining the design value for only one
receptor in the build scenario: the receptor with the highest modeled air quality
concentration, as described in Section 9.3. If the design value for this receptor is less
than or equal to the relevant NAAQS, it can be assumed that conformity requirements are
met at all receptors in the project area, without further analysis. If this is not the case, the
project sponsor could choose to add mitigation or control measures and then determine if
the new build scenario concentrations at the receptor with the highest modeled
concentrations is less than or equal to the relevant NAAQS. If this is not the case, the
project sponsor would calculate the design values at all receptors in the build scenario
and also model the no-build scenario. Design values should then be calculated for the no-
build scenario at all receptors with design values that exceeded the NAAQS in the build
scenario. Conformity requirements are met if the design value for every appropriate
receptor in the build scenario is less than or equal to the same receptor in the no-build
scenario.124 If not, then the project does not meet conformity requirements without
This would be the receptor at the same geographic location in the build and no-build scenarios.
128
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further mitigation or control measures to address air quality concentrations at such
receptors, except in certain cases described below.125
A build/no-build analysis is typically based on design value comparisons done on a
receptor-by-receptor basis. However, there may also be cases where a possible "new"
violation at one receptor (in the build scenario) is relocated from a different receptor (in
the no-build scenario). It would be necessary to calculate the design values for all
receptors in the build and no-build scenarios to determine whether a "new" violation is
actually a relocated violation. EPA addressed this issue in the preamble to the
November 24, 1993 transportation conformity rule (58 FR 62213), where a "new"
violation within the same intersection could be considered a relocated violation. Since
1993, EPA has made this interpretation only in limited cases with CO hot-spot analyses
where there is a clear relationship between such changes (e.g., a reduced CO NAAQS
violation is relocated from one corner of an intersection to another due to traffic-related
changes from an expanded intersection). Any potential relocated violations in PM hot-
spot analyses should be determined through the process established by each area's
interagency consultation procedures.
When completing air quality modeling for build and no-build scenarios, receptors should
be placed in identical locations so that direct comparisons can be made between design
values calculated at receptors under each scenario. Also, design values are compared to
the relevant NAAQS and between build and no-build scenarios after rounding has been
done, which occurs in the final steps of design value calculations.126 Further details on
rounding conventions for different PM NAAQS are included in Section 9.3 below.
Section 9.4 provides further information on determining appropriate receptors for the
annual PM2 5 NAAQS in cases involving unique locations.
Additional mitigation or control measures can be considered at any point in the hot-spot analysis
process. When such measures are considered, additional emissions and air quality modeling would need to
be completed and new design values calculated to ensure that conformity requirements are met.
126 For example, conformity requirements would be met at a receptor if the final build design value is no
greater than the final no-build design value, even if the pre-rounding build design value is greater than the
pre-rounding no-build design value.
129
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9.3 CALCULATING DESIGN VALUES AND DETERMINING CONFORMITY FOR
PM HOT-SPOT ANALYSES
9.3.1 General
As noted above, this conformity guidance is generally consistent with how design values
are calculated for air quality monitoring and other EPA regulatory programs.127
Further details are included below about how design values should be calculated at
receptors for build/no-build analyses, and examples of each design value calculation can
be found in Appendix K of this guidance. These details and examples are primarily
narrative in nature. EPA has also provided mathematical formulas of design values in
Appendix K, which may be helpful for certain users.
9.3.2 Annual PM2.5NAAQS
Design Value
The annual PM2 5 design value is currently defined as the average of three consecutive
years' annual averages, each estimated using equally-weighted quarterly averages.128
This NAAQS is met when the three-year average concentration is less than or equal to
the annual PM2.5 NAAQS (currently 15.0 |J,g/m3):
Annual PIVb.s design value = ([Yl] average + [Y2] average + [Y3] average) + 3
Where:
[Yl ] = Average annual PIVb.s concentration for the first year of air quality
monitoring data
[Y2] = Average annual PIVb.s concentration for the second year of air quality
monitoring data
[Y3] = Average annual PIVb.s concentration for the third year of air quality
monitoring data
The annual PIVb.s NAAQS is rounded to the nearest tenth of a |J,g/m3. For example,
15.049 rounds to 15.0, and 15.050 rounds to 15.1. These rounding conventions should
be followed when calculating design values for this NAAQS.
127 EPA notes that design value calculations for PM hot-spot analyses involve using air quality modeling
results based on either one year of site-specific measured meteorological data or five years of off-site
measured meteorological data, rather than three years.
The design value for the annual PM2.5 NAAQS is defined for air quality monitoring purposes in 40 CFR
Part 50.13.
129 A sufficient number of decimal places (3-4) should be retained during intermediate calculations for
design values, so that there is no possibility of intermediate rounding or truncation affecting the final result.
Rounding to the tenths place should only occur during final design value calculations, pursuant to
Appendix N to 40 CFR Part 50.
130
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Necessary Data
This design value calculation assumes the project sponsor already has the following data
in hand:
• Air quality modeling results: Average annual concentrations from the project and
any nearby sources should be calculated from the air quality model output files. 13°
The methodology for post-processing the air quality model output files will vary
depending on what air quality model is used. Refer to Appendix J for details on
preparing air quality model outputs for use in design value calculations.
• Air quality monitoring data: 12 quarters of background concentration
measurements (four quarters for each of three consecutive years). See Section 8
for more details on determining representative monitored background
concentrations that meet all applicable monitoring requirements (such as data
completeness).131
Calculating Design Values and Determining Conformity
Exhibit 9-3 (following page) illustrates how a design value is to be calculated and
conformity determined for the annual PM2 5 NAAQS. This exhibit assumes that the
project sponsor would first compare the receptor with the highest average annual
concentration in the build scenario to the NAAQS to determine conformity. If
conformity is not met at this receptor, design values would be calculated at all receptors
in the build scenario. For any receptors with design values above the NAAQS in the
build scenario, the project sponsor would then model the no-build scenario and calculate
design values to determine if conformity requirements are met.
An example of how to calculate design values for the annual PM2.5 NAAQS using this
procedure is included in Appendix K. The steps below can also be described
mathematically using the formulas found in Equation Set 1 in Appendix K.
The steps shown in Exhibit 9-3 are described below. The initial step is to compare the
build scenario to the NAAQS to see if the project conforms:
• Step 1. For each receptor, calculate the average annual concentrations with the air
quality modeling results for each quarter and year of meteorological data used. If
using AERMOD, the model does this step for you and provides the average
annual concentrations as output; proceed to Step 2. If using CAL3QHCR, for
each year of meteorological data, first determine the average concentration in
each quarter. Then, within each year of meteorological data, add the average
concentrations of all four quarters and divide by four to calculate the average
annual modeled concentration for each year of meteorological data. Sum the
130 See Section 7.5.3 for further information on the number of years of meteorological data used in air
quality modeling. For most PM hot-spot analyses, five years of meteorological data will be used.
131 The interagency consultation process should be used when situations require incorporation of any CTM
results into design value calculations.
131
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modeled average annual concentrations from each year of meteorological data,
and divide by the number of years of meteorological data used.
• Step 2. Identify the receptor with the highest modeled average annual
concentration.
• Step 3. For each year of background data, first determine the average monitored
concentration in each quarter. Then, within each year of background data, add the
average concentrations of all four quarters and divide by four to calculate the
average annual background concentration for each year of monitoring data. Next,
add the average annual concentrations from each of the consecutive years of
monitoring data and divide by three. This value is the average annual background
concentration based on monitoring data.132
Exhibit 9-3. Determining Conformity to the Annual PM2.s NAAQS
Build Scenario <= NAAQS
1. Calculate average
annual modeled
concentration at all
receptors (if using
AERMOD: skip to
Step 2)
2. Identify receptor
with the highest
average annual
concentration
3. Calculate average
annual background
concentration
4. Add values from
Steps 2 and 3
5. Round to nearest 0.1
Lig'm3
Is design value
less than or
equal to
NAAQS-?
Build Scenario <= No-build Scenario
6. Repeat Step 1 for all
receptors
7. Add values from
Steps 6 and 3
8. Round to nearest 0.1
Lig/m3 and identify all
receptors that exceed
NAAQS
9. Calculate annual
averages for the no-
build scenario
10. Add values from
Steps 9 and 3
1 1 . Round to nearest
0.1 Lig/m3
* May need to also determine appropriateness of receptors
** Mitigation and control measures can be considered at
any point in the process
132 Each year, EPA calculates quarterly average and annual average concentrations for all PM25 monitoring
sites reporting data to EPA's Air Quality System. The results are posted at:
www.epa.gov/airtrends/values.html. Results are in Excel spreadsheet form, in a worksheet with "site
listing" in the worksheet name.
132
-------
• Step 4. Add the average annual background concentration (from Step 3) to the
average annual modeled concentration at the highest receptor (from Step 2) to
determine the total average annual background concentration at this receptor.
• Step 5. Round to the nearest 0.1 |J,g/m3. This result is the annual PM2 5 design
value at the highest receptor in the build scenario.
The project sponsor should then compare the design value from Step 5 to the annual
PM2.5NAAQS (currently 15.0 |J,g/m3). If the value is less than or equal to the NAAQS,
the project conforms. If the design value is greater than the NAAQS, the project sponsor
should then continue to Step 6:
• Step 6. Repeat the calculations described in Step 1 to determine average annual
concentrations for all receptors in the build scenario.
• Step 7. Add the average annual modeled concentrations (from Step 6) to the
average annual background concentrations (from Step 3).133 The result will be the
total average annual concentration at each receptor in the build scenario.
• Step 8. Round to the nearest 0.1 |J,g/m3. At each receptor, this value is the annual
PM2.5 design value for the build scenario. Identify all receptors that exceed the
annual PM2.5 NAAQS.
• Step 9. From the no-build air quality modeling results, calculate the average
annual concentrations at each receptor identified in Step 8.
• Step 10. For the no-build scenario, add the average annual modeled
concentrations for the no-build scenario (from Step 9) to the average annual
background concentrations (from Step 3). The result will be the total average
annual concentration for each receptor identified in Step 8 under the no-build
scenario.
• Step 11. Round to the nearest 0.1 |J,g/m3. This result is the annual PM2 5 design
value for each receptor identified in Step 8 under the no-build scenario.
For each receptor with a design value that exceeded the NAAQS in the build scenario,
compare the build design value (Step 8) to the no-build design value (Step 11). For the
project to conform, the build design value must be less than or equal to the no-build
design value at each receptor in the build scenario that exceeded the NAAQS (Step 8). If
this is not the case, it may be necessary to determine if any receptors are at unique
locations and are not appropriate for conformity purposes (see Section 9.4).134
If a build scenario design value is greater than the no-build design value at any
appropriate receptor, the sponsor should then consider additional mitigation and control
measures, and revise the PM hot-spot analysis accordingly. Mitigation and control
133 As discussed in Section 8, the same air quality monitoring concentrations would not be expected to
change between the build and no-build scenarios. As a result, the same background concentrations would
be used for every receptor in the build and no-build scenario.
134 Project sponsors could decide to determine if any receptors are at unique locations for this NAAQS at
Step 8, for any receptors where a NAAQS violation is predicted to occur. Also, in certain cases, project
sponsors can also decide to calculate the design values for all receptors in the build and no-build scenarios
and use the interagency consultation process to determine whether a "new" violation has been relocated
(see Section 9.2).
133
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measures could also be considered at any other point in the analysis before the project-
level conformity determination is made. Refer to Section 10 for a discussion of potential
measures.
9.3.3 24-hour PM2.5NAAQS
Design Value
The 24-hour PIVb.s design value is currently defined as the average of three consecutive
years' 98* percentile concentrations of 24-hour values for each of those years.135 The
NAAQS is met when that three-year average concentration is less than or equal to the
currently applicable 24-hour PIVb.s NAAQS for a given area's nonattainment designation
(currently 35 |J,g/m3 for nonattainment areas for the 2006 PM2 5 NAAQS and 65 |J,g/m3 for
nonattainment areas for the 1997 PM2.5 NAAQS).136
The design value for comparison to any 24-hour PM2.5 NAAQS is rounded to the nearest
1 |J,g/m3 (decimals 0. 5 and greater are rounded up to the nearest whole number; decimals
lower than 0.5 are rounded down to the nearest whole number). For example, 35.499
rounds to 35 |J,g/m3, while 35.500 rounds to 36. 137 These r<
followed when calculating design values for this NAAQS.
rounds to 35 |J,g/m3, while 35.500 rounds to 36.137 These rounding conventions should be
There are two analysis options, or tiers, that are available to project sponsors to estimate a
24-hour PM2.5 design value.138 Project sponsors can start with either the first or second
tier analysis, since either tier is a viable approach for meeting conformity requirements.
There may be cases where a project sponsor may decide to start with a first tier analysis,
which is a conservative but less intensive approach.139 In other cases, project sponsors
may decide to go directly to a second tier analysis. For example, depending on how the
air quality model was run and its data post-processed, the actions needed to identify the
highest modeled 24-hour concentration by quarter for a second tier analysis may not
involve much additional time or effort, in which case the second tier approach may be
The design value for the 24-hour PM2 5 NAAQS is defined for air quality monitoring purposes in 40
CFRPart50.13.
136 There are only two areas where conformity currently applies for both the 1997 and 2006 24-hour PM25
NAAQS. While both 24-hour NAAQS must be considered in these areas, in practice if the more stringent
2006 24-hour PM2.5 NAAQS is met, then the 1997 24-hour PM2.5 NAAQS is met as well.
137 A sufficient number of decimal places (3-4) should be retained during intermediate calculations for
design values, so that there is no possibility of intermediate rounding or truncation affecting the final result.
Rounding should only occur during final design value calculations, pursuant to Appendix N to 40 CFR Part
50.
138 This approach is consistent with EPA's approach for calculating design values for other EPA regulatory
programs. See the EPA March 23, 2010 memorandum from Stephen D. Page at
www.epa.gov/scram001/Official%20Signed%20Modeling%20Proc%20for%20Demo%20Compli%20w%2
OPM2.5.pdf.
139 While less data intensive and therefore possibly quicker to execute, the first tier approach is considered
more conservative as compared to the second tier analysis. The first tier approach assumes that the
estimated highest predicted concentration attributable to the project and nearby sources will occur in the
future on each of the days from which the three-year average 98 percentile background concentration is
derived (which may not occur).
134
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preferred from that start. Under either tier, the contributions from the project, any nearby
sources, and background concentrations from other sources are combined for a given
analysis year, as described further below.
Examples of how to calculate design values for the 24-hour PM^.sNAAQS using each
tier are included in Appendix K.
Necessary Data
This design value calculation assumes the project sponsor already has the following data
in hand:
• Air quality modeling results: The highest 24-hour average concentration from the
project and any nearby sources should be calculated based on the air quality
model output files, depending on what tier of analysis is used:
o In a first tier analysis, the highest 24-hour values from each year of
meteorological data should be averaged together.
o In a second tier analysis, the highest 24-hour values from each quarter and
year of meteorological data should be averaged together per quarter.
Post-processing the air quality model output files will vary depending on what air
quality model is used in the hot-spot analysis. Refer to Appendix J for a
discussion of air quality model output file formats.
• Air quality monitoring data: 12 quarters of background concentration
measurements (four quarters for each of three consecutive years). See Section 8
for more details on determining representative monitored background
concentrations that meet all applicable monitoring requirements (such as data
completeness). 14°
Calculating Design Values and Determining Conformity Using a First Tier Analysis
The first tier consists of directly adding the highest average modeled 24-hour
concentrations to the average 98th percentile 24-hour background concentrations.
Exhibit 9-4 (following page) illustrates how a design value would be calculated under a
first tier analysis for a given receptor. The steps shown in Exhibit 9-4 are described in
detail below, and are also described mathematically using the formulas found in Equation
Set 2 in Appendix K.
140 The interagency consultation process should be used when situations require incorporation of any CTM
results into design value calculations.
135
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Exhibit 9-4. Determining Conformity to the 24-hour PM2.sNAAQS Using First Tier
Analysis
1. From build scenario
modeling results,
identify the receptor
with the highest
average 24-hour
concentration
2. Determine the 3-
year average of the
98* percentile 24-hour
background
concentrations
3. Add results of Steps
1 and 2 to obtain
design value
Project conforms
Yes / Is design value
4 ( less than or equal
\ toNAAQS?
No
Conduct no-build
analysis and/or
second tier
analysis
The initial step in a first tier analysis is to compare the build scenario to the NAAQS to
see if the project conforms:
• Step 1. From the air quality modeling results from the build scenario, identify the
receptor with the highest average 24-hour concentration. This is done by first
separating the air quality model output into each year of meteorological data.
Second, for each receptor and year of meteorological data, identify the 24-hour
period (midnight-to-midnight) with the highest average concentration throughout
the entire year. Finally, at each receptor, average the highest 24-hour
concentrations from each year of meteorological data across all years. The
receptor with the highest value is used to calculate the 24-hour PM2.5 design
value.
• Step 2. Calculate the average 98th percentile 24-hour background concentration
using the 98th percentile 24-hour concentrations of the three most recent years of
air quality monitoring data. To calculate the 98th percentile background
concentrations for each year of monitoring data, first count the number of 24-hour
background measurements in each year. Next, order the highest eight monitoring
values in each year from highest to lowest and rank each value from 1 (highest) to
8 (eighth highest). Consult Exhibit 9-5 (following page) to determine which of
these eight values is the 98th percentile value. Using the results from the three
136
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years of monitoring data, calculate the three-year average of the 98th percentile
141
concentrations.
• Step 3. Add the highest average 24-hour modeled concentration (Step 1) to the
average 98th percentile 24-hour background concentration (Step 2) and round to
the nearest 1 |J,g/m3. The result is the 24-hour PM2 5 design value at the highest
receptor in the build scenario.
Exhibit 9-5. Ranking of 98* Percentile Background Concentration Values
Number of
Background
Concentration
Values
1-50
51-100
101-150
151-200
201-250
251-300
301-350
351-366
Rank of Value
Corresponding to
98th Percentile
Concentration
1
2
3
4
5
6
7
8
If the design value calculated in Step 3 is less than or equal to the relevant 24-hour PM2.5
NAAQS, then the project conforms. If it is greater than the 24-hour PM2.5 NAAQS,
conformity is not met, and the project sponsor has two options:
• Repeat the first tier analysis for the no-build scenario at all receptors that
exceeded the NAAQS in the build scenario. If the calculated design value for the
build scenario is less than or equal to the design value for the no-build scenario at
all of these receptors, then the project conforms;143 or
• Conduct a second tier analysis as described below.
141 Assuming a regular monitoring schedule and a resulting data set that meets the completeness
requirements of 40 CFR Part 50 Appendix N, the result of Step 2 will be the design value for the
monitoring site used to estimate the background concentrations. Each year, EPA calculates the 98th
percentile concentration for each of the most recent three years and the average of the three current annual
values for every PM2 5 monitor, based on the data reported to EPA's Air Quality System. Project sponsors
may use the EPA-calculated design values directly instead of executing Step 2, or may compare their result
from Step 2 to the EPA-calculated design value. These design values appear in the worksheet "Site
Listing" of the latest PM2.5 design value spreadsheet posted at: www.epa.gov/airtrends/values.html.
142 This exhibit is based on a table in Appendix N to 40 CFR Part 50, and ranks the 98th percentile of
background concentrations pursuant to the total number of air quality monitoring measurements.
143 In certain cases, project sponsors can also decide to calculate the design values for all receptors in the
build and no-build scenarios and use the interagency consultation process to determine whether a "new"
violation has been relocated (see Section 9.2).
137
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Calculating Design Values and Determining Conformity Using a Second Tier Analysis
The second tier involves a greater degree of analysis, in that the highest modeled
concentrations and the 98th percentile background concentrations are not added together
for each receptor directly, as in a first tier analysis. Unlike a first tier analysis, which
uses the average of the highest modeled 24-hour concentration from each year of
meteorological data, a second tier analysis uses the average of the highest modeled 24-
hour concentration within each quarter of each year of meteorological data. In other
words, impacts from the project, nearby sources, and other background concentrations are
calculated on a quarterly basis before determining the 98th percentile concentration
resulting from these inputs.
Exhibit 9-6 (following page) and the following steps provide details for calculating a
design value for the 24-hour PIVb.s NAAQS under a second tier analysis. These steps can
also be described mathematically using the formulas found in Equation Set 3 in Appendix
K.
A project sponsor would initially complete these steps for the build scenario; then, if
necessary, repeat the steps for the no-build scenario. Steps 1 and 2 of a second tier
analysis are completed only once for all receptors, since the same background
concentrations would be used for every receptor in either the build or no-build scenario.
• Step 1. Count the number of measurements for each year of monitoring data used
for background concentrations for other sources.
• Step 2. For each year of monitoring data used, determine the eight highest 24-
hour background concentrations for each quarter modeled. For most hot-spot
analyses for the 24-hour PIVb.s NAAQS, modeling would be completed for all
four quarters of each analysis year. This would therefore result in 32 values
(eight concentrations for four quarters) for each year of monitoring data.144'145
The remaining steps are completed for calculating the 24-hour PM2.5 design value at each
receptor:
• Step 3. At each receptor, identify the highest modeled 24-hour concentration in
each quarter, averaged across each year of meteorological data used for air quality
modeling.
• Step 4. At each receptor, add the highest modeled concentration in each quarter
(from Step 3) to each of the eight highest 24-hour background concentrations for
the same quarter for each year of monitoring data (from Step 2). At each
receptor, this step will result in eight 24-hour concentrations in each of four
quarters for a total of 32 values for each year of monitoring data.
144 Section 3.3.4 describes how the number of quarters modeled should be determined. In most PM hot-
spot analyses for the 24-hour PM25 NAAQS, all four quarters of the analysis year will be modeled. There
are limited cases where modeling only one quarter would be appropriate.
145 24-hour PM2 5 concentrations for any monitoring site reported to EPA's Air Quality System can be
obtained by using the data download tools available at: www.epa.gov/airexplorer/monitor_kml.htm.
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Exhibit 9-6. Determining Conformity to the 24-hour PM^sNAAQS Using Second
Tier Analysis
*s=
1. Count the number of
measurements for each
year of background
data
2. Determine the 8
highest 24-hour
background values for
quarter
3. For each receptor in
each quarter, identify
the highest
concentration
4, At receptor,
add values from Steps
2 arid 3 for each.
quarter
5,Rank values in Step
4 from highest to
lowest for year of
monitoring
6. Determine the value
in Step 5
corresponding to the
98t%percentile
/.Repeat Step 6 for
each year of
background
i. Average the three
98*pereentile
concentrations
<=
10, Repeat Steps 3
through 9 using no-
build modeling results
Consider
measures to
reduce emissions
arid redo
analysis*
* Mitigation control measures be
considered at any in the process
139
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• Step 5. For each receptor and year of monitoring data, order the 32 values from
Step 4 from highest to lowest and rank each value from 1 (highest concentration)
to 32 (lowest concentration).
• Step 6. Based on the number of background concentration values you have (from
Step 1), use Exhibit 9-7 to determine which value in the column (from Step 5)
represents the 98 percentile concentration for each receptor. For example, if you
have 180 background concentration values in a year, Exhibit 9-7 shows that the
4 highest value would represent the 98l percentile. Take the value at each
receptor that has this rank.
Exhibit 9-7. Ranking of 98th Percentile Background Concentration Values146
Number of
Background
Concentration
Values
1-50
51-100
101-150
151-200
201-250
251-300
301-350
351-366
Rank of Value
Corresponding to
98th Percentile
Concentration
1
2
3
4
5
6
7
8
Step 7. Repeat Step 6 for each of the three years of background monitoring data.
The result will be three 24-hour 98th percentile concentrations at each receptor,
one for each year of monitoring data.
Step 8. At each receptor, calculate the average of the three 24-hour 98th percentile
concentrations determined in Step 7.
Step 9. Round the average concentrations from Step 8 to the nearest 1 |J,g/m3. At
each receptor, this value is the 24-hour PIVb.s design value for the build scenario.
Compare the design values to the relevant 24-hour PIVb.s NAAQS. If the design values at
all receptors are less than or equal to the NAAQS, then the project conforms. If this is
not the case, proceed to Step 10:
• Step 10. Using modeling results for the no-build scenario, repeat Steps 3 through
9 for all receptors with a design value that exceeded the PIVb.s NAAQS in the
build scenario. The result will be a 24-hour PIVb.s design value at such receptors
for the no-build scenario.
146 This exhibit is based on a table in Appendix N to 40 CFR Part 50, and ranks the 98 percentile of
background concentrations pursuant to the number of air quality monitoring measurements.
140
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Compare the build design values (from Step 9) to the no-build design values (from Step
10), identifying which value is higher at each receptor. For the project to conform, the
build design values must be less than or equal to the no-build design value for all of the
receptors that exceeded the NAAQS in the build scenario.147
If the build scenario design value is greater than the no-build design value at any
appropriate receptor, the project sponsor should then consider additional mitigation and
control measures, and revise the PM hot-spot analysis accordingly. Mitigation and
control measures could also be considered at any other point in the analysis before the
project-level conformity determination is made. Refer to Section 10 for a discussion of
potential measures.
9.3.4 24-hour PM10 NAAQS
Design Value
Compliance with the 24-hour PMi0 NAAQS is based on the expected number of 24-hour
exceedances of a particular level (currently 150 |j,g/m3), averaged over three consecutive
years.148 Currently, the NAAQS is met when the expected number of exceedances is less
than or equal to l.O.149
The 24-hour PMio NAAQS design value is rounded to the nearest 10 |J,g/m3. For
example, 155.511 rounds to 160, and 154.999 rounds to 150.15° These rounding
conventions should be followed when calculating design values for this NAAQS.
The contributions from the project, any nearby sources, and background concentrations
from other sources are combined for a given analysis year, as described further below.
Examples of how to calculate design values for the 24-hour PMio NAAQS are included in
Appendix K.
147 In certain cases, project sponsors can also decide to calculate the design values for all receptors in the
build and no-build scenarios and use the interagency consultation process to determine whether a "new"
violation has been relocated (see Section 9.2).
148 The 24-hour PM10 NAAQS and supporting technical documentation can be found in 40 CFR Part 50.6.
The term "expected" means that the actual number of observed exceedances is adjusted upwards when
observations are missing for some days, to reflect the air quality statistically expected for those days. The
design value for the 24-hour PM10 NAAQS is the next highest observed (monitored or modeled)
concentration after the concentrations that could be above 150 ng/m3 without causing the expected number
of exceedances to be greater than 1.0.
150 A sufficient number of decimal places (3-4) in modeling results should be retained during intermediate
calculations for design values, so that there is no possibility of intermediate rounding or truncation
affecting the final result. Rounding to the nearest 10 ug/m3 should only occur during final design value
calculations, pursuant to Appendix K to 40 CFR Part 50. Monitoring values typically are reported with
only one decimal place.
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Necessary Data
This design value calculation assumes the project sponsor already has the following data
in hand:
• Air quality modeling results: In most PM hot-spot analyses, five years of
meteorological data will be used to complete air quality modeling for the project
and any nearby sources.151 In this case, the sixth-highest 24-hour modeled
concentration should be calculated for each receptor.152 Note that AERMOD can
be configured to give you these values directly. CAL3QHCR output needs to be
post-processed to obtain the sixth-highest value from five years of meteorological
data. See more details below and refer to Appendix J for a discussion of air
quality model output file formats.
• Air quality monitoring data: 12 quarters of background concentration
measurements (four quarters for each of three consecutive years). See Section 8
for more details on determining representative monitored background
concentrations that meet all applicable monitoring requirements (such as data
completeness).153
Calculating Design Values and Determining Conformity
The 24-hour PMi0 design value is calculated at each receptor by directly adding the sixth-
highest modeled 24-hour concentrations (if using five years of meteorological data) to the
highest 24-hour background concentration (from three years of monitoring data).
Exhibit 9-8 (following page) illustrates how a design value would be calculated. The
steps shown in Exhibit 9-8 are described in detail below and are also described
mathematically using the formulas found in Equation Set 4 in Appendix K.
The initial step is to compare the build scenario to the NAAQS to see if the project
conforms:
• Step 1. From the air quality modeling results for the build scenario, identify the
sixth-highest 24-hour concentration for each receptor (across five years of
meteorological data, in most cases). When using AERMOD, the model can be
configured to produce these values.154 When using CAL3QHCR, output needs to
be post-processed to obtain the sixth-highest values from five years of
meteorological data.
• Step 2. Identify the receptor with the highest sixth-highest 24-hour concentration.
That is, compare the sixth-highest modeled concentrations (i.e., the concentrations
151 Section 7.5.3 of this guidance provides further information on the number of years of meteorological
data used in air quality modeling.
152 See description in Section 7.2.1.1 of Appendix W. Users with one year of site-specific meteorological
data should select the 2n highest 24-hour PMi0 concentration. If using less than one year of meteorological
data (such as one quarter), users should select the highest 24-hour concentration.
153 The interagency consultation process should be used when situations require incorporation of any CTM
results into design value calculations.
154
For example, users could employ the RECTABLE keyword in the AERMOD output pathway. See
Appendix J to this guidance for further information.
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at Rank 6) across receptors and identify the receptor with the highest value at
Rank 6.
Step 3. Identify the highest 24-hour background concentration from the three
most recent years of air quality monitoring data.155
Step 4. For the receptor identified in Step 2, add the sixth-highest 24-hour
modeled concentration to the highest 24-hour background concentration (from
Step 3).
Step 5. Round to the nearest 10 |J,g/m . The result is the highest 24-hour
design value in the build scenario.
Exhibit 9-8. Determining Conformity to the 24-hour PM10NAAQS
Build Scenario <= NAAQS
1. Identify the sixth
highest 24-hour
concentration at each
receptor
2. Identify the receptor
with the highest sixth-
hiahest concentration
3. Identify the highest
24-hourbackground
concentration
4. Add values from
Steps 2 and 3
5. Round to nearest 10
\ig/'m-
Is design value
less than or
equal to
NAAQS?
Build Scenario <= No-build Scenario
6. Add values from
Step 1 and Step 3 at
each receptor
7. Round to nearest 10
(ig/'m3 and identify all
receptors that exceed
NAAQS
S. From no-build
modeling results.
identify sixth-highest
concentration for each
receptor identified in
Step"
9. Add values from
Steps 8 and 3
* Mitigation and control measures can be
considered at any point in the process
155 24-hour PM10 concentrations for any monitoring site reported to EPA's Air Quality System can be
obtained by using the data download tools available at: www.epa.gov/airexplorer/monitor_kml.htm.
143
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The project sponsor should then compare the design value from Step 5 to the 24-hour
PMioNAAQS (currently 150 |j,g/m3). If the design value calculated in Step 5 is less than
or equal to the NAAQS, the project conforms. If the design value is greater than the
NAAQS, the project sponsor should then continue to Step 6:
• Step 6. For each receptor in the build scenario, add the sixth-highest 24-hour
modeled concentration (from Step 1) to the highest 24-hour background
concentration from the three most recent years of air quality monitoring data
(from Step 3).
• Step 7. Round to the nearest 10 |J,g/m3. At each receptor, this value is the 24-
hour PMio design value for the build scenario. Identify all receptors that exceed
the 24-hour PMio NAAQS.
• Step 8. From the no-build air quality modeling results, identify the sixth-highest
24-hour concentration for each receptor identified in Step 7.
• Step 9. Add the sixth-highest 24-hour modeled concentration in the no-build
scenario (from Step 8) to the highest 24-hour background concentration from the
three most recent years of air quality monitoring data (from Step 3).
• Step 10. Round to the nearest 10 |J,g/m . The result is the 24-hour PMio design
value under the no-build scenario for each receptor identified in Step 7.
For each receptor with a design value that exceeded the NAAQS in the build scenario,
compare the build design value (from Step 7) to the no-build design value (from Step 10).
For the project to conform, the build design value must be less than or equal to the no-
build design value at each receptor in the build scenario that exceeded the NAAQS (Step
7).156
If the build scenario design value is greater than the no-build design value at any
appropriate receptor, the project sponsor should then consider additional mitigation and
control measures, and revise the PM hot-spot analysis accordingly. Mitigation and
control measures could also be considered at any other point in the analysis before the
project-level conformity determination is made. Refer to Section 10 for a discussion of
potential measures.
More advanced methods of calculating a PMio design value, such as combining modeled
and monitored concentrations on a quarterly basis, may be considered on a case-by-case
basis by the EPA Regional Office, OTAQ, and OAQPS. Any alternative methods for
calculating PMio design values must be evaluated and chosen through the process
established by each area's interagency consultation procedures (40 CFR 93.105(c)(l)(i)).
156 In certain cases, project sponsors can also decide to calculate the design values for all receptors in the
build and no-build scenarios and use the interagency consultation process to determine whether a "new"
violation has been relocated (see Section 9.2).
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9.4 DETERMINING APPROPRIATE RECEPTORS FOR COMPARISON TO THE
ANNUAL PM2.5NAAQS
Note: Section 9.4 has been revised in accordance with EPA 's 2012 PMNAAQSfinal
rule that was published on January 15, 2013 (78 FR 3264).
9.4.1 Overview
When hot-spot analyses are done for the annual PM2.5 NAAQS, there is an additional step
that may be necessary in certain cases to determine whether a receptor is appropriate to
compare to this NAAQS. In the March 2006 final rule, EPA stated that PM2.5 hot-spot
analyses would be consistent with how the PIVb.s NAAQS are developed, monitored, and
implemented (71 FR 12471). Receptors cannot be used for PIVb.s hot-spot analyses if
they are at locations that would not be appropriate for air quality monitoring purposes for
the NAAQS. An "appropriate receptor location" under Section 93.123(c)(l) of the
conformity rule is a location that is suitable for comparison to the relevant NAAQS,
consistent with how the PM NAAQS are established and monitored for air quality
planning purposes.158
As a result of EPA's 2012 PM NAAQS final rule, in the majority of hot-spot analyses for
the annual PM2.5 NAAQS, project sponsors will not need to determine whether air quality
modeling receptor locations are appropriate for conformity purposes, because all
locations will generally be considered appropriate. However, there may be cases in which
the analysis area includes receptors that are not representative of area-wide air quality
because they are at unique locations, pursuant to the PM NAAQS final rule including
Section 58.1, Section 58.30(a) and Section 4.7.1 of Appendix D to 40 CFRPart 58. In
these cases, further consideration may be needed after air quality modeling is completed
to determine whether any of the modeled receptors are not appropriate for comparison to
the annual PM2 5 NAAQS, as discussed further below. If conformity requirements are
met at all receptors, it is unnecessary to determine whether receptors are appropriate for
comparison to the annual PM2 5 NAAQS; in such a case, project sponsors can conclude
that conformity requirements are met at all appropriate receptors.
9.4.2 2012 PMNAAQS final rule and revised conformity guidance
The paragraphs below describe the relevant regulatory provisions and revised guidance
for calculating design values and determining conformity for the annual PM2.5 NAAQS,
through the steps described in Section 9.3.2.
EPA committed to "review whether there is a need to issue new or revised transportation conformity
guidance in light of this final rule." (78 FR 3264) EPA is fulfilling this commitment through this guidance
revision. The previous version of Section 9.4 was issued in December 2010, EPA-420-B-10-040.
158 See CAA Section 176(c)(l)(B). EPA interprets "NAAQS" in this provision to mean the specific
NAAQS that has been established through rulemaking.
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Overview of 2012 PM NAAQS Final Rule
In the 2012 PM NAAQS final rule, EPA revised the form of the annual PM2.5 NAAQS to
protect the public health of "populations living near important sources of PM2.5, including
the large populations that live near major roadways." (78 FR 3127)159 This final rule also
included revisions to the PIVb.s monitoring regulations which are covered in more detail
below.
The annual PIVb.s NAAQS is to be monitored at "area-wide" locations, which is defined
under 40 CFR 58.1:
"Area-wide means all monitors sited at neighborhood, urban, and regional
scales, as well as those monitors sited at either micro- or middle-scale that
are representative of many such locations in the same CBSA."160
In order to be consistent with the revised annual PIVb.s NAAQS, an appropriate receptor
for hot-spot analyses for this NAAQS must also represent area-wide air quality.
EPA also added a near-road component to the PM2 5 monitoring network "to provide
characterization of concentrations in near-road environments including for comparison to
the NAAQS." (78 FR 3238). In establishing this new requirement, EPA has "made a
determination to protect all area-wide locations, including those locations with
populations living near major roads that are representative of many such locations
throughout an area." (78 FR 3240)
In the final rule, EPA also clarified what monitoring sites are eligible for comparison to
the annual PM2 5 NAAQS, and what unique locations may not be appropriate for
comparison to the annual PIVb.s NAAQS. Section 58.30(a) of the monitoring regulations
states:
"PM2.5 measurement data from all eligible monitors that are representative
of area-wide air quality are comparable to the annual PIVb.s NAAQS.
Consistent with appendix D to this part, section 4.7.1, when micro- or
middle-scale PIVb.s monitoring sites collectively identify a larger region of
localized high ambient PIVb.s concentrations, such sites would be
considered representative of an area-wide location and, therefore, eligible
for comparison to the annual PIVb.s NAAQS. PIVb.s measurement data
from monitors that are not representative of area-wide air quality but
rather of relatively unique micro-scale, or localized hotspot, or unique
middle-scale impact sites are not eligible for comparison to the annual
PM2.5 NAAQS. PM2.5 measurement data from these monitors are eligible
for comparison to the 24-hour PlVk.s NAAQS. For example, if a micro- or
middle-scale PIVb.s monitoring site is adjacent to a unique dominating
159 See 78 FR 3124-7 for more on the form of the annual PM2.5 NAAQS.
160 This requirement does not have to be satisfied for monitoring the 24-hour PM2 5 NAAQS or the 24-hour
PM10 NAAQS.
146
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local PM2.5 source, then the PM2.5 measurement data from such a site
would only be eligible for comparison to the 24-hour PM2.5 NAAQS." 161
EPA finalized generally what was proposed for Section 58.30(a), recognizing that "there
are cases where near-road environments can be considered a unique location...Examples
of such locations that are considered unique and should therefore not be considered
applicable to the annual PIVb.sNAAQS are explained later in section VTII.B.S.b.i." (78
FR 3237) In this part of the preamble, EPA stated:
"We do recognize, however, the possibility that some near-road
monitoring stations may be representative of relatively unique locations
versus the more representative area-wide situation mentioned above. This
could occur because an air agency made a siting decision based on NC>2
criteria that resulted in the characterization of a microscale environment
that is not considered area-wide for PM2.s; for example, due to proximity
to a unique source like a tunnel entrance, nearby major point source, or
other relatively unique microscale hot spot. In these types of scenarios, air
agencies would identify the site as a unique monitor comparable only to
the 24-hour PM2.5 NAAQS per the language in section 58.30...." (78 FR
3241)
See 78 FR 3234-41 of the preamble to the PM NAAQS final rule for further information
on the above revisions to the PM2.5 monitoring regulations.
Revised Conformity Guidance
Section 9.3.2 includes an approach for conducting build/no-build analyses for the annual
PM2.5 NAAQS, in which the appropriateness of receptors is determined only in cases
where a design value in the build scenario is higher than the NAAQS and the design
value in the no-build scenario. As noted above, if conformity requirements are met at all
receptors, it is unnecessary to determine whether receptors are not appropriate for
comparison to the annual PIVb.s NAAQS; in such a case, project sponsors can conclude
that conformity requirements are met at all appropriate receptors. Also as noted above,
the majority of hot-spot analyses for the annual PM2.5 NAAQS will meet Section
93.123(c)(l) of the conformity rule without specifically determining whether air quality
modeling receptor locations are appropriate for conformity purposes, because all
locations will generally be considered appropriate under the revised annual PM2.5
NAAQS and monitoring regulations. However, for those cases involving unique
locations - e.g., a tunnel entrance, a nearby major point source, or other relatively unique
microscale hot-spot - further consideration for appropriate receptors would be needed
after air quality modeling is completed for the annual PM2.s NAAQS.162
161See Section 4.7. l(b) and Section 4.7.1 (c) of Appendix D to 40 CFR Part 58 for further background on
middle and microscale locations.
162 As discussed in Section 7.6, receptors can be placed prior to air quality modeling for all PM NAAQS.
Furthermore, the appropriateness of receptor locations for the 24-hour PM25 NAAQS (and 24-hour PM10
NAAQS) can be determined prior to air quality modeling.
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Consistent with 40 CFR 58.30(a) of the PIVb.s monitoring regulations, the air quality
modeling results for the PM hot-spot analysis will provide critical information for
determining whether there is a large region of high PIVb.s concentrations, especially if
high concentrations are predicted in a large number of adjacent receptors. In order to
determine if "a larger region of localized high ambient PIVb.s concentrations" is present in
a given PM hot-spot analysis, it is critical to know which receptors have concentrations
above the NAAQS. If a significant number of similar adjacent receptors have high
concentrations representing a large portion of the project area, such receptors may
represent area-wide air quality, and not represent unique locations. Such an assessment
cannot be done qualitatively prior to air quality modeling.
Evaluating and choosing the models and associated methods and assumptions, including
appropriate receptor locations for the annual PIVb.s NAAQS, must be completed through
the process established by each area's interagency consultation procedures (40 CFR
93.105(c)(l)(i)). State and local air quality agencies and EPA have significant expertise
in air quality planning and monitoring purposes and may be useful resources in
determining appropriate receptor locations for the annual PM2 5 NAAQS.
9.5 DOCUMENTING CONFORMITY DETERMINATION RESULTS
Once a PM hot-spot analysis is completed, details need to be documented in the
conformity determination. See Section 3.10 for more information on properly
documenting a PM hot-spot analysis, including modeling data, assumptions, and results.
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Section 10: Mitigation and Control Measures
10.1 INTRODUCTION
This section describes mitigation and control measures that could be considered by
project sponsors to reduce emissions and any predicted new or worsened PM NAAQS
violations. These measures can be applied to the transportation project itself or other PM
sources in the project area. Written commitments for mitigation or control measures
must be obtained from the project sponsor and/or operator, or other emission source's
owner and/or operator, as appropriate, prior to making a project-level conformity
determination (40 CFR 93.123(c)(4) and 93.125(a)). If measures are selected, additional
emissions and air quality modeling will need to be completed and new design values
calculated to ensure that conformity requirements are met.
The following information provides more details on potential measures for PM hot-spot
analyses; others may be possible. Evaluating and choosing any models and associated
methods and assumptions for any measures that are relied upon in the PM hot-spot
analysis must be completed through the process established by each area's interagency
consultation procedures (40 CFR 93.105(c)(l)(i)). The models, methods, and
assumptions used to quantify reductions should be documented in the final project-level
conformity determination.
General categories of mitigation and control measures that could be considered include:
• Retrofitting, replacing vehicles/engines, and using cleaner fuels;
• Reducing idling;
• Redesigning the transportation project itself;
• Controlling fugitive dust; and
• Controlling other sources of emissions.
More information is provided for each of these categories below.
10.2 MITIGATION AND CONTROL MEASURES BY CATEGORY
10.2.1 Retrofitting, replacing vehicles/engines, and using cleaner fuels
• The installation of retrofit devices on older, higher emitting vehicles is one way to
reduce emissions. Retrofit devices such as Diesel Particulate Filters (DPFs) or
Diesel Oxidation Catalysts (DOCs) can be installed on diesel truck or bus fleets,
and off-road construction equipment when applicable to lower emissions cost-
effectively.163
163 It would be appropriate to replace or retrofit construction equipment in those cases where construction
emissions are included in the analysis (i.e., when construction emissions are not considered temporary).
149
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• Replacing older engines with newer, cleaner engines, including engines powered
by compressed natural gas (CNG), liquefied natural gas (LNG), biodiesel, or
electricity is another way to reduce emissions from existing diesel truck or bus
fleets. Many engines can also benefit from being rebuilt, repaired, upgraded to a
more recent standard, and properly maintained. The emission reduction
calculations should take into account whether retired vehicles or engines are
permanently scrapped.
• The accelerated retirement or replacement of older heavy-duty diesel vehicles
with cleaner vehicles is another way to reduce emissions. A replacement program
could apply to buses, trucks, or construction equipment.164 In some areas, local
regulations to ban older trucks at specific port facilities have encouraged early
replacement of vehicles. Such an option would need to be discussed with the
local government with implementing authority.
o For additional information about quantifying the benefits of retrofitting
and replacing diesel vehicles and engines for conformity determinations,
see EPA's website for the most recent guidance on this topic:
www.epa.gov/otaq/stateresources/transconf/policy.htm.
o Also see EPA's National Clean Diesel Campaign website, which includes
information about retrofitting vehicles, including lists of EPA-verified
retrofit technologies and certified technologies; clean fuels; grants; case
studies; toolkits; and partnership programs: www.epa.gov/otaq/diesel/.
10.2.2 Reduced idling programs
• Anti-idling programs for diesel trucks or buses may be relevant for projects where
significant numbers of diesel vehicles are congregating for extended periods of
time (e.g., restrictions on long duration truck idling, truck stop electrification, or
time limits on bus idling at a terminal).
o For additional information about quantifying the benefits of anti-idling
programs for conformity determinations, see EPA's website for the most
recent guidance on this topic:
www.epa.gov/otaq/stateresources/transconf/policy.htm.
o A list of EPA-verified anti-idle technologies for trucks can be found at:
www. epa. gov/otaq/smartwav/transport/what-smartwav/verified-
technologies.htm.
The Federal Transit Administration (FTA) has minimum service life requirements for transit vehicles
purchased with FTA funds. If a transit agency disposes of a vehicle earlier than its full useful service life,
it will incur a payback penalty. Please refer to Chapter IV of FTA Circular 5010. ID for the establishment
and calculation of a vehicle's useful service life. In addition, Appendix D of the circular address the useful
life calculation and disposition of vehicles acquired with FTA funds:
www.fta.dot.gov/documents/C_5010_lD_Finalpub.pdf.
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10.2.3 Transportation project design revisions
• For transit and other terminals, project sponsors could consider redesigning the
project to reduce the number of diesel vehicles congregating at any one location.
Terminal operators can also take steps to improve gate operations to reduce
vehicle idling inside and outside the facility. Fewer diesel vehicles congregating
could reduce localized PM2 5 or PMio emissions for transit and other terminal
projects.
o A list of strategies to reduce emissions from trucks operating at marine
and rail terminals are available at:
www. epa. gov/otaq/smartwav/transport/partner-resources/resources-
publications.htm.
• It may be possible in some cases to route existing or projected traffic away from
populated areas to an industrial setting (e.g., truck only lanes). Project sponsors
should take into account any changes in travel activity, including additional VMT,
that would result from rerouting this traffic. Note that this option may also
change the air quality modeling receptors that are examined in the PM hot-spot
analysis.
• Finally, project sponsors could consider additional modes for travel and goods
movement. An example would be transporting freight by cleaner rail instead of
by highway (e.g., putting port freight on electric trains instead of transporting it
by truck).
10.2.4 Fugitive dust control programs
Fugitive dust control programs will primarily be applicable in PMio hot-spot analyses,
since all PMio nonattainment and maintenance areas must include these emissions in such
analyses. However, there may be PM2 5 nonattainment and maintenance areas that also
could take advantage of these measures if re-entrained road dust or construction dust is
required for a PM2 5 hot-spot analysis. See Section 2.5 for further background.
• A project sponsor could commit to cover any open trucks used in construction of
the project if construction emissions are included in an analysis year. Some states
have laws requiring that open truck containers be covered to reduce dispersion of
material. Laws may differ in terms of requirements, e.g., some require covering
at all times, some require covering in limited circumstances, and some restrict
spillage.
• A project sponsor could employ or obtain a commitment from another local
agency to implement a street cleaning program. There is a variety of equipment
available for this purpose and such programs could include vacuuming or flushing
techniques. There have been circumstances where municipalities have
implemented street sweeping programs for air quality purposes.
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• Another option to reduce dust could be a site-watering program, which may be
relevant during the construction phase of a project, if construction emissions are
included in the PM hot-spot analysis.
• Project sponsors may consider street and shoulder paving and runoff and erosion
control in the project area, which can reduce significant quantities of dust.
• It may also be possible to reduce the use of sand in snow and ice control
programs, to apply additional chemical treatments, or to use harder material (that
is less likely to grind into finer particles).
10.2.5 Addressing other source emissions
Note: Controlling emissions from other sources may sufficiently reduce background
concentrations in the PM hot-spot analysis.
• Reducing emissions from school buses may be relevant where such emissions are
part of background concentrations. Information about retrofitting, replacing, and
reducing idling of school buses can be found on EPA's website at:
www.epa.gov/otaq/schoolbus/index.htm.
• Reducing emissions from ships, cargo handling equipment and other vehicles at
ports may change the result of the PM hot-spot analysis. Options such as
retrofitting, repowering, or replacing engines or vehicles, use of cleaner fuels, or
"cold ironing" (that allows ships to plug in to shore-side power units) could be
relevant where these sources significantly influence background concentrations in
the project area. More information about reducing emissions at ports can be
found on EPA's website at: www.epa.gov/otaq/diesel/ports/index.htm and
www. epa. gov/otaq/smartwav/transport/partner-resources/resources-
publications.htm.
• Adopting locomotive anti-idling policies or other measures. For additional
information, see the following EPA resources:
o "Guidance for Quantifying and Using Long Duration Switch Yard
Locomotive Idling Emission Reductions in State Implementation Plans,"
EPA420-B-04-09-037 (October 2009) available at:
www.epa.gov/otaq/diesel/documents/420b09037.pdf
o EPA-verified anti-idle technologies for locomotives can be found at:
www. epa. gov/otaq/smartwav/transport/what-smartway/verified-
technologies.htm.
• Remanufacturing existing locomotives to meet more stringent standards at a rate
faster than the historical average, or using only Tier 3 and/or Tier 4 locomotives
at a proposed terminal (once such locomotives become available).
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Reducing emissions from a stationary source might also change the result of the
PM hot-spot analysis. Reductions could come from adding a control technology
to a stationary source or adopting policies to reduce peak emissions at such a
source. EPA and the state and/or local air quality agency could provide input on
the feasibility and implementation of such a measure, as well as any necessary
commitments to such measures from operators.
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Transportation Conformity Guidance for
Quantitative Hot-Spot Analyses in
PM2.5 and PMi0 Nonattainment and
Maintenance Areas
Appendices A-K
Transportation and Climate Division
Office of Transportation and Air Quality
U.S. Environmental Protection Agency
&EPA
United States
Environmental Protection
Agency
EPA-420-B-13-053
November 2013
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APPENDIX A: CLEARINGHOUSE OF WEBSITES, GUIDANCE, AND OTHER TECHNICAL
RESOURCES FOR PM HOT-SPOT ANALYSES A-l
APPENDIX B: EXAMPLES OF PROJECTS OF LOCAL AIR QUALITY CONCERN B-l
APPENDIX C: HOT-SPOT REQUIREMENTS FOR PM10 AREAS WITH PRE-2006 APPROVED
CONFORMITY SIPS C-l
APPENDIX D: CHARACTERIZING INTERSECTION PROJECTS FOR MOVES D-l
APPENDIX E: EXAMPLE QUANTITATIVE PM HOT-SPOT ANALYSIS OF A HIGHWAY
PROJECT USING MOVES AND CAL3QHCR E-l
APPENDIX F: EXAMPLE QUANTITATIVE PM HOT-SPOT ANALYSIS OF A TRANSIT
PROJECT USING MOVES AND AERMOD F-l
APPENDIX G: EXAMPLE OF USING EMFAC2011 FOR A HIGHWAY PROJECT G-l
APPENDIX H: EXAMPLE OF USING EMFAC2011 TO DEVELOP EMISSION FACTORS FOR A
TRANSIT PROJECT H-l
APPENDIX I: ESTIMATING LOCOMOTIVE EMISSIONS 1-1
APPENDIX J: ADDITIONAL REFERENCE INFORMATION ON AIR QUALITY MODELS AND
DATA INPUTS J-l
APPENDIX K: EXAMPLES OF DESIGN VALUE CALCULATIONS FOR PM HOT-SPOT
ANALYSES K-l
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Appendix A:
Clearinghouse of Websites, Guidance, and Other Technical
Resources for PM Hot-spot Analyses
A.1 INTRODUCTION
This appendix is a centralized compilation of documents and websites referenced in the
guidance, along with additional technical resources that may be of use when completing
quantitative PM hot-spot analyses. Refer to the appropriate sections of the guidance for
complete discussions on how to use these resources in the context of completing a
quantitative PM hot-spot analysis. The references listed are current as of this writing;
readers are reminded the check for the latest versions when using them for a particular
PM hot-spot analysis.
A.2 TRANSPORTATION CONFORMITY AND CONTROL MEASURE GUIDANCE
The EPA hosts an extensive library of transportation conformity guidance online at:
www. epa.gov/otaq/stateresources/transconf/policy.htm (unless otherwise noted). The
following specific guidance documents, in particular, may be useful references when
implementing PM hot-spot analyses:
• "Policy Guidance on the Use of MOVES2010 for SIP Development and
Transportation Conformity, and Other Purposes," EPA-420-B-09-046 (December
2009). This document describes how and when to use the MOVES2010
emissions model for SIP development, transportation conformity determinations,
and other purposes.
• "EPA Releases MOVES2010 Mobile Source Emissions Model: Questions and
Answers," EPA-420-F-09-073 (December 2009).
• "EPA Releases MOVES201 Oa Mobile Source Emissions Model Update:
Questions and Answers," EPA-420-F-10-050 (August 2010).
• "Technical Guidance on the Use of MOVES2010 for Emission Inventory Prepara-
tion in State Implementation Plans and Transportation Conformity," EPA-420-B-
10-023 (December 2009). This document provides guidance on appropriate input
assumptions and sources of data for the use of MOVES2010 in SIP submissions
and regional emissions analyses for transportation conformity purposes.
• EPA and FHWA, "Transportation Conformity Guidance for Qualitative Hot-spot
Analyses in PM2.5 and PMio Nonattainment and Maintenance Areas," EPA-420-
B-06-902 (March 2006).
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• EPA and FHWA, "Guidance for the Use of Latest Planning Assumptions in
Transportation Conformity Determinations," EPA-420-B-08-901 (December
2008).
• "Guidance for Developing Transportation Conformity State Implementation
Plans," EPA-420-B-09-001 (January 2009).
• EPA-verified anti-idle technologies (including technologies that pertain to trucks)
can be found at: www. epa. gov/otaq/smartwav/transport/what-smartwav/verified-
technologies.htm#idle.
• For additional information about quantifying the benefits of retrofitting and
replacing diesel vehicles and engines for conformity determinations, see EPA's
website for the most recent guidance on this topic:
www. epa. gov/otaq/stateresources/transconf/policy. htm.
• For additional information about quantifying and using long duration truck idling
benefits for conformity determinations, see EPA's website for the most recent
guidance on this topic: www. epa. gov/otaq/stateresources/transconf/policy. htm.
FHWA's transportation conformity site has additional conformity information, including
examples of qualitative PM hot-spot analyses. Available at:
www. fhwa. dot, gov/environment/air qualitv/conformity/practices/.
A.3 MOVES MODEL TECHNICAL INFORMATION AND USER GUIDES
MOVES, any future versions of the model, the latest user guides, and technical
information can be found at www. epa. gov/otaq/models/moves/index. htm, including the
following:
• "User Guide for MOVES2010a." This guide provides detailed instructions for
setting up and running MOVES2010a. Available at
www.epa.gov/otaq/models/moves/index.htm.
Policy documents and Federal Register announcements related to the MOVES model can
be found on the EPA's website at:
www.epa.gov/otaq/stateresources/transconf/policy.htmtfmodels.
Guidance on using the MOVES model at the project level, as well as illustrative
examples of using MOVES for quantitative PM hot-spot analyses, can be found in
Section 4 of the guidance and in Appendices D, E and F.
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A. 4 EMFAC2007 MODEL TECHNICAL INFORMATION, USER GUIDES, AND
OTHER GUIDANCE
EMFAC2007, its user guides, and any future versions of the model can be downloaded
from the California Air Resources Board website at:
www. arb. ca. gov/msei/onroad/latest version, htm.
Policy documents and Federal Register announcements related to the EMFAC model can
be found on the EPA's website at:
www.epa.gov/otaq/stateresources/transconf/policy.htmtfmodels.
Supporting documentation for EMFAC, including the technical memorandum "Revision
of Heavy Heavy-Duty Diesel Truck Emission Factors and Speed Correction Factors"
cited in Section 5 of this guidance, can be found at
www.arb.ca.gov/msei/supportdocs.htmtfonroad.
Instructions on using the EMFAC model at the project level, as well as examples of using
EMFAC for quantitative PM hot-spot analyses, can be found in Section 5 of the guidance
and in Appendices G and H.
A. 5 DUST EMISSIONS METHODS AND GUIDANCE
Information on calculating emissions from paved roads, unpaved roads, and construction
activities can be found in AP-42, Chapter 13 (Miscellaneous Sources). AP-42 is EPA's
compilation of data and methods for estimating average emission rates from a variety of
activities and sources from various sectors. Refer to EPA's website to access the latest
versions of AP-42 sections and for more information about AP-42 in general:
www.epa.gov/ttn/chief/ap42/index.html.
Guidance on calculating dust emissions for PM hot-spot analyses can be found in Section
6 of the guidance.
A. 6 LOCOMOTIVE EMISSIONS GUIDANCE
The following guidance documents, unless otherwise noted, can be found on or through
the EPA's locomotive emissions website at: www.epa.gov/otaq/locomotives.htm:
• "Procedure for Emission Inventory Preparation - Volume IV: Mobile Sources,"
Chapter 6. Available online at: www.epa.gov/OMS/invntory/r92009.pdf. Note
that the emissions factors listed in Volume IV have been superseded by the April
2009 publication listed below for locomotives certified to meet EPA standards.
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• "Emission Factors for Locomotives," EPA-420-F-09-025 (April 2009). Available
online at: www.epa.gov/otaq/regs/nonroad/locomorv/420f08014.htm.
• "Control of Emissions from Idling Locomotives," EPA-420-F-08-014 (March
2008).
• "Guidance for Quantifying and Using Long Duration Switch Yard Locomotive
Idling Emission Reductions in State Implementation Plans," EPA-420-B-04-002
(January 2004). Available online at:
www. epa. gov/otaq/smartwav/documents/420b04002. pdf.
• EPA-verified anti-idle technologies (including technologies that pertain to
locomotives) can be found at: www. epa. gov/otaq/smartwav/transport/what-
smartwav/verified-technologies.htm#idle.
Guidance on calculating locomotive emissions for PM hot-spot analyses can be found in
Section 6 of the guidance and in Appendix I.
A. 7 AIR QUALITY DISPERSION MODEL TECHNICAL INFORMATION AND
USER GUIDES
The latest version of "Guideline on Air Quality Models" (Appendix W to 40 CFR Part
51) (dated 2005 as of this writing) can be found on EPA's SCRAM website at:
www. epa. gov/scramOO 1 /guidance_permit. htm.
Both AERMOD and CAL3QHCR models and related documentation can be obtained
through EPA's Support Center for Regulatory Air Models (SCRAM) web site at:
www. epa. gov/scramOOl. In particular, the following guidance may be useful when
running these models:
• AERMOD Implementation Guide
• AERMOD User Guide ("User's Guide for the AMS/EPA Regulatory Model -
AERMOD")
• CAL3QHCR User Guide ("User's Guide to CAL3QHC Version 2.0: A Modeling
Methodology for Predicting Pollutant Concentrations Near Roadway
Intersections")
• MPRM User Guide
• AERMET User Guide
A-4
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Information on locating and considering air quality monitoring sites can be found in 40
CFR Part 58 (Ambient Air Quality Surveillance), particularly in Appendices D and E to
that part.
Guidance on selecting and using an air quality model for quantitative PM hot-spot
analyses can be found in Sections 7 and 8 of the guidance and in Appendix J. Illustrative
examples of using an air quality model for a PM hot-spot analysis can be found in
Appendices E and F.
A. 8 TRANSPORTATION DATA AND MODELING CONSIDERATIONS
The following is a number of technical resources on transportation data and modeling
which may help implementers determine the quality of their inputs and the sensitivity of
various data.
A.8.1 Transportation model improvement
The FHWA Travel Model Improvement Program (TMIP) provides a wide range of
services and tools to help planning agencies improve their travel analysis techniques.
Available online at: http://tmip.fhwa.dot.gov/.
A.8.2 Speed
"Evaluating Speed Differences between Passenger Vehicles and Heavy Trucks for
Transportation-Related Emissions Modeling." Available online at:
www. ctre. iastate. edu/reports/truck speed, pdf.
A.8.3 Project level planning
"NCHRP 255: Highway Traffic Data for Urbanized Area Project Planning and Design."
Available online at:
http://tmip.fhwa.dot, gov/sites/tmip.fhwa.dot, gov/files/NCHRP 255.pdf.
A.8.4 Traffic analysis
Traffic Analysis Toolbox website: http://ops.fhwa.dot.gov/trafficanalvsistools/.
"Traffic Analysis Toolbox Volume I: Traffic Analysis Tools Primer." Federal Highway
Administration, FHWA-HRT-04-038 (June 2004). Available online at:
http://ops.fhwa.dot, gov/trafficanalysistools/tat vol 1 /vol 1 primer.pdf.
The Highway Capacity Manual Application Guidebook. Transportation Research Board,
Washington, D.C., 2003. Available online at: http://hcmguide.com/.
A-5
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The Highway Capacity Manual 2000. Transportation Research Board, Washington,
D.C., 2000. Not available online; purchase information available at:
http://144.171.ll.107/Main/Public/Blurbs/Highwav Capacity Manual 2000 152169.asp
x. As of this writing, the 2000 edition is most current; the most recent version of the
manual, and the associated guidebook, should be consulted when completing PM hot-
spot analyses.
A-6
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Appendix B:
Examples of Projects of Local Air Quality Concern
B.I INTRODUCTION
This appendix gives additional guidance on what types of projects may be projects of
local air quality concern requiring a quantitative PM hot-spot analysis under 40 CFR
93.123(b)(l). However, as noted elsewhere in this guidance, PMio nonattainment and
maintenance areas with approved conformity SIPs that include PMio hot-spot provisions
from previous rulemakings must continue to follow those approved conformity SIP
provisions until the SIP is revised; see Appendix C for more information.
B.2 EXAMPLES OF PROJECTS THAT REQUIRE PM HOT-SPOT ANALYSES
EPA noted in the March 2006 final rule that the examples below are considered to be the
most likely projects that would be covered by 40 CFR 93.123(b)(l) and require a PIVb.s
or PMio hot-spot analysis (71 FR 12491).l
Some examples of projects of local air quality concern that would be covered by 40 CFR
93.123(b)(l)(i)and(n)are:
• A project on a new highway or expressway that serves a significant volume of
diesel truck traffic, such as facilities with greater than 125,000 annual average
daily traffic (AADT) and 8% or more of such AADT is diesel truck traffic;
• New exit ramps and other highway facility improvements to connect a highway or
expressway to a major freight, bus, or intermodal terminal;
• Expansion of an existing highway or other facility that affects a congested
intersection (operated at Level-of-Service D, E, or F) that has a significant
increase in the number of diesel trucks; and,
• Similar highway projects that involve a significant increase in the number of
diesel transit busses and/or diesel trucks.
Some examples of projects of local air quality concern that would be covered by 40 CFR
93.123(b)(l)(m)and(iv)are:
• A major new bus or intermodal terminal that is considered to be a "regionally
significant project" under 40 CFR 93.1012; and,
1 EPA also clarified 93.123(b)(l)(i) in the January 24, 2008 final rule (73 FR 4435-4436).
2
40 CFR 93.101 defines a "regionally significant proj ect" as "a transportation proj ect (other than an
exempt project) that is on a facility which serves regional transportation needs (such as access to and from
the area outside of the region, major activity centers in the region, major planned developments such as
new retail malls, sports complexes, etc., or transportation terminals as well as most terminals themselves)
and would normally be included in the modeling of a metropolitan area's transportation network, including
at a minimum all principal arterial highways and all fixed guideway transit facilities that offer an
alternative to regional highway travel."
B-l
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• An existing bus or intermodal terminal that has a large vehicle fleet where the
number of diesel buses increases by 50% or more, as measured by bus arrivals.
A project of local air quality concern covered under 40 CFR 93.123(b)(l)(v) could be any
of the above listed project examples.
B.3 EXAMPLES OF PROJECTS THAT DO NOT REQUIRE PM HOT-SPOT
ANALYSES
The March 2006 final rule also provided examples of projects that would not be covered
by 40 CFR 93.123(b)(l) and would not require a PM2.5 or PMi0 hot-spot analysis (71 FR
12491).
The following are examples of projects that are not a local air quality concern under 40
CFR93.123(b)(l)(i)and(n):
• Any new or expanded highway project that primarily services gasoline vehicle
traffic (i.e., does not involve a significant number or increase in the number of
diesel vehicles), including such projects involving congested intersections
operating at Level-of-Service D, E, or F;
• An intersection channelization project or interchange configuration project that
involves either turn lanes or slots, or lanes or movements that are physically
separated. These kinds of projects improve freeway operations by smoothing
traffic flow and vehicle speeds by improving weave and merge operations, which
would not be expected to create or worsen PM NAAQS violations; and,
• Intersection channelization projects, traffic circles or roundabouts, intersection
signalization projects at individual intersections, and interchange reconfiguration
projects that are designed to improve traffic flow and vehicle speeds, and do not
involve any increases in idling. Thus, they would be expected to have a neutral or
positive influence on PM emissions.
Examples of projects that are not a local air quality concern under 40 CFR
93.123(b)(l)(m) and (iv) would be:
• A new or expanded bus terminal that is serviced by non-diesel vehicles (e.g.,
compressed natural gas) or hybrid-electric vehicles; and,
• A 50% increase in daily arrivals at a small terminal (e.g., a facility with 10 buses
in the peak hour).
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Appendix C:
Hot-Spot Requirements for PM10 Areas with Pre-2006
Approved Conformity SIPs
C.I INTRODUCTION
This appendix describes what projects require a quantitative PMio hot-spot analysis in
those limited cases where a state's approved conformity SIP is based on pre-2006
conformity requirements.1 The March 10, 2006 final hot-spot rule defined the current
federal conformity requirements for what projects require a PM hot-spot analysis (i.e.,
only certain highway and transit projects that involve significant levels of diesel vehicle
traffic or any other project identified in the PM SIP as a local air quality concern).2
However, there are some PMio nonattainment and maintenance areas where PMio hot-
spot analyses are required for different types of projects, as described further below.
This appendix will be relevant for only a limited number of PMio nonattainment and
maintenance areas with pre-2006 approved conformity SIPs. This appendix is not
relevant for any PM2.5 nonattainment or maintenance areas, since the current federal
PM2.5 hot-spot requirements apply in all such areas. Project sponsors can use the
interagency consultation process to verify applicable requirements before beginning a
quantitative PMio hot-spot analysis.
C.2 PMio AREAS WHERE THE PRE-2006 HOT-SPOT REQUIREMENTS APPLY
Prior to the March 2006 final rule, the federal conformity rule required some type of hot-
spot analysis for all non-exempt federally funded or approved projects in PMio
nonattainment and maintenance areas. These pre-2006 requirements are in effect for
those states with an approved conformity SIP that includes the pre-2006 hot-spot
requirements.
In PMio areas with approved conformity SIPs that include the pre-2006 hot-spot
requirements, a quantitative PMio hot-spot analysis is required for the following types of
projects:
• Projects which are located at sites at which PMio NAAQS violations have
been verified by monitoring;
• Projects which are located at sites which have vehicle and roadway emission
and dispersion characteristics that are essentially identical to those of sites
1 A "conformity SIP" includes a state's specific criteria and procedures for certain aspects of the
transportation conformity process (40 CFR 51.390).
See Section 2.2 and Appendix B of this guidance and the preamble of the March 2006 final rule (71 FR
12491-12493).
C-l
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with verified violations (including sites near one at which a violation has been
monitored); and
• New or expanded bus and rail terminals and transfer points which increase the
number of diesel vehicles congregating at a single location.
This guidance should be used to complete any quantitative PMi0 hot-spot analyses.
In addition, a qualitative PMio hot-spot analysis is required in the pre-2006 hot-spot
requirements for all other non-exempt federally funded or approved projects. For such
analyses, consult the 2006 EPA-FHWA qualitative hot-spot guidance.3
These pre-2006 hot-spot requirements continue to apply in PMio areas with approved
conformity SIPs that include them until the state acts to change the conformity SIP. The
conformity rule at 40 CFR 51.390 states that conformity requirements in approved
conformity SIPs "remain enforceable until the state submits a revision to its [conformity
SIP] to specifically remove them and that revision is approved by EPA."
C.3 REVISING A CONFORMITY SIP
EPA strongly encourages affected states to revise pre-2006 provisions and take advantage
of the streamlining flexibilities provided by the current Clean Air Act. EPA's January
2008 final conformity rule significantly streamlined the requirements for conformity SIPs
in 40 CFR 51.390. As a result, conformity SIPs are now required to include only three
provisions (consultation procedures and procedures regarding written commitments)
rather than all of the provisions of the federal conformity rule.
EPA recommends that states with pre-2006 PMio hot-spot requirements in their
conformity SIPs act to revise them to reduce the number of projects where a hot-spot
analysis is required. In affected PMio areas, the current conformity rule's PMio hot-spot
requirements at 40 CFR 93.123(b)(l) and (2) will be effective only when a state either:
• Withdraws the existing provisions from its approved conformity SIP and EPA
approves this SIP revision, or
• Revises its approved conformity SIP consistent with the requirements found at 40
CFR 93.123(b) and EPA approves this SIP revision.
"Transportation Conformity Guidance for Qualitative Hot-spot Analyses in PM2.5 and PMi0
Nonattainment and Maintenance Areas," EPA420-B-06-902, found on EPA's website at:
www.epa.gov/otaq/stateresources/transconf/policy/420b06902.pdf.
4 "Transportation Conformity Rule Amendments to Implement Provisions Contained in the 2005 Safe,
Accountable, Flexible, Efficient Transportation Equity Act: A Legacy for Users (SAFETEA-LU); Final
Rule," 73 FR 4420.
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Affected states should contact their EPA Regional Office to proceed with one of these
two options. For more information about conformity SIPs, see EPA's "Guidance for
Developing Transportation Conformity State Implementation Plans (SIPs)," EPA-420-B-
09-001 (January 2009); available online at:
www.epa.gov/otaq/stateresources/transconf/policy/420b09001.pdf.
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Appendix D:
Characterizing Intersection Projects for MOVES
D.I INTRODUCTION
This appendix expands upon the discussion in Section 4.2 on how best to characterize
links when modeling an intersection project using MOVES. The MOVES emissions
model allows users to represent intersection traffic activity with a higher degree of
sophistication compared to previous models. This appendix provides several options to
describe vehicle activity to take advantage of the capabilities MOVES offers to complete
more accurate PM hot-spot analyses of intersection projects. MOVES is the approved
emissions model for PM hot-spot analyses in areas outside of California.
Exhibit D-l is an example of a simple signalized intersection showing the links
developed by a project sponsor to represent the two general categories of vehicle activity
expected to take place at this intersection (approaching the intersection and departing the
intersection).
Exhibit D-l. Example of Approach and Departure Links for a Simple Intersection
Approach Link
Departure Link
D-l
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When modeling an intersection, each approach link or departure link can be modeled as
one or more links in MOVES depending on the option chosen to enter traffic activity.
This guidance suggests three possible options for characterizing activity on each
approach and departure link (such as those shown in Exhibit D-l):
• Option 1: Using average speeds
• Option 2: Using link drive schedules
• Option 3: Using Op-Mode distributions
While Option 1 may need to be relied upon more during the initial transition to using
MOVES, as more detailed data are available to describe vehicle activity, users are
encouraged to consider using the Options 2 and 3 to take full advantage of the
capabilities of MOVES.
Once a decision has been made on how to characterize links, users should continue to
develop the remaining MOVES inputs as discussed in Section 4 of the guidance.
D.2 OPTION i: USING AVERAGE SPEEDS
The first option is for the user to estimate the average speeds for each link in the
intersection based on travel time and distance. Travel time should account for the total
delay attributable to traffic signal operation, including the portion of travel when the light
is green and the portion of travel when the light is red. The effect of a traffic signal cycle
on travel time includes deceleration delay, move-up time in a queue, stopped delay, and
acceleration delay. Using the intersection example given in Exhibit D-l, each approach
link would be modeled as one link to reflect the higher emissions associated with vehicle
idling through lower speeds affected by stopped delay; each departure link would be
modeled as one link to reflect the higher emissions associated with vehicle acceleration
through lower speeds affected by acceleration delay.
Project sponsors can determine congested speeds by using appropriate methods based on
best practices for highway analyses. Some resources are available through FHWA's
Travel Model Improvement Program (TMIP).l Methodologies for computing
intersection control delay are provided in the Highway Capacity Manual.2 All
assumptions, methods, and data underlying the estimation of average speeds and delay
should be documented as part of the PM hot-spot analysis.
1 See FHWA's TMIP website: http://tmip.fhwa.dot.gov/.
Users should consult the most recent version of the Highway Capacity Manual. As of the release of this
guidance, the latest version is the Highway Capacity Manual 2000, which can be obtained from the
Transportation Research Board (see http://144.171.ll.107/Main/Public/Blurbs/152169.aspx for details).
D-2
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D.3 OPTION 2: USING LINK DRIVE SCHEDULES
A more refined approach is to enter vehicle activity into MOVES as a series of link drive
schedules to represent individual segments of cruise, deceleration, idle, and acceleration
of a congested intersection. A link drive schedule defines a speed trajectory to represent
the entire vehicle fleet via second-by-second changes in speed and highway grade.
Unique link drive schedules can be defined to describe types of vehicle activity that have
distinct emission rates, including cruise, deceleration, idle, and acceleration.
Exhibit D-2 illustrates why using this more refined approach can result in a more detailed
emissions analysis. This exhibit shows the simple trajectory of a single vehicle
approaching an intersection during the red signal phase of a traffic light cycle. This
trajectory is characterized by several distinct phases (a steady cruise speed, decelerating
to a stop for the red light, idling during the red signal phase, and accelerating when the
light turns green). In contrast, the trajectory of a single vehicle approaching an
intersection during the green signal phase of a traffic light cycle is characterized by a
more or less steady cruise speed through the intersection.
Exhibit D-2. Example Single Vehicle Speed Trajectory Through a Signalized
Intersection
50
45
40
35
£• 30
Q.
OJ
OJ
20
15
10
5
0
Green Light
Cruise
Decelerate Idle
Accelerate
Cruise
-100 -80 -60 -40 -20 0 20
Distance (m)
40
60
80
100
For the example intersection in Exhibit D-l, link drive schedules representing the
different operating modes of vehicle activity on the approach and departure links can be
determined. For approach links, the length of a vehicle queue is dependent on the
number of vehicles subject to stopping at a red signal. Vehicles approaching a red traffic
D-3
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signal decelerate over a distance extending from the intersection stop line back to the
stopping distance required for the last vehicle in the queue. The average stopping
distance can be calculated from the average deceleration rate and the average cruise
speed. Similarly, for the departure links, vehicles departing a queue when the light turns
green accelerate over a distance extending from the end of the vehicle queue to the
distance required for the first vehicle to reach the cruise speed, given the rate of
acceleration and cruise speed. Exhibit D-3 provides an illustration of how the different
vehicle operating modes may be apportioned spatially near this signalized intersection.
Exhibit D-3. Example Segments of Vehicle Activity Near a Signalized Intersection
Decelerate
Idle
Accelerate
Cruise
There are other considerations with numerous vehicles stopping and starting at an
intersection over many signal cycles during an hour. For instance, heavy trucks
decelerate and accelerate at slower rates than passenger cars. Drivers tend not to
decelerate at a constant rate, but through a combination of coasting and light and heavy
braking. Acceleration rates are initially higher when starting from a complete stop at an
intersection, becoming progressively lower to make a smooth transition to cruise speed.
In the case of an uncongested intersection, the rates of vehicles approaching and
departing the intersection are in equilibrium. Some vehicles may slow, and then speed up
to join the dissipating queue without having to come to a full stop. Once the queue
clears, approaching vehicles during the remainder of the green phase of the cycle will
cruise through the intersection virtually unimpeded.
In the case of a congested intersection, the rate of vehicles approaching the intersection is
greater than the rate of departure, with the result that no vehicle can travel through
without stopping; vehicles approaching the traffic signal, whether it is red or green, will
have to come to a full stop and idle for one or more cycles before departing the
intersection. The latest Highway Capacity Manual is a good source of information for
D-4
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vehicle operation through signalized intersections. All assumptions, methods, and data
underlying the development of link drive schedules should be documented as part of the
PM hot-spot analysis.
The MOVES emission factors for each segment of vehicle activity obtained via
individual link drive schedules are readily transferable to either AERMOD or
CAL3QHCR, as discussed further in Section 7 of the guidance. There will most likely be
a need to divide the cruise and the acceleration segments to account for differences in
approach and departure traffic volumes.
Note: For both free-flow highway and intersection links, users may directly enter output
from traffic simulation models in the form of second-by-second individual vehicle
trajectories. These vehicle trajectories for each road segment can be input into MOVES
using the Link Drive Schedule Importer and defined as unique LinklDs. There are no
limits in MOVES as to how many links can be defined; however, model run times
increase as the user defines more links. A representative sampling of vehicles can be
used to model higher volume segments by adjusting the resulting sum of emissions to
account for the higher traffic volume. For example, if a sampling of 5,000 vehicles
(5,000 links) was used to represent the driving patterns of 150,000 vehicles, then the sum
of emissions would be adjusted by a factor of 30 to account for the higher traffic volume
(i.e., 150,000 vehicles/5,000 vehicles). Since the vehicle trajectories include idling,
acceleration, deceleration, and cruise, separate roadway links do not have to be
explicitly defined to show changes in driving patterns. The sum of emissions from each
vehicle trajectory (LinkID) represents the total emission contribution of a given road
segment.
D. 4 OPTION 3: USING OP-MODE DISTRIBUTIONS
A third option is for a user to generate representative Op-Mode distributions for approach
and departure links by calculating the fraction of fleet travel times spent in each mode of
operation. For any given signalized intersection, vehicles are cruising, decelerating,
idling, and accelerating. Op-Mode distributions can be calculated from the ratios of
individual mode travel times to total travel times on approach links and departure links.
This type of information could be obtained from Op-Mode distribution data from (1)
existing intersections with similar geometric and operational (traffic) characteristics, or
(2) output from traffic simulation models for the proposed project or similar projects.
Acceleration and deceleration assumptions, methods, and data underlying the activity-to-
Op-Mode calculations should be documented as part of the PM hot-spot analysis.
The following methodology describes a series of equations to assist in calculating vehicle
travel times on approach and departure links. Note that a single approach and single
departure link should be defined to characterize vehicles approaching, idling at, and
departing an intersection (e.g., there is no need for an "idling link," as vehicle idling is
captured as part of the approach link).
D-5
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D.4.1 Approach links
When modeling each approach link, the fraction of fleet travel times in seconds (s) in
each mode of operation should be determined based on the fraction of time spent
cruising, decelerating, accelerating, and idling:
Total Fleet Travel Time (s) = Cruise Time + Decel Time + Accel Time +
Idle Time
The cruise travel time can be represented by the number of vehicles cruising multiplied
by the length of approach divided by the average cruise speed:
Cruise Time (s) = Number of Cruising Vehicles * (Length of Approach (mi) +
Average Cruise Speed (mi/hr)) * 3600 s/hr
The deceleration travel time can be represented by the number of vehicles decelerating
multiplied by the average cruise speed divided by the average deceleration rate:
Decel Time (s) = Number of Decelerating Vehicles * (Average Cruise Speed
(mi/hr) + Average Decel Rate (mi/hr/s))
The acceleration travel time occurring on an approach link can be similarly represented.
However, to avoid double-counting acceleration activity that occurs on the departure link,
users should multiply the acceleration time by the proportion of acceleration that occurs
on the approach link (Accel Length Fraction on Approach):
Accel Time (s) = Number of Accelerating Vehicles * (Average Cruise Speed
(mi/hr) •+ Average Accel Rate (mi/hr/s)) * Accel Length Fraction on
Approach
The idle travel time can be represented by the number of vehicles idling multiplied by the
average stopped delay (average time spent stopped at an intersection):
Idle Time (s) = Number of Idling Vehicles * Average Stopped Delay (s)
Control delay (total delay caused by an intersection) may be used in lieu of average
stopped delay, but control delay includes decelerating and accelerating travel times,
which should be subtracted out (leaving only idle time).
After calculating the fraction of time spent in each mode of approach activity, users
should select the appropriate MOVES Op-Mode corresponding to each particular type of
activity (see Section 4.5.7 for more information). The operating modes in MOVES
typifying approach links include:
• Cruise/acceleration (OpModelD 11-16, 22-25, 27-30, 33, 35, 37-40);
• Low and moderate speed coasting (OpModelD 11,21);
• Braking (OpModelD 0, 501);
D-6
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• Idling (OpModelD 1); and
• Tire wear (OpModelD 400-416).
The relative fleet travel time fractions can be allocated to the appropriate Op-Modes in
MOVES. The resulting single Op-Mode distribution accounts for relative times spent in
the different driving modes (cruise, deceleration, acceleration, and idle) for the approach
link. A simple example of deriving Op-Mode distributions for a link using this
methodology is demonstrated in Step 3 of Appendix F for a bus terminal facility.
D.4.2 Departure links
When modeling each departure link, the fraction of fleet travel times spent in each mode
of operation should be determined based on the fraction of time spent cruising and
accelerating:
Total Fleet Travel Time (s) = Cruise Time + Accel Time
The cruise travel time can be represented by the number of vehicles cruising multiplied
by the travel distance divided by the average cruise speed:
Cruise Time (s) = Number of Cruising Vehicles * (Length of Departure (mi) +
Average Cruise Speed (mi/hr)) * 3600 s/hr
The acceleration travel time occurring during the departure link can be represented by the
number of vehicles accelerating multiplied by the average cruise speed divided by the
average acceleration rate. However, to avoid double-counting acceleration activity that
occurs on the approach link, users should multiply the resulting acceleration time by the
proportion of acceleration that occurs on the departure link (Accel Length Fraction on
Departure):
Accel Time (s) = Number of Accelerating Vehicles * (Average Cruise Speed
(mi/hr) + Average Accel Rate (mi/hr/s)) * Accel Length Fraction on
Departure
After calculating fraction of time spent in each mode of departure activity, users should
select the appropriate MOVES Op-Mode corresponding to each particular type of activity
(see Section 4.5.7 for more information). The operating modes typifying departure links
include:
• Cruise/acceleration (OpModelD 11-16, 22-25, 27-30, 33, 35, 37-40); and
• Tire wear (OpModelD 401-416).
The relative fleet travel time fractions can be allocated to the appropriate Op-Modes. The
resulting single Op-Mode distribution accounts for relative times spent in the different
driving modes (cruise and acceleration) for the departure link.
D-7
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Appendix E:
Example Quantitative PM Hot-spot Analysis of a Highway
Project using MOVES and CAL3QHCR
E.I INTRODUCTION
The purpose of this appendix is to demonstrate the procedures for completing a hot-spot
analysis using MOVES and CAL3QHCR following the basic steps described in Section
3. Readers should reference the appropriate sections in the guidance as needed for more
detail on how to complete each step of the analysis. This example is limited to showing
the build scenario; in practice, project sponsors may also have to analyze the no-build
scenario. While this example calculates emission rates using MOVES, EMFAC users
may find the air quality modeling described in this appendix helpful.
Note: The following example of a quantitative PM hot-spot analysis is highly simplified
and intended only to demonstrate the basic procedures described in the guidance. This
example uses default data in places where the use of project-specific data in a real-world
situation would be expected. In addition, actual PM hot-spot analyses could be
significantly more complex and are likely to require more documentation of data and
decisions. In this example, the interagency consultation process is used as needed for
evaluating and choosing models, methods, and assumptions, according to the
requirements of 40 CFR 93.105(c)(l)(i).
E.2 PROJECT DESCRIPTION AND CONTEXT
The proposed project is the construction of a highway interchange connecting a four-lane
principle arterial with a six-lane freeway through on-and-off ramps (see Exhibit E-l).
The project is being built to allow truck access to local businesses. The project is located
in an area that was designated nonattainment for the 2006 24-hour PM2.5 NAAQS and
1997 annual PM2.5 NAAQS.
The following is some additional pertinent data about the project:
• The project is located in a medium-sized city (within one county) in a state other
than California.
• The project is expected to take less than a year to complete and has an estimated
completion date of 2013. The year of peak emissions is expected to be 2015,
when considering the project's emissions and background concentrations.
• In 2015, the average annual daily traffic (AADT) at this location is expected to
exceed 125,000 vehicles and greater than eight percent of the traffic will be
heavy-duty diesel trucks.
• The area surrounding the proposed project is primarily residential, with no nearby
sources that need to be included in air quality modeling.
E-l
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• The state does not have an adequate or approved SIP budget for either PM2.5
NAAQS, and neither the EPA nor the state air agency has made a finding that
road dust is a significant contributor to the PM2.5 nonattainment problem.
Exhibit E-l. Simple Diagram of the Proposed Highway Project
400 meters
E.3 DETERMINE NEED FOR PM HOT-SPOT ANALYSIS (STEP i)
The proposed project is determined to be of local air quality concern under the
conformity rule because it is a new freeway project with a significant number of diesel
vehicles (see 40 CFR 93.123(b)(l)(i) and Sections 2.2 and Appendix B of the guidance).
Therefore, a quantitative PM hot-spot analysis is required.
E-2
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E.4 DETERMINE APPROACH, MODELS, AND DATA (STEP 2)
E. 4.1 Determining geographic area and emission sources to be covered by the analysis
First, the interagency consultation process is used to ensure that the project area is
defined so that the analysis includes the entire project, as required by 40 CFR
93.123(c)(2). As previously noted, it is also determined that, in this case, there are no
nearby emission sources to be included in air quality modeling (see Section 3.3.2).
E. 4.2 Deciding the general analysis approach and analysis year(s)
Second, the project sponsor determines that the preferred approach in this case is to
model the build scenario first, completing a no-build scenario only if necessary.
In addition, it is determined that the year of peak emissions (within the timeframe of the
current transportation plan) is mostly likely to be 2015. Therefore, 2015 is selected as the
year of the analysis, and the analysis considers traffic data from 2015 (see Section 3.3.3).
E. 4.3 Determining the PMNAAQS to be evaluated
Because the area has been designated nonattainment for both the 2006 24-hour PM2 5
NAAQS and 1997 annual PM2.5 NAAQS, the results of the analysis will have to be
compared to both NAAQS (see Section 3.3.4). All four quarters are included in the
analysis in order to estimate a year's worth of emissions for both NAAQS.
E. 4.4 Deciding on the type ofPM emissions to be modeled
Next, the following directly-emitted PM2.5 emissions are determined to be relevant for
estimating the emissions in the analysis (see Section 2.5):
• Vehicle exhaust1
• Brake wear
• Tire wear
E. 4.5 Determining the models and methods to be used
Since this project is located outside of California, MOVES is used for emissions
modeling. In addition, it is determined that, since this is a highway project with no
nearby sources that need to be included in the air quality modeling, either AERMOD or
CAL3QHCR could be used for air quality modeling (see Section 3.3.6). In this case,
CAL3QHCR is selected. Making the decision on what air quality model to use at this
stage is important so that the appropriate data are collected, among other reasons (see
next step).
1 Represented in MOVES as PM^i™,^ and PMtotei crankcase miming.
E-3
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E. 4.6 Obtaining project-specific data
Finally, the project sponsor compiles the data required to use MOVES, including project
traffic data, vehicle types and age, and temperature and humidity data for the months and
hours to be modeled (specifics on the data collected are described in the following steps).
In addition, information necessary to use CALSQHCRto model air quality is gathered,
including meteorological data and information on representative air quality monitors.
The sponsor also ensures the latest planning assumptions are used and that data used for
the analysis are consistent with that used in the latest regional emissions analysis, as
required by the conformity rule (see Section 3.3.7).
E.5 ESTIMATE ON-ROAD MOTOR VEHICLE EMISSIONS (STEP 3)
Having completed the analysis preparations described above, the project sponsor then
follows the instructions provided in Section 4 of the guidance to use MOVES to estimate
the project's on-road emissions:
E. 5.1 Characterizing the project in terms of links
As described in Section 4.2 of the guidance, links are defined based on the expected
emission rate variability across the project. Generally, a highway project like the one
proposed in this example can be broken into four unique activity modes:
• Freeway driving at 55 mph;
• Arterial cruise at 45 mph;
• Acceleration away from intersections to a cruising speed of 45/55 mph; and
• Cruise, deceleration, and idle/cruise (depending on light timing) at intersections.
Following the guidance given in Section 4.2, 20 links are defined for MOVES and
CAL3QHCR modeling, each representing unique geographic and activity parameters (see
Exhibits E-2 and E-3). Each LinkID is defined with the necessary information for air
quality modeling: link length, link width, link volume, as well as link start and end points
(xl, yl, x2, y2 coordinates).
Decisions on how to best define links are based on an analysis of vehicle activity and
patterns within the project area. AADT is calculated from a travel demand model for
passenger cars, passenger trucks, intercity buses, short haul trucks, and long haul trucks.
From these values, both an average-hour and peak-hour volume is calculated. The
average and peak-hour vehicle counts for each part of the project are shown in Exhibit E-
3.
E-4
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Exhibit E-2. Diagram of Proposed Highway Project Showing Links
LIMK11
LINK4
%
400 meters
Based on the conditions in the project area, for this analysis peak traffic is assumed to be
representative of morning rush hour (AM: 6 a.m. to 9 a.m.) and evening rush hour (PM: 4
p.m. to 7 p.m.), while average hour traffic represents all other hours: midday (MD: 9 a.m.
to 4 p.m.), and overnight (ON: 7 p.m. to 6 a.m.) Identical traffic volume and speed
profiles are assumed for all quarters of the year. Quarters are defined as described in
Section 3.3.4 of the guidance: Ql (January-March), Q2 (April-June), Q3 (July-
September), and Q4 (October-December).
E-5
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Exhibit E-3. Peak-Hour and Average-Hour Traffic Counts for Each Project Link
Freeway
Passenger Cars
Passenger Trucks
Intercity Buses
Short Haul Trucks (gas)
Long Haul Trucks (diesel)
Total
Exit Ramps
Passenger Cars
Passenger Trucks
Intercity Buses
Short Haul Trucks (gas)
Long Haul Trucks (diesel)
Total
Entrance Ramps
Passenger Cars
Passenger Trucks
Intercity Buses
Short Haul Trucks (gas)
Long Haul Trucks (diesel)
Total
Arterial Road
Passenger Cars
Passenger Trucks
Intercity Buses
Short Haul Trucks (gas)
Long Haul Trucks (diesel)
Total
Peak Hour Count
2260
1760
36
60
944
5060
Peak Hour Count
124
124
8
12
300
568
Peak Hour Count
176
148
0
16
276
616
Peak Hour Count
124
116
12
0
316
568
Average Hour Count
452
352
7
12
189
1012
Average Hour Count
25
25
2
2
60
114
Average Hour Count
35
30
0
3
55
123
Average Hour Count
25
23
2
0
63
114
Fraction of Total
0.45
0.35
0.01
0.01
0.19
1.00
Fraction of Total
0.22
0.22
0.01
0.02
0.53
1.00
Fraction of Total
0.29
0.24
0.00
0.03
0.45
1.00
Fraction of Total
0.22
0.20
0.02
0.00
0.56
1.00
A significant amount of traffic using the project is expected to be diesel trucks. While
the freeway contains approximately 19% diesel truck traffic, traffic modeling for the on-
and off-ramps connecting the freeway to the arterial road suggests approximately half of
vehicles are long-haul diesel trucks.
The average speeds on the freeway, arterial, and on/off-ramps are anticipated to be
identical in the analysis year for both peak and average hours and assumed to
approximately reflect the speed limit (55 mph, 45 mph, and 45 mph, respectively).
Traffic flow through the two intersections north and south of the freeway is controlled by
a signalized light with a 60% idle time for vehicles exiting the freeway and 40% idle time
for traffic entering the freeway from the arterial road or traveling north and south on the
E-6
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arterial road passing over the freeway. The total project emissions, therefore, are
determined to be a function of:
• Vehicles traveling east and west on the freeway at a relatively constant 55 mph;
• Exiting vehicles decelerating to a stop at either the north or south signalized
intersection (or continuing through if the light is green);
• Vehicles accelerating away from the signalized intersections north and south, as
well as accelerating to a 55 mph cruise speed on the on-ramps;
• Idling activity at both intersections during the red phase of the traffic light; and
• Vehicles traveling between the north and south intersections at a constant 45 mph.
As there is no new parking associated with the project (e.g., parking lots), there are no
start emissions to be considered. Additionally, there are no trucks parked or "hoteling" in
extended idle mode anywhere in the project area, so extended idle emissions do not need
to be calculated.
E. 5.2 Deciding how to handle link activity
As discussed in Section 4.2 of the guidance, MOVES offers several options for users to
apply activity information to each LinklD. For illustrative purposes, based on the
available information for the project (in this case, average speed, link average and peak
volume, and red-light idle time) several methods of deriving Op-Mode distributions are
employed in this example, as described below.
The links parameter table in Exhibit E-4 shows the various methods that activity is
entered into MOVES for each link. The column "MOVES activity input" describes how
the Op-Mode distribution is calculated for each particular link:
• Freeway links (links 1 and 4) are defined through a 55 mph average speed input,
from which MOVES calculated an Op-Mode distribution (as described in
Appendix D.2).
• Arterial cruise links (links 12 and 18) and links approaching an intersection queue
(links 2, 5, 9 and 15) are defined through a link-drive schedule with a constant
speed of 45 mph; indicating vehicles are cruising at 45 mph, with no acceleration
or deceleration (as described in Appendix D.3).
• Links representing vehicles accelerating away from intersections (links 7, 8, 11,
14, 17, 20) are given "adjusted average speeds" calculated from guidance in the
Highway Capacity Manual 2000, based on the link cruise speed (45 mph or 55
mph), red-light timing, and expected volume to capacity ratios. The adjusted
average speeds (16.6 mph or 30.3 mph) are entered into MOVES, which
calculates an Op-Mode distribution to reflect the lower average speed and
subsequent higher emissions (as described in Appendix D.2).
• Queue links (links 3, 6, 10, 13, 16, and 19) are given an Op-Mode distribution that
represents vehicles decelerating and idling (red light) as well as cruising through
(green light) (as described in Appendix D.4).
Step 1. First, an Op-Mode distribution is calculated for the link average speed
(45 mph).
E-7
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Step 2. Because this does not adequately account for idling at the intersection,
the Op-Mode fractions are re-allocated to add in idling. For instance, after
consulting the Highway Capacity Manual 2000, for this project scenario the
red light timing corresponds to approximately 40% idle time. A fraction of
0.4 for Op-Mode "1" is therefore added to the Op-Mode distribution
calculated from the 45 mph average speed in Step 1. The resulting Op-Mode
distribution represents all activity on a queuing intersection link.
The length of the queue links are estimated as a function of the length of three trucks, one
car, and one passenger truck with two meters in between each car and five meters in
between each truck.
Departure links on the arterial road are assumed to have a link length of 125 meters
(estimated to be the approximate distance that vehicles accelerate to a 45 mph cruising
speed). The departure links from the intersection to the on-ramp are assumed to have a
link length of 200 meters (estimated to be the approximate distance that vehicles
accelerate to a 55 mph cruising speed).
Exhibit E-4. Link Parameters (Peak Traffic)
11 link parameters.xls £]pl(S]
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
A
linkID
1
B C
linkLengt
935
D
E
linkwidth inkVolume inkAvgSpeed
12 5060 55
2| 250 9
3
4
5
6
I
8
87
940
9
12
220 j 9
87
450
'9
9
520 9
9 75] 9
10
11
12
13
14
61
125
190
61
125
15 75
1BJ 61
17
18
19
20
125
189
61
125
9
a
a
9
•9
9
.9
9
9
9
9
568 45
568 45
5060 55
F
adj.
average
speed
n/a
n/a
n/a
n/a
568 45 n/a
5B8
616
616
568
568
568
568
m
5S8
568
568
45
45
45
n/a
16.6
G
inkDescription
EB highway
EB off-ramp cruise
EB off-rarnp queue
WB highway
WB off-rarnp cruise
WB off-ramp queue
EB on-ramp
16.6 WB on-ramp
45 n/a
45
45
45
45
n/a
303
n/a
n/a
45! 30.3
45 n/a
45
568 45
568
568
568
45
45
45
in < > n\link/
n/a
30.3
n/a
n/a
30.3
sNB cruise
sNB queue
sNB depart
MB connect
nNB queue
nNB depart
nSB cruise
nSB queue
nSB depart
SB connect
sSB queue
sSB depart
H
MOVES activity input
average speed
linkdrive schedule
avg spd/opMode
average speed
inkdrive schedule
avg spd/opMode
adj. average speed
adj. average speed
linkdrive schedule
avg spd/opMode
adj. average speed
inkdrive schedule
avg spd/opMode
adj. average speed
linkdrive schedule
avg spd/opMode
adj. average speed
linkdrive schedule
avg spd/opMode
adj. average speed
l<
I
x1
-422
-337
-89
358
315
96
19
-14
26
18
12
9
2
1
-10
-8
-9
-7
-3
2
J
-469
-424
-386
44
29
13
-367
2
-507
-433
-371
-246
-56
5
142
68
6
-122
-311
-371
K
x2
367
-83
-3
-440
96
10
300
-360
L
32
-386
-372
-453
13
I
-13
-386
18 -433
12
9
-3
1
1
-8
-9
-7
-3
-246
-58
6
130
68
6
-311
2| -371
12
-501
V
>
Eo
-O
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E.5.3 Determining the number of MOVES runs
Following the guidance given in Section 4.3, it is determined that 16 MOVES runs
should be completed to produce emission factors that show variation across four hourly
periods (12 a.m., 6 a.m., 12 p.m., and 6 p.m., corresponding to overnight, morning,
midday, and evening traffic scenarios, respectively) and four quarterly periods
(represented by the months of January, April, July, and October; see Section 3.3).
MOVES will calculate values for all project links for the time period specified in each
run. The 16 emission factors produced for each link are calculated as grams/vehicle-
mile, which will then be paired with corresponding traffic volumes (peak or average
hour, depending on the hour) and used in CAL3QHCR.
E.5.4 Developing basic run specification inputs
When configuring MOVES for the analysis, the project sponsor follows Section 4.4 of
the guidance, including, but not limited to, the following:
• From the Scale panel, selecting the "Project" domain; in addition, choosing output
in "Emission Rates," so that emission factors will be in grams/vehicle-mile as
needed for CAL3QHCR (see Section 4.4.2).
• From the Time Spans panel, the appropriate year, month, day, and hour for each
run is selected (see Section 4.4.3).
• From the Geographic Bounds panel, the custom domain is selected (see Section
4.4.4).
• From the Vehicles/Equipment panel, appropriate Source Types are selected (see
Section 4.4.5).
• From the Road Types panel, Urban Restricted and Urban Unrestricted road types
are selected (see Section 4.4.6).
• From the Pollutants and Processes panel, the appropriate pollutant/processes are
selected according to Section 4.4.7 of the guidance for "highway links."
• In the Output panel, an output database is specified with grams and miles selected
as units (see Section 4.4.10).
E. 5.5 Entering project details using the Project Data Manager
Meteorology
As described previously, it is determined that MOVES should be run 16 times to reflect
the following scenarios: 12 a.m., 6 a.m., 12 p.m., and 6 p.m. (corresponding to overnight,
morning, midday, and evening traffic scenarios, respectfully) for the months of January,
April, July, and October. Temperature and humidity data from a representative
meteorological monitoring station are obtained and confirmed to be consistent with data
used in the regional emissions analysis from the currently conforming transportation plan
and TIP (see Section 4.5.1). Average values for each hour and month combination are
used for each of the 16 MOVES runs. As an example, temperature and humidity values
for 12 a.m. January are shown in Exhibit E-5.
E-9
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Exhibit E-5. Temperature and Humidity Input (January 12 a.m.)
S metjanl 2am.xls Q@[5<]
1
2
I 3
4
5
6
_J_
M 4
A
monthID
1
> w\Zo
B
zonelD
990010
neMonthH
C
hourlD
1
our/ Hour
D
E
temperaturrelHurniditi
26.2 75.4
F T
•
..1
OfAi | < > ]
Age Distribution
Section 4.5.2 of the guidance specifies that default data should be used only if an
alternative local dataset cannot be obtained and the regional conformity analysis relies on
national defaults. However, for the sake of simplicity only, in this example the national
default age distribution for 2015 is used for all vehicles and all runs (see Exhibit E-6).
Exhibit E-6. Age Distribution Table (Partial)
m aeedist.xls 00®
1
2
] 3
I 4
! 5
I 6
7
8
9
10
I 11
12
13
14
15
I 16
17
18
I 19
20
21
22
23
A
sourceTyp
21
21
21
21
21
21
B
yearlD
2015
2015
2015
2015
2015
2015
21 | 2015
21
21
21
21
21
21
21
21
21
21
21
21
21
21
21
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
C
agelD
0
1
..2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
D
E
ageFraction
0.0599
0.0609
0.0616
0.0622
0.0620
0.0579
0.0559
0.0556
0.0578
0.0584
0.0591
0.0558.
0.0497
0.0461
0.0404
0.0339
0.0286
0.0215
0.0163
0.0125
0.0109
0.0089
H < > w \soijrceTypeAgeDistribiition / ]<
F | -^
•
-
v
i > r
E-10
-------
Fuel Supply and Fuel Formulation
In this example, it is determined appropriate to use the default fuel supply and
formulation (see Exhibits E-7 and E-8). The default fuel supply and formulation are
imported for each respective quarter (January, April, July, and October) and used for the
corresponding MOVES runs.
Exhibit E-7. Fuel Supply Table
H fuelsupply.xls | _ |(6]d
1
2
3
4
5
6
7
8
9
H <
A
B
countylD fuelYearlD
99001
99001
2015
2015
C
D
E
F
G
monthGroLfuelFormul;marketShsmarketShareCV
1
1
20011
3809
I
1
0.5
0.5
> M \FuelSupplyX! FuelFormulation / County / F |<
H
>
A
V
I
Exhibit E-8. Fuel Formulation Table
H fuclformulation.xls | - || Cl || X |
1
2
3
4
5
C
A
fuelFormul
20011
3809
H < > H / CO
B
fuelSubtyp
20"
12
unty \Fue
C
RVP
|
3.5
Formulatic
D
sulfurLevel
11
23.3286
n/ FuelSu
E
ETOHVolu
Q
10
DP <
F
MTBEVolu
0
0
G
ETBEVolu
0
0
jt,
TA;-
-,
v
J
E-ll
-------
Inspection and Maintenance (I/M)
As there is no PM emissions benefit in MOVES for I/M programs, this menu item is
skipped (see Section 4.5.4).
Link Source Type
The distribution of vehicle types on each link is defined in the Link Source Type table
(Exhibit E-9) following the guidance in Section 4.5.5. The fractions are derived from the
vehicle count estimates in Exhibit E-3.
Exhibit E-9. Link Source Type Table
TsS linksource.xls ].
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
A
B
C
D
n x
ET
linkID sourceTyp sourceTypeHourFraction
1
1
1
1
1
2
2
2
2
2
j^,
3
3
3
3
4
4
21
31
41
61
62
21
31
41
61
62
21
31
41
61
62
21
31
0.45
0.35
0:01
0.01
0.19
0/22
0:22
0.01
0,02
0:53
0:22
0,22
0.01
0:02
0:53
o;45
0.35
H < > H \HnkSourceTy peHour/ Sourc | <
•
m
> \
Links
The Links input table shown in Exhibit E-10 is used to define each individual project link
in MOVES. Road Types 4 and 5 indicate Urban Restricted (freeway) and Urban
Unrestricted (arterial) road types, respectively; these correspond to the two road types
represented in this example. The average speed is entered for all links, but only used to
calculate Op-Mode distributions for links 1, 4, 7, 8, 11, 14, 17, and 20 (other links are
explicitly defined with a link-drive schedule or Op-Mode distribution). Link length and
link volume is entered for each link; however, since the "Emission Rates" option is
selected in the Scale panel, MOVES will produce grams/vehicle-mile. The volume and
link length will become relevant when running the air quality model later in this analysis.
E-12
-------
Exhibit E-10. Links Input (AM Period)
SI links xb |T
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
94
H 1
A
linkID
1
2
B
countylD
99001
99001
3! 99001
4
5
6
99001
99001
99001
7 j 99001
8 i 99001
8
10
99001
99001
1 1 99001
12 99001
13
14
15
99001
99001
99001
16 99001
17 99001
18| 99001
19
20
> n\lrn
99001
99001
:/^ County
C
zonelD
990010
990010
990010
990010
990010
990010
990010
990010
990010
990010
990010
990010
990010
990010
990010
990010
990010
990010
990010
990010
/ RoadTyp
D I E
roadTypelD
4J
5
5
4
5
5
5
5
6
5
fi
S
6
5
5
6
5
i
5
5
F
linkLenglh NnkVolume
0.58
0.16
o:os
0.5B
0.14
0:05
OI28
0.32
0.05
0.04
O.DB
0.12
0.04
o:os
0.05
0.04
0.08
0.12
0.04
0.08
5060
568
568
50BO
568
568
616
616
568
568
568
568
568
568
568
568
568
568
568
568
3 /Zone/ DB,_
G
NnkAvgSpeed
55
45
45
H
linkDescription
EB highway
EB off-ramp cruise
EB off-ramp queue
0S
hr
55 WB highway
45 WB off-ramp cruise
45 WB off-ramp queue
16.6
EB on-ramp
16.6 WB on-ramp
45
45
30.3
45
45
30.3
45
45
30.3
45
45
30.3
sNB cruise
sNB queue
sNB depart
NB connect
nNB queue
nNB depart
nSB cruise
nSB queue
nSB depart
SB connect
sSB queue
sSB depart
>]
The remaining links are defined with an Op-Mode distribution (Exhibit E-l 1) calculated
separately, as discussed earlier. Operating modes used in this analysis vary by both link
and source type, but not by hour or day.
Exhibit E-ll. Operating Mode Distribution Table (Partial)
Hopmode.xls ]- |]n||X|
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
HQ
H 4
A
sourceTyp
21
21
21
21
21
21
21
21
21
21
21
21
21
21
21
21
21
21
21
21
21
21
21
B
c
hourDaylD linkID
15
15
IS
15
15
|g
g
15
15
IS:
||
g
15
15
15
15
15
15
IS
15
1
1
1
1
1
1
1
1
1
1:
1
1
i
i
i
T
1
1
1
1
15 1
15
g
21 1 15
~H i 1C.
> w \Op_modexS
1
t
1
D
E
polProcessopModelD
9101 35
9101
9101
9101
9101
9101
9190
9190
9190
9190
9190
9190
11001
11001
11001
11001
11001
11001
11015
11015
11015
11015
11015
11015
•f. ijrn-7
heet2 / Sheets /
40
38
39
0
33
35
40
38
39
0
m
35
40
38
39
0
33
35
40'
38
39
|
33
T<
F
G
opModeFraction
0.2
0.28
.0.08
0.08
0.2.
0.16
Ov2
0.28
0.08
0.08
0.2
0.16
0.2
:o.28
0.08
0.08
0.2
0.16
0;2
0.28
0.08!
:O.OB
0.2
0.16 1
n *il
H
>
A
£
E-13
-------
Off-Network
As it was determined that there are no off-network links (such as parking lots or truck
stops) that would have to be considered using the Off-Network Importer, there is no need
to use this option in this example.
E.5.6 Generating emission factors for use in air quality modeling
After generating the run specification and entering the required information into the
Project Data Manager as described above, MOVES is run 16 times, once for each unique
hour/month combination. Upon completion of each run, the MOVES output is located in
the MySQL output database table "rateperdistance" and sorted by Month, Hour, LinkID,
ProcessID, and PollutantlD. An aggregate PM2.5 emission factor is then calculated by the
project sponsor for each Month, Hour, and LinkID combination using the following
equation and the guidance given in Section 4.4.7 of the guidance:2
PMaggregate totai = (PMtotai running) + (PMtotai crankcase running) + (brake wear) + (tire wear)
The 16 resulting grams/vehicle-mile emission factors (Exhibit E-12) for each link are
then ready to be used as input into the CAL3QHCR dispersion model to predict future
PM2 5 concentrations.
EPA is considering creating one or more MOVES scripts that would automate the summing of aggregate
emissions when completing project-level analyses. These scripts would be made available for download on
the MOVES website (www.epa.gov/otaq/models/moves/tools.htm'), when available.
E-14
-------
Exhibit E-12. Grams/Vehicle-Mile Emission Factors Calculated from MOVES
Output by Link, Quarter, and Hour
Houtput_summary.xls [_ ](n]fS n\ Output \gramspervehiclemile /
0.333 0.331 0.331
G
Apr12am
0.098
0.371
0.246
0.098
0.371
0.246
0.498
0.498
0.396
0.316
0.346
0.396
0.316
0.346
0.396
0.316
0.346
0.396
0.316
0.346
Oct12am
0.096
0.370
0.244
0.096
0.370
0.244
0.489
0.489
0.395
0.313
0.340
0.395
H
Apt6am
0.103
0.372
0.249
0.103
0.372
0.249
0.507
0.507
0.397
0.320
0.350
0.397
0.320
0.350
I
Apr12pm
0.090
0.371
0.242
0.090
0.371
0.242
0.484
0.484
0.396
0.309
0.340
0.396
0.309
0.340
0.397 1 0.396
0.320 0.309
0.350 0.340
0:397" 0.396
0.320
0.350
Oct6am
0.099
0.371
0.247
0.099
0.371
J I -rl
Apr6pm
0.089
0.370
0.241
0.089
0.370
0.241
0.482
0.482
0.395
0.308
0.339
0.395
0.308
0.339
0.395
0.308
0.339
0.395
0.309 0.308
0.340 0.339
Oct12pm
0.088
0.370
0.240
0.088
0.370
0:247 0.240
0.495
0.495
0.396
0.316
0.343
0.475
0.475
0.394
0.306
0.334
0.396 0.394
0.3131 0.316
0.340
0.395
0.343
0.396
0.306
Oct6pm
0.088
0.370
0.240
0.088
0.370
0.240
0.476
0.476
0.395
0.307
0.334
0.395
0.307
0.334J 0.334
0.394
0.395
0.3131 0.3161 0.3061 0-307
0.340
0.395
0.313
0.340
CAL3QHCR Inputs / |<
0.343
0.396
0.316
0.343
0.334
0.394
0.306
0.334
0.334
0.395
0.307
0.334
V
>l
E-15
-------
E.6 ESTIMATE EMISSIONS FROM ROAD DUST, CONSTRUCTION, AND
ADDITIONAL SOURCES (STEP 4)
E. 6.1 Estimating re-entrained road dust
In this case, this area does not have any adequate or approved SIP budgets for either
PM2 5 NAAQS, and neither the EPA nor the state air agency have made a finding that
road dust emissions are a significant contributor to the air quality problem for either
PM2.5 NAAQS. Therefore, PIVb.s emissions from road dust do not need to be considered
in this analysis (see Sections 2.5.3 and 6.2).
E. 6.2 Estimating transportation-related construction dust
The construction of this project will not occur during the analysis year. Therefore,
emissions from construction dust are not included in this analysis (see Sections 2.5.5 and
6.4).
E. 6.3 Estimating additional sources of emissions in the project area
It is determined that the project area in the analysis year does not include locomotives or
other nearby emission sources that have to be considered in the air quality modeling (see
Section 6.6).
E.7 SELECT AN AIR QUALITY MODEL, DATA INPUTS, AND RECEPTORS
(STEP 5)
E. 7.1 Characterizing emission sources
As discussed previously, the CAL3QHCR model is selected to estimate PIVb.s
concentrations for this analysis (see Section 7.3). Each link is defined in CAL3QHCR
with coordinates and dimensions matching the project parameters (shown in Exhibit E-4).
The necessary inputs for link length, traffic volume, and corresponding link emission
factor are also added using the CAL3QHCR Tier II approach. Each MOVES emission
factor (12 a.m., 6 a.m., 12 p.m., and 6 p.m.) and traffic volume (average or peak) for each
link is applied to multiple hours of the day, as follows:
• Morning peak (AM) emissions based on traffic data and meteorology occurring
between 6 a.m. and 9 a.m.;
• Midday (MD) emissions based on data from 9 a.m. to 4 p.m.;
• Evening peak (PM) emissions based on data from 4 p.m. to 7 p.m.;
• Overnight (ON) emissions based on data from 7 p.m. to 6 a.m.
In addition, these factors are applied to each of the four quarters being modeled.
E-16
-------
CAL3QHCR scenarios are built to model traffic conditions for all 24 hours of a weekday
in each quarter (partial elements of the CAL3QHCR input file can be found in Exhibits
E-13a and 13b, as file requires one to scroll down the screen): in all, four separate
scenarios.
Exhibit E-13a. CAL3QHCR Quarter 1, 6 a.m. Input File (Partial)
C' highway_jan.lNP - Notepad
File Edit
Format View Help
'Hot-Spot Highway Exampl
1 1 98
94823
1 1 'U
'!'
'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'
'34'
'35'
'36'
'37'
'38'
'39'
'40'
'41'
12 31 98
^8 94823 98
-42.9 -20
-28.8 -3.1
-16. 5 29
-16.5 48.8
29.6 31.8
12.7 -101
-14.6 -100.1
15.5 -152.9
-14.6 -154.7
-12.7 -220.7
17.4 -205.6
-11.8 -265.9
21.2 -257.4
19.3 -334.7
35.3 -333.7
34.4 -317.7
-21.2 -395.9
-23.1 -349.7
24 -13.1
-31.6 15.8
-3.3 -435.5
12.7 -7.8
24 -379
28.7 -411
45.7 -353.5
-9.9 -360.1
-12.7 -320.5
-42.9 -365.8
-19.3 -21
-22.2 -57.7
10.8 19.6
46.6 20.5
10.8 52.5
13.6 -32.3
48.5 -6.8
-7.1 -386.5
-43.8 -394
-6.2 -410
43.8 -387.4
-33.5 -38.9
33.4 -432.7
jL-jLJ
1
e' 60. 175. 0. 0. 41 1 0 <*;
1.8
1.8
1.8
1.8
1.8
1.8
1.8
1.8
1.8
1.8
1.8
1.8
1.8
1.8
1.8
1.8
1.8
1.8
1.8
1.8
1.8
1.8
1.8
1.8
1.8
1.8
1.8
1.8
1.8
1.8
1.8
1.8
1.8
1.8
1.8
1.8
1.8
1.8
1.8
1.8
1.8|
E-17
-------
Exhibit E-13b. CAL3QHCR Quarter 1, 6 a.m. Input File (Partial)
P highwayJan.lNP - Notepad [_ IfnJfX
File Edit Format
View Help
2 'P'
1111111
'Example Highway Project'
1 1
' EB highway'
2 1
1 EB off -ramp
3 1
1 EB off -ramp
4 1
'WB highway'
5 1
'WB off -ramp
6 1
'WB off -ramp
7 1
1 EB on-ramp'
8 1
'WB on-ramp'
9 1
'SNB cruise'
10 1
'sNB queue'
11 1
'SNB depart'
12 1
' NB connect '
13 1
'nNB queue'
14 1
' nNB depart '
15 1
' nSB cruise'
16 1
' nSB queue'
17 1
' nSB depart '
18 1
1 SB connect '
19 1
'SSB queue'
20 1
'SSB depart'
01 0.0
1
2
3
4
5
6
7
8
9
10
11
'ag'
cruise'
queue'
'ag'
cruise'
queue'
'ag'
'ag'
'ag'
'ag'
'ag'
'br'
'ag'
'ag1
'ag'
'ag'
'ag'
'br'
'ag'
'ag'
5060
568
568
5060
568
568
616
616
568
568
568
-422
'ag1
'ag1
358
'ag1
'ag1
19
-14
26
18
12
9
2
1
-10
-8
-9
-7
~3
2
0.1214
0.3737
0. 2605
0.1214
0.3737
0.2605
0. 5392
0. 5392
0.3985
0.3356
0. 3642
20
367
-337
-89
-440
315
96
300
-360
18
12
9
2
1
1
-8
-9
-7
-3
2
12
-469
-89
-3
44
96
10
-367
2
-507
-433
-371
-246
-56
5
142
68
6
-122
-311
-371
32
-424
-386
-453
29
13
-13
-386
-433
-371
-246
-56
5
130
68
6
-122
-311
-371
-501
0
-386
-372
0
13
7
0
0
0
0
0
0
0
0
0
0
0
0
0
0
A
12
12
0 9
0 9
9
9
9
9
9
9
9
9
9
9
9
9
9
9
11
Section 7.5 of the guidance recommends that users run the air quality model for five
years of meteorological data when site-specific meteorology data is not available. Since
CAL3QHCR can only process one year of meteorological data for each run, each
quarterly scenario is run for five years of meteorological data for a total of 20 runs.3
3 As explained in Section 7, AERMOD allows five years of meteorological data to be modeled in a single
run (see Section 7.5.3)
E-18
-------
E. 7.2 Incorporating meteorological data
A representative set of meteorology data, as well as an appropriate surface roughness, are
selected (see Section 7.5). The recommended five years of meteorological data are
obtained from a local airport for calendar years 1998-2002. A surface roughness of 175
cm is selected for the site, consistent with the recommendations made in the Section 7.
E. 7.3 Placing receptors
Using the guidance given in Section 7.6, receptors are placed at appropriate locations
within the area substantially affected by the project (Exhibit E-14).4 Note that this grid is
shown for illustrative purposes only; placement, location, and spacing of actual receptors
should follow the guidance in Section 7.6. Receptor heights are set at 1.8 meters.
Additionally, a background concentration of "0" is input into the model. Representative
background concentrations are added later (see Step 7).
CAL3QHCR is then run with five years of meteorological data (1998 through 2002) and
output is produced for all receptors for each of the five years of meteorological data.
Exhibit E-14. Receptor Locations for Air Quality Modeling
400 meters
1 The number and arrangement of receptors used in this example are simplified for ease of explanation.
E-19
-------
E.8 DETERMINE BACKGROUND CONCENTRATIONS FROM NEARBY AND
OTHER EMISSION SOURCES (STEP 6)
Through the interagency consultation process, a nearby upwind PM2.5 monitor that has
been collecting ambient data for both the annual and 24-hour PIVb.s NAAQS is
determined to be representative of the background air quality at the project location. The
most recent data set is used (in this case, calendar year 2008 through 2010) and average
24-hour PM2 5 values are taken in a four-day/three-day measurement interval. As
previously noted, no nearby sources needing to be included in the air quality model are
identified.
Note: This is a highly simplified situation for illustrative purposes; refer to Section 8 of
the guidance for additional considerations for how to most accurately reflect background
concentrations in a real-world scenario.
E-20
-------
E.9 CALCULATE DESIGN VALUES AND DETERMINE CONFORMITY (STEP 7)
With both CAL3QHCR outputs and background concentrations now available, the
project sponsor can calculate the design values. For illustrative purposes, calculations for
a single receptor with the highest modeled concentrations for the build scenario are
shown in this example.5 In this step, the guidance from Sections 9.3.2 and 9.3.3 are used
to calculate design values from the modeled results and the background concentrations
for comparison with the annual and 24-hour PIVb.s NAAQS.
E. 9. 1 Determining conformity to the annual PM2.s NAAQS
First, average background concentrations are determined for each year of monitored data
(shown in Exhibit E-15).
Exhibit E-15. Annual Average Background Concentration for Each Year
Monitoring
Year
2008
2009
2010
Annual Average
Background
Concentration
13.348
12.785
13.927
The three-year average background concentration is then calculated (see Exhibit E-16).
Exhibit E-16. Calculation of Annual Design Value (At Highest Receptor)
Annual Average
Background
Concentration
(Three-year
Average)
13.353
Annual Average
Modeled
Concentration
(Five-year
Average)
1.580
Sum of
Background +
Project
14.933
Annual Design Value
14.9
In an actual PM hot-spot analysis, design values would be calculated at additional receptors as described
in Section 9.3.
E-21
-------
To determine the annual PIVb.s design value, the annual average background
concentration is added to the five-year annual average modeled concentration (at the
receptor with the highest annual average concentration from the CAL3QHCR output).
This calculation is shown in Exhibit E-16. The sum (project + background) results in a
design value of 14.9 |J,g/m3. This value at the highest receptor is less than the 1997
annual PM2 5 NAAQS of 15.0 |J,g/m3. It can be assumed that all other receptors with
lower modeled concentrations will also have design values less than this NAAQS. In this
example it is unnecessary to determine appropriate receptors in the build scenario (per
Section 9.4 of the guidance) or develop a no-build scenario for the annual PM2.5 NAAQS,
since the build scenario demonstrates that the hot-spot analysis requirements in the
transportation conformity rule are met at all receptors.
E.9.2 Determining conformity to the 24-Hour PM2.sNAAQS
The next step is to calculate a design value to compare with the 2006 24-hour PIVb.s
NAAQS through a "Second Tier" analysis as described in Section 9.3.3. For ease of
explanation, this process has been divided into individual steps, consistent with the
guidance.
Step 7.1
The number of background measurements is counted for each year of monitored data
(2008 to 2010). Based on a 4-day/3-day measurement interval, the dataset has 104 values
per year.
Step 7.2
For each year of monitored concentrations, the eight highest daily background
concentrations for each quarter are determined, resulting in 32 values (4 quarters; 8
concentrations/quarter) for each year of data (shown in Exhibit E-17).
Step 7.3
Identify the highest-predicted modeled concentration resulting from the project in each
quarter, averaged across each year of meteorological data used for air quality modeling.
For illustrative purposes, the highest average concentration across five years of
meteorological data for a single receptor in each quarter is shown in Exhibit E-18. Note
that, in a real-world situation, this process would be repeated for all receptors in the build
scenario.
E-22
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Exhibit E-17. Highest Daily Background Concentrations for Each Quarter and
Each Year
2008
Rank
1
2
3
4
5
6
7
8
Q1
20.574
20.152
19.743
19.346
18.961
18.588
18.226
17.874
Q2
21.262
20.823
20.398
19.985
19.584
19.196
18.819
18.454
Q3
22.354
22.042
21.735
21.434
21.140
20.851
20.568
20.291
Q4
20.434
20.016
19.611
19.218
18.837
18.467
18.109
17.761
2009
Rank
1
2
3
4
5
6
7
8
Q1
20.195
19.784
19.386
19.000
18.625
18.262
17.910
17.568
Q2
20.867
20.440
20.026
19.624
19.235
18.857
18.490
18.135
Q3
21.932
21.628
21.329
21.037
20.750
20.469
20.194
19.924
Q4
20.058
19.651
19.257
18.875
18.504
18.145
17.796
17.457
2010
Rank
1
2
3
4
5
6
7
8
Q1
21.137
20.698
20.272
19.860
19.459
19.071
18.694
18.329
Q2
21.847
21.390
20.948
20.519
20.102
19.698
19.307
18.927
Q3
22.980
22.655
22.336
22.023
21.717
21.417
21.123
20.834
Q4
20.990
20.556
20.135
19.726
19.330
18.945
18.572
18.211
Exhibit E-18. Five-year Average 24-hour Modeled Concentrations for Each Quarter
(At Example Receptor)
Five Year Average
Maximum
Concentration (At
Example Receptor)
Q1
10.42
Q2
10.62
Q3
10.74
Q4
10.61
E-23
-------
Step 7.4
The highest modeled concentration in each quarter (from Step 7.3) is added to each of the
eight highest monitored concentrations for the same quarter for each year of monitoring
data (from Step 7.2). As shown in Exhibit E-19, this step results in eight concentrations
in each of four quarters for a total of 32 values for each year of monitoring data. As
mentioned, this example analysis shows only a single receptor's values, but project
sponsors may need to calculate design values at all receptors in the build scenario (see
Section 9.3 of the guidance).
Exhibit E-19. Sum of Background and Modeled Concentrations at Example
Receptor for Each Quarter
2008
Rank
1
2
3
4
5
6
7
8
Q1
31.084
30.662
30.253
29.856
29.471
29.098
28.736
28.384
Q2
31.902
31.463
31.038
30.625
30.224
29.836
29.459
29.094
Q3
32.994
32.682
32.375
32.074
31.780
31.491
31.208
30.931
Q4
31.074
30.656
30.251
29.858
29.477
29.107
28.749
28.401
2009
Rank
1
2
3
4
5
6
7
8
Q1
30.705
30.294
29.896
29.510
29.135
28.772
28.420
28.078
Q2
31.507
31.080
30.666
30.264
29.875
29.497
29.130
28.775
Q3
32.572
32.268
31.969
31.677
31.390
31.109
30.834
30.564
Q4
30.698
30.291
29.897
29.515
29.144
28.785
28.436
28.097
2010
Rank
1
2
3
4
5
6
7
8
Q1
31.647
31.208
30.782
30.370
29.969
29.581
29.204
28.839
Q2
32.487
32.030
31.588
31.159
30.742
30.338
29.947
29.567
Q3
33.620
33.295
32.976
32.663
32.357
32.057
31.763
31.474
Q4
31.630
31.196
30.775
30.366
29.970
29.585
29.212
28.851
E-24
-------
Step 7.5
As shown in Exhibit E-20, for each year of monitoring data, the 32 values from Step 7.4
are ordered together in a column and assigned a yearly rank for each value, from 1
(highest concentration) to 32 (lowest concentration).
Exhibit E-20. Ranking Sum of Background and Modeled Concentrations at
Example Receptor for Each Year of Background Data
Rank
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
2008
32.994
32.682
32.375
32.074
31.902
31.780
31.491
31.463
31.208
31.084
31.074
31.038
30.931
30.662
30.656
30.625
30.253
30.251
30.224
29.858
29.856
29.836
29.477
29.471
29.459
29.107
29.098
29.094
28.749
28.736
28.401
28.384
2009
32.572
32.268
31.969
31.677
31.507
31.390
31.109
31.080
30.834
30.705
30.698
30.666
30.564
30.294
30.291
30.264
29.897
29.896
29.875
29.515
29.510
29.497
29.144
29.135
29.130
28.785
28.775
28.772
28.436
28.420
28.097
28.078
2010
33.620
33.295
32.976
32.663
32.487
32.357
32.057
32.030
31.763
31.647
31.630
31.588
31.474
31.208
31.196
31.159
30.782
30.775
30.742
30.370
30.366
30.338
29.970
29.969
29.947
29.585
29.581
29.567
29.212
29.204
28.851
28.839
E-25
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Step 7.6
For each year of monitoring data, the value with a rank that corresponds to the projected
98th percentile concentration is determined. As discussed in Section 9, an analysis
employing 101-150 background values for each year (as noted in Step 7.1, this analysis
uses 104 values per year) uses the 3rd highest rank to represent a 98th percentile. The 3rd
highest concentration (highlighted in Exhibit E-20) is referred to as the "projected 98th
percentile concentration."
Steps 7.1 through 7.6 are repeated to calculate a projected 98th percentile concentration at
For the example receptor, the average of the three projected 98th percentile concentrations
Step 7.7
Steps 7.1
each receptor based on each year of monitoring data and modeled concentrations.
Step 7.8
For the e
(see Step 7.6) is calculated.
Step 7.9
The resulting value of 32.440 |J,g/m3 is then rounded to the nearest whole |J,g/m3, resulting
in a design value at the example receptor of 32 |J,g/m3. At each receptor this process
should be repeated. In the case of this analysis, the example receptor is the receptor with
the highest design value in the build scenario.
Step 7.10
The design values calculated at each receptor are compared to the NAAQS. In the case
of this example, the highest 24-hour design value (32 |J,g/m3) is less than the 2006 24-
hour PM2.5 NAAQS of 35 |J,g/m3. Since this is the design value at the highest receptor, it
can be assumed that the conformity requirements are met at all receptors in the build
scenario. Therefore, it is unnecessary for the project sponsor to calculate design values
for the no-build scenario for the 24-hour NAAQS.
E.10 CONSIDER MITIGATION AND CONTROL MEASURES (STEP 8)
In this case, the project is determined to conform. In situations when this is not the case,
it may be necessary to consider additional mitigation or control measures. If measures
are considered, additional air quality modeling would need to be completed and new
design values calculated to ensure that conformity requirements are met. See Section 10
for more information, including some specific measures that might be considered.
E. 11 DOCUMENT THE PM HOT-SPOT ANALYSIS (STEP 9)
The final step is to properly document the PM hot-spot analysis in the conformity
determination (see Section 3.10).
E-26
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Appendix F:
Example Quantitative PM Hot-spot Analysis of a Transit
Project using MOVES and AERMOD
F.I INTRODUCTION
The purpose of this appendix is to demonstrate the procedures for completing a hot-spot
analysis using MOVES and AERMOD following the basic steps described in Section 3.
Readers should reference the appropriate sections in the guidance as needed for more
detail on how to complete each step of the analysis. This example is limited to showing
the build scenario; in practice, project sponsors may have to also analyze the no-build
scenario. While this example calculates emission rates using MOVES, EMFAC users
may find the air quality modeling described in this appendix helpful.
Note: The following example of a quantitative PM hot-spot analysis is highly simplified
and intended only to demonstrate the basic procedures described in the guidance. This
example uses default data in places where the use of project-specific data in a real-world
situation would be expected. In addition, actual PM hot-spot analyses could be
significantly more complex and are likely to require more documentation of data and
decisions. In this example, the inter agency consultation process is used as needed for
evaluating and choosing models, methods, and assumptions, according to the
requirements of 40 CFR 93.105(c)(l)(i).
F.2 PROJECT DESCRIPTION AND CONTEXT
The proposed project is a new regionally significant bus terminal that would be created
by taking a downtown street segment one block in length and reserving it for bus use
only. It would be an open-air facility containing six "sawtooth" lanes where buses enter
to load and unload passengers. The terminal is designed to handle about 575 diesel buses
per day with up to 48 buses in the peak hour. The project is located in an area designated
nonattainment for the 2006 24-hour PM2.5 NAAQS and 1997 annual PM2.5 NAAQS.
The following is some additional pertinent data about the project:
• The proposed project is located in a medium-size city (within one county) in a
state other than California.
• The project is expected to take less than a year to complete and has an estimated
completion date of 2013. The year of peak emissions is expected to be 2015,
when considering the project's emissions and background concentrations.
• The area surrounding the proposed project is primarily commercial, with no
nearby sources of PM2.5 that need to be modeled. This assumption is made to
simplify the example. In most cases, transit projects include parking lots with
emissions that would be considered in a PM hot-spot analysis.
F-l
-------
The state does not have an adequate or approved SIP budget for either PM2.5
NAAQS, and neither the EPA nor the state air quality agency has made a finding
that road dust is a significant contributor to the PM2 5 nonattainment problem.
F.3 DETERMINE NEED FOR PM HOT-SPOT ANALYSIS (STEP i)
The proposed project is determined to be of local air quality concern under the
conformity rule because it is a new bus terminal that has a significant number of diesel
vehicles congregating at a single location (see 40 CFR 93.123(b)(l)(iii) and Section 2.2
and Appendix B of the guidance). Therefore, a quantitative PM hot-spot analysis is
required.
F.4 DETERMINE APPROACH, MODELS, AND DATA (STEP 2)
F. 4.1 Determining geographic area and emission sources to be covered by the analysis
First, the interagency consultation process is used to ensure that the project area is
defined so that the analysis includes the entire project, as required by 40 CFR
93.123(c)(2). As previously noted, it is also determined that, in this case, there are no
nearby emission sources to be modeled (see Section 3.3.2).
F. 4.2 Deciding the general analysis approach and analysis year(s)
The project sponsor then determines that the preferred approach in this case is to model
the build scenario first, completing a no-build scenario only if necessary.
The year of peak emissions (within the timeframe of the current transportation plan) is
determined to be 2015. Therefore, 2015 is selected as the year of the analysis, and the
analysis will consider traffic data from 2015 (see Section 3.3.3).
F. 4.3 Determining the PM NAAQS to be evaluated
Because the area has been designated nonattainment for both the 2006 24-hour PM2.5
NAAQS and 1997 annual PM2.5 NAAQS, the results of the analysis will be compared to
both NAAQS (see Section 3.3.4). All four quarters are included in the analysis in order
to estimate a year's worth of emissions for both NAAQS.
F-2
-------
F. 4.4 Deciding on the type ofPM emissions to be modeled
Next, the following directly-emitted PM emissions are determined to be relevant for
estimating the emissions in the analysis (see Section 2.5):
• Vehicle exhaust1
• Brake wear
• Tire wear
F. 4.5 Determining the models and methods to be used
Since this project will be located outside of California, MOVES is used for emissions
modeling. In addition, it is determined that, since this is a terminal project, the
appropriate air quality model to use would be AERMOD (see Section 3.3.6). Making the
decision on what air quality model to use at this stage is important so that the appropriate
data are collected, among other reasons (see next step).
F. 4.6 Obtaining project-specific data
Finally, having selected a model and a general modeling approach, the project sponsor
compiles the data required to use MOVES, including project traffic data, vehicle types
and age, and temperature and humidity data for the months and hours to be modeled
(specifics on the data collected are described in the following steps). In addition,
information required to use AERMOD to model air quality is gathered, including
meteorological data and information on representative air quality monitors. The sponsor
ensures the latest planning assumptions are used and that data used for the analysis are
consistent with that used in the latest regional emissions analysis, as required by the
conformity rule (see Section 3.3.7).
F.5 ESTIMATE ON-ROAD MOTOR VEHICLE EMISSIONS (STEP 3)
Having completed the analysis preparations described above, the project sponsor then
follows the instructions provided in Section 4 of the guidance to use MOVES to estimate
the on-road emissions from this terminal project:
F.5.1 Characterizing the project in terms of links
Using the guidance described in Section 4.2, a series of links are defined in order to
accurately capture the activity at the proposed terminal. As shown in Exhibit F-l, two
one-way running links north and south of the facility ("Link 1" and "Link 2") are defined
to describe buses entering and exiting the terminal. A third running/idle link (shown as
"Link 3" to the north of the facility), is used to describe vehicles idling at the signalized
1 Represented in MOVES as PMtotai mlmmg, PMtotal crankcase running, PMtotal ext. ldie, and PMtotal cmlkcase ext. idle.
F-3
-------
light before exiting the facility. Links 4 through 9 represented bus bays where buses
drop-off and pick-up passengers; these are referred to as the terminal links.2
Exhibit F-l. Diagram of Proposed Bus Terminal Showing Links
um.2
m -
50 feet
The running links have the following dimensions:
Link 1: 200 feet long by 24 feet wide
Link 2: 160 feet long by 24 feet wide
Link 3: 40 feet long by 24 feet wide
Additionally, the dimensions of the six terminal links (Links 4 through 9) are 60 feet long
by 12 feet wide. These links are oriented diagonally from southwest to northeast. The
queue link (Link 3) is defined with a length of 40 feet, based on the average length of a
transit bus.
After identifying and defining the links, traffic conditions are estimated for the project in
the analysis year of 2015. The terminal was presumed to be in operation all hours of the
year. Based on expected terminal operations, the anticipated future traffic volumes are
available for each hour of an average weekday (see Exhibit F-2). To simplify the
analysis, the sponsor conservatively assumes weekday traffic for all days of the year,
even though the operating plan calls for reduced service on weekends.3 Identical traffic
volume and activity profiles are assumed for all quarters of the year. Quarters are defined
for this analysis as described in Section 3.3.4 of the guidance: Ql (January-March), Q2
(April-June), Q3 (July-September), and Q4 (October-December).
The project area in this example is not realistic and has been simplified for demonstration purposes.
Analyses of transit facilities will likely include inbound and outbound links beyond what is described in
this simplified example, as well as the surrounding area.
3 This decision is made to save time and effort, as it would result in the need for fewer modeling runs.
More accurate results would be obtained by treating weekends differently and modeling them using the
actual estimated Saturday and Sunday traffic.
F-4
-------
Exhibit F-2. Average Weekday Bus Trips through Transit Terminal for Each Hour
Hour
12am - 1am
1am - 2am
2am - Sam
Sam - 4am
4am - Sam
Sam - Sam
Sam - 7am
7am - Sam
Sam - 9am
9am - 10am
10am - 1 1am
11am - 12pm
12pm - 1pm
1pm - 2pm
2pm - 3pm
3pm - 4pm
4pm - 5pm
5pm - 6pm
6pm - 7pm
7pm - 8pm
8pm - 9pm
9pm - 10pm
10pm - 1 1pm
11pm - 12am
Bus Trips
7
6
6
6
7
9
27
48
39
29
26
28
30
31
31
39
44
42
26
21
22
17
13
10
F.5.2 Deciding on how to handle link activity
As discussed in Section 4.2 of the guidance, MOVES offers several options for users to
apply activity information to each LinklD. For illustrative purposes, based on the
available information for the project (average speed, hourly bus volume, idle time, and
fraction of vehicles encountering a red light) several methods of deriving Op-Mode
distributions are employed in this example, as described below.
• Links 1 and 2 represent buses driving at an average of 5 mph through the
terminal, entering and exiting the bus bays. An average speed of 5 mph is entered
into the MOVES "links" input, which calculates an Op-Mode distribution to
reflect the MOVES default 5 mph driving pattern.
• The queue link (Link 3) is given an Op-Mode distribution that represents buses
decelerating, idling, and accelerating (red light) as well as cruising through (green
light). First, an Op-Mode distribution is calculated for the link average speed (5
mph). Because this does not adequately account for idling at the intersection, the
Op-Mode fractions are re-allocated to add in 50% idling (determined after
consulting the Highway Capacity Manual 2000 to approximate idle time in an
under-capacity scenario) reflecting 50% of buses encountering a red light. A
F-5
-------
fraction of 0.5 for Op-Mode "1" is added to the re-allocated 5 mph average speed
Op-Mode distribution. The resulting Op-Mode distribution represents all activity
on a queuing intersection link.
• The bus bays (Links 4 through 9) are represented by a single link (modeled in
MOVES as "LinkID 4") and activity is defined in the Links table by an average
speed of "0", representing exclusively idle activity.
F.5.3 Determining the number of MOVES runs
Following the guidance given in Section 4.3, it is determined that 16 MOVES runs
should be completed to produce emission factors that show variation across four hourly
periods (12 a.m., 6 a.m., 12 p.m., and 6 p.m., corresponding to overnight, morning,
midday, and evening traffic scenarios, respectively) and four quarterly periods
(represented by the months of January, April, July, and October; see Section 3.3).
MOVES would calculate values for all project links for the time period specified in each
run. Although traffic data is available for 24 hours, the emission factors produced from
the 16 scenarios would be post-processed into grams/vehicle-hour and further converted
to grams/hour emission factors that vary based on the hour-specific vehicle count. This
methodology avoids running 24 hourly scenarios for four quarters (96 runs). Grams/hour
emissions rates are required to use AERMOD.
F.5.4 Developing basic run specification inputs
When configuring MOVES for the analysis, the project sponsor follows Section 4.4 of
the guidance, including, but not limited to, the following:
• From the Scale menu, selecting the "Project" domain; in addition, choosing
output in "Inventory" so that total emission results are produced for each link,
which is equivalent to a grams/hour/link emission factor needed by AERMOD
(see Section 4.4.2).
• From the Time Spans panel, the appropriate year, month, day, and hour for each
run is selected (see Section 4.4.3).
• From the Geographic Bounds panel, the custom domain is selected (see Section
4.4.4).
• From the Vehicles/Equipment panel, Diesel Transit Buses are selected (see
Section 4.4.5).
• From the Road Types panel, the Urban Unrestricted road type is selected (see
Section 4.4.6).
• From the Pollutants and Processes panel, appropriate pollutant/processes are
selected according to Section 4.4.7 of the guidance for "highway links."
• In the Output panel, an output database is specified with grams and miles selected
as units (see Section 4.4.10).
F-6
-------
F. 5.5 Entering project details using the Project Data Manager
Meteorology
As described previously, it is determined that MOVES should be run 16 times to reflect
the following scenarios: 12 a.m., 6 a.m., 12 p.m., and 6 p.m. (corresponding to overnight,
morning, midday, and evening traffic scenarios, respectively) for the months of January,
April, July, and October. Temperature and humidity data from a representative
meteorological monitoring station are obtained and confirmed to be consistent with data
used in the regional emissions analysis from the currently conforming transportation plan
and TIP (see Section 4.5.1). Average values for each hour and month combination are
used for each of the 16 MOVES runs. As an example, temperature and humidity values
for 12 a.m. January are shown in Exhibit F-3.
Exhibit F-3. Temperature and Humidity Input (January 6 a.m.)
H metjan6am.xls 3@S
1
2
3
4
5
B
1
A
B
C
D
E F -
monthID zonelD hourlD temperatutrelHumidity
11 390610 7 21.7 78.6
H * > w \ZoneMonthHour /, HourOfAr ] <
3
*
>\
F-7
-------
Age Distribution
Section 4.5.2 of the guidance specifies that default data should be used only if an
alternative local dataset cannot be obtained and the regional conformity analysis relies on
national defaults. However, for the sake of simplicity only, in this example the national
default age distribution for 2015 is used for all vehicles and all runs (see Exhibit F-4). As
discussed in the guidance, transit agencies should be able to provide a fleet-specific age
distribution, and the use of fleet-specific data is always recommended (and would be
expected in a real-world scenario) because emission factors vary significantly depending
on the age of the fleet.
Exhibit F-4. Age Distribution Table (Partial)
H dgedist.xls EJOS
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
A | B
C
sourceTyp yearlD agelD
42 2015
42| 2015
42 2015
42 I 2015
42l 2015
42) 2015
42 | 2015
42 | 2015
42 2015
42 2015
42 2015
42) 2015
D E F —
ageFraction
:D| 0.052013
1
2
0.052432
0.051104
:3i 0.050951
4
1
6
7
0.0509
0.050341
0.045595
0.038191
8 0.034719
9 0.0381 S3
10
11
42 1 2015 12
42 2015i 13
42 ! 2015,
421 2015
42! 2015
14
15
0.043573
0.043438
0.051516
0.047071
0.043819
0.035929
16 0.031348
V
H < > n\sourceTypeAgeDistr|bution/ |< > |
F-8
-------
Fuel Supply and Fuel Formulation
An appropriate fuel supply and formulation is selected to match the project area's diesel
use. In MOVES, diesel fuel formulation is constant across all quarters, so one fuel
supply/fuel formulation combination is used for all MOVES runs. Also, it is known that
all transit buses would use the same diesel fuel, so a fraction of 1 is entered for fuel
20011 (ultra-low-sulfur diesel fuel) in the Fuel Supply Table. In the case of this example,
the default fuel supply/formulation matches the actual fuel supply/formulation, so it is
therefore appropriate to use the default in the analysis (see Exhibits F-5 and F-6).
Exhibit F-5. Fuel Supply Table
U fuelsupply.xls
1
2
3
4
5
e
A
B
countylD fuelYearlD
99001 2015
C
D
monthGrmfuelFormul
1
20011
BBS
E
F
G
marketShs marketShareCV
1
H < > w \FuelSupply / County / FuelFormulation
0.5
A-
v
>l
Exhibit F-6. Fuel Formulation Table
D fuelformulation.xls BO®
1
2
3
4
5
c
H 4
A
fuelForrnul
20011
> M/Cc
B
[^f
fuelTypelD fuelTypeDe
2
unty \Fue
Diesel Fue
Formulatic
D
fuelSubtyp
20'
n/ FuelSu
E
F
fuelSubtyp RVP
Conventior
nplyYear /
D
N<
G
H
sulfurLevel ETOHVolu
11
0
i -r
MTBEVc-
i
F-9
-------
Inspection and Maintenance (I/M)
As there is no PM emissions benefit in MOVES for I/M programs, this menu item is
skipped (see Section 4.5.4).
Link Source Type
The distribution of vehicle types on each link is defined in the Link Source Type table
following the guidance in Section 4.5.5. Given that the project will be a dedicated transit
bus terminal this analysis assumes only transit buses are operating on all links.
Therefore, a fraction of 1 is entered for Source Type 42 (Transit Buses) for each LinkID
indicating 100% of vehicles using the project are transit buses (see Exhibit F-7).
Exhibit F-7. Link Source Type Table
H linksource.xls QEIS
1
2
3
4
5
6
7
8
9
10
11
H <
A
linkID
1
2
3
4
B
C
sourceTypelD sourceTypeHourFraction
42 1
42
42
42
1
1
1
~D | =
—
v
> w \linkSourceTypeHour / SourceL | < I > |
F-10
-------
Links
The Links table (see Exhibit F-8) is populated with parameters for the four defined links
of the bus terminal: three running links (Links 1-3) and one idle link (representing the
terminal links). The link length is entered in terms of miles for each link. The road type
for the four links is classified as "5" (Urban Unrestricted). The entrance and exit links
(Links 1 and 2) are given an average speed of 5 mph. The queue link (Link 3) is given an
average speed of 2.5 mph, representing 50% of the vehicle operating hours in idling
mode and 50% operating hours traveling at 5 mph. Although MOVES is capable of
calculating emissions from an average speed (as is done for Links 1 and 2), the specific
activity on Link 3 is directly entered with an Op-Mode distribution. LinkID 4 is given a
link average speed of "0" mph, which indicates entirely idle operation. Link volume
(which represents the number of buses per hour) is entered for each link; however, since
the goal of the analysis is to produce an estimate in grams/vehicle-hour, the volume (i.e.,
the number of vehicles) will be divided out during post-processing. Also, because link
volume is arbitrary, the Links table shown in Exhibit F-8 can be used for all 16 MOVES
runs.
Exhibit F-8. Links Table
€1 links, xl* £"](§f!r|
1
2
3
t
5
6
J
a
9
10
11
12
13
14
15
i r
!' '
A B
linktt) couniylO
t 99001
2 99001
3 93001
4 99001
C
zonelD
990010
990010
990010
990010
D
E
icatfTypelt linkLenglh
5 0.038
5 0.030
5 0.006
5
, ,
0.011
F C*
ImkVolume
48
24
24
8
I*
link AH] Speed
5
25
0
•> . A
hnkDescitption
Entrance bnk
Exit Approach Link
Ltft Turn Exit Link
Terminate
V
> 1 .
Describing Vehicle Activity
MOVES can capture details about vehicle activity in a number of ways. In this case, it is
decided to use average speeds for Links 1, 2, and 4 and a detailed Op-Mode distribution
for Link 3 (see Section 4.5.7).
Op-Mode distributions for Links 1 and 2 are calculated within MOVES based on a 5 mph
average speed. The MOVES model calculates a default Op-Mode distribution based on
average speed and road type (for these links, 5 mph on road type 5). Link 3 is given a
unique Op-Mode distribution to better simulate the queuing and idling that occurs prior to
buses exiting the facility at a traffic signal. The sponsor estimates that 50% of buses
F-ll
-------
would idle at a red light before exiting the facility, so the idling operation (OpMode ID 1)
is assumed to be 0.5 for Link 3. The remaining 50% is re-allocated based on the default 5
mph Op-Mode distribution calculated for Links 1 and 2 (which includes acceleration,
deceleration, and cruise operating modes). This process requires an additional MOVES
run to extract the default 5 mph Op-Mode distribution from the MOVES execution
database. By selecting "save data" for the "Operating Mode Distribution Generator
(Running OMDG)" under the MOVES "Advanced Performance Features" panel, the Op-
Mode distributions generated for 5 mph on an urban unrestricted road type are saved in
the MOVES execution database in the MySQL table "opmodedistribution." The Op-
Mode distribution used in the analysis for Link 3 is partially shown in Exhibit F-9.
Exhibit F-9. Link 3 (Queue Link) Op-Mode Distribution Input Table (Partial)
H opmode.xls 0(10®
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
13
19
20
21
22
23
24
25
26
27
28
29
30
31
.3?
H 4
A
B
C
sourceTyp hourDaylD linkID
42J_ 75
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
75
75
75
75
75
75
75
75
75
75
75
75
75
75
75
75
75
75
75
75
75
75
42 75
42
42
42
42
42
42
47
> H \op
75
75
75
75
75
75
7S
ModeDistr
3
3
3
3
3
3
3:
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3,
3
3
|
3
3;
3
i
bution/ h
D
E I F
polProcessopModelD
9101 1
9190
11001
11015
11017
11090
11101
11115
11117
11190
11201
11215
11217
11290
11501
11515
11517
11590
11609
11710
9101
9190
11001
11015
11017
11090
11101
11115
11117
11190
1
1
|
1
1
1
I
I
1
1
1
I
|
1
f
1
1
1
1
11
11
11
11
11
11
11
11
11
11
U20lL 1L
ourDay / OperatingMode
opModeFr;
0.5
0.5
0.5
0.5
0.5
0.5
0.5
o:.5
.0.5
0.5
0.5
0.5
.0,5
0,5
0.5
.0.5
.0.5
0.5
0:5
0.5
0.25
0.25
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0.25
0.25
0.25
0.25
0.25
0.25
0.25
l, n's
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action
H
I -
0
m&
F-12
-------
Off-Network
As it is assumed that there are no off-network links (such as parking lots or truck stops)
that would have to be considered using the Off-Network Importer (bus idling at the
terminal is captured by the terminal links), there is no need to use this option in this
example. As noted earlier, this assumption is made to simplify the example. Most transit
projects would include rider parking lots and should include these emissions in a PM hot-
spot analysis.
F.5.6 Generating emission factors for use in air quality modeling
After generating the run specification and entering the required information into the
Project Data Manager as described above, MOVES is run 17 times: 16 runs (four hours
of the day for four quarters of the year) plus an initial run to generate the Op-Mode
distribution for 5 mph as discussed earlier. Upon completion of each run, the MOVES
output is located in the MySQL output database table "movesoutput" and sorted by
Month, Hour, LinkID, ProcessID, and PollutantlD. An aggregate PM2.5 emission factor
is then calculated by the project sponsor for each Month, Hour, and LinkID combination
using the following equation and the guidance given in Section 4.4.7 of the guidance:4
PMaggregate totai = (PMtotai running) + (PMtotai crankcase running) + (brake wear) + (tire wear)
For each link, the total emissions are divided by the number of vehicles on each link (as
reported in the "movesactivityoutput" table ActivitytypelD = 6) to produce a
grams/vehicle-hour value. This value is then multiplied by the number of buses on each
link, for each of the 24 hours where data are available (see Exhibit F-2).
The emission factor (grams/vehicle-hour) for LinkID 4 (links 4 through 9) is converted
into grams per vehicle-minute, and then multiplied by the total idle time for each unique
hour. For instance, the hour from 5 p.m. to 6 p.m. has a volume of 42 buses per hour (7
buses per bus bay). If each bus is expected to idle for 60 seconds each hour, the total idle
time for each bus bay for that hour would be 7 minutes per hour. If MOVES calculated a
PM emission factor of 2.0 grams per vehicle-minute, the emission factor for each bus bay
link under this scenario would be 14.0 grams/hour.
To account for temperature changes throughout the day, emission factors are evenly
paired with corresponding traffic volumes (six hours per period):
• 6 a.m. results - traffic data from 3 a.m. to 9 a.m.
• 12 p.m. results - traffic data from 9 a.m. to 3 p.m.
• 6 p.m. results - traffic data from 3 p.m. to 9 p.m.
• 12 p.m. results - traffic data from 9 p.m. to 3 a.m.
The emission factor results for each quarter are similarly paired with traffic volumes.
4 EPA is considering creating one or more MOVES scripts that would automate the summing of aggregate
emissions when completing project-level analyses. These scripts would be made available for download on
the MOVES website (www.epa.gov/otaq/models/moves/tools.htm'), when available.
F-13
-------
The 96 resulting grams/hour emission factors (24 hours each for four quarters) for each
link are then ready to be used as an input to the AERMOD dispersion model to predict
PM2.5 concentrations.
F.6 ESTIMATE EMISSIONS FROM ROAD DUST, CONSTRUCTION AND
OTHER ADDITIONAL SOURCES (STEP 4)
F. 6.1 Estimating re-entrained road dust
In this case, this area does not have any adequate or approved SIP budgets for either
PM2.5 NAAQS, and neither the EPA nor the state air agency has made a finding that road
dust emissions are a significant contributor to the air quality problem for either PM2.5
NAAQS. Therefore, PM2.5 emissions from road dust do not need to be considered in this
analysis (see Sections 2.5.3 and 6.2).
F. 6.2 Estimating transportation-related construction dust
The construction of this project will not occur during the analysis year. Therefore,
emissions from construction dust are not included in this analysis (see Sections 2.5.5 and
6.4).
F. 6.3 Estimating additional sources of emissions in the project area
Through interagency consultation, it is determined that the project area in the analysis
year does not include locomotives or other nearby emissions sources that would have to
be included in the air quality modeling (see Section 6.6).
F.7 SELECT AN AIR QUALITY MODEL, DATA INPUTS, AND RECEPTORS
(STEP 5)
F. 7.1 Characterizing emission sources
Because this is a transit terminal project, EPA's AERMOD model is determined to be the
appropriate dispersion model to use for this analysis (see Section 7.3). AERMOD is run
to estimate PM2.5 concentrations in and around the bus terminal project. Each link is
represented in AERMOD as an "Area Source" with dimensions matching the project
description (see Exhibit F-l). The emission release height is set to three meters, the
approximate exhaust height of most transit buses.
Emission factors generated from the MOVES runs are added to the AERMOD input file
(see Exhibit F-10). For this analysis, emissions vary significantly from hour to hour due
to fluctuating bus volumes as well as from daily and quarterly temperature effects.
Adjustment factors (EMISFACT) are used to model these hourly and quarterly variations
F-14
-------
in emission factors. Refer to Appendix J for additional detail on using hour-by-hour
emission differences in an AERMOD input file.
Exhibit F-10. AERMOD Input File (Partial) with Seasonal (Quarterly) and Hourly
Adjustment Factors (Circled)
C AERMOD lnput.txt - Notepad
File Edit Format View Help
CO STARTING
CO TITLEDHE
CO MODELOPT
CO RUNORNOT
CO AVERTIME
CO POLLUTID
CO FINISHED
SO STARTING
SO ELEVUNIT
SO LOCATION
SO LOCATION
SO LOCATION
SO LOCATION
SO LOCATION
SO LOCATION
SO LOCATION
SO LOCATION
SO LOCATION
SO SRCPARAM
SO SRCPARAM
SO SRC PARAM
SO SRCPARAM
SO SRCPAP.AM
SO SRCPARAM
SO SRCPARAM
SO SRCPARAM
SO SRCPARAM
SO AREAVERT
SO AREAVERT
SO AREAVERT
SO AREAVERT
SO AREAVERT
SO AREAVERT
SO EMISFACT
SO EMISFACT
SO EMISFACT
SO EMISFACT
SO EMISFACT
SO EMISFACT
SO EMISFACT,,
SO EMISFA
SO EMISFACT
SO EMISFACT
SO EMISFACT
SO EMISFftCT
SO EMISFACT
SO EMISFA
SO EMISFACT
SO EMISFACT
SO EMISFACT
SO EMISFACT
SO EMISFACT
SO EMISFACT
SO EMISFACT
Transit Example
FLAT CONC|
RUN
2.4 ANNUAL
OTHER
METERS
LINK1
LINKS
LINKS
LINKS
LINK4
LINK7
LINKS
LINKS
LINKS
LINK1
LINK2
LINKS
LINK5
LINK4
LINK?
LINKS
LINK9
LINKS
LINKS
LINK4
LINK7
LINKS
LINKS
LINKS
LINK1
LINK1
LINK1
LINK1
jK-r
IKl
LINK1
LINK1
LINK1
LINK1
LINK1
LINKS
LINK2
LINK2
LINK2
INK2
LTNK2
LINK2
LINK2
LINK2
LINK2
AR.EA
AREA
AREA
AREAPOLY
AREAPOLY
AREAPOLY
AREAPOLY
AREAPOLY
AREAPOLY
7E-Q6 3
4E-06
4E-OS
2E-06
2E-06
2E-06
2E-06
2E-06
2E-06
-156.1 -47
-163.5 -47
-140.5 -47
-132.9 -47
-125.3 -47
-148.0 -47
-1S6.7
-166.6
-118.1
-156.1
-1S3.5
-140.5
-132.9
-125.3
-148
60.6
-50.9
-33.2
-33.2
-47.4
-47.4
-47.4
-47.4
-47.3
-47
3.6
3.6
3.6
.4
0
0.0
0.0
0.0
SEASHR
J
SEASHR
SEASHR
SEASHR
SEASHR
SEASHR
SEASHR
SEASHR
SEASHR
SEASHR
SEASHR
SEASHR
SEASHR
SEASHR
SEASHR
ASHR
F. 7.2 Incorporating meteorological data
A representative set of meteorology data, as well as an appropriate surface roughness are
selected (see Section 7.5). The recommended five years of meteorological data is
obtained from a local airport for calendar years 1998-2002. The appropriate surface
roughness is set at 1 meter, consistent with the recommendations made in the AERMOD
Implementation Guide.
F-15
-------
F. 7.3 Placing receptors
Using the guidance given in Section 7.6, receptors are placed at appropriate locations
within the area substantially affected by the project (see Exhibit F-l I).5 It is determined
in this instance to locate receptors around the perimeter of the project in increments of
five meters as well as within the passenger loading areas adjacent to the bus bays.
Receptor heights are set at 1.8 meters. A background concentration of "0" is input into
the model. Representative background concentrations are added at a later step (see Step
7).
AERMOD is run using five years of meteorological data and output produced for all
receptors for each of the five years of meteorological data.
Exhibit F-ll. Area Source and Receptor Locations for Air Quality Modeling
LINK2
1 : , ^—, — —, ^—, — 1
LINKS
1
30 meters
The number and arrangement of receptors used in this example are simplified for ease of explanation;
real-world projects could expect to see more receptors and include the surrounding area.
F-16
-------
F.8 DETERMINE BACKGROUND CONCENTRATIONS FROM NEARBY AND
OTHER EMISSION SOURCES (STEP 6)
Through the interagency consultation process, a nearby upwind PM2.5 monitor that has
been collecting ambient data for both the annual and 24-hour PIVb.s NAAQS is
determined to be representative of the background air quality at the project location (see
Exhibit F-12). The most recent data set is used (in this case, calendar year 2008 through
2010) and average 24-hour PIVb.s values are provided in a four-day/three-day
measurement interval. As previously noted, no nearby sources requiring modeling are
identified.
Note: This is a highly simplified situation for illustrative purposes; refer to Section 8 of
the guidance for additional considerations for how to most accurately reflect background
concentrations in a real-world scenario.
Exhibit F-12. PM2.s Monitor Data from a Representative Nearby Site (Partial)
H backeroundcalcs.xls Q@f5<]
1
2
3
4
5
6
I 7
8
9
10
I 11
i U
13
14
! 15
16
17
18
I 19
20
21
'22
23
24
25
26
: 27
28
29
''30
31
A
Month
1
i
1
1
1
1
1
1
i
2
2
2
2
2
2
2
2
3
3
3
3
3
3
3
3
3
4
4
4
4
BCD E
Day
1
5
8
12
15
19
22
26
29
2
5
9
12
16
19
23
26
1
4
8
11
!f
18
22
25
29
1
5
8
Year
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
Date PM2.5 Concentration
1/1/2008; 23.08
1/5/2008 ; 5.69
1/8/2008: 12.19
1/12/2008 6.71
1/15/2008 7.26
1/19/2008 17.92
1/22/2008 11.90
1/26/2008 14.37
1/29/2008 16.54
2/2/2008 7.40
2/5/2008 13.63
2/9/2008 19.15
2/12/2008 12.65
2/16/2008 14.77
2/19/2008 11.08
2/23/2008 18.00
2/26/2008 21 .62
3/1/2008 14.65
3/4/2008 ; 6.93
3/8/2008. 19.03
3/11/2008 20.66
3/15/2008 11.99
3/18/2008 4.71
3/22/2008 11.05
3/25/2008 15.64
3/29/2008 6.64
4/1/2008 11.68
4/5/2008 5.04
4/8/2008 10.11
F
G -T
12 2008 4/12/2008 11.96 v
H < > M \Monitoring Data/ AERMOD 24-hour Output | < > \
F-17
-------
F.9 CALCULATE DESIGN VALUES AND DETERMINE CONFORMITY (STEP 7)
With both MOVES outputs and background concentrations now available, the project
sponsor can calculate the design values. For illustrative purposes, calculations for a
single receptor with the highest modeled concentrations for the build scenario are shown
in this example. 6 In Step 7, the guidance from Sections 9.3.2 and 9.3.3 are used to
calculate design values from the modeled results and the background concentrations for
comparison with the annual and 24-hour PlVk.s NAAQS.
F.9. 1 Determining conformity to the annual PM2.s NAAQS
First, average background concentrations are determined for each year of monitored data
(shown in Exhibit F-13). The three-year average background concentration is then
calculated (see Exhibit F-14).
Exhibit F-13. Annual Average Background Concentration for Each Year
Monitoring
Year
2008
2009
2010
Annual
Average
Annual Average
Background
Concentration
13.348
12.785
13.927
13.353
Exhibit F-14. Calculation of Annual Design Value (At Highest Receptor)
Annual Average
Background
Concentration
(Three-year
Average)
13.353
Annual Average
Modeled
Concentration
(Five-year
Average)
1.423
Sum of
Background +
Project
14.776
Annual Design Value
14.8
6 In an actual PM hot-spot analysis, design values would be calculated at additional receptors as described
in Section 9.3.
F-18
-------
To determine the annual PIVb.s design value, the annual average background
concentration is added to the five-year annual average modeled concentration (at the
receptor with the highest annual average concentration from the AERMOD output). This
calculation is shown in Exhibit F-14. The sum (project + background) results in a design
value of 14.8 |J,g/m3. This value at the highest receptor is less than the 1997 annual PIVb.s
NAAQS of 15.0 |J,g/m3. It can be assumed that all other receptors with lower modeled
concentrations will also have design values less than the 1997 annual PM2.5 NAAQS. In
this example it is unnecessary to determine appropriate receptors in the build scenario or
develop a no-build scenario for the annual PIVb.s NAAQS, since the build scenario
demonstrates that the hot-spot analysis requirements in the transportation conformity rule
are met at all receptors.
F.9.2 Determining conformity to the 24-Hour PM2.5NAAQS
The next step is to calculate a design value to compare with the 2006 24-hour PIVb.s
NAAQS through a "Second Tier" analysis as described in Section 9.3.3. For ease of
explanation, this process has been divided into individual steps, consistent with the
guidance.
Step 7.1
The number of background measurements is counted for each year of monitored data
(2008 to 2010). Based on a 4-day/3-day measurement interval, the dataset has 104 values
per year.
Step 7.2
For each year of monitored concentrations, the eight highest daily background
concentrations for each quarter are determined, resulting in 32 values (4 quarters; 8
concentrations/quarter) for each year of data (shown in Exhibit F-15).
Step 7.3
Identify the highest modeled 24-hour concentration in each quarter, averaged across each
year of meteorological data. For illustrative purposes, the highest average concentration
across five years of meteorological data for a single receptor in each quarter is shown in
Exhibit F-16. Note that, in a real-world situation, this process would be repeated for all
receptors in the build scenario.
F-19
-------
Exhibit F-15. Highest Daily Background Concentrations for Each Quarter and
Each Year
2008
Rank
1
2
3
4
5
6
7
8
Q1
20.574
20.152
19.743
19.346
18.961
18.588
18.226
17.874
Q2
21.262
20.823
20.398
19.985
19.584
19.196
18.819
18.454
Q3
22.354
22.042
21.735
21.434
21.140
20.851
20.568
20.291
Q4
20.434
20.016
19.611
19.218
18.837
18.467
18.109
17.761
2009
Rank
1
2
3
4
5
6
7
8
Q1
20.195
19.784
19.386
19.000
18.625
18.262
17.910
17.568
Q2
20.867
20.440
20.026
19.624
19.235
18.857
18.490
18.135
Q3
21.932
21.628
21.329
21.037
20.750
20.469
20.194
19.924
Q4
20.058
19.651
19.257
18.875
18.504
18.145
17.796
17.457
2010
Rank
1
2
3
4
5
6
7
8
Q1
21.137
20.698
20.272
19.860
19.459
19.071
18.694
18.329
Q2
21.847
21.390
20.948
20.519
20.102
19.698
19.307
18.927
Q3
22.980
22.655
22.336
22.023
21.717
21.417
21.123
20.834
Q4
20.990
20.556
20.135
19.726
19.330
18.945
18.572
18.211
Exhibit F-16. Five-year Average of Highest Modeled Concentrations for Each
Quarter (At Example Receptor)
Five Year Average
Maximum
Concentration (At
Example Receptor)
Q1
6.51
Q2
6.64
Q3
6.71
Q4
6.63
F-20
-------
Step 7.4
The highest modeled concentration in each quarter (from Step 7.3) is added to each of the
eight highest monitored concentrations for the same quarter for each year of monitoring
data (from Step 7.2). As shown in Exhibit F-17, this step results in eight concentrations
in each of four quarters for a total of 32 values for each year of monitoring data. As
mentioned, this example analysis shows only a single receptor's values, but project
sponsors should calculate design values at all receptors in the build scenario.
Exhibit F-17. Sum of Background and Modeled Concentrations at Example
Receptor for Each Quarter
2008
1
2
3
4
5
6
7
8
Q1
27.088
26.667
26.258
25.861
25.476
25.102
24.740
24.389
Q2
27.901
27.462
27.037
26.624
26.224
25.835
25.459
25.093
Q3
29.063
28.750
28.443
28.143
27.848
27.560
27.277
27.000
Q4
26.948
26.530
26.125
25.732
25.351
24.982
24.623
24.275
2009
1
2
3
4
5
6
7
8
Q1
26.709
26.298
25.900
25.514
25.140
24.776
24.424
24.082
Q2
27.506
27.079
26.665
26.264
25.874
25.496
25.130
24.774
Q3
28.641
28.336
28.038
27.745
27.459
27.178
26.903
26.633
Q4
26.572
26.166
25.772
25.389
25.019
24.659
24.310
23.971
2010
1
2
3
4
5
6
7
8
Q1
27.651
27.212
26.787
26.374
25.974
25.585
25.209
24.843
Q2
28.486
28.030
27.587
27.158
26.742
26.338
25.946
25.566
Q3
29.689
29.363
29.044
28.732
28.426
28.125
27.831
27.543
Q4
27.505
27.070
26.649
26.240
25.844
25.460
25.087
24.725
F-21
-------
Step 7.5
As shown in Exhibit F-18, for each year of monitoring data, the 32 values from Step 7.4
are ordered together in a column and assigned a yearly rank for each value, from 1
(highest concentration) to 32 (lowest concentration).
Exhibit F-18. Ranking Sum of Background and Modeled Concentrations at
Example Receptor for Each Year of Background Data
Rank
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
2008
29.063
28.750
28.443
28.143
27.901
27.848
27.560
27.462
27.277
27.088
27.037
27.000
26.948
26.667
26.624
26.530
26.258
26.224
26.125
25.861
25.835
25.732
25.476
25.459
25.351
25.102
25.093
24.982
24.740
24.623
24.389
24.275
2009
28.641
28.336
28.038
27.745
27.506
27.459
27.178
27.079
26.903
26.709
26.665
26.633
26.572
26.298
26.264
26.166
25.900
25.874
25.772
25.514
25.496
25.389
25.140
25.130
25.019
24.776
24.774
24.659
24.424
24.310
24.082
23.971
2010
29.689
29.363
29.044
28.732
28.486
28.426
28.125
28.030
27.831
27.651
27.587
27.543
27.505
27.212
27.158
27.070
26.787
26.742
26.649
26.374
26.338
26.240
25.974
25.946
25.844
25.585
25.566
25.460
25.209
25.087
24.843
24.725
F-22
-------
Step 7.6
For each year of monitoring data, the value with a rank that corresponds to the projected
98th percentile concentration is determined. As discussed in Section 9, an analysis
employing 101-150 background values for each year (as noted in Step 7.1, this analysis
uses 104 values per year) uses the 3rd highest rank to represent a 98th percentile. The 3rd
highest concentration (highlighted in Exhibit F-18) is referred to as the "projected 98th
percentile concentration."
Steps 7.1 through 7.6 are repeated to calculate a projected 98th percentile concentration at
For the example receptor, the average of the three projected 98th percentile concentrations
Step 7.7
Steps 7.1
each receptor based on each year of monitoring data and modeled concentrations.
Step 7.8
For the e
(highlighted in Exhibit F-18) is calculated.
Step 7.9
The resulting value of 28.508 |J,g/m3 is then rounded to the nearest whole |J,g/m3 resulting
in a design value at the example receptor of 29 |J,g/m3. At each receptor this process
should be repeated. However, in the case of this analysis, the example receptor is the
receptor with the highest design value in the build scenario.
Step 7. 10
The design values calculated at each receptor are compared to the NAAQS. In the case
of this example, the highest 24-hour design value (29 |J,g/m3) is less than the 2006 24-
hour PM2.5 NAAQS of 35 |J,g/m3. Since this is the design value at the highest receptor, it
can be assumed that the conformity requirements are met at all receptors in the build
scenario. Therefore, it is unnecessary for the project sponsor to calculate design values
for the no-build scenario for the 24-hour PIVb.s NAAQS.
F. 1 0 CONSIDER MITIGATION AND CONTROL MEASURES (STEP 8)
In this case, the project is determined to conform. In situations when this is not the case,
it may be necessary to consider additional mitigation or control measures. If measures
are considered, additional air quality modeling would need to be completed and new
design values calculated to ensure that conformity requirements are met. See Section 10
for more information, including some specific measures that might be considered.
F. 1 1 DOCUMENT THE PM HOT-SPOT ANALYSIS (STEP 9)
The final step is to properly document the PM hot-spot analysis in the conformity
determination (see Section 3.10).
F-23
-------
Appendix G:
Example of Using EMFAC2011 for a Highway Project
G.I INTRODUCTION
The purpose of this appendix is to demonstrate the procedures described in Section 5 of
the guidance on using EMFAC2011 to generate emission factors for air quality modeling.
The following example, based on a hypothetical, simplified highway project, illustrates
the modeling steps required for users to run the EMFAC2011-PL tool to develop project-
specific PM running exhaust emission factors using the "simplified approach" described
in Section 5.5 of the guidance.
As discussed in the guidance, application of the simplified approach and use of the
EMFAC2011-PL tool is only appropriate when the project-specific fleet age distribution
does not differ from the EMFAC2011 defaults and the project does not include start or
idling emissions. See Appendix H for an example of using the detailed approach to
modify a default age distribution.
Users will be able to generate running emission factors (in grams/vehicle-mile) in a
single EMFAC2011-PL run; multiple links and calendar years can also be handled within
one run. This example does not include the subsequent air quality modeling; refer to
Appendix E for an example of how to run an air quality model for a highway project for
PM hot-spot analyses.
G.2 PROJECT CHARACTERISTICS
The hypothetical highway project is located in Sacramento County, California. For
illustrative purposes, the project is characterized by a single link with an average link
travel speed for all traffic equal to 65 mph.1 Project-specific age distributions do not
differ from the EMFAC2011 defaults, so a simplified modeling approach using the
EMFAC2011-PL tool will be used to develop a link-specific PM2.5 emission rate.
The project's first full year of operation is assumed to be the year 2013. Through the
interagency consultation process, it is determined that 2015 should be the analysis year
(based on the project's emissions and background concentrations). The build scenario
2015 traffic data for this highway project shows that 25% of the total project VMT is
from trucks and 75% from non-trucks. This truck/non-truck fleet mix will be used to
post-process the EMFAC-PL output.
1 These are simplified data to illustrate the use of EMFAC2011; this example does not, for instance,
separate data by peak vs. off-peak periods, divide the project into separate links, or consider additional
analysis years, all of which would likely be required for an actual project.
G-l
-------
G.3 DESCRIBING THE SCENARIO USING THE EMFACIO 11 -PL TOOL
Based on the project characteristics, it is first necessary to describe the modeling scenario
in the EMFAC2011-PL interface (see Exhibits G-l and G-2).
Exhibit G-l. Basic Inputs in EMFAC2011-PL for the Hypothetical Highway Project
Step
1
2
3
4
5
6
7
8
Input Category
Vehicle Category
Scheme
Region type
Region
CalYr
Season
Vehicle Category
Fuel Type
Speed
Input Data
Truck / Non-Truck
Categories
County
Sacramento
2015
Annual
ALL
TOT
65MPH
Note
Provides rates for truck/non-truck
categories
Per Section 5.5.2 of the guidance
Select from drop-down list
Select from drop-down list
Select from drop-down list
Provides rates for HD and LD
Does not generate separate rates for
gasoline and diesel
Select from drop-down list
G-2
-------
Exhibit G-2. EMFAC2011-PL GUI Showing Selections Made for the Hypothetical
Highway Project
Main Page
EMFAC2011-PL(Verl.l)
Project-level Emission Rates Database
Vehicle Category
Scheme:
Region type:
Reset
c EMFAC20U Vehicle Categories r EMFAC2007 Vehicle Categories
** Trucks/Non-Trucks Categories O Trucks 1/Trucks 2/Non-Trucks Categories
O Total (Fleet average)
State Air Basin Air District
MPO
Region
CalYr
Season
Sacramento
2015 ||
Annual v
Vehicle Category ALL
0 Fuel Type
TOT
13 Speed
65MPH
Download
County <~ GA1
Exit
G-3
-------
G.4 CALCULATING A LINK-SPECIFIC EMISSION RATE FROM
EMFAC2011-PL OUTPUT
After running EMFAC2011-PL, an output Excel file (Exhibit G-3) is produced in the
EMFAC2011-PL folder. From this file, emission rates are appropriately processed to
calculate a single link emission rate appropriate for dispersion modeling. This process is
described below.
Exhibit G-3. EMFAC2011-PL Output File
| EMFAC2011-PL Emission Rates - Sacramento County - 2015 Annual (Oct 15, 9.54 AM.LxIs [Compatibilit... -
1 [Region.
2 County
3 I County
4I
P
E
F
ion CalYr Season Veh Fuel
Sacramen 2015 Annual Non-Trucl
-------
These rates are then summed separately for Trucks and Non-Truck categories (shown in
Exhibit G-6).
Exhibit G-6. Calculation of Truck and Non-Truck Total PM2.5 EF
Non-trucks
Trucks
Running
Exhaust EF
0.0022297
0.0229593
Tire wear EF
0.0020026
0.0025758
Break wear EF
0.0166726
0.0206886
Total PM2.5 EF
0.020905
0.046224
From the calculated Total PM2 5 EF, the truck and non-truck rates are then weighted
together based on the relative VMT for each vehicle type. In this example, trucks
account for 25% of VMT while non-trucks account for 75% of VMT. Exhibit G-7
demonstrates how the EFs are weighted to calculate a single link emission rate.
Exhibit G-7. Calculation of Total PM2.5 Link Emission Rate
Non-trucks
Trucks
Total
Emission
Rate
0.020905
0.046224
VMT adjustment
0.75
0.25
Weighted
Emission Rate
0.0156788
0.011556
0.027235
This completes the use of the EMFAC2011-PL tool to determine emissions factors for
this project using the simplified approach. The total running link emission factor of
0.027235 grams per vehicle-mile can be now be used in combination with link length and
link volume as inputs into the selected air quality model, as discussed in Section 7 of the
guidance.
G-5
-------
Appendix H:
Example of Using EMFAC2011 to Develop Emission Factors
for a Transit Project
H.I INTRODUCTION
The purpose of this appendix is to illustrate the modeling steps required for users to
develop PM idling emission factors for a hypothetical bus terminal project using
EMFAC2011. It also shows how to generate emission factors from EMFAC2011 for a
project that involves a limited selection of vehicle classes (e.g., urban buses) and an age
distribution that differs from the EMFAC2011 defaults.l Because the project age
distribution differs from the EMFAC2011 defaults, use of the simplified approach and
EMFAC2011-PL tool is not appropriate. Instead, the detailed approach described in
Section 5.6 of the guidance will be used.
This example uses the "Emfac" mode in EMFAC2011-LDV to generate grams per
vehicle-hour (g/veh-hr) emission factors stored in the "Summary Rate" output file (.rts
file) suitable for use in the AERMOD air quality model. This example does not include
the subsequent air quality modeling; refer to Appendix F for an example of how to run
AERMOD for a transit project for PM hot-spot analyses.
The assessment of a bus terminal or other non-highway project can involve modeling two
different categories of emissions: (1) the idle and/or start emissions at the project site, and
(2) the running exhaust emissions on the links approaching and departing the project site.
As discussed in Section 5.7.4, EMFAC2011-LVD allows users to generate emission
factors for all of these in a single run. This appendix walks through the steps to model
idle emissions for this hypothetical project. Users will be able to generate idle emission
factors in a single EMFAC2011-LDV model run; multiple calendar years can also be
handled within one model run. As described in the main body of this section, each run
will be specific to either PMio or PM2 5; however, this example is applicable to both.
This example is intended to help project sponsors understand how to create representative
idle emission factors based on the best available information supplied by EMFAC2011,
thus providing an example of how users may have to adapt the information in
EMFAC2011 to their individual project circumstances.
To estimate idle emissions at a terminal project, the main task will involve modifying the
default vehicle populations and VMT distribution, by vehicle, fuel, and age distribution
embedded in EMFAC2011 to reflect the project-specific bus fleet.
1 This is a highly simplified example showing how to employ EMFAC2011 to calculate idle emission
factors for use in air quality modeling. An actual project would be expected to be significantly more
complex.
H-l
-------
H.2 PROJECT CHARACTERISTICS
A PMio hot-spot analysis is conducted for a planned bus terminal project in Sacramento
County, California. The project's first full year of operation is assumed to be the year
2013. Through the interagency consultation process, it is determined that 2015 should be
the analysis year (based on the project's emissions and background concentrations). The
PM analysis is focused on idle emissions from buses operated in the terminal.
Additionally, all buses in this example operate using diesel fuel and are ten years old (age
10).
It is determined that the appropriate EMFAC2011 vehicle category for the urban transit
buses included in the project is "UBUS-DSL," which is a type found in the
EMFAC2011-LDV module (see Section 5.6.2 of the guidance). Therefore, we will be
applying the EMFAC2011-LDV procedure described in Section 5.7 of the guidance.
H.3 PREPARING EMFACIOI 1 BASIC INPUTS
Based on the project characteristics, basic inputs and default settings in EMFAC2011-
LDV are first specified (see Exhibit H-l). These basic inputs are similar to those
specified for highway projects. To generate idle emission factors for urban transit buses
(UBUS-DSL) from EMFAC2011-LDV, a speed bin of 5 mph must be selected in the
EMFAC2011-LDV interface.
Exhibit H-l. Basic Inputs in EMFAC2011-LDV for the Hypothetical Highway
Project
Step
1
2
3
4
5
6
7
8
9
10
11
12
Input Category
Geographic Area
Calculation Method
Calendar Years
Season or Month
Scenario Title
Model Years
Vehicle Classes
I/M Program Schedule
Temperature
Relative Humidity
Speed
Emfac Rate Files
Output Particulate
Input Data
County -^ Sacramento
Use Average
2015
Annual
Use default
Use default
Use default
Use default
60F
70%RH
Use default
Summary Rates (RTS)
PM10
Note
Select from drop-down list
Default (not visible in the
EMF AC20 1 1 -LDV user interface)
Select from drop-down list
Select from drop-down list
Define default title in the
EMF AC20 1 1 -LDV user interface
Include all model years
Include all vehicle classes
Include all pre-defined I/M program
parameters
Delete all default temperature bins
and input 60
Delete all default relative humidity
bins and input 70
Include speed bin of 5 mph
Select from EMFAC20 1 1 -LDV user
interface
Select from EMFAC20 1 1 -LDV user
interface
H-2
-------
H.4 EDITING EMFACIOI I-LDV DEFAULT VMT AND POPULATION TO
REFLECT PROJECT-SPECIFIC BUS FLEET
To generate idle emission factors that reflect the bus terminal project data, vehicle
population and VMT by vehicle class must be modified in the EMFAC2011-LDV user
interface. The EMFAC2011 module has data limitations regarding idle emissions:
among the available vehicle classes in EMFAC2011-LDV, idle emission factors are
available only for the LHDT1, LHDT2, MHDT, HHDT, School Buses, and Other Buses
vehicle types. Although EMFAC2011-LDV does not explicitly provide idle emission
factors for the "UBUS-DSL" class (the class most typically associated with urban transit
buses), as described in Section 5.7.4 of the guidance, the 5 mph emission factors may be
used to represent transit buses by multiplying the rate (grams/vehicle-mile) by 5 miles per
hour, resulting in a grams/veh-hour rate.
Since the fuel use and age distribution of the bus fleet are known, it is necessary to edit
the EMFAC2011 -LDV program constants (defaults) to reflect this information. First,
VMT "By Vehicle and Fuel" will be edited to reflect entirely diesel Urban Bus operation
by changing gasoline Urban Bus VMT to "1" (because "0" will cause an error). Next,
Population "By Vehicle and Fuel" will be edited to reflect entirely diesel Urban Bus
operation by changing the number of gasoline Urban Buses to "1". Finally, the
Population "By Vehicle/Fuel/Age" will be edited to reflect the known Urban Bus age
distribution by preserving the number of Urban Buses "age 10", and changing the number
of buses of all other ages to "0" (note this must be done by exporting the default age
distribution to Excel, as explained in Exhibit H-4).
As shown in Figure H-2, VMT is edited to reflect only diesel operation by Urban Buses.
For this example bus terminal, a very low value ("1") is entered into the interface for
gasoline Urban Buses to represent the project-specific fuel data.
H-3
-------
Exhibit H-2. Changing EMFAC2011-LDV Default VMT to Reflect Project-Specific
Fuel Use
Editing VMT data for scenario 1 : Bus Idle and Start Emission Rates
TotalVMT for area Copy wilh Headings
Sacramento County
Editing Mode
T otal VM T I By Vehicle Class By Vehicle and F
01 -Light-Duty Autos (PC)
02 -Light-Duty! rucks (T1)
03 -Light-Duty! rucks (T 2)
04 - Medium-Duty Trucks (T3)
05- Light HD Trucks (T4)
06- Light HD Trucks (T5)
07 • CAIRP+OOS*IS Trc/Sngl (T6)
08- Agriculture (T6)
09 - Public + Utility (T6)
10 -Out of State [T7]
11 -CAIRPfT?)
12 -Instate Tractor (T7)
13 -Instate Single (T7)
14-Poit(Drayage)(T7)
15- Agriculture (T7)
16 - Public*Util*SolidWaste(T7)
17 -Other Buses
18 -Urban Buses
19 -Motorcycles
20 -School Buses
21 -Motor Homes
uel
\
1
u
1
Paste Data Only
Editing VMT (vehicle miles traveled per weekday)
By Vehicle/Fuel/Hour
Fuel (l = Gas/2=Diesel/3=FJectiic)
z
3
4
5
6
7
3
9
10
11
12
13
14
IS
16
17
IS
19
20
21
i
1
2654502.0 3210.5 3767.7 1
6942192.5 3167.3 0.0 1
5802926.0 5605.0 0.0 1
1125473.1 6397S9.4 0.0 1
96861. 8 15268Z.S 0.0 1
147654.2 0.0 0. 0 1
0.0 0.0 0.0 1
0.0 0.0 0. 0 1
0_0 0_ 0 0. 0 1
0.0 0.0 0. 0 1
0.0 0.0 0. 0 1
39505.8 0.0 0.0 1
0.0 0.0 0. 0 1
0.0 0.0 0. 0 1
0.0 0.0 0. 0 1
33112.3 0.0 0. 0 1
| 31876.8 59091.6 0.0
242062.3 0.0 0. 0 •
7472.8 0.0 0. 0 1
73544.2 11321.4 0.0 |
^^^^^^^^^^^^m
Done
Default EMFAC2011-LDV data before modification
H-4
-------
Editing VMT data for scenario 1: Bus Idle and Start Emission Rates
Total VMT for area
Sacramento County I
Copy with Headings I
Paste Data Only I
Editing Mode Editing VMT (vehicle miles traveled per weekday)
TotalVMT] By Vehicle Class By Vehicle and Fuel | ByVehicle/Fuel/Hour
01 -Light-Duty Autos (PC)
02-Light-Duty Trucks (T1)
03-Light-Duly Trucks (T 2)
04 - Medium-Duty Trucks (T3)
05 • Light HD Trucks (T4)
06-Light HD Trucks (T5)
07 - CAIRPtOOS+IS Trc/Sngl (T6)
OB - Agriculture (T6)
09-Public*Utility(T6)
10-Out of State (T 7)
11-CAIRP(T7)
12-Instate Tractor (T7)
13-Instate Single (T7)
14-Port(Drayage)(T7)
15 - Agriculture (T7)
16 • Public+Util+SolioWaste|T7)
17-Other Buses
18-Urban Buses
19-Motorcycles
20 • School Buses
21 - Motor Homes
Fuel (1=Gas/2=Diesel/3=Electric)
Apply
Cancel
Modified EMFAC2011-LDV data
H-5
-------
Next, in Exhibit H-3 the default EMFAC2011-LDV vehicle population is similarly edited
to reflect an entirely diesel-fueled bus fleet.
Exhibit H-3. Changing EMFAC2011-LDV Default Population to Reflect Project-
Specific Fuel Use
Editing Population data for scenario 1 : Bus Idle and Start Emission Rates
Total Population for area
Sacramento County
Editing Mode
Total Population | By Vehicle Clas
01 -Light-Duty Autos (PC)
02-Light-DutyTrucks(T1)
03 -Light-Duty Trucks (T 2)
04 -Medium-Duty Trucks (T 3)
05- Light HD Trucks (T4)
06 - Light HD Trucks (T 5)
07 - CAIRP+OOS*IS Trc/Sngl (T6)
08- Agriculture (T6)
09- Public + Utility (T 6)
10 -Out of State (T 7)
11 -CAIRP(T7)
12- Instate Tractor (T7)
13 -Instate Single (T 7)
1 4 - Port (Drayage) (T7)
15-Agriculture(T7)
1 6 - Public*UtikSoliaWaste(T7)
17 -Other Buses
18 -Urban Buses
19 -Motorcycles
20 -School Buses
21 -Motor Homes
Apply
Copy with Headings
s By Vehicle
Editing F
and Fuel
\
1
ij
Paste Data Only
opulation (registered vehicles with adjustments)
3yVehicle/Fuel/Age]
Fuel (I = Gas/2=Diesel/3=Oectric)
1
2
3
4
5
6
7
3
0
1
2
3
4
5
6
7
3
19
20
21
i
497902.3
71285.5
172196.6
146270.0
26467.5
2274.8
3183. 5
0. 0
0. 0
0. 0
0. 0
0. 0
319. 7
0. 0
0. 0
0.0
769.4
246. 8
23510.2
171.7
5512.6
Caned
z
1931.0
93.8
81.2
144.0
15029.4
3599.7
Q.O
0.0
0.0
0.0
0,0
0.0
0.0
0.0
0.0
0.0
0.0
457.5
0.0
0.0
893.3
Done
3
420.4
93.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1
Default EMFAC2011-LDV data before modification
-------
Editing Population data for scenario 1: Bus Idle and Start Emission Rates
Total Population for area
Sactamento County I
Editing Mode
Total Population | By Vehicle Class
Editing Population (registered vehicles with adjustments)
By Vehicle and Fuel | By Vehicle/Fuel/Age j
01 -Lighl-Duty Autos (PC)
02 -Light-Duty Trucks (T1)
03 -Light-Duty Trucks (T 2)
04 - Medium-Duty Trucks (T3)
05 - Light HD Trucks (T 4)
06 - Light HD Trucks (T 5)
07 - CAIHP+OOS+IS Trc/Sngl (T6)
08- Agriculture (T6)
09 - Public + Utility (T6)
10 -Out of State (T 7)
11-CAIRP(T7)
12 -Instate Tractor (T 7)
13 -Instate Single (T7)
14-Port(Drayage)(T7J
15-Agriculture(T7)
16 - Public4JtikSoliaWaste(T7)
17 -Other Buses
18 -Urban Buses
19 - Motorcycles
20 - School Buses
21 • Motor Homes
\
!>
j
s
•2
f
1
2
3
4
0
1
Z
3
4
5
6
7
3
-?-
±
•
Fuel (1 = Gas/2=Diesel/3=Electric)
Z | 3
497302.3 1931.0 420.4
71285.5 93-8 99.0
172196.6 81.2 0.0
146270. 0 144.0 0.0
26467. 5 15029.4 0.0
2274.8 3599.7 0.0
3183. £ 0.0 0.0
0.0 0.0 0.0
0.0 0.0 0.0
0.0 0.0 0.0
0.0 0.0 0.0
0.0 0.0 0.0
319. 7 0.0 0.0
0.0 0.0 0.0
0.0 0.0 0.0
0.0 0.0 0.0
769. 4 0.0 0.0
1,0 704,0 0.0
28E10.2 0.0 0.0
171. 7 0.0 0.0
£512. 6 853. 3 0.0
Apply
Modified EMFAC2011-LDV data
Finally, in Exhibit H-4, it is necessary to export the default age distribution for
modification in Excel. The Urban Bus type has a default age distribution that does not
match the project. To change the default, zeros ("0") are entered for all ages except
"AgelO" to reflect a fleet that is entirely 10 year-old buses. The table is copied and
pasted back into the EMFAC2011-LDV module.
H-7
-------
Exhibit H-4. Changing EMFAC2011-LDV Default Age Distribution to Reflect
Project-Specific Bus Roster
Editing Population data for scenario 1: Bus Idle and Start Emission Rates
Total Population for area
Sacramento County I
Copy with Headings
Paste Data Only
Editing Mode Editing Population (registered vehicles with adjustments)
Total Population | By Vehicle Class | By Vehicle and Fuel By Vehicle^Fuel Age
\ Vehicle Class ^
4J
I
<
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
16 17
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
18
4.6
13.4
28.3
5.9
0.0
0.0
0.0
137.8
9.1
13.6
28.8
13.7
25.7
110.3
0.0
22.6
6.0
17.3
5.8
43.4
36.0
19
0.0
0.0 r IT
Fuel Type
o.o i
o.o Gas [
o"Q || Diesel |
0-0 _. .
Electric
0.0
o.o
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0 v
H^HI >
Done
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A BCD
Sacramento County Diesel P AgeOl AgeOZ Age03
01-Light-Duty Autos (PC) 133.4758 137.1166 152.1877
02-Light-Duty Trucks (Tl) 6.95752 7.152435 7.606674
03 - Light-Duty Trucks (T2) 4.866089 9.060982 10.413
04 -Medium-Duty Trucks (T2 S.03714 7.291153 8.159173
05-Light HD Trucks (T4) 707.3047 684.5059 650.1201
06-Light HD Trucks (T5) 171.5688 161.188 160.5263
07-CAIRP-t-OOS-HSTrc/Sngll 000
08-Agriculture (T6) 0 0
09-Public + Utility (T6) 0
10 - Out of State (T7) 0
11-CAIRP(T7) 0_ 0
12-Instate Tractor
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Editing Population data for scenario 1: Bus Idle and Start Emission Rates
Total Population for area
Sacramento County
Copy with Headings
Paste Data Only
Editing Mode Editing Population [registered vehicles with adjustments)
Total Population | By Vehicle Class | By Vehicle and Fuel By Vehicle/Fuel/Age I
Mr
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0.0
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19 20
0.0 0.0
0.0 0.0
0.0 0.0
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Modified EMFAC2011-LDV data
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H.6 PROCESSING IDLE EMISSION FACTORS
Urban Buses ("UBUS") is the vehicle class best representing transit buses in this
hypothetical bus terminal project. After the EMFAC2011-LDV run is completed, the
project-specific idle exhaust emission factors are presented in Table 1 of the output
Summary Rates file (.rts file) as shown in Exhibit H-5.
Exhibit H-5. EMFAC2011-LDV Output
C sac rame nto_t ransit. its - Notepad - LJ X
File Edit Format View Help
Pollutant Name: PM10
Humidity: 70%
speed
MPH
0
5
10
15
20
25
30
35
40
45
50
55
60
65
LDA
0.
0.
0.
0.
0.
0.
U.
0.
U.
0.
0.
0.
U.
0.
000
009
006
004
003
002
002
002
001
001
001
001
002
002
LOT
0.
0.
0.
0.
0.
0.
U.
0.
U.
0.
0.
0.
0.
0.
000
Oil
007
005
004
003
002
002
002
002
002
002
002
002
MDT
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
088
021
015
012
009
007
006
005
005
004
004
004
004
004
Temperature:
HOT
0.
0.
0.
0.
U.
0.
U.
0.
0.
0.
0.
0.
0.
0.
000
034 |
023
016
Oil
009
008
007
007
007
007
008
010
Oil
UBUS
0.000
0.106 1
0.077
0.058
0.045
0.036
0.030
0.026
0.023
0.022
0.021
0.021
0.021
0.023
A
70F Relative
MCY
0.000
0.001
0.001
0.001
0.001
0.001
0.000
0.000
0.001
0.001
0.001
0.001
0.001
0.001
ALL
0.018
0.013
0.009
0.006
0.005
0.004
0.003
0.003
0.002
0.002
0.002
0.002
0.002
0.003
V
As discussed, the Urban Bus type does not have an explicit idle emission rate. Therefore,
the 5 mph emission rate will be used to represent idle operation. As highlighted in
Exhibit H-5, the PMio 5 mph exhaust emission factor for the Urban Buses is 0.106
grams/veh-mile. In order to produce a grams/veh-hour emission factor for use in
AERMOD, this emission factor (0.106 grams/vehicle-mile) is multiplied by 5 miles per
hour. The resulting rate is 0.53 grams/veh-hour. Note that buses typically do not idle for
the entire hour, so this rate should be applied to the actual number of bus idle-hours (i.e.,
[grams/vehicle-hour] x [idling time of each vehicle in fraction of an hour] x [number of
vehicles]) expected in the project area to produce an updated grams/hour rate.
This completes the use of EMFAC2011-LDV for determining idle emission factors for
this project. The grams/hour idle rate can now be input into AERMOD as discussed in
Section 7 of the guidance.
H-ll
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Appendix I:
Estimating Locomotive Emissions
1.1 INTRODUCTION
This appendix describes how to quantify locomotive emissions when they are a
component of a transit or freight terminal or otherwise a source in the project area being
modeled. Note that state or local air quality agencies may have experience modeling
locomotive emissions and therefore could be of assistance when quantifying these
emissions for a PM hot-spot analysis.
Generally speaking, locomotive emissions can be estimated in the following manner:
1. Determine where in the project area locomotive emissions should be estimated.
2. Determine when to analyze emissions.
3. Describe the locomotive activity within the project area, including:
• The locomotives present in the project area (the "locomotive roster"); and
• The percentage of time each locomotive spends in various throttle settings
(the "duty cycle").
4. Calculate locomotive emissions using either:
• Horsepower rating and load factors, or
• Fuel consumption data.l
The estimated locomotive emission rates that result from this process would then be used
for air quality modeling. The interagency consultation process must be used to evaluate
and choose the model and associated method and assumptions used for quantifying
locomotive emissions for PM hot-spot analyses (40 CFR 93.105(c)(l)(i)).
1.2 DETERMINING WHERE IN THE PROJECT AREA LOCOMOTIVE
EMISSIONS SHOULD BE ESTIMATED
Under certain circumstances, it is appropriate to model different locations within the
project area as separate sources to characterize differences in locomotive type and/or
activity appropriately. This step is analogous to dividing a highway project into links (as
described in Sections 4.2 and 5.2 of the guidance) and improves the accuracy of
emissions modeling and subsequent air quality modeling. For example, in an intermodal
terminal, emissions from a mainline track (which will have a large percentage of higher
1 These are the two methods described in this appendix; others may be possible. See Appendix 1.5 for
details.
1-1
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speed operations with little idling) should be estimated separately from the associated
passenger or freight terminal (which would be expected to experience low speed
operations and significant idling).
The following activities are among those typically undertaken by locomotives and are
candidates for being modeled as separate sources if they occur at different locations
within the project area:
• Idling within the project area;
• Trains arriving into, or departing from, the project area (e.g., terminal arrival and
departure operations);
• Testing, idling, and service movements in maintenance areas or sheds;
• Switching operations;
• Movement of trains passing through, but not stopping in, the project area.
The project area may also be divided into separate sources if it includes several different
locomotive rosters (see Appendix 1.4.1, below)
1.3 DETERMINING WHEN TO ANALYZE EMISSIONS
The number of hours and days that have to be analyzed depends on the range of activity
expected to occur within the project area. For rail projects where activity varies from
hour to hour, day to day, and possibly month to month, it is recommended that, at a
minimum, project sponsors calculate emissions based on 24 hours of activity for both a
typical weekday and weekend day and for four representative quarters of the analysis
year when comparing emissions to all PIVb.s NAAQS.2 For projects in areas that violate
only the 24-hour PMio or PIVb.s NAAQS, the project sponsor may choose to model only
one quarter, in appropriate cases. See Section 3.3.4 of the guidance for further
information.
These resulting emission rates should be applied to AERMOD and used to calculate
design values to compare with the applicable PM NAAQS as described in Sections 7
through 9 of the guidance.
1.4 DESCRIBING THE LOCOMOTIVE ROSTERS AND DUTY CYCLES
Before calculating locomotive emission rates, it is necessary to know what locomotives
are present in the locations being analyzed in the project area (see Appendix 1.2, above)
and what activities these locomotives are undertaking at these locations. This data will
impact how emissions are calculated.
2 If there is no difference in activity between weekday and weekend activity, it may not be necessary to
examine weekend day activity separately. Similarly, if there is no difference in activity between quarters,
emission rates can be determined for one quarter, which can then be used to represent every quarter of the
analysis year.
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1.4.1 Locomotive rosters
Because emissions can vary significantly depending on a locomotive's make, model,
engine, and year of engine manufacture (or re-manufacture), it is important to know what
locomotives are expected to be operating within the project area. Project sponsors should
develop a "locomotive roster" (i.e., a list of each locomotive's make, model, engine, and
year) for the locomotives that will be operating within the specific project area being
analyzed. The more detailed the locomotive roster, the more accurate the estimated
emissions will be.
In some cases, it will be necessary to develop more than one locomotive roster to reflect
the operations in the project area accurately (for example, switcher locomotives may be
confined to one portion of a facility and therefore may be represented by their own
roster). In these situations, users should model areas with different rosters as separate
sources to account for the variability in emissions (see Appendix 1.2).
/. 4.2 Locomotive duty cycles
Diesel locomotive engine power is controlled by "notched" throttles; idling, braking, and
moving the locomotive is conducted by placing the throttle in one of several available
"notch settings."3 A locomotive's "duty cycle" is a description of how much time, on
average, the locomotive spends in each notch setting when operating. Project sponsors
should use the latest locally-generated or project-specific duty cycles whenever possible;
this information may be available from local railway authorities or the state or local air
agency.4 The default duty cycles for line-haul and switch locomotives, found in Tables 1
and 2 of 40 CFR 1033.530 (EPA's regulations on controlling emissions from
locomotives), should be used only if they adequately represent the locomotives that will
be present in the project area and no local or project-specific duty cycles are available.
1.5 CALCULATING LOCOMOTIVE EMISSIONS
Once a project's locomotive rosters and respective duty cycles have been determined,
locomotive emissions can then be calculated for each part of the project area using either
(1) horsepower rating and load factors, or (2) fuel consumption data. These two methods
are summarized below. Unless otherwise determined through consultation, only one
method should be used for a given project.
3 A diesel locomotive typically has eight notch settings for movement (run notches), in addition to one or
more idle or dynamic brake notch settings. Dynamic braking is when the locomotive engine, rather than
the brake, is used to control speed.
4 The state or local air agency may have previously developed locally-appropriate duty cycles for emissions
inventory purposes.
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/. 5.1 Finding emission factors
Regardless of method chosen, locomotive emissions factors will be needed for the
analysis. Locomotive emission factors depend on the type of engine, the power rating of
the locomotive (engine horsepower), and the year of engine manufacture (or re-
manufacture). Default PMio emission factors for line-haul and switch locomotives can be
obtained from Tables 1 and 2 of EPA's "Emission Factors for Locomotives," EPA-420-
F-09-025 (April 2009).5 These PMio emission factors are in grams/horsepower-hour and
can easily be converted to PIVb.s emission factors. However, these are simply default
values; locomotive-specific data may be available from manufacturers and should be
used whenever possible. In addition, see Appendix 1.5.4 for other variables that must be
considered when determining the appropriate locomotive emission factors.
Note that the default locomotive emission factors promulgated by EPA may change over
time as new information becomes available. The April 2009 guidance cited above
contains the latest emission factors as of this writing. Project sponsors should consult the
EPA's website at: www. epa. gov/otaq/locomotives.htm for the latest locomotive default
emission factors and related guidance.
/. 5.2 Calculating emissions using horsepower rating and load factors
One way locomotive emissions can be calculated is to use PM2 5 or PMio locomotive
emission factors, the horsepower rating of the engines found on the locomotive roster,
and engine load factors (which are calculated from the duty cycle).
Calculating Engine Load Factors
The horsepower of the locomotive engines, including the horsepower used in each notch
setting, should be available from the rail operator or locomotive manufacturer.
Locomotive duty cycle data (see Appendix 1.4.2) can then be used to determine how
much time each locomotive spends in each notch setting, including braking and idling.
An engine's "load factor" is the percent of maximum available horsepower it uses over
the course of its duty cycle. In other words, a load factor is the weighted average power
used by the locomotive divided by the engine's maximum rated power.6 Load factors can
be calculated by summing the actual horsepower-hours of work generated by the engine
in a given period of time and dividing it by the engine's maximum horsepower and the
hours during which the engine was being used, with the result expressed as a percentage.
For example, if a 4000 hp engine spends one hour at full power (generating 4000 hp-hrs)
and one hour at 50 percent power (generating 2000 hp-hrs), its load factor would be 75
5 Table 1 of EPA's April 2009 document includes default emission factors for higher power cycles
representative of general line-haul operation; Table 2 includes emission factors for lower power cycles used
for switching operations. The April 2009 document also includes information on how to convert PMi0
emission factors for PM2.5 purposes. Note that Table 6 (PM10 Emission Factors) should not be used for PM
hot-spot analyses, since these factors are national fleet averages rather than emission factors for any
specific project.
6 "Weighted average power" in this case is the average power used by the locomotive weighted by the time
spent in each notch, as explained further below.
1-4
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percent (6000 hp-hrs +• 4000 hp +• 2 hrs). Note that, in this example, it would be
equivalent to calculate the load factor using the percent power values instead: ((100% * 1
hr) + (50% * 1 hr) +• 2 hrs = 75%). To simplify emission factor calculations, it is
recommended that locomotive activity be generalized into the operational categories of
"moving" and "idling," with separate load factors calculated for each.
An engine's load factor is calculated by completing the following steps:
Step 1. Determine the number of notch settings the engine being analyzed has and the
horsepower used by the engine in each notch setting.7 Alternatively, as described above,
the percent of maximum power available in each notch could instead be used.
Step 2. Identify the percentage of time the locomotive being analyzed spends in each
notch setting based on its duty cycle (see Appendix 1.4.2).
Step 3. To make emission rate calculations easier, it is useful to calculate two separate
load factors for an engine: one for when the locomotive is idling and one for when it is
moving. Therefore, the percentage of time the locomotive spends in each notch (from
Step 2) needs to be adjusted so that all idling and all moving notches are considered
separately. For example, if a locomotive has just one idle notch setting, it spends 100%
of its idling time in that setting, even if it only idles during part of its duty cycle. While
calculating the time spent idling will usually be simple, for the non-idle (moving) notch
settings some additional adjustment to the locomotive's duty cycle percentages will be
required to determine the time spent in each moving notch as a fraction of total time spent
moving, disregarding any time spent idling.
For example, say a locomotive spends 30% of its time idling and 70% of its time moving
over the course of its duty cycle and that 15% of this total time (idling and moving
together) is spent in notch 2. When calculating the moving load factor, this percentage
needs to be adjusted to determine what fraction of just the 70% of time spent moving is
spent in notch 2. In this example, 15% of the total duty cycle spent in notch 2 would
equal 21.4% (15% * 100% - 70%) of the locomotive's time when it is not at idle; that is,
whenever it is moving, this locomotive spends 21.4% of its time in notch 2. This
calculation is repeated for each moving notch setting. The result will be the fraction of
time spent in each notch when considering idle and moving modes of operation
separately.
Step 4. The next step is to calculate what fraction of maximum available horsepower is
being used based on the time spent in each notch setting as was calculated in Step 3. This
is determined by summing the product of the percentage of time spent in each notch
(calculated in Step 3) by the horsepower generated by the engine at that notch setting
(determined in Step 1). For example, if the locomotive with a rated engine power of
7 For locomotives that are equipped with multiple dynamic braking notches and/or multiple idle notches, it
may be necessary to assume a single dynamic braking notch and a single idle notch, depending on what
information is available about the particular engine.
8 In this case, "moving" refers to all non-idle notch settings: that is, dynamic braking and all run notches.
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3000 hp spends 21.4% of its moving time in notch 2 and 78.6% of its moving time in
notch 6, and is known to generate 500 hp while in notch 2 and 2000 hp while in notch 6,
then its weighted average power would be 1679 hp (107 hp (500 hp * 0.214) + 1572 hp
(2000 hp *0.786) = 1679 hp).
Step 5. The final step is to determine the load factors. This is done by dividing the
weighted average horsepower (calculated in Step 4) by the maximum engine horsepower.
For idling, this should be relatively simple. For example, if there is one idle notch setting
and it is known that a 4000 hp engine uses 20 hp when in its idle notch, then its idle load
factor will be 0.5% (20 hp +• 4000 hp). To determine the load factor for all power
notches, the weighted horsepower calculated in Step 4 should be divided by the total
engine horsepower. For example, if the same 4000 hp engine is determined to use an
average of 1800 hp while in motion (as determined by adjusting the horsepower by the
time spent in each "moving" notch setting in Step 4), then the moving load factor would
be 45% (1800 hp - 4000 hp).
The resulting idling and moving load factors represent the average amount of the total
engine horsepower the locomotive is using when idling and moving, respectfully. These
load factors can then be used to modify PM emission factors and generate emission rates
as described below.
Generating Emission Rates Based on Load Factors
As noted above, EPA's "Emission Factors for Locomotives" provides emission factors in
grams/brake horsepower-hour. This will also likely be the case with any specific
emission factors obtained from manufacturer's specifications. These units can be
converted into grams/second (g/s) emission rates by using the load factor on the engines
and the time spent in each operating mode, as described below.
The first step is to adjust the PM emission factors to reflect how the engine will actually
be operating.9 This is done by multiplying the appropriate PM emission factor by the
idling and moving load factors calculated for that particular engine.10 Next, to determine
the emission rate, this adjusted emission factor is further multiplied by the amount of
time the locomotive spends idling and moving while in the project area.u
For example, if the PM emission factor known to be 0.18 g/bhp-hr, the engine being
analyzed has an idling load factor of 0.5%, and the locomotive is anticipated to idle 24
minutes per hour in the project area, then the resulting emission rate would be 0.035
grams/hour (0.18 g/bhp-hr * 0.5% * 0.4 hours).
Because combustion characteristics of an engine vary by throttle notch position, it is appropriate to adjust
the emission factor to reflect the average horsepower actually being used by the engine.
10 Project sponsors are reminded to check www.epa.gov/otaq/locomotives.htm to ensure the latest default
emission factors for idle and moving emissions are being used.
11 Note that this may or may not match up with the idle and moving time as described by the duty cycle
used to calculate the load factors, depending on how project-specific that duty cycle is.
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Emission rates need to be converted into g/s for use by AERMOD, as described further in
Sections 7 through 9 of the guidance. These calculations should be repeated until the
entire locomotive roster is represented in each part of the project area being analyzed.
Appendix 1.7 provides an example of calculating g/s locomotive emission rates using this
methodology.
7.5.3 Calculating emissions using fuel consumption data
Another method to calculate locomotive emissions involves using fuel consumption data.
Chapter 6.3 of EPA's "Procedure for Emission Inventory Preparation ~ Volume IV:
Mobile Sources" (reference information provided in Appendix 1.6, below) is a useful
reference and should be consulted when using this method.
Note that, for this method, it may be useful to scale down data already available to the
project sponsor. For example, if rail car miles/fuel consumption is known for trains
operating in situations identical to those being estimated in the project area, this data can
be used to estimate fuel consumption rates for a defined track length within the project
area.
Calculating Average Fuel Consumption
Locomotive fuel consumption is specific to a particular locomotive engine and the
throttle (notch) setting it is using. Data on the fuel consumption of various engines at
different notch settings can often be obtained from the locomotive or engine
manufacturer's specifications. When only partial data is available (e.g., only data for the
lowest and highest notch settings are known), interpolation combined with best available
engineering judgment can be used to determine fuel consumption at the intermediate
notch settings.
A locomotive's average fuel consumption can be calculated by determining how long
each locomotive is expected to spend in each notch setting based on its duty cycle (see
Appendix 1.4.2). This data can be aggregated to generate an average fuel consumption
rate for each locomotive type. See Chapter 6.3 of Volume IV for details on how to
generate this data based on a specific locomotive roster and duty cycle.
Once the average fuel consumption rates have been determined, they should be
multiplied by the appropriate emission factors to determine a composite average hourly
emission rate for each engine in the roster. Since the objective is to determine an average
fuel consumption rate for the entire locomotive roster, this calculation should be repeated
for each engine on the roster at each location analyzed.
If several individual sources will be modeled at different sections of the project area as
described in Appendix 1.2, train schedule data should be consulted to determine the hours
of operation of each locomotive within each section of the project area. Hourly emission
rates per locomotive should then be multiplied by the number of hours the locomotive is
1-7
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operating, for each hour of the day in each section of the project area to provide average
hourly emission rates for each section of the project. These should then be converted to
grams/second for use in AERMOD, as described further in Sections 7 through 9 of the
guidance.
Examples of calculating locomotive emissions using this method can be found in Chapter
6 of Volume IV.
/. 5.4 Factors influencing locomotive emissions and emission factors
The following considerations will influence locomotive emissions regardless of the
method used and should be examined when determining how to characterize locomotives
for emissions modeling or when choosing the appropriate emission factors:
• Project sponsors should be aware of the emission reductions that would result
from remanufacturing existing locomotives (or replacing existing locomotives
with new locomotives) that meet EPA's Tier 3 or Tier 4 emission standards when
they become available. The requirements that apply to existing and new
locomotives were addressed in EPA's 2008 rulemaking entitled "Control of
Emissions of Air Pollution from Locomotive Engines and Marine Compression-
Ignition Engines Less Than 30 liters Per Cylinder" (73 FR 37095). Beginning in
2012 all locomotives will be required to use ultra-low sulfur diesel fuel (69 FR
38958). Additionally, when existing locomotives are remanufactured, certified
remanufacture systems will have to be installed to reduce emissions. Beginning
in 2011, new locomotives must meet tighter Tier 3 emission standards. Finally,
beginning in 2015 even more stringent Tier 4 emission standards for new
locomotives will begin to be phased in.
• For locomotives manufactured before 2005, a given locomotive may be in one of
three possible configurations, depending on when it was last remanufactured: (1)
uncertified; (2) certified to the standards in 40 CFR Part 92; or (3) certified to the
standards in 40 CFR Part 1033. Each of these configurations should be treated as
a separate locomotive type when conducting a PM hot-spot analysis.
• Emissions from locomotives certified to meet Family Emission Limits (FELs)
may differ from the emission standard identified on the engine's Emission
Control Information label. Rail operators will know if their locomotives
participate in this program. Any locomotives in the project area participating in
this program should be identified so that the actual emissions from the particular
locomotives being analyzed are considered in the analysis, rather than the family
emissions level listed on their FEL labels.
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1.6 AVAILABLE RESOURCES
These resources and websites should be checked prior to beginning any PM hot-spot
analysis to ensure that the latest data (such as emission factors) are being used:
• "Emission Factors for Locomotives," EPA-420-F-09-025 (April 2009). Available
online at: www.epa. gov/otaq/locomotives.htm.
• Chapter 6 of "Procedure for Emission Inventory Preparation - Volume IV: Mobile
Sources." Available online at: www.epa.gov/OMS/invntory/r92009.pdf. Note
that, as of this writing, the emission factors listed in Volume IV have been
superseded by the April 2009 publication listed above for locomotives certified to
meet current EPA standards.12
• "Control of Emissions from Idling Locomotives," EPA-420-F-08-014, March
2008. Available online at:
www. epa. gov/otaq/regs/nonroad/locomotv/420f08014. htm.
• See Section 10 of the guidance for additional information regarding potential
locomotive emission control measures.
1.7 EXAMPLE OF CALCULATING LOCOMOTIVE EMISSION RATES USING
HORSEPOWER RATING AND LOAD FACTOR ESTIMATES
The following example demonstrates how to estimate locomotive emissions using the
engine horsepower rating/load factor method described in Appendix 1.5.2.
The hypothetical proposed project in this example includes the construction of an
intermodal terminal in an area that is designated as nonattainment for both the 1997
annual PM2.5 NAAQS and the 2006 24-hour PM2.5 NAAQS. The terminal in this
example is to be completed and operational in 2013. The hot-spot analysis is performed
for 2015, because it is determined through interagency consultation that this will be the
year of peak emissions, when considering the project's emissions and the other emissions
in the project area.
In this example, the operational schedule anticipates that 32 locomotives will be in the
project area over a 24-hour period, with 16 locomotives in the project area during the
peak hour. Based on the schedule, it is further determined that while in the project area
each train will spend 540 seconds idling and 76 seconds moving.
12 Although the emission factors have been superseded, the remainder of the Volume IV guidance remains
in effect.
1-9
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The locomotive PIVb.s emissions are calculated based on horsepower rating and load
factors.
/. 7.1 Calculate idle and moving load factors
As described in 1.5.2, the project sponsor uses a series of steps to calculate load factors.
These steps are described below and the results from each step are shown in table form in
Exhibit I-1.
Step 1: The project sponsor first needs some information about the locomotives expected
to be operating at the terminal in the analysis year.
For each locomotive, the horsepower used by the locomotive in each notch setting as well
as under dynamic braking and at idle must be determined. For the purpose of this
example it is assumed that all of the locomotives that will serve this terminal are very
similar: all use the same horsepower under each of operating conditions, and all have
only one idle and dynamic braking notch setting. The horsepower generated at each
notch setting is obtained from the engine specifications (see second column of Exhibit I-
1). In this case, the rated engine horsepower is 4000 hp (generated at notch 8).
Step 2: The next step is to determine the average amount of time that the locomotives
spend in each notch and expressing the results as a percentage of the locomotive's total
operating time. In this example, it is determined that, based on their duty cycle, the
locomotives that will service this terminal spend 38% of their time idling and 62% of
their time in motion in one of the eight run notch settings or under dynamic braking. The
percentage of time spent in each notch is shown in the third column of Exhibit 1-1.
Step 3: To make emission factor calculations easier, it is decided to calculate separate
idling and moving load factors. The next step, then, is for the project sponsor to calculate
the actual percentage of time that the locomotives spend in each notch, treating idling and
moving time separately. This is done by excluding the time spent idling and
recalculating the percentage of time spent in the other notches (i.e., dynamic braking and
each of the eight notch settings) so that the total time spent in non-idle notches adds to
100%. The results are shown in the fourth column of Exhibit 1-1.
Step 4: The next step is to calculate the weighted average horsepower for this engine
using the horsepower generated in each notch and the percentage of time spent in each
notch as adjusted in Step 3. For locomotives that are idling, this is simply the horsepower
used at idle. For the other notches, the actual horsepower for each notch is determined by
multiplying the horsepower generated in a given notch (determined in Step 1) by the
actual percentage of time that the locomotive is in that notch, as adjusted (calculated in
Step 3). The results are shown in the fifth column of Exhibit 1-1.
Step 5: The final step in this part of the analysis is to determine the idle and moving load
factors. The idle load factor is just the horsepower generated at idle divided by the
maximum engine horsepower, with the result expressed as a percentage. To determine
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the moving load factor, the weighted average horsepower for all non-idle notches
(calculated in Step 4) is divided by the maximum engine horsepower, with the result
expressed as a percentage. The final column of Exhibit 1-1 shows the results of these
calculations, with the idling and moving load factors highlighted.
Exhibit 1-1. Calculating Locomotive Load Factors
Notch
Setting
Step 1:
Horsepower
(hp)
used in
notch
Step 2:
Average %
time spent
in notch
Step 3:
Reweighted
time spent in
each notch
(adjusted so
that non-idle
notches add to
100%)
Step 4:
Time-
weighted
hp used,
based on
time
spent in
notch
Step 5:
Load
factors
(idle and
moving)
Idling load factor:
Idle
14
38.0%
100.0%
14.0
0.4%
Moving load factor:
Dynamic
Brake
1
2
3
4
5
6
7
8
Total
136
224
484
984
1149
1766
2518
3373
4,000
12.5%
6.5%
6.5%
5.2%
4.4%
3.8%
3.9%
3.0%
16.2%
62.0%
20.2%
10.5%
10.5%
8.4%
7.1%
6.1%
6.3%
4.8%
26.1%
100.0%
27.5
23.5
50.8
82.7
81.6
107.8
158.6
161.9
1,044.0
1,752.4
43.8%
/. 7.2 Using the load factors to calculate idle and moving emission rates
Now that the idle and moving load factors have been determined, the gram/second (g/s)
emission rates can be calculated for the idling and moving locomotives.
First, the project sponsor would determine how many locomotives are projected to be
idling and how many are projected to be in motion during the peak hour of operation and
over a 24-hour period. As previously noted, it is anticipated that 32 locomotives will be
in the project area over a 24-hour period, with 16 locomotives in the project area during
the peak hour. It was further determined that, while in the project area, each train will
spend 540 seconds idling and 76 seconds moving.
For the purpose of this example, it has been assumed that each locomotive idles for the
same amount of time and is in motion for the same amount of time. Note that, in this
case, the number of locomotives considered "moving" will be double the actual number
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of locomotives present in order to account for the fact that each locomotive moves twice
through the project area (as it arrives and departs the terminal).
Next, the project sponsor would determine the PM2.5 emission factor to be used in this
analysis for 2015. These emission factors can be determined from the EPA guidance
titled "Emission Factors for Locomotives."
Table 1 of "Emission Factors for Locomotives" presents PMio emission factors in terms
of grams/brake horsepower-hour (g/bhp-hr) for line haul locomotives that are typically
used by commuter railroads. Emission factors are presented for uncontrolled
locomotives, locomotives manufactured to meet Tier 0 through Tier 4 emission
standards, and locomotives remanufactured to meet more stringent emission standards.
It's important to determine the composition of the fleet of locomotives that will use the
terminal in the year that is being analyzed so that the emission factors in Table 1 can be
used in the calculations. This information would be available from the railway operator.
In this example, we are assuming that all of the locomotives meet the Tier 2 emission
standard. However, an actual PM hot-spot analysis would likely have a fleet of
locomotives that meets a combination of these emission standards. The calculations
shown below would have to be repeated for each different standard that applies to the
locomotives in the fleet.
The final step in these calculations is to use the information shown in Exhibit 1-1 and the
other project data collected to calculate the PM2 5 emission rates for idling and moving
locomotives during both the peak hour and over a 24-hour basis.13
Calculating Peak Hour Idling Emissions
The following calculation would be used to determine the idling emission rate during the
peak hour of operation:14
PM2.5 Emission Rate = (16 trains/hr) * (1 hr/3,600 s) * (540 s/train) * (4,000 hp) *
(0.004) * (0.18 g/bhp-hr) * (1 hr/3,600 s) * (0.97)
PM2.5 Emission Rate = 0.0019 g/s
Where:
• Trains per hour =16 (number of trains present in peak hour)
• Idle time per train = 540 s (from anticipated schedule)
• Locomotive horsepower = 4,000 hp (from engine specifications)
• Idle load factor = 0.004 (0.4%, calculated in Exhibit 1-1)
13 Peak hour emission rates will not be necessary for all analyses; however, for certain projects that involve
very detailed air quality modeling analyses, peak hour emission rates may be necessary to more accurately
reflect the contribution of locomotive emissions to air quality concentrations in the project area.
14 Note that, for the calculations shown here, any units expressed in hours or days need to be converted to
seconds since a g/s emission rate is required for AERMOD.
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• Tier 2 Locomotive Emission Factor = 0.18 g/bhp-hr (from "Emission
Factors for Locomotives")
• Ratio of PM2.5 to PMio = 0.97 (from "Emission Factors for Locomotives")
Calculating 24-hour Moving Emissions
Similarly, the following equation would be used to calculate the moving emission rate for
the 24-hour period:
PM2.5 Emission Rate = (64 trams/day) * (76 s/tram) * (1 day/86,400 s) * (4,000 hp) *
(0.438) * (0.18 g/bhp-hr) * (lhr/3,600 s) * (0.97)
PM2.5 Emission Rate = 0.0048 g/s
Where:
Trains per day = 64 (double the actual number of trains present over 24
hours to account for each train moving twice through the project area)
Moving time per train = 76 s (from anticipated schedule)
Locomotive horsepower = 4,000 hp (from engine specifications)
Moving load factor = 0.438 (43.8%, calculated in Exhibit 1-1)
Tier 2 Locomotive Emission Factor = 0.18 g/bhp-hr (from "Emission
Factors for Locomotives")
Ratio of PM2.sto PMio= 0.97 (from "Emission Factors for Locomotives")
A summary of the variables used in the above equations and the resulting emission rates
can be found in Exhibit 1-2, below.
Exhibit 1-2. PMi.5 Locomotive Emission Rates
Operational
Mode
Idle
Moving
Number of
Locomotives
Peak
hour
16
32
24
hours
32
64
Time/
Train
(s)
540
76
PM25
Emission
Factor
(g/bhp-hr)
0.18
0.18
Calculated
Peak Hour
Emission Rate
(g/s)
0.0019
0.057
Calculated
24-hour
Emission
Rate
(g/s)
0.00016
0.0048
These peak and 24-hour emission rates can now be used in air quality modeling for the
project area, as described in Sections 7 through 9 of the guidance.
Note that, since this area is designated as nonattainment for both the 1997 annual PM2 5
NAAQS and the 2006 24-hour PM2.5NAAQS, the results of the analysis will be
compared to both NAAQS (see Section 3.3.4 of the guidance). Since the area is in
nonattainment of the annual PM2 5 NAAQS, all four quarters will need to be included in
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the analysis to estimate a year's worth of emissions. If there is no change in locomotive
activity across quarters, the emission rates calculated here could be used for each quarter
of the year (see Appendix 1.3).
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Appendix J:
Additional Reference Information on Air Quality Models and
Data Inputs
J.I INTRODUCTION
This appendix supplements Section 7's discussion of air quality models. Specifically,
this appendix describes how to configure AERMOD and CAL3QHCR for PM hot-spot
analysis modeling, as well as additional information on handling the data required to run
the models for these analyses. This appendix is not intended to replace the user guides
for air quality models, but discuss specific model inputs, keywords, and formats for PM
hot-spot modeling. This appendix is organized so that it references the appropriate
discussions in Section 7 of the guidance.
J.2 SELECTING AN APPROPRIATE AIR QUALITY MODEL
The following discussion supplements Section 7.3 of the guidance and describes how to
appropriately configure AERMOD and CAL3QHCR when completing a PM hot-spot
analysis. Users should also refer to the model user guides, as appropriate.
J. 2.1 Using AERMOD for PM hot-spot analyses
There are no specific commands unique to transportation projects that are necessary when
using AERMOD. By default, AERMOD produces output for particulate matter in units
of micrograms per cubic meter of air (|j,g/m3). All source types in AERMOD require that
emissions are specified in terms of emissions per unit time, although AREA-type sources
also require specification of emissions per unit time per unit area. AERMOD has no
specific traffic queuing mechanisms. Emissions output from MOVES, EMFAC, AP-42,
and other types of methods should be formatted as described in the AERMOD User
Guide. *
J. 2.2 Using CALSQHCRfor PM hot-spot analyses
CAL3QHCR is an extension of the CAL3QHC model that allows the processing of a full
year of hourly meteorological data, the varying of traffic-related inputs by hour of the
week, and calculation of long-term average concentrations. It also will display the five
highest concentration days for the time period being modeled. Emissions output from
MOVES, EMFAC, AP-42, and other emission methods should be formatted as described
1 Extensive documentation is available describing the various components of AERMOD, including user
guides, model formulation, and evaluation papers. See EPA's SCRAM website for AERMOD
documentation: www.epa.gov/scramOO I/dispersion prefrec.htm#aermod.
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in the CAL3QHCR User Guide.2 In addition, the following guidance is provided when
using CAL3QHCR for a PM hot-spot analysis:
Specifying the Right Pollutant
When using CAL3QHCR for PM hot-spot analyses, the MODE keyword must be used to
specify analyses for PM so that concentrations are described in micrograms per cubic
meter of air (|j,g/m3) rather than parts per million (ppm).
Entering Emission Rates
MOVES emission rates for individual roadway links are based on the Op-Mode
distribution associated with each link and are able to include emissions resulting from
idling. MOVES-based emission factors that incorporate relevant idling time and other
delays should be entered in CAL3QHCR using the EFL keyword. Therefore, within
CAL3QHCR, the IDLFAC keyword's emission rates should be set to zero, because the
effects of idling are already included within running emissions. (Note that if a non-zero
emission rate is used in CAL3QHCR, the model will treat idling emission rates separately
from running emission rates.) The same recommendation applies when using emission
rates calculated by EMFAC.
Assigning Speeds
Although the user guide for CAL3QHCR specifies that the non-queuing links should be
assigned speeds in the absence of delay caused by traffic signals, the user should use
speeds that reflect delay when using CAL3QHCR for a hot-spot analysis. Since MOVES
emission factors already include the effects of delay (i.e., Op-Mode distributions that are
user-specified or internally calculated include the effects of delay), the speeds used in
CAL3QHCR links will already reflect the relevant delay on the link over the appropriate
averaging time. The same recommendation applies when using EMFAC.
Using the Queuing Algorithm
When applying CAL3QHCR for the analysis of highway and intersection projects, its
queuing algorithm should not be used.3 This includes the CAL3QHCR keywords
NLANE, CAVG, RAVG, YFAC, IV, and IDLFAC. As discussed in Sections 4 and 5,
idling vehicle emissions should instead be accounted for by properly specifying links for
emission analysis and reflecting idling activity in the activity patterns used for MOVES
or EMFAC modeling.
2 The CAL3QHCR user guide and other model documentation can be found on EPA's SCRAM website:
www. epa. gov/scramOO 1 /dispersion_prefrec. htm#cal3 qhc.
3 CALSQHCR's algorithm for estimating the length of vehicle queues associated with intersections is based
on the 1985 Highway Capacity Manual, which is no longer current. Furthermore, a number of other
techniques are now available that can be used to estimate vehicle queuing around intersections.
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J.3 CHARACTERIZING EMISSION SOURCES
The following discussion supplements Section 7.4 of the guidance and describes in more
detail how to characterize sources in CAL3QHCR and AERMOD, including the physical
characteristics, location, and timing of sources. This discussion assumes the user is
familiar with handling data in these models, including the use of specific keywords. For
additional information, refer to the CAL3QHCR and AERMOD user guides.
J. 3.1 Physical characteristics and locations of sources in CAL3QHCR
CAL3QHCR characterizes highway and intersection projects as line sources. The
geometry and operational patterns of each roadway link are described using the following
variables, which in general may be obtained from engineering diagrams and design plans
of the project:4
• The coordinates (X, Y) of the endpoints of each link;5
• The width of the "highway mixing zone" (see below);
• The type of link ("at grade," "fill," "bridge," or "depressed");
• The height of the roadway relative to the surrounding ground (not to exceed ±10
meters);6 and
• The hourly flow of traffic (vehicles per hour).
CAL3QHCR treats the area over each roadway link as a "mixing zone" that accounts for
the area of turbulent air around the roadway resulting from vehicle-induced turbulence.
The width of the mixing zone is an input to the model. Users should specify the width of
a link in CAL3QHCR as the width of the traveled way (traffic lanes, not including
shoulders) plus three meters on either side. Users should treat divided highways as two
separate links. See Section 7.6 of the guidance for more information on placing
receptors.
J. 3.2 Timing of emissions in CAL3QHCR
The CAL3QHCR User Guide describes two methods for accepting time-varying
emissions and traffic data; these are labeled the "Tier I" and "Tier II" approaches.7
4 Traffic engineering plans and diagrams may include information such as the number, width, and
configuration of lanes, turning channels, intersection dimensions, and ramp curvature, as well as
operational estimates such as locations of weave and merge sections and other descriptions of roadway
geometry that may be useful for specifying sources.
5 In CAL3QHCR, the Y-axis is aligned due north.
6 The CALINE3 dispersion algorithm in CAL3QHCR is sensitive to the height of the road. In particular,
the model treats bridges and above-grade "fill" roadways differently. It also handles below-grade roadways
with height of less than zero (0) meters as "cut" sections. Information on the topological features of the
project site is needed to make such a determination. Note that in the unusual circumstance that a roadway
is more than ten meters below grade, CALINE3 has not been evaluated, so CAL3QHCR is not
recommended for application. In this case, the relevant EPA Regional Office should be consulted for
determination of the most appropriate model.
7 This nomenclature is unrelated to EPA's motor vehicle emission standards and the design value
calculation options described in Section 9 of this guidance.
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Project-level PM hot-spot modeling should use the Tier II method, which can
accommodate different hourly emission patterns for each day of the week. Most
emissions data will not be so detailed, but the Tier II approach can accommodate
emissions data similar to that described in Sections 4 and 5 of the guidance. The
CAL3QHCR Tier I approach should not be used, as it employs only one hour of
emissions and traffic data and therefore cannot accommodate the emissions data required
in a PM hot-spot analysis.
Through the IPATRY keyword, CAL3QHCR allows up to seven 24-hour profiles
representing hour-specific emission, traffic, and signalization (ETS) data for each day of
the week. Depending on the number of MOVES runs, the emission factors should be
mapped to the appropriate hours of the day. For example, peak traffic emissions data for
each day would be mapped to the CAL3QHCR entry hours corresponding to the relevant
times of day (in this case, the morning and afternoon peak traffic periods). If there are
more MOVES runs than the minimum specified in the Section 4, they should be modeled
and linked to the correct days and hours using IPATRY.
As described in Section 7 of the guidance, the number of CAL3QHCR runs required for a
given PM hot-spot analysis will vary based on the amount of meteorological data
available.
J. 3.3 Physical characteristics and locations of sources in AERMOD
The following discussion gives guidance on how to best characterize a source.
AERMOD includes different commands (keywords) for volume, area, and point sources.
Modeling Volume Sources
Many different sources in a project undergoing a PM hot-spot analysis might be modeled
as volume sources. Examples include areas designated for truck or bus queuing or idling
(e.g., off-network links in MOVES), driveways and pass-throughs in transit or freight
terminals, and locomotive emissions.8 AERMOD can also approximate a highway "line
source" using a series of adjacent volume sources (see the AERMOD User Guide for
suggestions). Certain nearby sources that have been selected to be modeled may also be
appropriately treated as a volume source (see Section 8 of the guidance for more
information on considering background concentrations from other sources).
Volume source parameters are entered using the source parameter (SRCPARAM)
keyword in the AERMOD input file. This requires the user to provide the following
information:
• The emission rate (mass per unit time, such as g/s);
• The initial lateral dispersion coefficient determined from the initial lateral
dimension (width) of the volume;
See Section 6 and Appendix I for information regarding calculating locomotive emissions.
J-4
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The initial vertical dispersion coefficient determined from the initial vertical
dimension (height) of the volume; and
The source release height of the volume source center, (i.e., meters above the
ground).
Within AERMOD, the volume source algorithms are applicable to line sources with some
initial plume depth (e.g., highways, rail lines).9
characterize the initial size of a roadway plume:
initial plume depth (e.g., highways, rail lines).9 There are three inputs needed to
1. Initial lateral dispersion coefficient (oyn. Syinif). First, estimate the initial lateral
dimension (or width) of the volume source. One of the following options can be
used:
a) The average vehicle width plus 6 meters, when modeling a single lane of
traffic;
b) The road width multiplied by 2; or
c) A set width, such as 10 meters per lane of traffic.
To specify the initial lateral dispersion coefficient (oyo), referred to as Syinit in
AERMOD, the AERMOD User Guide recommends dividing the initial width by 2.15.
This is to ensure that the overlapping distributions from adjacent volume sources
simulate a line source of emissions.
2. Initial vertical dispersion coefficient (o70, Szinif). First, estimate the initial vertical
dimension (height) of the plume for volume sources. A typical approach is to assume
it is about 1.7 times the average vehicle height, to account for the effects of vehicle-
induced turbulence. For light-duty vehicles, this is about 2.6 meters, using an average
vehicle height of 1.53 meters or 5 feet. For heavy-duty vehicles, this is about 6.8
meters, using an average vehicle height of 4.0 meters. Since most road links will
consist of a combination of light-duty and heavy-duty traffic, the initial vertical
dimension should be a combination of their respective values. There are two options
available to estimate initial vertical dimension:
a) Estimate the initial vertical dimension using an emissions-weighted average.
For example, if light-duty and heavy-duty vehicles contribute 40% and 60%
of the emissions of a given volume source, respectively, the initial vertical
dimension would be (0.4 * 2.6) + (0.6 * 6.8) = 5.1 meters.
b) Alternatively, the initial vertical dimension may be estimated using a traffic
volume weighted approach based on light-duty and heavy-duty vehicle
fractions.
The AERMOD User Guide recommends that the initial vertical dispersion coefficient
(ozo), termed Szinit in AERMOD, be estimated for a surface-based volume source by
dividing the initial vertical dimension by 2.15. For typical light-duty vehicles, this
9 The vehicle-induced turbulence around roadways with moving traffic suggests that prior to transport
downwind, a roadway plume has an initial size; that is, the emissions from the tailpipe are stirred because
the vehicle is moving and therefore the plume "begins" from a three-dimensional volume, rather than from
a point source (the tailpipe).
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corresponds to a Szinit (ozo) of 1.2 meters. For typical heavy-duty vehicles, the initial
value of Szinit (ozo) is 3.2 meters.
3. Source release height. The source release height (Relhgt in AERMOD), which is
the height at which wind effectively begins to affect the plume, may be estimated
from the midpoint of the initial vertical dimension. For moving light-duty vehicles,
this is about 1.3 meters. For moving heavy-duty vehicles, it is 3.4 meters. Since
most road links will consist of a combination of light-duty and heavy-duty traffic, the
source release height should be a combination of their respective values. There are
two options available to estimate source release height:
a) Estimate using an emissions-weighted average. For a 40% light-duty and
60% heavy-duty emissions share, the source release height would be (0.4 *
1.3)+ (0.6* 3.4) = 2.6 meters.
b) Alternatively, the source release height may be estimated using a traffic
volume weighted approach based on light-duty and heavy-duty VMT.
Another way of dealing with Syinit, Szinit, and/or Relhgt parameters that change as a
result of different fractions of light-duty and heavy-duty vehicles is to create two
overlapping versions of each roadway source, corresponding to either light-duty and
heavy-duty traffic. These two sources could be superimposed in space, but have
emission rates and Syinit, Szinit, and Relhgt parameters that are specific to light-duty or
heavy-duty traffic.
Also, AERMOD (version dated 09292) allows Syinit, Szinit, and Relhgt to change by
hour of the day, which may be considered if the fraction of heavy-duty vehicles is
expected to significantly change throughout a day. Users should consult the latest
information on AERMOD when starting a PM hot-spot analysis.
Groups of idling vehicles may also be modeled as one or more volume sources. In those
cases, the initial dimensions of the source, dispersion coefficients, and release heights
should be calculated assuming that the vehicles themselves are inducing no turbulence.
When using adjacent volume sources to represent emissions from a source such as a
roadway, a sufficient number of volume sources should be employed to represent a
consistent density of emissions for a single link in a MOVES or EMFAC analysis. In
addition, when the source-receptor spacing in AERMOD is shorter than the distance
between adjacent volume sources, AERMOD may produce aberrant results. In the
present version of the model, receptors within a volume source in AERMOD are assigned
concentrations of zero. When volume sources are used and publicly-accessible locations
are closer to a source than the distance between adjacent volume sources, it is
recommended that smaller volume sources be used with shorter spacing between them.
For example, for such a segment along a highway segment, individual lanes might be
modeled discretely, rather than using a single volume source for all lanes. This will
reduce the spacing between volume sources and increase the quality of results closest to a
source. Receptors near area and point sources are not affected by this concern.
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Consult the AERMOD User Guide and AERMOD Implementation Guide for details in
applying AERMOD to roadway sources.
Modeling Area Sources
AERMOD can represent rectangular, polygon-shaped, and circular area sources using the
AREA, AREAPOLY, or AREACIRC keywords. Sources that may be modeled as area
sources may include areas within which emissions occur relatively evenly, such as a
single link modeled using MOVES or EMFAC.10 Evenly-distributed ground-level
sources might also be modeled as area sources.
AERMOD requires the following information when modeling an area source:
• The emission rate per unit area (mass per unit area per unit time);
• The release height above the ground;
• The length of the north-south side of the area;
• The length of the east-west side of the area (if the area is not a square);
• The orientation of the rectangular area in degrees relative to north; and
• The initial height (vertical dimension) of the area source plume.
In using a series of area sources to represent emissions of a roadway, the release height
and initial vertical dimension of the plume should be calculated as described above for
volume sources.
Modeling Point Sources
It may be appropriate to model some emission sources as fixed point sources, such as
exhaust fans or stacks on a bus garage or terminal building. If a source is modeled with
the POINT keyword in AERMOD, the model requires:
• The emission rate (mass per unit time);
• The release height above the ground;
• The exhaust gas exit temperature;
• The stack gas exit velocity; and,
• The stack inside diameter in meters.
These parameters can often be estimated using the plans and engineering diagrams for
ventilation systems.
For projects with emissions on or near rooftops, such as bus terminals or garages,
building downwash should also be modeled for the relevant sources. The potential for
building downwash should also be addressed for nearby sources whose emissions are on
or near rooftops in the project area. Building downwash occurs when air moving over a
10At present, the area sources in AERMOD do not include AERMOD's "plume meander approach."
Consult the latest version of the AERMOD Implementation Guide for the most current information on
when volume sources or area sources are most appropriate.
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building mixes to the ground on the "downwind" side of the building. AERMOD
includes algorithms to model the effects of building downwash on plumes from nearby or
adjacent point sources. Consult the AERMOD User Guide for additional detail on how
to enter building information.
J. 3.4 Placement and sizing of sources within AERMOD
There are several general considerations with regard to placing and sizing sources within
AERMOD.
First, volume, area, and point sources should be placed in the locations where emissions
are most likely to occur. For example: if buses enter and exit a bus terminal from a single
driveway, the driveway should be modeled using one or more discrete volume or area
sources in the location of that driveway, rather than spreading the emissions from that
driveway across the entire terminal yard.
Second, for emissions from the sides or tops of buildings (as may be found from a bus
garage exhaust fan), it may be necessary to use the BPIPPRIME utility in AERMOD to
appropriately capture the characteristics of these emissions (such as downwash).
Third, the initial dimensions and other parameters of each source should be as realistic as
is feasible. Chapter 3 of the AERMOD User Guide includes recommendations for how
to appropriately characterize the shape of area and volume sources.
Finally, if nearby sources are to be included in air quality modeling (see discussion in
Section 8 of the guidance), a combination of all these source types may be needed to
appropriately represent their emissions within AERMOD. For instance, evenly-
distributed ground-level sources might also be modeled as area sources, while a nearby
power plant stack might be modeled as a point source.
J. 3.5 Timing of emissions in AERMOD
Within AERMOD, emissions that vary across a year should be described with the
EMISFACT keyword (see Section 3.3.5 of the AERMOD User Guide). The number of
quarters that need to be analyzed may vary based on a particular PM hot-spot analysis.
See Section 2.5 of the guidance for more information on when PM emissions need to be
evaluated, and Sections 4 and 5 of the guidance on determining the number of MOVES
and EMFAC runs.
The Qflag parameter under EMISFACT may be used with a secondary keyword to
describe different patterns of emission variations throughout a year. Note that AERMOD
defines seasons in the following manner: winter (December, January, February), spring
(March, April, May), summer (June, July, August), and fall (September, October,
November). Emission data obtained from MOVES or EMFAC should be appropriately
matched with the relevant time periods in AERMOD. For example, if four MOVES or
EMFAC runs are completed (one for each quarter of a year), there are emission estimates
J-8
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corresponding to four months of the year (January, April, July, October) and peak and
average periods within each day. In such a circumstance, January runs should be used to
represent all AERMOD winter months (December, January, February), April runs for all
spring months (March, April, May), July runs for all summer months (June, July,
August), and October for all fall months (September, October, November).
If separate weekend emission rates are available, season-specific weekday runs should be
used for the Monday-Friday entries; weekend runs would be assigned to the Saturday and
Sunday entries. The peak/average runs for each day should be mapped to the AERMOD
entry hours corresponding to the relevant time of day from the traffic analysis. Qflag can
be used to represent emission rates that vary by season, hour of day, and day of the week.
Consult the AERMOD User Guide for details.
J.4 INCORPORATING METEOROLOGICAL DATA
This discussion supplements Section 7.5 of the guidance and describes in more detail
how to handle meteorological data in AERMOD and CAL3QHCR. Section 7.2.3 of
Appendix W to 40 CFR Part 51 provides the basis for determining the urban/rural status
of a source. Consult the AERMOD Implementation Guide for instructions on what type
of population data should be used in making urban/rural determinations.
J. 4.1 Specifying urban or rural sources in AERMOD
As described in Section 7 of the guidance, AERMOD employs nearby population as a
surrogate for the magnitude of differential urban-rural heating (i.e., the urban heat island
effect). When modeling urban sources in AERMOD, users should use the URBANOPT
keyword to enter this data.
When considering urban roughness lengths, users should consult the AERMOD
Implementation Guide. Any application of AERMOD that utilizes a value other than 1
meter for the urban roughness length should be considered a non-regulatory application
and would require appropriate documentation and justification as an alternate model (see
Section 7.3.3 of the guidance).
For urban applications using representative National Weather Service (NWS)
meteorological data, consult the AERMOD Implementation Guide. For urban
applications using NWS data, the URBANOPT keyword should be selected, regardless of
whether the NWS site is located in a nearby rural or urban setting. When using site-
specific meteorological data in urban applications, consult the AERMOD Implementation
Guide.
J-9
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J.4.2 Specifying urban or rural sources in CAL3QHCR
CAL3QHCR requires that users specify the run as being rural or urban using the "RU"
keyword.n Users should make the appropriate entry depending if the source is
considered urban or rural as described in Section 7.5.5 of the guidance.
J.5 MODELING COMPLEX TERRAIN
This discussion supplements Section 7.5 of the guidance and describes in more detail
how to address complex terrain in AERMOD and CAL3QHCR. In most situations, the
project area should be modeled as having flat terrain. Additional detail on how this
should be accomplished in each model is found below. However, in some situations a
project area may include complex terrain, such that sources and receptors included in the
model are found at different heights.
J.5.7 AERMOD
This guidance reflects the AERMOD Implementation Guide as of March 19, 2009.
Analysts should consult the most recent AERMOD Implementation Guide for the latest
guidance on modeling complex terrain.
For most highway and transit projects, the analyst should apply the non-DFAULT option
in AERMOD and assume flat, level terrain. In the AERMOD input file, the FLAT option
should be used in the MODELOPT keyword. This recommendation is made to avoid
underestimating concentrations in two circumstances likely to occur with the low-
elevation, non-buoyant emissions from transportation projects. First, in DFAULT mode,
AERMOD will tend to underestimate concentrations from low-level, non-buoyant
sources where there is up-sloping terrain with downwind receptors uphill since the
DFAULT downwind horizontal plume will pass below the actual receptor elevation.
Second, in DFAULT mode, AERMOD will tend to underestimate concentrations when a
plume is terrain-following. Therefore, the FLAT option should be selected in most cases.
There may be some cases where significant concentrations result from nearby elevated
sources. In these cases, interagency consultation should be used on a case-by-case basis
to determine whether to include terrain effects and use the DFAULT option. In those
cases, AERMAP should be used to prepare input files for AERMOD; consult the
AERMOD and AERMAP user guides and the latest AERMOD Implementation Guide
for information on obtaining and processing relevant terrain data.
11 Specifying urban modeling with the "RU" keyword converts stability classes E and F to D.
J-10
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J.5.2 CAL3QHCR
CAL3QHCR does not handle complex terrain. No action is therefore required.
J.6 RUNNING THE MODEL AND OBTAINING RESULTS
This discussion supplements Section 7.7 of the guidance and describes in more detail
how to handle data outputs in AERMOD and CAL3QHCR. AERMOD and CAL3QHCR
produce different output file formats, which must be post-processed in different ways to
enable calculation of design values as described in Section 9.3 of the guidance. This
guidance is applicable regardless of how many quarters are being modeled.
J. 6.1 AERMOD output
AERMOD requires that users specify the type and format of output files in the main input
file for each run. See Section 3.7 of the AERMOD User Guide for details on the various
output options. Output options should be specified to enable the relevant design value
calculations required in Section 9.3. Note that many users will have multiple years of
meteorological data, so multiple output files may be required (unless the meteorological
files have been joined prior to running AERMOD).
For the annual PM2.5 design value calculations described in Section 9.3.2, averaging
times should be specified that allow calculation of the annual average concentrations at
each receptor. For example, when using five years of meteorological data, the PERIOD
averaging time could be specified using the CO AVERTIME keyword.
For the 24-hour PM2.5 design value calculations described in Section 9.3.3, the
DAYTABLE option provides output files with 24-hour concentrations at each receptor
for each day processed. Users should flag the quarter and year for each day listed in the
DAYTABLE that AERMOD generates. Note users should also specify a 24-hour
averaging time with the CO AVERTIME command as well.
Another option for calculating 24-hour PM2.5 design values is with a POSTFILE, a file of
results at each receptor for each day processed. By specifying a POSTFILE with a 24-
hour averaging time, a user can generate a file of daily concentrations for each day of
meteorological data. When using this option, users should specify a POSTFILE with a
24-hour averaging time to generate the outputs needed to calculate design values and flag
the quarter and year for each day listed in the POSTFILE that AERMOD generates. Note
that POSTFILE output files can be very large.
For the 24-hour PMio calculations described in Section 9.3.4, the RECTABLE keyword
may be used to obtain the six highest 24-hour concentrations over the entire modeling
period. A RECTABLE is a file summarizing the highest concentrations at each receptor
over an averaging period (e.g., 24 hours) across a modeling period (e.g., 5 years).
J-ll
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EPA is actively working towards a post-processing tool for AERMOD that will provide
the appropriate modeling metrics that may then be combined with background
concentrations for comparisons to the PM NAAQS. EPA will announce these new
options as they become available on EPA's SCRAM website at:
www. epa. gov/scramOO 1 /.
J. 6.2 CAL3QHCR output
For each year of meteorological data and quarterly emission inputs, CAL3QHCR reports
the five highest 24-hour concentrations and the quarterly average concentrations in its
output file.
For calculating annual PM2 5 design values using CAL3QHCR output, some post-
processing is required. CALSQHCR's output file refers to certain data under the display:
"THE HIGHEST ANNUAL AVERAGE CONCENTRATIONS." If four quarters of
emission data are separately run in CAL3QHCR, each quarter's outputs listed under
"THE HIGHEST ANNUAL AVERAGE CONCENTRATIONS" are actually quarterly-
average concentrations. As described in Section 7, per year of meteorological data,
CAL3QHCR should be run for as many quarters as analyzed using MOVES and
EMFAC, as CAL3QHCR accepts only a single quarter's emission factors per input file.
Calculating 24-hour PM2 5 design values under a first or second tier analysis is described
in Section 9.3.3. To get annual average modeled concentrations for a first tier analysis
(Step 1), the highest 24-hour concentrations in each quarter and year of meteorological
data should be identified. Within each year of meteorological data, the highest 24-hour
concentration at each receptor should be identified. For a first tier analysis, at each
receptor, the highest concentrations from each year of meteorological data should be
averaged together. Under a second tier analysis, at each receptor, the highest modeled
concentration in each quarter, from each year of meteorological data, should be averaged
together. These average highest 24-hour concentrations in each quarter, across multiple
years of meteorological data, are used in second tier PM2.5 design value calculations.
In calculating 24-hour PMio design values, it is necessary to estimate the sixth-highest
concentration in each year if using five years of meteorological data. For each period of
meteorological data, CAL3QHCR outputs the five highest 24-hour concentrations. To
estimate the sixth-highest concentration at a receptor, the five highest 24-hour
concentrations from each quarter and year of meteorological data should be arrayed
together and ranked. From all quarters and years of meteorological data, the sixth-
highest concentration should be identified. This concentration, at each receptor, is used
in calculations of the PMio design value described in Section 9.3.4.
J-12
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Appendix K:
Examples of Design Value Calculations for PM Hot-spot
Analyses
K.1 INTRODUCTION
This appendix supplements Section 9's discussion of calculating and applying design
values for PM hot-spot analyses. While this guidance can apply to any PM NAAQS, this
appendix provides examples of how to calculate design values for the PM NAAQS in
effect at the time the guidance was issued (the 1997 annual PM2 5 NAAQS, the 2006 and
1997 24-hour PM2.5 NAAQS, and the 1987 24-hour PMi0 NAAQS). The design values
in this appendix are calculated using the steps described in Section 9.3. Readers should
reference the appropriate sections of the guidance as needed for more detail on how to
complete each step of these analyses.
These illustrative example calculations demonstrate the basic procedures described in the
guidance and therefore are simplified in the number of receptors considered and other
details that would occur in an actual PM hot-spot analysis. Where users would have to
repeat steps for additional receptors, it is noted. These examples are organized according
to the build/no-build analysis steps that are described in Sections 2 and 9 of this guidance.
The final part of this appendix provides mathematical formulas that describe the design
value calculations discussed in Section 9 and this appendix.
K.2 PROJECT DESCRIPTION AND CONTEXT FOR ALL EXAMPLES
For the following examples, a PM hot-spot analysis is being done for an expansion of an
existing highway with a significant increase in the number of diesel vehicles (40 CFR
93.123(b)(l)(i)). The highway expansion will serve an expanded freight terminal. The
traffic at the terminal will increase as a result of the expanded highway project's increase
in truck traffic, and therefore the freight terminal is projected to have higher emissions
under the build scenario than under the no-build scenario. The freight terminal is not part
of the project; however, it is a nearby source that will be included in the air quality
modeling, as described further below.
The air quality monitor selected to represent background concentrations from other
sources is a Federal Equivalent Method (FEM) monitor that is 300 meters upwind of the
project. The monitor is on a l-in-3 day sampling schedule. In this example, the three
most recent years of monitoring data are from 2008, 2009, and 2010. Since 2008 is a
leap year (366 days), for this example, there are 122 monitored values in that year and
121 values for both 2009 and 2010 (365 days each).1
1 Note that the number of air quality monitoring measurements may vary by year. For example, with 1 -in-
3 measurements, there could be 122 or 121 measurements in a year with 365 days. Or, there may be fewer
K-l
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However, through interagency consultation, it is determined that the freight terminal's
emissions are not already captured by this air quality monitor. AERMOD has been
selected as the air quality model to estimate PM concentrations produced by the project
(the highway expansion) and the nearby source (the freight terminal).2 There are five
years of representative off-site meteorological data being used in this analysis.
As discussed in Section 2.4, a project sponsor could consider mitigation and control
measures at any point in the process. However, since the purpose of these examples is to
show the design value calculations, in this appendix such measures are not considered
until after the calculations are done.
K.3 EXAMPLE: ANNUAL PM2.5 NAAQS
K.3.1 General
This example illustrates the approach to calculating design values for comparison to the
annual PM2 5 NAAQS, as described in Section 9.3.2. The annual PM2 5 design value is
the average of three consecutive years' annual averages. The design value for
comparison is rounded to the nearest tenth of a ug/m3 (nearest 0. 1 ug/m3). For example,
15. 049 rounds to 15.0, and 15.050 rounds to 15. 1.3
Each year's annual average concentrations include contributions from the project, any
nearby sources modeled, and background concentrations. For air quality monitoring
purposes, the annual PIVb.s NAAQS is met when the three-year average concentration is
less than or equal to the current annual PIVb.s NAAQS (i.e., 15.0 ug/m3):
Annual PIVb.s design value = ([Yl] average + [Y2] average + [Y3] average) + 3
Where:
[Yl] = Average annual PIVb.s concentration for the first year of air quality
monitoring data
[Y2] = Average annual PIVb.s concentration for the second year of air quality
monitoring data
[Y3] = Average annual PIVb.s concentration for the third year of air quality
monitoring data
actual monitored values if sampling was not conducted on some scheduled days or the measured value was
invalidated due to quality assurance concerns. The actual number of samples with valid data should be
used.
EPA notes that CAL3QHCR could not be used in this particular PM hot-spot analysis, since air quality
modeling included the project and a nearby source. See Section 7.3 of the guidance for further information.
3 A sufficient number of decimal places (3-4) should be retained during intermediate calculations for design
values, so that there is no possibility of intermediate rounding or truncation affecting the final result.
Rounding to the tenths place should only occur during final design value calculations, pursuant to
Appendix N to 40 CFR Part 50.
K-2
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For this example, the project described in Appendix K.2 is located in an annual
NAAQS nonattainment area. This example illustrates how an annual PM2.5 design value
could be calculated at the same receptor in the build and no-build scenarios, based on air
quality modeling results and air quality monitoring data. In an actual PM hot-spot
analysis, design values would be calculated at additional receptors, as described further in
Section 9.3.2.
K. 3.2 Build scenario
For the build scenario, the PIVb.s impacts from the project and from the nearby source are
estimated with AERMOD at all receptors.4
Steps 1-2. Because AERMOD is used for this project, Step 1 is skipped. The receptor
with the highest average annual concentration, using five years of meteorological data, is
identified directly from the AERMOD output. This receptor's average annual
concentration is 3.603 ug/m3.
Step 3. Based on the three years of measurements at the background air quality monitor,
the average monitored background concentrations in each quarter is determined. Then,
for each year of background data, the four quarters are averaged to get an average annual
background concentration (last column of Exhibit K-l). These three average annual
background concentrations are averaged, and the resulting value is 11.582 ug/m3, as
shown in Exhibit K-l:
Exhibit K-l. Background Concentrations
Background
Concentrations
2008
2009
2010
Qi
13.013
14.214
11.890
Q2
17.037
14.872
16.752
Q3
8.795
7.912
9.421
Q4
8.145
7.639
9.287
3 -year average:
Average
Annual
11.748
11.159
11.838
11.582
Step 4. The 3-year average annual background concentration (from Step 3) is added to
the average annual modeled concentration from the project and nearby source (from Step
2):
11.582 + 3.603 = 15.185
Step 5. Rounding to the nearest 0.1 ug/m3 produces a design value of 15.2 ug/m3.
4 As noted above, there is a single nearby source that is projected to have higher emissions under the build
scenario than the no-build scenario as a result of the project and its impacts are not expected to be captured
by the monitor chosen to provide background concentrations. Therefore, emissions from the project and
this nearby source are both included in the AERMOD output.
K-3
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In this example, the concentration at the highest receptor is estimated to exceed the
current annual PM2.5 NAAQS of 15.0 |J,g/m3.
Steps 6-8: Since the design value in Step 5 is greater than the NAAQS, design value
calculations are then completed for all receptors in the build scenario, and receptors with
design values above the NAAQS are identified. After this is done, the no-build scenario
is modeled for comparison.
K. 3.3 No-b uild scenario
The no-build scenario (i.e., the existing highway and freight terminal without the
proposed highway and freight terminal expansion), is modeled at all of the receptors in
the build scenario, but design values are only calculated in the no-build scenario at
receptors where the design value for the build scenario is above the annual PM2.5 NAAQS
(from Steps 6-8 above).
Step 9. For this example, the receptor with the highest average annual concentration in
the build scenario is used to illustrate the no-build scenario design value calculation. The
average annual concentration modeled at this receptor in the no-build scenario is 3.521
|ag/m3.
Step 10. The background concentrations from the representative monitor are unchanged
from the build scenario, so the average annual modeled concentration of 3.521 is added to
the 3-year average annual background concentrations of 11.528 |J,g/m3 from Step 3:
11.582 + 3.521 = 15.103
Step 11. Rounding to the nearest 0.1 |J,g/m3 produces a design value of 15.1 |J,g/m3.
In this example, the design value at the receptor in the build scenario (15.2 ug/m ) is
greater than the design value at the same receptor in the no-build scenario (15.1 ug/m ).
In an actual PM hot-spot analysis, design values would also be compared between build
and no-build scenarios at all receptors in the build scenario that exceeded the annual
PM2.5 NAAQS. The interagency consultation process would then be used to discuss next
steps, e.g., appropriateness of receptors. Refer to Sections 9.2 and 9.4 for additional
details.
If it is determined that conformity requirements are not met at all appropriate receptors,
the project sponsor should then consider additional mitigation or control measures, as
discussed in Section 10. After measures are selected, a new build scenario that includes
the controls should be modeled and new design values calculated. Design values for the
no-build scenario shown above would not need to be recalculated since the no-build
scenario would not change.
Values are compared after rounding. As long as the build design value is no greater than the no-build
design value after rounding, the project would meet conformity requirements at a given receptor, even if
the pre-rounding build design value is greater than the pre-rounding no-build design value.
K-4
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K.4 EXAMPLE: 24-HOURPM2.5NAAQS
K.4.1 General
This example illustrates the two-tiered approach to calculating design values for
comparison with the 24-hour PIVb.s NAAQS, as described in Section 9.3.3. The 24-hour
design value is the average of three consecutive years' 98th percentile PM2.5 concentration
of 24-hour values for each of those years. For air quality monitoring purposes, the
NAAQS is met when that three-year average concentration is less than or equal to the
currently applicable 24-hour PIVb.s NAAQS for a given area's nonattainment designation
(35 |J,g/m3 for nonattainment areas for the 2006 PIVb.s NAAQS and 65 |J,g/m3 for
nonattainment areas for the 1997 PIVb.s NAAQS).6 The design value for comparison to
any 24-hour PIVb.s NAAQS is rounded to the nearest 1 |J,g/m3 (i.e., decimals 0.5 and
greater are rounded up to the nearest whole number, and any decimal lower than 0.5 is
rounded down to the nearest
while 35.500 rounds to 36.7
rounded down to the nearest whole number). For example, 35.499 rounds to 35 |J,g/m ,
For this example, the project described in Appendix K.2 is located in a nonattainment
area for the 2006 24-hour PIVb.s NAAQS. This example presents first tier and second tier
build scenario results for a single receptor to illustrate how the calculations should be
made based on air quality modeling results and air quality monitoring data. It also shows
second tier no-build scenario results for this same receptor. In an actual PM hot-spot
analysis, design values would be calculated at additional receptors, as described further in
Section 9.3.3.
As explained in Section 9.3.3, project sponsors can start with either a first or second tier
analysis. This example begins with a first tier analysis. However, it would also be
acceptable to begin with the second tier analysis and skip the first tier altogether.
K. 4.2 Build scenario
PM2.5 contributions from the project and the nearby source are estimated together with
AERMOD in each of four quarters using meteorological data from five consecutive
years, using a 24-hour averaging time. As discussed in Appendix K.2 above, the one
nearby source (the freight terminal) was included in air quality modeling.
6 There are only two PM2 5 areas where conformity currently applies for both the 1997 and 2006 24-hour
NAAQS. While both 24-hour NAAQS must be considered in these areas, in practice if the more stringent
2006 24-hour PM2.5 NAAQS is met, then the 1997 24-hour PM2.5 NAAQS is met as well.
7 A sufficient number of decimal places (3-4) should be retained during intermediate calculations for design
values, so that there is no possibility of intermediate rounding or truncation affecting the final result.
Rounding should only occur during final design value calculations, pursuant to Appendix N to 40 CFR Part
50.
K-5
-------
First Tier Analysis
Under a first tier analysis, the average highest modeled 24-hour concentrations at a given
receptor are added to the average 98l percentile 24-hour background concentrations,
regardless of the quarter in which they occur. The average highest modeled 24-hour
concentrations are produced by AERMOD, using five years of meteorological data in one
run.
Step 1. The receptor with the highest average modeled 24-hour concentration is
r-r-, 8
identified. This was obtained directly from the AERMOD output. For this example, the
data from this receptor is shown in Exhibit K-2. Exhibit K-2 shows the highest 24-hour
concentration for each year of meteorological data used, regardless of the quarter in
which they were modeled. The average concentration of these outcomes, 6.710 |J,g/m3
(highlighted in Exhibit K-2), is the highest, compared to the averages at all of the other
receptors.
Exhibit K-2. Modeled PMi.5 Concentrations from Project and Nearby Source
Year
Met Year 1
Met Year 2
Met Year 3
Met Year 4
Met Year 5
Average
Highest PM2.5
Concentration
6.413
5.846
6.671
7.951
6.667
6.710
Step 2. The average 98th percentile 24-hour background concentration for a first tier
analysis is calculated using the 98th percentile 24-hour concentrations of the three most
recent years of monitoring data from the representative air quality monitor selected (see
Appendix K.2). Since the background monitor is on a l-in-3 day sampling schedule, it
made either 122 or 121 measurements per year during 2008 - 2010. According to Exhibit
9-5, with this number of monitored values per year, the 98th percentile is the third highest
concentration. Exhibit K-3 depicts the top eight monitored concentrations (in |J,g/m3) of
the monitor throughout the years employed for estimating background concentrations.
8 If CAL3QHCR were being used, some additional processing of model output would be needed. Refer to
Section 9.3.3.
K-6
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Exhibit K-3. Top Eight Monitored Concentrations in Years 2008 - 2010
Rank
1
2
3
4
5
6
7
8
2008
34.123
31.749
31.443
30.809
30.219
30.134
30.099
28.481
2009
33.537
32.405
31.126
30.819
30.487
29.998
29.872
28.937
2010
35.417
31.579
31.173
31.095
30.425
30.329
30.193
28.751
The third-ranked concentration of each year (highlighted in Exhibit K-3) is the 98th
percentile value. These are averaged:
(31.443 + 31.126 + 31.173) - 3 = 31.247 |ag/m3.
Step 3. Then, the highest average 24-hour modeled concentration for this receptor (from
Step 1) is added to the average 98th percentile 24-hour background concentration (from
Step 2):
6.710 + 31.247 = 37.957 |ag/m3.
Rounding to the nearest whole number results in a 24-hour PIVb.s design value of 3 8
|j,g/m3.
Because this concentration is greater than the 2006 24-hour PM2 5 NAAQS (35 |j,g/m3),
this first tier analysis does not demonstrate that conformity is met. As described in
Section 9.3.3, the project sponsor has two options:
• Repeat the first tier analysis for the no-build scenario at all receptors that
exceeded the NAAQS in the build scenario. If the calculated design value for the
build scenario is less than or equal to the design value for the no-build scenario at
all of these receptors, then the project conforms;9 or
• Conduct a second tier analysis.
In this example, the next step chosen is to conduct a second tier analysis.
Second Tier Analysis
In a second tier analysis, the highest modeled concentrations are not added to the 98l
percentile background concentrations on a yearly basis. Instead, a second tier analysis
uses the average of the highest modeled 24-hour concentration within each quarter of
each year of meteorological data. Impacts from the project, nearby sources, and other
background concentrations are calculated on a quarterly basis before determining the 98th
9 In certain cases, project sponsors can also decide to calculate the design values for all receptors in the
build and no-build scenarios and use the interagency consultation process to determine whether a "new"
violation has been relocated (see Section 9.2).
K-7
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percentile concentration resulting from these inputs. The steps presented below follow
the steps described in Section 9.3.3.
Step 1. The first step is to count the number of measurements for each year of
monitoring data used for background concentrations. As described in Appendix K.2 and
in Step 2 of the first tier analysis above, there are 122 monitored values during 2008, 121
values during 2009, and 121 values during 2010.
Step 2. For each year of monitoring data, the eight highest 24-hour background
concentrations in each quarter are determined. The eight highest concentrations in each
quarter of 2008, 2009, and 2010 are shown in Exhibit K-4.
Exhibit K-4. Eight Highest 24-hour Background Concentrations By Quarter for
Each Year
Year
2008
2009
2010
Rank of
Background
Concentration
1
2
3
4
5
6
7
8
1
2
3
4
5
6
7
8
1
2
3
4
5
6
7
8
Qi
27.611
25.974
25.760
25.493
25.099
24.902
24.780
23.287
26.962
24.820
24.330
23.768
23.685
23.287
23.226
22.698
27.493
24.637
24.637
24.392
24.050
23.413
22.453
22.061
Q2
31.749
30.219
30.134
28.368
27.319
25.788
25.564
24.794
32.405
30.487
28.937
27.035
25.880
25.867
25.254
24.268
31.579
31.173
30.193
27.994
25.439
24.253
23.006
21.790
Q3
34.123
31.443
30.809
28.481
27.372
25.748
25.288
24.631
33.537
30.819
29.998
29.872
25.596
25.148
24.744
24.267
35.417
31.095
30.329
28.751
26.084
24.890
24.749
22.538
Q4
30.099
28.096
26.990
25.649
25.526
25.509
25.207
24.525
31.126
28.553
25.920
25.856
25.565
24.746
24.147
23.142
30.425
26.927
26.263
25.684
25.170
24.254
23.425
22.891
K-8
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Step 3. The highest modeled 24-hour concentrations in each quarter are identified at each
receptor. Exhibit K-5 presents the highest 24-hour concentrations within each quarter at
one receptor (for each of the five years of meteorological data used in air quality
modeling) as well as the average of these quarterly concentrations. This step would be
repeated for each receptor in an actual PM hot-spot analysis.
Exhibit K-5. Highest Modeled 24-hour Concentrations Within Each Quarter (Build
Scenario)
Met Year 1
Met Year 2
Met Year 3
Met Year 4
Met Year 5
Average
Qi
6.413
3.229
6.671
7.095
6.664
6.014
Q2
3.332
3.481
3.330
3.584
4.193
3.584
Q3
6.201
5.846
5.696
7.722
4.916
6.076
Q4
6.193
4.521
6.554
7.951
6.667
6.377
The average highest concentrations on a quarterly basis (i.e., the values highlighted in
Exhibit K-5) constitute the contributions of the project and nearby source to the projected
24-hour PM2.5 design value, and are used in subsequent calculations.
Step 4. For each receptor, the highest modeled 24-hour concentration in each quarter
(from Step 3) is added to each of the eight highest monitored concentrations for the same
quarter for each year of monitoring data (from Step 2). To obtain this result, the average
highest modeled concentration for each quarter, found in the last row of Exhibit K-5, is
added to each of the eight highest background concentrations in each quarter in Exhibit
K-4. The results are shown in Exhibit K-6.
K-9
-------
Exhibit K-6. Sum of Modeled and Monitored Concentrations (Build Scenario)
Year
2008
2009
2010
Rank of
Background
Concentration
1
2
3
4
5
6
7
8
1
2
3
4
5
6
7
8
1
2
3
4
5
6
7
8
Qi
33.625
31.989
31.774
31.507
31.113
30.916
30.794
29.301
32.976
30.835
30.344
29.782
29.700
29.301
29.240
28.712
33.507
30.651
30.651
30.406
30.064
29.428
28.468
28.075
Q2
35.333
33.803
33.718
31.952
30.903
29.372
29.148
28.378
35.989
34.071
32.521
30.619
29.464
29.451
28.838
27.852
35.163
34.757
33.777
31.578
29.022
27.837
26.590
25.374
Q3
40.200
37.520
36.886
34.557
33.448
31.824
31.365
30.707
39.613
36.895
36.074
35.948
31.672
31.225
30.820
30.343
41.493
37.172
36.405
34.827
32.160
30.966
30.825
28.614
Q4
36.476
34.474
33.368
32.026
31.903
31.886
31.584
30.902
37.503
34.931
32.297
32.233
31.942
31.124
30.524
29.520
36.802
33.304
32.640
32.062
31.547
30.631
29.803
29.269
Step 5. The 32 values from each year in Exhibit K-6 are then ranked from highest to
lowest, regardless of the quarter from which each value comes. This step is shown in
Exhibit K-7. Note that only the top eight values are shown for each year instead of the
entire set of 32. Exhibit K-7 also displays the quarter from which each concentration
comes and the value's rank within its quarter.
K-10
-------
Exhibit K-7. Eight Highest Concentrations in Each Year, Ranked from Highest to
Lowest (Build Scenario)
Year
2008
2009
2010
Hg/m3
40.200
37.520
36.886
36.476
35.333
34.557
34.474
33.803
39.613
37.503
36.895
36.074
35.989
35.948
34.931
34.071
41.493
37.172
36.802
36.405
35.163
34.827
34.757
33.777
Yearly
Rank
1
2
3
4
5
6
7
8
1
2
3
4
5
6
7
8
1
2
3
4
5
6
7
8
Quarter
Q3
Q3
Q3
Q4
Q2
Q3
Q4
Q2
Q3
Q4
Q3
Q3
Q2
Q3
Q4
Q2
Q3
Q3
Q4
Q3
Q2
Q3
Q2
Q2
Quarterly
Rank
1
2
3
1
1
4
2
2
1
1
2
3
1
4
2
2
1
2
1
3
1
4
2
3
Steps 6-7. The value that represents the 98th percentile 24-hour concentration is
determined, based on the number of background concentration values there are. As
described in Step 1, there are 122 monitored values for the year 2008 and 121 values for
both 2009 and 2010. According to Exhibit 9-7 in Section 9.3.3, for a year with 101-150
samples per year, the 98l percentile is the 3r highest concentration for that year.
Therefore, for this example, the 3r highest 24-hour concentration of each year,
highlighted in Exhibit K-7, represents the 98l percentile value for that year.
Step 8. At each receptor, the average of the three 24-hour 98th percentile concentrations
is calculated. For the receptor in this example, the average is:
(36.886 + 36.895 + 36.802) - 3 = 36.861
K-ll
-------
Step 9. The average for the receptor in this example from Step 8 (36.861 |J,g/m3) is then
rounded to the nearest whole number (37 |J,g/m3) and compared to the 2006 24-hour
PM2.5NAAQS (35 jag/m3).
The design value at the receptor in this example is higher than the relevant 24-hour PM2.5
NAAQS. In an actual PM2.5 hot-spot analysis, the design value calculations need to be
repeated for all receptors, and compared to the NAAQS. Since one (and possibly more)
receptors have design values greater than the 24-hour PIVb.s NAAQS, the project will
only conform if the design value in the build scenario is less than or equal to the design
value in the no-build scenario for all receptors that exceeded the NAAQS in the build
scenario. Therefore, the no-build scenario needs to be modeled for comparison, as
described further below. Because the build scenario was modeled with a second tier
analysis, the no-build scenario must also be modeled with a second tier analysis.
K. 4.3 No-b uild scenario
The no-build scenario is described in Section 9.3.3 as Step 10:
• Step 10. Using modeling results for the no-build scenario, repeat Steps 3 through
9 for all receptors with a design value that exceeded the PIVb.s NAAQS in the
build scenario. The result will be a 24-hour PIVb.s design value at such receptors
for the no-build scenario.
For this part of the example, air quality modeling is completed for the no-build scenario
for the same receptor as the build scenario. Steps 1 and 2 for the build scenario do not
need to be repeated, since the background concentrations in the no-build scenario are
identical to those in the build scenario. Exhibit K-4, which shows the eight highest
monitored concentrations in each quarter over three years, therefore can also be used for
the no-build scenario.
Step 3. For the same receptor examined above in the build scenario, the highest modeled
24-hour concentrations for the no-build scenario are calculated for each quarter, using
each year of meteorological data used for air quality modeling. Exhibit K-8 provides
these concentrations, as well as the quarterly averages (highlighted).
Exhibit K-8. Highest Modeled 24-hour Concentrations Within Each Quarter (No-
Build Scenario)
Met Year 1
Met Year 2
Met Year 3
Met Year 4
Met Year 5
Average
Qi
6.757
3.402
7.029
7.476
7.022
6.337
Q2
3.383
3.535
3.381
3.639
4.258
3.639
Q3
6.725
6.340
6.177
8.374
5.331
6.589
Q4
6.269
4.577
6.635
8.048
6.748
6.455
K-12
-------
Step 4. The highest modeled 24-hour concentration in each quarter (i.e., the values in the
last row of Exhibit K-8) are added to each of the eight highest concentrations for the
same quarter for each year of monitoring data (found in Exhibit K-4), and the resulting
values are shown in Exhibit K-9.
Exhibit K-9. Sum of Modeled and Monitored Concentrations (No-Build Scenario)
Year
2008
2009
2010
Rank of
Background
Concentration
1
2
3
4
5
6
7
8
1
2
3
4
5
6
7
8
1
2
3
4
5
6
7
8
Qi
33.948
32.312
32.097
31.830
31.436
31.239
31.117
29.624
33.299
31.158
30.667
30.105
30.023
29.624
29.563
29.035
33.830
30.974
30.974
30.729
30.387
29.751
28.791
28.398
Q2
35.389
33.858
33.774
32.007
30.959
29.428
29.204
28.433
36.044
34.126
32.576
30.674
29.520
29.506
28.894
27.907
35.218
34.812
33.832
31.633
29.078
27.893
26.645
25.429
Q3
40.713
38.033
37.399
35.070
33.961
32.337
31.878
31.220
40.127
37.408
36.587
36.461
32.185
31.738
31.333
30.856
42.007
37.685
36.918
35.340
32.674
31.479
31.338
29.127
Q4
36.555
34.552
33.446
32.104
31.981
31.964
31.662
30.980
37.581
35.009
32.375
32.311
32.020
31.202
30.602
29.598
36.880
33.382
32.719
32.140
31.625
30.709
29.881
29.347
Step 5. The 32 values from each year in Exhibit K-9 are ranked from highest to lowest,
regardless of the quarter from which each value comes. This step is shown in Exhibit K-
10. Note that only the top eight values are shown for each year instead of the entire set of
32.
K-13
-------
Exhibit K-10. Eight Highest Concentrations in Each Year, Ranked from Highest to
Lowest (No-Build Scenario)
Year
2008
2009
2010
Hg/m3
40.713
38.033
37.399
36.555
35.389
35.070
34.552
33.961
40.127
37.581
37.408
36.587
36.461
36.044
35.009
34.126
42.007
37.685
36.918
36.880
35.340
35.218
34.812
33.832
Yearly
Rank
1
2
3
4
5
6
7
8
1
2
3
4
5
6
7
8
1
2
3
4
5
6
7
8
Quarter
Q3
Q3
Q3
Q4
Q2
Q3
Q4
Q3
Q3
Q4
Q3
Q3
Q3
Q2
Q4
Q2
Q3
Ql
Ql
Q4
Q4
Ql
Q4
Q4
Quarterly
Rank
1
2
3
1
1
4
2
5
1
1
2
3
4
1
2
2
7
3
2
8
6
1
2
3
Steps 6-7. Based on the number of background measurements available per year in this
example (122 for 2008 and 121 for both 2009 and 2010, as discussed in the analysis of
the build scenario), Exhibit 9-7 in Section 9.3.3 indicates that the 3r highest 24-hour
concentration in each year represents the 98l percentile concentration for that year. The
third highest concentrations are highlighted in Exhibit K-10.
Step 8. For this receptor, the average of the Rank 3 concentrations in 2008, 2009, and
2010 is calculated:
(37.399 + 37.408 + 36.918) - 3 = 37.242
Step 9. The average for the receptor in this example from Step 8 (37.242 |J,g/m3) is
rounded to the nearest whole |J,g/m3 (37 |j,g/m3).
K-14
-------
In this example, the design value at this receptor for both the build and no-build scenarios
is 37 |J,g/m3, which is greater than the 2006 24-hour NAAQS (35 mg/m3). However, the
build scenario's design value is equal to the design value in the no-build scenario.10 For
the project to conform, the build design values must be less than or equal to the no-build
value for all the receptors that exceeded the NAAQS in the build scenario. Assuming
that this is the case at all other receptors, the proposed project in this example would
therefore demonstrate conformity.
K.5 EXAMPLE: 24-HOUR PMIO NAAQS
K.5.1 General
This example illustrates calculating design values for comparison with the 24-hour
NAAQS, as described in Section 9.3.4. The 24-hour PMio design value is based on the
expected number of 24-hour exceedances of 150 |J,g/m3, averaged over three consecutive
years. For air quality monitoring purposes, the NAAQS is met when the number of
exceedances is less than or equal to 1.0. The 24-hour PMio design value is rounded to the
nearest 10 |J,g/m3. For example, 155.511 rounds to 160, and 154.999 rounds to 150.11
The 24-hour PMio design value is calculated at each air quality modeling receptor by
directly adding the sixth-highest modeled 24-hour concentration (if using five years of
meteorological data) to the highest 24-hour background concentration (from three years
of monitored data).
For this example, the project described in Appendix K.2 is located in a nonattainment
area for the 24-hour PMio NAAQS. This example presents build scenario results for a
single receptor to illustrate how the calculations should be made based on air quality
modeling results and air quality monitoring data.
10 Values are compared after rounding. As long as the build design value is no greater than the no-build
design value after rounding, the project would meet conformity requirements at a given receptor, even if
the pre-rounding build design value is greater than the pre-rounding no-build design value.
11 A sufficient number of decimal places (3-4) in modeling results should be retained during intermediate
calculations for design values, so that there is no possibility of intermediate rounding or truncation
affecting the final result. Rounding to the nearest 10 ug/m3 should only occur during final design value
calculations, pursuant to Appendix K to 40 CFR Part 50. Monitoring values typically are reported with
only one decimal place.
K-15
-------
K.5.2 Build Scenario
Step 1. From the air quality modeling results from the build scenario, the sixth-highest
24-hour concentration is identified at each receptor. These sixth-highest concentrations
are the sixth highest that are modeled at each receptor, regardless of year of
meteorological data used.12 AERMOD was configured to produce these values.
Step 2. The sixth-highest modeled concentrations (i.e., the concentrations at Rank 6) are
compared across receptors, and the receptor with the highest value at Rank 6 is identified.
For this example, the highest sixth-highest 24-hour concentration at any receptor is
15.218 |J,g/m3. (That is, at all other receptors, the sixth-highest concentration is less than
15.218 |j,g/m3.) Exhibit K-l 1 shows the six highest 24-hour concentrations at this
receptor.
Exhibit K-ll. Receptor with the Highest Sixth-Highest 24-Hour Concentration
(Build Scenario)
Rank
1
2
3
4
5
6
Highest 24-Hour
Concentrations
17.012
16.709
15.880
15.491
15.400
15.218
Step 3. The highest 24-hour background concentration from the three most recent years
of monitoring data (2008, 2009, and 2010) is identified. In this example, the highest 24-
hour background concentration from these three years is 86.251 |J,g/m3.
Step 4. The sixth-highest 24-hour modeled concentration of 15.218 |J,g/m from the
highest receptor (from Step 2) is added to the highest 24-hour background concentration
of 86.251 |ag/m3 (from Step 3):
15.218 + 86.251 = 101.469
Step 5. This sum is rounded to the nearest 10 |J,g/m , which results in a design value of
100|ag/m3.
This result is then compared to the 24-hour PMio NAAQS. In this case, the concentration
calculated at all receptors is less than the 24-hour PMio NAAQS of 150 |J,g/m3, therefore
12 The six highest concentrations could occur anytime during the five years of meteorological data. They
'ears, or thev mav he snread out over several, or even all five, years of the
may be clustered in one or two years, or they may be spread out over :
meteorological data.
K-16
-------
the analysis shows that the project conforms. However, if the design value for this
receptor had been greater than 150 |J,g/m3, the remainder of the steps in Section 9.3.4
would be completed. That is, build scenario design values for each receptor would be
calculated (Steps 6-7 in Section 9.3.4) and, for all those that exceed the NAAQS, the no-
build design values would also be calculated (Steps 8-10 in Section 9.3.4). The build and
no-build design values would then be compared.13
K.6 MATHEMATICAL FORMULAS FOR DESIGN VALUE CALCULATIONS
K. 6.1 In troduction
This part of the appendix includes mathematical formulas to represent the calculations
described narratively in Section 9.3. This information is intended to supplement Section
9, which may be helpful for certain users.
Appendix K.6 relies on conventions of mathematical and logical notation that are
described after the formulas are presented. Several symbols are used that may be useful
to review prior to reading the individual formulas.
Notation symbols
• x - a single bar over variable x represents a single arithmetic mean of that
variable
• x - double bars over variable x represents an "average of averages"
• x - a "hat" over variable x represents the arithmetic of multiple high
concentration values from different years, either from monitoring data or from
modeling results
Logical symbols
• Vx - an upside down A before variable x means "for all" values of x
• e x - an " e " before variable x means "in x"
• Vx e y - means "for all x in y"
The following information present equations for calculating design values for the PM2.5
annual NAAQS, 24-hour PM2.5 NAAQS, and 24-hour PMio NAAQS. The equations are
organized into the sets that are referenced in Section 9.3.
13 Values are compared after rounding. As long as the build design value is no greater than the no-build
design value after rounding, the project would meet conformity requirements at a given receptor, even if
the pre-rounding build design value is greater than the pre-rounding no-build design value.
K-17
-------
K. 6. 2 Equation Set 1: Annual PM2.s design value
Formulas
c,=b,+
When using CAL3QHCR, plk = —
Definitions
bi = average of three consecutive years' average annual background concentrations at
receptor /
bim = quarterly-weighted average annual background concentrations at receptor / during
monitoring year m
bijm = quarterly average background concentration at receptor /', during quarter 7 in
monitoring year m
ct = annual PM2 5 design value at receptor /
/ = receptor
j = quarter
k = year of meteorological data
/ = length in years of meteorological data record
m = year of background monitoring data
pik = average modeled quarterly average concentrations at receptor / for meteorological
year k. When using AERMOD, it is presumed that AERMOD's input file is used
to specify this averaging time. When using CAL3QHCR with a single quarter of
meteorological data, pik must be calculated using each ~pijk for each quarter of
meteorological year k.
pijk = quarterly average concentration at receptor / for quarter 7, in meteorological data
year k. This variable is the product of CAL3QHCR when run with a single
quarter of meteorological data. pik can be calculated directly using AERMOD
without explicitly calculating pijk .
K-18
-------
K. 6. 3 Equation Set 2: 24-Hour PM2.5 design value (First Tier Analysis)
Formulas
A = b, + p,
bm=Vbymem
3 /,
""1
CAL3QHCR), which compresses to:
k=\
pi = y"' - k lk (when using AERMOD with maximum concentration by year)
k=\ '
Definitions
bt = the average of 98th percentile 24-hour concentrations from three consecutive years of
monitoring data
bijm = daily 24-hour background concentration at receptor /', during quarter y in monitoring
year m
bim = ~^bijm G m = All 24-hour background concentration measurements in year m
bim.r = The 24-hour period within year m whose concentration rank among all 24-hour
measurements in year m is rm (this represents the 98th percentile of 24-hour
background concentrations within one year.)
ci = 24-hour PIVb.s design value at receptor /
/ = receptor
j = quarter
k = year of meteorological data
/ = length in years of meteorological data record
m = year of background monitoring data
maxt = maximum predicted 24-hour concentration within meteorological year k
maxjyt = maximum predicted 24-hour concentration within quarter y' within
meteorological year k
pi = average of highest predicted concentrations from each year modeled with the / years
from which meteorological data are used (>5 years for off-site data, >1 year for
on-site data)
pijk = modeled daily 24-hour concentration at receptor /', in quarter y' and meteorological
year A:
pik = modeled daily 24-hour concentration at receptor /', in meteorological year k
rm = concentration rank of bim corresponding to 98th percentile of all bim in year m, based
on number of background concentration measurements per year (nm). rm is given
by the following table:
K-19
-------
nm
1-50
51-100
101-150
151-200
201-250
251-300
301-350
351-366
rm
I
2
3
4
5
6
7
8
K-20
-------
K.6.4 Equation Set 3: 24-Hour PM2.s design value (Second Tier Analysis)
Formulas
^c,._
c,
m=l
~ X^ Cim.r
"i=L—r
cijm = bym + Ay' f°r the eight (8) highest bijm in quarter^ in monitoring year m
i
Definitions
bijm = daily 24-hour background concentration at receptor /', during quarter 7 in monitoring
year m
ci = 24-hour PM2.5 design value at receptor /
ctjm = The set of all sums of modeled concentrations (ptj) with background
concentrations from quarter 7 and monitoring year m, using the eight highest
background concentrations (bijm) for the corresponding receptor, quarter, and
monitoring year.
cim = ^Cijm ^m = the set of all cimi corresponding to monitoring year m
cim.r = predicted 98th percentile total concentration from the project, nearby sources, and
background measurements from year m. Given by the value of cim whose
concentration rank in year m is rm, using background measurements from year m.
i = receptor
7 = quarter
k = year of meteorological data
/ = length in years of meteorological data record
m = year of background monitoring data
maxjyt = maximum predicted 24-hour concentration within quarter7' within
meteorological year k
pijk = Predicted daily 24-hour concentration at receptor /', during quarter7, based on data
from meteorological year k
ptj = Average highest 24-hour modeled concentration (pijk) using / years of
meteorological data
rm = concentration rank of cim corresponding to 98l percentile of all cim in year m, based
on number of background concentration measurements per year (nm). rm is given
by the following table:
K-21
-------
nm
1-50
51-100
101-150
151-200
201-250
251-300
301-350
351-366
rm
I
2
3
4
5
6
7
8
K-22
-------
K. 6. 5 Equation Set 5: 24-Hour PMj o design value
Formulas
ct = b,+ Pi
bm=\Jbi
m=\
Pi = P,l.r,
1
\n
ik
Pa=\Jp.
k=l
Definitions
ct = 24-hour PMio design value
bt = maximum monitored 24-hour PMio background concentration at within bin
bim = the set of all monitored 24-hour PMio background concentrations at receptor /'
within monitoring year m
bin = the set of all bim within monitoring years n
i = receptor
k = year of meteorological data
/ = length in years of meteorological data record.
maxin = the maximum monitored 24-hour background concentration at receptor /' within
monitoring years n
n = the set of all years of monitoring data, m = {1,2,3}
Pi = PUT, = modeled 24-hour PMio concentration with concentration rank of n among all
concentrations modeled using / years of meteorological data
pa = set of all modeled 24-hour concentrations at receptor / across / years of
meteorological data
n = l + 1 (for example, n = 6 when using 5 years of meteorological data)
\\ca = the set (finite union) of all ca with integer values of a = {1,... ,z}
a=l
K-23
------- |