PM Hot-spot Guidance
Transportation Conformity Guidance
for Quantitative Hot-spot Analyses
in PM2 5 and PM10 Nonattainment
and Maintenance Areas
SEPA
United States
Environmental Protection
Agency
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PM Hot-spot Guidance
Transportation Conformity Guidance
for Quantitative Hot-spot Analyses
in PM2 5 and PM10 Nonattainment
and Maintenance Areas
Transportation and Climate Division
Office of Transportation and Air Quality
U.S. Environmental Protection Agency
United States
Environmental Protection
^1 Agency
EPA-420-B-21-037
October 2021
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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 Requirement for 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 10
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 14
2.5.5 PM Emissions from Construction-Related Activities 14
2.6 NAAQS Considered in PM Hot-Spot Analyses 14
2.7 Background Concentrations 15
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 17
2.9.3 EPA 17
2.9.4 State and Local Transportation and Air Agencies 17
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) 21
3.3.4 Determining the PM NAAQS to Be Evaluated 21
3.3.5 Deciding on the Type of PM Emissions to Be Modeled 21
3.3.6 Determining the Models and Methods to Be Used 21
3.3.7 Obtaining Project-Specific Data 22
3.4 Estimate On-Road Motor Vehicle Emissions (Step 3) 22
3.5 Estimate Emissions from Road Dust, Construction, and Additional Sources (Step 4) 23
3.6 Select Source Types, Data Inputs, and Receptors for AERMOD (Step 5) 23
3.7 Determine Background Concentrations from Nearby and Other Sources (Step 6) 23
3.8 Calculate Design Concentrations and Determine Conformity (Step 7) 24
3.9 Consider Mitigation or Control Measures (Step 8) 24
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3.10 Document the PM Hot-Spot Analysis (Step 9) 24
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 32
4.3.1 General 32
4.3.2 Projects with Typical Travel Activity Data 34
4.3.3 Proj ects with Additional Travel Activity Data 35
4.4 Developing Run Specification Inputs 36
4.4.1 Description 36
4.4.2 Scale 36
4.4.3 Time Spans 37
4.4.4 Geographic Bounds 38
4.4.5 Onroad Vehicles 38
4.4.6 Road Type 38
4.4.7 Pollutants and Processes 39
4.4.8 General Output 41
4.4.9 Output Emissions Detail 41
4.4.10 Create Input Database 42
4.4.11 Advanced Features 42
4.5 Entering Project Details Using the Project Data Manager 43
4.5.1 Meteorology Data 45
4.5.2 Age Distribution 45
4.5.3 Fuel 46
4.5.4 I/M Programs 47
4.5.5 Retrofit Data 47
4.5.6 Links 47
4.5.7 Link Source Types 48
4.5.8 Options for Describing Running Activity (Running and Idling) 49
4.5.9 Describing Off-Network Activity (Starting and Hotelling) 51
4.6 Generating Emission Factors for Use in Air Quality Modeling 54
Section 5: Estimating Project-Level PM Emissions Using the EMFAC Model in California 57
5.1 Introduction 57
5.2 Characterizing a Project in Terms of Links 58
5.2.1 Highway and Intersection Projects 58
5.2.2 Transit and Other Terminal Projects 59
5.3 Determining the Number of EMFAC Runs 60
5.3.1 General 60
5.3.2 Projects with Typical Travel Activity Data 60
5.3.3 Proj ects with Additional Travel Activity Data 61
Section 6: Estimating Emissions from Road Dust, Construction, and Additional Sources 62
6.1 Introduction 62
6.2 Overview of Dust Methods and Requirements 62
6.3 Estimating Re-entrained Road Dust 63
6.3.1 PM2 5 Nonattainment and Maintenance Areas 63
6.3.2 PM10 Nonattainment and Maintenance Areas 63
6.3.3 Using AP-42 for Road Dust on Paved Roads 63
6.4 Adding Dust Emissions to MOVES/EMFAC Modeling Results 63
6.4.1 Using AP-42 for Road Dust on Unpaved Roads 63
6.4.2 Using Alternative Local Approaches for Road Dust 64
6.5 Estimating Transportation-Related Construction Dust 64
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6.5.1 Determining Whether Construction Dust Must Be Considered 64
6.5.2 Using AP-42 for Construction Dust 64
6.5.3 Using Alternative Approaches for Construction Dust 65
6.6 Estimating Additional Sources of Emissions in the Project Area 65
6.6.1 Construction-Related Vehicles and Equipment 65
6.6.2 Locomotives 65
6.6.3 Additional Emission Sources 65
Section 7: Estimating Project-Level PM Concentrations Using AERMOD 67
7.1 Introduction 67
7.2 General Overview of Air Quality Modeling 67
7.3 Using AERMOD 69
7.3.1 AERMOD Is EPA's Dispersion Model for Transportation Projects 69
7.3.2 How Emissions Are Represented in AERMOD 69
7.3.3 Alternate Models 70
7.4 Characterizing Emission Sources 71
7.4.1 Physical Characteristics and Location 71
7.4.2 Emission Rates/Emission Factors 72
7.4.3 Timing of Emissions 72
7.5 Incorporating Meteorological Data 72
7.5.1 Finding Representative Meteorological Data 72
7.5.2 Surface and Upper Air Data 74
7.5.3 Time Duration of Meteorological Data Record 75
7.5.4 Considering Surface Characteristics 76
7.5.5 Specifying Urban or Rural Sources 77
7.6 Placing Receptors 78
7.6.1 Overview 78
7.6.2 General Guidance for Receptors for All PM NAAQS 78
7.7 Running the Model and Obtaining Results 81
Section 8: Determining Background Concentrations from Nearby and Other Emission Sources 82
8.1 Introduction 82
8.2 Nearby Sources that Require Modeling 83
8.3 Options for Background Concentrations 85
8.3.1 Using Ambient Monitoring Data to Estimate Background Concentrations 85
8.3.2 Adjusting Air Quality Monitoring Data to Account for Future Changes in Air Quality:
Using Chemical Transport Models 88
Section 9: Calculating PM Design Concentrations and Determining Conformity 92
9.1 Introduction 92
9.2 Using Design Concentrations in Build/No-Build Analyses 93
9.3 Calculating Design Concentrations and Determining Conformity for PM Hot-Spot Analyses 96
9.3.1 General 96
9.3.2 Annual PM25 NAAQS 96
9.3.3 24-hour PM2 5 NAAQS 100
9.3.4 24-hour PMio NAAQS 104
9.4 Determining Appropriate Receptors for Comparison to the Annual PM2 5 NAAQS 107
9.4.1 Overview 108
9.4.2 2012 PM NAAQS Final Rule and Conformity Guidance 108
9.5 Documenting Conformity Determination Results Ill
Section 10: Mitigation and Control Measures 112
10.1 Introduction 112
10.2 Mitigation and Control Measures by Category 112
10.2.1 Retrofitting, Replacing Vehicles/Engines, and Using Cleaner Fuels 112
10.2.2 Reduced Idling Programs 113
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10.2.3 Transportation Project Design Revisions 114
10.2.4 Fugitive Dust Control Programs 114
10.2.5 Addressing Emissions from Other Sources 115
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List of Exhibits
Exhibit 3-1. Overview of a PM Hot-Spot Analysis 19
Exhibit 4-1. Steps for Using MOVES in a Quantitative PM Hot-Spot Analysis 27
Exhibit 4-2. Typical Minimum Number of MOVES Runs for an Analysis Year 33
Exhibit 7-1. Overview and Data Flow for Air Quality Modeling with AERMOD 68
Exhibit 9-1. General Process for Calculating Design Concentrations for PM Hot-Spot Analyses 92
Exhibit 9-2. General Process for Using Design Concentrations in Build/No-build Analyses 94
Exhibit 9-3. Determining Conformity to the Annual PM2 5NAAQS 98
Exhibit 9-4. Determining Conformity to the 24-hour PM2 5 NAAQS Using First Tier Approach 102
Exhibit 9-5. Ranking of 98th Percentile Background Concentration Values 103
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List of Appendices
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: [RESERVED] E-l
AppendixF: [RESERVED] F-l
Appendix G: [RESERVED] G-l
AppendixH: [RESERVED] II-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 Concentration Calculations for PM Hot-Spot Analyses K-l
Appendix L: Calculating 24-hour PM2.5 Design Concentrations Using a Second Tier Approach L-l
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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 PM2.5 and PM10 (PM) nonattainment and maintenance
areas.1 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.2 It also outlines how to apply EPA's AERMOD dispersion
model 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 PM10. 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.3
1.2 Requirement for Quantitative PM Hot-Spot Analyses
All PM hot-spot analyses necessary for meeting the requirements of transportation
conformity must be quantitative. The requirement that these analyses be quantitative has
been in effect since 2012. For additional information, see EPA's December 20, 2010
1 PM, or particulate matter, includes PM10, which are particles with diameters that are generally 10 microns
and smaller, and PM25, which are particles with diameters generally 2.5 microns and smaller. For more
information, see https ://www.epa. gov/pm-pollution.
2 This guidance is applicable to MOVES3 and future versions of the MOVES model unless EPA notes
otherwise when approving the model for conformity purposes.
3 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:
https://www.epa.gov/state-and-local-transportation/proiect-level-conformitv-and-hot-spot-
analvses#coguidance.
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Federal Register announcement that models and guidance for PM hot-spot analyses were
available (75 FR 79370, December 20, 2010).
Quantitative hot-spot analyses must be based on the latest emissions model, according to
40 CFR 93.111. EPA publishes a Federal Register notice of availability for MOVES
(and EMFAC in California) when a new model can be used for conformity and
establishes a grace period before its use is required as the latest emissions model for PM
hot-spot analyses. The effective date of the Federal Register notice constitutes the start
of the conformity grace period for the use of that version of the model.4 EPA has issued
policy guidance on when these models are used for PM hot-spot analyses and other
purposes, which provides more details on model transition.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 (40 CFR
93.116(a) and 93.123(b)). 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 (40 CFR
93.116(a)). 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-
4 EPA posts all Federal Register notices for new emissions models on its web site:
https://www.epa.gov/state-and-local-transportation/policY-and-technical-guidance-state-and-local-
transportation#emission.
5 The latest version of the policy guidance on the use of MOVES for state implementation plan
development and transportation conformity is available online at: https ://www .epa. gov/state-and-local-
transportation/policv-and-technical-guidance-state-and-local-transportation#emission.
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spot requirements that existed before the March 2006 final rule.6 EPA strongly
encourages states to revise these outdated conformity SIPs to take advantage of the
streamlining flexibilities provided by the current CAA.7 See Appendix C of this
guidance 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 and is the only EPA guidance that covers how to
conduct a PM hot-spot analysis for a transportation project. Certain sections of this
technical guidance may also apply when completing analyses of transportation projects
for other purposes, such as general conformity determinations, National Environmental
Policy Act (NEPA) analyses, or assessing near-source air quality in communities with
environmental justice concerns.8 For example, the approach described in Section 4 may
be used to estimate transportation project emissions using MOVES, and Sections 7 and 8
may 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.
• Section 4 describes how to estimate vehicle emissions from a project using the
latest emissions model MOVES (for all states other than California).
• Section 5 provides information to consider for modeling projects in California
with EMFAC and is in addition to California Air Resources Board (CARB)
handbook for using EMFAC to estimate emissions from projects.9
• 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.
6 A "conformity SIP" includes a state's specific criteria and procedures for certain aspects of the
transportation conformity process (40 CFR 51.390).
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:
https://www.epa.gov/state-and-local-transportation/policY-and-technical-guidance-state-and-local-
transportation#state.
8 For more information about environmental justice, see https://www.epa.gov/environmentaliustice.
9 CARB's EMFAC welcome website is found at: https://arb,ca. gov/emfac/. This link as well as the CARB
EMFAC training website, https://ww2.arb.ca.gov/our-work/programs/mobile-source-emissions-
inventorv/msei-training-materials. include training videos. EMFAC documentation, including
documentation for project-level modeling (titled, PL Handbook), is found at: https://ww2.arb.ca. gov/our-
work/programs/mobile-source-emissions-inventorv/msei-modeling-tools-emfac-software-and.
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• 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 concentrations and
determine whether or not the project conforms. The term "design concentration"
refers to the combination of the appropriate background concentration with the
estimated modeled impact of the project. See Section 2.4.1 for additional
discussion.
• 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.
• 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, F, G, and H: reserved.10
• 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 concentration
calculations.
• Appendix K has examples of how to calculate design concentrations and
determine transportation conformity.
• Appendix L provides information on how to calculate 24-hour PM2.5 design
concentrations using a "second tier" approach.
Except where indicated, this guidance applies for the annual PM2.5 NAAQS, the 24-hour
PM2.5 NAAQS, and the 24-hour PM10 NAAQS. This guidance is written for current and
future PM2.5 and PM10 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: https://www.epa.gov/state-and-local-transportation/epa-regional-contacts-
regarding-state-and-local-transportation.
10 Appendices E through H have been retained for the purpose of maintaining references throughout the
document only. Their content has been removed.
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General questions about this guidance and technical questions about conformity hot-spot
analyses can be directed to Laura Berry at EPA's Office of Transportation and Air
Quality, berry.laura@epa.gov.
Specific questions related to using MOVES at the project scale can be directed to the
MOVES email in-box, mobile@epa.gov.
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.
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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)(1) 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)(1)(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
milestones in any area."11
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)(1) of the conformity rule defines the projects that require a PM2.5 or
PM10 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;
11 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 (D.C. Cir. 2006) and Environmental Defense vs. EPA, 509 F.3d 553 (D.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 PM2.5 or PM10 applicable implementation plan or implementation
plan submission, as appropriate, as sites of violation or possible violation."
For all other non-exempt federal 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)(1). 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.12 Appendix B includes the additional examples found
in EPA's PM Hot-Spot Analysis FAQs.13
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
12 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).
13 EPA, PM Hot-spot Analyses: Frequently Asked Questions, EPA-420-F-18-011, June 2018, found on
EPA's website at: https://www.epa.gov/state-and-local-transportation/proiect-level-conformitv-and-hot-
spot-analvses#faa.
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be limited cases when conformity requirements apply after the initial NEPA process has
been completed.14
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.
The conformity rule also requires agencies completing project-level conformity
determinations to establish a proactive public involvement process that provides
14 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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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.15 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.
See Section 3.10 for information about documenting the decisions made in an analysis.
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).16 These air quality concentrations are determined by calculating a
"design concentration," a statistic that describes a future air quality concentration in the
project area that includes both the background and the impact from the project that can be
compared to a particular NAAQS. The concept of design concentration is similar to the
concept of a design value:
• A design value is a statistic that describes the air quality status of a given location
relative to the level of the NAAQS.17 Design values are based on data from air
quality monitors and can be used to determine the air quality status of a given
nonattainment or maintenance area (40 CFR Part 50).
• A "design concentration" also describes air quality relative to the NAAQS and is
the combination of the appropriate background concentration with the estimated
modeled impact of the proposed transportation project. This term is adapted from
Section 9.2.2 of Appendix W of 40 CFR Part 51 (hereafter, "Appendix W").18
15 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."
16 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.
17 This definition is found on EPA's website at: https://www.epa.gov/air-trends/air-qualitv-design-values.
18 Appendix W of 40 CFR Part 51 is the regulation known as The Guideline on Air Quality Models. The
most recent update to this regulation is the final rule published January 17, 2017, (82 FR 5182), found on
EPA's website at: https://www.epa.gov/sites/default/files/2020-09/documents/appw 17.pdf.
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It is always necessary to complete emissions and air quality modeling on the build
scenario and compare the resulting design concentrations 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. As always, the approach should be discussed and agreed to within
the area's interagency consultation process:
• First, model the build scenario and account for background concentrations in
accordance with this guidance.
o If the design concentrations 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),
o 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 concentrations greater than the NAAQS
(e.g., even with the addition of mitigation or control measures), 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.
o If the design concentrations for the build scenario are less than or equal to the
design concentrations for the no-build scenario, then the project meets the
conformity rule's hot-spot requirements,
o 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 concentrations 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 concentrations 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.19 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
19 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
(40 CFR 93.125).
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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
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 concentration 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 [design
concentration] for the "new" site would be less than the design value [design
concentration] at the "old" site without the project - that is, if there would be a net air
quality benefit" (58 FR 62213).20 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
20 Note that this sentence is from the 1993 conformity rule, which predates the distinction made between
"design value" and "design concentration" in the Appendix W regulation; the sentence is referring to
design concentration. For more information, see Section 2.4.1 of this guidance.
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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.21
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:
• 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.22
• 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
concentrations 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.23
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.
21 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.
22 Such as AERSCREEN or AERMOD using meteorological conditions suitable for screening analyses.
23 Since Section 93.123(b)(1) of the conformity rule requires PM hot-spot analyses forprojects 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.
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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.
2.5 Emissions Considered in PM Hot-Spot Analyses
2.5.1 General Requirements
PM hot-spot analyses include only directly emitted PM2.5 or PM10 emissions. PM2.5 and
PM10 precursors are not considered in PM hot-spot analyses, since precursors take time at
the regional level to form into secondary PM.24
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 included
in a project's PM2.5 or PM10 hot-spot analysis. See Section 4 for how to quantify these
emissions using MOVES (outside California). See Section 5 and the latest EMFAC
model documentation from CARB for how to quantify these emissions using EMFAC
(within California).25
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).26
• If a PM2.5 area has no adequate or approved SIP budgets for the PM2.5 NAAQS.
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 PM2.5 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.
24 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).
25 See footnote 9 (Section 1.6) for CARB reference information.
26 See the July 1, 2004 final conformity rule (69 FR 40004).
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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 0 Emissions from Re-entrained Road Dust
Re-entrained road dust must be included in all PM10 hot-spot analyses. Because road
dust is a significant component of PM10 inventories, EPA has historically required road
dust emissions to be included in all conformity analyses of direct PM10 emissions -
including hot-spot analyses.27 See Section 6 for further information regarding how to
estimate re-entrained road dust for PM10 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 PM10 hot-
spot analyses (because, in most cases, the construction phase is less than five years at any
one site; see 40 CFR 93.123(c)(5)).28 However, there may be limited cases where a large
project is constructed over a longer time period (five years or greater) at any individual
site, 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 is designated nonattainment or
maintenance ("relevant NAAQS"). Therefore, a project-level conformity determination
must address all applicable NAAQS for a given pollutant.29
Accordingly, results from a quantitative hot-spot analysis will need to be compared to all
relevant PM2.5 and PM10 NAAQS in effect for the area undertaking the analysis. For
example, in an area designated nonattainment or maintenance for only an annual PM2.5
NAAQS or only a 24-hour PM2.5 NAAQS, the hot-spot analysis would have to address
only that relevant PM2.5 NAAQS. If an area is designated nonattainment or maintenance
27 See the March 2006 final rule (71 FR 12496-98).
28 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).
29 See EPA's March 2006 final rule (71 FR 12468-12511).
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for both an annual and 24-hour PM2.5 NAAQS, the hot-spot analysis would have to
address both NAAQS for conformity purposes. Note that conformity applies for both
primary and secondary NAAQS; in most cases they are the same.
Refer to EPA's web site at https://www.epa.gov/state-and-local-transportation/baseline-
vear-baseline-vear-test-40-cfr-93119 for a list of the PM NAAQS in effect. EPA's
"Green Book" web site at https://www.epa.gov/green-book also has information about
the PM NAAQS in effect, areas designated, and implementation regulations. Additional
guidance about implementing the latest PM NAAQS for conformity is found on EPA's
web site at: https://www.epa.gov/state-and-local-transportation/policv-and-technical-
guidance-state-and-local-transportation#requirements.
2.7 Background Concentrations
As required by 40 CFR 93.123(c)(1) 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
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.30
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.31 Analysis years must be
within the timeframe of the transportation plan, per 40 CFR 93.116(a). In isolated rural
areas, analysis years must be within the timeframe of regional emissions analysis, based
on 40 CFR 93.116(a) and 40 CFR 93.109(g)(2)(i). 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
30 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.
31If 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.
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• 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.32
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
of the completed project.33 As another example, it may be useful to select a near-term
year when emissions rates will be highest as well as a future year when vehicle volumes
and/or vehicle miles traveled is highest. Selecting appropriate analysis year(s) should be
considered through the process established by each area's interagency consultation
procedures (40 CFR 93.105(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.
32 See EPA's July I, 2004 final conformity rule (69 FR 40056-40058).
33 See EPA's July 1, 2004 final rule (69 FR 40057).
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2.9.2 DOT
DOT is responsible for making project-level conformity determinations for FHWA/FTA
projects (see 40 CFR 93.101 for the definition). 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. EPA provides tools for emissions modeling, including the MOVES emission
model and associated tools, documentation, and scripts. EPA also provides tools for air
quality modeling, including the AERMOD dispersion model, its associated pre-
processors, and documentation. As the agency that develops and promulgates these tools,
EPA would make decisions about the use of alternative dispersion models in a PM hot-
spot analysis according to Appendix W.34 EPA would also make decisions about
whether monitoring data can be excluded from the background concentrations based on
exceptional events in consultation with the relevant state or local air agency.35
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. 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.
34 See footnote 18 (Section 2.4.1) for Appendix W reference information.
35 See Additional Methods, Determinations, and Analyses to Modify Air Quality Data Beyond Exceptional
Events, EPA-457/B-19-002, April 2019, available onEPA's website at: https://www.epa.gov/state-and-
local-transportation/proiect-level-conformitv-and-hot-spot-analvses#modifV-methods.
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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 1)
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, including proposed
receptor locations;
• 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)).
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Exhibit 3-1. Overview of a PM Hot-Spot Analysis
Step 1: Determine Need
for Analysis
Step 2:
Determine Approach, Models, and Data
Step 3: Estimate On-Road Motor
Vehicle Emissions
KIs project located
in California?
Step 5: Set Up and Run
Air Quality Model
(AERMOD)
Obtain and input
required site data (e.g
meteorological)
Input MOVES/
EMFAC, dust, and
nearby source outputs
Run air quality model
and obtain results
Step 7: Calculate Design
Concentrations and Compare
Build/No-Build Results
Add Step 5 results to
background concentrations
to obtain design
concentrations for
build/no-build scenarios
I
Do the design
concentrations
allow the project
to conform?
Yes
No
Step 8:
Consider Mitigation or
Control Measures
Consider measures to
reduce emissions and redo
analysis
i
Yes
Do the design
concentrations
allow the project
to conform?
Step 9:
Document Analysis
No
Step 6:
Determine Background
Concentrations
Project conforms
Project does not
conform
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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.36 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)(1)). 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.37 In addition to emissions from the proposed
highway or transit project,38 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.
Note that interagency consultation should be used to help identify the appropriate
receptor locations in the area substantially affected by the project. For example, the area
substantially affected by a highway widening project may include an interchange or parts
of an intersecting arterial. These types of effects should be considered when determining
which areas are to be modeled.
Questions regarding the scope of a given PM hot-spot analysis should be determined
through the interagency consultation process.
36 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.
37 See more in the March 24, 2010 final conformity rule entitled, Transportation Conformity Rule PM2.5
and PMw Amendments, 75 FR 14281; found online at: https://www.epa.gov/state-and-local-
transportation/transportation-conformitv-chronological-list-rulemakings.
38 40 CFR 93.101 defines "highway project" and "transit project" for transportation conformity purposes.
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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
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. For example, if an
area is nonattainment for only the 24-hour NAAQS and has always been in attainment for
the annual NAAQS, then only the design concentration for the 24-hour NAAQS would
need to be evaluated. A hot-spot analysis for an annual PM2.5 NAAQS would involve
data and modeling throughout a given analysis year. A hot-spot analysis for the 24-hour
PM2.5 or PM10 NAAQS would also involve data and modeling throughout an analysis
year.
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 emissions model must be
used in PM hot-spot analyses (40 CFR 93.111). The air quality model and methods must
be based on the requirements specified in Appendix W.39 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.
39 See footnote 18 (Section 2.4.1) for Appendix W reference information.
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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
Section 4 (MOVES) and in Section 5 and CARB model documentation40 (EMFAC):
• 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.
Data that will be needed for air quality modeling, as described in Sections 7 through 9,
include:
• Surface meteorological data from monitors that measure the atmosphere near the
ground;
• 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. See Section 5 and CARB
model documentation for how to apply EMFAC for estimating these emissions for
projects in California.
40 See footnote 9 (Section 1.6) for CARB reference information.
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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 Source Types, Data Inputs, and Receptors for AERMOD
(Step 5)
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
then included in air quality modeling. EPA's air quality model AERMOD is required for
use in PM hot-spot analyses; (see Appendix W to part 51, Section 4.2.3.5 "Models for
PM2.5" and Section 4.2.3.6, "Models for PM10").
AERMOD predicts how emissions are dispersed based on meteorological and other input
data. Emissions are described or characterized within AERMOD as sources, and there
are several types with different attributes that can be used. The specific locations in the
project area where AERMOD estimates PM concentrations are known as receptors. See
Section 7.6 for additional information about placing receptors.
Additional information about AERMOD 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.
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3.8 Calculate Design Concentrations 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
concentration; how it is calculated depends on the form of the NAAQS. (Refer to Section
2.4.1 for more discussion of design concentrations.) If the design concentration 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
concentration is greater than the NAAQS in the build scenario, a project could still meet
conformity requirements if the design concentrations in the build scenario were less than
or equal to the design concentrations 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
concentrations 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.
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. The transportation conformity regulation at 40 CFR 93.105(e)
requires that "affected agencies making conformity determinations on transportation
plans, programs, and projects shall establish a proactive public involvement process.
The regulation also states, "These agencies shall also provide opportunity for public
involvement in conformity determinations for projects whether otherwise required by
law." Documentation of the project-level conformity determination, including technical
and policy information considered in the PM hot-spot analysis, should be made available
to the public at the beginning of the comment period.
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
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activity projected for the analysis year(s), and what part of 40 CFR 93.123(b)(1)
applies. Maps and diagrams are useful for conveying this information;41
• 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);
• Explanation of naming conventions, if used, for project links so that these can be
related to specific areas of the project;
• Written narrative that explains step-by-step how emissions from MOVES or
EMFAC were used as inputs in air quality modeling. If MOVES emission rates
were generated, explain how such rates are used in the air quality model
specifically, including information about grade, speed, and vehicle mix (e.g.,
percentage of light- and heavy-duty vehicles) on each link of the project. Include
sufficient information, such as link-by-link traffic volumes, scripts used, and
intermediate tables, so that a reviewer can follow and recreate the process of how
MOVES emission rates are applied to the specific sources in AERMOD;
• Air quality modeling data, including modeling inputs and results and description
of the sources and 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 project meets 40 CFR 93.116 and 93.123
conformity requirements for the PM2.5 and/or PM10NAAQS.
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.
41 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.42 This
section presumes users already have a basic understanding of how to run the MOVES
model.43 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.44
MOVES is a computer model designed by EPA to estimate emissions from cars, trucks,
buses, and motorcycles, and nonroad equipment. MOVES can estimate PM emissions at
high resolution, accounting for fuel characteristics, ambient temperatures, and vehicle
activity patterns including speed and acceleration. As a result, MOVES allows users to
incorporate a wide array of vehicle activity data for each roadway link, as well as start,
idling, and hotelling activity.45 For more information about MOVES, including the EPA
rulemakings, emissions data, and new features included in the latest version of the model,
please see https://www.epa.gov/moves/latest-version-motor-vehicle-emission-simulator-
moves.
Exhibit 4-1 (on the following page) shows the necessary steps for applying the MOVES
model for project-level PM hot-spot analyses.
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 and 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 CFR 93.110 and 93.123(c)).
42 This guidance applies to M0VES3 and future versions of the MOVES model, unless EPA notes
otherwise when approving the model for conformity purposes.
43 The MOVES model and supporting documentation are available online at: www.epa. gov/moves.
44 The most recent technical guidance on using MOVES for regional emissions inventories can be found
online at: www.epa.gov/state-and-local-transportation/policv-and-technical-guidance-state-and-local-
transportation#emission.
45 "Hotelling" refers to any long period of time that drivers spend in their long-haul combination trucks
(source type 62) during mandated rest times. When hotelling, one or more accessories such as a heater, air
conditioner, television, or computer could be running. More information is included in Sections 4.2 and
4.5.
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Exhibit 4-1. Steps for Using MOVES in a Quantitative PM Hot-Spot Analysis
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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
concentration 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, described
further below, and the associated emission processes (e.g., running, start, brake wear, tire
wear, hotelling, 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, idling, and hotelling
emissions are typically needed; in some cases, these projects will also need to
address running exhaust, brake wear and tire wear from cruise, approach and
departure on affected links.
Within MOVES, a link represents a segment of road or an "off-network" location where
a certain type of vehicle activity occurs.46 The goal of defining a project's links is to
accurately estimate emissions from a specific type of activity where that activity occurs.
In modeling highway and intersection projects, the user will primarily be defining links
representing road segments, and for transit and other terminal projects, the user will be
defining activity at an off-network location. However, in modeling either of the two
types of projects described above, the user may need a combination of links representing
road segments and off-network areas.
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 specific hour
chosen by the modeler for the MOVES run. In MOVES, running emissions, including
46 "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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periods of idling,47 can be defined in the Links Importer (see Section 4.5.6); there are also
other alternatives when the user has additional information (see Section 4.5.8). Starts and
hotelling of combination long-haul trucks are defined in the Off-Network Importer (see
Section 4.5.9). There are no limits to the number of links representing road segments that
can be defined in a MOVES run, but only one off-network link can be defined per run.
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.48 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 4.5.8).
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. Some resources are available
47 All kinds of idling that are not specifically long-haul combination truck hotelling are modeled as running
emissions on running links at Project Scale in MOVES. This includes idling at traffic signals, idling during
pick up and drop off of passengers, idling during deliveries, etc. For users that are familiar with the County
Scale features of MOVES, note that Project Scale does not implicitly model "Off-Network Idling" (ONI).
The kinds of idle that would be accounted for as ONI in County Scale (such as idling during pick up and
drop off of passengers) are instead accounted for in Project Scale using running links. See Section 4.5.8 for
more information.
48 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.
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through FHWA's Travel Model Improvement Program (TMIP).49 Methodologies for
computing intersection control delay are provided in the Highway Capacity Manual,50
As described further in Section 4.5.8, users should take advantage of the full capabilities
of MOVES for estimating emissions on different highway and intersection project links.
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 Schedules 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. For example, a single, one directional, four-
lane highway could be simply characterized as one link. More sophisticated analyses for
a facility may use multiple links to vary operating modes or drive cycles depending on
the relative acceleration, cruise, or deceleration activity occurring on each segment of that
link. Another possibility is to define multiple links for the same road segment, for
various vehicle types. For example, one link could be for light-duty vehicles and a
second link for heavy-duty vehicles if these two categories of vehicles are expected to
have different vehicle activity on that road segment. In general, the definition of a link
will depend on the traffic volume present, how 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,
49 See FHWA's TMIP website: http://tmip.fhwa.dot.gov/.
50 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, Sixth Edition: A Guide for Multimodal
Mobility Analysis, released September 2016 by the Transportation Research Board (see
www.trb.org/Main/Blurbs/175169.aspx for details).
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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 on the specific details of that
project and the amount of available activity information. Idling at an intersection should
be represented in combination with decelerating, accelerating, and free-flow traffic on an
approach segment of an intersection.
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. More information on using vehicle trajectories
from traffic micro-simulation models is found in Appendix D.
Off-network Links
If the analysis involves an area that is not part of the road network, such as a terminal or a
parking area, such an area can be modeled using an off-network link defined in the Off-
Network Importer and one or more links defined in the Links Importer:
• Start and hotelling activity would be defined in the Off-Network Importer.
Section 4.5 describes the inputs needed.
• Running and idling activity at this area would be defined the way other road links
are defined (e.g., in the Links Importer, using on-network road types).
4.2.2 Transit and Other Terminal Projects
Projects such as a bus terminal or intermodal freight terminal can also be defined in terms
of links. On these types of projects, a variety of activity - start, hotelling, idling, or
running - may be occurring, and can be defined in MOVES in terms of links. (Note that
while included in this list for completeness, hotelling would not likely be occurring at a
terminal.)
The user should have information on the activity occuring in this area: starts per hour,
number of long-haul trucks hotelling, and number of vehicles idling during each hour.51
This activity will likely vary from hour to hour.
Start Activity: If there are vehicles starting, it is necessary to provide an estimate of the
duration that vehicles are parked before starting (soak-time distribution). If there are
multiple areas of start activity within a project with roughly the same soak time
distributions, these areas can be modeled with one off-network link using an
appropriately weighted distribution of soak times.52
51 Idling here is non-hotelling idling.
52 In the event that a project has multiple areas of start activity in different locations that have different soak
time distributions, please consult with EPA before modeling.
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Hotelling: Hotelling activity, including extended idling, auxiliary power unit (APU) use,
and electrification, applies only to long-haul combination trucks. This type of activity is
defined on an off-network link and would not likely be occurring at transit or other
terminals. (Shorter periods of idling for long-haul combination trucks should be modeled
as a running link via the Links Importer.)
Idling Activity: Areas within the project with different amounts of idling can be
specified as separate running links. See Section 4.5.8 for more information on how to
model idling with running links.
Running Activity: 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 the other activities happening
on the off-network link (e.g., start activity, hotelling, idling activity) outside of the
MOVES 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.
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
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).53 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.
53 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, available on EPA's website at: https://www.epa.gov/state-and-
local-transportation/policv-and-technical-guidance-state-and-local-transportation#reauirements.
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The number of MOVES runs should be based on the best available activity data and the
PM NAAQS involved. MOVES models the PM impact of activity, fuel and temperature
conditions that may change over a day and across a year.
However, the PM temperature adjustment has changed in MOVES3, as described in
EPA's report, Emission Adjustments for Temperature, Humidity, Air Conditioning, and
Inspection and Maintenance for Onroad Vehicles inMOVES3 54 To summarize, while
there is a temperature effect on PM start emissions from gasoline vehicles, there is no
temperature effect for PM running emissions from gasoline vehicles, and there is no
temperature effect for any PM emissions from diesel or CNG vehicles.
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, and these recommendations depend on whether or not the project
includes start activity from gasoline vehicles. Exhibit 4-2 includes EPA's general
recommendations for PM hot-spot analyses:
Exhibit 4-2. Typical Minimum Number of MOVES Runs for an Analysis Year
Type of Project
Applicable
NAAQS
Build Scenario
No-build
Scenario55
Projects without
gasoline start activity
All PM2.5 and
PM10 NAAQS
4
4
Projects with start
activity from
gasoline vehicles
All PM2.5 and
PM10 NAAQS
16
16
Many types of projects do not include gasoline start activity, including new highways,
expanded highways, projects that affect intersections, and those terminal projects that
predominantly involve diesel rather than gasoline vehicles. For projects that do not
include gasoline start activity, hot-spot analyses for any of the PM NAAQS could be
done using four unique MOVES runs, to represent four different time periods of the day:
morning peak, midday, evening peak, and overnight. In this case, the month selected in
MOVES should be a month with the seasonal fuel that results in the highest PM
emissions,56 and modelers should input the VMT from the month where VMT is the
greatest.57 Note that the month with the highest VMT may be different than the month
with the seasonal fuel with the highest PM emissions. For a typical build/no-build
54 See EPA's report, Emission Adjustments for Temperature, Humidity, Air Conditioning, and Inspection
and Maintenance for Onroad Vehicles in MOVES3, EPA-420-R-20-013, November 2020, available on
EPA's website at: https://www.epa.gOv/moves/moves-onroad-technical-reports#moves3.
55 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.
56 If this is not known, a modeler can do a simple run to determine which seasonal fuel produces the highest
emissions.
57 If only annual VMT or daily VMT is available, modelers can export the default MOVES table that
apportions VMT across the months of the year.
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analysis, a total of eight runs would be needed (four for the build scenario and four for
the no-build scenario).
Using four runs as described here instead of 16 may be more conservative. Modelers
have the choice to run MOVES more times, e.g., for four different seasons, or for
additional time periods of the day, to better represent variation in VMT across seasons
and across the day if they choose.
In contrast, where projects include start activity from gasoline vehicles, such as projects
that include a parking area or parking garage, hot-spot analyses 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).
The product of the MOVES analysis is a year's worth of hour-specific emission factors
for each project link that will be applied in AERMOD (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. 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)). It is important to capture variation in emission rates as activity and
in some cases ambient temperature change (as noted above) over the period being
analyzed.
For projects that do not include start activity from gasoline vehicles, four runs would be
done for the month with the seasonal fuel that results in the highest PM emissions using
the highest monthly VMT.
For projects that include start activity from gasoline vehicles, 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).58 The emission factors for each month's runs
should be used for the other months within the season. Each of the four months
suggested for the minimum number of MOVES runs represent emissions in that month as
58Weekdays usually have higher activity than weekend days. In the case of a project where that is not true,
weekend days should be chosen instead. Note the rationale for choosing weekend days over weekdays
should be discussed within the interagency consultation process and documented in the analysis.
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well as the months immediately before and after that month. For instance, January
emissions represent emissions in the months of December, January, and February; April
emissions represent emissions in March, April and May; and so forth.59
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 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 (AADT minus the total volume assigned to the peak 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 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.
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.
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, soak times, 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. For example, if the start and idling
temporal patterns are likely to differ significantly from the temporal patterns in VMT,
and start and idling emissions make a notable contribution to the total PM emissions, then
additional modeling may be useful. 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.
59 For example, January 2030 emissions represent emissions in January, February, and December of 2030
(rather than December 2029).
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4.4 Developing 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, and the emission-producing
processes and pollutants that will be included in the analysis. Once selections are made
for the RunSpec, the user has to create an input database for that RunSpec using the
MOVES Project Data Manager, described in Section 4.5.
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
• Onroad Vehicles
• Road Type
• Pollutants and Processes
• General Output
• Output Emissions Detail
• Create Input Database
• Advanced Features
Additional information on each panel can be found in the resources for MOVES training
available on EPA's website (https://www.epa.gov/moves/moves-training-sessions).
4.4.1 Description
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
The Scale Panel in MOVES allows the user to select different scales or domains for the
MOVES analysis. In this panel, MOVES allows users to choose the "Onroad" or
"Nonroad" module; "Onroad" is the appropriate choice for project-level analyses. All
MOVES runs for project-level analysis must be done using the "Project" domain in the
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Scale Panel. Selecting the "Project" domain is necessary to allow MOVES to accept
detailed activity input at the link level.60
The Scale Panel also requires that the user select a calculation type of either Inventory or
Emission Rates:
• If Inventory is selected, MOVES provides emission estimates as mass for each
link, using the link activity entered by the user. Inventory emission estimates at
Project Scale are equivalent to link-specific grams per hour emission factors.
• If Emission Rates is selected, MOVES provides emission rates as mass per unit
of activity. The Emission Rates mode produces link-specific grams per vehicle-
mile emission factors.
The selection of calculation type is required early in the RunSpec construction process
because this choice affects the available options in later panels. The Emission Rates mode
is more complex than the Inventory mode. Successful application of this mode requires
careful planning and a clear understanding of the rates calculations in MOVES. Large
differences in results between the Inventory and Emission Rates modes usually indicate a
mistake in post-processing of the emission rates using the Emission Rates mode. The
most common mistakes when using the Emission Rates mode are:
• not including all pollutant processes, and
• multiplying emission rates by the wrong activity.
Even when done correctly, minor differences in post-processing methods can create small
differences in results. EPA recommends that the same mode be used in any analysis that
compares two or more cases, e.g., the same mode should be used for build and no-build
scenarios of an analysis, and for multiple years in the same analysis. The interagency
consultation process should be used to agree upon a common approach and to share
detailed results during reviews of draft PM hot-spot analyses that support project-level
conformity determinations.
This guidance explains the steps of post-processing both "Inventory" and "Emission
Rates" results to produce the desired emission inputs for AERMOD in Section 4.6.
4.4.3 Time Spans
At the Project scale, each MOVES run represents one specific hour. 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 year, month, day, and hour that the run will
represent. As Project Scale models only one hour at a time, only the start hour needs to
be selected on this panel.
The user should enter the desired time period (i.e., the specific year, month, type of day,
and hour) in the MOVES Time Spans Panel for estimating PM2.5 and/or PM10 emissions
60 Running MOVES using the "County" or "Default" domains would not allow for detailed link-level input
or output that is needed for PM hot-spot analyses.
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for the relevant NAAQS in a given nonattainment or maintenance area. The "day"
selection should be set to "weekdays" or "weekend," but not both. Most users will be
defining activity for a typical weekday. For instance, one run for the hot-spot analysis
might be for the specific hour of: 2030, January, Weekdays, 8:00 to 8:59 a.m. The user
may choose to build a batch file to automate the process of running multiple scenarios.61
4.4.4 Geographic Bounds
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
the 3,000-plus 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 can be included in a MOVES run at
the Project Scale. If a project spans multiple counties, users have two options:
1. If the county-specific local data (e.g., fuel information, 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.
4.4.5 Onroad Vehicles
The Onroad Vehicles 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). Users should generally select
all 13 vehicle types. The exception may be when modeling projects that contain a captive
fleet where only certain types of vehicles are present (e.g., a transit bus terminal).
Selecting a vehicle type will include the relevant fuel types for that vehicle. To change
the percentages of vehicles using the different fuel types in the project, use the Fuel
Importer of the Project Data Manager (discussed in Section 4.5.3).
4.4.6 Road Type
The Road Type Panel is used to define the types of roads that are included in the project.
MOVES defines five different road types:
• Off-Network - any location where the predominant activity is vehicle starts and
hotelling (parking lots, truck stops, rest areas, freight or bus terminals);
• 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);
61 For more information about using batch commands, see Running MOVES from the Windows command
line.
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• Urban Restricted Access - an urban highway that can be accessed only by an on-
ramp; and
• Urban Unrestricted Access - all other urban roads (arterials, connectors, and local
streets).
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 to 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 hotelling for long-haul combination trucks 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 hotelling activity are given in Section 4.5.9.
4.4.7 Pollutants and Processes
The Pollutants and Processes Panel is used to select both the types of pollutants and the
emission processes that produce them. For PM2.5 or PM10 emissions, MOVES calculates
emissions for several pollutant species:
• Total running exhaust PM, calculated from the pollutant species of elemental
carbon (EC), non-elemental carbon (Non-ECPM) and sulfate particulate
• Brakewear Particulate
• Tirewear Particulate
In addition, MOVES divides emissions by pollutant process. For a PM hot-spot analysis,
the relevant processes are:
• Running Exhaust
• Crankcase Running Exhaust
• Brakewear
• Tirewear
• Start Exhaust
• Crankcase Start Exhaust
• Extended Idle Exhaust (associated with hotelling)
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• Crankcase Extended Idle Exhaust (associated with hotelling), and
• Auxiliary Power Exhaust
For a PM2.5 hot-spot analysis, the user should select "Primary Exhaust PM2.5 - Total" (or
"Primary Exhaust PM10 - Total" if it is a PM10 hot-spot analysis), which is an aggregate
of each of the pollutant species (Composite Non-ECPM, EC, and sulfate) for each
process. For MOVES to run, users must select "Primary Exhaust PM2.5 - Total" and
click the button "Select Prerequisites" to ensure all necessary species are selected.
(These can be viewed by clicking the [+] next to "Primary Exhaust PM2.5 (or PM10) -
Species.) In addition, if the analysis has road links with running emissions, users would
also select "Primary PM2.5 - Brakewear Particulate" and "Primary PM2.5 - Tirewear
Particulate" (or their PM10 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 has created several MOVES scripts that automate the
summing of aggregate emissions when completing project-level analyses. These scripts
are available in the Post-Processing Menu item of the MOVES graphical user interface
(GUI) and are described further in Section 4.6.
If the scripts are not used, 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 is specified as a
grams/vehicle-mile emission factor ("Emission Rates" output), the aggregate total PM
emission factor (i.e., the sum of all PM emission factors for a link) is calculated as
follows:
PIVI aggregate total (PIVI total running ) + (PMtotai crankcase running) + (brakewear) + (tirewear)
The same equation above is also used for highway links where output is specified as
grams/hour ("Inventory output") and "Emissions Process" is selected on the Output
Emissions Detail Panel.62
For off-network links (links with start and hotelling activity), where output is selected as
grams/hour ("Inventory" output) and "Emissions Process" is selected on the Output
Emissions Detail Panel, the aggregate total PM emission factor (i.e., the sum of all PM
emission factors for a link) is calculated as follows:
62 If "Emissions Process" is not selected on the Output Emissions Detail Panel, MOVES will combine PM
total running and total crankcase running emissions; brake wear and tire wear will still need to be added for
the aggregate PM total.
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PMaggregate total (PMtotal starts) (PMtotal crankcase starts) (PMtotal ext. idle) (PMauxiliary power
exhaust) + (PMtotal crankcase ext. idle)''''
However, EPA recommends the use of the existing scripts to eliminate the possibility of
error in post-processing.
4.4.8 General Output
In the General Output Panel, users create or identify an output database where MOVES
will put the results of the run. It is helpful for the output database name to be related to
the name of the project to help both the modeler and future reviewers keep track. EPA
also recommends that an output database name end with " out" to indicate it is an output
database and distinguish it from an input database. Only letters, numbers, and
underscores can be used for database names.
An output database can hold the results of multiple MOVES runs. EPA recommends that
modelers use the same output database for all of the runs associated with a project. More
discussion of good data management practices is found in Section 4.4.10.
Units for output of "grams", "joules, and "miles" are already chosen and the user can
change them as needed. Also, "Distance Traveled" and "Population" should be selected
under the "Activity" heading to obtain vehicle volume information for each link in the
output.
4.4.9 Output Emissions De tail
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
and "Emission Process" will also be checked if Emission Rates was selected on the Scale
Panel. For an Inventory mode run, if start and hotelling emissions need to be quantified
separately (e.g., vehicle starts and hotelling activity are geographically separated), the
"Emissions Process" box should be checked; otherwise, it can be left unchecked. In
addition, if the modeler wants to distinguish between light and heavy-duty emissions,
"Source Use Type" should be selected; otherwise, it can be left unchecked.64 No other
boxes should be selected in order to produce fleet aggregate emission factors for each
link. Emission rates for each process can be appropriately summed using a MOVES
63 If "Emissions Process" is not selected on the Output Emissions Detail Panel, MOVES will combine PM
total starts, crankcase starts, extended idle, auxiliary power exhaust, and total crankcase extended idle
together; they would not need to be summed. If there is a need to geographically separate start emissions
from hotelling emissions, then "Emissions Process" should be selected on the Output Emissions Detail
Panel so that MOVES reports these emissions separately.
64 Users would select output by Source Use Type when modeling light- and heavy-duty emissions as
separate sources in AERMOD, or when characterizing a source's initial vertical dimension and source
release height using the emission-weighted average of light-duty and heavy-duty vehicles rather than the
volume-weighted average. See Section J.3.3 of the Appendix for more information on characterizing
sources.
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post-processing script to calculate aggregate PM emission factors for each link (as
described in Section 4.6).
4.4.10 Create Input Database
The Create Input Database Panel becomes available after all the other Navigation Panel
items have been completed and have green checks. The user can create the input
database by entering a name. (However, it is not necessary to create the database before
opening the Project Data Manager (PDM), which can be done by clicking the "Enter/Edit
Data" button.)
Since modeling a project involves multiple MOVES runs, good data management
practices are essential to prevent confusion and errors. As described in Section 4.3, a PM
hot-spot analysis will involve multiple MOVES runs, each needing its own input
database. It is helpful for the input database name to be related to the name of the project
and the hour selected for the run, to help both the modeler and future reviewers keep
track. For example, EPA recommends the following conventions:
• Use a naming protocol for each of the input databases that reflects the purpose of
that run, e.g., "SpringAMPeak in". EPA recommends that input database names
end with " in" to indicate it is a user input database. Only letters, numbers, and
underscores can be used for database names.
• When the RunSpec is complete, save each RunSpec with a name that relates to
the input database name, e.g., "SpringAMPeak.mrs". EPA recommends saving
RunSpecs with the extension ".mrs", short for "MOVES RunSpec", so that these
files can be easily identified.
Section 4.5 describes how to populate an input database using the PDM. Once a database
has been completely populated and the PDM has been closed, users should ensure that
the correct database is selected on the Create Input Database Panel. If it is not auto-
populated, users may have to hit the Refresh button to make sure the database they
created appears in the dropdown list.
4.4.11 Advanced Features
The Advanced Features Panel is used to invoke features that are used for model
diagnostics and other special purposes. In general, the features on this panel are not
appropriate for SIP and transportation conformity use, except for states that have adopted
California Low Emission Vehicle (LEV) criteria pollutant standards (and such California
standards have received a Clean Air Act waiver from EPA) and states in the Ozone
Transport Commission (OTC) that received early implementation of National Low
Emitting Vehicle (NLEV) standards. In these cases, the "Input Data Sets" feature on this
panel should be used in conjunction with the LEV/NLEV tools accessed through the
Tools drop-down menu in the MOVES GUI. Specifically:
• OTC states that did not adopt California LEV standards but were subject to the
early implementation of NLEV should use the "Build NLEV Input Database"
tool.
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• OTC states that adopted California LEV standards prior to the 2001 model year
should use the "Build LEV Input Database" tool.
• OTC states that were subject to the early implementation of NLEV and adopted
California LEV standards beginning with model year 2001 or later should use
both the "Build LEV Input Database" and the "Build NLEV Input Database"
tools.
• All other states that adopted California LEV standards in any year should use the
"Build LEV Input Database" tool.
Detailed instructions on how to use both tools are available in the MOVES GUI: after
opening the tool via the Tools drop-down menu, click the "Open Instructions" button.
After creating the input database(s) with the appropriate tool, users should include these
databases in the RunSpec through the "Input Data Sets" section of the Advanced Features
Panel. Select the appropriate input database in the database drop-down menu (users may
need to click the Refresh button if the database does not appear in the list), and then click
the Add button.
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
populate an input database to describe the project in detail for the period of time selected
in the RunSpec. An input database is a set of tables that describe project-specific data to
be used for the run, and the Project Data Manager assists the user in creating and
populating this set of tables. The Project Data Manager can be accessed from the Create
Input Database Panel of the RunSpec with the Enter/Edit Data button.
As described in Section 4.3, a typical PM hot-spot analysis will involve multiple MOVES
runs, and therefore, a typical analysis will involve 4 or 16 unique RunSpecs and the same
number of unique input databases for each build or no-build scenario for each analysis
year, one for each RunSpec. See Section 4.4.10 above for EPA's recommendations for
good data management practices.
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.
If an input database was not created (by defining a name for it) in the Create Input
Database Panel of the RunSpec, a database must be created on the Database Tab. When
the database is created, MOVES records the selections in the RunSpec at that moment
and uses this information to populate and evaluate database entries. Users should avoid
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making changes to the RunSpec after the input database has been created, because this
can create inconsistencies between the input database and the rest of the RunSpec.
The Project Data Manager includes multiple tabs to open importers used to enter project-
specific data. These importers are:
Meteorology Data
Age Distribution
Fuel
I/M Programs
Retrofit Data
Links
Link Source Types
Link Drive Schedules
Operating Mode Distribution
Off-Network
Hotelling
Generic
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
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 MOVES training.65 Guidance for the use of these importers in PM hot-spot
analyses is described below.
To run MOVES, each of these importers or tabs must have a green check; MOVES3 will
not run if any of them have red Xs. The initial status of the tabs depends on the
selections made in the RunSpec. For instance, when a project has no off-network links,
the off-network road type would not be selected in the RunSpec. In this case, the Off-
Network and Hotelling Importers would not be used and therefore those tabs will display
green checks. However, if any hotelling processes are selected in the RunSpec, the
Hotelling Importer will begin with a red X to indicate data is needed.
In addition, the status of some tabs depends on data loaded on other tabs. For example,
when a project has an off-network link, the Operating Mode Distribution tab will start
with a green check when the database is first created. When the Links tab is used to
import an off-network link, the Operating Mode Distribution tab will change to show a
red X, indicating that data is needed. Once the Operating Mode Distribution tab is used
to import the vehicle soak activity, the tab will update to show a green check.
65 See the latest version of "Hands-On Training" at: https://www.epa.gov/moves/moves-training-sessions.
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Most analyses will not use all of the importers. Some tabs, such as Link Drive
Schedules, Retrofit Data, and Generic are optional and always have green checks unless
there is an issue with any of the imported data.
4.5.1 Meteorology Data
The Meteorology Data Importer is used to import temperature and humidity data for the
month and hour that are defined in the MOVES RunSpec. 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.
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 (covered in Section 7.5). In most cases, users should simply use
the MOVES meteorology file for the county in which the project is located that was used
in the latest SIP or transportation conformity regional emissions analysis.
When modeling projects using four runs (e.g., projects without gasoline start activity),
use temperature inputs that are consistent with those used in the regional emissions
analyses for the month chosen in the RunSpec.
For projects that include gasoline vehicle start activity, users should enter data specific to
the project's location and time period modeled, as gasoline vehicle PM start emissions
vary with temperature. The accuracy of emission estimates for these projects improves
when meteorological data specific to the modeled location is included. In this case,
within each period of day in each season, 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 the January AM peak MOVES
run. 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
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 and calendar year. 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).
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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. The
MOVES3 Technical Guidance covers how this would be created.66
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.
3. If no state or local age distribution is available, the MOVES default age
distribution should be used by exporting it from the Age Distribution Importer.
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 estimates, so the default data for local fleets should be used only if an
alternative state or local dataset cannot be obtained. For single unit long-haul and
combination long-haul trucks, it is generally more appropriate to use MOVES
national default age distributions.
4.5.3 Fuel
The user needs to define in MOVES what fuel(s) and fuel mix will be used in the project
area. The four required tables in the Fuel Importer: Fuel Supply, FuelFormulation,
FuelUsageFraction, and AVFT (Alternative Vehicle and Fuel Technology) are used to
enter the necessary information describing fuel mix and fuel type for each MOVES run,
including the appropriate fractions of gasoline, diesel, CNG and electric vehicles. 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 by
exporting it from the Fuel Importer, and make changes only if local volumetric fuel
property information is available. Otherwise, EPA strongly recommends that the
MOVES default fuel supply and formulation information be used unless a full local fuel
property study exists. The one exception to this guidance is in the case of Reid Vapor
Pressure (RVP), where a user should change the value to reflect any specific local
regulatory requirements and differences between ethanol and non-ethanol blended
gasoline not reflected in the default database. Any changes to RVP (or to any other
gasoline formulation parameters) should be made using the "Fuel Wizard" tool accessible
in the Fuel Importer.
66 See EPA's MOVES3 Technical Guidance: Using MOVES to Prepare Emission Inventories for State
Implementation Plans and Transportation Conformity, EPA-420-B-20-052
November 2020, available on EPA's web site at: https://www.epa.gov/state-and-local-
transportation/policv-and-technical-guidance-state-and-local-transportation#emission.
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For additional guidance on defining fuel supply and formulation information, consult
EPA's MOVES Technical Guidance.67
4.5.4 I/M Programs
MOVES does not provide a PM emission benefit from Inspection and Maintenance (I/M)
programs. Therefore, if the modeler includes an I/M program, the selection will have no
impact on PM emissions. However, this importer needs a green check for the MOVES
run to execute. For a PM hot-spot analysis, a modeler can get a green check for this
importer by checking the box labeled "No I/M Program" on this tab.
4.5.5 Retrofit Data
The Retrofit Data Tab in MOVES allows users to enter heavy-duty diesel retrofit and/or
replacement program data that apply adjustments to vehicle emission rates. There are no
default retrofit or replacement data in MOVES. However, users are not required to input
such data into MOVES; they would only do so if they have a retrofit or replacement
program that they want to model. For example, a bus terminal project might include
plans to mitigate emissions by retrofitting or replacing 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 or replacement project using the Retrofit Data
Importer. Please refer to EPA's latest guidance on quantifying emission reductions from
retrofit and replacement programs for conformity purposes.68 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.
4.5.6 Links
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; 100 percent equals a 45-degree slope). 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.
67 The MOVES3 Technical Guidance can be found at: httos ://www. epa. gov/state-and-local-
transportation/policv-and-technical-guidance-state-and-local-transportation#emission.
68 Diesel Retrofit and Replacement Projects: Quantifying and Using Their Emission Benefits in SIPs and
Conformity - Guidance for State and Local Air and Transportation Agencies, EPA-420-B-18-017, March
2018. This guidance can be found on EPA's web site at: https://www.epa.gov/state-and-local-
transportation/policY-and-technical-guidance-state-and-local-transportation#quantifVing.
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This importer also includes a column to add a link description. Descriptions are helpful
to both modelers and reviewers to keep track of what is included in the modeling run.
Note that if the run includes the off-network road type, the Operating Mode Distribution
Importer will not display a green check until the vehicle soak distribution for the off-
network link is entered using the Operating Mode Distribution Importer.
4.5.7 Link Source Types
The Link Source Types Importer allows the user to enter the fraction of the link traffic
volume that is represented by each vehicle type (source type). For each LinkID, the
"SourceTypeHourFractions" must sum to one across all source types. If there is an off-
network link, that LinkID should not be included; instead, information for an off-network
link will need to be included in the Off-Network and Operating Mode Distribution
Importers.69
Additionally, the user needs to ensure that the source types selected in the MOVES
Onroad Vehicles 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 links
being modeled and for each MOVES run, as vehicle mixes may vary by link and 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 example, 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, interstates tend to have a
higher fraction of truck traffic than minor arterial roads. Therefore, the interstate
69 When using MOVES 3.0.0 or 3.0.1, and the only link in a MOVES run is an off-network link, the Link
Source Types Importer will still need a green check. In this case, create a template for the
linkSourceTypeHour table. This will create a file with a row for each source type in the run. Fill in linkID
as 0 for each row, and provide a sourceTypeHourFraction that sums to 1. This distribution will not be used
since there is no linkID 0 defined in the Links importer, but it will provide a green check for this importer.
This workaround is not needed for MOVES3.0.2 or later versions.
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source type distribution used in the regional emissions analysis may be
appropriate to use for an interstate project.
4.5.8 Options for Describing Running Activity (Running and Idling)
This section describes the options for describing running activity: running and idling,
and covers two optional importers, the Link Drive Schedules Importer and Operating
Mode Distribution Importer.
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.
There are several methods that users may employ to generate an operating 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:
1. Provide average speed and road type through the Links Importer:
Using this approach, MOVES will calculate emissions based on a default drive
cycle for a given speed and road type. Input of link drive schedules or operating
mode distributions is not needed under this option. For users modeling a free-
flow link with only basic information on average speed, volume, and grade 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. Additionally, the default drive schedules may be more
appropriate for links on flat terrain.
Average speed is an appropriate input when running MOVES in Inventory mode
to model an idle-only link, using a running link with an average speed of 0. The
result for such a link would be the emissions from the volume vehicles on that
link idling for the entire hour. If vehicles idle for only part of the hour, the link
volume needs to be multiplied by the fraction of idling time, i.e., (minutes of
idling/60 minutes) before being input. For example, if 30 transit buses idle on a
link for 20 minutes of the hour, the volume of this link should be the number of
transit buses (30) multiplied by (20/60), which is a volume of 10.
When running in Emission Rates mode, an idle-only link must be modeled using
an operating mode distribution (see below).
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2. Provide a link drive schedule using the Link Drive Schedules Importer:
The Link Drive Schedules Importer allows the user to define the precise speed
and grade as a function of time (seconds) on each 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).70 If this optional importer is used, MOVES will build an
operating mode distribution from the information in the Link Drive Schedules
table combined with default assumptions regarding vehicle weights and road load
coefficients. This MOVES-calculated operating mode distribution will be used to
calculate link running emissions instead of using the average speed in the Links
table.
Link Drive Schedules are applied to all source types operating on the link. 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;71 or
• Output from traffic microsimulation models.72
If this optional importer is used, MOVES will use these operating mode fractions
for calculating link running emissions instead of creating an operating mode
distribution from the average speed included in the Links table.
70 Note that MOVES does not determine if the vehicle speed trajectory is realistic for assumed vehicle
characteristics and the grade input. Users should ensure that vehicle speeds are realistic and appropriate for
all characteristics of a link, including grade.
71 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.
72 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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When running MOVES in Emission Rates mode, the operating mode distribution
input can be used to model an idle-only link:
• With the Links Importer, specify a running link with an average speed of 1
mph.73
• With the Operating Mode Distribution Importer:
o For all running polProcessIDs (i.e., polProcessIDs with the last two
digits of "01"), input a fraction of:
¦ 1.0 for opModelD 1
¦ 0.0 for opModelDs 0 and 11 through 40
o To account for brakewear, input the following fractions for
polProcessID 11609 (PM2.5) and 10609 (PM10):
¦ 1.0 for opModelD 501
¦ 0.0 for opModelDs 0 through 40
o To account for tirewear, input the following fractions for
polProcessID 11610 (PM2.5) and 10610 (PM10):
¦ 1.0 for opModelD 400
¦ 0.0 for opModelDs 401 through 416
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 choice of whether to
rely on average speed information in the Links Importer, or add more detailed
information through the Link Drive Schedules or Op-Mode Distribution Importers should
be based on the data available to the user. Regardless of which option is used, the inputs
should reflect the latest available vehicle activity and behavior information on each link.
4.5.9 Describing Off-Network Activity (Starting and Hotelling)
Where a project analysis includes areas where vehicles are not driving on the project
links, but are part of the area substantially affected by the project, the user will define this
"off-network" activity in MOVES as well. For example, an off-network link would be
used if the area substantially affected by the project includes a parking area, a bus
terminal, or a freight terminal. 74 Interagency consultation should be used to help identify
appropriate receptor locations in the area substantially affected by the project. (See
Section 7.6 for additional discussion of placing receptors in air quality modeling.)
73 The units for the running emissions process in Rates mode is "mass per distance," and no distance is
traveled while idling. Therefore, an average speed of 1 mph is used to transform the units for an idling link
to "mass per hour."
74 Smaller off-network areas within the project area that are determined to be insignificant through
interagency consultation can be omitted. An example might be an employee parking area.
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Activity at these areas may include:
• vehicles starting, which would be defined through the Off-Network and Operating
Mode Distribution Importers,
• hotelling by long-haul combination trucks, which would be defined through the
Off-Network and Hotelling Importers, and
• vehicles running and idling. Even though the activity is occurring in the same
area as off-network activity, running and idling activity in these areas would be
defined using one or more running links. See Section 4.5.8 above for more
information on how to specify activity on running links.
The methods and assumptions used to derive off-network inputs (including starts,
hotelling activity, and soak-time distributions) should be documented as part of the
analysis, including any adjustments based on data from similar projects.
Off-Network Importer. The Off-Network Importer should be used if the project includes
an area where highway vehicles are parked, starting their engines, or in hotelling mode
(such as at a truck stop, parking lot, or passenger or freight intermodal terminal). The
Off-Network Importer allows only one off-network link to be described per run. If more
than one off-network link is associated with the project, another set of MOVES runs may
be needed to characterize each additional off-network location for each build or no-build
scenario.75
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" (which refers to all hotelling activity rather than only
extended idling):
• The "vehiclePopulation" column reflects the total number of vehicles of each
source type parked on the off-network area over the course of the hour covered by
the MOVES run.76
• The "startFraction" column is the fraction of that total vehicle population that
starts during the hour.
• The "extendedldleFraction" specifies the fraction of time that the vehicle
population spends in hotelling operation in the hour. This column should be zero
for all vehicles other than long-haul combination trucks, because hotelling is an
activity that applies only to long-haul combination trucks. For combination long-
haul trucks (SourceTypelD 62), if a non-zero number is entered, the user would
also complete the Hotelling Importer.
75 Alternatively, if the off-network links are identical in terms of fleet mix and soak times, one off-network
link can be used and the results post-processed so that they can be used to represent parking areas with
different numbers of starts per hour. See the MOVES module of EPA's PM hot-spot training for more
information, available on the web site at: https://www.epa.gov/state-and-local-transportation/proiect-level-
training-quantitative-pm-hot-spot-analvses. Please consult with EPA if your project includes more than
one off-network area.
76 Note that while link volume for the off-network link is required on the Links input, the vehicle
population column of the Off-Network table is what MOVES uses to calculate emissions on this link.
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• The "parkedVehicleFraction" is not required as an input and can be left blank as it
is used for evaporative emissions and does not apply to PM modeling.
Operating Mode Distribution Importer. 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. 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. 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. 77
When a template is created for this importer, operating modes for the running and
braking processes (i.e., opModelDs 0 through 40 and 501) will be present if these
processes are selected in the RunSpec. These operating modes should be deleted unless
the user is supplying detailed operating mode distributions to describe running activity, as
discussed in Section 4.5.8.
Hotelling Importer. Hotelling applies only to long-haul combination trucks (source type
62) and is defined as the operation of the truck in "hotelling" mode, typically at overnight
rest areas. In order to heat and cool the cab, as well as to run appliances, an added energy
load is necessary. This energy is provided from four possible modes, defined in the
Hotelling Importer for each model year:
• Extended idling (OpModelD 200), where the truck engine is operating at a higher
RPM than during normal idling to accommodate the extra load from the
accessories;
• Diesel auxiliary power unit (OpModelD 201), or APU, where a small, separate
diesel engine is used to power accessories;
• Battery power (OpModelD 203), where the engine is off and the accessories are
being run from battery power; and
• Engine-off (OpModelD 204), where accessories are powered by an external
source of electricity available at the truck stop.78
Note that battery power and engine-off both yield zero emissions. Local hotelling
activity for a given project will likely be different than the national defaults. Default
77 When a template is created for this importer, if operating modes other than soak time are present, they
should be deleted. For example, the template may include operating modes for hotelling, but hotelling
operating modes are input through the Hotelling importer. Note that soak time op-mode definitions are
listed in a tab of the spreadsheet. In addition, these definitions can be found on the MOVES Onroad Cheat
Sheet available at:
https://github.com/USEPA/EPA MOVES Model/blob/master/docs/MO VES3CheatsheetOnroad.pdf.
78 More information is available in the Population and Activity of Onroad Vehicles in MOVES3, EPA-420-
R021-012, April 2021, available onEPA's website at: https://www.epa.gov/moves/moves-onroad-
technical-reports#moves3.
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information is available but should be used only in the absence of local information.
Users should look at the default information and decide whether it is consistent with the
expected operating modes in the project's location.
Sources of Information and Documentation. 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. (Again, note that bus
idling at a bus terminal project would be defined with a running link.) 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 number of vehicles
and the distribution of starts throughout the day for a project being analyzed could be
determined by studying a similar parking lot.
The methods and assumptions used to derive off-network inputs (including starts, soak-
time distributions, and hotelling) 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 mode is
selected) or an emission rate (if Emission Rates mode is selected). The emission results
calculated for each pollutant are in the following terms (assuming grams and miles are
selected on the General Output Panel, as described in Section 4.4.8):
• grams/hour for each link in Inventory mode
• grams/vehicle-mile for each link in Emission Rates mode
Regardless of which mode is used, MOVES will produce emission results at the level of
detail selected on the Output Emissions Detail Panel of the RunSpec, as described in
Section 4.4.9. For example, if output by "Emission Process" is selected, MOVES will
produce separate grams/hour or grams/vehicle-mile results for each emission process
modeled.
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However, AERMOD requires a single emissions value for each time unit and link being
modeled. AERMOD uses a gram/time emission factor for each source and for each hour
of the day. AERMOD sources should be mapped to links modeled by MOVES and the
time of day should be mapped based on the time periods analyzed, as described in
Section 4.3. See Section 7 and Appendix J for instructions on running AERMOD for PM
hot-spot analyses.
MOVES includes post-processing scripts that can calculate a single emissions value for
each time unit and link being modeled. After running MOVES, these scripts can be run
on the output database. First, make sure that the correct output database is selected on the
General Output Panel. Then, in the Post Processing menu, select "Run MySQL Script on
Onroad Output Database." In the pop-up window, select the desired script, and click OK.
After reading the next informational dialog that pops up, click OK to run the script. Each
script will produce a table in the output database, with the table name corresponding to
the name of the script. The SQL screen may need to be refreshed to display the new table
created by the script.
• If Inventory mode is used, the following scripts will calculate total emissions in
grams/hour for each MOVES run, year, month, hour, and link in the output
database:
o PM25_Grams_Per_Hour.sql
o PMlOGramsPerHour.sql79
These grams/hour emissions would need to be converted into the appropriate
inputs for AERMOD, such as grams/second (volume source type), or
grams/second/square meter (line/area source type).
• If Emission Rates mode is used, the following scripts will calculate total
emissions in grams/vehicle-mile for each MOVES run, year, month, hour, and
link in the output database:
o PM25_Grams_Per_Veh_Mile.sql
o PM10_Grams_Per_Veh_Mile.sql
These grams/vehicle-mile emissions from MOVES would need to be converted
into the appropriate inputs for AERMOD. Converting these emissions is more
complicated than converting results from Inventory mode, because these rates
must be multiplied by the correct hourly volumes and link lengths first, then
converted to into the appropriate inputs such as grams/second (volume source
type), or grams/second/square meter (line/area source type).
EPA also has a tool, "MOVES2AERMOD," to convert MOVES results done with
Inventory mode into a format that can be included in AERMOD (with the AERMOD
79 See EPA's PM hot-spot training for examples of running scripts - refer to the MOVES module of the
training zip file on EPA's website at: https://www.epa.gov/state-and-local-transportation/proiect-level-
training-quantitative-pm-hot-spot-analvses.
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keyword EMISFACT). The MOVES2AERMOD script can be found on EPA's MOVES
website.80 The ZIP file contains instructions for using the tool.
Section 7 and Appendix J discuss AERMOD in further detail.
80 See EPA's website at: https://www.epa.gOv/moves/tools-develop-or-convert-moves-inputs#emisfact.
The MOVES2AERMOD tool can be used with any number of MOVES runs. MOVES runs represent
emissions at different times. In the MOVES2AERMOD tool, the modeler assigns the runs to the
appropriate hours of the day in all four seasons of the year via the "Traffic Distribution" spreadsheet, one
of the three spreadsheets that modelers need to populate to use the tool.
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Section 5: Estimating Project-Level PM Emissions Using the
EMFAC Model in California
5.1 Introduction
This section of the guidance describes characterizing a project in terms of links and
determining the number of runs necessary when using the EMFAC model. 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 PM10
emission rates for three exhaust emission processes (running, starting, and idle), tire
wear, and brake wear. CARB provides its own documentation for how to use the
EMFAC model at the project scale. Please refer to CARB's web page for this
documentation; note that the latest EPA-approved version of EMFAC would be used for
a PM hot-spot analysis, or the previous version during the conformity grace period.81
EPA notes that the latest state, local, or project-specific assumptions should be used for
conducting PM hot-spot analyses with EMFAC to meet conformity requirements. For
example, a project sponsor should use age distribution assumptions from their SIP or
transportation conformity regional emissions analysis, or other project-specific age
distribution data, if available. Project-specific age distribution data and other significant
data for emissions modeling purposes, such as project-specific rest/soak times for
relevant projects, should be used rather than EMFAC defaults for the county in which the
project is located. If a terminal project is designed to serve a fleet that operates only
locally, such as a drayage yard or bus terminal, the project sponsor should provide
project-specific fleet age distribution data. The interagency consultation process should
be used to determine the use of the latest planning assumptions for projects on a case-by-
case basis.
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 concentrations 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 concentrations for the build scenario are greater than the relevant NAAQS.
81 The Federal Register notice for EPA's most recent approval of the EMFAC model can be found on
EPA's website at: https://www.epa.gov/state-and-local-transportation/policv-and-technical-guidance-state-
and-local-transportation#emission. See footnote 9 (Section 1.6) for CARB reference information.
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5.2 Characterizing a Project in Terms of Links
Prior to using EMFAC, 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 estimate emissions from a specific
type of activity where that activity occurs. 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.
Users of EMFAC should ensure that the latest information about vehicles operating on
the project is used in the emissions modeling.
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.82 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 EMFAC, an average speed and traffic volume is needed for each link.83
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
82 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.
83 Unlike MOVES, EMFAC 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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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
geometry of the intersection, how that geometry affects vehicle activity, and the level of
detail of available activity information.
When using EMFAC, 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. Some resources are available
through FHWA's Travel Model Improvement Program (TMIP).84 Methodologies for
computing intersection control delay are provided in the Highway Capacity Manual.85
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
more unique running links as described in Section 5.2.1, in addition to the other running
links associated with roads of the project. These running link emissions can then be
84 See FHWA's TMIP website: http://tmip.fhwa.dot.gov/.
85 Users should consult the most recent version of the Highway Capacity Manual. See footnote 50 (Section
4.2.1) for reference information.
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aggregated with emissions from starts and idling from non-running activity on the transit
or other terminal link outside of the EMFAC 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 EMFAC Runs
5.3.1 General
Before using EMFAC 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).86 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 EMFAC 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
period, divided by the number of off-peak hours). These 18 hours would be divided into
a midday (MD) and overnight (ON) scenario.
86 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/otaa/stateresources/transconf/policY/420b08901.pdf.
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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 EMFAC runs needed to represent changes in fleet mix depends on what
modeling approach is required to complete the analysis. See CARB's model
documentation for details.
Since PM emission rates do not vary with temperature and humidity in EMFAC, it is not
not necessary to run multiple EMFAC 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 CARB handbook 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 EMFAC
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).
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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 (https://www.epa.gov/air-emissions-factors-and-
quantification/ap-42-compilation-air-emissions-factors) 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
of AP-42, as the methodology and procedures may change over time.87
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.
87 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 PM2.5 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 PM10 Nonattainment and Maintenance Areas
Re-entrained road dust must be included in all PM10 hot-spot analyses. EPA has
historically required road dust emissions to be included in all conformity analyses of
direct PM10 emissions - including hot-spot analyses. See Section 2.5 for further
information.
6.3.3 Using AP-42 for 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.88
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).
6.4 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.
6.4.1 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.
88 This section can be downloaded from EPA's website. See website information in Section 6.2.
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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)).
6.4.2 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.
6.5 Estimating Transportation-Related Construction Dust
6.5.1 Determining Whether Construction Dust Must Be Considered
Construction-related PM2.5 or PM10 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.
6.5.2 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.89 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.
89 This section can be downloaded from EPA's website. See website information in Section 6.2.
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6.5.3 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
equations. In such cases, users may consider alternative methods that are more
appropriate for local conditions.
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. For example, a port could be the source of
additional emissions that would need to be included in air quality modeling. EPA's Port
Emissions Inventory Guidance provides methodologies on how to develop port-related
and goods movement emissions inventories, including emissions of PM.90 This guidance
describes the latest, state-of-the-science methodologies for preparing an emissions
inventory in the following mobile source sectors: ocean-going vessels, harbor craft,
recreational marine, cargo handling equipment, and rail. Note that while the Port
90 EPA, Port Emissions Inventory Guidance: Methodologies for Estimating Port-Related and Goods
Movement Mobile Source Emissions, EPA-420-B-20-046, September 2020, available on EPA's website at:
https://www.epa.gov/state-and-local-transportation/port-emissions-inventorv-guidance.
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Emissions Inventory Guidance also includes sections on estimating emissions from
onroad vehicles and locomotives, Section 4 of the PMHot-Spot Guidance (this guidance)
provides the latest information on estimating PM emissions from onroad vehicles for PM
hot-spot analyses, and Appendix I of the PM Hot-Spot Guidance provides information for
estimating emissions from locomotives for PM hot-spot analyses.
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Section 7: Estimating Project-Level PM Concentrations Using
AERMOD
7.1 Introduction
This section describes the recommended source characterization, data inputs, and
receptor considerations when using AERMOD for PM hot-spot analyses. This guidance
is consistent with the conformity rule and requirements for air quality modeling in EPA's
Guideline on Air Quality Models regulation (Appendix W to 40 CFR Part 51).91
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
modeling. EPA has also included additional details on air quality modeling in Appendix
J of this guidance. The AERMOD model, AERMOD User's Guide, and other supporting
documentation and materials (such as preprocessors and examples) are available through
EPA's Support Center for Regulatory Air Models (SCRAM) website at:
https://www.epa.gov/scram. Project sponsors conducting PM hot-spot analyses will need
to refer to the latest AERMOD User's Guide and other available guidance for complete
instructions.92 EPA's Office of Air Quality Planning and Standards maintains the
SCRAM website and maintains and supports AERMOD on an ongoing basis. Modelers
should regularly check this website to ensure use of the latest regulatory version. In
addition, there is helpful information on EPA's project-level conformity and hot-spot
analysis page, including information about air quality modeling:
https://www.epa.gov/state-and-local-transportation/proiect-level-conformitv-and-hot-
spot-analyses.
7.2 General Overview of Air Quality Modeling
Air quality modeling 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 concentrations and
comparison to the NAAQS (see Section 9).
91 See footnote 18 (Section 2.4.1) for Appendix W reference information.
92 For AERMOD-related documentation, see EPA's website at: https://www.epa.gov/scram/air-aualitv-
dispersion-modeling-preferred-and-recommended-models#aermod.
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Exhibit 7-1. Overview and Data Flow for Air Quality Modeling with AERMOD
Modeling sequence
Action
CD
Results previously
calculated
— — *•
|^J Document
re
External data
Model inputs
*
If applicable
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7.3 Using AERMOD
7.3.1 AERMOD Is EPA's Dispersion Model for Transportation Projects
PM hot-spot analyses should be developed consistent with EPA's current recommended
model under Appendix W to 40 CFR Part 51,93
The American Meteorological Society/EPA Regulatory Model (AERMOD) is EPA's
required near-field dispersion model for many regulatory applications. EPA first
recommended AERMOD in a November 9, 2005 final rule, Guideline on Air Quality
Models, that amended EPA's Appendix W regulation after more than ten years of
development and peer review that resulted in substantial improvements and
enhancements.
In the 2017 update to Appendix W, EPA removed the CALINE3 model from the
regulations, making AERMOD the only model for refined modeling for mobile source
applications such as PM hot-spot analyses.94 The three-year transition period set forth in
that final rule for the use of CALINE3-based models has now transpired. Therefore, as
of January 2020, all PM hot-spot analyses must use AERMOD for air quality modeling
(see Appendix W to part 51, Section 4.2.3.5 "Models for PM2.5" and Section 4.2.3.6,
"Models for PM10").
AERMOD includes options for modeling emissions from line/area, volume, and point
sources and can therefore model the impacts of many different source types, including
highway and transit projects. AERMOD is 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.
7.3.2 How Emissions Are Represented in AERMOD
AERMOD simulates how pollutants disperse in the atmosphere. To do so, the model
classifies emission sources within a project as line, area, volume, or point sources:
• Line sources are generally linear emission sources, which can include highways,
intersections, and rail lines. A highway "line source" can be modeled using a
series of adjacent line/area sources (see the AERMOD User Guide and the
AERMOD Implementation Guide for suggestions).95
• Volume sources are three-dimensional spaces from which emissions originate
(e.g., areas designated for truck or bus queuing or idling that correspond to off-
network links in MOVES, driveways and pass-throughs in bus terminals, and
locomotive activity at commuter rail or freight rail terminals).96 A highway "line
source" can be modeled using a series of adjacent volume sources.
93 See footnote 18 (Section 2.4.1) for Appendix W reference information.
94 Note that while CAL3QHCR can no longer be used for PM hot-spot analyses, CAL3QHC can still be
used for CO screening analyses. See 82 FR 5190 and 5192, January 17, 2017.
95 The latest versions of these documents are available on EPA's website; see footnote 92 (Section 7.1).
96 See Appendix I for information on estimating locomotive emissions.
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• Point source emissions 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 a series of adjoining
line/area or volume sources in AERMOD. 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.
The latest version of AERMOD now also includes two additional source types to
represent line sources: "RLINE" and "RLINEXT" (for RLINE-extended). RLINE is a
Beta feature, meaning its use requires alternative model approval (see Section 7.3.3), and
RLINEXT is an Alpha feature, meaning it is for research purposes only.97
When modeling highway and intersection sources using AERMOD, experience in the
field has shown that area sources may be easier to characterize correctly compared to
volume sources, and have a shorter run time.98
It is helpful for modelers to consider in advance which source type to use for a project in
advance of the modeling, since source characterization inputs vary by source type. For
example, a modeling protocol can be useful in this process of thinking through the
project's elements and the options for how it can best be modeled. Such a protocol can
also be useful to get input from other agencies involved in the interagency consultation
process (required in the transportation conformity regulation, 40 CFR 93.105 and
93.112), before modeling is begun, ultimately saving time in the process. When project
sponsors use a modeling protocol, it does not prohibit a change in modeling approach.
Appendix J includes important additional information about configuring AERMOD when
using it to complete PM hot-spot analyses.
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 the Appendix W regulation, "Selection of the best techniques
for each individual air quality analysis is always encouraged, but the selection should be
97 For more information, seeEPA's Guidance on New R-LINE Additions to AERMOD 19191 for Refined
Transportation Project Analyses, EPA-420-B-19-042, September 2019, available onEPA's website at
https://www.epa.gov/state-and-local-transportation/proiect-level-conformitv-and-hot-spot-
analvses#dispersionmodel.
98 For additional information on issues related to applying volume sources, see EPA's presentation, "PM
Hot-spot Modeling: Lessons Learned in the Field":
http://www3.epa.gOv/otaa/stateresources/transconf/proiectlevel-hotspot.htm#training.
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done in a consistent manner."99 This section of the Appendix W regulation 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
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 guide for AERMOD for specific
information about how physical characteristics and location of sources are included in the
model.
99 See footnote 18 (Section 2.4.1) for Appendix W reference information.
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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.100 Consult
Appendix J for guidance on when to include building downwash for these projects.
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 EMF AC-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.
AERMOD accepts emission rates in grams/time. When employing line/area sources with
AERMOD (e.g., roads or 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.101 Sections 4 and 5 describe how to account
for different periods of the day in emissions modeling with MOVES and EMF AC. This
approach is then applied to air quality modeling to estimate air quality concentrations
throughout a day and year.
Section 4 and Appendix J describe how results from MOVES and EMF AC should be
prepared for use as inputs in AERMOD.
7.5 Incorporating Meteorological Data
7.5.1 Finding Representative Me teorological 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 AERMOD 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 the AERMOD user and
implementation guides. EPA's SCRAM web site also contains additional information,
100 Building downwash occurs when air moving over a building mixes to the ground on the downwind side
of the building.
101 The timing of emissions in AERMOD is described in Section 3.3.6 of the AERMOD User Guide.
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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.102 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.
AERMOD can include variations in emissions (e.g., by season and hour) and multiple
years of meteorological data using a single input file and run. See further information in
Section 7.5.3.
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 determine appropriate meteorological data inputs for AERMOD, EPA maintains the
meteorological processing software called AERMET on the SCRAM website.103
AERMET produces input data files that AERMOD reads to produce calculations of
atmospheric dispersion. The AERMET user guide should be consulted for specific
instructions.
The meteorological data used as an input to AERMOD should be selected on the basis of
geographic and climatologic representativeness and how well measurements at one site
102 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).
103 These programs and their user guides may be downloaded from the SCRAM website at:
https://www.epa.gOv/scram/meteorological-processors-and-accessorv-programs#aermet.
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represent the likely transport and dispersion conditions in the area around the project.
The most important attribute for these data is representativeness, although more recent
meteorological data are generally preferred over older data. For example, older data from
a representative meteorological data site may be better than newer data from a site that is
not representative. 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.104
Modelers should consult the most recent version of the AERMOD Implementation Guide
for assistance in obtaining and handling meteorological information.
7.5.2 Surface and Upper A ir Data
Surface Data
AERMOD needs representative meteorological data from a near-ground surface weather
monitoring station ("surface data"). 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).
For details, refer to the AERMET user guide on the SCRAM website.105
Upper Air Data
Upper air soundings measure vertical gradients of temperature in the atmosphere, which
are used by air quality models to calculate convective mixing heights. AERMOD needs
upper air sounding data from a representative measurement site; consult the AERMOD
Implementation Guide for specific recommendations.
104 See footnote 92 (Section 7.1).
105 See https://www.epa.gOv/scram/meteorological-processors-and-accessorv-programs#aermet.
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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 Federal Aviation Administration,
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.106
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.107 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 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. When using five years of off-site meteorological
data, it is recommended that a single, five-year meteorological data set be developed (and
run in one AERMOD run) to allow for simpler post-processing and design concentration
calculation. See Section 9 for more details.
106 See Section 8.3.3 in Appendix W to 40 CFR Part 51 ("Site Specific Data") (see footnote 18 in Section
2.4.1 of this guidance for Appendix W reference information) and the Meteorological Monitoring
Guidance for Regulatory Modeling Applications (https://www.epa.gov/scram/air-modeling-meteorological-
guidance). Other meteorological guidance documents are also available through SCRAM, including
procedures for addressing missing data and for quality assuring meteorological measurements.
107 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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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 AERMOD and AERMET:
• 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 (Bo), which indicates how much heat the ground imparts to the air,
instead of evaporating moisture at the surface.
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. 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.108 As of the writing of this guidance, the
latest version of the NLCD was for 2019. Consult the AERMOD Implementation Guide
for recommendations for using NLCD data when processing meteorological data.109
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 should be characterized at different heights. See
Appendix J for information on handling complex terrain in air quality modeling.
108 This database can be accessed at: https ://www.mrlc. gov/.
109 The AERSURFACE model, a non-regulatory component of AERMOD, may also be used to generate
information on surface roughness, albedo, and Bowen ratio. The latest version of AERSURFACE may be
accessed via SCRAM (https://www.epa.gov/scram/air-aualitv-dispersion-modeling-related-model-support-
programs#aersurface').
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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."110 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
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.111
AERMOD can account for the urban/rural differences in dispersion. Modeling sources as
urban or rural in AERMOD can have a large impact on predicted concentrations. 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.
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. Refer also to Appendix J for additional information
on how to handle this data.
110 Thq Meteorological Processor for Regulatory Models (MPRM) User's Guide, EPA-454-B-96-002,
August 1996, refers to the "urban heat island effect" as "anthropogenic heat flux."
111 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. See footnote 18 (Section
2.4.1) for Appendix W reference information.
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7.6 Placing Receptors112
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)(1) 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.113
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.
7.6.2 General Guidance for Receptors for All PM NAAQS
Section 7.2.2 of Appendix W 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.114 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. Receptors should be placed in areas that are considered
ambient air (i.e., where the public generally has access). Examples of areas where
receptors should not be placed include 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.
112 Section 7.6 reflects EPA's 2012 PM NAAQS final rule that was published on January 15, 2013 (78 FR
3264).
113 CAA section 176(c)(1)(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.
114 See footnote 18 (Section 2.4.1) for Appendix W reference information.
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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. 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. Note that interagency consultation should be used to
help identify the appropriate receptor locations in the area substantially affected by the
project. Some examples where maximum concentrations may not be located closest to
the project itself include:
• a highway project that adds additional traffic and creates maximum
concentrations along an intersecting arterial that is not being modified by the
project;
• a highway project that consists of a new bypass that branches off an existing
highway with significant emissions where maximum concentrations may be
expected at receptors farther from the project, but closer to the existing highway;
and
• a highway project that influences emissions of a nearby source, such as a highway
that provides access to a port. Because the highway expansion means that
emissions at the port can increase, the maximum concentration could be at the
port instead of the highway.
These types of effects should be considered when determining which areas are to be
modeled and where receptors should be placed.
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.115 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 concentrations 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
115 See 40 CFR Part 58, Appendix D, Section 4.7.1(c)(1); 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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project area, depending on the spatial extent of the project and the impacts of other
modeled sources.
Receptors should be placed with finer spacing (e.g., 25 meters) closer to a near ground
source to cover a distance of at least 100 meters from the project. Given the closest set of
receptors would usually be five meters from the source, five rows of receptors around the
project, covering a distance from five meters away from the project to 105 meters away
from the project at 25-meter intervals, would be sufficient for most projects. These rows
would not be straight lines, but instead would follow the boundaries of the project area.
In these rows, receptors should be placed 25 meters apart. In most cases, placing
receptors in five rows around the project as described would ensure that the area of
highest concentrations is captured.
However, additional receptors may be needed for some projects. Some examples of
when additional receptors will be necessary include those projects where a project area
includes one or more nearby sources that need to be included in the modeling, where
mobile sources will be modeled at elevations above ground level such that the emissions
would have a maximum impact more than 5 m from the edge of the roadway (e.g., an
overpass or bridge), or where other structures or barriers such as noise walls are present.
Receptors may also be important where there are communities with environmental justice
concerns located in the project area. For example, if there are such communities in the
project area, receptors in these communities would be important for understanding the
project's effects on these residents.
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. The area's
interagency consultation procedures must be used to determine the models and associated
methods and assumptions for a PM hot-spot analysis, including receptor placement.
Receptor placement should be discussed in the process established by the area's
interagency consultation procedures before the modeling is done. An adequate number
and placement of receptors is necessary to identify maximum concentrations in
communities in the area substantially affected by the project, including minority, low
income, and indigenous populations.
For PM hot-spot analyses of transportation projects, 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 multiple heights above
ground level 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 concentrations 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
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information regarding calculating design concentrations in a build/no-build analysis and
appropriate receptors.
7.7 Running the Model and Obtaining Results
After preparing all model inputs, AERMOD 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 concentrations, as described in
Section 9.
For PMio, PM2.5 annual NAAQS, and most PM2.5 24-hr NAAQS analyses, AERMOD
will produce a single value at each receptor that is appropriate to add directly to a single
monitored value. See Sections 8 and 9 for information on this process.
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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)(1) 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 itself.116 EPA's Appendix W regulation provides the appropriate framework for
defining the elements of background concentrations, as opposed to modeled
concentrations from the project. Section 8.3.1 of Appendix W states that "background
concentrations are an essential part of the total air quality concentration to be considered
in determining source impacts."117 Thus, 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 when they are not appropriately reflected in the background data or
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.
Concentrations are expected to vary throughout a PM nonattainment or maintenance area,
resulting from differences in emission sources, meteorology, terrain, and other factors.
Section 93.123(c)(1) requirements for PM hot-spot analyses are met differently from how
these requirements have historically been met 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.
116 See Sections 4 through 6 for more information on how to estimate project emissions.
117 Section 8.3.3 of Appendix W recommends for "multi-source areas" that "two components of
background should be determined: contributions from nearby sources and contributions from other
sources." See footnote 18 (Section 2.4.1 of this guidance) for Appendix W reference information.
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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
93.105(c)(l)(i)).
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.118 In general, nearby sources need to be included in air quality modeling when
those sources are not appropriately reflected in the background data or 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?
118 Section 8.3.3 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." See footnote 18 (Section 2.4.1 of this guidance) for
Appendix W reference information.
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o Are emissions from any nearby sources expected to differ between the
build and no-build scenarios as a result of the project?
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, AERMOD should be used to model the project as well as
any nearby sources that need to be included in the PM hot-spot analysis. 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. Tables 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 PM10 NAAQS, it is also
important to consider Section 8.3.3 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.
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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.119 There are
several options provided below that meet the requirements of Section 93.123(c)(1) 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
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 PM2.5 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 PM2.5 and PM10 concentrations that may be appropriate for
estimating background concentrations.120 Project sponsors, relevant state or local air
agencies, and the EPA Regional Office should identify the appropriate PM10 and PM2.5
monitoring data, along with information on each monitor's site location, purpose,
geographic scale, nearby land uses, and sampling frequency. Monitoring data can be
obtained from EPA's Air Data web site, which includes an interactive map of air quality
monitors 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).121
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).122
119 Section 8.3.3 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)...". See footnote 18 (Section 2.4.1 of this guidance) for Appendix W reference information.
120 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.
121 Available online at: https://www.epa.gov/outdoor-air-qualitv-data.
122 See also EPA's guidance, Additional Methods, Determinations, and Analyses to Modify Air Quality
Data Beyond Exceptional Events, EPA-457-B-19-002, April 2019, for additional information about when
air quality data may be excluded or adjusted.
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Using a Single Monitor
Background concentration data should be as representative as possible for the project area
examined by the PM hot-spot analysis.123 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:
• 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.124 Preference should be given to upwind monitors for this factor,
whenever appropriate.
123 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.
124
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.
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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
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
15 miles from the site, respectively, the weighting of data from monitor A:
If concentrations at A, B, and C are 10.0, 20.0, and 30.0 |ag/m\ 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
EPA's SCRAM website contains two programs for calculating wind statistics and wind roses, WINDROSE
and WRPLOT.
The weighting for monitor B:
The weighting for monitor C:
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inverse-squared distance weighting that weights monitors based on how close they are to
the project (1/distance squared).
Other, more advanced statistical methods to interpolate monitoring data may also be
used, but these require significant geostatistical expertise.125
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.126 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). Note that this method applies in areas
that have appropriate photochemical modeling outputs available. In most cases,
photochemical modeling is only available to estimate PM2.5 concentrations, however,
there may be limited cases where PM10 information is also available.
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
125 EPA's MATS (https://www.epa.gov/scram/photochemical-modeling-tools') and BenMAP
(https://www.epa.gov/benmap') models incorporate another interpolation-based approach (Voronoi
Neighbor Averaging). Consult those models' documentation for further information.
126 Examples of commonly employed CTMs are shown on the SCRAM website at:
https://www.epa.gov/scram/photochemical-air-qualitv-modeling.
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concentrations.127 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 Modeling Guidance for Demonstrating Attainment of Air Quality
Goals for Ozone, PM2.5, and Regional Haze,128 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)). Consult the appropriate EPA Regional Office to determine if such data
are available (see Section 1.7). 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 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.129 An RRF is generally calculated as:
Concentrations in future year, predicted by CTM
/v/vi —
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:
127 Many CTM applications are post-processed with EPA's MATS program available at:
https://www.epa.gov/scram/photochemical-modeling-tools. 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.
128 EP A, Modeling Guidance for Demonstrating Attainment of Air Quality Goals for Ozone, PM2.5, and
Regional Haze, EPA-454-R-18-009, 2018, found on EPA's web site at:
https://www.epa.gov/sites/production/files/2020-10/documents/o3-pm-rh-modeling guidance-2018.pdf.
129 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.
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• The CTM has demonstrated acceptable performance for the project area using
standard indicators of model performance.130
• 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).
• 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 2020, and the PM hot-spot analysis year is 2030,
then the 2020 background estimate could be used for 2030. A project sponsor could not
make a further adjustment based on an extrapolation to the year 2030; 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)(1)
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:
Differencereceptori Concentrationrecep(-or j()Uji(jScenarj0 Concentrationrecep(-orjno_i)Uji(jScenarj0
130 Details on model performance evaluation and examples of model evaluation statistics may be found in
Modeling Guidance for Demonstrating Attainment of Air Quality Goals for Ozone, PM2.5, and Regional
Haze, see reference information in footnote 128 above.
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The result - the difference between the build and no-build scenarios at each receptor -
should be added to background concentrations when calculating design concentrations 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 should be used in calculating design concentrations. 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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Section 9: Calculating PM Design Concentrations and
Determining Conformity
9.1 Introduction
This section describes how to combine all previous steps of a PM hot-spot analysis into a
design concentration so that a project sponsor can determine if conformity requirements
are met. For conformity purposes, a design concentration is a statistic that describes a
future air quality concentration in the project area that can be compared to a particular
NAAQS.131 In general, design concentrations 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 Concentrations for PM Hot-Spot
Analyses
131 Design values based on monitoring data are used to determine the air quality status of a given
nonattaimnent or maintenance area (40 CFR Part 50). Design values are also used for SIP modeling and
other air quality planning purposes.
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This section describes how to calculate the specific statistical form of design
concentrations for each PM NAAQS and how to apply design concentrations 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 and with how design
concentrations are calculated for stationary sources for NAAQS compliance
demonstrations. This guidance is written for current and future PM2.5 and PM10 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 concentrations 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 Concentrations in Build/No-Build Analyses
Design concentrations 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 or any required interim emission reductions or
other milestones as compared to the no-build scenario (40 CFR 93.116(a) and
93.123(c)(1)).
Exhibit 9-2 (following page) illustrates the build/no-build analysis approach suggested in
Section 2.4.
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Exhibit 9-2. General Process for Using Design Concentrations in Build/No-build
Analyses
In general, project sponsors could begin by determining the design concentration 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 concentration 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 concentrations at all receptors
in the build scenario and also model the no-build scenario. Design concentrations should
then be calculated for the no-build scenario at all receptors with design concentrations
that exceeded the NAAQS in the build scenario. Conformity requirements are met if the
design concentration for every appropriate receptor in the build scenario is less than or
equal to the same receptor in the no-build scenario.132 If not, then the project does not
132 This would be the receptor at the same geographic location in the build and no-build scenarios.
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meet conformity requirements without further mitigation or control measures to address
air quality concentrations at such receptors, except in certain cases described below.133
A build/no-build analysis is typically based on design concentration 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 concentrations 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
concentrations calculated at receptors under each scenario. Also, design concentrations
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 the calculations. That is,
conformity requirements would be met at a receptor if the final build design
concentration is less than or equal to the final no-build design concentration, even if the
pre-rounding build scenario results are greater than the pre-rounding no-build design
concentration. 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.
133 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 concentrations calculated to ensure that conformity requirements are met. See
40 CFR 93.123(c)(4) and 93.125 for more information about including mitigation and control measures in a
hot-spot analysis.
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9.3 Calculating Design Concentrations 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
and design concentrations are calculated for air quality monitoring and other EPA
regulatory programs.134
Further details are included below about how design concentrations should be calculated
at receptors for build/no-build analyses, and examples of each design concentration
calculation can be found in Appendix K of this guidance. These details and examples are
primarily narrative in nature.
EPA recognizes that there may be local phenomena that affect background concentrations
and emissions that may call for alternative considerations for determining design
concentrations (see Section 8.3 of Appendix W for combining background concentrations
with modeling data).135 More advanced methods of calculating a PMNAAQS design
concentration, 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 PMNAAQS design concentrations
must be evaluated and chosen through the process established by each area's interagency
consultation procedures (40 CFR 93.105(c)(l)(i)).
9.3.2 Annual PM2.5 NAAQS
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.136
This NAAQS is met when the three-year average concentration is less than or equal to
the annual PM2.5 NAAQS (the primary standard for this NAAQS is 12.0 |j,g/m3):137
Annual PM2.5 design value = ([Yl] average + [Y2] average + [Y3] average) ^ 3
134 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.
135 See footnote 18 (Section 2.4.1) for Appendix W reference information.
136 The design value for the annual PM2 5 NAAQS is defined for air quality monitoring purposes in 40 CFR
Part 50.13.
137 In December 2012, EPA promulgated a revised annual primary PM2 5 NAAQS of 12.0 |ig/m\ Note that
there are still some areas designated nonattainment for the 1997 annual PM2 5 NAAQS (15.0 |ig/m3). which
is revoked as areas attain it.
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Where:
[Yl] = Average annual PM2.5 concentration for the first year of air quality
monitoring data
[Y2] = Average annual PM2.5 concentration for the second year of air quality
monitoring data
[Y3] = Average annual PM2.5 concentration for the third year of air quality
monitoring data
The annual PM2.5 NAAQS is rounded to the nearest tenth of a |ag/m3. For example,
12.049 rounds to 12.0, and 12.050 rounds to 12.1.138 These rounding conventions should
be followed when calculating design concentrations for this NAAQS.
Necessary Data
This design concentration 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.139
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 concentration 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).140
Calculating Design Concentrations and Determining Conformity
Exhibit 9-3 (following page) illustrates how a design concentration 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 concentrations would be calculated at all
receptors in the build scenario. For any receptors with design concentrations above the
NAAQS in the build scenario, the project sponsor would then model the no-build
scenario and calculate design concentrations to determine if conformity requirements are
met.
138 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.
139 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.
140 The interagency consultation process should be used when situations require incorporation of any CTM
results into design value calculations.
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An example of how to calculate design concentrations for the annual PM2.5 NAAQS
using this procedure is included 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:
Exhibit 9-3. Determining Conformity to the Annual PM2.5 NAAQS
Build Scenario <= NAAQS
1. Identify receptor
with the highest
average annual
concentration
2. Calculate average
annual background
concentration
3. Add values from
Steps 1 and 2
4. Round to nearest 0.1
Hg/m3
Is design
concentration
less than or
equal to
NAAQS?
Yes
Project
conforms
Build Scenario <= No-build Scenario
5. For all receptors,
add average annual
concentration from
AERMOD to the value
in Step 2
Are build design
concentrations
less than or
equal to no-
build?*
No
6. Round to nearest 0.1
(ig/'m3 and identify all
receptors that exceed
NAAQS
7. For these receptors,
calculate annual
averages for the no-
build scenario
. Add values from
Steps 7 and 2
9. Round to nearest 0.1
Hg/m3
Project does not
conform
Consider
measures to
reduce emissions
and redo analysis
* May need to also determine appropriateness of receptors
* Mitigation and control measures can be considered
at any point in the process
• Step 1. Identify the receptor with the highest modeled average annual
concentration from the AERMOD output.
• Step 2. Obtain or calculate the average annual background concentration for the
most recent three years. One way of accomplishing Step 2 is to use the average
annual background concentration already calculated by EPA for the appropriate
background monitor.141 However, if data are to be excluded, this concentration
will need to be calculated as follows: For each year of background data, first
141 See the interactive map at EPA's website, https://www.epa.gov/outdoor-air-qualitv-data/interactive-
map-air-qualitv-monitors. Using the interactive map, select the layer "PM2.5 Active" and zoom in on the
area, and click the monitor on the map. From there, download the monitor report spreadsheet file. The
data can be found on the tab labeled, "Table 6a. Site-Level Design Value History for the 2012 Annual
PM2.5 NAAQS."
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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.
• Step 3. Add the average annual background concentration (from Step 2) to the
average annual modeled concentration at the highest receptor (from Step 1) to
determine the total average annual background concentration at this receptor.
• Step 4. Round to the nearest 0.1 |j,g/m3. This result is the annual PM2.5 design
concentration at the highest receptor in the build scenario.
The project sponsor should then compare the design concentration from Step 4 to the
annual PM2.5 NAAQS (currently 12.0 |j,g/m3). If the value is less than or equal to the
NAAQS, the project conforms. If the design concentration is greater than the NAAQS,
the project sponsor should then continue to Step 5:
• Step 5. For all receptors, add the average annual modeled concentrations from
AERMOD to the average annual background concentrations (from Step 2).142
The result will be the total average annual concentration at each receptor in the
build scenario.
• Step 6. Round to the nearest 0.1 |j,g/m3. At each receptor, this value is the annual
PM2.5 design concentration for the build scenario. Identify all receptors that
exceed the annual PM2.5 NAAQS.
• Step 7. From the no-build air quality modeling results, calculate the average
annual concentrations at each receptor identified in Step 6.
• Step 8. For the no-build scenario, add the average annual modeled concentrations
for the no-build scenario (from Step 7) to the average annual background
concentrations (from Step 2). The result will be the total average annual
concentration for each receptor identified in Step 6 under the no-build scenario.
• Step 9. Round to the nearest 0.1 |j,g/m3. This result is the annual PM2.5 design
concentration for each receptor identified in Step 6 under the no-build scenario.
For each receptor with a design concentration that exceeded the NAAQS in the build
scenario, compare the build design concentration (Step 6) to the no-build design
concentration (Step 9). For the project to conform, the build design concentration must
be less than or equal to the no-build design concentration at each receptor in the build
scenario that exceeded the NAAQS (Step 6). 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).143
142 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.
143 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
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If a build scenario design concentration is greater than the no-build design concentration
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 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 PM2.5 NAAQS
Design Value
The 24-hour PM2.5 design value is currently defined as the average of three consecutive
years' 98th percentile concentrations of 24-hour values for each of those years.144 The
NAAQS is met when that three-year average concentration is less than or equal to the
currently applicable 24-hour PM2.5 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).145
The design value for comparison to any 24-hour PM2.5 NAAQS is rounded to the nearest
1 ng/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 |ag/m\ while 35.500 rounds to 36.146 These rounding conventions should be
followed when calculating design values for this NAAQS.
There are two analysis options, or tiers, that are available to project sponsors to estimate a
24-hour PM2.5 design concentration.147 Project sponsors should begin with the first tier
approach as it requires significantly less post-processing than the second tier. However,
if through interagency consultation, it is determined that the impacts from the project's
PM2.5 emissions are highest in one season, and are not temporally correlated with
background PM2.5 levels that are highest during a different season, combining modeled
and monitored contributions through a first tier approach may potentially be overly
conservative. In such cases a second tier approach may be used, as described in Appendix
L.
and use the interagency consultation process to determine whether a "new" violation has been relocated
(see Section 9.2).
144 The design value for the 24-hour PM2 5 NAAQS is defined for air quality monitoring purposes in 40
CFRPart 50.13.
145 There are only two areas where conformity currently applies for both the 1997 and 2006 24-hour PM2 5
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.
146 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.
147 This approach is consistent with EPA's approach for calculating design values for other EPA regulatory
programs. See EPA's Guidance for PM2.5 Permit Modeling, EPA 454-B-14-001, 2014, available at
https://www.epa.gov/scram/clean-air-act-permit-modeling-guidance.
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Under either tier, the contributions from the project, any nearby sources, and background
concentrations from other sources are combined for a given analysis year. The first tier
approach is described further below.
An example of how to calculate design concentrations for the 24-hour PM2.5NAAQS
using a first tier approach is included in Appendix K.
Necessary Data
This design concentration calculation assumes the project sponsor already has the
following data in hand:
• Air quality modeling results: For each receptor, the 98th percentile 24-hour
concentration in each year, averaged across the five years of meteorological data,
from the project and any nearby sources. 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).148
Calculating Design Concentrations and Determining Conformity
The first tier approach consists of directly adding the five-year average 98th percentile
modeled 24-hour concentrations to the three-year average 98th percentile 24-hour
background concentrations.
Exhibit 9-4 (following page) illustrates how a design concentration would be calculated
under a first tier approach for a given receptor. The steps shown in Exhibit 9-4 are
described in detail below.
148 The interagency consultation process should be used when situations require incorporation of any CTM
results into design value calculations.
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Exhibit 9-4. Determining Conformity to the 24-hour PM2.5 NAAQS Using First Tier
Approach
Project conforms
/ Is design
/ concentration
4 ( less than or
\ equal to
\ NAAQS?
Conduct no-build
analysis and/or
second tier
analysis
The initial step in a first tier approach 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 98th percentile 24-hour concentration.
AERMOD reports this directly in the output.
• Step 2. Obtain or calculate the 98th percentile 24-hour background concentration
for the most recent three years. One way of accomplishing Step 2 is to use the
concentration already calculated by EPA for the appropriate background
monitor.149 However, if data are to be excluded, this concentration will need to
be calculated. To calculate the 98th percentile background concentrations for each
year of monitoring data, first count the number of 24-hour background
149 See the interactive map at EPA's website, https://www.epa.gov/outdoor-air-qualitv-data/interactive-
map-air-qualitv-monitors. Using the interactive map, select the layer "PM2.5 Active" and zoom in on the
area, and click the monitor on the map. From there, download the monitor report spreadsheet file. The
data can be found on the tab labeled, "Table 5b. Site-Level Design Values for the 2006 24-hour PM2.5
NAAQS."
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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 below to determine which of these eight values is
the 98th percentile value. Using the results from the three years of monitoring
data, calculate the three-year average of the 98th percentile concentrations.
• Step 3. Add the average 98th percentile 24-hour modeled concentration (Step 1)
to the average 98th percentile 24-hour background concentration (Step 2) and
round to the nearest 1 |ag/m\ The result is the 24-hour PM2.5 design
concentration at the highest receptor in the build scenario.
Exhibit 9-5. Ranking of 98th Percentile Background Concentration Values150
Number of
Rank of Value
Background
Corresponding to
Concentration
98th Percentile
Values
Concentration
1-50
1
51-100
2
101-150
3
151-200
4
201-250
5
251-300
6
301-350
7
351-366
8
If the design concentration 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 approach for the no-build scenario at all receptors that
exceeded the NAAQS in the build scenario. If the calculated design
concentration for the build scenario is less than or equal to the design
concentration for the no-build scenario at all of these receptors, then the project
conforms;151 or
• Conduct a second tier approach as described in Appendix L.
150 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.
151 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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9.3.4 24-hour PMioNAAQS
Design Value
Compliance with the 24-hour PMio 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.152 Currently, the NAAQS is met when the expected number of exceedances is less
than or equal to 1.0.153
The 24-hour PMio NAAQS design value is rounded to the nearest 10 |j,g/m3. For
example, 155.000 rounds to 160, and 154.999 rounds to 150.154 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 concentrations for the 24-hour PMioNAAQS are
included in Appendix K.
Necessary Data
This design concentration 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.155 In this case, the sixth-highest 24-hour modeled
concentration should be calculated for each receptor.156 AERMOD can be
configured to produce these values directly. 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
152 The 24-hour PMio NAAQS and supporting technical documentation can be found in 40 CFR Part 50.6.
153 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 PMio NAAQS is the next highest observed (monitored or modeled)
concentration after the concentrations that could be above 150 |ig/m3 without causing the expected number
of exceedances to be greater than 1.0.
154 This is the rounding convention at Appendix K to 40 CFR Part 50. 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.
Monitoring values typically are reported with only one decimal place.
155 Section 7.5.3 of this guidance provides further information on the number of years of meteorological
data used in air quality modeling.
156 See description in Section 7.2.1.1 of Appendix W. Users with one year of site-specific meteorological
data should select the 2nd highest 24-hour PMio concentration. If using less than one year of meteorological
data (such as one quarter), users should select the highest 24-hour concentration. See footnote 18 (Section
2.4.1 of this guidance) for Appendix W reference information.
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concentrations that meet all applicable monitoring requirements (such as data
completeness).157
Calculating Design Concentrations and Determining Conformity
The 24-hour PMio design concentration is calculated at each receptor by directly adding
the sixth-highest modeled 24-hour concentrations (if using five years of meteorological
data) to the appropriate monitor value for the 24-hour background concentration from
three years of monitoring data, based on Exhibit 9-6.158
Exhibit 9-6: Monitor Value Used for Design Concentration Calculation
Number of Background
Concentration Values from
the Monitor
Monitor Value Used for
Design Concentration
Calculation
<347
Highest Monitor Value
348 - 695
Second Highest Value
696 - 1042
Third Highest Value
1043 - 1096
Fourth Highest Value
For example, if the sampling frequency of the monitor was every day and there are 15
days where the monitor did not sample, there would be 1080 background concentration
values (3 years x 365 days - 15 = 1080). In this case, the design concentration would be
calculated by adding the sixth highest modeled concentration to the fourth highest
monitored concentration.
Exhibit 9-7 (following page) illustrates how a design concentration would be calculated.
The steps shown in Exhibit 9-7 are described in detail below.
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). AERMOD can be configured to produce
these values.159
• 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
at Rank 6) across receptors and identify the receptor with the highest value at
Rank 6.
157 The interagency consultation process should be used when situations require incorporation of any CTM
results into design value calculations.
158 Exhibit 9-6 is adapted from EPA's PMw SIP Development Guideline, EPA-450/2-86-001, June 1987,
Table 6-1, "Tabular Estimation of PMio Design Concentrations," p. 6-5, and is based on the form of the
PMio design value that allows one exceedance per year.
159 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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• Step 3. Identify the appropriate 24-hour background concentration from the three
most recent years of air quality monitoring data based on Exhibit 9-6.160
• Step 4. For the receptor identified in Step 2, add the sixth-highest 24-hour
modeled concentration to the appropriate 24-hour background concentration
(from Step 3).
• Step 5. Round to the nearest 10 |j,g/m3. The result is the highest 24-hour PMio
design concentration in the build scenario.
Exhibit 9-7. Determining Conformity to the 24-hour PMioNAAQS
Build Scenario <= NAAQS
1. Identify the sixth
highest 24-hour
concentration at each
receptor
2. Identify the receptor
with the highest sixth-
highest concentration
3. Identify the
appropriate monitor
value (e.g., fourth
highest) 24-hour
background
concentration
4. Add values from
Steps 2 and 3
5. Round to nearest 10
Hg/m3
Is design
concentration
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
Hg/m3 and identify all
receptors that exceed
NAAQS
8. From no-build
modeling results,
identify sixth-highest
concentration for each
receptor identified in
Step 7
9. Add values from
Steps 8 and 3
10. Round to nearest
10 (tg/m3
Are build design
concentrations
less than or
equal to no-
build?
No
Project does not
conform
Mitigation and control measures can be considered at any point in the process
Consider
measures to
reduce emissions
and redo
analysis*
The project sponsor should then compare the design concentration from Step 5 to the 24-
hour PMioNAAQS (150 |j,g/m3). If the design concentration calculated in Step 5 is less
161124-hour PMio concentrations for any monitoring site reported to EPA's Air Quality System can be
obtained by using the data download tools available at: https://www.epa.gov/outdoor-air-qualitv-data.
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than or equal to the NAAQS, the project conforms. If the design concentration 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 appropriate 24-hour background
concentration from the three most recent years of air quality monitoring data
based on Exhibit 9-6 (from Step 3).
• Step 7. Round to the nearest 10 |j,g/m3. At each receptor, this value is the 24-
hour PMio design concentration 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 appropriate 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/m3. The result is the 24-hour PMio design
concentration under the no-build scenario for each receptor identified in Step 7.
For each receptor with a design concentration that exceeded the NAAQS in the build
scenario, compare the build design concentration (from Step 7) to the no-build design
concentration (from Step 10). For the project to conform, the build design concentration
must be less than or equal to the no-build design concentration at each receptor in the
build scenario that exceeded the NAAQS (Step 7).161
If the build scenario design concentration is greater than the no-build design
concentration 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.
9.4 Determining Appropriate Receptors for Comparison to the
Annual PM2 5 NAAQS
Note: Section 9.4 was revised in the 2015 version of this guidance in accordance with
EPA's 2012 PM NAAQS final rule that was published on January 15, 2013 (78 FR
3264).162 It has not been changed in this version.
161 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).
162EPA 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 fulfilled this commitment by revising this guidance
in November 2015, EPA-420-B-15-084. The previous version of Section 9.4 was issued in December
2010, EPA-420-B-10-040.
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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 PM2.5 NAAQS are developed, monitored, and
implemented (71 FR 12471). Receptors cannot be used for PM2.5 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)(1) 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.163
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 PM NAAQS Final Rule and Conformity Guidance
The paragraphs below describe the relevant regulatory provisions and guidance for
calculating design concentrations and determining conformity for the annual PM2.5
NAAQS, through the steps described in Section 9.3.2.
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)164 This final rule also
included revisions to the PM2.5 monitoring regulations which are covered in more detail
below.
163 See CAA Section 176(c)(1)(B). EPA interprets "NAAQS" in this provision to mean the specific
NAAQS that has been established through rulemaking.
164 See 78 FR 3124-7 for more on the form of the annual PM2.5 NAAQS.
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The annual PM2.5 NAAQS is to be monitored at "area-wide" locations, which is defined
under 40 CFR58.1:
"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."165
In order to be consistent with the revised annual PM2.5 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 PM2.5 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 PM2.5 NAAQS.
Consistent with appendix D to this part, section 4.7.1, when micro- or
middle-scale PM2.5 monitoring sites collectively identify a larger region of
localized high ambient PM2.5 concentrations, such sites would be considered
representative of an area-wide location and, therefore, eligible for
comparison to the annual PM2.5 NAAQS. PM2.5 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 PM2.5 NAAQS. For example, if a micro- or middle-scale PM2.5
monitoring site is adjacent to a unique dominating 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." 166
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 PM2.5NAAQS are explained later in section VIII.B.3.b.i." (78
FR 3237) In this part of the preamble, EPA stated:
165 This requirement does not have to be satisfied for monitoring the 24-hour PM2 5 NAAQS or the 24-hour
PM10 NAAQS.
166See Section 4.7.1(b) and Section 4.7.1(c) of Appendix D to 40 CFR Part 58 for further background on
middle and microscale locations.
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"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 NO2 criteria that
resulted in the characterization of a microscale environment that is not
considered area-wide for PM2.5; 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.
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 concentration in the build scenario is higher than the NAAQS and the
design concentration 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 PM2.5 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)(1) 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 PM2.5 NAAQS.167
Consistent with 40 CFR 58.30(a) of the PM2.5 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 PM2.5 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 PM2.5 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.
167 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 PM2 5 NAAQS (and 24-hour PM10
NAAQS) can be determined prior to air quality modeling.
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Evaluating and choosing the models and associated methods and assumptions, including
appropriate receptor locations for the annual PM2.5 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, and their emissions benefit included in the hot-spot analysis.
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 concentrations 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.168
168 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).
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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.169 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:
https://www.epa.gov/state-and-local-transportation/policv-and-technical-
guidance-state-and-local-transportation.
o Also see EPA's Verified Technologies for SmartWay and Clean Diesel
website, which includes information about technologies that save fuel and
reduce emissions, including lists of EPA-verified technologies and
information about grant and partnership programs:
www.epa.gov/verifieddiesel-tech/verified-technologies-list-clean-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 A list of EPA-verified anti-idle technologies for trucks can be found at:
https://www.epa.gov/verified-diesel-tech/idling-reduction-technologies-
irts-trucks-and-school-buses.
169 The Federal Transit Administration (FTA) has minimum service life requirements for transit vehicles
purchased with FTA funds. Any disposition of federally assisted property before the end of its useful life
requires prior FTA approval. FTA is entitled to its share of the remaining federal interest. Please refer to
Chapter IV of FTA Circular 5010. IE for the establishment and calculation of a vehicle's useful service
life. In addition, Appendix E of the circular address the useful life calculation and disposition of vehicles
acquired with FTA funds: https://www.transit.dot.gov/sites/fta.dot.gov/files/docs/regulations-and-
guidance/fta-circulars/58051/5010-le-circular-award-management-reauirements-7-16-18.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 PM10 emissions for transit and other terminal
projects.
• 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 PM10 hot-spot analyses,
since all PM10 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.
• 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.
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• 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 Emissions from Other Sources
Note: Controlling emissions from other sources may sufficiently reduce background
concentrations in the PM hot-spot analysis.
• 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.
o See EPA's Ports Initiative website (https://www.epa.gov/ports-initiative)
for additional information on potential mobile source strategies for
reducing port-related activity from drayage trucks, locomotives, ocean-
going vessels, harbor craft, and cargo handling equipment.
o See also EPA's Port Emissions Inventory Guidance, which provides
methodologies on how to develop port-related and goods movement
emissions inventories, including emissions of PM. This guidance
describes the latest, state-of-the-science methodologies for preparing an
emissions inventory in the following mobile source sectors: ocean-going
vessels, harbor craft, recreational marine, and cargo handling
equipment.170 Note that while the Port Emissions Inventory Guidance
also includes sections on estimating emissions from onroad vehicles and
locomotives, Section 4 of the PM Hot-Spot Guidance (this guidance)
provides the latest information on estimating PM emissions from onroad
vehicles for PM hot-spot analyses, and Appendix I of the PM Hot-Spot
Guidance provides information for estimating emissions from locomotives
for PM hot-spot analyses.
1 70
EPA, Port Emissions Inventory Guidance: Methodologies for Estimating Port-Related and Goods
Movement Mobile Source Emissions, EPA-420-B-20-046, September 2020, available on EPA's website at:
https://www.epa.gov/state-and-local-transportation/port-emissions-inventorv-guidance.
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• 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:
https://www.epa.gov/state-and-local-transportation/policv-and-technical-
guidance-state-and-local-transportation.
o EPA-verified anti-idle technologies for locomotives can be found at:
https://www.epa.gov/verified-diesel-tech/locomotive-technology.
• 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).
• 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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List of Appendices
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: [RESERVED] E-l
AppendixF: [RESERVED] F-l
Appendix G: [RESERVED] G-l
AppendixH: [RESERVED] II-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 Concentration Calculations for PM Hot-Spot Analyses K-l
Appendix L: Calculating 24-hour PM2.5 Design Concentrations Using a Second Tier Approach L-l
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Appendix A:
Clearinghouse of Websites, Guidance, and Other Technical
Resources for PM Hot-Spot Analyses
A.l 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 to check for the latest versions when using them for a particular PM
hot-spot analysis.
A.2 Transportation Conformity and Control Measure Guidance
EPA's transportation conformity guidance can be found online at:
https://www.epa.gov/state-and-local-transportation/policv-and-technical-guidance-state-
and-1 ocal-transportation (unless otherwise noted). See guidance and other information
for hot-spot analyses under "Project-Level Conformity," as well as other headings such
as "Emission Models and Conformity" and "Quantifying Benefits of Control Measures in
SIPs and Conformity." The following specific guidance documents may be useful
references when implementing PM hot-spot analyses:
• The most recent version of the MOVES policy guidance, e.g., Policy Guidance on
the Use of MOVES3 for State Implementation Plan Development, Transportation
Conformity, General Conformity, and Other Purposes. This document describes
how and when to use the latest version of MOVES for SIP development,
conformity determinations, and other purposes.
• The most recent version(s)1 of the MOVES technical guidance, e.g., M0VES3
Technical Guidance: Using MOVES to Prepare Emission Inventories for State
Implementation Plans and Transportation Conformity. This document provides
guidance on appropriate input assumptions and sources of data for the use of
MOVES in SIP submissions and regional emissions analyses for transportation
conformity purposes.
1 More than one version may be available at the same time because of the new emission model grace period
in the conformity regulation at 40 CFR 93.111. During such a grace period, more than one version of a
model may be used for conformity.
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• EPA and DOT Joint 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.
• Diesel Retrofit and Replacement Projects: Quantifying and Using Their
Emissions Benefits in SIPs and Conformity, EPA-420-B-18-017, March 2018.
FHWA's transportation conformity site has additional conformity information, including
examples of quantitative PM hot-spot analyses. Available at:
www.fhwa.dot.gov/environment/air qualitv/conformitv/practices/.
A.3 MOVES Model Technical Information
MOVES, including the latest version of the model and technical information, can be
found at https://www.epa.gov/moves/latest-version-motor-vehicle-emission-simulator-
moves. MOVES3 onroad technical reports can be found at
https://www.epa.gOv/moves/moves-onroad-technical-reports#moves3. including the
following:2
• Overview of EPA's MOtor Vehicle Emissions Simulator (MOVES3), EPA-4220-
R-21-004, March 2021. This report is a high-level overview of M0VES3 that
includes references to technical documentation and other MOVES information.
• Brake and Tire Wear Emissions from Onroad Vehicles in MOVES3, EPA-420-R-
20-014, November 2020.
• Emission Adjustments for Temperature, Humidity, Air Conditioning, and
Inspection and Maintenance for Onroad Vehicles inMOVES3, November 2020,
EPA-420-R-20-013.
• Exhaust Emission Rates for Heavy-Duty Onroad Vehicles in MOVES3, November
2020, EPA-420-R-20-018.
• Exhaust Emission Rates for Light-Duty Onroad Vehicles in MOVES3, November
2020, EPA-420-R-20-019.
• Fuel Effects on Exhaust Emissions from Onroad Vehicles in MOVES3, November
2020, EPA-420-R-20-016.
2 Note that older model versions and their accompanying documentation can also be found on this EPA
website, under the links on the left for "MOVES Limited Use Models" for models that can still be used
during the model grace period, and "Previous MOVES versions" for versions no longer in use.
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Policy guidance and Federal Register announcements related to the MOVES model can
be found on the EPA's website at: https://www.epa.gov/state-and-local-
transportation/policv-and-technical-guidance-state-and-local-transportation#emission.
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 this guidance, in Appendix D of this guidance, and within EPA's Project
Level Training for Quantitative PM Hot-Spot Analyses, which can be downloaded from
https://www.epa.gov/state-and-local-transportation/proiect-level-training-quantitative-
pm-hot-spot-analvses.
A.4 EMFAC Model Technical Information
EPA approves the EMFAC model for use in California and EPA's most recent Federal
Register notice approving EMFAC is found at: https://www.epa.gov/state-and-local-
transportation/policv-and-technical-guidance-state-and-local-transportation#emission.
The approved version of EMFAC, user guides, supporting documentation, and any future
versions of the model can be downloaded from the California Air Resources Board
(CARB) website at: https://ww2.arb.ca.gov/our-work/programs/mobile-source-
emissions-inventory/msei-modeling-tools-emfac-software-and. General guidance on
using EMFAC for PM hot-spot analyses can be found in Section 5. Note that additional
information for project-level modeling with EMFAC is included in documents titled, "PL
Handbook" on CARB's website.
There may be versions of EMFAC available at this website that have not been approved
by EPA for use in SIP and transportation conformity purposes. Modelers must use the
latest version of the model approved by EPA according to the details of that approval.
Federal Register announcements related to EPA's approval of the EMFAC model can be
found on the EPA's website at: https://www.epa.gov/state-and-local-
transportation/policv-and-technical-guidance-state-and-local-transportation#emission. In
addition to the link above, see also CARB's EMFAC welcome website at:
https://arb.ca.gov/emfac/. This link as well as the CARB EMFAC training website,
https://ww2.arb.ca.gov/our-work/programs/mobile-source-emissions-inventory/msei-
training-materials. include training videos.
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:
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https://www.epa.gov/air-emissions-factors-and-quantification/ap-42-compilation-air-
emissions-factors.
Guidance on calculating dust emissions for PM hot-spot analyses can be found in Section
6 of this 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: https://www.epa.gov/regulations-emissions-
vehicles-and-engines/regulations-emissions-locomotives:
• Procedure for Emission Inventory Preparation - Volume IV: Mobile Sources,
Chapter 6. Available online at:
https://nepis.epa.gov/Exe/ZvPDF.cgi/P1009ZEK.PDF?Dockev=P 1009ZEK.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.
• Emission Factors for Locomotives, EPA-420-F-09-025, April 2009. Available
online at:
https://nepis.epa.gov/Exe/ZvPDF.cgi/P100500B.PDF?Dockev=Pl 00500B.PDF.
• Control of Emissions from Idling Locomotives, EP A-420-F-08-014, March 2008.
Available online at: https://www.epa.gov/nscep.
• Guidance for Quantifying and Using Long Duration Switch Yard Locomotive
Idling Emission Reductions in State Implementation Plans, EPA-420-B-09-037,
October 2009. Available online at:
https://nepis.epa.gov/Exe/ZvPDF.cgi/P1005MER.PDF?Dockev=P 1005MER.PDF
• EPA-verified anti-idle technologies for locomotives can be found at:
https://www.epa.gov/verified-diesel-tech/smartwav-verified-list-idling-reduction-
technologies-irts-locomotives.
• Port Emissions Inventory Guidance: Methodologies for Estimating Port-Related
and Goods Movement Mobile Source Emissions, EPA-420-B-20-046, September
2020, available on EPA's website at: https://www.epa.gov/state-and-local-
transportation/port-emissions-inventory-guidance. Section 8 of the Port Emission
Inventory Guidance provides methodologies for preparing an emissions inventory
for the rail sector of a port.
Guidance on calculating locomotive emissions for PM hot-spot analyses can be found in
Section 6 of this guidance and in Appendix I.
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A.7 AERMOD Model Technical Information and User Guides
The latest version of the regulation titled, Guideline on Air Quality Models (Appendix W
to 40 CFR Part 51, dated 2017 as of this writing) can be found on EPA's website at:
https://www.epa.gov/scram/2017-appendix-w-final-rule.
AERMOD and related documentation can be obtained through EPA's Support Center for
Regulatory Air Models (SCRAM) web site at: https://www.epa.gov/scram/air-qualitv-
dispersion-modeling-preferred-and-recommended-models. In particular, the following
guidance may be useful:
• AERMOD Implementation Guide
• User's Guide for the AMS/EPA Regulatory Model - AERMOD, ("AERMOD
User's Guide")
• AERMET User Guide
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 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 within EPA's Project
Level Training for Quantitative PM Hot-Spot Analyses, which can be downloaded from
https://www.epa.gov/state-and-local-transportation/proiect-level-training-quantitative-
pm-hot-spot-analvses.
A.8 Transportation Data and Modeling Considerations
Below are 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: www.fhwa.dot.gov/planning/tmip/.
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A.8.2 Project level planning
National Cooperative Highway Research Program (NCHRP) Report 765: Analytical
Travel Forecasting Approaches for Project-Level Planning and Design describes
methods, data sources, and procedures for producing travel forecasts for highway project-
level analyses. This report provides an update to NCHRP Report 255: Highway Traffic
Data for Urbanized Area Project Planning and Design. Available online at:
http://onlinepubs.trb.org/onlinepubs/nchrp/nchrp rpt 765.pdf.
A.8.3 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/trafficanalvsistools/tat voll/voll primer.pdf.
Highway Capacity Manual, Sixth Edition: A Guide for Multimodal Mobility Analysis,
Transportation Research Board, Washington, D.C., 2020. Not available online; purchase
information available at: http://www.trb.org/Main/Blurbs/175169.aspx. The most recent
version of the manual, and the associated guidebook, should be consulted when
completing PM hot-spot analyses. (As of this writing, the 2016 edition is most current.)
The Highway Capacity Manual Application Guidebook, Transportation Research Board,
Washington, D.C., 2003. Available online at: http://hcmguide.com/.
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Appendix B:
Examples of Projects of Local Air Quality Concern
B.l 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)(1). However, as noted elsewhere in this guidance, PMiononattainment 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)(1) and require a PM2.5
or PMio hot-spot analysis (71 FR 12491).1
Some examples of projects of local air quality concern that would be covered by 40 CFR
93.123(b)(l)(i) and (ii) 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 buses and/or diesel trucks.
Some examples of projects of local air quality concern that would be covered by 40 CFR
93.123(b)(l)(iii) 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)(1)® in the January 24, 2008 final rule (73 FR 4435-4436).
2 40 CFR 93.101 defines a "regionally significant project" as "a transportation project (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
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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)(1) and would not require a PM2.5 or PM10 hot-spot analysis (71 FR
12491).
The following are examples of projects that are not a local air quality concern under 40
CFR 93.123 (b)( 1 )(i) and (ii):
• 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 and capacity.
Examples of projects that are not a local air quality concern under 40 CFR
93.123(b)(l)(iii) 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).
EPA expanded on these examples in 2018, based on decisions made in the field about
projects in these general categories since the requirement for quantitative PM hot-spot
analyses took effect.3 These examples are repeated here.
at a minimum all principal arterial highways and all fixed guideway transit facilities that offer an
alternative to regional highway travel."
3 See PM Hot-spot Analyses: Frequently Asked Questions, EPA-420-F-18-011, June 2018, available on
EPA's website at: https://www.epa.gov/state-and-local-transportation/proiect-level-conformitv-and-hot-
spot-analvses#faa.
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The following projects typically do not involve "a significant number of diesel vehicles"
or "a significant increase in the number of diesel vehicles" as described in 40 CFR
93.123(b)(1), and thus typically would not need a PM2.5 or PM10 hot-spot analysis:
• New high occupancy vehicle (HOV) lanes and ramp HOV lanes which do not
involve a "a significant number of diesel vehicles" or "a significant increase in the
number of diesel vehicles" as described in 40 CFR 93.123(b)(1);
• Bus rapid transit projects where the buses are non-diesel, (e.g., CNG buses);
• New transit stations or transit lines with no diesel vehicles; and
• Light rail projects powered by electricity.
In addition to these examples, projects listed in 40 CFR 93.126, "Table 2 - Exempt
Projects" are exempt from conformity and as a result, would not need a PM hot-spot
analysis. In 2017, based on information from implementation in the field, EPA and
Federal Highway Administration (FHWA) determined the following projects belong to
categories listed in Table 2, and thus would not need a PM hot-spot analysis:
• Road diets: A road diet is a project where one or more vehicle travel lanes are
removed to accommodate a variety of transportation modes.4 Road diets are done
for safety purposes. If a road diet is part of a state's Highway Safety
Improvement Program, the road diet is exempt under the Table 2 item, "Highway
Safety Improvement Program implementation." If not, a road diet can still be
considered exempt under the Table 2 item, "Projects that correct, improve, or
eliminate a hazardous location or feature." For more information about road
diets, including the "Road Diet Informational Guide," please refer to FHWA's
webpage at https://safetv.fhwa.dot.gov/road diets/.
• Auxiliary lanes less than 1 mile in length: An auxiliary lane is defined as the
portion of the roadway adjoining the traveled way for speed change, turning,
weaving, truck climbing, maneuvering of entering and leaving traffic, and other
purposes supplementary to through traffic movement.5 If an auxiliary lane is less
than 1 mile in length, it can be considered exempt under the Table 2 item,
"Projects that correct, improve, or eliminate a hazardous location or feature." For
more information about auxiliary lanes, please refer to FHWA's webpage at
https://ops.fhwa.dot.gov/freewavmgmt/publications/frwv mgmt handbook/chapt
er5.htm#5-4.
• Ramp metering: Ramp metering projects involve installing traffic signals on
highway on-ramps to control the frequency at which vehicles enter the flow of
traffic, and they are also exempt under the Table 2 item, "Projects that correct,
4 A typical road diet involves converting an existing four-lane undivided roadway segment to a three-lane
segment consisting of two through lanes and a center, two-way left-turn lane. The reclaimed space can be
allocated for other uses, such as turn lanes, bus lanes, pedestrian refuge islands, bike lanes, sidewalks, etc.
5 "A Policy on Geometric Design of Highways and Streets," American Association of State Highway and
Transportation Officials, Washington, D.C., 2001. As cited in FHWA's "Freeway Management and
Operations Handbook," Chapter 5, found at
https://ops.fhwa.dot.gov/freewavmgmt/publications/frwv mgmt handbook/chapter5.htm#ref5.
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improve, or eliminate a hazardous location or feature." For more information
about ramp metering projects, please refer to FHWA's webpage at
https://ops.fhwa.dot.gov/publications/fhwahopl4020/secl.htm.
Note that 40 CFR 93.126 states that a project on the list in Table 2 is not exempt if,
through interagency consultation procedures, it is determined that the project has
potentially adverse emissions impacts. Government agencies should refer to the
governing interagency consultation procedures for the process to evaluate whether it
should be treated as non-exempt.
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Appendix C:
Hot-Spot Requirements for PMio Areas with Pre-2006
Approved Conformity SIPs
C.l 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. Agencies in PMio areas can contact their state air
agency and/or the EPA Regional Office if there are questions regarding the status of the
conformity SIP.
C.l 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;
1 A "conformity SIP" includes a state's specific criteria and procedures for certain aspects of the
transportation conformity process (40 CFR 51.390).
2 See Section 2.2 and Appendix B of this guidance and the preamble of the March 2006 final rule (71 FR
12491-12493).
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• Projects which are located at sites which have vehicle and roadway emission
and dispersion characteristics that are essentially identical to those of sites
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.
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 Clean Air Act.4 EPA's January 2008
final conformity rule significantly streamlined the requirements for conformity SIPs in 40
CFR 51.390.5 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)(1) 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.
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
3 "Transportation Conformity Guidance for Qualitative Hot-spot Analyses in PM2 5 and PMio
Nonattainment and Maintenance Areas," EPA420-B-06-902, March 2006. This guidance can be found at
EPA's National Service Center for Environmental Publications (NSCEP) at https://nepis.epa.gov/ by
searching using the document number "420b06902".
4 The 2005 Safe, Accountable, Flexible, Efficient Transportation Equity Act: A Legacy for Users
(SAFETEA-LU) amended the Clean Air Act's requirements for conformity SIPs.
5 "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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Developing Transportation Conformity State Implementation Plans (SIPs), EPA-420-B-
09-001, January 2009; available online at: https://www.epa.gov/state-and-local-
transportation/policv-and-technical-guidance-state-and-local-transportation#state.
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Appendix D:
Characterizing Intersection Projects for MOVES
D.l Introduction
This appendix expands upon the discussion in Section 4.2 on how 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 latest
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 intersection
divided into areas of approach and departure. The dotted arrows represent where vehicles
approach the signal, and the solid arrows represent where vehicles depart from the signal.
Exhibit D-l. Example of a Simple Intersection
1
r
j
1
r
t
b
Approach Link
Departure Link
When modeling an intersection, each area of approach and departure 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:
• Option 1: Using average speeds
• Option 2: Using link drive schedules
• Option 3: Using Op-Mode distributions
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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 1: 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, one example is
to model each direction as a series of links that represent different areas of activity. Each
of these links could have a unique average speed based on all the activity occuring on that
link.
Exhibit D-2. Example Links at a Simple Intersection
i
f
t
k
Link 1 Link 2
-
•
Link 4
Approach
Departure
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In this example:
• Link 1 represents a "cruise" link where activity is not affected by the traffic
signal.
• Link 2 represents a "queue" link that reflects the higher emissions associated with
vehicle idling through lower speeds affected by stopped delay. Activity on this
link includes deceleration, idle, and acceleration when the signal is red; and cruise
activity when the signal is green.
• Link 3 represents an "acceleration" link that reflects the higher emissions
associated with vehicle acceleration through lower speeds affected by acceleration
delay when the signal is red; and cruise activity when the signal is green.
• Link 4, like Link 1, represents a cruise link where activity is not affected by the
traffic signal. Cruise links further away from intersections would not have any
delay from the traffic signal.
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).1 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.
Project sponsors will also need to determine the length of each link, which is influenced
by the traffic signal's impact on the length of the queueing vehicles, the deceleration rate
of vehicles, and the acceleration rate of vehicles.
D.3 Option 2: Using Link Drive Schedules
A more refined approach is to enter vehicle activity into MOVES as one or more link
drive schedules to represent cruise, deceleration, idle, and acceleration activity 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. By defining a link
drive schedule, all of these activity types can be included in the link.
Exhibit D-2 illustrates why using this more refined approach can result in a more detailed
emissions analysis. This exhibit shows the trajectories of two vehicles approaching and
progressing through an intersection: one vehicle that stops because of the red phase of a
traffic light cycle (the red-light link, shown as the red dotted line), and a second vehicle
that does not stop because the light is green (the green-light link, shown as the solid green
line).
1 See FHWA's TMIP website: https://www.fhwa.dot.gov/planning/tmip/.
2 Users should consult the most recent version of the Highway Capacity Manual. See Appendix A8.
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Exhibit D-3. Example Link Drive Schedules for Links Representing a Signalized
Intersection
Red-light Link
Green-light Link
Time (seconds)
For the example intersection in Exhibit D-l, two links could be used to represent each
direction of travel. If the vehicle mix and drive schedules are the same for each direction
of travel, then two links could be used for all directions (with a total volume representing
all four directions of travel). If the streets have different speed limits, or have different
percentages of trucks, then two links would be needed for each direction.3
The two links would have distinct drive schedules that represent either the vehicles
encountering the red light or vehicles encountering the green light, as shown in Exhibit
D-3:
• Red-light link: The red-light link 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. Each vehicle
approaching the intersection when the light is red (or yellow) would have a
similar speed trace except for the duration of idle time, which would vary
depending on whether the vehicle was stopped at the beginning, middle, or end of
the red light phase. Therefore, the red-light link drive schedule can be input with
the average idle time of vehicles that stop at that signal.
• Green-light link: In contrast, vehicles progressing through an intersection during
the green signal phase of a traffic light cycle can be characterized by a more or
less steady cruise speed through the intersection. These vehicles can be
represented with a separate link with a link drive schedule reflecting this steady
cruise activity.
• Vehicle volumes for the red-light link and the green-light link should total the
number of vehicles proceeding through the intersection in the hour. (The vehicle
3 Regardless, the modeler will need to ensure that MOVES results for these links are included in AERMOD
correctly and should document how the results from these links are input into AERMOD.
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volumes may or may not be equal; it depends on the percent of time that the light
is red vs. green.)
• The link lengths of these two links should be the same.
Modelers should use additional links if necessary to capture the differences in vehicle
types. For instance, heavy-duty vehicles decelerate and accelerate at slower rates than
passenger cars. These could be defined with additional links that have unique link drive
schedules. In this case, the links need to reflect the appropriate vehicle types (done
through the Link Source Type Input).
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. In this case, the green-light link could either be not included in the Links
table or given a vehicle volume of zero. The latest Highway Capacity Manual is a good
source of information for 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 results for each road segment obtained via individual link drive schedules
need to be appropriately post-processed before being used in AERMOD. For example, if
Inventory mode is used, the results for all the link drive schedules representing a specific
source in AERMOD would need to be summed. If Emission Rates mode is used, the
results for the link drive schedules representing a specific source in AERMOD have to be
multiplied by the appropriate factors, then summed. Note that AERMOD sources can
also be defined by vehicle type: a source could include emissions from all vehicles, or
two sources could be defined at the same location, one for light-duty and one for heavy-
duty emissions. Modelers should take care to document specifically how results from
MOVES are applied in AERMOD, i.e., list the post-processing steps taken. See Sections
4.6 and Section 7 of the guidance as well as Appendix J.
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
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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 multiplied 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 (i.e., both the red light and green light driving
cycles are going to be represented in these 5000 links). 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).
I). 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
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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 total 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);
• 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.
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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 total 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.
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Appendix E: Reserved
Note: EPA removed the example of a PM hot-spot analysis of a highway project in
Appendix E in the previous version of this guidance (2015) because it was superseded by
the example analyses found in EPA's quantitative PM hot-spot analysis training course.
The course materials, including the presentation of the example analysis and all of the
files necessary to repeat the analysis are available for download at:
https://www.epa.gov/state-and-local-transportation/proiect-level-training-quantitative-
pm-hot-spot-analvses.
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Appendix F: Reserved
Note: EPA removed the example of a PM hot-spot analysis of a transit project in
Appendix F in the previous version of this guidance (2015) because it was superseded by
the example analyses found in EPA's quantitative PM hot-spot analysis course. The
course materials, including the presentation of the example analysis and all of the files
necessary to repeat the analysis are available for download at:
https://www.epa.gov/state-and-local-transportation/proiect-level-training-quantitative-
pm-hot-spot-analvses.
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Appendix G: Reserved
Note: EPA removed the example using EMFAC in Appendix G because it pertained to a
version of EMFAC no longer in use. See Appendix A.4 for more information on
EMFAC available at California Air Resources Board's website.
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Appendix H: Reserved
Note: EPA removed the example using EMFAC in Appendix H because it pertained to a
version of EMFAC no longer in use. See Appendix A.4 for more information on
EMFAC available at California Air Resources Board's website.
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Appendix I:
Estimating Locomotive Emissions
I.l 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.
Note that Section 8 of EPA's Port Emissions Inventory Guidance: Methodologies for
Estimating Port-Related and Goods Movement Mobile Source Emissions, EPA-420-B-
20-046, September 2020, available on EPA's website at: https://www.epa.gov/state-and-
local-transportation/port-emissions-inventory-guidance is also a useful reference. Section
8 covers methodologies for preparing an emissions inventory for the rail sector of a port.
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.1
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 These are the two methods described in this appendix; others may be possible. See Appendix 1.5 for
details.
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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
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 PM2.5 NAAQS.2 Or, project sponsors could
calculate emissions based on the highest 24 hours of activity during the year, and use
those emissions to represent all days of the year.
These resulting emission rates should be applied to AERMOD and used to calculate
design concentrations to compare with the applicable PM NAAQS as described in
Sections 7 through 9 of the guidance.
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 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.
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).
1.4.2 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.
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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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.
1.5.1 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 PM2.5 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 https://www.epa.gov/regulations-emissions-vehicles-and-
engines/regulations-emissions-locomotives for the latest locomotive default emission
factors and related information. In addition, see https://www.epa.gov/state-and-local-
transportation/transportation-related-documents-state-and-local-transportation for related
guidance.
1.5.2 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.
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 PMio
emission factors for PM2 5 purposes. Note that Table 6 (PMio 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.
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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 percent:
((4000 hp-hrs + 2000 hp-hrs) / (4000 hp* 2 hrs)) * 100% = 75%
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.8 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.
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.
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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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
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.
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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.11
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).
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.
1.5.3 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.
9 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 ensure the latest default emission factors for idle and moving emissions
are being used. See Appendix Section 1.5.1.
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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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
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.
1.5.4 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 must use ultra-low sulfur diesel fuel (69 FR 38958).
Additionally, when existing locomotives are remanufactured, certified
remanufacture systems 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 were 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)
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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.
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:
• Port Emissions Inventory Guidance: Methodologies for Estimating Port-Related
and Goods Movement Mobile Source Emissions, EPA-420-B-20-046, September
2020, available on EPA's website at: https://www.epa.gov/state-and-local-
transportation/port-emissions-inventory-guidance. Section 8, which covers
methodologies for preparing an emissions inventory for the rail sector of a port,
includes PM emission factors for line-haul and switcher locomotives.
• Emission Factors for Locomotives, EPA-420-F-09-025, April 2009. Available
online at: https://nepis.epa.gov/. Use the document number (420F09025) to
search for this document.
• Chapter 6 of Procedure for Emission Inventory Preparation - Volume IV: Mobile
Sources. Available online at: https://nepis.epa.gov/. 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-13-50, December
2013. Available online at:
https://nepis.epa.gov/Exe/ZyPdf.cgi?Dockey=P 100HP4Q.pdf. .
• See Section 10 of the guidance for additional information regarding potential
locomotive emission control measures.
12 Although the emission factors have been superseded, the remainder of the Volume IV guidance remains
in effect.
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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 2012
annual PM2.5 NAAQS and the 2006 24-hour PM2.5 NAAQS. The terminal in this
example is to be completed and operational in 2025. The hot-spot analysis is performed
for 2030, 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.
The locomotive PM2.5 emissions are calculated based on horsepower rating and load
factors.
1.7.1 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 1-1.
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.
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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
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.
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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
136
12.5%
20.2%
27.5
1
224
6.5%
10.5%
23.5
2
484
6.5%
10.5%
50.8
3
984
5.2%
8.4%
82.7
4
1149
4.4%
7.1%
81.6
5
1766
3.8%
6.1%
107.8
6
2518
3.9%
6.3%
158.6
7
3373
3.0%
4.8%
161.9
8
4,000
16.2%
26.1%
1,044.0
Total
62.0%
100.0%
1,752.4
43.8%
1.7.2 Using the loadfactors 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
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).
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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 (see Appendix 1.6).
Table 1 of Emission Factors for Locomotives presents PM10 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)
• Tier 2 Locomotive Emission Factor = 0.18 g/bhp-hr (from "Emission Factors for
Locomotives")
• Ratio of PM2.5 to PM10 = 0.97 (from "Emission Factors for Locomotives")
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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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 trains/day) * (76 s/train) * (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 PM2.5 to PM10 = 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. PM2.5 Locomotive Emission Rates
Operational
Mode
Number of
Locomotives
Time/
Train
pm25
Emission
Factor
Calculated
Peak Hour
Emission Rate
Calculated
24-hour
Emission
Rate
Peak
hour
24
hours
(s)
(g/bhp-hr)
(g/s)
(g/s)
Idle
16
32
540
0.18
0.0019
0.00016
Moving
32
64
76
0.18
0.057
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 2012 annual PM2.5
NAAQS and the 2006 24-hour PM2.5 NAAQS, the results of the analysis will be
compared to both NAAQS (see Section 3.3.4 of the guidance). 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 AERMOD
J.l Introduction
This appendix supplements Section 7's discussion of AERMOD. Specifically, this
appendix describes how to configure AERMOD for PM hot-spot analysis modeling, as
well as additional information on handling the data required to run the model for these
analyses. This appendix is not intended to replace the "User's Guide for the AMS/EPA
Regulatory Model (AERMOD)" (in this document, "AERMOD User's Guide"), but
discusses specific model inputs, keywords, and formats for PM hot-spot modeling.1 This
appendix is organized so that it references the appropriate discussions in Section 7 of the
guidance.
J.2 AERMOD Input and Output Units
The following discussion supplements Section 7.3 of the guidance.
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
traffic queuing mechanisms. Emissions output from MOVES, EMFAC, AP-42, and
other types of methods should be formatted as described in the AERMOD User's Guide.2
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 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 AERMOD User's Guide and EPA's quantitative PM hot-spot
analysis training course, available for download at https://www.epa.gov/state-and-local-
transportation/proiect-level-training-quantitative-pm-hot-spot-analvses.
1 User's Guide for the AMS/EPA Regulatory Model (AERMOD), EPA-454/B-21-001, April 2021, can be
found on EPA's website at: https://www.epa.gov/scram/air-qualitv-dispersion-modeling-preferred-and-
recommended-models#aermod.
2 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 1/dispersion prefrec.htm#aermod.
J-l
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J. 3.1 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 line, area, volume, and point
sources. It is acceptable to use either line/area or volume sources to simulate roadways in
AERMOD. When modeling roadway links, experience in the field has shown that
line/area sources may be easier to characterize correctly compared to volume sources.3
Volume sources can also have longer run time than line/area sources. Users may want to
be particularly mindful of making errors when using volume sources.4
Modeling Area Sources
AERMOD can represent rectangular, polygon-shaped, and circular area sources using the
AREA, AREAPOLY, AREACIRC, or LINE 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. Evenly-distributed ground-level sources
might also be modeled as area sources. EPA recommends that the LINE source keyword
be used for modeling roadway sources as it greatly simplifies defining the physical
location and orientation of sources.
AERMOD requires the following information when modeling an area source using the
LINE source keyword:
• The emission rate per unit area (mass per unit area per unit time);
• The coordinates of midpoint of the ends (Xi,Yi, X2,Y2)
• The width of the source in meters;
• The initial vertical dimension of the area source plume and initial vertical
dispersion coefficient; and
• The release height above the ground.
Width of the Source. To estimate the width of the source, one of the following options
should be used:
a) The width of the traveled way, typically 3.7 m (12 ft) per lane for a high-speed,
high volume roadway and 3.3 m (11 ft) per lane for an arterial/collector; or
b) The width of the traveled way (all travel lanes) + 6 meters.5
Initial Vertical Dimension. A typical approach is to assume the initial vertical dimension
is about 1.7 times the average vehicle height, to account for the effects of vehicle-induced
3 Sources defined by the LINE keyword are equivalent to rectangular AREA sources; input parameters for
LINE are streamlined.
4 For additional information on issues related to applying volume sources, see slides 16-19 in EPA's "PM
Hot-spot Modeling: Lessons Learned in the Field" presentation (January 2014) found on:
https://www.epa.gov/state-and-local-transportation/proiect-level-conformitv-and-hot-spot-
analvses#training.
5 Option (b) is based on the Haul Road Workgroup Final Report (December 2011), found on the web at
https://www.epa.gov/sites/production/files/2020-10/documents/haul road workgroup-
final report package-20120302.pdf.
J-2
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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.
Initial Vertical Dispersion Coefficient. The AERMOD User's Guide recommends that
the initial vertical dispersion coefficient (oZ0), termed Szinit in AERMOD, be estimated
by dividing the initial vertical dimension by 2.15. For typical light-duty vehicles, this
corresponds to a Szinit (oZ0) of 1.2 meters. For typical heavy-duty vehicles, the initial
value of Szinit (oZ0) is 3.2 meters.
Release Height. The source release height (Relhgt), which is the height at which wind
effectively begins to affect the plume, may be estimated as the midpoint of the initial
vertical dimension. In other words, Relhgt is the initial vertical dimension multiplied by
0.5. As noted above, most road links will consist of a combination of light-duty and
heavy-duty traffic. For each roadway source, the source release height (Relhgt) should be
based on the same initial vertical dimension used for calculated its Szinit, as described
above.
Another way of dealing with Szinit and/or release height (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 the same space, but
would have emission rates and Szinit and Relhgt parameters that are specific to light-duty
or heavy-duty traffic.
Also, AERMOD allows 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
beginning a PM hot-spot analysis.
Groups of idling vehicles may also be modeled as one or more area sources. In those
cases, the initial vertical dimension of the source, dispersion coefficients, and release
heights should be calculated assuming that the vehicles themselves are inducing no
turbulence. Source characterization should be based on the type of vehicles idling, e.g., if
the vehicles idling are primarily heavy-duty trucks, then the release height would be 4
meters.
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Modeling Volume Sources
Another option for modeling sources in a PM hot-spot analysis is to use volume sources.
When modeling highway and intersection links, experience in the field has shown that
line/area sources may be easier to characterize compared to volume sources. Project
sponsors using volume sources should seek the assistance of their EPA Region through
the interagency consultation process, based on 40 CFR 93.105(c)(l)(i). Consulting with
EPA on parameters that will be used to describe the sources may save time in avoiding
errors.
Examples of project sources that may be modeled with volume sources could include
areas designated for truck or bus queuing or idling, driveways and pass-throughs in
transit or freight terminals, and locomotive emissions.6 AERMOD can also approximate
a highway using a series of adjacent volume sources (see the AERMOD User's Guide for
suggestions), but as noted above, experience in the field has shown that line/area sources
may be easier to characterize correctly compared to volume sources. Volume sources can
also have longer run time as compared to line/area sources. 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).
When using volume sources, users need 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;
• 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).7 See the above discussion on area sources
for guidance on defining release height and initial vertical dispersion coefficients.
The goal of using volume sources to represent a roadway is to create a uniform emissions
characterization. Ensure that volume sources are not spaced too widely along the
roadway. Adjacent volume sources should overlap and the distance between them should
be equal to the width of the source, as described in the AERMOD User's Guide. Any
other approximation of roadways with volume sources will result in adjacent receptors
being over or under-estimated depending on their proximity to the center of the volume
source.
6 See Section 6 and Appendix I for information regarding calculating locomotive emissions.
7 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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To specify the initial lateral dispersion coefficient (oy0), referred to as Syinit in
AERMOD, the AERMOD User's 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.
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.
Source characterization should be based on the type of vehicles idling, e.g., if the vehicles
idling are primarily heavy-duty diesel trucks, then the release height would be 4 meters.
In addition, when the source-receptor spacing in AERMOD is shorter than the distance
between adjacent volume sources, AERMOD may produce aberrant results. Therefore,
ensure that no receptors are placed within a distance of (2.15 x Syinit + 1 meter) of the
center of a volume source, known as the "receptor exclusion zone." As a practical
recommendation, when using volume sources to simulate a roadway where receptors are
placed five meters from the edge of the roadway, the width of a volume source should be
less than eight meters. This will ensure that no receptors fall within the receptor
exclusion zone. If the width of the roadway is larger than eight meters, it is
recommended that additional volume sources be defined (e.g., separate each lane of
traffic), or area sources be used.
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
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's Guide for additional detail on how
to enter building information.
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J. 3.2 Placement and sizing of sources within AERMOD
There are several general considerations with regard to placing and sizing sources within
AERMOD.
First, line/area, volume, 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's 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. 3.3 Timing of Emissions in AERMOD
Within AERMOD, emissions that vary across a year should be described with the
EMISFACT keyword (see Section 3.3.11 of the AERMOD User's 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 emission model runs for each day should be mapped to the hours they represent in
the AERMOD input file, corresponding to the relevant hours of the day based on the
traffic analysis. The Qflag parameter under EMISFACT may be used with a secondary
keyword to describe different patterns of emission variations throughout a year. Qflag
can be used to represent emission rates that vary by season, hour of day, and day of the
week. Consult the AERMOD User's Guide for details.
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).
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Emission data obtained from MOVES or EMFAC should be appropriately matched with
the relevant time periods in AERMOD:
• If only four MOVES runs are done based on Section 4.3 of this guidance, those
four runs would be applied to the 24 hours of every month. In this case, the Qjlag
parameter to use would be HRODAY, so that emission rates vary by hour-of-day
only.
• If additional MOVES or EMFAC runs are completed to capture seasonal variation
in emissions, such as 16 runs to model four times of the day in each season of a
year, the Qjlag parameter to use would be SEASHR to allow emission rates to
vary by season and hour-of-day.8
• 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.
For additional information, see the AERMOD User's Guide.
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. 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.
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-
8 In the case of 16 runs, for example, the January morning MOVES run emissions would be used in
AERMOD for all the morning hours of December, January, and February. Similarly, the January midday
MOVES run emissions would apply for all the midday hours of December, January, and February. In this
way, the modeler would apply the emissions from the 16 MOVES runs to the 24 hours in the four seasons
in AERMOD as appropriate.
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specific meteorological data in urban applications, consult the AERMOD Implementation
Guide.
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. 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.
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.
J.6 Running AERMOD and Obtaining Results
This discussion supplements Section 7.7 of the guidance and describes in more detail
how to handle data outputs in AERMOD.
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's Guide for details on the
various output options. Output options should be specified to enable the relevant design
concentration 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 - which is
recommended for most analyses).
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For the annual PM2.5 design concentration 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 ANNUAL averaging time should be specified using the AVERTIME keyword
in the CO pathway. For the OU pathway, a POSTFILE keyword should be defined to
obtain the annual average concentrations at each receptor.
For the 24-hour PM2.5 design concentration calculations described in Section 9.3.3, the
RECTABLE keyword should be used to obtain the average 98th percentile concentration
at each receptor. The eighth high value should be requested, because this would be the
98th percentile concentration for the year, that is, of 365 values. In conjunction with
defining PM2.5 in the POLLUTID keyword of the Control pathway, the concentrations
generated in the output will be an average across N-years of meteorological data. If five
years of meteorological data were used, the output will be calculated as the average 98th
percentile value and can be added directly to the 98th percentile background concentration
to determine the 24-hr PM2.5 design concentration for a first tier approach (described in
Section 9 and Appendix K).
See Appendix L for information on using AERMOD for a second tier design
concentration approach.
For the 24-hour PM10 calculations, the RECTABLE keyword may be used to obtain the
sixth highest 24-hour concentrations over the entire modeling period (assuming five years
of meteorological data were used). The output will be calculated as the sixth high value
at each receptor and can be added directly to the appropriate background concentration
(i.e., fourth-, third-, second-highest, or highest, based on Exhibit 9-6) to determine the 24-
hr PM10 design concentration (described in Section 9 and Appendix K).
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Appendix K:
Examples of Design Concentration Calculations for PM Hot-
Spot Analyses
K.1 Introduction
This appendix supplements Section 9's discussion of calculating and applying design
concentrations for PM hot-spot analyses. While this guidance can apply to any PM
NAAQS, this appendix provides examples of how to calculate design concentrations for
the PM NAAQS that apply in most areas:
• the 2012 annual PM2.5 NAAQS,
• the 2006 and 1997 24-hour PM2.5 NAAQS, and
• the 1987 24-hour PM10 NAAQS.
The design concentrations 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.
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 2018, 2019, and 2020. For this example,
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there are 121 monitored values for both 2018 and 2019 (365 days each), and 122 values
in 2020 since it is a leap year (366 days).1
However, through interagency consultation, it is determined that the freight terminal's
emissions are not already captured by this air quality monitor, so AERMOD is used to
estimate PM concentrations produced by the project (the highway expansion) and the
nearby source (the freight terminal). 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 concentration 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 concentrations 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 |ig/m3 (nearest 0.1 (j,g/m3). For example,
12.049 rounds to 12.0, and 12.050 rounds to 12.1.2
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 PM2.5 NAAQS is met when the three-year average concentration is
less than or equal to the current annual PM2.5 NAAQS (i.e., 15.0 (j,g/m3):
Annual PM2.5 design value = ([Yl] average + [Y2] average + [Y3] average) ^ 3
Where:
[Yl] = Average annual PM2.5 concentration for the first year of air quality
monitoring data
[Y2] = Average annual PM2.5 concentration for the second year of air quality
monitoring data
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
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.
2 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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[Y3] = Average annual PM2.5 concentration for the third year of air quality
monitoring data
For this example, the project described in Appendix K.2 is located in an annual PM2.5
NAAQS nonattainment area. This example illustrates how an annual PM2.5 design
concentration 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 concentrations would be calculated at additional
receptors, as described further in Section 9.3.2.
K. 3.2 Build Scenario
For the build scenario, the PM2.5 impacts from the project and from the nearby source are
estimated with AERMOD at all receptors.3
Steps 1. 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 [j,g/m3.
Step 2. 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 (j,g/m3, as
shown in Exhibit K-l:
Exhibit K-l. Background Concentrations
Background
Concentrations
Ql
Q2
Q3
Q4
Average
Annual
Year 1
13.013
17.037
8.795
8.145
11.748
Year 2
14.214
14.872
7.912
7.639
11.159
Year 3
11.890
16.752
9.421
9.287
11.838
3-year average:
11.582
Step 3. The 3-year average annual background concentration (from Step 2) is added to
the average annual modeled concentration from the project and nearby source (from Step
1):
11.582 + 3.603 = 15.185
3 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 modeling.
K-3
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Step 4. Rounding to the nearest 0.1 |j,g/m3 produces a design concentration of 15.2
Hg/m3.
In this example, the concentration at the highest receptor is estimated to exceed the 2012
annual PM2.5 NAAQS of 12.0 |j,g/m3.
Steps 5-6: Since the design concentration in Step 4 is greater than the NAAQS, design
concentration calculations are then completed for all receptors in the build scenario, and
receptors with design concentrations above the NAAQS are identified. After this is done,
the no-build scenario is modeled for comparison.
K. 3.3 No-Build 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 concentrations are only calculated in the no-build scenario
at receptors where the design concentration for the build scenario is above the annual
PM2.5 NAAQS (from Steps 5-6 above).
Step 7. For this example, the receptor with the highest average annual concentration in
the build scenario is used to illustrate the no-build scenario design concentration
calculation. The average annual concentration modeled at this receptor in the no-build
scenario is 3.521 |j,g/m3.
Step 8. 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 9. Rounding to the nearest 0.1 |j,g/m3 produces a design concentration of 15.1
Hg/m3.
In this example, the design concentration at the receptor in the build scenario (15.2
(j,g/m3) is greater than the design concentration at the same receptor in the no-build
scenario (15.1 (j,g/m3).4 In an actual PM hot-spot analysis, design concentrations 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
4 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.
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discussed in Section 10. After measures are selected, a new build scenario that includes
the controls should be modeled and new design concentrations calculated. Design
concentrations for the no-build scenario shown above would not need to be recalculated
since the no-build scenario would not change.
K.4 Example: 24-Hour PM2.5 NAAQS
K. 4.1 General
This example illustrates a first tier approach to calculating design concentrations for
comparison with the 24-hour PM2.5 NAAQS. As discussed in Section 9, while either
approach is acceptable, EPA recommends beginning with a first tier approach as there are
very few cases where a second tier approach would not produce a more conservative
design concentration. See Appendix L for information on using a second tier approach.
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 PM2.5 NAAQS for a given area's nonattainment
designation (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).5 The design value for comparison
to any 24-hour PM2.5 NAAQS is rounded to the nearest 1 |ag/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 whole number). For example, 35.499 rounds to 35 |ag/m3,
while 35.500 rounds to 36.6
For this example, the project described in Appendix K.2 is located in a nonattainment
area for the 2006 24-hour PM2.5 NAAQS. This example presents the first 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. In an actual PM
hot-spot analysis, design concentrations would be calculated at additional receptors, as
described further in Section 9.3.3.
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.
5 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.
6 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
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Under a first tier analysis, the average 98th percentile modeled 24-hour concentrations at
a given receptor are added to the average 98th percentile 24-hour background
concentrations, regardless of the quarter in which they occur. The average 98th percentile
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 98th percentile modeled 24-hour
concentration is identified from the AERMOD output. For this example, the data from
this receptor is shown in Exhibit K-2. Exhibit K-2 shows the 98th percentile 24-hour
concentration for each year of meteorological data used. The average concentration of
these outcomes, 3.710 |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 98th Percentile PM2.5 Concentrations from Project and
Nearby Source
98th Percentile
PM25
Year
Concentration
Met Year 1
3.413
Met Year 2
2.846
Met Year 3
3.671
Met Year 4
4.951
Met Year 5
3.667
Average
3.710
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 the three most recent years.
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 |ag/m3) of the monitor throughout the years employed for estimating
background concentrations.
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Exhibit K-3. Top Eight Monitored Concentrations in the Three Most Recent Years
Rank
Year 1
Year 2
Year 3
1
34.123
33.537
35.417
2
31.749
32.405
31.579
3
31.443
31.126
31.173
4
30.809
30.819
31.095
5
30.219
30.487
30.425
6
30.134
29.998
30.329
7
30.099
29.872
30.193
8
28.481
28.937
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 ng/m3.
Step 3. Then, the 98th percentile 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):
3.710 + 31.247 = 34.957 ng/m3.
Rounding to the nearest whole number results in a 24-hour PM2.5 design concentration of
35 |jg/m3.
This concentration is equal to the 2006 24-hour PM2.5 NAAQS (35 |j,g/m3), and therefore
this analysis demonstrates that conformity is met.
If the project had not passed the initial build comparison, the project sponsor has two
options:
1. 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
concentration for the build scenario is less than or equal to the design
concentration for the no-build scenario at all of these receptors, then the project
conforms; or
2. Conduct a second tier approach - See Appendix L.
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K.5 Example: 24-Hour PM10NAAQS
K.5.1 General
This example illustrates calculating design concentrations for comparison with the 24-
hour PMio NAAQS, as described in Section 9.3.4. The 24-hour PMio NAAQS is based
on the expected number of 24-hour exceedances of 150 |ag/m\ averaged over three
consecutive years. For air quality monitoring purposes, the NAAQS is met when the
expected number of days per calendar year with a 24-hour concentration above 150
Hg/m3 is less than or equal to 1.0. The 24-hour PMio daily value is rounded to the nearest
10 |j,g/m3. For example, 155.500 rounds to 160, and 154.999 rounds to 150.7
The 24-hour PMio design concentration 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 appropriate monitor value for the 24-hour
background concentration (from three years of monitored data), based on Exhibit 9-6.
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.
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.8 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-4 shows the six highest 24-hour concentrations at this
receptor.
7 This rounding convention comes from Appendix K to 40 CFR Part 50. 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.
8 The six highest concentrations could occur anytime during the five years of meteorological data. They
may be clustered in one or two years, or they may be spread out over several, or even all five, years of the
meteorological data.
K-8
-------
Exhibit K-4. Receptor with the Highest Sixth-Highest 24-Hour Concentration
(Build Scenario)
Rank
Highest 24-Hour
Concentrations
1
17.012
2
16.709
3
15.880
4
15.491
5
15.400
6
15.218
Step 3. In this example, the background monitor collects data every third day (l-in-3
sampling) and has a total of 360 daily readings in the most recent three year period. The
appropriate 24-hour background concentration from the three most recent years of
monitoring data is identified based on Exhibit 9-6. The information in Exhibit 9-6 has
been repeated in Exhibit K-5 below, along with the highest four values from the
background monitor:
Exhibit K-5: Highest Values from the Chosen Background Monitor (360 Readings
in the Most Recent Three-Year Period)
Number of Background
Concentration Values
from the Monitor
Monitor Value Used
for Design
Concentration
Calculation
Highest Values from
the Chosen
Background Monitor
<347
Highest Monitor Value
112.490
348 - 695
Second Highest Value
86.251
696 - 1042
Third Highest Value
75.821
1043 - 1096
Fourth Highest Value
75.217
Because the monitor has 360 readings in the most recent three-year period, the second-
highest 24-hour background concentration is used for the design concentration
calculation. The second-highest value is 86.251 |j,g/m3.
Step 4. The sixth-highest 24-hour modeled concentration of 15.218 |j,g/m3 from the
highest receptor (from Step 2) is added to the second-highest 24-hour background
concentration of 86.251 |j,g/m3 (from Step 3):
15.218 + 86.251 = 101.469
Step 5. This sum is rounded to the nearest 10 |ag/m\ which results in a design
concentration of 100 |j,g/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 |ag/m\ therefore
K-9
-------
the analysis shows that the project conforms. However, if the design concentration for
this receptor had been greater than 150 ng/m3, the remainder of the steps in Section 9.3.4
would be completed. That is, build scenario design concentrations 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 concentrations would also be calculated (Steps 8-10 in
Section 9.3.4). The build and no-build design concentrations would then be compared.9
9 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-10
-------
Appendix L:
Calculating 24-hour PM2.5 Design Concentrations
Using a Second Tier Approach
L.l Introduction
As described in Section 9, design concentrations for the 24-hr PM2.5 NAAQS may be
calculated using either a first tier or second tier approach. Generally, the first tier
approach involves adding the 98th percentile monitored data directly to each receptor's
98th percentile modeled concentrations. The second tier approach requires developing a
98th percentile background concentration for each quarter. Those values are then read
into the AERMOD input file and used to calculate an appropriate 98th percentile design
concentration for each receptor - done entirely within the model. EPA believes that most
analyses should be done with a first tier approach, as described in Section 9 and
illustrated in Appendix K. The first tier approach requires much less processing of
monitoring data and modeled concentrations. However, users may choose to follow the
second tier approach to meet conformity requirements if through interagency consultation
it is determined that a first tier approach is overly conservative. The second tier process
includes the following general steps:
1) Calculate quarterly 98th percentile values from the monitoring data
2) Add quarterly background concentrations to AERMOD input file
3) Run AERMOD to generate 98th percentile concentrations at each receptor
This process differs from the methodology described for the first tier approach, as well as
PM2.5 annual and PM10 design concentration calculations. Notably, background is
handled first, then added into the AERMOD input file. AERMOD will automatically
generate the appropriate 98th percentile design concentration.
The remainder of Appendix L describes an example of a second tier design concentration
approach, as well as the steps involved with adding background concentrations to an
AERMOD input file.
L.2 Preparing Monitoring Data
This appendix provides an illustrative example of the calculations and data sorting
recommendations for the background monitoring data to be used in a second tier
modeling approach.1 In this example, it was determined through interagency
consultation that the impacts from the project's PM2.5 emissions were most prominent
during the cool season and were not temporally correlated with background PM2.5 levels
that were typical highest during the warm season. So, combining the modeled and
1 This example has been adapted from the 2014 Guidance for PM2 5 Permit Modeling, available at:
http://www.epa.gov/ttn/scram/guidance/guide/Guidance for PM25 Permit Modeling.pdf.
L-l
-------
monitored contributions through a first tier approach was determined to be potentially
overly conservative.
The example provided is from an idealized Federal Reference Method (FRM) PM2.5
monitoring site that operates on a daily (1-in-l day) frequency with 100% data
completeness. In this case, the annual 98th percentile concentration is the 8th highest
concentration of the year. In most cases, the FRM monitoring site will likely operate on a
l-and-3 day frequency and will also likely have missing data due to monitor maintenance
or collected data not meeting all of the quality assurance criteria. Please reference
Section 9 (Exhibit 9.5) and Appendix N to 40 CFR Part 50 to determine the appropriate
98th percentile rank of the monitored data based on the monitor sampling frequency and
valid number of days sampled during each year. The appropriate seasonal (or quarterly)
background concentrations to be included as input to the AERMOD model per a second
tier approach are as follows:
Step 1 - Start with the most recent three years of representative background PM2.5
ambient monitoring data that are being used to develop the monitored background PM2.5
concentration. In this example, the three years are labeled Year 1, Year 2, and Year 3.
Step 2 - For each year, determine the appropriate rank for the daily 98th percentile PM2.5
concentration. Again, this idealized example is from a 1-in-l day monitor with 100% data
completeness. So, the 8th highest concentration of each year is the 98th percentile PM2.5
concentration. The 98th percentile PM2.5 concentration for Year 1 is highlighted in Exhibit
L-l. The full concentration data from Year 2 and Year 3 are not shown across the steps in
this Appendix for simplicity but would be similar to that of Year 1.
Step 3 - Remove from further consideration in this analysis the PM2.5 concentrations
from each year that are greater than the 98th percentile PM2.5 concentration. In the case
presented for a 1-in-l day monitor, the top 7 concentrations are removed. If the monitor
were a l-in-3 day monitor, only the top 2 concentrations would be removed. The
resultant dataset after the top 7 concentrations have been removed from further
consideration in this analysis for Year 1 is presented in Exhibit L-2.
Step 4 - For each year, divide the resultant annual dataset of the monitored data equal to
or less than the 98th percentile PM2.5 concentration into each season (or quarter). For
Year 1, the seasonal subsets are presented in Exhibit L-3.
Step 5 - Determine the maximum PM2.5 concentration from each of the seasonal (or
quarterly) subsets created in Step 4 for each year. The maximum PM2.5 concentration
from each season for Year 1 is highlighted in both Exhibits L-3 and L-4.
Step 6 - Average the seasonal (or quarterly) maximums from Step 5 across the three
years of monitoring data to create the four seasonal background PM2.5 concentrations to
be included as inputs to the AERMOD model. These averages for the Year 1, Year 2,
and Year 3 dataset used in this example are presented in Exhibit L-4. As noted above,
the full concentration data only from Year 1 is shown in the exhibits in this appendix for
L-2
-------
simplicity, but the seasonal maximums from Years 2 and 3 presented in Exhibit L-4 were
determined by following the previous five steps, similar to that of Year 1.
L-3
-------
Exhibit L-l. Year 1 Daily PM2.5 Concentrations
Date
Cone.
Date
Cone.
Date
Cone.
Date
Cone.
Date
Cone.
Date
Cone.
Date
Cone.
Date
Cone.
1-Jan
10.4
16-Feb
15.1
2-Apr
10.5
18-May
11.1
3-Jul
17.1
18-Aug
18.7
3-Oct
12.3
18-Nov
4.4
2-Jan
5.4
17-Feb
11.8
3-Apr
8.2
19-May
7.7
4-Jul
19.8
19-Aug
21.5
4-Oct
19.5
19-Nov
8.2
3-Jan
10.0
18-Feb
3.4
4-Apr
9.7
20-May
13.6
5-Jul
14.3
20-Aug
20.1
5-Oct
23.7
20-Nov
11.1
4-Jan
16.4
19-Feb
4.5
5-Apr
6.9
21-May
12.1
6-Jul
11.5
21-Aug
18.4
6-Oct
19.8
21-Nov
5.3
5-Jan
11.2
20-Feb
4.8
6-Apr
6.3
22-May
10.0
7-Jul
14.3
22-Aug
16.7
7-Oct
21.7
22-Nov
8.9
6-Jan
11.1
21-Feb
11.9
7-Apr
7.9
23-May
13.3
8-Jul
12.2
23-Aug
13.8
8-Oct
12.2
23-Nov
14.0
7-Jan
10.2
22-Feb
20.1
8-Apr
9.8
24-May
11.2
9-Jul
11.1
24-Aug
19.0
9-Oct
5.1
24-Nov
12.7
8-Jan
11.4
23-Feb
11.4
9-Apr
16.5
25-May
17.7
10-Jul
9.7
25-Aug
17.6
10-Oct
10.2
25-Nov
9.7
Wan
8.1
24-Feb
19.3
10-Apr
13.3
26-May
14.2
11-Jul
16.4
26-Aug
15.4
11-Oct
10.7
26-Nov
12.8
10-Jan
9.4
25-Feb
18.2
11-Apr
11.0
27-May
15.4
12-Jul
21.5
27-Aug
12.6
12-Oct
5.6
27-Nov
16.6
11-Jan
5.7
26-Feb
12.8
12-Apr
8.8
28-May
13.9
13-Jul
25.1
28-Aug
12.1
13-Oct
5.9
28-Nov
17.2
12-Jan
8.9
27-Feb
5.5
13-Apr
6.3
29-May
9.3
14-Jul
11.7
29-Aug
10.1
14-Oct
9.7
29-Nov
16.6
13-Jan
18.1
28-Feb
9.7
14-Apr
5.1
30-May
14.5
15-Jul
18.9
30-Aug
17.2
15-Oct
12.8
30-Nov
4.5
14-Jan
11.0
29-Feb
12.1
15-Apr
7.9
31-May
20.5
16-Jul
28.9
31-Aug
19.9
16-Oct
16.4
1-Dec
7.5
15-Jan
11.8
1-Mar
9.6
16-Apr
8.2
1-Jun
15.3
17-Jul
27.6
1-Sep
19.4
17-Oct
12.0
2-Dec
10.6
16-Jan
10.7
2-Mar
5.6
17-Apr
14.7
2-Jun
11.5
18-Jul
12.8
2-Sep
18.2
18-Oct
7.9
3-Dec
16.7
17-Jan
10.0
3-Mar
12.5
18-Apr
22.5
3-Jun
17.9
19-Jul
6.2
3-Sep
24.0
19-Oct
6.6
4-Dec
12.5
18-Jan
15.6
4-Mar
7.1
19-Apr
12.8
4-Jun
21.1
20-Jul
20.1
4-Sep
15.4
20-Oct
8.1
5-Dec
7.3
19-Jan
18.0
5-Mar
4.9
20-Apr
6.9
5-Jun
17.9
21-Jul
26.5
5-Sep
12.4
21-Oct
12.2
6-Dec
10.4
20-Jan
6.6
6-Mar
9.9
21-Apr
7.5
6-Jun
17.6
22-Jul
16.9
6-Sep
12.5
22-Oct
4.6
7-Dec
13.4
21-Jan
7.4
7-Mar
11.2
22-Apr
6.0
7-Jun
15.0
23-Jul
12.8
7-Sep
15.8
23-Oct
6.1
8-Dec
10.5
22-Jan
13.5
8-Mar
5.5
23-Apr
9.1
8-Jun
22.3
24-Jul
7.9
8-Sep
23.4
24-Oct
4.6
9-Dec
9.3
23-Jan
16.0
9-Mar
8.8
24-Apr
10.3
9-Jun
27.9
25-Jul
15.7
9-Sep
11.5
25-Oct
4.5
10-Dec
6.5
24-Jan
9.4
10-Mar
11.0
25-Apr
12.0
10-Jun
21.6
26-Jul
24.9
10-Sep
6.0
26-Oct
10.5
11-Dec
3.0
25-Jan
12.6
11-Mar
12.1
26-Apr
12.5
11-Jun
19.4
27-Jul
22.2
11-Sep
11.8
27-Oct
6.4
12-Dec
3.5
26-Jan
13.6
12-Mar
9.7
27-Apr
11.3
12-Jun
21.2
28-Jul
17.5
12-Sep
10.7
28-Oct
4.6
13-Dec
10.2
27-Jan
16.1
13-Mar
15.1
28-Apr
7.6
13-Jun
29.1
29-Jul
19.1
13-Sep
7.6
29-Oct
5.6
14-Dec
17.6
28-Jan
10.0
14-Mar
21.6
29-Apr
7.4
14-Jun
15.6
30-Jul
21.1
14-Sep
7.5
30-Oct
7.6
15-Dec
12.4
29-Jan
10.4
15-Mar
16.6
30-Apr
11.4
15-Jun
14.8
31-Jul
18.0
15-Sep
7.1
31-Oct
11.2
16-Dec
9.7
30-Jan
6.9
16-Mar
7.9
1-May
12.6
16-Jun
17.8
1-Aug
16.3
16-Sep
7.7
1-Nov
16.2
17-Dec
7.0
31-Jan
4.9
17-Mar
9.6
2-May
10.0
17-Jun
12.6
2-Aug
19.3
17-Sep
11.3
2-Nov
17.3
18-Dec
7.9
1-Feb
5.4
18-Mar
10.3
3-May
11.2
18-Jun
10.5
3-Aug
17.9
18-Sep
16.8
3-Nov
18.3
19-Dec
6.9
2-Feb
7.1
19-Mar
8.4
4-May
10.4
19-Jun
15.0
4-Aug
25.1
19-Sep
14.8
4-Nov
8.9
20-Dec
8.1
3-Feb
10.9
20-Mar
4.9
5-May
15.7
20-Jun
22.7
5-Aug
29.3
20-Sep
8.0
5-Nov
5.8
21-Dec
4.9
4-Feb
12.1
21-Mar
8.7
6-May
16.1
21-Jun
18.7
6-Aug
19.1
21-Sep
10.8
6-Nov
8.6
22-Dec
7.7
5-Feb
17.1
22-Mar
13.3
7-May
16.8
22-Jun
15.2
7-Aug
14.0
22-Sep
14.5
7-Nov
15.0
23-Dec
7.7
6-Feb
10.3
23-Mar
12.2
8-May
14.5
23-Jun
16.8
8-Aug
10.8
23-Sep
21.2
8-Nov
8.3
24-Dec
10.5
7-Feb
4.0
24-Mar
10.3
9-May
11.7
24-Jun
15.1
9-Aug
15.0
24-Sep
8.6
9-Nov
10.0
25-Dec
6.5
8-Feb
9.7
25-Mar
11.9
10-May
9.0
25-Jun
20.7
10-Aug
21.7
25-Sep
1.2
10-Nov
12.8
26-Dec
7.6
9-Feb
11.5
26-Mar
20.1
11-May
6.7
26-Jun
23.0
11-Aug
14.3
26-Sep
16.0
11-Nov
11.8
27-Dec
13.3
10-Feb
3.0
27-Mar
22.5
12-May
7.9
27-Jun
17.8
12-Aug
14.7
27-Sep
12.1
12-Nov
14.8
28-Dec
6.4
11-Feb
5.5
28-Mar
18.2
13-May
8.3
28-Jun
12.4
13-Aug
13.0
28-Sep
18.0
13-Nov
14.5
29-Dec
3.7
12-Feb
18.9
29-Mar
10.8
14-May
12.2
29-Jun
12.7
14-Aug
13.5
29-Sep
17.8
14-Nov
7.7
30-Dec
4.7
13-Feb
17.6
30-Mar
6.4
15-May
13.1
30-Jun
8.9
15-Aug
17.5
30-Sep
16.4
15-Nov
3.6
31-Dec
4.4
14-Feb
11.2
31-Mar
3.3
16-May
8.8
1-Jul
7.1
16-Aug
23.9
1-Oct
12.3
16-Nov
4.6
15-Feb
14.4
1-Apr
7.8
17-May
8.2
2-Jul
13.8
17-Aug
18.4
2-Oct
8.2
17-Nov
7.8
Annual 98th Percentile Concentration (highlighted green value) = 25.1
-------
Exhibit L-2: Year 1 Daily PM2.5 Concentrations Less Than or Equal to the 98th Percentile
Date
Cone.
Date
Cone.
Date
Cone.
Date
Cone.
Date
Cone.
Date
Cone.
Date
Cone.
Date
Cone.
1-Jan
10.4
16-Feb
15.1
2-Apr
10.5
18-May
11.1
3-Jul
17.1
18-Aug
18.7
3-Oct
12.3
18-Nov
4.4
2-Jan
5.4
17-Feb
11.8
3-Apr
8.2
19-May
7.7
4-Jul
19.8
19-Aug
21.5
4-Oct
19.5
19-Nov
8.2
3-Jan
10.0
18-Feb
3.4
4-Apr
9.7
20-May
13.6
5-Jul
14.3
20-Aug
20.1
5-Oct
23.7
20-Nov
11.1
4-Jan
16.4
19-Feb
4.5
5-Apr
6.9
21-May
12.1
6-Jul
11.5
21-Aug
18.4
6-Oct
19.8
21-Nov
5.3
5-Jan
11.2
20-Feb
4.8
6-Apr
6.3
22-May
10.0
7-Jul
14.3
22-Aug
16.7
7-Oct
21.7
22-Nov
8.9
6-Jan
11.1
21-Feb
11.9
7-Apr
7.9
23-May
13.3
8-Jul
12.2
23-Aug
13.8
8-Oct
12.2
23-Nov
14.0
7-Jan
10.2
22-Feb
20.1
8-Apr
9.8
24-May
11.2
9-Jul
11.1
24-Aug
19.0
9-Oct
5.1
24-Nov
12.7
8-Jan
11.4
23-Feb
11.4
9-Apr
16.5
25-May
17.7
10-Jul
9.7
25-Aug
17.6
10-Oct
10.2
25-Nov
9.7
Wan
8.1
24-Feb
19.3
10-Apr
13.3
26-May
14.2
11-Jul
16.4
26-Aug
15.4
11-Oct
10.7
26-Nov
12.8
10-Jan
9.4
25-Feb
18.2
11-Apr
11.0
27-May
15.4
12-Jul
21.5
27-Aug
12.6
12-Oct
5.6
27-Nov
16.6
11-Jan
5.7
26-Feb
12.8
12-Apr
8.8
28-May
13.9
13-Jul
RC
28-Aug
12.1
13-Oct
5.9
28-Nov
17.2
12-Jan
8.9
27-Feb
5.5
13-Apr
6.3
29-May
9.3
14-Jul
11.7
29-Aug
10.1
14-Oct
9.7
29-Nov
16.6
13-Jan
18.1
28-Feb
9.7
14-Apr
5.1
30-May
14.5
15-Jul
18.9
30-Aug
17.2
15-Oct
12.8
30-Nov
4.5
14-Jan
11.0
29-Feb
12.1
15-Apr
7.9
31-May
20.5
16-Jul
RC
31-Aug
19.9
16-Oct
16.4
1-Dec
7.5
15-Jan
11.8
1-Mar
9.6
16-Apr
8.2
1-Jun
15.3
17-Jul
RC
1-Sep
19.4
17-Oct
12.0
2-Dec
10.6
16-Jan
10.7
2-Mar
5.6
17-Apr
14.7
2-Jun
11.5
18-Jul
12.8
2-Sep
18.2
18-Oct
7.9
3-Dec
16.7
17-Jan
10.0
3-Mar
12.5
18-Apr
22.5
3-Jun
17.9
19-Jul
6.2
3-Sep
24.0
19-Oct
6.6
4-Dec
12.5
18-Jan
15.6
4-Mar
7.1
19-Apr
12.8
4-Jun
21.1
20-Jul
20.1
4-Sep
15.4
20-Oct
8.1
5-Dec
7.3
19-Jan
18.0
5-Mar
4.9
20-Apr
6.9
5-Jun
17.9
21-Jul
RC
5-Sep
12.4
21-Oct
12.2
6-Dec
10.4
20-Jan
6.6
6-Mar
9.9
21-Apr
7.5
6-Jun
17.6
22-Jul
16.9
6-Sep
12.5
22-Oct
4.6
7-Dec
13.4
21-Jan
7.4
7-Mar
11.2
22-Apr
6.0
7-Jun
15.0
23-Jul
12.8
7-Sep
15.8
23-Oct
6.1
8-Dec
10.5
22-Jan
13.5
8-Mar
5.5
23-Apr
9.1
8-Jun
22.3
24-Jul
7.9
8-Sep
23.4
24-Oct
4.6
9-Dec
9.3
23-Jan
16.0
9-Mar
8.8
24-Apr
10.3
9-Jun
RC
25-Jul
15.7
9-Sep
11.5
25-Oct
4.5
10-Dec
6.5
24-Jan
9.4
10-Mar
11.0
25-Apr
12.0
10-Jun
21.6
26-Jul
24.9
10-Sep
6.0
26-Oct
10.5
11-Dec
3.0
25-Jan
12.6
11-Mar
12.1
26-Apr
12.5
11-Jun
19.4
27-Jul
22.2
11-Sep
11.8
27-Oct
6.4
12-Dec
3.5
26-Jan
13.6
12-Mar
9.7
27-Apr
11.3
12-Jun
21.2
28-Jul
17.5
12-Sep
10.7
28-Oct
4.6
13-Dec
10.2
27-Jan
16.1
13-Mar
15.1
28-Apr
7.6
13-Jun
RC
29-Jul
19.1
13-Sep
7.6
29-Oct
5.6
14-Dec
17.6
28-Jan
10.0
14-Mar
21.6
29-Apr
7.4
14-Jun
15.6
30-Jul
21.1
14-Sep
7.5
30-Oct
7.6
15-Dec
12.4
29-Jan
10.4
15-Mar
16.6
30-Apr
11.4
15-Jun
14.8
31-Jul
18.0
15-Sep
7.1
31-Oct
11.2
16-Dec
9.7
30-Jan
6.9
16-Mar
7.9
1-May
12.6
16-Jun
17.8
1-Aug
16.3
16-Sep
7.7
1-Nov
16.2
17-Dec
7.0
31-Jan
4.9
17-Mar
9.6
2-May
10.0
17-Jun
12.6
2-Aug
19.3
17-Sep
11.3
2-Nov
17.3
18-Dec
7.9
1-Feb
5.4
18-Mar
10.3
3-May
11.2
18-Jun
10.5
3-Aug
17.9
18-Sep
16.8
3-Nov
18.3
19-Dec
6.9
2-Feb
7.1
19-Mar
8.4
4-May
10.4
19-Jun
15.0
4-Aug
25.1
19-Sep
14.8
4-Nov
8.9
20-Dec
8.1
3-Feb
10.9
20-Mar
4.9
5-May
15.7
20-Jun
22.7
5-Aug
RC
20-Sep
8.0
5-Nov
5.8
21-Dec
4.9
4-Feb
12.1
21-Mar
8.7
6-May
16.1
21-Jun
18.7
6-Aug
19.1
21-Sep
10.8
6-Nov
8.6
22-Dec
7.7
5-Feb
17.1
22-Mar
13.3
7-May
16.8
22-Jun
15.2
7-Aug
14.0
22-Sep
14.5
7-Nov
15.0
23-Dec
7.7
6-Feb
10.3
23-Mar
12.2
8-May
14.5
23-Jun
16.8
8-Aug
10.8
23-Sep
21.2
8-Nov
8.3
24-Dec
10.5
7-Feb
4.0
24-Mar
10.3
9-May
11.7
24-Jun
15.1
9-Aug
15.0
24-Sep
8.6
9-Nov
10.0
25-Dec
6.5
8-Feb
9.7
25-Mar
11.9
10-May
9.0
25-Jun
20.7
10-Aug
21.7
25-Sep
1.2
10-Nov
12.8
26-Dec
7.6
9-Feb
11.5
26-Mar
20.1
11-May
6.7
26-Jun
23.0
11-Aug
14.3
26-Sep
16.0
11-Nov
11.8
27-Dec
13.3
10-Feb
3.0
27-Mar
22.5
12-May
7.9
27-Jun
17.8
12-Aug
14.7
27-Sep
12.1
12-Nov
14.8
28-Dec
6.4
11-Feb
5.5
28-Mar
18.2
13-May
8.3
28-Jun
12.4
13-Aug
13.0
28-Sep
18.0
13-Nov
14.5
29-Dec
3.7
12-Feb
18.9
29-Mar
10.8
14-May
12.2
29-Jun
12.7
14-Aug
13.5
29-Sep
17.8
14-Nov
7.7
30-Dec
4.7
13-Feb
17.6
30-Mar
6.4
15-May
13.1
30-Jun
8.9
15-Aug
17.5
30-Sep
16.4
15-Nov
3.6
31-Dec
4.4
14-Feb
11.2
31-Mar
3.3
16-May
8.8
1-Jul
7.1
16-Aug
23.9
1-Oct
12.3
16-Nov
4.6
15-Feb
14.4
1-Apr
7.8
17-May
8.2
2-Jul
13.8
17-Aug
18.4
2-Oct
8.2
17-Nov
7.8
Annual 98th Percentile Concentration (highlighted green value) = 25.1
RC = Above 98th Percentile and Removed from Consideration (highlighted peach values)
-------
Exhibit L-3. Year 1 Daily PM2.5 Concentrations Less Than or Equal to the 98th Percentile by Quarter
Season / Quarter 1
Date
Cone.
Date
Cone.
1-Jan
10.4
16-Feb
15.1
2-Jan
5.4
17-Feb
11.8
3-Jan
10.0
18-Feb
3.4
4-Jan
16.4
19-Feb
4.5
5-Jan
11.2
20-Feb
4.8
6-Jan
11.1
21-Feb
11.9
7-Jan
10.2
22-Feb
20.1
8-Jan
11.4
23-Feb
11.4
9-Jan
8.1
24-Feb
19.3
10-Jan
9.4
25-Feb
18.2
11-Jan
5.7
26-Feb
12.8
12-Jan
8.9
27-Feb
5.5
13-Jan
18.1
28-Feb
9.7
14-Jan
11.0
29-Feb
12.1
15-Jan
11.8
1-Mar
9.6
16-Jan
10.7
2-Mar
5.6
17-Jan
10.0
3-Mar
12.5
18-Jan
15.6
4-Mar
7.1
19-Jan
18.0
5-Mar
4.9
20-Jan
6.6
6-Mar
9.9
21-Jan
7.4
7-Mar
11.2
22-Jan
13.5
8-Mar
5.5
23-Jan
16.0
9-Mar
00
00
24-Jan
9.4
10-Mar
11.0
25-Jan
12.6
11-Mar
12.1
26-Jan
13.6
12-Mar
9.7
27-Jan
16.1
13-Mar
15.1
28-Jan
10.0
14-Mar
21.6
29-Jan
10.4
15-Mar
16.6
30-Jan
6.9
16-Mar
7.9
31-Jan
4.9
17-Mar
9.6
1-Feb
5.4
18-Mar
10.3
2-Feb
7.1
19-Mar
8.4
3-Feb
10.9
20-Mar
4.9
4-Feb
12.1
21-Mar
8.7
5-Feb
17.1
22-Mar
13.3
6-Feb
10.3
23-Mar
12.2
7-Feb
4.0
24-Mar
10.3
8-Feb
9.7
25-Mar
11.9
9-Feb
11.5
26-Mar
20.1
10-Feb
3.0
27-Mar
22.5
11-Feb
5.5
28-Mar
18.2
12-Feb
18.9
29-Mar
10.8
13-Feb
17.6
30-Mar
6.4
14-Feb
11.2
31-Mar
3.3
15-Feb
14.4
Seasonal/ QuarterlyMaximum
22.5
Season / Quarter 2
Date
Cone.
Date
Cone.
1-Apr
7.8
17-May
8.2
2-Apr
10.5
18-May
11.1
3-Apr
8.2
19-May
7.7
4-Apr
9.7
20-May
13.6
5-Apr
6.9
21-May
12.1
6-Apr
6.3
22-May
10.0
7-Apr
7.9
23-May
13.3
8-Apr
9.8
24-May
11.2
9-Apr
16.5
25-May
17.7
10-Apr
13.3
26-May
14.2
11-Apr
11.0
27-May
15.4
12-Apr
8.8
28-May
13.9
13-Apr
6.3
29-May
9.3
14-Apr
5.1
30-May
14.5
15-Apr
7.9
31-May
20.5
16-Apr
8.2
1-Jun
15.3
17-Apr
14.7
2-Jun
11.5
18-Apr
22.5
3-Jun
17.9
19-Apr
12.8
4-Jun
21.1
20-Apr
6.9
5-Jun
17.9
21-Apr
7.5
6-Jun
17.6
22-Apr
6.0
7-Jun
15.0
23-Apr
9.1
8-Jun
22.3
24-Apr
10.3
9-Jun
RC
25-Apr
12.0
10-Juii
21.6
26-Apr
12.5
11-Jun
19.4
27-Apr
11.3
12-Jun
21.2
28-Apr
7.6
13-Jun
RC
29-Apr
7.4
14-Jun
15.6
30-Apr
11.4
15-Jun
14.8
1-May
12.6
16-Jun
17.8
2-May
10.0
17-Jun
12.6
3-May
11.2
18-Jun
10.5
4-May
10.4
19-Jun
15.0
5-May
15.7
20-Jun
22.7
6-May
16.1
21-Jun
18.7
7-May
16.8
22-Jun
15.2
8-May
14.5
23-Jun
16.8
9-May
11.7
24-Jun
15.1
10-May
9.0
25-Jun
20.7
11-May
6.7
26-Jun
23.0
12-May
7.9
27-Jun
17.8
13-May
8.3
28-Jun
12.4
14-May
12.2
29-Jun
12.7
15-May
13.1
30-Jun
8.9
16-May
8.8
Seasonal / Quarterly Maximum
23.0
Season / Quarter 3
Date
Cone.
Date
Cone.
1-Jul
7.1
16-Aug
23.9
2-Jul
13.8
17-Aug
18.4
3-Jul
17.1
18-Aug
18.7
4-Jul
19.8
19-Aug
21.5
5-Jul
14.3
20-Aug
20.1
6-Jul
11.5
21-Aug
18.4
7-Jul
14.3
22-Aug
16.7
8-Jul
12.2
23-Aug
13.8
9-Jul
11.1
24-Aug
19.0
10-Jul
9.7
25-Aug
17.6
11-Jul
16.4
26-Aug
15.4
12-Jul
21.5
27-Aug
12.6
13-Jul
RC
28-Aug
12.1
14-Jul
11.7
29-Aug
10.1
15-Jul
18.9
30-Aug
17.2
16-Jul
RC
31-Aug
19.9
17-Jul
RC
1-Sep
19.4
18-Jul
12.8
2-Sep
18.2
19-Jul
6.2
3-Sep
24.0
20-Jul
20.1
4-Sep
15.4
21-Jul
RC
5-Sep
12.4
22-Jul
16.9
6-Sep
12.5
23-Jul
12.8
7-Sep
15.8
24-Jul
7.9
8-Sep
23.4
25-Jul
15.7
9-Sep
11.5
26-Jul
24.9
10-Sep
6.0
27-Jul
22.2
11-Sep
11.8
28-Jul
17.5
12-Sep
10.7
29-Jul
19.1
13-Sep
7.6
30-Jul
21.1
14-Sep
7.5
31-Jul
18.0
15-Sep
7.1
1-Aug
16.3
16-Sep
7.7
2-Aug
19.3
17-Sep
11.3
3-Aug
17.9
18-Sep
16.8
4-Aug
25.1
19-Sep
14.8
5-Aug
RC
20-Sep
8.0
6-Aug
19.1
21-Sep
10.8
7-Aug
14.0
22-Sep
14.5
8-Aug
10.8
23-Sep
21.2
9-Aug
15.0
24-Sep
8.6
10-Aug
21.7
25-Sep
1.2
11-Aug
14.3
26-Sep
16.0
12-Aug
14.7
27-Sep
12.1
13-Aug
13.0
28-Sep
18.0
14-Aug
13.5
29-Sep
17.8
15-Aug
17.5
30-Sep
16.4
Seasonal/ Quarterly Maxi mum
25.1
Season / Quarter 4
Date
Cone.
Date
Cone.
1-Oct
12.3
16-Nov
4.6
2-Oct
8.2
17-Nov
7.8
3-Oct
12.3
18-Nov
4.4
4-Oct
19.5
19-Nov
8.2
5-Oct
23.7
20-Nov
11.1
6-Oct
19.8
21-Nov
5.3
7-Oct
21.7
22-Nov
8.9
8-Oct
12.2
23-Nov
14.0
9-Oct
5.1
24-Nov
12.7
10-Oct
10.2
25-Nov
9.7
11-Oct
10.7
26-Nov
12.8
12-Oct
5.6
27-Nov
16.6
13-Oct
5.9
28-Nov
17.2
14-Oct
9.7
29-Nov
16.6
15-Oct
12.8
30-Nov
4.5
16-Oct
16.4
1-Dec
7.5
17-Oct
12.0
2-Dec
10.6
18-Oct
7.9
3-Dec
16.7
19-Oct
6.6
4-Dec
12.5
20-Oct
8.1
5-Dec
7.3
21-Oct
12.2
6-Dec
10.4
22-Oct
4.6
7-Dec
13.4
23-Oct
6.1
8-Dec
10.5
24-Oct
4.6
9-Dec
9.3
25-Oct
4.5
10-Dec
6.5
26-Oct
10.5
11-Dec
3.0
27-Oct
6.4
12-Dec
3.5
28-Oct
4.6
13-Dec
10.2
29-Oct
5.6
14-Dec
17.6
30-Oct
7.6
15-Dec
12.4
31-Oct
11.2
16-Dec
9.7
1-Nov
16.2
17-Dec
7.0
2-Nov
17.3
18-Dec
7.9
3-Nov
18.3
19-Dec
6.9
4-Nov
8.9
20-Dec
8.1
5-Nov
5.8
21-Dec
4.9
6-Nov
8.6
22-Dec
7.7
7-Nov
15.0
23-Dec
7.7
8-Nov
8.3
24-Dec
10.5
9-Nov
10.0
25-Dec
6.5
10-Nov
12.8
26-Dec
7.6
11-Nov
11.8
27-Dec
13.3
12-Nov
14.8
28-Dec
6.4
13-Nov
14.5
29-Dec
3.7
14-Nov
7.7
30-Dec
4.7
15-Nov
3.6
31-Dec
4.4
Seasonal / Quarterly Maximum
23.7
Seasonal/Quarterly Maximum Concentration (highlighted blue values)
RC = Above 98th Percentile and Removed from Consideration (highlighted peach values)
L-5
-------
Exhibit L-4: Resulting Average of Seasonal (or Quarterly) Maximums from Year 1
for Inclusion into AERMOD
Seasonal / Quarterly Average Highest Monitored Concentration
(From Annual Datasets Equal To and Less Than the 98th
Percentile)
Ql
Q2
Q3
Q4
Year 1
22.5
23.0
25.1
23.7
Year 2
21.1
20.7
21.2
19.8
Year 3
20.7
22.6
23.5
20.7
Average
21.433
22.100
23.267
21.400
Note, the complete datasets for Year 2 and Year 3 are not shown in this appendix but
would follow the same steps as for Year 1.
L.3 Running AERMOD
After calculating the seasonal 98th percentile background concentrations, the four average
seasonal values (shown in the last row of Exhibit L-4) can be added to the AERMOD
input file. There are four important steps to follow when creating an input file consistent
with the second tier design concentration approach.
1) AERMOD must be run with five years of concatenated met data (assuming the
use of an off-site monitor). This allows for the calculation of the 98th percentile
value across all years of data.
2) Ensure that "PM2.5" is listed for the POLLUTID keyword in the CO pathway.
This will trigger calculations in AERMOD that automatically average across five
years of meteorological data to determine the 98th percentile concentration at each
receptor.
3) Add a line in the SO pathway with the keyword BACKGRND, followed by
SEASON. This will allow the definition of four seasonal values. For the example
shown above in Appendix L.2, the appropriate line in AERMOD would be:
SO BACKGRND SEASON 21.433 22.100 23.267 21.400
Also, ensure that BACKGRND is added to the SRCGROUP line of the SO
pathway.
4) Finally, since the 98th percentile of 365 days is the eighth highest day, use the
RECTABLE keyword of the OU pathway to define the "8th" highest value to
report.
L-6
-------
After running AERMOD, the RECTABLE generated will report 98th percentile
concentrations, averaged across five years of meteorological data, for each receptor.
These values can be compared directly to the NAAQS, or in the case of a build/no-build
analysis, the values at the same receptor in the build scenario.
L-7
------- |